From 277d9afc7657a1291cf173c62d3940b74ac74fc5 Mon Sep 17 00:00:00 2001
From: Jingru923 <Jingru923@users.noreply.github.com>
Date: Thu, 11 Jan 2024 15:36:15 +0000
Subject: [PATCH] deploy: bf2751359fd0dbefdc641849d09ea3e422aefe39

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diff --git a/build/index.html b/build/index.html
index 7053cb16d..0830b275a 100644
--- a/build/index.html
+++ b/build/index.html
@@ -268,11 +268,11 @@ <h2 data-number="1.1" class="anchored" data-anchor-id="modules"><span class="hea
 <li><a href="../build/index.html#CommonSolve.solve!-Tuple{Ribasim.Model}"><code>solve!</code></a></li>
 <li><a href="../build/index.html#BasicModelInterface.finalize-Tuple{Ribasim.Model}"><code>BMI.finalize</code></a></li>
 </ul>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/Ribasim.jl#LL1-L14" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/Ribasim.jl#LL1-L14" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.config" href="#Ribasim.config">#</a> <strong><code>Ribasim.config</code></strong> — <em>Module</em>.</p>
 <div class="sourceCode" id="cb2"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="kw">module</span> config</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Ribasim.config is a submodule of <a href="../build/index.html#Ribasim.Ribasim"><code>Ribasim</code></a> to handle the configuration of a Ribasim model. It is implemented using the <a href="https://configurations.rogerluo.dev/stable/">Configurations</a> package. A full configuration is represented by <a href="../build/index.html#Ribasim.config.Config-Tuple{AbstractString}"><code>Config</code></a>, which is the main API. Ribasim.config is a submodule mainly to avoid name clashes between the configuration sections and the rest of Ribasim.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/config.jl#LL1-L8" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/config.jl#LL1-L8" class="documenter-source">source</a><br></p>
 <p><a id="Types"></a></p>
 <p><a id="Types-1"></a></p>
 </section>
@@ -281,14 +281,14 @@ <h2 data-number="1.2" class="anchored" data-anchor-id="types"><span class="heade
 <p><a id="Ribasim.AllocationModel" href="#Ribasim.AllocationModel">#</a> <strong><code>Ribasim.AllocationModel</code></strong> — <em>Type</em>.</p>
 <p>Store information for a subnetwork used for allocation.</p>
 <p>objective<em>type: The name of the type of objective used allocation</em>network<em>id: The ID of this allocation network capacity: The capacity per edge of the allocation graph, as constrained by nodes that have a max</em>flow<em>rate problem: The JuMP.jl model for solving the allocation problem Δt</em>allocation: The time interval between consecutive allocation solves</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL7-L15" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL7-L15" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.AllocationModel-Tuple{Ribasim.config.Config, Int64, Ribasim.Parameters, Float64}" href="#Ribasim.AllocationModel-Tuple{Ribasim.config.Config, Int64, Ribasim.Parameters, Float64}">#</a> <strong><code>Ribasim.AllocationModel</code></strong> — <em>Method</em>.</p>
 <p>Construct the JuMP.jl problem for allocation.</p>
 <p><strong>Inputs</strong></p>
 <p>config: The model configuration with allocation configuration in config.allocation p: Ribasim problem parameters Δt_allocation: The timestep between successive allocation solves</p>
 <p><strong>Outputs</strong></p>
 <p>An AllocationModel object.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL658-L670" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL658-L670" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.Basin" href="#Ribasim.Basin">#</a> <strong><code>Ribasim.Basin</code></strong> — <em>Type</em>.</p>
 <p>Requirements:</p>
 <ul>
@@ -298,22 +298,22 @@ <h2 data-number="1.2" class="anchored" data-anchor-id="types"><span class="heade
 </ul>
 <p>Type parameter C indicates the content backing the StructVector, which can be a NamedTuple of vectors or Arrow Tables, and is added to avoid type instabilities. The node<em>id are Indices to support fast lookup of e.g.&nbsp;current</em>level using ID.</p>
 <p>if autodiff T = DiffCache{Vector{Float64}} else T = Vector{Float64} end</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL57-L73" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL57-L73" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.DiscreteControl" href="#Ribasim.DiscreteControl">#</a> <strong><code>Ribasim.DiscreteControl</code></strong> — <em>Type</em>.</p>
 <p>node<em>id: node ID of the DiscreteControl node; these are not unique but repeated by the amount of conditions of this DiscreteControl node listen</em>node<em>id: the ID of the node being condition on variable: the name of the variable in the condition greater</em>than: The threshold value in the condition condition<em>value: The current value of each condition control</em>state: Dictionary: node ID =&gt; (control state, control state start) logic_mapping: Dictionary: (control node ID, truth state) =&gt; control state record: Namedtuple with discrete control information for results</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL342-L352" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL342-L352" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.EdgeMetadata" href="#Ribasim.EdgeMetadata">#</a> <strong><code>Ribasim.EdgeMetadata</code></strong> — <em>Type</em>.</p>
 <p>Type for storing metadata of edges in the graph: id: ID of the edge (only used for labeling flow output) type: type of the edge allocation<em>network</em>id<em>source: ID of allocation network where this edge is a source (0 if not a source) from</em>id: the node ID of the source node to<em>id: the node ID of the destination node allocation</em>flow: whether this edge has a flow in an allocation graph</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL36-L45" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL36-L45" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.FlatVector" href="#Ribasim.FlatVector">#</a> <strong><code>Ribasim.FlatVector</code></strong> — <em>Type</em>.</p>
 <div class="sourceCode" id="cb3"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="kw">struct</span> FlatVector{T} <span class="op">&lt;:</span><span class="dt"> AbstractVector{T}</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>A FlatVector is an AbstractVector that iterates the T of a <code>Vector{Vector{T}}</code>.</p>
 <p>Each inner vector is assumed to be of equal length.</p>
 <p>It is similar to <code>Iterators.flatten</code>, though that doesn’t work with the <code>Tables.Column</code> interface, which needs <code>length</code> and <code>getindex</code> support.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL1143-L1152" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL1143-L1152" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.FlowBoundary" href="#Ribasim.FlowBoundary">#</a> <strong><code>Ribasim.FlowBoundary</code></strong> — <em>Type</em>.</p>
 <p>node<em>id: node ID of the FlowBoundary node active: whether this node is active and thus contributes flow flow</em>rate: target flow rate</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL235-L239" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL235-L239" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.FractionalFlow" href="#Ribasim.FractionalFlow">#</a> <strong><code>Ribasim.FractionalFlow</code></strong> — <em>Type</em>.</p>
 <p>Requirements:</p>
 <ul>
@@ -322,13 +322,13 @@ <h2 data-number="1.2" class="anchored" data-anchor-id="types"><span class="heade
 <li>fraction must be positive.</li>
 </ul>
 <p>node<em>id: node ID of the TabulatedRatingCurve node fraction: The fraction in [0,1] of flow the node lets through control</em>mapping: dictionary from (node<em>id, control</em>state) to fraction</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL207-L217" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL207-L217" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.InNeighbors" href="#Ribasim.InNeighbors">#</a> <strong><code>Ribasim.InNeighbors</code></strong> — <em>Type</em>.</p>
 <p>Iterate over incoming neighbors of a given label in a MetaGraph, only for edges of edge_type</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL113-L115" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL113-L115" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.LevelBoundary" href="#Ribasim.LevelBoundary">#</a> <strong><code>Ribasim.LevelBoundary</code></strong> — <em>Type</em>.</p>
 <p>node_id: node ID of the LevelBoundary node active: whether this node is active level: the fixed level of this ‘infinitely big basin’</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL224-L228" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL224-L228" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.LinearResistance" href="#Ribasim.LinearResistance">#</a> <strong><code>Ribasim.LinearResistance</code></strong> — <em>Type</em>.</p>
 <p>Requirements:</p>
 <ul>
@@ -336,7 +336,7 @@ <h2 data-number="1.2" class="anchored" data-anchor-id="types"><span class="heade
 <li>to: must be (Basin,) node</li>
 </ul>
 <p>node<em>id: node ID of the LinearResistance node active: whether this node is active and thus contributes flows resistance: the resistance to flow; Q = Δh/resistance control</em>mapping: dictionary from (node<em>id, control</em>state) to resistance and/or active state</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL146-L156" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL146-L156" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.ManningResistance" href="#Ribasim.ManningResistance">#</a> <strong><code>Ribasim.ManningResistance</code></strong> — <em>Type</em>.</p>
 <p>This is a simple Manning-Gauckler reach connection.</p>
 <ul>
@@ -366,48 +366,48 @@ <h2 data-number="1.2" class="anchored" data-anchor-id="types"><span class="heade
 <li>profile_slope &gt;= 0</li>
 <li>(profile<em>width == 0) xor (profile</em>slope == 0)</li>
 </ul>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL164-L196" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL164-L196" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.Model" href="#Ribasim.Model">#</a> <strong><code>Ribasim.Model</code></strong> — <em>Type</em>.</p>
 <div class="sourceCode" id="cb5"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a><span class="fu">Model</span>(config_path<span class="op">::</span><span class="dt">AbstractString</span>)</span>
 <span id="cb5-2"><a href="#cb5-2" aria-hidden="true" tabindex="-1"></a><span class="fu">Model</span>(config<span class="op">::</span><span class="dt">Config</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Initialize a Model.</p>
 <p>The Model struct is an initialized model, combined with the <a href="../build/index.html#Ribasim.config.Config-Tuple{AbstractString}"><code>Config</code></a> used to create it and saved results. The Basic Model Interface (<a href="https://github.com/Deltares/BasicModelInterface.jl">BMI</a>) is implemented on the Model. A Model can be created from the path to a TOML configuration file, or a Config object.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/lib.jl#LL6-L15" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/lib.jl#LL6-L15" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.NodeMetadata" href="#Ribasim.NodeMetadata">#</a> <strong><code>Ribasim.NodeMetadata</code></strong> — <em>Type</em>.</p>
 <p>Type for storing metadata of nodes in the graph type: type of the node allocation<em>network</em>id: Allocation network ID (0 if not in subnetwork)</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL26-L30" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL26-L30" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.OutNeighbors" href="#Ribasim.OutNeighbors">#</a> <strong><code>Ribasim.OutNeighbors</code></strong> — <em>Type</em>.</p>
 <p>Iterate over outgoing neighbors of a given label in a MetaGraph, only for edges of edge_type</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL122-L124" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL122-L124" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.Outlet" href="#Ribasim.Outlet">#</a> <strong><code>Ribasim.Outlet</code></strong> — <em>Type</em>.</p>
 <p>node<em>id: node ID of the Outlet node active: whether this node is active and thus contributes flow flow</em>rate: target flow rate min<em>flow</em>rate: The minimal flow rate of the outlet max<em>flow</em>rate: The maximum flow rate of the outlet control<em>mapping: dictionary from (node</em>id, control<em>state) to target flow rate is</em>pid_controlled: whether the flow rate of this outlet is governed by PID control</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL289-L297" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL289-L297" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.PidControl" href="#Ribasim.PidControl">#</a> <strong><code>Ribasim.PidControl</code></strong> — <em>Type</em>.</p>
 <p>PID control currently only supports regulating basin levels.</p>
 <p>node<em>id: node ID of the PidControl node active: whether this node is active and thus sets flow rates listen</em>node<em>id: the id of the basin being controlled pid</em>params: a vector interpolation for parameters changing over time. The parameters are respectively target, proportional, integral, derivative, where the last three are the coefficients for the PID equation. error: the current error; basin<em>target - current</em>level</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL370-L380" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL370-L380" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.Pump" href="#Ribasim.Pump">#</a> <strong><code>Ribasim.Pump</code></strong> — <em>Type</em>.</p>
 <p>node<em>id: node ID of the Pump node active: whether this node is active and thus contributes flow flow</em>rate: target flow rate min<em>flow</em>rate: The minimal flow rate of the pump max<em>flow</em>rate: The maximum flow rate of the pump control<em>mapping: dictionary from (node</em>id, control<em>state) to target flow rate is</em>pid_controlled: whether the flow rate of this pump is governed by PID control</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL246-L254" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL246-L254" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.Subgrid" href="#Ribasim.Subgrid">#</a> <strong><code>Ribasim.Subgrid</code></strong> — <em>Type</em>.</p>
 <p>Subgrid linearly interpolates basin levels.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL420" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL420" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.TabulatedRatingCurve" href="#Ribasim.TabulatedRatingCurve">#</a> <strong><code>Ribasim.TabulatedRatingCurve</code></strong> — <em>Type</em>.</p>
 <div class="sourceCode" id="cb6"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a><span class="kw">struct</span> TabulatedRatingCurve{C}</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Rating curve from level to discharge. The rating curve is a lookup table with linear interpolation in between. Relation can be updated in time, which is done by moving data from the <code>time</code> field into the <code>tables</code>, which is done in the <code>update_tabulated_rating_curve</code> callback.</p>
 <p>Type parameter C indicates the content backing the StructVector, which can be a NamedTuple of Vectors or Arrow Primitives, and is added to avoid type instabilities.</p>
 <p>node<em>id: node ID of the TabulatedRatingCurve node active: whether this node is active and thus contributes flows tables: The current Q(h) relationships time: The time table used for updating the tables control</em>mapping: dictionary from (node<em>id, control</em>state) to Q(h) and/or active state</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL121-L137" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL121-L137" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.Terminal" href="#Ribasim.Terminal">#</a> <strong><code>Ribasim.Terminal</code></strong> — <em>Type</em>.</p>
 <p>node_id: node ID of the Terminal node</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL335-L337" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL335-L337" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.User" href="#Ribasim.User">#</a> <strong><code>Ribasim.User</code></strong> — <em>Type</em>.</p>
 <p>demand: water flux demand of user per priority over time active: whether this node is active and thus demands water allocated: water flux currently allocated to user per priority return<em>factor: the factor in [0,1] of how much of the abstracted water is given back to the system min</em>level: The level of the source basin below which the user does not abstract priorities: All used priority values. Each user has a demand for all these priorities, which is 0.0 if it is not provided explicitly. record: Collected data of allocation optimizations for output file.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL391-L400" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL391-L400" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.config.Config-Tuple{AbstractString}" href="#Ribasim.config.Config-Tuple{AbstractString}">#</a> <strong><code>Ribasim.config.Config</code></strong> — <em>Method</em>.</p>
 <div class="sourceCode" id="cb7"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a><span class="fu">Config</span>(config_path<span class="op">::</span><span class="dt">AbstractString</span>; kwargs<span class="op">...</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Parse a TOML file to a Config. Keys can be overruled using keyword arguments. To overrule keys from a subsection, e.g.&nbsp;<code>dt</code> from the <code>solver</code> section, use underscores: <code>solver_dt</code>.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/config.jl#LL148-L153" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/config.jl#LL148-L153" class="documenter-source">source</a><br></p>
 <p><a id="Functions"></a></p>
 <p><a id="Functions-1"></a></p>
 </section>
@@ -416,161 +416,161 @@ <h2 data-number="1.3" class="anchored" data-anchor-id="functions"><span class="h
 <p><a id="BasicModelInterface.finalize-Tuple{Ribasim.Model}" href="#BasicModelInterface.finalize-Tuple{Ribasim.Model}">#</a> <strong><code>BasicModelInterface.finalize</code></strong> — <em>Method</em>.</p>
 <div class="sourceCode" id="cb8"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a>BMI.<span class="fu">finalize</span>(model<span class="op">::</span><span class="dt">Model</span>)<span class="op">::</span><span class="dt">Model</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Write all results to the configured files.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL141-L145" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL141-L145" class="documenter-source">source</a><br></p>
 <p><a id="BasicModelInterface.initialize-Tuple{Type{Ribasim.Model}, AbstractString}" href="#BasicModelInterface.initialize-Tuple{Type{Ribasim.Model}, AbstractString}">#</a> <strong><code>BasicModelInterface.initialize</code></strong> — <em>Method</em>.</p>
 <div class="sourceCode" id="cb9"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb9-1"><a href="#cb9-1" aria-hidden="true" tabindex="-1"></a>BMI.<span class="fu">initialize</span>(T<span class="op">::</span><span class="dt">Type{Model}</span>, config_path<span class="op">::</span><span class="dt">AbstractString</span>)<span class="op">::</span><span class="dt">Model</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Initialize a <a href="../build/index.html#Ribasim.Model"><code>Model</code></a> from the path to the TOML configuration file.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL1-L5" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL1-L5" class="documenter-source">source</a><br></p>
 <p><a id="BasicModelInterface.initialize-Tuple{Type{Ribasim.Model}, Ribasim.config.Config}" href="#BasicModelInterface.initialize-Tuple{Type{Ribasim.Model}, Ribasim.config.Config}">#</a> <strong><code>BasicModelInterface.initialize</code></strong> — <em>Method</em>.</p>
 <div class="sourceCode" id="cb10"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb10-1"><a href="#cb10-1" aria-hidden="true" tabindex="-1"></a>BMI.<span class="fu">initialize</span>(T<span class="op">::</span><span class="dt">Type{Model}</span>, config<span class="op">::</span><span class="dt">Config</span>)<span class="op">::</span><span class="dt">Model</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Initialize a <a href="../build/index.html#Ribasim.Model"><code>Model</code></a> from a <a href="../build/index.html#Ribasim.config.Config-Tuple{AbstractString}"><code>Config</code></a>.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL11-L15" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL11-L15" class="documenter-source">source</a><br></p>
 <p><a id="CommonSolve.solve!-Tuple{Ribasim.Model}" href="#CommonSolve.solve!-Tuple{Ribasim.Model}">#</a> <strong><code>CommonSolve.solve!</code></strong> — <em>Method</em>.</p>
 <div class="sourceCode" id="cb11"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a><span class="fu">solve!</span>(model<span class="op">::</span><span class="dt">Model</span>)<span class="op">::</span><span class="dt">ODESolution</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Solve a Model until the configured <code>endtime</code>.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/lib.jl#LL56-L60" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/lib.jl#LL56-L60" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.add_constraints_absolute_value!-Tuple{JuMP.Model, Ribasim.Parameters, Int64, Ribasim.config.Config}" href="#Ribasim.add_constraints_absolute_value!-Tuple{JuMP.Model, Ribasim.Parameters, Int64, Ribasim.config.Config}">#</a> <strong><code>Ribasim.add_constraints_absolute_value!</code></strong> — <em>Method</em>.</p>
 <p>Minimizing |expr| can be achieved by introducing a new variable expr<em>abs and posing the following constraints: expr</em>abs &gt;= expr expr_abs &gt;= -expr</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL514-L519" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL514-L519" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.add_constraints_capacity!-Tuple{JuMP.Model, SparseArrays.SparseMatrixCSC{Float64, Int64}, Ribasim.Parameters, Int64}" href="#Ribasim.add_constraints_capacity!-Tuple{JuMP.Model, SparseArrays.SparseMatrixCSC{Float64, Int64}, Ribasim.Parameters, Int64}">#</a> <strong><code>Ribasim.add_constraints_capacity!</code></strong> — <em>Method</em>.</p>
 <p>Add the flow capacity constraints to the allocation problem. Only finite capacities get a constraint. The constraint indices are (edge<em>source</em>id, edge<em>dst</em>id).</p>
 <p>Constraint: flow over edge &lt;= edge capacity</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL363-L370" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL363-L370" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.add_constraints_flow_conservation!-Tuple{JuMP.Model, Ribasim.Parameters, Int64}" href="#Ribasim.add_constraints_flow_conservation!-Tuple{JuMP.Model, Ribasim.Parameters, Int64}">#</a> <strong><code>Ribasim.add_constraints_flow_conservation!</code></strong> — <em>Method</em>.</p>
 <p>Add the flow conservation constraints to the allocation problem. The constraint indices are user node IDs.</p>
 <p>Constraint: sum(flows out of node node) &lt;= flows into node + flow from storage and vertical fluxes</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL452-L458" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL452-L458" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.add_constraints_fractional_flow!-Tuple{JuMP.Model, Ribasim.Parameters, Int64}" href="#Ribasim.add_constraints_fractional_flow!-Tuple{JuMP.Model, Ribasim.Parameters, Int64}">#</a> <strong><code>Ribasim.add_constraints_fractional_flow!</code></strong> — <em>Method</em>.</p>
 <p>Add the fractional flow constraints to the allocation problem. The constraint indices are allocation edges over a fractional flow node.</p>
 <p>Constraint: flow after fractional_flow node &lt;= fraction * inflow</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL579-L585" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL579-L585" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.add_constraints_source!-Tuple{JuMP.Model, Ribasim.Parameters, Int64}" href="#Ribasim.add_constraints_source!-Tuple{JuMP.Model, Ribasim.Parameters, Int64}">#</a> <strong><code>Ribasim.add_constraints_source!</code></strong> — <em>Method</em>.</p>
 <p>Add the source constraints to the allocation problem. The actual threshold values will be set before each allocation solve. The constraint indices are (edge<em>source</em>id, edge<em>dst</em>id).</p>
 <p>Constraint: flow over source edge &lt;= source flow in subnetwork</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL395-L402" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL395-L402" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.add_constraints_user_returnflow!-Tuple{JuMP.Model, Ribasim.Parameters, Int64}" href="#Ribasim.add_constraints_user_returnflow!-Tuple{JuMP.Model, Ribasim.Parameters, Int64}">#</a> <strong><code>Ribasim.add_constraints_user_returnflow!</code></strong> — <em>Method</em>.</p>
 <p>Add the user returnflow constraints to the allocation problem. The constraint indices are user node IDs.</p>
 <p>Constraint: outflow from user &lt;= return factor * inflow to user</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL483-L489" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL483-L489" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.add_flow!-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Number}" href="#Ribasim.add_flow!-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Number}">#</a> <strong><code>Ribasim.add_flow!</code></strong> — <em>Method</em>.</p>
 <p>Add the given flow q to the flow over the edge on the horizontal (self-loop) edge from id to id.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL193-L195" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL193-L195" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.add_flow!-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.NodeID, Number}" href="#Ribasim.add_flow!-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.NodeID, Number}">#</a> <strong><code>Ribasim.add_flow!</code></strong> — <em>Method</em>.</p>
 <p>Add the given flow q to the existing flow over the edge between the given nodes.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL184-L186" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL184-L186" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.add_variables_absolute_value!-Tuple{JuMP.Model, Ribasim.Parameters, Int64, Ribasim.config.Config}" href="#Ribasim.add_variables_absolute_value!-Tuple{JuMP.Model, Ribasim.Parameters, Int64, Ribasim.config.Config}">#</a> <strong><code>Ribasim.add_variables_absolute_value!</code></strong> — <em>Method</em>.</p>
 <p>Certain allocation distribution types use absolute values in the objective function. Since most optimization packages do not support the absolute value function directly, New variables are introduced that act as the absolute value of an expression by posing the appropriate constraints.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL342-L347" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL342-L347" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.add_variables_flow!-Tuple{JuMP.Model, Ribasim.Parameters, Int64}" href="#Ribasim.add_variables_flow!-Tuple{JuMP.Model, Ribasim.Parameters, Int64}">#</a> <strong><code>Ribasim.add_variables_flow!</code></strong> — <em>Method</em>.</p>
 <p>Add the flow variables F to the allocation problem. The variable indices are (edge<em>source</em>id, edge<em>dst</em>id). Non-negativivity constraints are also immediately added to the flow variables.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL326-L330" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL326-L330" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.adjust_edge_capacities!-Tuple{Ribasim.AllocationModel, Ribasim.Parameters, Int64}" href="#Ribasim.adjust_edge_capacities!-Tuple{Ribasim.AllocationModel, Ribasim.Parameters, Int64}">#</a> <strong><code>Ribasim.adjust_edge_capacities!</code></strong> — <em>Method</em>.</p>
 <p>Set the values of the edge capacities. 2 cases:</p>
 <ul>
 <li>Before the first allocation solve, set the edge capacities to their full capacity;</li>
 <li>Before an allocation solve, subtract the flow used by allocation for the previous priority from the edge capacities.</li>
 </ul>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL862-L867" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL862-L867" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.adjust_source_flows!-Tuple{Ribasim.AllocationModel, Ribasim.Parameters, Int64}" href="#Ribasim.adjust_source_flows!-Tuple{Ribasim.AllocationModel, Ribasim.Parameters, Int64}">#</a> <strong><code>Ribasim.adjust_source_flows!</code></strong> — <em>Method</em>.</p>
 <p>Adjust the source flows.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL824-L826" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL824-L826" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.all_neighbor_labels_type-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.EdgeType.T}" href="#Ribasim.all_neighbor_labels_type-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.EdgeType.T}">#</a> <strong><code>Ribasim.all_neighbor_labels_type</code></strong> — <em>Method</em>.</p>
 <p>Get the in- and outneighbor node IDs of the given node ID (label) over the given edge type in the graph.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL242-L245" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL242-L245" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.allocate!-Tuple{Ribasim.Parameters, Ribasim.AllocationModel, Float64}" href="#Ribasim.allocate!-Tuple{Ribasim.Parameters, Ribasim.AllocationModel, Float64}">#</a> <strong><code>Ribasim.allocate!</code></strong> — <em>Method</em>.</p>
 <p>Update the allocation optimization problem for the given subnetwork with the problem state and flows, solve the allocation problem and assign the results to the users.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL901-L904" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL901-L904" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.allocation_graph-Tuple{Ribasim.Parameters, Int64}" href="#Ribasim.allocation_graph-Tuple{Ribasim.Parameters, Int64}">#</a> <strong><code>Ribasim.allocation_graph</code></strong> — <em>Method</em>.</p>
 <p>Build the graph used for the allocation problem.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL300-L302" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL300-L302" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.allocation_graph_used_nodes!-Tuple{Ribasim.Parameters, Int64}" href="#Ribasim.allocation_graph_used_nodes!-Tuple{Ribasim.Parameters, Int64}">#</a> <strong><code>Ribasim.allocation_graph_used_nodes!</code></strong> — <em>Method</em>.</p>
 <p>Find all nodes in the subnetwork which will be used in the allocation network. Some nodes are skipped to optimize allocation optimization.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL1-L4" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL1-L4" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.allocation_path_exists_in_graph-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.NodeID}" href="#Ribasim.allocation_path_exists_in_graph-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.NodeID}">#</a> <strong><code>Ribasim.allocation_path_exists_in_graph</code></strong> — <em>Method</em>.</p>
 <p>Find out whether a path exists between a start node and end node in the given allocation graph.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL1211" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL1211" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.allocation_problem-Tuple{Ribasim.config.Config, Ribasim.Parameters, SparseArrays.SparseMatrixCSC{Float64, Int64}, Int64}" href="#Ribasim.allocation_problem-Tuple{Ribasim.config.Config, Ribasim.Parameters, SparseArrays.SparseMatrixCSC{Float64, Int64}, Int64}">#</a> <strong><code>Ribasim.allocation_problem</code></strong> — <em>Method</em>.</p>
 <p>Construct the allocation problem for the current subnetwork as a JuMP.jl model.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL630-L632" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL630-L632" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.allocation_table-Tuple{Ribasim.Model}" href="#Ribasim.allocation_table-Tuple{Ribasim.Model}">#</a> <strong><code>Ribasim.allocation_table</code></strong> — <em>Method</em>.</p>
 <p>Create an allocation result table for the saved data</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/io.jl#LL242" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/io.jl#LL242" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.assign_allocations!-Tuple{Ribasim.AllocationModel, Ribasim.Parameters, Float64, Int64}" href="#Ribasim.assign_allocations!-Tuple{Ribasim.AllocationModel, Ribasim.Parameters, Float64, Int64}">#</a> <strong><code>Ribasim.assign_allocations!</code></strong> — <em>Method</em>.</p>
 <p>Assign the allocations to the users as determined by the solution of the allocation problem.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL784-L786" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL784-L786" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.avoid_using_own_returnflow!-Tuple{Ribasim.Parameters, Int64}" href="#Ribasim.avoid_using_own_returnflow!-Tuple{Ribasim.Parameters, Int64}">#</a> <strong><code>Ribasim.avoid_using_own_returnflow!</code></strong> — <em>Method</em>.</p>
 <p>Remove allocation user return flow edges that are upstream of the user itself.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL278-L280" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL278-L280" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.basin_bottom-Tuple{Ribasim.Basin, Ribasim.NodeID}" href="#Ribasim.basin_bottom-Tuple{Ribasim.Basin, Ribasim.NodeID}">#</a> <strong><code>Ribasim.basin_bottom</code></strong> — <em>Method</em>.</p>
 <p>Return the bottom elevation of the basin with index i, or nothing if it doesn’t exist</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL705" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL705" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.basin_bottoms-Tuple{Ribasim.Basin, Ribasim.NodeID, Ribasim.NodeID, Ribasim.NodeID}" href="#Ribasim.basin_bottoms-Tuple{Ribasim.Basin, Ribasim.NodeID, Ribasim.NodeID, Ribasim.NodeID}">#</a> <strong><code>Ribasim.basin_bottoms</code></strong> — <em>Method</em>.</p>
 <p>Get the bottom on both ends of a node. If only one has a bottom, use that for both.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL718" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL718" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.basin_table-Tuple{Ribasim.Model}" href="#Ribasim.basin_table-Tuple{Ribasim.Model}">#</a> <strong><code>Ribasim.basin_table</code></strong> — <em>Method</em>.</p>
 <p>Create the basin result table from the saved data</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/io.jl#LL153" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/io.jl#LL153" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.create_callbacks-Tuple{Ribasim.Parameters, Ribasim.config.Config}" href="#Ribasim.create_callbacks-Tuple{Ribasim.Parameters, Ribasim.config.Config}">#</a> <strong><code>Ribasim.create_callbacks</code></strong> — <em>Method</em>.</p>
 <p>Create the different callbacks that are used to store results and feed the simulation with new data. The different callbacks are combined to a CallbackSet that goes to the integrator. Returns the CallbackSet and the SavedValues for flow.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL204-L209" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL204-L209" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.create_graph-Tuple{SQLite.DB, Ribasim.config.Config, Vector{Int64}}" href="#Ribasim.create_graph-Tuple{SQLite.DB, Ribasim.config.Config, Vector{Int64}}">#</a> <strong><code>Ribasim.create_graph</code></strong> — <em>Method</em>.</p>
 <p>Return a directed metagraph with data of nodes (NodeMetadata): <a href="../build/index.html#Ribasim.NodeMetadata"><code>NodeMetadata</code></a></p>
 <p>and data of edges (EdgeMetadata): <a href="../build/index.html#Ribasim.EdgeMetadata"><code>EdgeMetadata</code></a></p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL18-L24" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL18-L24" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.create_storage_tables-Tuple{SQLite.DB, Ribasim.config.Config}" href="#Ribasim.create_storage_tables-Tuple{SQLite.DB, Ribasim.config.Config}">#</a> <strong><code>Ribasim.create_storage_tables</code></strong> — <em>Method</em>.</p>
 <p>Read the Basin / profile table and return all area and level and computed storage values</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL317" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL317" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.datetime_since-Tuple{Real, Dates.DateTime}" href="#Ribasim.datetime_since-Tuple{Real, Dates.DateTime}">#</a> <strong><code>Ribasim.datetime_since</code></strong> — <em>Method</em>.</p>
 <div class="sourceCode" id="cb12"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb12-1"><a href="#cb12-1" aria-hidden="true" tabindex="-1"></a><span class="fu">datetime_since</span>(t<span class="op">::</span><span class="dt">Real</span>, t0<span class="op">::</span><span class="dt">DateTime</span>)<span class="op">::</span><span class="dt">DateTime</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Convert a Real that represents the seconds passed since the simulation start to the nearest DateTime. This is used to convert between the solver’s inner float time, and the calendar.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/io.jl#LL39-L44" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/io.jl#LL39-L44" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.datetimes-Tuple{Ribasim.Model}" href="#Ribasim.datetimes-Tuple{Ribasim.Model}">#</a> <strong><code>Ribasim.datetimes</code></strong> — <em>Method</em>.</p>
 <p>Get all saved times as a Vector{DateTime}</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/lib.jl#LL40" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/lib.jl#LL40" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.discrete_control_affect!-Tuple{Any, Int64, Union{Missing, Bool}}" href="#Ribasim.discrete_control_affect!-Tuple{Any, Int64, Union{Missing, Bool}}">#</a> <strong><code>Ribasim.discrete_control_affect!</code></strong> — <em>Method</em>.</p>
 <p>Change parameters based on the control logic.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL404-L406" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL404-L406" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.discrete_control_affect_downcrossing!-Tuple{Any, Any}" href="#Ribasim.discrete_control_affect_downcrossing!-Tuple{Any, Any}">#</a> <strong><code>Ribasim.discrete_control_affect_downcrossing!</code></strong> — <em>Method</em>.</p>
 <p>An downcrossing means that a condition (always greater than) becomes false.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL371-L373" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL371-L373" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.discrete_control_affect_upcrossing!-Tuple{Any, Any}" href="#Ribasim.discrete_control_affect_upcrossing!-Tuple{Any, Any}">#</a> <strong><code>Ribasim.discrete_control_affect_upcrossing!</code></strong> — <em>Method</em>.</p>
 <p>An upcrossing means that a condition (always greater than) becomes true.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL335-L337" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL335-L337" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.discrete_control_condition-NTuple{4, Any}" href="#Ribasim.discrete_control_condition-NTuple{4, Any}">#</a> <strong><code>Ribasim.discrete_control_condition</code></strong> — <em>Method</em>.</p>
 <p>Listens for changes in condition truths.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL269-L271" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL269-L271" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.discrete_control_table-Tuple{Ribasim.Model}" href="#Ribasim.discrete_control_table-Tuple{Ribasim.Model}">#</a> <strong><code>Ribasim.discrete_control_table</code></strong> — <em>Method</em>.</p>
 <p>Create a discrete control result table from the saved data</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/io.jl#LL226" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/io.jl#LL226" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.expand_logic_mapping-Tuple{Dict{Tuple{Ribasim.NodeID, String}, String}}" href="#Ribasim.expand_logic_mapping-Tuple{Dict{Tuple{Ribasim.NodeID, String}, String}}">#</a> <strong><code>Ribasim.expand_logic_mapping</code></strong> — <em>Method</em>.</p>
 <p>Replace the truth states in the logic mapping which contain wildcards with all possible explicit truth states.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL850-L853" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL850-L853" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.find_allocation_graph_edges!-Tuple{Ribasim.Parameters, Int64}" href="#Ribasim.find_allocation_graph_edges!-Tuple{Ribasim.Parameters, Int64}">#</a> <strong><code>Ribasim.find_allocation_graph_edges!</code></strong> — <em>Method</em>.</p>
 <p>This loop finds allocation graph edges in several ways:</p>
 <ul>
 <li>Between allocation graph nodes whose equivalent in the subnetwork are directly connected</li>
 <li>Between allocation graph nodes whose equivalent in the subnetwork are connected with one or more allocation graph nodes in between</li>
 </ul>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL61-L66" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL61-L66" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.findlastgroup-Tuple{Int64, AbstractVector{Int64}}" href="#Ribasim.findlastgroup-Tuple{Int64, AbstractVector{Int64}}">#</a> <strong><code>Ribasim.findlastgroup</code></strong> — <em>Method</em>.</p>
 <p>For an element <code>id</code> and a vector of elements <code>ids</code>, get the range of indices of the last consecutive block of <code>id</code>. Returns the empty range <code>1:0</code> if <code>id</code> is not in <code>ids</code>.</p>
 <div class="sourceCode" id="cb13"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb13-1"><a href="#cb13-1" aria-hidden="true" tabindex="-1"></a><span class="co">#                         1 2 3 4 5 6 7 8 9</span></span>
 <span id="cb13-2"><a href="#cb13-2" aria-hidden="true" tabindex="-1"></a>Ribasim.<span class="fu">findlastgroup</span>(<span class="fl">2</span>, [<span class="fl">5</span>,<span class="fl">4</span>,<span class="fl">2</span>,<span class="fl">2</span>,<span class="fl">5</span>,<span class="fl">2</span>,<span class="fl">2</span>,<span class="fl">2</span>,<span class="fl">1</span>])</span>
 <span id="cb13-3"><a href="#cb13-3" aria-hidden="true" tabindex="-1"></a><span class="co"># output</span></span>
 <span id="cb13-4"><a href="#cb13-4" aria-hidden="true" tabindex="-1"></a><span class="fl">6</span><span class="op">:</span><span class="fl">8</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL477-L488" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL477-L488" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.findsorted-Tuple{Any, Any}" href="#Ribasim.findsorted-Tuple{Any, Any}">#</a> <strong><code>Ribasim.findsorted</code></strong> — <em>Method</em>.</p>
 <p>Find the index of element x in a sorted collection a. Returns the index of x if it exists, or nothing if it doesn’t. If x occurs more than once, throw an error.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL579-L583" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL579-L583" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.flow_table-Tuple{Ribasim.Model}" href="#Ribasim.flow_table-Tuple{Ribasim.Model}">#</a> <strong><code>Ribasim.flow_table</code></strong> — <em>Method</em>.</p>
 <p>Create a flow result table from the saved data</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/io.jl#LL172" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/io.jl#LL172" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.formulate_basins!-Tuple{AbstractVector, Ribasim.Basin, MetaGraphsNext.MetaGraph, AbstractVector}" href="#Ribasim.formulate_basins!-Tuple{AbstractVector, Ribasim.Basin, MetaGraphsNext.MetaGraph, AbstractVector}">#</a> <strong><code>Ribasim.formulate_basins!</code></strong> — <em>Method</em>.</p>
 <p>Smoothly let the evaporation flux go to 0 when at small water depths Currently at less than 0.1 m.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL535-L538" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL535-L538" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.formulate_flow!-Tuple{Ribasim.LinearResistance, Ribasim.Parameters, AbstractVector, Number}" href="#Ribasim.formulate_flow!-Tuple{Ribasim.LinearResistance, Ribasim.Parameters, AbstractVector, Number}">#</a> <strong><code>Ribasim.formulate_flow!</code></strong> — <em>Method</em>.</p>
 <p>Directed graph: outflow is positive!</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL792-L794" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL792-L794" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.formulate_flow!-Tuple{Ribasim.ManningResistance, Ribasim.Parameters, AbstractVector, Number}" href="#Ribasim.formulate_flow!-Tuple{Ribasim.ManningResistance, Ribasim.Parameters, AbstractVector, Number}">#</a> <strong><code>Ribasim.formulate_flow!</code></strong> — <em>Method</em>.</p>
 <p>Conservation of energy for two basins, a and b:</p>
 <pre><code>h_a + v_a^2 / (2 * g) = h_b + v_b^2 / (2 * g) + S_f * L + C / 2 * g * (v_b^2 - v_a^2)</code></pre>
@@ -598,130 +598,130 @@ <h2 data-number="1.3" class="anchored" data-anchor-id="functions"><span class="h
 <pre><code>R_h = A / P</code></pre>
 <p>Where P is the wetted perimeter.</p>
 <p>The average of the upstream and downstream water depth is used to compute cross-sectional area and hydraulic radius. This ensures that a basin can receive water after it has gone dry.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL858-L896" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL858-L896" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.formulate_flow!-Tuple{Ribasim.TabulatedRatingCurve, Ribasim.Parameters, AbstractVector, Number}" href="#Ribasim.formulate_flow!-Tuple{Ribasim.TabulatedRatingCurve, Ribasim.Parameters, AbstractVector, Number}">#</a> <strong><code>Ribasim.formulate_flow!</code></strong> — <em>Method</em>.</p>
 <p>Directed graph: outflow is positive!</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL828-L830" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/solve.jl#LL828-L830" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.get_area_and_level-Tuple{Ribasim.Basin, Int64, Real}" href="#Ribasim.get_area_and_level-Tuple{Ribasim.Basin, Int64, Real}">#</a> <strong><code>Ribasim.get_area_and_level</code></strong> — <em>Method</em>.</p>
 <p>Compute the area and level of a basin given its storage. Also returns darea/dlevel as it is needed for the Jacobian.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL389-L392" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL389-L392" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.get_chunk_sizes-Tuple{Ribasim.config.Config, Int64}" href="#Ribasim.get_chunk_sizes-Tuple{Ribasim.config.Config, Int64}">#</a> <strong><code>Ribasim.get_chunk_sizes</code></strong> — <em>Method</em>.</p>
 <p>Get the chunk sizes for DiffCache; differentiation w.r.t. u and t (the latter only if a Rosenbrock algorithm is used).</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/create.jl#LL778-L781" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/create.jl#LL778-L781" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.get_compressor-Tuple{Ribasim.config.Results}" href="#Ribasim.get_compressor-Tuple{Ribasim.config.Results}">#</a> <strong><code>Ribasim.get_compressor</code></strong> — <em>Method</em>.</p>
 <p>Get the compressor based on the Results section</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL735" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL735" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.get_flow-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Any}" href="#Ribasim.get_flow-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Any}">#</a> <strong><code>Ribasim.get_flow</code></strong> — <em>Method</em>.</p>
 <p>Get the flow over the given horizontal (selfloop) edge (val is needed for get_tmp from ForwardDiff.jl).</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL210-L212" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL210-L212" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.get_flow-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.NodeID, Any}" href="#Ribasim.get_flow-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.NodeID, Any}">#</a> <strong><code>Ribasim.get_flow</code></strong> — <em>Method</em>.</p>
 <p>Get the flow over the given edge (val is needed for get_tmp from ForwardDiff.jl).</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL202-L204" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL202-L204" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.get_fractional_flow_connected_basins-Tuple{Ribasim.NodeID, Ribasim.Basin, Ribasim.FractionalFlow, MetaGraphsNext.MetaGraph}" href="#Ribasim.get_fractional_flow_connected_basins-Tuple{Ribasim.NodeID, Ribasim.Basin, Ribasim.FractionalFlow, MetaGraphsNext.MetaGraph}">#</a> <strong><code>Ribasim.get_fractional_flow_connected_basins</code></strong> — <em>Method</em>.</p>
 <p>Get the node type specific indices of the fractional flows and basins, that are consecutively connected to a node of given id.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL1111-L1114" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL1111-L1114" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.get_jac_prototype-Tuple{Ribasim.Parameters}" href="#Ribasim.get_jac_prototype-Tuple{Ribasim.Parameters}">#</a> <strong><code>Ribasim.get_jac_prototype</code></strong> — <em>Method</em>.</p>
 <p>Get a sparse matrix whose sparsity matches the sparsity of the Jacobian of the ODE problem. All nodes are taken into consideration, also the ones that are inactive.</p>
 <p>In Ribasim the Jacobian is typically sparse because each state only depends on a small number of other states.</p>
 <p>Note: the name ‘prototype’ does not mean this code is a prototype, it comes from the naming convention of this sparsity structure in the differentialequations.jl docs.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL910-L921" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL910-L921" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.get_level-Tuple{Ribasim.Parameters, Ribasim.NodeID, Number}" href="#Ribasim.get_level-Tuple{Ribasim.Parameters, Ribasim.NodeID, Number}">#</a> <strong><code>Ribasim.get_level</code></strong> — <em>Method</em>.</p>
 <p>Get the current water level of a node ID. The ID can belong to either a Basin or a LevelBoundary. storage: tells ForwardDiff whether this call is for differentiation or not</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL671-L675" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL671-L675" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.get_scalar_interpolation-Tuple{Dates.DateTime, Float64, AbstractVector, Int64, Symbol}" href="#Ribasim.get_scalar_interpolation-Tuple{Dates.DateTime, Float64, AbstractVector, Int64, Symbol}">#</a> <strong><code>Ribasim.get_scalar_interpolation</code></strong> — <em>Method</em>.</p>
 <p>Linear interpolation of a scalar with constant extrapolation.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL504" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL504" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.get_storage_from_level-Tuple{Ribasim.Basin, Int64, Float64}" href="#Ribasim.get_storage_from_level-Tuple{Ribasim.Basin, Int64, Float64}">#</a> <strong><code>Ribasim.get_storage_from_level</code></strong> — <em>Method</em>.</p>
 <p>Get the storage of a basin from its level.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL338" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL338" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.get_storages_and_levels-Tuple{Ribasim.Model}" href="#Ribasim.get_storages_and_levels-Tuple{Ribasim.Model}">#</a> <strong><code>Ribasim.get_storages_and_levels</code></strong> — <em>Method</em>.</p>
 <p>Get the storage and level of all basins as matrices of nbasin × ntime</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/io.jl#LL128" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/io.jl#LL128" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.get_storages_from_levels-Tuple{Ribasim.Basin, Vector}" href="#Ribasim.get_storages_from_levels-Tuple{Ribasim.Basin, Vector}">#</a> <strong><code>Ribasim.get_storages_from_levels</code></strong> — <em>Method</em>.</p>
 <p>Compute the storages of the basins based on the water level of the basins.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL376" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL376" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.get_tstops-Tuple{Any, Dates.DateTime}" href="#Ribasim.get_tstops-Tuple{Any, Dates.DateTime}">#</a> <strong><code>Ribasim.get_tstops</code></strong> — <em>Method</em>.</p>
 <p>From an iterable of DateTimes, find the times the solver needs to stop</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL665" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL665" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.get_value-Tuple{Ribasim.Parameters, Ribasim.NodeID, String, Float64, AbstractVector{Float64}, Float64}" href="#Ribasim.get_value-Tuple{Ribasim.Parameters, Ribasim.NodeID, String, Float64, AbstractVector{Float64}, Float64}">#</a> <strong><code>Ribasim.get_value</code></strong> — <em>Method</em>.</p>
 <p>Get a value for a condition. Currently supports getting levels from basins and flows from flow boundaries.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL290-L293" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL290-L293" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.id_index-Tuple{Dictionaries.Indices{Ribasim.NodeID}, Ribasim.NodeID}" href="#Ribasim.id_index-Tuple{Dictionaries.Indices{Ribasim.NodeID}, Ribasim.NodeID}">#</a> <strong><code>Ribasim.id_index</code></strong> — <em>Method</em>.</p>
 <p>Get the index of an ID in a set of indices.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL697" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL697" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.indicate_allocation_flow!-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.NodeID}" href="#Ribasim.indicate_allocation_flow!-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.NodeID}">#</a> <strong><code>Ribasim.indicate_allocation_flow!</code></strong> — <em>Method</em>.</p>
 <p>Add to the edge metadata that the given edge is used for allocation flow. If the edge does not exist, it is created.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL42-L45" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL42-L45" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.inflow_id-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID}" href="#Ribasim.inflow_id-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID}">#</a> <strong><code>Ribasim.inflow_id</code></strong> — <em>Method</em>.</p>
 <p>Get the unique inneighbor over a flow edge.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL285-L287" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL285-L287" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.inflow_ids-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID}" href="#Ribasim.inflow_ids-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID}">#</a> <strong><code>Ribasim.inflow_ids</code></strong> — <em>Method</em>.</p>
 <p>Get the inneighbors over flow edges.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL264-L266" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL264-L266" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.inflow_ids_allocation-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID}" href="#Ribasim.inflow_ids_allocation-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID}">#</a> <strong><code>Ribasim.inflow_ids_allocation</code></strong> — <em>Method</em>.</p>
 <p>Get the inneighbors of the given ID such that the connecting edge is an allocation flow edge.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL424-L427" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL424-L427" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.inneighbor_labels_type-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.EdgeType.T}" href="#Ribasim.inneighbor_labels_type-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.EdgeType.T}">#</a> <strong><code>Ribasim.inneighbor_labels_type</code></strong> — <em>Method</em>.</p>
 <p>Get the inneighbor node IDs of the given node ID (label) over the given edge type in the graph.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL218-L221" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL218-L221" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.inoutflow_ids-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID}" href="#Ribasim.inoutflow_ids-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID}">#</a> <strong><code>Ribasim.inoutflow_ids</code></strong> — <em>Method</em>.</p>
 <p>Get the in- and outneighbors over flow edges.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL271-L273" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL271-L273" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.is_allocation_source-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.NodeID}" href="#Ribasim.is_allocation_source-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.NodeID}">#</a> <strong><code>Ribasim.is_allocation_source</code></strong> — <em>Method</em>.</p>
 <p>Find out whether the given edge is a source for an allocation network.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL34-L36" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL34-L36" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.is_current_module-Tuple{Any}" href="#Ribasim.is_current_module-Tuple{Any}">#</a> <strong><code>Ribasim.is_current_module</code></strong> — <em>Method</em>.</p>
 <div class="sourceCode" id="cb18"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb18-1"><a href="#cb18-1" aria-hidden="true" tabindex="-1"></a><span class="fu">is_current_module</span>(log<span class="op">::</span><span class="dt">LogMessageType</span>)<span class="op">::</span><span class="dt">Bool</span></span>
 <span id="cb18-2"><a href="#cb18-2" aria-hidden="true" tabindex="-1"></a>Returns <span class="cn">true</span> <span class="cf">if</span> the log message is from the current <span class="kw">module</span> or a submodule.</span>
 <span id="cb18-3"><a href="#cb18-3" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb18-4"><a href="#cb18-4" aria-hidden="true" tabindex="-1"></a>See https<span class="op">://</span>github.com<span class="op">/</span>JuliaLogging<span class="op">/</span>LoggingExtras.jl<span class="op">/</span>blob<span class="op">/</span>d35e7c8cfc197853ee336ace17182e6ed36dca24<span class="op">/</span>src<span class="op">/</span>CompositionalLoggers<span class="op">/</span>earlyfiltered.jl<span class="co">#L39</span></span>
 <span id="cb18-5"><a href="#cb18-5" aria-hidden="true" tabindex="-1"></a><span class="cf">for</span> the information available <span class="kw">in</span> log.</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/logging.jl#LL1-L7" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/logging.jl#LL1-L7" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.is_flow_constraining-Tuple{Ribasim.AbstractParameterNode}" href="#Ribasim.is_flow_constraining-Tuple{Ribasim.AbstractParameterNode}">#</a> <strong><code>Ribasim.is_flow_constraining</code></strong> — <em>Method</em>.</p>
 <p>Whether the given node node is flow constraining by having a maximum flow rate.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL1204" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL1204" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.is_flow_direction_constraining-Tuple{Ribasim.AbstractParameterNode}" href="#Ribasim.is_flow_direction_constraining-Tuple{Ribasim.AbstractParameterNode}">#</a> <strong><code>Ribasim.is_flow_direction_constraining</code></strong> — <em>Method</em>.</p>
 <p>Whether the given node is flow direction constraining (only in direction of edges).</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL1207" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL1207" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.load_data-Tuple{SQLite.DB, Ribasim.config.Config, Type{<:Legolas.AbstractRecord}}" href="#Ribasim.load_data-Tuple{SQLite.DB, Ribasim.config.Config, Type{<:Legolas.AbstractRecord}}">#</a> <strong><code>Ribasim.load_data</code></strong> — <em>Method</em>.</p>
 <div class="sourceCode" id="cb19"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb19-1"><a href="#cb19-1" aria-hidden="true" tabindex="-1"></a><span class="fu">load_data</span>(db<span class="op">::</span><span class="dt">DB</span>, config<span class="op">::</span><span class="dt">Config</span>, nodetype<span class="op">::</span><span class="dt">Symbol</span>, kind<span class="op">::</span><span class="dt">Symbol</span>)<span class="op">::</span><span class="dt">Union{Table, Query, Nothing}</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Load data from Arrow files if available, otherwise the database. Returns either an <code>Arrow.Table</code>, <code>SQLite.Query</code> or <code>nothing</code> if the data is not present.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/io.jl#LL47-L52" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/io.jl#LL47-L52" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.load_structvector-Union{Tuple{T}, Tuple{SQLite.DB, Ribasim.config.Config, Type{T}}} where T<:Tables.AbstractRow" href="#Ribasim.load_structvector-Union{Tuple{T}, Tuple{SQLite.DB, Ribasim.config.Config, Type{T}}} where T<:Tables.AbstractRow">#</a> <strong><code>Ribasim.load_structvector</code></strong> — <em>Method</em>.</p>
 <div class="sourceCode" id="cb20"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb20-1"><a href="#cb20-1" aria-hidden="true" tabindex="-1"></a><span class="fu">load_structvector</span>(db<span class="op">::</span><span class="dt">DB</span>, config<span class="op">::</span><span class="dt">Config</span>, <span class="op">::</span><span class="dt">Type{T}</span>)<span class="op">::</span><span class="dt">StructVector{T}</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Load data from Arrow files if available, otherwise the database. Always returns a StructVector of the given struct type T, which is empty if the table is not found. This function validates the schema, and enforces the required sort order.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/io.jl#LL83-L89" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/io.jl#LL83-L89" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.low_storage_factor-Union{Tuple{T}, Tuple{AbstractVector{T}, Dictionaries.Indices{Ribasim.NodeID}, Ribasim.NodeID, Real}} where T<:Real" href="#Ribasim.low_storage_factor-Union{Tuple{T}, Tuple{AbstractVector{T}, Dictionaries.Indices{Ribasim.NodeID}, Ribasim.NodeID, Real}} where T<:Real">#</a> <strong><code>Ribasim.low_storage_factor</code></strong> — <em>Method</em>.</p>
 <p>If id is a Basin with storage below the threshold, return a reduction factor != 1</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL1189" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL1189" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.main-Tuple{Vector{String}}" href="#Ribasim.main-Tuple{Vector{String}}">#</a> <strong><code>Ribasim.main</code></strong> — <em>Method</em>.</p>
 <div class="sourceCode" id="cb21"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb21-1"><a href="#cb21-1" aria-hidden="true" tabindex="-1"></a><span class="fu">main</span>(<span class="cn">ARGS</span><span class="op">::</span><span class="dt">Vector{String}</span>)<span class="op">::</span><span class="dt">Cint</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>This is the main entry point of the application. Performs argument parsing and sets up logging for both terminal and file. Calls Ribasim.run() and handles exceptions to convert to exit codes.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/main.jl#LL9-L14" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/main.jl#LL9-L14" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.metadata_from_edge-Tuple{MetaGraphsNext.MetaGraph, Graphs.SimpleGraphs.SimpleEdge{Int64}}" href="#Ribasim.metadata_from_edge-Tuple{MetaGraphsNext.MetaGraph, Graphs.SimpleGraphs.SimpleEdge{Int64}}">#</a> <strong><code>Ribasim.metadata_from_edge</code></strong> — <em>Method</em>.</p>
 <p>Get the metadata of an edge in the graph from an edge of the underlying DiGraph.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL292-L295" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL292-L295" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.nodefields-Tuple{Ribasim.Parameters}" href="#Ribasim.nodefields-Tuple{Ribasim.Parameters}">#</a> <strong><code>Ribasim.nodefields</code></strong> — <em>Method</em>.</p>
 <p>Get all node fieldnames of the parameter object.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL904" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL904" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.nodetype-Union{Tuple{Legolas.SchemaVersion{T, N}}, Tuple{N}, Tuple{T}} where {T, N}" href="#Ribasim.nodetype-Union{Tuple{Legolas.SchemaVersion{T, N}}, Tuple{N}, Tuple{T}} where {T, N}">#</a> <strong><code>Ribasim.nodetype</code></strong> — <em>Method</em>.</p>
 <p>From a SchemaVersion(“ribasim.flowboundary.static”, 1) return (:FlowBoundary, :static)</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/validation.jl#LL37-L39" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/validation.jl#LL37-L39" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.outflow_id-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID}" href="#Ribasim.outflow_id-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID}">#</a> <strong><code>Ribasim.outflow_id</code></strong> — <em>Method</em>.</p>
 <p>Get the unique outneighbor over a flow edge.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL278-L280" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL278-L280" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.outflow_ids-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID}" href="#Ribasim.outflow_ids-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID}">#</a> <strong><code>Ribasim.outflow_ids</code></strong> — <em>Method</em>.</p>
 <p>Get the outneighbors over flow edges.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL257-L259" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL257-L259" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.outflow_ids_allocation-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID}" href="#Ribasim.outflow_ids_allocation-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID}">#</a> <strong><code>Ribasim.outflow_ids_allocation</code></strong> — <em>Method</em>.</p>
 <p>Get the outneighbors of the given ID such that the connecting edge is an allocation flow edge.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL438-L441" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL438-L441" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.outneighbor_labels_type-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.EdgeType.T}" href="#Ribasim.outneighbor_labels_type-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.EdgeType.T}">#</a> <strong><code>Ribasim.outneighbor_labels_type</code></strong> — <em>Method</em>.</p>
 <p>Get the outneighbor node IDs of the given node ID (label) over the given edge type in the graph.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL230-L233" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL230-L233" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.parse_static_and_time-Tuple{SQLite.DB, Ribasim.config.Config, String}" href="#Ribasim.parse_static_and_time-Tuple{SQLite.DB, Ribasim.config.Config, String}">#</a> <strong><code>Ribasim.parse_static_and_time</code></strong> — <em>Method</em>.</p>
 <p>Process the data in the static and time tables for a given node type. The ‘defaults’ named tuple dictates how missing data is filled in. ‘time_interpolatables’ is a vector of Symbols of parameter names for which a time interpolation (linear) object must be constructed. The control mapping for DiscreteControl is also constructed in this function. This function currently does not support node states that are defined by more than one row in a table, as is the case for TabulatedRatingCurve.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/create.jl#LL1-L9" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/create.jl#LL1-L9" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.process_allocation_graph_edges!-Tuple{SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Vector{Ribasim.NodeID}}, Ribasim.Parameters, Int64}" href="#Ribasim.process_allocation_graph_edges!-Tuple{SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Vector{Ribasim.NodeID}}, Ribasim.Parameters, Int64}">#</a> <strong><code>Ribasim.process_allocation_graph_edges!</code></strong> — <em>Method</em>.</p>
 <p>For the composite allocation graph edges:</p>
 <ul>
@@ -729,86 +729,86 @@ <h2 data-number="1.3" class="anchored" data-anchor-id="functions"><span class="h
 <li>Compute their capacity</li>
 <li>Find out their allowed flow direction(s)</li>
 </ul>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL143-L148" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL143-L148" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.profile_storage-Tuple{Vector, Vector}" href="#Ribasim.profile_storage-Tuple{Vector, Vector}">#</a> <strong><code>Ribasim.profile_storage</code></strong> — <em>Method</em>.</p>
 <p>Calculate a profile storage by integrating the areas over the levels</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL302" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL302" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.qh_interpolation-Tuple{Int64, StructArrays.StructVector}" href="#Ribasim.qh_interpolation-Tuple{Int64, StructArrays.StructVector}">#</a> <strong><code>Ribasim.qh_interpolation</code></strong> — <em>Method</em>.</p>
 <p>From a table with columns node<em>id, discharge (Q) and level (h), create a LinearInterpolation from level to discharge for a given node</em>id.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL566-L569" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL566-L569" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.reduction_factor-Union{Tuple{T}, Tuple{T, Real}} where T<:Real" href="#Ribasim.reduction_factor-Union{Tuple{T}, Tuple{T, Real}} where T<:Real">#</a> <strong><code>Ribasim.reduction_factor</code></strong> — <em>Method</em>.</p>
 <p>Function that goes smoothly from 0 to 1 in the interval [0,threshold], and is constant outside this interval.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL1174-L1177" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL1174-L1177" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.run-Tuple{AbstractString}" href="#Ribasim.run-Tuple{AbstractString}">#</a> <strong><code>Ribasim.run</code></strong> — <em>Method</em>.</p>
 <div class="sourceCode" id="cb22"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb22-1"><a href="#cb22-1" aria-hidden="true" tabindex="-1"></a><span class="fu">run</span>(config_file<span class="op">::</span><span class="dt">AbstractString</span>)<span class="op">::</span><span class="dt">Model</span></span>
 <span id="cb22-2"><a href="#cb22-2" aria-hidden="true" tabindex="-1"></a><span class="fu">run</span>(config<span class="op">::</span><span class="dt">Config</span>)<span class="op">::</span><span class="dt">Model</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Run a <a href="../build/index.html#Ribasim.Model"><code>Model</code></a>, given a path to a TOML configuration file, or a Config object. Running a model includes initialization, solving to the end with <code>[</code>solve!<code>](@ref)</code> and writing results with <a href="../build/index.html#BasicModelInterface.finalize-Tuple{Ribasim.Model}"><code>BMI.finalize</code></a>.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL663-L668" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL663-L668" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.save_flow-Tuple{Any, Any, Any}" href="#Ribasim.save_flow-Tuple{Any, Any, Any}">#</a> <strong><code>Ribasim.save_flow</code></strong> — <em>Method</em>.</p>
 <p>Copy the current flow to the SavedValues</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL547" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL547" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.save_subgrid_level-Tuple{Any, Any, Any}" href="#Ribasim.save_subgrid_level-Tuple{Any, Any, Any}">#</a> <strong><code>Ribasim.save_subgrid_level</code></strong> — <em>Method</em>.</p>
 <p>Interpolate the levels and save them to SavedValues</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL563" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL563" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.scalar_interpolation_derivative-Tuple{DataInterpolations.LinearInterpolation{Vector{Float64}, Vector{Float64}, true, Float64}, Float64}" href="#Ribasim.scalar_interpolation_derivative-Tuple{DataInterpolations.LinearInterpolation{Vector{Float64}, Vector{Float64}, true, Float64}, Float64}">#</a> <strong><code>Ribasim.scalar_interpolation_derivative</code></strong> — <em>Method</em>.</p>
 <p>Derivative of scalar interpolation.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL531" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL531" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.seconds_since-Tuple{Dates.DateTime, Dates.DateTime}" href="#Ribasim.seconds_since-Tuple{Dates.DateTime, Dates.DateTime}">#</a> <strong><code>Ribasim.seconds_since</code></strong> — <em>Method</em>.</p>
 <div class="sourceCode" id="cb23"><pre class="sourceCode julia code-with-copy"><code class="sourceCode julia"><span id="cb23-1"><a href="#cb23-1" aria-hidden="true" tabindex="-1"></a><span class="fu">seconds_since</span>(t<span class="op">::</span><span class="dt">DateTime</span>, t0<span class="op">::</span><span class="dt">DateTime</span>)<span class="op">::</span><span class="dt">Float64</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>Convert a DateTime to a float that is the number of seconds since the start of the simulation. This is used to convert between the solver’s inner float time, and the calendar.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/io.jl#LL31-L36" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/io.jl#LL31-L36" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.set_current_value!-Tuple{NamedTuple, Vector{Int64}, StructArrays.StructVector, Dates.DateTime}" href="#Ribasim.set_current_value!-Tuple{NamedTuple, Vector{Int64}, StructArrays.StructVector, Dates.DateTime}">#</a> <strong><code>Ribasim.set_current_value!</code></strong> — <em>Method</em>.</p>
 <p>From a timeseries table <code>time</code>, load the most recent applicable data into <code>table</code>. <code>table</code> must be a NamedTuple of vectors with all variables that must be loaded. The most recent applicable data is non-NaN data for a given ID that is on or before <code>t</code>.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL629-L633" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL629-L633" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.set_flow!-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Number}" href="#Ribasim.set_flow!-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Number}">#</a> <strong><code>Ribasim.set_flow!</code></strong> — <em>Method</em>.</p>
 <p>Set the given flow q on the horizontal (self-loop) edge from id to id.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL175-L177" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL175-L177" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.set_flow!-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.NodeID, Number}" href="#Ribasim.set_flow!-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Ribasim.NodeID, Number}">#</a> <strong><code>Ribasim.set_flow!</code></strong> — <em>Method</em>.</p>
 <p>Set the given flow q over the edge between the given nodes.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL166-L168" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL166-L168" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.set_fractional_flow_in_allocation!-Tuple{Ribasim.Parameters, Ribasim.NodeID, Number}" href="#Ribasim.set_fractional_flow_in_allocation!-Tuple{Ribasim.Parameters, Ribasim.NodeID, Number}">#</a> <strong><code>Ribasim.set_fractional_flow_in_allocation!</code></strong> — <em>Method</em>.</p>
 <p>Update the fractional flow fractions in an allocation problem.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL496-L498" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL496-L498" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.set_initial_discrete_controlled_parameters!-Tuple{Any, Vector{Float64}}" href="#Ribasim.set_initial_discrete_controlled_parameters!-Tuple{Any, Vector{Float64}}">#</a> <strong><code>Ribasim.set_initial_discrete_controlled_parameters!</code></strong> — <em>Method</em>.</p>
 <p>Set parameters of nodes that are controlled by DiscreteControl to the values corresponding to the initial state of the model.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL180-L183" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL180-L183" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.set_objective_priority!-Tuple{Ribasim.AllocationModel, Ribasim.Parameters, Float64, Int64}" href="#Ribasim.set_objective_priority!-Tuple{Ribasim.AllocationModel, Ribasim.Parameters, Float64, Int64}">#</a> <strong><code>Ribasim.set_objective_priority!</code></strong> — <em>Method</em>.</p>
 <p>Set the objective for the given priority. For an objective with absolute values this also involves adjusting constraints.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL692-L695" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/allocation.jl#LL692-L695" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.set_static_value!-Tuple{NamedTuple, Vector{Int64}, StructArrays.StructVector}" href="#Ribasim.set_static_value!-Tuple{NamedTuple, Vector{Int64}, StructArrays.StructVector}">#</a> <strong><code>Ribasim.set_static_value!</code></strong> — <em>Method</em>.</p>
 <p>Load data from a source table <code>static</code> into a destination <code>table</code>. Data is matched based on the node_id, which is sorted.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL611-L614" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL611-L614" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.set_table_row!-Tuple{NamedTuple, Any, Int64}" href="#Ribasim.set_table_row!-Tuple{NamedTuple, Any, Int64}">#</a> <strong><code>Ribasim.set_table_row!</code></strong> — <em>Method</em>.</p>
 <p>Update <code>table</code> at row index <code>i</code>, with the values of a given row. <code>table</code> must be a NamedTuple of vectors with all variables that must be loaded. The row must contain all the column names that are present in the table. If a value is NaN, it is not set.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL595-L600" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL595-L600" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.sorted_table!-Tuple{StructArrays.StructVector{<:Legolas.AbstractRecord}}" href="#Ribasim.sorted_table!-Tuple{StructArrays.StructVector{<:Legolas.AbstractRecord}}">#</a> <strong><code>Ribasim.sorted_table!</code></strong> — <em>Method</em>.</p>
 <p>Depending on if a table can be sorted, either sort it or assert that it is sorted.</p>
 <p>Tables loaded from the database into memory can be sorted. Tables loaded from Arrow files are memory mapped and can therefore not be sorted.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/validation.jl#LL398-L403" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/validation.jl#LL398-L403" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.timesteps-Tuple{Ribasim.Model}" href="#Ribasim.timesteps-Tuple{Ribasim.Model}">#</a> <strong><code>Ribasim.timesteps</code></strong> — <em>Method</em>.</p>
 <p>Get all saved times in seconds since start</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/lib.jl#LL37" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/lib.jl#LL37" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.update_allocation!-Tuple{Any}" href="#Ribasim.update_allocation!-Tuple{Any}">#</a> <strong><code>Ribasim.update_allocation!</code></strong> — <em>Method</em>.</p>
 <p>Solve the allocation problem for all users and assign allocated abstractions to user nodes.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL594" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL594" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.update_basin-Tuple{Any}" href="#Ribasim.update_basin-Tuple{Any}">#</a> <strong><code>Ribasim.update_basin</code></strong> — <em>Method</em>.</p>
 <p>Load updates from ‘Basin / time’ into the parameters</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL569" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL569" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.update_jac_prototype!-Tuple{SparseArrays.SparseMatrixCSC{Float64, Int64}, Ribasim.Parameters, Ribasim.AbstractParameterNode}" href="#Ribasim.update_jac_prototype!-Tuple{SparseArrays.SparseMatrixCSC{Float64, Int64}, Ribasim.Parameters, Ribasim.AbstractParameterNode}">#</a> <strong><code>Ribasim.update_jac_prototype!</code></strong> — <em>Method</em>.</p>
 <p>Method for nodes that do not contribute to the Jacobian</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL971-L973" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL971-L973" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.update_jac_prototype!-Tuple{SparseArrays.SparseMatrixCSC{Float64, Int64}, Ribasim.Parameters, Ribasim.PidControl}" href="#Ribasim.update_jac_prototype!-Tuple{SparseArrays.SparseMatrixCSC{Float64, Int64}, Ribasim.Parameters, Ribasim.PidControl}">#</a> <strong><code>Ribasim.update_jac_prototype!</code></strong> — <em>Method</em>.</p>
 <p>The controlled basin affects itself and the basins upstream and downstream of the controlled pump affect eachother if there is a basin upstream of the pump. The state for the integral term and the controlled basin affect eachother, and the same for the integral state and the basin upstream of the pump if it is indeed a basin.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL1048-L1053" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL1048-L1053" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.update_jac_prototype!-Tuple{SparseArrays.SparseMatrixCSC{Float64, Int64}, Ribasim.Parameters, Union{Ribasim.LinearResistance, Ribasim.ManningResistance}}" href="#Ribasim.update_jac_prototype!-Tuple{SparseArrays.SparseMatrixCSC{Float64, Int64}, Ribasim.Parameters, Union{Ribasim.LinearResistance, Ribasim.ManningResistance}}">#</a> <strong><code>Ribasim.update_jac_prototype!</code></strong> — <em>Method</em>.</p>
 <p>If both the unique node upstream and the unique node downstream of these nodes are basins, then these directly depend on eachother and affect the Jacobian 2x Basins always depend on themselves.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL936-L940" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL936-L940" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.update_jac_prototype!-Tuple{SparseArrays.SparseMatrixCSC{Float64, Int64}, Ribasim.Parameters, Union{Ribasim.User, Ribasim.Outlet, Ribasim.Pump, Ribasim.TabulatedRatingCurve}}" href="#Ribasim.update_jac_prototype!-Tuple{SparseArrays.SparseMatrixCSC{Float64, Int64}, Ribasim.Parameters, Union{Ribasim.User, Ribasim.Outlet, Ribasim.Pump, Ribasim.TabulatedRatingCurve}}">#</a> <strong><code>Ribasim.update_jac_prototype!</code></strong> — <em>Method</em>.</p>
 <p>If both the unique node upstream and the nodes down stream (or one node further if a fractional flow is in between) are basins, then the downstream basin depends on the upstream basin(s) and affect the Jacobian as many times as there are downstream basins Upstream basins always depend on themselves.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL999-L1004" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/utils.jl#LL999-L1004" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.update_tabulated_rating_curve!-Tuple{Any}" href="#Ribasim.update_tabulated_rating_curve!-Tuple{Any}">#</a> <strong><code>Ribasim.update_tabulated_rating_curve!</code></strong> — <em>Method</em>.</p>
 <p>Load updates from ‘TabulatedRatingCurve / time’ into the parameters</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/bmi.jl#LL602" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/bmi.jl#LL602" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.valid_discrete_control-Tuple{Ribasim.Parameters, Ribasim.config.Config}" href="#Ribasim.valid_discrete_control-Tuple{Ribasim.Parameters, Ribasim.config.Config}">#</a> <strong><code>Ribasim.valid_discrete_control</code></strong> — <em>Method</em>.</p>
 <p>Check:</p>
 <ul>
@@ -816,50 +816,50 @@ <h2 data-number="1.3" class="anchored" data-anchor-id="functions"><span class="h
 <li>Whether the supplied truth states have the proper length;</li>
 <li>Whether look_ahead is only supplied for condition variables given by a time-series.</li>
 </ul>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/utils.jl#LL750-L755" class="documenter-source">source</a><br></p>
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 <p><a id="Ribasim.valid_edge_types-Tuple{SQLite.DB}" href="#Ribasim.valid_edge_types-Tuple{SQLite.DB}">#</a> <strong><code>Ribasim.valid_edge_types</code></strong> — <em>Method</em>.</p>
 <p>Check that only supported edge types are declared.</p>
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 <p><a id="Ribasim.valid_edges-Tuple{MetaGraphsNext.MetaGraph}" href="#Ribasim.valid_edges-Tuple{MetaGraphsNext.MetaGraph}">#</a> <strong><code>Ribasim.valid_edges</code></strong> — <em>Method</em>.</p>
 <p>Test for each node given its node type whether the nodes that</p>
 <p><strong>are downstream (‘down-edge’) of this node are of an allowed type</strong></p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/validation.jl#LL435-L438" class="documenter-source">source</a><br></p>
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 <p>Test whether static or discrete controlled flow rates are indeed non-negative.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/validation.jl#LL489-L491" class="documenter-source">source</a><br></p>
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 <p>Check that nodes that have fractional flow outneighbors do not have any other type of outneighbor, that the fractions leaving a node add up to ≈1 and that the fractions are non-negative.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/validation.jl#LL565-L568" class="documenter-source">source</a><br></p>
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 <p><a id="Ribasim.valid_n_neighbors-Tuple{Ribasim.Parameters}" href="#Ribasim.valid_n_neighbors-Tuple{Ribasim.Parameters}">#</a> <strong><code>Ribasim.valid_n_neighbors</code></strong> — <em>Method</em>.</p>
 <p>Test for each node given its node type whether it has an allowed number of flow/control inneighbors and outneighbors</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL466-L469" class="documenter-source">source</a><br></p>
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 <p><a id="Ribasim.valid_profiles-Tuple{Dictionaries.Indices{Ribasim.NodeID}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}" href="#Ribasim.valid_profiles-Tuple{Dictionaries.Indices{Ribasim.NodeID}, Vector{Vector{Float64}}, Vector{Vector{Float64}}}">#</a> <strong><code>Ribasim.valid_profiles</code></strong> — <em>Method</em>.</p>
 <p>Check whether the profile data has no repeats in the levels and the areas start positive.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/validation.jl#LL456-L458" class="documenter-source">source</a><br></p>
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 <p><a id="Ribasim.valid_sources-Tuple{Ribasim.Parameters, Int64}" href="#Ribasim.valid_sources-Tuple{Ribasim.Parameters, Int64}">#</a> <strong><code>Ribasim.valid_sources</code></strong> — <em>Method</em>.</p>
 <p>The source nodes must only have one allocation outneighbor and no allocation inneighbors.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/allocation.jl#LL244-L246" class="documenter-source">source</a><br></p>
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 <p><a id="Ribasim.valid_subgrid-Tuple{Int64, Ribasim.NodeID, Dict{Ribasim.NodeID, Int64}, Vector{Float64}, Vector{Float64}}" href="#Ribasim.valid_subgrid-Tuple{Int64, Ribasim.NodeID, Dict{Ribasim.NodeID, Int64}, Vector{Float64}, Vector{Float64}}">#</a> <strong><code>Ribasim.valid_subgrid</code></strong> — <em>Method</em>.</p>
 <p>Validate the entries for a single subgrid element.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/validation.jl#LL634-L636" class="documenter-source">source</a><br></p>
+<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/bf2751359fd0dbefdc641849d09ea3e422aefe39/core/src/validation.jl#LL634-L636" class="documenter-source">source</a><br></p>
 <p><a id="Ribasim.water_balance!-Tuple{ComponentArrays.ComponentVector, ComponentArrays.ComponentVector, Ribasim.Parameters, Number}" href="#Ribasim.water_balance!-Tuple{ComponentArrays.ComponentVector, ComponentArrays.ComponentVector, Ribasim.Parameters, Number}">#</a> <strong><code>Ribasim.water_balance!</code></strong> — <em>Method</em>.</p>
 <p>The right hand side function of the system of ODEs set up by Ribasim.</p>
-<p><a target="_blank" href="https://github.com/Deltares/Ribasim.jl/blob/3da66d77e7b2c46323559e8e973f15e71493b484/core/src/solve.jl#LL1154-L1156" class="documenter-source">source</a><br></p>
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 <p><a id="Ribasim.write_arrow-Tuple{AbstractString, NamedTuple, TranscodingStreams.Codec}" href="#Ribasim.write_arrow-Tuple{AbstractString, NamedTuple, TranscodingStreams.Codec}">#</a> <strong><code>Ribasim.write_arrow</code></strong> — <em>Method</em>.</p>
 <p>Write a result table to disk as an Arrow file</p>
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 <p><a id="Ribasim.config.algorithm-Tuple{Ribasim.config.Solver}" href="#Ribasim.config.algorithm-Tuple{Ribasim.config.Solver}">#</a> <strong><code>Ribasim.config.algorithm</code></strong> — <em>Method</em>.</p>
 <p>Create an OrdinaryDiffEqAlgorithm from solver config</p>
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 <p><a id="Ribasim.config.input_path-Tuple{Ribasim.config.Config, String}" href="#Ribasim.config.input_path-Tuple{Ribasim.config.Config, String}">#</a> <strong><code>Ribasim.config.input_path</code></strong> — <em>Method</em>.</p>
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 <p><a id="Constants"></a></p>
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@@ -880,7 +880,7 @@ <h2 data-number="1.4" class="anchored" data-anchor-id="constants"><span class="h
 <li><code>ImplicitEuler</code></li>
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 <p><a id="Index"></a></p>
 <p><a id="Index-1"></a></p>
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+<li><a href="../build/index.html#Ribasim.formulate_flow!-Tuple{Ribasim.LinearResistance, Ribasim.Parameters, AbstractVector, Number}"><code>Ribasim.formulate_flow!</code></a></li>
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 <li><a href="../build/index.html#Ribasim.set_flow!-Tuple{MetaGraphsNext.MetaGraph, Ribasim.NodeID, Number}"><code>Ribasim.set_flow!</code></a></li>
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diff --git a/python/examples.html b/python/examples.html
index a42bbe712..cdf9bac99 100644
--- a/python/examples.html
+++ b/python/examples.html
@@ -187,6 +187,12 @@
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+  <div class="sidebar-item-container"> 
+  <a href="../python/test-models.html" class="sidebar-item-text sidebar-link">
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@@ -553,7 +559,7 @@ <h1 data-number="2"><span class="header-section-number">2</span> Update the basi
 <span id="cb28-4"><a href="#cb28-4" aria-hidden="true" tabindex="-1"></a>ax <span class="op">=</span> df_flow.pivot_table(index<span class="op">=</span><span class="st">"time"</span>, columns<span class="op">=</span><span class="st">"edge"</span>, values<span class="op">=</span><span class="st">"flow_m3d"</span>).plot()</span>
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 <div class="cell-output cell-output-display" data-execution_count="26">
-<pre><code>&lt;matplotlib.legend.Legend at 0x7f56d0123a50&gt;</code></pre>
+<pre><code>&lt;matplotlib.legend.Legend at 0x7f8f0637bd10&gt;</code></pre>
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  <span class="menu-text">API Reference</span></a>
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+</li>
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index 4b1c0e7f4..7d9b7fe38 100644
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+ <span class="menu-text">Test models</span></a>
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+  <a href="../python/test-models.html" class="sidebar-item-text sidebar-link active">
+ <span class="menu-text">Test models</span></a>
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+<h1 class="title">Test models</h1>
+</div>
+
+
+
+<div class="quarto-title-meta">
+
+    
+  
+    
+  </div>
+  
+
+</header>
+
+<p>Ribasim developers use the following models in its testbench and in order to test new features.</p>
+<div class="cell" data-execution_count="1">
+<details>
+<summary>Code</summary>
+<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> ribasim_testmodels</span>
+<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> matplotlib.pyplot <span class="im">as</span> plt</span>
+<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a><span class="cf">for</span> model_name, model_constructor <span class="kw">in</span> ribasim_testmodels.constructors.items():</span>
+<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a>    <span class="cf">if</span> model_name.startswith(<span class="st">"invalid"</span>):</span>
+<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a>        <span class="cf">continue</span></span>
+<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb1-8"><a href="#cb1-8" aria-hidden="true" tabindex="-1"></a>    model <span class="op">=</span> model_constructor()</span>
+<span id="cb1-9"><a href="#cb1-9" aria-hidden="true" tabindex="-1"></a>    fig, ax <span class="op">=</span> plt.subplots()</span>
+<span id="cb1-10"><a href="#cb1-10" aria-hidden="true" tabindex="-1"></a>    model.plot(ax)</span>
+<span id="cb1-11"><a href="#cb1-11" aria-hidden="true" tabindex="-1"></a>    ax.set_title(label<span class="op">=</span>model_name, loc<span class="op">=</span><span class="st">"left"</span>)</span>
+<span id="cb1-12"><a href="#cb1-12" aria-hidden="true" tabindex="-1"></a>    fig.text(<span class="dv">0</span>, <span class="dv">1</span>, model_constructor.__doc__)</span>
+<span id="cb1-13"><a href="#cb1-13" aria-hidden="true" tabindex="-1"></a>    fig.tight_layout()</span>
+<span id="cb1-14"><a href="#cb1-14" aria-hidden="true" tabindex="-1"></a>    plt.show()</span>
+<span id="cb1-15"><a href="#cb1-15" aria-hidden="true" tabindex="-1"></a>    plt.close(fig)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</details>
+<div class="cell-output cell-output-display">
+<p><img src="test-models_files/figure-html/cell-2-output-1.png" width="676" height="359"></p>
+</div>
+<div class="cell-output cell-output-display">
+<p><img src="test-models_files/figure-html/cell-2-output-2.png" width="677" height="292"></p>
+</div>
+<div class="cell-output cell-output-display">
+<p><img src="test-models_files/figure-html/cell-2-output-3.png" width="724" height="494"></p>
+</div>
+<div class="cell-output cell-output-display">
+<p><img src="test-models_files/figure-html/cell-2-output-4.png" width="724" height="457"></p>
+</div>
+<div class="cell-output cell-output-display">
+<p><img src="test-models_files/figure-html/cell-2-output-5.png" width="724" height="494"></p>
+</div>
+<div class="cell-output cell-output-stderr">
+<pre><code>/home/runner/work/Ribasim/Ribasim/python/ribasim/ribasim/geometry/edge.py:77: UserWarning:
+
+The GeoDataFrame you are attempting to plot is empty. Nothing has been displayed.
+</code></pre>
+</div>
+<div class="cell-output cell-output-display">
+<p><img src="test-models_files/figure-html/cell-2-output-7.png" width="677" height="418"></p>
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diff --git a/search.json b/search.json
index f35de8dc6..c64c7d92b 100644
--- a/search.json
+++ b/search.json
@@ -266,172 +266,144 @@
     "text": "4.3 Empty basins\nReduction factors are introduced at several points in the definition of \\(\\mathbf{f}\\) to smooth out otherwise discontinuous transitions (e.g. the flow rate of a pump going to zero when the source basin dries out). If flows are not too large with respect to basin storage, this will prevent basins from reaching 0. Rather, the basin gets a very small storage. The reduction factors help with performance, but are also an important tool to avoid getting negative storage in basins. Negative storage needs to be avoided since it is not a real solution, and would introduce water into the model that doesn’t exist. Another tool used to avoid negative storage is the isoutoutofdomain option, which Ribasim makes use of. This reject timesteps that lead to negative storage, instead retrying with a smaller timestep."
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+    "title": "Test models",
     "section": "",
-    "text": "1 Basic model with static forcing\n\nfrom pathlib import Path\n\nimport geopandas as gpd\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nimport ribasim\n\nSetup the basins:\n\nprofile = pd.DataFrame(\n    data={\n        \"node_id\": [1, 1, 3, 3, 6, 6, 9, 9],\n        \"area\": [0.01, 1000.0] * 4,\n        \"level\": [0.0, 1.0] * 4,\n    }\n)\n\n# Convert steady forcing to m/s\n# 2 mm/d precipitation, 1 mm/d evaporation\nseconds_in_day = 24 * 3600\nprecipitation = 0.002 / seconds_in_day\nevaporation = 0.001 / seconds_in_day\n\nstatic = pd.DataFrame(\n    data={\n        \"node_id\": [0],\n        \"drainage\": [0.0],\n        \"potential_evaporation\": [evaporation],\n        \"infiltration\": [0.0],\n        \"precipitation\": [precipitation],\n        \"urban_runoff\": [0.0],\n    }\n)\nstatic = static.iloc[[0, 0, 0, 0]]\nstatic[\"node_id\"] = [1, 3, 6, 9]\n\nbasin = ribasim.Basin(profile=profile, static=static)\n\nSetup linear resistance:\n\nlinear_resistance = ribasim.LinearResistance(\n    static=pd.DataFrame(\n        data={\"node_id\": [10, 12], \"resistance\": [5e3, (3600.0 * 24) / 100.0]}\n    )\n)\n\nSetup Manning resistance:\n\nmanning_resistance = ribasim.ManningResistance(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [2],\n            \"length\": [900.0],\n            \"manning_n\": [0.04],\n            \"profile_width\": [6.0],\n            \"profile_slope\": [3.0],\n        }\n    )\n)\n\nSet up a rating curve node:\n\n# Discharge: lose 1% of storage volume per day at storage = 1000.0.\nq1000 = 1000.0 * 0.01 / seconds_in_day\n\nrating_curve = ribasim.TabulatedRatingCurve(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [4, 4],\n            \"level\": [0.0, 1.0],\n            \"discharge\": [0.0, q1000],\n        }\n    )\n)\n\nSetup fractional flows:\n\nfractional_flow = ribasim.FractionalFlow(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [5, 8, 13],\n            \"fraction\": [0.3, 0.6, 0.1],\n        }\n    )\n)\n\nSetup pump:\n\npump = ribasim.Pump(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [7],\n            \"flow_rate\": [0.5 / 3600],\n        }\n    )\n)\n\nSetup level boundary:\n\nlevel_boundary = ribasim.LevelBoundary(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [11, 17],\n            \"level\": [0.5, 1.5],\n        }\n    )\n)\n\nSetup flow boundary:\n\nflow_boundary = ribasim.FlowBoundary(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [15, 16],\n            \"flow_rate\": [1e-4, 1e-4],\n        }\n    )\n)\n\nSetup terminal:\n\nterminal = ribasim.Terminal(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [14],\n        }\n    )\n)\n\nSet up the nodes:\n\nxy = np.array(\n    [\n        (0.0, 0.0),  # 1: Basin,\n        (1.0, 0.0),  # 2: ManningResistance\n        (2.0, 0.0),  # 3: Basin\n        (3.0, 0.0),  # 4: TabulatedRatingCurve\n        (3.0, 1.0),  # 5: FractionalFlow\n        (3.0, 2.0),  # 6: Basin\n        (4.0, 1.0),  # 7: Pump\n        (4.0, 0.0),  # 8: FractionalFlow\n        (5.0, 0.0),  # 9: Basin\n        (6.0, 0.0),  # 10: LinearResistance\n        (2.0, 2.0),  # 11: LevelBoundary\n        (2.0, 1.0),  # 12: LinearResistance\n        (3.0, -1.0),  # 13: FractionalFlow\n        (3.0, -2.0),  # 14: Terminal\n        (3.0, 3.0),  # 15: FlowBoundary\n        (0.0, 1.0),  # 16: FlowBoundary\n        (6.0, 1.0),  # 17: LevelBoundary\n    ]\n)\nnode_xy = gpd.points_from_xy(x=xy[:, 0], y=xy[:, 1])\n\nnode_id, node_type = ribasim.Node.node_ids_and_types(\n    basin,\n    manning_resistance,\n    rating_curve,\n    pump,\n    fractional_flow,\n    linear_resistance,\n    level_boundary,\n    flow_boundary,\n    terminal,\n)\n\n# Make sure the feature id starts at 1: explicitly give an index.\nnode = ribasim.Node(\n    df=gpd.GeoDataFrame(\n        data={\"type\": node_type},\n        index=pd.Index(node_id, name=\"fid\"),\n        geometry=node_xy,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup the edges:\n\nfrom_id = np.array(\n    [1, 2, 3, 4, 4, 5, 6, 8, 7, 9, 11, 12, 4, 13, 15, 16, 10], dtype=np.int64\n)\nto_id = np.array(\n    [2, 3, 4, 5, 8, 6, 7, 9, 9, 10, 12, 3, 13, 14, 6, 1, 17], dtype=np.int64\n)\nlines = node.geometry_from_connectivity(from_id, to_id)\nedge = ribasim.Edge(\n    df=gpd.GeoDataFrame(\n        data={\n            \"from_node_id\": from_id,\n            \"to_node_id\": to_id,\n            \"edge_type\": len(from_id) * [\"flow\"],\n        },\n        geometry=lines,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup a model:\n\nmodel = ribasim.Model(\n    network=ribasim.Network(\n        node=node,\n        edge=edge,\n    ),\n    basin=basin,\n    level_boundary=level_boundary,\n    flow_boundary=flow_boundary,\n    pump=pump,\n    linear_resistance=linear_resistance,\n    manning_resistance=manning_resistance,\n    tabulated_rating_curve=rating_curve,\n    fractional_flow=fractional_flow,\n    terminal=terminal,\n    starttime=\"2020-01-01 00:00:00\",\n    endtime=\"2021-01-01 00:00:00\",\n)\n\nLet’s take a look at the model:\n\nmodel.plot()\n\n&lt;Axes: &gt;\n\n\n\n\n\nWrite the model to a TOML and GeoPackage:\n\ndatadir = Path(\"data\")\nmodel.write(datadir / \"basic/ribasim.toml\")\n\nPosixPath('data/basic/ribasim.toml')\n\n\n\n\n2 Update the basic model with transient forcing\nThis assumes you have already created the basic model with static forcing.\n\nimport numpy as np\nimport pandas as pd\nimport ribasim\nimport xarray as xr\n\n\nmodel = ribasim.Model(filepath=datadir / \"basic/ribasim.toml\")\n\n\ntime = pd.date_range(model.starttime, model.endtime)\nday_of_year = time.day_of_year.to_numpy()\nseconds_per_day = 24 * 60 * 60\nevaporation = (\n    (-1.0 * np.cos(day_of_year / 365.0 * 2 * np.pi) + 1.0) * 0.0025 / seconds_per_day\n)\nrng = np.random.default_rng(seed=0)\nprecipitation = (\n    rng.lognormal(mean=-1.0, sigma=1.7, size=time.size) * 0.001 / seconds_per_day\n)\n\nWe’ll use xarray to easily broadcast the values.\n\ntimeseries = (\n    pd.DataFrame(\n        data={\n            \"node_id\": 1,\n            \"time\": pd.date_range(model.starttime, model.endtime),\n            \"drainage\": 0.0,\n            \"potential_evaporation\": evaporation,\n            \"infiltration\": 0.0,\n            \"precipitation\": precipitation,\n            \"urban_runoff\": 0.0,\n        }\n    )\n    .set_index(\"time\")\n    .to_xarray()\n)\n\nbasin_ids = model.basin.static.df[\"node_id\"].to_numpy()\nbasin_nodes = xr.DataArray(\n    np.ones(len(basin_ids)), coords={\"node_id\": basin_ids}, dims=[\"node_id\"]\n)\nforcing = (timeseries * basin_nodes).to_dataframe().reset_index()\n\n\nstate = pd.DataFrame(\n    data={\n        \"node_id\": basin_ids,\n        \"level\": 1.4,\n    }\n)\n\n\nmodel.basin.time.df = forcing\nmodel.basin.state.df = state\n\n\nmodel.write(datadir / \"basic_transient/ribasim.toml\")\n\nPosixPath('data/basic_transient/ribasim.toml')\n\n\nNow run the model with ribasim basic_transient/ribasim.toml. After running the model, read back the results:\n\ndf_basin = pd.read_feather(datadir / \"basic_transient/results/basin.arrow\")\ndf_basin_wide = df_basin.pivot_table(\n    index=\"time\", columns=\"node_id\", values=[\"storage\", \"level\"]\n)\ndf_basin_wide[\"level\"].plot()\n\n&lt;Axes: xlabel='time'&gt;\n\n\n\n\n\n\ndf_flow = pd.read_feather(datadir / \"basic_transient/results/flow.arrow\")\ndf_flow[\"edge\"] = list(zip(df_flow.from_node_id, df_flow.to_node_id))\ndf_flow[\"flow_m3d\"] = df_flow.flow * 86400\nax = df_flow.pivot_table(index=\"time\", columns=\"edge\", values=\"flow_m3d\").plot()\nax.legend(bbox_to_anchor=(1.3, 1), title=\"Edge\")\n\n&lt;matplotlib.legend.Legend at 0x7f56d0123a50&gt;\n\n\n\n\n\n\ntype(df_flow)\n\npandas.core.frame.DataFrame\n\n\n\n\n3 Model with discrete control\nThe model constructed below consists of a single basin which slowly drains trough a TabulatedRatingCurve, but is held within a range around a target level (setpoint) by two connected pumps. These two pumps behave like a reversible pump. When pumping can be done in only one direction, and the other direction is only possible under gravity, use an Outlet for that direction.\nSet up the nodes:\n\nxy = np.array(\n    [\n        (0.0, 0.0),  # 1: Basin\n        (1.0, 1.0),  # 2: Pump\n        (1.0, -1.0),  # 3: Pump\n        (2.0, 0.0),  # 4: LevelBoundary\n        (-1.0, 0.0),  # 5: TabulatedRatingCurve\n        (-2.0, 0.0),  # 6: Terminal\n        (1.0, 0.0),  # 7: DiscreteControl\n    ]\n)\n\nnode_xy = gpd.points_from_xy(x=xy[:, 0], y=xy[:, 1])\n\nnode_type = [\n    \"Basin\",\n    \"Pump\",\n    \"Pump\",\n    \"LevelBoundary\",\n    \"TabulatedRatingCurve\",\n    \"Terminal\",\n    \"DiscreteControl\",\n]\n\n# Make sure the feature id starts at 1: explicitly give an index.\nnode = ribasim.Node(\n    df=gpd.GeoDataFrame(\n        data={\"type\": node_type},\n        index=pd.Index(np.arange(len(xy)) + 1, name=\"fid\"),\n        geometry=node_xy,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup the edges:\n\nfrom_id = np.array([1, 3, 4, 2, 1, 5, 7, 7], dtype=np.int64)\nto_id = np.array([3, 4, 2, 1, 5, 6, 2, 3], dtype=np.int64)\n\nedge_type = 6 * [\"flow\"] + 2 * [\"control\"]\n\nlines = node.geometry_from_connectivity(from_id, to_id)\nedge = ribasim.Edge(\n    df=gpd.GeoDataFrame(\n        data={\"from_node_id\": from_id, \"to_node_id\": to_id, \"edge_type\": edge_type},\n        geometry=lines,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup the basins:\n\nprofile = pd.DataFrame(\n    data={\n        \"node_id\": [1, 1],\n        \"area\": [1000.0, 1000.0],\n        \"level\": [0.0, 1.0],\n    }\n)\n\nstatic = pd.DataFrame(\n    data={\n        \"node_id\": [1],\n        \"drainage\": [0.0],\n        \"potential_evaporation\": [0.0],\n        \"infiltration\": [0.0],\n        \"precipitation\": [0.0],\n        \"urban_runoff\": [0.0],\n    }\n)\n\nstate = pd.DataFrame(data={\"node_id\": [1], \"level\": [20.0]})\n\nbasin = ribasim.Basin(profile=profile, static=static, state=state)\n\nSetup the discrete control:\n\ncondition = pd.DataFrame(\n    data={\n        \"node_id\": 3 * [7],\n        \"listen_feature_id\": 3 * [1],\n        \"variable\": 3 * [\"level\"],\n        \"greater_than\": [5.0, 10.0, 15.0],  # min, setpoint, max\n    }\n)\n\nlogic = pd.DataFrame(\n    data={\n        \"node_id\": 5 * [7],\n        \"truth_state\": [\"FFF\", \"U**\", \"T*F\", \"**D\", \"TTT\"],\n        \"control_state\": [\"in\", \"in\", \"none\", \"out\", \"out\"],\n    }\n)\n\ndiscrete_control = ribasim.DiscreteControl(condition=condition, logic=logic)\n\nThe above control logic can be summarized as follows: - If the level gets above the maximum, activate the control state “out” until the setpoint is reached; - If the level gets below the minimum, active the control state “in” until the setpoint is reached; - Otherwise activate the control state “none”.\nSetup the pump:\n\npump = ribasim.Pump(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": 3 * [2] + 3 * [3],\n            \"control_state\": 2 * [\"none\", \"in\", \"out\"],\n            \"flow_rate\": [0.0, 2e-3, 0.0, 0.0, 0.0, 2e-3],\n        }\n    )\n)\n\nThe pump data defines the following:\n\n\n\nControl state\nPump #2 flow rate (m/s)\nPump #3 flow rate (m/s)\n\n\n\n\n“none”\n0.0\n0.0\n\n\n“in”\n2e-3\n0.0\n\n\n“out”\n0.0\n2e-3\n\n\n\nSetup the level boundary:\n\nlevel_boundary = ribasim.LevelBoundary(\n    static=pd.DataFrame(data={\"node_id\": [4], \"level\": [10.0]})\n)\n\nSetup the rating curve:\n\nrating_curve = ribasim.TabulatedRatingCurve(\n    static=pd.DataFrame(\n        data={\"node_id\": 2 * [5], \"level\": [2.0, 15.0], \"discharge\": [0.0, 1e-3]}\n    )\n)\n\nSetup the terminal:\n\nterminal = ribasim.Terminal(static=pd.DataFrame(data={\"node_id\": [6]}))\n\nSetup a model:\n\nmodel = ribasim.Model(\n    network=ribasim.Network(\n        node=node,\n        edge=edge,\n    ),\n    basin=basin,\n    pump=pump,\n    level_boundary=level_boundary,\n    tabulated_rating_curve=rating_curve,\n    terminal=terminal,\n    discrete_control=discrete_control,\n    starttime=\"2020-01-01 00:00:00\",\n    endtime=\"2021-01-01 00:00:00\",\n)\n\nLet’s take a look at the model:\n\nmodel.plot()\n\n&lt;Axes: &gt;\n\n\n\n\n\nListen edges are plotted with a dashed line since they are not present in the “Edge / static” schema but only in the “Control / condition” schema.\n\ndatadir = Path(\"data\")\nmodel.write(datadir / \"level_setpoint_with_minmax/ribasim.toml\")\n\nPosixPath('data/level_setpoint_with_minmax/ribasim.toml')\n\n\nNow run the model with level_setpoint_with_minmax/ribasim.toml. After running the model, read back the results:\n\nfrom matplotlib.dates import date2num\n\ndf_basin = pd.read_feather(datadir / \"level_setpoint_with_minmax/results/basin.arrow\")\ndf_basin_wide = df_basin.pivot_table(\n    index=\"time\", columns=\"node_id\", values=[\"storage\", \"level\"]\n)\n\nax = df_basin_wide[\"level\"].plot()\n\ngreater_than = model.discrete_control.condition.df.greater_than\n\nax.hlines(\n    greater_than,\n    df_basin.time[0],\n    df_basin.time.max(),\n    lw=1,\n    ls=\"--\",\n    color=\"k\",\n)\n\ndf_control = pd.read_feather(\n    datadir / \"level_setpoint_with_minmax/results/control.arrow\"\n)\n\ny_min, y_max = ax.get_ybound()\nax.fill_between(df_control.time[:2], 2 * [y_min], 2 * [y_max], alpha=0.2, color=\"C0\")\nax.fill_between(df_control.time[2:4], 2 * [y_min], 2 * [y_max], alpha=0.2, color=\"C0\")\n\nax.set_xticks(\n    date2num(df_control.time).tolist(),\n    df_control.control_state.tolist(),\n    rotation=50,\n)\n\nax.set_yticks(greater_than, [\"min\", \"setpoint\", \"max\"])\nax.set_ylabel(\"level\")\nplt.show()\n\n\n\n\nThe highlighted regions show where a pump is active.\nLet’s print an overview of what happened with control:\n\nmodel.print_discrete_control_record(\n    datadir / \"level_setpoint_with_minmax/results/control.arrow\"\n)\n\n0. At 2020-01-01 00:00:00 the control node with ID 7 reached truth state TTT:\n    For node ID 1 (Basin): level &gt; 5.0\n    For node ID 1 (Basin): level &gt; 10.0\n    For node ID 1 (Basin): level &gt; 15.0\n\n   This yielded control state \"out\":\n    For node ID 2 (Pump): flow_rate = 0.0\n    For node ID 3 (Pump): flow_rate = 0.002\n\n1. At 2020-02-08 19:02:21.861000 the control node with ID 7 reached truth state TFF:\n    For node ID 1 (Basin): level &gt; 5.0\n    For node ID 1 (Basin): level &lt; 10.0\n    For node ID 1 (Basin): level &lt; 15.0\n\n   This yielded control state \"none\":\n    For node ID 2 (Pump): flow_rate = 0.0\n    For node ID 3 (Pump): flow_rate = 0.0\n\n2. At 2020-07-05 08:56:10.319000 the control node with ID 7 reached truth state FFF:\n    For node ID 1 (Basin): level &lt; 5.0\n    For node ID 1 (Basin): level &lt; 10.0\n    For node ID 1 (Basin): level &lt; 15.0\n\n   This yielded control state \"in\":\n    For node ID 2 (Pump): flow_rate = 0.002\n    For node ID 3 (Pump): flow_rate = 0.0\n\n3. At 2020-08-11 06:05:15.592000 the control node with ID 7 reached truth state TTF:\n    For node ID 1 (Basin): level &gt; 5.0\n    For node ID 1 (Basin): level &gt; 10.0\n    For node ID 1 (Basin): level &lt; 15.0\n\n   This yielded control state \"none\":\n    For node ID 2 (Pump): flow_rate = 0.0\n    For node ID 3 (Pump): flow_rate = 0.0\n\n\n\nNote that crossing direction specific truth states (containing “U”, “D”) are not present in this overview even though they are part of the control logic. This is because in the control logic for this model these truth states are only used to sustain control states, while the overview only shows changes in control states.\n\n\n4 Model with PID control\nSet up the nodes:\n\nxy = np.array(\n    [\n        (0.0, 0.0),  # 1: FlowBoundary\n        (1.0, 0.0),  # 2: Basin\n        (2.0, 0.5),  # 3: Pump\n        (3.0, 0.0),  # 4: LevelBoundary\n        (1.5, 1.0),  # 5: PidControl\n        (2.0, -0.5),  # 6: outlet\n        (1.5, -1.0),  # 7: PidControl\n    ]\n)\n\nnode_xy = gpd.points_from_xy(x=xy[:, 0], y=xy[:, 1])\n\nnode_type = [\n    \"FlowBoundary\",\n    \"Basin\",\n    \"Pump\",\n    \"LevelBoundary\",\n    \"PidControl\",\n    \"Outlet\",\n    \"PidControl\",\n]\n\n# Make sure the feature id starts at 1: explicitly give an index.\nnode = ribasim.Node(\n    df=gpd.GeoDataFrame(\n        data={\"type\": node_type},\n        index=pd.Index(np.arange(len(xy)) + 1, name=\"fid\"),\n        geometry=node_xy,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup the edges:\n\nfrom_id = np.array([1, 2, 3, 4, 6, 5, 7], dtype=np.int64)\nto_id = np.array([2, 3, 4, 6, 2, 3, 6], dtype=np.int64)\n\nlines = node.geometry_from_connectivity(from_id, to_id)\nedge = ribasim.Edge(\n    df=gpd.GeoDataFrame(\n        data={\n            \"from_node_id\": from_id,\n            \"to_node_id\": to_id,\n            \"edge_type\": 5 * [\"flow\"] + 2 * [\"control\"],\n        },\n        geometry=lines,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup the basins:\n\nprofile = pd.DataFrame(\n    data={\"node_id\": [2, 2], \"level\": [0.0, 1.0], \"area\": [1000.0, 1000.0]}\n)\n\nstatic = pd.DataFrame(\n    data={\n        \"node_id\": [2],\n        \"drainage\": [0.0],\n        \"potential_evaporation\": [0.0],\n        \"infiltration\": [0.0],\n        \"precipitation\": [0.0],\n        \"urban_runoff\": [0.0],\n    }\n)\n\nstate = pd.DataFrame(\n    data={\n        \"node_id\": [2],\n        \"level\": [6.0],\n    }\n)\n\nbasin = ribasim.Basin(profile=profile, static=static, state=state)\n\nSetup the pump:\n\npump = ribasim.Pump(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [3],\n            \"flow_rate\": [0.0],  # Will be overwritten by PID controller\n        }\n    )\n)\n\nSetup the outlet:\n\noutlet = ribasim.Outlet(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [6],\n            \"flow_rate\": [0.0],  # Will be overwritten by PID controller\n        }\n    )\n)\n\nSetup flow boundary:\n\nflow_boundary = ribasim.FlowBoundary(\n    static=pd.DataFrame(data={\"node_id\": [1], \"flow_rate\": [1e-3]})\n)\n\nSetup flow boundary:\n\nlevel_boundary = ribasim.LevelBoundary(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [4],\n            \"level\": [1.0],  # Not relevant\n        }\n    )\n)\n\nSetup PID control:\n\npid_control = ribasim.PidControl(\n    time=pd.DataFrame(\n        data={\n            \"node_id\": 4 * [5, 7],\n            \"time\": [\n                \"2020-01-01 00:00:00\",\n                \"2020-01-01 00:00:00\",\n                \"2020-05-01 00:00:00\",\n                \"2020-05-01 00:00:00\",\n                \"2020-07-01 00:00:00\",\n                \"2020-07-01 00:00:00\",\n                \"2020-12-01 00:00:00\",\n                \"2020-12-01 00:00:00\",\n            ],\n            \"listen_node_id\": 4 * [2, 2],\n            \"target\": [5.0, 5.0, 5.0, 5.0, 7.5, 7.5, 7.5, 7.5],\n            \"proportional\": 4 * [-1e-3, 1e-3],\n            \"integral\": 4 * [-1e-7, 1e-7],\n            \"derivative\": 4 * [0.0, 0.0],\n        }\n    )\n)\n\nNote that the coefficients for the pump and the outlet are equal in magnitude but opposite in sign. This way the pump and the outlet equally work towards the same goal, while having opposite effects on the controlled basin due to their connectivity to this basin.\nSetup a model:\n\nmodel = ribasim.Model(\n    network=ribasim.Network(\n        node=node,\n        edge=edge,\n    ),\n    basin=basin,\n    flow_boundary=flow_boundary,\n    level_boundary=level_boundary,\n    pump=pump,\n    outlet=outlet,\n    pid_control=pid_control,\n    starttime=\"2020-01-01 00:00:00\",\n    endtime=\"2020-12-01 00:00:00\",\n)\n\nLet’s take a look at the model:\n\nmodel.plot()\n\n&lt;Axes: &gt;\n\n\n\n\n\nWrite the model to a TOML and GeoPackage:\n\ndatadir = Path(\"data\")\nmodel.write(datadir / \"pid_control/ribasim.toml\")\n\nPosixPath('data/pid_control/ribasim.toml')\n\n\nNow run the model with ribasim pid_control/ribasim.toml. After running the model, read back the results:\n\nfrom matplotlib.dates import date2num\n\ndf_basin = pd.read_feather(datadir / \"pid_control/results/basin.arrow\")\ndf_basin_wide = df_basin.pivot_table(\n    index=\"time\", columns=\"node_id\", values=[\"storage\", \"level\"]\n)\nax = df_basin_wide[\"level\"].plot()\nax.set_ylabel(\"level [m]\")\n\n# Plot target level\ntarget_levels = model.pid_control.time.df.target.to_numpy()[:4]\ntimes = date2num(model.pid_control.time.df.time)[:4]\nax.plot(times, target_levels, color=\"k\", ls=\":\", label=\"target level\")\npass\n\n\n\n\n\n\n5 Model with allocation\nSetup the nodes:\n\nxy = np.array(\n    [\n        (0.0, 0.0),  # 1: FlowBoundary\n        (1.0, 0.0),  # 2: Basin\n        (1.0, 1.0),  # 3: User\n        (2.0, 0.0),  # 4: LinearResistance\n        (3.0, 0.0),  # 5: Basin\n        (3.0, 1.0),  # 6: User\n        (4.0, 0.0),  # 7: TabulatedRatingCurve\n        (4.5, 0.0),  # 8: FractionalFlow\n        (4.5, 0.5),  # 9: FractionalFlow\n        (5.0, 0.0),  # 10: Terminal\n        (4.5, 0.25),  # 11: DiscreteControl\n        (4.5, 1.0),  # 12: Basin\n        (5.0, 1.0),  # 13: User\n    ]\n)\nnode_xy = gpd.points_from_xy(x=xy[:, 0], y=xy[:, 1])\n\nnode_type = [\n    \"FlowBoundary\",\n    \"Basin\",\n    \"User\",\n    \"LinearResistance\",\n    \"Basin\",\n    \"User\",\n    \"TabulatedRatingCurve\",\n    \"FractionalFlow\",\n    \"FractionalFlow\",\n    \"Terminal\",\n    \"DiscreteControl\",\n    \"Basin\",\n    \"User\",\n]\n\n# All nodes belong to allocation network id 1\nnode = ribasim.Node(\n    df=gpd.GeoDataFrame(\n        data={\"type\": node_type, \"allocation_network_id\": 1},\n        index=pd.Index(np.arange(len(xy)) + 1, name=\"fid\"),\n        geometry=node_xy,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup the edges:\n\nfrom_id = np.array(\n    [1, 2, 2, 4, 5, 5, 7, 3, 6, 7, 8, 9, 12, 13, 11, 11],\n    dtype=np.int64,\n)\nto_id = np.array(\n    [2, 3, 4, 5, 6, 7, 8, 2, 5, 9, 10, 12, 13, 10, 8, 9],\n    dtype=np.int64,\n)\n# Denote the first edge, 1 =&gt; 2, as a source edge for\n# allocation network 1\nallocation_network_id = len(from_id) * [None]\nallocation_network_id[0] = 1\nlines = node.geometry_from_connectivity(from_id, to_id)\nedge = ribasim.Edge(\n    df=gpd.GeoDataFrame(\n        data={\n            \"from_node_id\": from_id,\n            \"to_node_id\": to_id,\n            \"edge_type\": (len(from_id) - 2) * [\"flow\"] + 2 * [\"control\"],\n            \"allocation_network_id\": allocation_network_id,\n        },\n        geometry=lines,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup the basins:\n\nprofile = pd.DataFrame(\n    data={\n        \"node_id\": [2, 2, 5, 5, 12, 12],\n        \"area\": 300_000.0,\n        \"level\": 3 * [0.0, 1.0],\n    }\n)\n\nstatic = pd.DataFrame(\n    data={\n        \"node_id\": [2, 5, 12],\n        \"drainage\": 0.0,\n        \"potential_evaporation\": 0.0,\n        \"infiltration\": 0.0,\n        \"precipitation\": 0.0,\n        \"urban_runoff\": 0.0,\n    }\n)\n\nstate = pd.DataFrame(data={\"node_id\": [2, 5, 12], \"level\": 1.0})\n\nbasin = ribasim.Basin(profile=profile, static=static, state=state)\n\nSetup the flow boundary:\n\nflow_boundary = ribasim.FlowBoundary(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [1],\n            \"flow_rate\": 2.0,\n        }\n    )\n)\n\nSetup the linear resistance:\n\nlinear_resistance = ribasim.LinearResistance(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [4],\n            \"resistance\": 0.06,\n        }\n    )\n)\n\nSetup the tabulated rating curve:\n\ntabulated_rating_curve = ribasim.TabulatedRatingCurve(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": 7,\n            \"level\": [0.0, 0.5, 1.0],\n            \"discharge\": [0.0, 0.0, 2.0],\n        }\n    )\n)\n\nSetup the fractional flow:\n\nfractional_flow = ribasim.FractionalFlow(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [8, 8, 9, 9],\n            \"fraction\": [0.6, 0.9, 0.4, 0.1],\n            \"control_state\": [\"divert\", \"close\", \"divert\", \"close\"],\n        }\n    )\n)\n\nSetup the terminal:\n\nterminal = ribasim.Terminal(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [10],\n        }\n    )\n)\n\nSetup the discrete control:\n\ncondition = pd.DataFrame(\n    data={\n        \"node_id\": [11],\n        \"listen_feature_id\": 5,\n        \"variable\": \"level\",\n        \"greater_than\": 0.52,\n    }\n)\n\nlogic = pd.DataFrame(\n    data={\n        \"node_id\": 11,\n        \"truth_state\": [\"T\", \"F\"],\n        \"control_state\": [\"divert\", \"close\"],\n    }\n)\n\ndiscrete_control = ribasim.DiscreteControl(condition=condition, logic=logic)\n\nSetup the users:\n\nuser = ribasim.User(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [6, 13],\n            \"demand\": [1.5, 1.0],\n            \"return_factor\": 0.0,\n            \"min_level\": -1.0,\n            \"priority\": [1, 3],\n        }\n    ),\n    time=pd.DataFrame(\n        data={\n            \"node_id\": [3, 3, 3, 3],\n            \"demand\": [0.0, 1.0, 1.2, 1.2],\n            \"priority\": [1, 1, 2, 2],\n            \"return_factor\": 0.0,\n            \"min_level\": -1.0,\n            \"time\": 2 * [\"2020-01-01 00:00:00\", \"2020-01-20 00:00:00\"],\n        }\n    ),\n)\n\nSetup the allocation:\n\nallocation = ribasim.Allocation(use_allocation=True, timestep=86400)\n\nSetup a model:\n\nmodel = ribasim.Model(\n    network=ribasim.Network(\n        node=node,\n        edge=edge,\n    ),\n    basin=basin,\n    flow_boundary=flow_boundary,\n    linear_resistance=linear_resistance,\n    tabulated_rating_curve=tabulated_rating_curve,\n    terminal=terminal,\n    user=user,\n    discrete_control=discrete_control,\n    fractional_flow=fractional_flow,\n    allocation=allocation,\n    starttime=\"2020-01-01 00:00:00\",\n    endtime=\"2020-01-20 00:00:00\",\n)\n\nLet’s take a look at the model:\n\nmodel.plot()\n\n&lt;Axes: &gt;\n\n\n\n\n\nWrite the model to a TOML and GeoPackage:\n\ndatadir = Path(\"data\")\nmodel.write(datadir / \"allocation_example/ribasim.toml\")\n\nPosixPath('data/allocation_example/ribasim.toml')\n\n\nNow run the model with ribasim allocation_example/ribasim.toml. After running the model, read back the results:\n\nimport matplotlib.ticker as plticker\n\ndf_allocation = pd.read_feather(datadir / \"allocation_example/results/allocation.arrow\")\ndf_allocation_wide = df_allocation.pivot_table(\n    index=\"time\",\n    columns=[\"user_node_id\", \"priority\"],\n    values=[\"demand\", \"allocated\", \"abstracted\"],\n)\ndf_allocation_wide = df_allocation_wide.loc[:, (df_allocation_wide != 0).any(axis=0)]\n\nfig, axs = plt.subplots(1, 3, figsize=(8, 5))\nfig.suptitle(f\"Objective type: {model.allocation.objective_type}\", fontweight=\"bold\")\n\ndf_allocation_wide[\"demand\"].plot(ax=axs[0], ls=\":\")\ndf_allocation_wide[\"allocated\"].plot(ax=axs[1], ls=\"--\")\ndf_allocation_wide[\"abstracted\"].plot(ax=axs[2])\n\nfig.tight_layout()\nloc = plticker.MultipleLocator(2)\n\naxs[0].set_ylabel(\"level [m]\")\n\nfor ax, title in zip(axs, [\"Demand\", \"Allocated\", \"Abstracted\"]):\n    ax.set_title(title)\n    ax.set_ylim(0.0, 1.6)\n    ax.xaxis.set_major_locator(loc)\n\n\n\n\nSome things to note about this plot:\n\nAbstraction behaves somewhat erratically at the start of the simulation. This is because allocation is based on flows computed in the physical layer, and at the start of the simulation these are not known yet.\nAlthough there is a plotted line for abstraction per priority, abstraction is actually accumulated over all priorities per user.\n\n\ndf_basin = pd.read_feather(datadir / \"allocation_example/results/basin.arrow\")\ndf_basin_wide = df_basin.pivot_table(\n    index=\"time\", columns=\"node_id\", values=[\"storage\", \"level\"]\n)\n\nax = df_basin_wide[\"level\"].plot()\nax.set_title(\"Basin levels\")\nax.set_ylabel(\"level [m]\")\n\nText(0, 0.5, 'level [m]')"
+    "text": "Ribasim developers use the following models in its testbench and in order to test new features.\n\n\nCode\nimport ribasim_testmodels\nimport matplotlib.pyplot as plt\n\nfor model_name, model_constructor in ribasim_testmodels.constructors.items():\n    if model_name.startswith(\"invalid\"):\n        continue\n\n    model = model_constructor()\n    fig, ax = plt.subplots()\n    model.plot(ax)\n    ax.set_title(label=model_name, loc=\"left\")\n    fig.text(0, 1, model_constructor.__doc__)\n    fig.tight_layout()\n    plt.show()\n    plt.close(fig)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n/home/runner/work/Ribasim/Ribasim/python/ribasim/ribasim/geometry/edge.py:77: UserWarning:\n\nThe GeoDataFrame you are attempting to plot is empty. Nothing has been displayed."
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+    "text": "The Ribasim Python package (named ribasim) aims to make it easy to build, update and analyze Ribasim models programmatically.\nThe Ribasim QGIS plugin allows users to construct a model from scratch without programming. For specific tasks, like adding observed rainfall timeseries, it can be faster to use Python instead.\nOne can also use Ribasim Python to build entire models from base data, such that your model setup is fully reproducible.\nThe package is registered in PyPI and can therefore be installed with pip:\npip install ribasim\nFor wheel (.whl) downloads, including nightly builds, see the download section. After downloading wheels can be installed by referring to the correct path:\npip install path/to/ribasim-*.whl\nFor documentation please see the examples and API reference."
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+    "text": "Node()\nThe Ribasim nodes as Point geometries.\n\n\n\n\n\nName\nDescription\n\n\n\n\nconnectivity_from_geometry\nDerive from_node_id and to_node_id for every edge in lines. LineStrings\n\n\ngeometry_from_connectivity\nCreate edge shapely geometries from connectivities.\n\n\nplot\nPlot the nodes. Each node type is given a separate marker.\n\n\n\n\n\nNode.connectivity_from_geometry(lines)\nDerive from_node_id and to_node_id for every edge in lines. LineStrings may be used to connect multiple nodes in a sequence, but every linestring vertex must also a node.\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nnode\nNode\n\nrequired\n\n\nlines\nnp.ndarray\nArray of shapely linestrings.\nrequired\n\n\n\n\n\n\n\n\n\nType\nDescription\n\n\n\n\nnp.ndarray of int\n\n\n\nnp.ndarray of int\n\n\n\n\n\n\n\n\nNode.geometry_from_connectivity(from_id, to_id)\nCreate edge shapely geometries from connectivities.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nnode\nRibasim.Node\n\nrequired\n\n\nfrom_id\nSequence[int]\nFirst node of every edge.\nrequired\n\n\nto_id\nSequence[int]\nSecond node of every edge.\nrequired\n\n\n\n\n\n\n\n\n\nType\nDescription\n\n\n\n\nnp.ndarray\nArray of shapely LineStrings.\n\n\n\n\n\n\n\nNode.plot(ax=None, zorder=None)\nPlot the nodes. Each node type is given a separate marker.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nax\nOptional\nThe axis on which the nodes will be plotted.\nNone\n\n\n\n\n\n\n\n\n\nType\nDescription\n\n\n\n\nNone"
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+    "text": "Name\nDescription\n\n\n\n\nconnectivity_from_geometry\nDerive from_node_id and to_node_id for every edge in lines. LineStrings\n\n\ngeometry_from_connectivity\nCreate edge shapely geometries from connectivities.\n\n\nplot\nPlot the nodes. Each node type is given a separate marker.\n\n\n\n\n\nNode.connectivity_from_geometry(lines)\nDerive from_node_id and to_node_id for every edge in lines. LineStrings may be used to connect multiple nodes in a sequence, but every linestring vertex must also a node.\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nnode\nNode\n\nrequired\n\n\nlines\nnp.ndarray\nArray of shapely linestrings.\nrequired\n\n\n\n\n\n\n\n\n\nType\nDescription\n\n\n\n\nnp.ndarray of int\n\n\n\nnp.ndarray of int\n\n\n\n\n\n\n\n\nNode.geometry_from_connectivity(from_id, to_id)\nCreate edge shapely geometries from connectivities.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nnode\nRibasim.Node\n\nrequired\n\n\nfrom_id\nSequence[int]\nFirst node of every edge.\nrequired\n\n\nto_id\nSequence[int]\nSecond node of every edge.\nrequired\n\n\n\n\n\n\n\n\n\nType\nDescription\n\n\n\n\nnp.ndarray\nArray of shapely LineStrings.\n\n\n\n\n\n\n\nNode.plot(ax=None, zorder=None)\nPlot the nodes. Each node type is given a separate marker.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nax\nOptional\nThe axis on which the nodes will be plotted.\nNone\n\n\n\n\n\n\n\n\n\nType\nDescription\n\n\n\n\nNone"
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-    "text": "Model()\nA full Ribasim model schematisation with all input.\nRibasim model containing the location of the nodes, the edges between the nodes, and the node parametrization.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nstarttime\ndatetime.datetime\nStarting time of the simulation.\nrequired\n\n\nendtime\ndatetime.datetime\nEnd time of the simulation.\nrequired\n\n\nupdate_timestep\n\nThe output time step of the simulation in seconds (default of 1 day)\nrequired\n\n\ninput_dir\n\nThe directory of the input files.\nrequired\n\n\nresults_dir\n\nThe directory of the results files.\nrequired\n\n\nnetwork\n\nClass containing the topology (nodes and edges) of the model.\nrequired\n\n\nresults\n\nResults configuration options.\nrequired\n\n\nsolver\n\nSolver configuration options.\nrequired\n\n\nlogging\n\nLogging configuration options.\nrequired\n\n\nallocation\n\nThe allocation configuration.\nrequired\n\n\nbasin\nBasin\nThe waterbodies.\nrequired\n\n\nfractional_flow\nFractionalFlow\nSplit flows into fractions.\nrequired\n\n\nlevel_boundary\nLevelBoundary\nBoundary condition specifying the water level.\nrequired\n\n\nflow_boundary\nFlowBoundary\nBoundary conditions specifying the flow.\nrequired\n\n\nlinear_resistance\n\nLinear flow resistance.\nrequired\n\n\nmanning_resistance\nManningResistance\nFlow resistance based on the Manning formula.\nrequired\n\n\ntabulated_rating_curve\nTabulatedRatingCurve\nTabulated rating curve describing flow based on the upstream water level.\nrequired\n\n\npump\nPump\nPrescribed flow rate from one basin to the other.\nrequired\n\n\noutlet\nOutlet\nPrescribed flow rate from one basin to the other.\nrequired\n\n\nterminal\nTerminal\nWater sink without state or properties.\nrequired\n\n\ndiscrete_control\nDiscreteControl\nDiscrete control logic.\nrequired\n\n\npid_control\nPidControl\nPID controller attempting to set the level of a basin to a desired value using a pump/outlet.\nrequired\n\n\nuser\nUser\nUser node type with demand and priority.\nrequired\n\n\n\n\n\n\n\n\n\nName\nDescription\n\n\n\n\nplot\nPlot the nodes and edges of the model.\n\n\nread\nRead model from TOML file.\n\n\nvalidate_model\nValidate the model.\n\n\nvalidate_model_node_field_ids\nCheck whether the node IDs of the node_type fields are valid.\n\n\nvalidate_model_node_ids\nCheck whether the node IDs in the data tables correspond to the node IDs in the network.\n\n\nwrite\nWrite the contents of the model to disk and save it as a TOML configuration file.\n\n\n\n\n\nModel.plot(ax=None)\nPlot the nodes and edges of the model.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nax\nmatplotlib.pyplot.Artist\nAxes on which to draw the plot.\nNone\n\n\n\n\n\n\n\n\n\nType\nDescription\n\n\n\n\nmatplotlib.pyplot.Artist\n\n\n\n\n\n\n\n\nModel.read(filepath)\nRead model from TOML file.\n\n\n\nModel.validate_model()\nValidate the model.\nChecks: - Whether the node IDs of the node_type fields are valid - Whether the node IDs in the node field correspond to the node IDs on the node type fields\n\n\n\nModel.validate_model_node_field_ids()\nCheck whether the node IDs of the node_type fields are valid.\n\n\n\nModel.validate_model_node_ids()\nCheck whether the node IDs in the data tables correspond to the node IDs in the network.\n\n\n\nModel.write(filepath)\nWrite the contents of the model to disk and save it as a TOML configuration file.\nIf filepath.parent does not exist, it is created before writing.\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nfilepath\nPath | str\n\nrequired"
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-    "text": "Name\nType\nDescription\nDefault\n\n\n\n\nstarttime\ndatetime.datetime\nStarting time of the simulation.\nrequired\n\n\nendtime\ndatetime.datetime\nEnd time of the simulation.\nrequired\n\n\nupdate_timestep\n\nThe output time step of the simulation in seconds (default of 1 day)\nrequired\n\n\ninput_dir\n\nThe directory of the input files.\nrequired\n\n\nresults_dir\n\nThe directory of the results files.\nrequired\n\n\nnetwork\n\nClass containing the topology (nodes and edges) of the model.\nrequired\n\n\nresults\n\nResults configuration options.\nrequired\n\n\nsolver\n\nSolver configuration options.\nrequired\n\n\nlogging\n\nLogging configuration options.\nrequired\n\n\nallocation\n\nThe allocation configuration.\nrequired\n\n\nbasin\nBasin\nThe waterbodies.\nrequired\n\n\nfractional_flow\nFractionalFlow\nSplit flows into fractions.\nrequired\n\n\nlevel_boundary\nLevelBoundary\nBoundary condition specifying the water level.\nrequired\n\n\nflow_boundary\nFlowBoundary\nBoundary conditions specifying the flow.\nrequired\n\n\nlinear_resistance\n\nLinear flow resistance.\nrequired\n\n\nmanning_resistance\nManningResistance\nFlow resistance based on the Manning formula.\nrequired\n\n\ntabulated_rating_curve\nTabulatedRatingCurve\nTabulated rating curve describing flow based on the upstream water level.\nrequired\n\n\npump\nPump\nPrescribed flow rate from one basin to the other.\nrequired\n\n\noutlet\nOutlet\nPrescribed flow rate from one basin to the other.\nrequired\n\n\nterminal\nTerminal\nWater sink without state or properties.\nrequired\n\n\ndiscrete_control\nDiscreteControl\nDiscrete control logic.\nrequired\n\n\npid_control\nPidControl\nPID controller attempting to set the level of a basin to a desired value using a pump/outlet.\nrequired\n\n\nuser\nUser\nUser node type with demand and priority.\nrequired"
+    "text": "The Model class represents an entire Ribasim model.\n\n\n\nModel\nA full Ribasim model schematisation with all input.\n\n\n\n\n\n\nThe Node and Edge database layers define the network layout.\n\n\n\nNode\nThe Ribasim nodes as Point geometries.\n\n\nEdge\nDefines the connections between nodes.\n\n\n\n\n\n\nAvailable node types to model different situations.\n\n\n\nBasin\n\n\n\nFractionalFlow\n\n\n\nTabulatedRatingCurve\n\n\n\nPump\n\n\n\nOutlet\n\n\n\nUser\n\n\n\nLevelBoundary\n\n\n\nFlowBoundary\n\n\n\nLinearResistance\n\n\n\nManningResistance\n\n\n\nTerminal\n\n\n\nDiscreteControl\n\n\n\nPidControl"
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-    "text": "Name\nDescription\n\n\n\n\nplot\nPlot the nodes and edges of the model.\n\n\nread\nRead model from TOML file.\n\n\nvalidate_model\nValidate the model.\n\n\nvalidate_model_node_field_ids\nCheck whether the node IDs of the node_type fields are valid.\n\n\nvalidate_model_node_ids\nCheck whether the node IDs in the data tables correspond to the node IDs in the network.\n\n\nwrite\nWrite the contents of the model to disk and save it as a TOML configuration file.\n\n\n\n\n\nModel.plot(ax=None)\nPlot the nodes and edges of the model.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nax\nmatplotlib.pyplot.Artist\nAxes on which to draw the plot.\nNone\n\n\n\n\n\n\n\n\n\nType\nDescription\n\n\n\n\nmatplotlib.pyplot.Artist\n\n\n\n\n\n\n\n\nModel.read(filepath)\nRead model from TOML file.\n\n\n\nModel.validate_model()\nValidate the model.\nChecks: - Whether the node IDs of the node_type fields are valid - Whether the node IDs in the node field correspond to the node IDs on the node type fields\n\n\n\nModel.validate_model_node_field_ids()\nCheck whether the node IDs of the node_type fields are valid.\n\n\n\nModel.validate_model_node_ids()\nCheck whether the node IDs in the data tables correspond to the node IDs in the network.\n\n\n\nModel.write(filepath)\nWrite the contents of the model to disk and save it as a TOML configuration file.\nIf filepath.parent does not exist, it is created before writing.\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nfilepath\nPath | str\n\nrequired"
+    "text": "The Model class represents an entire Ribasim model.\n\n\n\nModel\nA full Ribasim model schematisation with all input."
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-    "text": "1 PidControl\nPidControl()"
+    "text": "The Node and Edge database layers define the network layout.\n\n\n\nNode\nThe Ribasim nodes as Point geometries.\n\n\nEdge\nDefines the connections between nodes."
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-    "text": "1 LinearResistance\nLinearResistance()"
+    "text": "Available node types to model different situations.\n\n\n\nBasin\n\n\n\nFractionalFlow\n\n\n\nTabulatedRatingCurve\n\n\n\nPump\n\n\n\nOutlet\n\n\n\nUser\n\n\n\nLevelBoundary\n\n\n\nFlowBoundary\n\n\n\nLinearResistance\n\n\n\nManningResistance\n\n\n\nTerminal\n\n\n\nDiscreteControl\n\n\n\nPidControl"
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-    "text": "Ribasim has been designed to provide a computationally efficient representation of surface water for MODFLOW 6. It does so by connecting to basic MODFLOW 6 boundary conditions: the river and drainage packages.\nRibasim connects to MODFLOW 6 via the Basic Model Interface (BMI) and Extended Model Interface (XMI) (Hughes et al. 2022). BMI describes the interface to initialize a model, get values from its memory, run a timestep, etc. XMI extends this interface to allow much finer control into MODFLOW 6’s solution procedures. We have written a Julia package (Deltares 2022) which implements this interface for the Julia programming language. In coupling, Ribasim uses this interface to get the head values, the boundary condition water levels, and the budgets term of the MODFLOW 6 groundwater model while MODFLOW 6 is running.\nAdditionally, links can be made with other (BMI/XMI-compliant) processes and models. One example of such a link is using the surface runoff and the agricultural irrigation demand calculated by an unsaturated zone model; in the Netherlands Hydrological Instrument MetaSWAP provides this demand."
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-    "text": "1.1 Drainage\nThe drainage package can be simulated to agricultural drains, ditches, or draining streams. The amount of water removed from the aquifer is proportional to the difference between the groundwater head and the drainage elevation. Drainage only occurs when the head is larger than the elevation; this boundary condition does not allow infiltration into the groundwater.\n\\[\nQ_{drain} = \\left\\{\n    \\begin{array}{ c l }\n        C_{drain} (\\phi - h_{drain}) & \\quad \\textrm{if } \\phi &gt; h_{drain} \\\\\n        0                            & \\quad \\textrm{otherwise}\n     \\end{array}\n\\right.\n\\]"
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-    "text": "1.2 River\nThe river package can both drain the groundwater, or infiltrate surface water to the groundwater. It limits the amount of water that can infiltrate when the groundwater head falls below the river bottom, in which cases it assumes atmospheric pressure conditions underneath the surface water.\n\\[\nQ_{river} = \\left\\{\n    \\begin{array}{ c l }\n        C_{river} (\\phi - h_{river}) & \\quad \\textrm{if } \\phi &gt; b_{river} \\\\\n        C_{river} (h_{river} - b_{river}) & \\quad \\textrm{if } \\phi &lt;= b_{river}\n     \\end{array}\n\\right.\n\\]\nIn the Netherlands, it is somewhat common to make a distinction between the drainage and infiltration conductance of surface waters. Drainage conductance is often larger than the infiltration conductance due to clogging processes, seepage through sides of the ditches, less contracted flow lines, etc.\n\\[\nQ_{river} = \\left\\{\n    \\begin{array}{ c l }\n        C_{river,drn} (\\phi - h_{river}) & \\quad \\textrm{if } \\phi &gt; h_{river} \\\\\n        C_{river,inf} (\\phi - h_{river}) & \\quad \\textrm{if } \\phi &lt;= h_{river} \\\\\n        C_{river,inf} (h_{river} - b_{river}) & \\quad \\textrm{if } \\phi &lt;= b_{river}\n     \\end{array}\n\\right.\n\\]\nMODFLOW 6 does not support this (currently), but an identical effect may be achieved by “stacking” a drainage package on top of a river package with these values:\n\\[\n\\begin{array}{ c l }\n  h_{drain} = h_{river} \\\\\n  C_{drain} = C_{river,drn} - C_{river,inf}\n\\end{array}\n\\]"
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+    "text": "In our test cases, we will work with the Dutch national groundwater model (LHM). For testing, we simplify the top boundary conditions to just three surface water “systems”, from large to small:\n\nPrimary\nSecondary\nTertiary\n\nThese systems are separated in the groundwater model schematization due to the relatively small size of the surface waters (several meters in width) in comparison with relatively coarse cells of the groundwater model (250 m): most cells in the LHM contain more than one surface water, and are included via representative parameters which take the physical scaling into account. In case of sufficiently small cell sizes, no overlap occurs and all surface waters can be represented in a single grid.\nRibasim has no knowledge of these systems unless explicitly separated into different (sub-)basins. In the examples below, these three systems are represented by one basin with a single volume. For the purposes of testing, we have not yet created empirical volume-level relationships for the surface water of every cell extracted from a hydraulic model. Instead, we have chosen an (over)simplified parametrization of the hydraulic properties, which makes it easy to verify the behavior of Ribasim and the coupling procedures:\n\nPrimary, secondary, and tertiary systems have a rectangular profile: the area of the surface water does not change with water level or volume.\nWater depth is constant for a system within a basin.\nWater depth increases linearly with volume. (This follows from 1.)\nWater depth is distributed across the systems in a geometric progression: when the tertiary system contains 0.1 m of water, the secondary system contains 0.2 m, and the primary system contains 0.4 m.\nWater depth is 0.0 m for all systems when basin volume is 0.0. (This follows from 4.)\nThe distribution of water occurs according to the surface water area (width times length) used for the LHM parametrization of river bed conductance.\n\nFor freely draining basins, a simplified storage-discharge relationship has been derived as follows:\n\nThe area of the basin polygon has been multiplied by 1 mm/d (roughly the average precipitation excess in the Netherlands). This yields a “normative discharge”.\nA corresponding normative volume has been chosen, corresponding with water depths of 0.4, 0.2, and 0.1 m for the primary, secondary, and tertiary surface waters respectively.\nA dead storage volume has been chosen, corresponding with water depths of 0.2, 0.1, and 0.05 m for the primary, secondary, and tertiary surface waters respectively. The basin only starts discharging when the storage volume exceeds this value.\n\n\n\n\n\n\n\nNote\n\n\n\nRibasim is not limited to such oversimplified parametrization! Ribasim uses tabulations and therefore supports arbitrary (piecewise linear) volume-depth and volume-discharge relationships.\n\n\nA visual representation of this simplified conceptual schematization is given in Figure 1 and Figure 2.\n\n\n\nFigure 1: Distribution of water depths over the primary, secondary, and tertiary system.\n\n\n\n\n\nFigure 2: Discharge as a function of basin storage volume.\n\n\nAn example of the resulting parameters for a single cell is shown in Table 1. The first row shows the water levels when the basin is empty. The level for primary, secondary, and tertiary are equal to the bottom elevation of the surface waters. The second row shows the volume and levels for water depths of 0.4, 0.2, and 0.1 m. The third row shows the volume and levels for a tenfold larger volume. This results in implausible water levels with depths of 4.0, 2.0 and 1.0 m; the water level in the primary system is over two meters higher than in the tertiary system. In reality, the surface waters would overflow and surface ponding would occur; this mechanism is ignored in the test cases for the sake of simplicity.\n\n\nTable 1: Volume-level table for a single cell in the Hupsel basin.\n\n\nVolume (m3)\nPrimary (m NAP)\nSecondary (m NAP)\nTertiary (m NAP)\n\n\n\n\n0.0\n25.65\n25.83\n26.60\n\n\n6843.1\n26.05\n26.03\n26.70\n\n\n68431.0\n29.65\n27.83\n27.60\n\n\n\n\nFigure 3 shows the volume of the first row of the cell based input for the primary system. Symbology is set to unique values. While water levels differ per cell in this parametrization, the “normative volume” defined above is shared by all cells in a basin.\n\n\n\nFigure 3: Basin normative volume of the primary system.\n\n\nFigure 3 shows the water level corresponding to the normative storage volume based input for the primary system (it corresponds to the value shown in the first row of the primary column in Table 1). We see a clear gradient from west to east: as our simplified parametrization assumes a constant water depth for all cells in a single system, water levels spatially fall and rise with the bottom elevation.\n\n\n\nFigure 4: Water level corresponding to the normative basin volume of the primary system."
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-    "text": "2.1 Numerical solution in MODFLOW\nMODFLOW uses a backward-in-time implicit solution scheme. This creates a large system of equations (a water balance for every cell), which it solves by repeatedly solving a linearized system of equations instead. In matrix form, this system of equations is expressed by:\n\\[\n\\mathbf{Ax} = \\mathbf{b}\n\\]\nWhere \\(\\mathbf{x}\\) is a vector containing the head of every cell.\nFor the boundary conditions, this requires linearization of the flow equations. Flow from outside of the aquifer (cell) may be represented by:\n\\[\na = p\\phi + q\n\\]\n(Equation 2-6 in the MODFLOW 6 documentation (Langevin et al. 2017).)\nFor e.g. a draining boundary condition, the flow is head dependent:\n\\[\na = C(h - \\phi) = -C\\phi + Ch\n\\]\nWith \\(C\\) the conductance, \\(h\\) the boundary head or elevation, and \\(\\phi\\) the groundwater head.\nIn MODFLOW’s internal formulation, the term in \\(\\mathbf{A}\\) is called “coefficient of head” or hcof. Terms in \\(\\mathbf{b}\\) are called “right hand side” or rhs. We can separate the equation above:\n\\[\n\\begin{aligned}\np = \\text{hcof} = -C \\\\\nq = \\textrm{rhs} = -Ch \\\\\na = -C\\phi + Ch = \\text{hcof} * \\phi - \\text{rhs}\n\\end{aligned}\n\\]\nFor every boundary condition, MODFLOW 6 stores the hcof and rhs values. This makes it quite convenient for us to compute the water budget for every boundary condition: we simply multiply the hcof value by the head of the cell and subtract the rhs.\nNote that hcof may have a value of 0! For example, when for a river boundary the \\(\\phi &lt;= b_{river}\\) condition occurs, the flow into the cell is controlled only by \\(h_{river}\\) and \\(b_{river}\\) (equal to recharge for the linear solution)."
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+    "text": "In our test cases, we will work with the Dutch national groundwater model (LHM). For testing, we simplify the top boundary conditions to just three surface water “systems”, from large to small:\n\nPrimary\nSecondary\nTertiary\n\nThese systems are separated in the groundwater model schematization due to the relatively small size of the surface waters (several meters in width) in comparison with relatively coarse cells of the groundwater model (250 m): most cells in the LHM contain more than one surface water, and are included via representative parameters which take the physical scaling into account. In case of sufficiently small cell sizes, no overlap occurs and all surface waters can be represented in a single grid.\nRibasim has no knowledge of these systems unless explicitly separated into different (sub-)basins. In the examples below, these three systems are represented by one basin with a single volume. For the purposes of testing, we have not yet created empirical volume-level relationships for the surface water of every cell extracted from a hydraulic model. Instead, we have chosen an (over)simplified parametrization of the hydraulic properties, which makes it easy to verify the behavior of Ribasim and the coupling procedures:\n\nPrimary, secondary, and tertiary systems have a rectangular profile: the area of the surface water does not change with water level or volume.\nWater depth is constant for a system within a basin.\nWater depth increases linearly with volume. (This follows from 1.)\nWater depth is distributed across the systems in a geometric progression: when the tertiary system contains 0.1 m of water, the secondary system contains 0.2 m, and the primary system contains 0.4 m.\nWater depth is 0.0 m for all systems when basin volume is 0.0. (This follows from 4.)\nThe distribution of water occurs according to the surface water area (width times length) used for the LHM parametrization of river bed conductance.\n\nFor freely draining basins, a simplified storage-discharge relationship has been derived as follows:\n\nThe area of the basin polygon has been multiplied by 1 mm/d (roughly the average precipitation excess in the Netherlands). This yields a “normative discharge”.\nA corresponding normative volume has been chosen, corresponding with water depths of 0.4, 0.2, and 0.1 m for the primary, secondary, and tertiary surface waters respectively.\nA dead storage volume has been chosen, corresponding with water depths of 0.2, 0.1, and 0.05 m for the primary, secondary, and tertiary surface waters respectively. The basin only starts discharging when the storage volume exceeds this value.\n\n\n\n\n\n\n\nNote\n\n\n\nRibasim is not limited to such oversimplified parametrization! Ribasim uses tabulations and therefore supports arbitrary (piecewise linear) volume-depth and volume-discharge relationships.\n\n\nA visual representation of this simplified conceptual schematization is given in Figure 1 and Figure 2.\n\n\n\nFigure 1: Distribution of water depths over the primary, secondary, and tertiary system.\n\n\n\n\n\nFigure 2: Discharge as a function of basin storage volume.\n\n\nAn example of the resulting parameters for a single cell is shown in Table 1. The first row shows the water levels when the basin is empty. The level for primary, secondary, and tertiary are equal to the bottom elevation of the surface waters. The second row shows the volume and levels for water depths of 0.4, 0.2, and 0.1 m. The third row shows the volume and levels for a tenfold larger volume. This results in implausible water levels with depths of 4.0, 2.0 and 1.0 m; the water level in the primary system is over two meters higher than in the tertiary system. In reality, the surface waters would overflow and surface ponding would occur; this mechanism is ignored in the test cases for the sake of simplicity.\n\n\nTable 1: Volume-level table for a single cell in the Hupsel basin.\n\n\nVolume (m3)\nPrimary (m NAP)\nSecondary (m NAP)\nTertiary (m NAP)\n\n\n\n\n0.0\n25.65\n25.83\n26.60\n\n\n6843.1\n26.05\n26.03\n26.70\n\n\n68431.0\n29.65\n27.83\n27.60\n\n\n\n\nFigure 3 shows the volume of the first row of the cell based input for the primary system. Symbology is set to unique values. While water levels differ per cell in this parametrization, the “normative volume” defined above is shared by all cells in a basin.\n\n\n\nFigure 3: Basin normative volume of the primary system.\n\n\nFigure 3 shows the water level corresponding to the normative storage volume based input for the primary system (it corresponds to the value shown in the first row of the primary column in Table 1). We see a clear gradient from west to east: as our simplified parametrization assumes a constant water depth for all cells in a single system, water levels spatially fall and rise with the bottom elevation.\n\n\n\nFigure 4: Water level corresponding to the normative basin volume of the primary system."
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-    "text": "2.2 Sequential coupled solution\nA coupled run stars by initializing both models and creating the exchange information: which MODFLOW 6 boundary condition is connected to which Ribasim basin. While the model is running, the model proceeds through time as follows:\n\nRibasim solves the equations on a basin level; this occurs with adaptive timestepping via ModelingToolkit.\nAt a specified time (in accordance with the MODFLOW 6 time discretization), the volumes are converted to MODFLOW 6 boundary condition levels using a Callback function.\nMODFLOW 6 runs a timestep.\nThe drainage and infiltration budgets are computed from MODFLOW 6 using the equations described above and aggregated per basin.\nThe aggregated values are set as Ribasim boundary conditions, and Ribasim solves until the next preset exchange time.\n\nThese steps run until the final timestep is finished."
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+    "text": "2 Example: Configuration\nAn example of the MODFLOW 6 section of TOML configuration required for a coupled run can be seen below:\n[modflow]\nsimulation = \"../data/hupsel/mfsim.nam\"\nmode = \"sequential\"\ntimestep = 86400.0\n\n[modflow.models]\n\n[modflow.models.gwf]\ntype = \"gwf\"\ndataset = \"../data/volume_level_profile-hupsel.nc\"\nbasins = \"basin_id\"\n\n[[modflow.models.gwf.bounds]]\nriver = \"RIV_P\"\ndrain = \"DRN_P\"\nprofile = \"profile_primary\"\n\n[[modflow.models.gwf.bounds]]\nriver = \"RIV_S\"\ndrain = \"DRN_S\"\nprofile = \"profile_secondary\"\n\n[[modflow.models.gwf.bounds]]\ndrain = \"DRN_T\"\nprofile = \"profile_tertiary\"\nThe section starts by stating the path to the MODFLOW 6 simulation name file (simulation). The next section contains the information regarding the MODFLOW 6 model(s) to couple to Ribasim’s basins. Per model, a path to the coupling parameter dataset is provided (dataset), along with the variable to use as the basin identification number (basins). Next, for every boundary condition that should be coupled to Ribasim, the package names (river, drain) used by MODFLOW 6 must be specified (as we look for these names in the MODFLOW 6 memory), along with the name of the variable in the coupling dataset which provides the volume-level relationship (profile).\nAs can be seen in the example, the coupling mechanism supports coupling of:\n\nA single drainage package (drain entry).\nA single river package (river entry).\nA combination of river and drainage package (when infiltration conductance does not equal drainage conductance) both (river and drain entry)."
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-    "text": "2.3 Iterative coupled solution\n\n\n\n\n\n\nNote\n\n\n\nWe have not implemented an iterative coupled solution yet. The section below describes an approach.\n\n\nThe simplest form of a iterative solution occurs as follows:\n\nMODFLOW 6 computes drainage and infiltration flows.\nRibasim uses these flows to compute a storage volume for the basin.\nThe volume is translated to a water level for every MODFLOW 6 boundary condition in the basins.\nMODFLOW 6 recomputes drainage and infiltration flows with the updated water levels, etc.\n\nSuch a scheme is not maximally efficient: the discharge and infiltration terms are not constant, but are driven by a head difference. This head difference depends on the level of the boundary conditions and head of every cell of the groundwater model. If the surface waters of a basin empty, the water level will decrease and drainage and infiltration flows will change. Ideally, we can provide Ribasim with more information, so that it may estimate drainage and infiltration terms better.\nAs groundwater flow is often (approximately) linear, we can use linearization to more efficiently compute the flow from Ribasim’s side as well. In the iterative coupled solution, we are solving both MODFLOW 6 and Ribasim repeatedly, until they produce same drainage or infiltration (approximately). One of Ribasim’s basins contains many MODFLOW cells with boundary conditions. We could add every boundary condition to Ribasim’s equations, but this is costly and cumbersome. Fortunately, linearization allows us to “stack” (superpose) all the different boundary conditions into a single, simple equation. In linear form, every equation takes the form of:\n\\[\na = ph + q\n\\]\nNote the \\(h\\) rather than \\(\\phi\\), we are formulating from Ribasim’s perspective! We can sum all coefficients for p and q to provide a linear groundwater response to Ribasim.\n\n2.3.1 Drainage\nFrom Ribasim’s perspective, the groundwater head is constant given a timestep, so that:\n\\[\\begin{align}\np = -C \\\\\nq = -C\\phi\n\\end{align}\\]\nWhen the head falls below the drainage elevation, the coefficients are 0.\n\n\n2.3.2 River\nFrom Ribasim’s perspective, infiltration is never limited when the head falls below the bottom:\n\\[\\begin{align}\np = -C \\\\\nq = -Cb\n\\end{align}\\]\nOtherwise, infiltration and drainage occur with the same equation as for the drainage package:\n\\[\\begin{align}\np = -C \\\\\nq = -C\\phi\n\\end{align}\\]"
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+    "section": "3 Test case: Hupsel",
+    "text": "3 Test case: Hupsel\nTo test the coupling, the following simulations have been setup and run:\n\nA standalone MODFLOW 6 run of sequential steady-states (i.e. no storage) with differing groundwater recharge values.\nA coupled run where the MODFLOW 6 stages are updated by the Ribasim coupler process, but without Ribasim. This results in volumes of 0.0, so all MODFLOW 6 water levels are set equal to bed elevation.\nA coupled run where the water levels are updated by Ribasim.\n\nFrom these tests, we expect the following behavior:\n\nDrainage terms should remain largely the same when the water level is lowered in a steady-state: the amount of recharge is fixed, and this is locally drained.\nIn case of negative recharge (evapotranspiration), infiltration occurs in the surface waters. Infiltration should be zero when the basin volume is 0.\n\n\n\n\nFigure 5: Water balance of the MODFLOW 6 boundary conditions for the Hupsel basin for a standalone MODFLOW 6 run. The four sequential steady states (01, 02, 03, 04) use net groundwater recharge values of 1.0, 0.5, -0.05 and -0.1 mm/d.\n\n\nFigure 5 shows the water balance of steady-state for submodel of the LHM that has been by selecting the cells belonging to the district containing the Hupsel catch, the Berkel.\nThe Hupsel basin show the expected behavior: for a net groundwater recharge of 1.0 mm/d, most is precipitation with a minor part lateral inflow from higher areas. In terms of outgoing flows, most of the precipitation ends up in the surface water, primarily in the many ditches of the tertiary system. Only a relatively small part of the water leaves the basin via the groundwater. Interbasin flows through the groundwater form such a minor role, as the aquifer is thin and transmissivity is limited.\nReducing groundwater recharge to 0.5 mm/d reduces all flows, with the tertiary system playing a less dominant role, relatively speaking: as its elevation is the highest compared to the primary and secondary system, the head difference is reduced strongest for the tertiary system.\nWith evapotranspiration (ET) excess (-0.05 and 0.1 mm/d; low values are chosen here since most ET would be drawn from storage, which is not available in a steady-state model), the surface waters provide mostly inflow, and recharge is a negative term. In this case, the secondary system provides a small amount of infiltration; most of the water is drawn from the surroundings instead.\n\n\n\nFigure 6: Water balance of the MODFLOW 6 boundary conditions for the Hupsel basin for a zero volume run. The four sequential steady states (01, 02, 03, 04) use net groundwater recharge values of 1.0, 0.5, -0.05 and -0.1 mm/d.\n\n\nFigure 6 shows the same model, with 0-basin volume which causes water levels to be set equal to bed elevation. Consequently, primary and secondary outflow terms are larger for positive groundwater recharge as they drain at a lower level and intercept the water before the tertiary system does. Secondly, with negative groundwater recharge, no infiltration occurs and the water is drawn from the surroundings instead. This shows the coupling mechanism adjusting MODFLOW 6 water levels successfully."
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-    "text": "3.1 Parametrization\nIn coupling Ribasim to MODFLOW 6, relations translating the Ribasim volume must be given for every every cell of every boundary condition. These consist of piecewise linear relationships between the basin volume and its associated water level for the boundary condition in the cell.\nThese values are stored in a netCDF dataset. This dataset must meet the following requirements:\n\nIt must contain a x and y coordinate. The extent and cell size of these coordinates must match the domain of the coupled MODFLOW 6 model exactly.\nIt must contain a variable (x, y) denoting the basin IDs.\nIt must contain a volume-level variable (x, y, row, column) for every coupled MODFLOW 6 boundary condition, describing the volume-level lookup table per cell.\n\n\n\n\n\n\n\nNote\n\n\n\nThe x and y coordinates are valid for structured MODFLOW 6 models (DIS). Discretized-by-vertices (DISV) and fully unstructured discretization (DISU). are not yet supported, but require no fundamental changes: one basin is connected to multiple MODFLOW 6 cells, and the coupling parameters must match the (structured, unstructured) grid of the MODFLOW 6 model exactly.\n\n\nThe MODFLOW 6 coupling example cases show examples of such a parametrization."
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+    "text": "4 Test case: de Tol\nTo test the coupling, the following simulations have been setup and run:\n\nA standalone MODFLOW 6 run of sequential steady-states (i.e. no storage) with differing groundwater recharge values.\nA coupled run where the MODFLOW 6 stages are updated by the Ribasim coupler process, but without Ribasim. This results in volumes of 0.0, so all MODFLOW 6 water levels are set equal to bed elevation.\nA coupled run where the water levels are updated by Ribasim.\n\n\n\n\nFigure 7: Water balance of the MODFLOW 6 boundary conditions for De Tol basin for a standalone MODFLOW 6 run. The four sequential steady states (01, 02, 03, 04) use net groundwater recharge values of 1.0, 0.5, -0.05 and -0.1 mm/d.\n\n\nFigure 7 shows the water balance of steady-state for a submodel of the LHM for the Polder de Tol and its surroundings. While groundwater recharge is the dominant ingoing flow, lateral groundwater flow (over the entire depth of the groundwater model) is a sizable inflow for the area; the larger lateral inflow shows that De Tol is a net receiver of groundwater which is mostly discharged through the secondary system. In contrast to the Hupsel, the tertiary system is almost entirely absent: drainage occurs not through ephemeral tertiary ditches, but by the permanently water-bearing ditches of the primary and secondary system. Unlike the Hupsel, the water balance does not shrink to very small discharges, as there is sizable regional groundwater flow.\n\n\n\nFigure 8: Water balance of the MODFLOW 6 boundary conditions for De Tol basin for a zero volume run. The four sequential steady states (01, 02, 03, 04) use net groundwater recharge values of 1.0, 0.5, -0.05 and -0.1 mm/d.\n\n\nFigure 8 shows the same model, with 0-basin volume which causes water levels to be set equal to bed elevation. The total discharge is larger: the primary and secondary systems are set to lower levels, and so the head difference is larger. While De Tol’s evapotranspiration excess can be fed by the regional groundwater, the primary and secondary ditches also provide some part; as expected, they do not feed when the coupling mechanism adjusts MODFLOW 6’s water levels."
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-    "text": "Ribasim is a water resources model, designed to be the replacement of the regional surface water modules Mozart and SIMRES in the Netherlands Hydrological Instrument (NHI). Ribasim is a work in progress, it is a prototype that demonstrates all essential functionalities. Further development of the prototype in a software release is planned in 2022 and 2023.\nRibasim is written in the Julia programming language and is built on top of the SciML: Open Source Software for Scientific Machine Learning libraries, notably DifferentialEquations.jl."
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-    "text": "3.1 Water balance equations\nThe water balance equation for a drainage basin (Wikipedia contributors 2022) can be defined by a first-order ordinary differential equation (ODE), where the change of the storage \\(S\\) over time is determined by the inflow fluxes minus the outflow fluxes.\n\\[\n\\frac{\\mathrm{d}S}{\\mathrm{d}t} = Q_{in} - Q_{out}\n\\]\nWe can split out the fluxes into separate terms, such as precipitation \\(P\\), evapotranspiration \\(ET\\) and runoff \\(R\\). For now other fluxes are combined into \\(Q_{rest}\\). If we define all fluxes entering our reservoir as positive, and those leaving the system as negative, all fluxes can be summed up.\n\\[\n\\frac{\\mathrm{d}S}{\\mathrm{d}t} = R + P + ET + Q_{rest}\n\\]"
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-    "text": "3.2 Time\nThe water balance equation can be applied on many timescales; years, weeks, days or hours. Depending on the application and available data any of these can be the best choice. In Ribasim, we make use of DifferentialEquations.jl and its ODE solvers. Many of these solvers are based on adaptive time stepping, which means the solver will decide how large the time steps can be depending on the state of the system.\nThe forcing, like precipitation, is generally provided as a time series. Ribasim is set up to support unevenly spaced timeseries. The solver will stop on timestamps where new forcing values are available, so they can be loaded as the new value.\nRibasim is essentially a continuous model, rather than daily or hourly. If you want to use hourly forcing, you only need to make sure that your forcing data contains hourly updates. The output frequency can be configured independently. To be able to write a closed water balance, we accumulate the fluxes. This way any variations in between timesteps are also included, and we can output in m³ rather than m³s⁻¹."
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-    "text": "3.3 Space\nThe water balance equation can be applied on different spatial scales. Besides modelling a single lumped watershed, it allows you to divide the area into a network of connected representative elementary watersheds (REWs) (Reggiani, Sivapalan, and Majid Hassanizadeh 1998). At this scale global water balance laws can be formulated by means of integration of point-scale conservation equations over control volumes. Such an approach makes Ribasim a semi-distributed model. In this document we typically use the term “basin” to refer to the REW. (In Mozart the spatial unit was called Local Surface Water (LSW)). Each basin has an associated polygon, and the set of basins is connected to each other as described by a graph, which we call the network. Below is a representation of both on the map.\n\n\n\nMozart Local Surface Water polygons and their drainage.\n\n\nThe network is described as graph. Flow can be bi-directional, and the graph does not have to be acyclic.\n\n\n\n\ngraph LR;\n    A[\"basin A\"] --- B[\"basin B\"];\n    A --- C[\"basin C\"];\n    B --- D[\"basin D\"];\n    C --- D;\n\n\n\n\n\nInternally a directed graph is used. The direction is defined to be the positive flow direction, and is generally set in the dominant flow direction. The basins are the nodes of the network graph. Basin states and properties such storage volume and wetted area are associated with the nodes (A, B, C, D), as are most forcing data such as precipitation, evaporation, or water demand. Basin connection properties and interbasin flows are associated with the edges (the lines between A, B, C, and D) instead.\nMultiple basins may exist within the same spatial polygon, representing different aspects of the surface water system (perennial ditches, ephemeral ditches, or even surface ponding). Figure 1, Figure 2, Figure 3 show the 25.0 m rasterized primary, secondary, and tertiary surface waters as identified by BRT TOP10NL (PDOK 2022) in the Hupsel basin (as defined in the Mozart LSW’s). These systems may represented in multiple ways.\n\n\n\nFigure 1: Hupsel: primary surface water.\n\n\n\n\n\nFigure 2: Hupsel: secondary surface water.\n\n\n\n\n\nFigure 3: Hupsel: tertiary surface water.\n\n\nAs a single basin (A) containing all surface water, discharging to its downstream basin to the west (B):\n\n\n\n\ngraph LR;\n    A[\"basin A\"] --&gt; B[\"basin B\"];\n\n\n\n\n\nSuch a system may be capable of representing discharge, but it cannot represent residence times or differences in solute concentrations: within a single basin, drop of water is mixed instantaneously. Instead, we may the group primary (P), secondary (S), and tertiary (T) surface waters. Then T may flow into S, S into P, and P discharges to the downstream basin (B.)\n\n\n\n\ngraph LR;\n    T[\"basin T\"] --&gt; S[\"basin S\"];\n    S --&gt; P[\"basin P\"];\n    P --&gt; B[\"basin B\"];\n\n\n\n\n\nAs each (sub)basin has its own volume, low throughput (high volume, low discharge, long residence time) and high throughput (low volume, high discharge, short residence time) systems can be represented in a lumped manner; of course, more detail requires more parameters."
+    "text": "Ribasim can be coupled to other software, for instance to model another process or domain, or to control a simulation from another process.\nTo enable this, Ribasim can be compiled as a shared library (libribasim) instead of a command line interface (ribasim). This shared library exposes a C API in the form of the Basic Model Interface (BMI). Other software can then load libribasim and load a Ribasim model, exchange data, and control the time stepping.\nAn initial coupling to MODFLOW 6 was done in 2022 inside the Julia core as a proof of concept. Read about the coupling setup and see the demonstration. Going forward this and other coupling codes will be implemented outside of the core, by making use of iMOD Coupler and libribasim. iMOD Coupler is a generic coupling tool, and can be used to couple to other models as well."
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     "text": "1.6 Index\n\nRibasim.Ribasim\nRibasim.config\nRibasim.config.algorithms\nRibasim.AllocationModel\nRibasim.AllocationModel\nRibasim.Basin\nRibasim.DiscreteControl\nRibasim.EdgeMetadata\nRibasim.FlatVector\nRibasim.FlowBoundary\nRibasim.FractionalFlow\nRibasim.InNeighbors\nRibasim.LevelBoundary\nRibasim.LinearResistance\nRibasim.ManningResistance\nRibasim.Model\nRibasim.NodeMetadata\nRibasim.OutNeighbors\nRibasim.Outlet\nRibasim.PidControl\nRibasim.Pump\nRibasim.Subgrid\nRibasim.TabulatedRatingCurve\nRibasim.Terminal\nRibasim.User\nRibasim.config.Config\nBasicModelInterface.finalize\nBasicModelInterface.initialize\nBasicModelInterface.initialize\nCommonSolve.solve!\nRibasim.add_constraints_absolute_value!\nRibasim.add_constraints_capacity!\nRibasim.add_constraints_flow_conservation!\nRibasim.add_constraints_fractional_flow!\nRibasim.add_constraints_source!\nRibasim.add_constraints_user_returnflow!\nRibasim.add_flow!\nRibasim.add_flow!\nRibasim.add_variables_absolute_value!\nRibasim.add_variables_flow!\nRibasim.adjust_edge_capacities!\nRibasim.adjust_source_flows!\nRibasim.all_neighbor_labels_type\nRibasim.allocate!\nRibasim.allocation_graph\nRibasim.allocation_graph_used_nodes!\nRibasim.allocation_path_exists_in_graph\nRibasim.allocation_problem\nRibasim.allocation_table\nRibasim.assign_allocations!\nRibasim.avoid_using_own_returnflow!\nRibasim.basin_bottom\nRibasim.basin_bottoms\nRibasim.basin_table\nRibasim.config.algorithm\nRibasim.config.input_path\nRibasim.config.results_path\nRibasim.config.snake_case\nRibasim.create_callbacks\nRibasim.create_graph\nRibasim.create_storage_tables\nRibasim.datetime_since\nRibasim.datetimes\nRibasim.discrete_control_affect!\nRibasim.discrete_control_affect_downcrossing!\nRibasim.discrete_control_affect_upcrossing!\nRibasim.discrete_control_condition\nRibasim.discrete_control_table\nRibasim.expand_logic_mapping\nRibasim.find_allocation_graph_edges!\nRibasim.findlastgroup\nRibasim.findsorted\nRibasim.flow_table\nRibasim.formulate_basins!\nRibasim.formulate_flow!\nRibasim.formulate_flow!\nRibasim.formulate_flow!\nRibasim.get_area_and_level\nRibasim.get_chunk_sizes\nRibasim.get_compressor\nRibasim.get_flow\nRibasim.get_flow\nRibasim.get_fractional_flow_connected_basins\nRibasim.get_jac_prototype\nRibasim.get_level\nRibasim.get_scalar_interpolation\nRibasim.get_storage_from_level\nRibasim.get_storages_and_levels\nRibasim.get_storages_from_levels\nRibasim.get_tstops\nRibasim.get_value\nRibasim.id_index\nRibasim.indicate_allocation_flow!\nRibasim.inflow_id\nRibasim.inflow_ids\nRibasim.inflow_ids_allocation\nRibasim.inneighbor_labels_type\nRibasim.inoutflow_ids\nRibasim.is_allocation_source\nRibasim.is_current_module\nRibasim.is_flow_constraining\nRibasim.is_flow_direction_constraining\nRibasim.load_data\nRibasim.load_structvector\nRibasim.low_storage_factor\nRibasim.main\nRibasim.metadata_from_edge\nRibasim.nodefields\nRibasim.nodetype\nRibasim.outflow_id\nRibasim.outflow_ids\nRibasim.outflow_ids_allocation\nRibasim.outneighbor_labels_type\nRibasim.parse_static_and_time\nRibasim.process_allocation_graph_edges!\nRibasim.profile_storage\nRibasim.qh_interpolation\nRibasim.reduction_factor\nRibasim.run\nRibasim.save_flow\nRibasim.save_subgrid_level\nRibasim.scalar_interpolation_derivative\nRibasim.seconds_since\nRibasim.set_current_value!\nRibasim.set_flow!\nRibasim.set_flow!\nRibasim.set_fractional_flow_in_allocation!\nRibasim.set_initial_discrete_controlled_parameters!\nRibasim.set_objective_priority!\nRibasim.set_static_value!\nRibasim.set_table_row!\nRibasim.sorted_table!\nRibasim.timesteps\nRibasim.update_allocation!\nRibasim.update_basin\nRibasim.update_jac_prototype!\nRibasim.update_jac_prototype!\nRibasim.update_jac_prototype!\nRibasim.update_jac_prototype!\nRibasim.update_tabulated_rating_curve!\nRibasim.valid_discrete_control\nRibasim.valid_edge_types\nRibasim.valid_edges\nRibasim.valid_flow_rates\nRibasim.valid_fractional_flow\nRibasim.valid_n_neighbors\nRibasim.valid_profiles\nRibasim.valid_sources\nRibasim.valid_subgrid\nRibasim.water_balance!\nRibasim.write_arrow\nRibasim.config.@addfields\nRibasim.config.@addnodetypes"
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-    "text": "Ribasim can be coupled to other software, for instance to model another process or domain, or to control a simulation from another process.\nTo enable this, Ribasim can be compiled as a shared library (libribasim) instead of a command line interface (ribasim). This shared library exposes a C API in the form of the Basic Model Interface (BMI). Other software can then load libribasim and load a Ribasim model, exchange data, and control the time stepping.\nAn initial coupling to MODFLOW 6 was done in 2022 inside the Julia core as a proof of concept. Read about the coupling setup and see the demonstration. Going forward this and other coupling codes will be implemented outside of the core, by making use of iMOD Coupler and libribasim. iMOD Coupler is a generic coupling tool, and can be used to couple to other models as well."
+    "text": "Ribasim is a water resources model, designed to be the replacement of the regional surface water modules Mozart and SIMRES in the Netherlands Hydrological Instrument (NHI). Ribasim is a work in progress, it is a prototype that demonstrates all essential functionalities. Further development of the prototype in a software release is planned in 2022 and 2023.\nRibasim is written in the Julia programming language and is built on top of the SciML: Open Source Software for Scientific Machine Learning libraries, notably DifferentialEquations.jl."
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-    "text": "In our test cases, we will work with the Dutch national groundwater model (LHM). For testing, we simplify the top boundary conditions to just three surface water “systems”, from large to small:\n\nPrimary\nSecondary\nTertiary\n\nThese systems are separated in the groundwater model schematization due to the relatively small size of the surface waters (several meters in width) in comparison with relatively coarse cells of the groundwater model (250 m): most cells in the LHM contain more than one surface water, and are included via representative parameters which take the physical scaling into account. In case of sufficiently small cell sizes, no overlap occurs and all surface waters can be represented in a single grid.\nRibasim has no knowledge of these systems unless explicitly separated into different (sub-)basins. In the examples below, these three systems are represented by one basin with a single volume. For the purposes of testing, we have not yet created empirical volume-level relationships for the surface water of every cell extracted from a hydraulic model. Instead, we have chosen an (over)simplified parametrization of the hydraulic properties, which makes it easy to verify the behavior of Ribasim and the coupling procedures:\n\nPrimary, secondary, and tertiary systems have a rectangular profile: the area of the surface water does not change with water level or volume.\nWater depth is constant for a system within a basin.\nWater depth increases linearly with volume. (This follows from 1.)\nWater depth is distributed across the systems in a geometric progression: when the tertiary system contains 0.1 m of water, the secondary system contains 0.2 m, and the primary system contains 0.4 m.\nWater depth is 0.0 m for all systems when basin volume is 0.0. (This follows from 4.)\nThe distribution of water occurs according to the surface water area (width times length) used for the LHM parametrization of river bed conductance.\n\nFor freely draining basins, a simplified storage-discharge relationship has been derived as follows:\n\nThe area of the basin polygon has been multiplied by 1 mm/d (roughly the average precipitation excess in the Netherlands). This yields a “normative discharge”.\nA corresponding normative volume has been chosen, corresponding with water depths of 0.4, 0.2, and 0.1 m for the primary, secondary, and tertiary surface waters respectively.\nA dead storage volume has been chosen, corresponding with water depths of 0.2, 0.1, and 0.05 m for the primary, secondary, and tertiary surface waters respectively. The basin only starts discharging when the storage volume exceeds this value.\n\n\n\n\n\n\n\nNote\n\n\n\nRibasim is not limited to such oversimplified parametrization! Ribasim uses tabulations and therefore supports arbitrary (piecewise linear) volume-depth and volume-discharge relationships.\n\n\nA visual representation of this simplified conceptual schematization is given in Figure 1 and Figure 2.\n\n\n\nFigure 1: Distribution of water depths over the primary, secondary, and tertiary system.\n\n\n\n\n\nFigure 2: Discharge as a function of basin storage volume.\n\n\nAn example of the resulting parameters for a single cell is shown in Table 1. The first row shows the water levels when the basin is empty. The level for primary, secondary, and tertiary are equal to the bottom elevation of the surface waters. The second row shows the volume and levels for water depths of 0.4, 0.2, and 0.1 m. The third row shows the volume and levels for a tenfold larger volume. This results in implausible water levels with depths of 4.0, 2.0 and 1.0 m; the water level in the primary system is over two meters higher than in the tertiary system. In reality, the surface waters would overflow and surface ponding would occur; this mechanism is ignored in the test cases for the sake of simplicity.\n\n\nTable 1: Volume-level table for a single cell in the Hupsel basin.\n\n\nVolume (m3)\nPrimary (m NAP)\nSecondary (m NAP)\nTertiary (m NAP)\n\n\n\n\n0.0\n25.65\n25.83\n26.60\n\n\n6843.1\n26.05\n26.03\n26.70\n\n\n68431.0\n29.65\n27.83\n27.60\n\n\n\n\nFigure 3 shows the volume of the first row of the cell based input for the primary system. Symbology is set to unique values. While water levels differ per cell in this parametrization, the “normative volume” defined above is shared by all cells in a basin.\n\n\n\nFigure 3: Basin normative volume of the primary system.\n\n\nFigure 3 shows the water level corresponding to the normative storage volume based input for the primary system (it corresponds to the value shown in the first row of the primary column in Table 1). We see a clear gradient from west to east: as our simplified parametrization assumes a constant water depth for all cells in a single system, water levels spatially fall and rise with the bottom elevation.\n\n\n\nFigure 4: Water level corresponding to the normative basin volume of the primary system."
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+    "text": "3.1 Water balance equations\nThe water balance equation for a drainage basin (Wikipedia contributors 2022) can be defined by a first-order ordinary differential equation (ODE), where the change of the storage \\(S\\) over time is determined by the inflow fluxes minus the outflow fluxes.\n\\[\n\\frac{\\mathrm{d}S}{\\mathrm{d}t} = Q_{in} - Q_{out}\n\\]\nWe can split out the fluxes into separate terms, such as precipitation \\(P\\), evapotranspiration \\(ET\\) and runoff \\(R\\). For now other fluxes are combined into \\(Q_{rest}\\). If we define all fluxes entering our reservoir as positive, and those leaving the system as negative, all fluxes can be summed up.\n\\[\n\\frac{\\mathrm{d}S}{\\mathrm{d}t} = R + P + ET + Q_{rest}\n\\]"
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+    "text": "3.2 Time\nThe water balance equation can be applied on many timescales; years, weeks, days or hours. Depending on the application and available data any of these can be the best choice. In Ribasim, we make use of DifferentialEquations.jl and its ODE solvers. Many of these solvers are based on adaptive time stepping, which means the solver will decide how large the time steps can be depending on the state of the system.\nThe forcing, like precipitation, is generally provided as a time series. Ribasim is set up to support unevenly spaced timeseries. The solver will stop on timestamps where new forcing values are available, so they can be loaded as the new value.\nRibasim is essentially a continuous model, rather than daily or hourly. If you want to use hourly forcing, you only need to make sure that your forcing data contains hourly updates. The output frequency can be configured independently. To be able to write a closed water balance, we accumulate the fluxes. This way any variations in between timesteps are also included, and we can output in m³ rather than m³s⁻¹."
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+    "text": "3.3 Space\nThe water balance equation can be applied on different spatial scales. Besides modelling a single lumped watershed, it allows you to divide the area into a network of connected representative elementary watersheds (REWs) (Reggiani, Sivapalan, and Majid Hassanizadeh 1998). At this scale global water balance laws can be formulated by means of integration of point-scale conservation equations over control volumes. Such an approach makes Ribasim a semi-distributed model. In this document we typically use the term “basin” to refer to the REW. (In Mozart the spatial unit was called Local Surface Water (LSW)). Each basin has an associated polygon, and the set of basins is connected to each other as described by a graph, which we call the network. Below is a representation of both on the map.\n\n\n\nMozart Local Surface Water polygons and their drainage.\n\n\nThe network is described as graph. Flow can be bi-directional, and the graph does not have to be acyclic.\n\n\n\n\ngraph LR;\n    A[\"basin A\"] --- B[\"basin B\"];\n    A --- C[\"basin C\"];\n    B --- D[\"basin D\"];\n    C --- D;\n\n\n\n\n\nInternally a directed graph is used. The direction is defined to be the positive flow direction, and is generally set in the dominant flow direction. The basins are the nodes of the network graph. Basin states and properties such storage volume and wetted area are associated with the nodes (A, B, C, D), as are most forcing data such as precipitation, evaporation, or water demand. Basin connection properties and interbasin flows are associated with the edges (the lines between A, B, C, and D) instead.\nMultiple basins may exist within the same spatial polygon, representing different aspects of the surface water system (perennial ditches, ephemeral ditches, or even surface ponding). Figure 1, Figure 2, Figure 3 show the 25.0 m rasterized primary, secondary, and tertiary surface waters as identified by BRT TOP10NL (PDOK 2022) in the Hupsel basin (as defined in the Mozart LSW’s). These systems may represented in multiple ways.\n\n\n\nFigure 1: Hupsel: primary surface water.\n\n\n\n\n\nFigure 2: Hupsel: secondary surface water.\n\n\n\n\n\nFigure 3: Hupsel: tertiary surface water.\n\n\nAs a single basin (A) containing all surface water, discharging to its downstream basin to the west (B):\n\n\n\n\ngraph LR;\n    A[\"basin A\"] --&gt; B[\"basin B\"];\n\n\n\n\n\nSuch a system may be capable of representing discharge, but it cannot represent residence times or differences in solute concentrations: within a single basin, drop of water is mixed instantaneously. Instead, we may the group primary (P), secondary (S), and tertiary (T) surface waters. Then T may flow into S, S into P, and P discharges to the downstream basin (B.)\n\n\n\n\ngraph LR;\n    T[\"basin T\"] --&gt; S[\"basin S\"];\n    S --&gt; P[\"basin P\"];\n    P --&gt; B[\"basin B\"];\n\n\n\n\n\nAs each (sub)basin has its own volume, low throughput (high volume, low discharge, long residence time) and high throughput (low volume, high discharge, short residence time) systems can be represented in a lumped manner; of course, more detail requires more parameters."
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-    "text": "In our test cases, we will work with the Dutch national groundwater model (LHM). For testing, we simplify the top boundary conditions to just three surface water “systems”, from large to small:\n\nPrimary\nSecondary\nTertiary\n\nThese systems are separated in the groundwater model schematization due to the relatively small size of the surface waters (several meters in width) in comparison with relatively coarse cells of the groundwater model (250 m): most cells in the LHM contain more than one surface water, and are included via representative parameters which take the physical scaling into account. In case of sufficiently small cell sizes, no overlap occurs and all surface waters can be represented in a single grid.\nRibasim has no knowledge of these systems unless explicitly separated into different (sub-)basins. In the examples below, these three systems are represented by one basin with a single volume. For the purposes of testing, we have not yet created empirical volume-level relationships for the surface water of every cell extracted from a hydraulic model. Instead, we have chosen an (over)simplified parametrization of the hydraulic properties, which makes it easy to verify the behavior of Ribasim and the coupling procedures:\n\nPrimary, secondary, and tertiary systems have a rectangular profile: the area of the surface water does not change with water level or volume.\nWater depth is constant for a system within a basin.\nWater depth increases linearly with volume. (This follows from 1.)\nWater depth is distributed across the systems in a geometric progression: when the tertiary system contains 0.1 m of water, the secondary system contains 0.2 m, and the primary system contains 0.4 m.\nWater depth is 0.0 m for all systems when basin volume is 0.0. (This follows from 4.)\nThe distribution of water occurs according to the surface water area (width times length) used for the LHM parametrization of river bed conductance.\n\nFor freely draining basins, a simplified storage-discharge relationship has been derived as follows:\n\nThe area of the basin polygon has been multiplied by 1 mm/d (roughly the average precipitation excess in the Netherlands). This yields a “normative discharge”.\nA corresponding normative volume has been chosen, corresponding with water depths of 0.4, 0.2, and 0.1 m for the primary, secondary, and tertiary surface waters respectively.\nA dead storage volume has been chosen, corresponding with water depths of 0.2, 0.1, and 0.05 m for the primary, secondary, and tertiary surface waters respectively. The basin only starts discharging when the storage volume exceeds this value.\n\n\n\n\n\n\n\nNote\n\n\n\nRibasim is not limited to such oversimplified parametrization! Ribasim uses tabulations and therefore supports arbitrary (piecewise linear) volume-depth and volume-discharge relationships.\n\n\nA visual representation of this simplified conceptual schematization is given in Figure 1 and Figure 2.\n\n\n\nFigure 1: Distribution of water depths over the primary, secondary, and tertiary system.\n\n\n\n\n\nFigure 2: Discharge as a function of basin storage volume.\n\n\nAn example of the resulting parameters for a single cell is shown in Table 1. The first row shows the water levels when the basin is empty. The level for primary, secondary, and tertiary are equal to the bottom elevation of the surface waters. The second row shows the volume and levels for water depths of 0.4, 0.2, and 0.1 m. The third row shows the volume and levels for a tenfold larger volume. This results in implausible water levels with depths of 4.0, 2.0 and 1.0 m; the water level in the primary system is over two meters higher than in the tertiary system. In reality, the surface waters would overflow and surface ponding would occur; this mechanism is ignored in the test cases for the sake of simplicity.\n\n\nTable 1: Volume-level table for a single cell in the Hupsel basin.\n\n\nVolume (m3)\nPrimary (m NAP)\nSecondary (m NAP)\nTertiary (m NAP)\n\n\n\n\n0.0\n25.65\n25.83\n26.60\n\n\n6843.1\n26.05\n26.03\n26.70\n\n\n68431.0\n29.65\n27.83\n27.60\n\n\n\n\nFigure 3 shows the volume of the first row of the cell based input for the primary system. Symbology is set to unique values. While water levels differ per cell in this parametrization, the “normative volume” defined above is shared by all cells in a basin.\n\n\n\nFigure 3: Basin normative volume of the primary system.\n\n\nFigure 3 shows the water level corresponding to the normative storage volume based input for the primary system (it corresponds to the value shown in the first row of the primary column in Table 1). We see a clear gradient from west to east: as our simplified parametrization assumes a constant water depth for all cells in a single system, water levels spatially fall and rise with the bottom elevation.\n\n\n\nFigure 4: Water level corresponding to the normative basin volume of the primary system."
+    "text": "Ribasim has been designed to provide a computationally efficient representation of surface water for MODFLOW 6. It does so by connecting to basic MODFLOW 6 boundary conditions: the river and drainage packages.\nRibasim connects to MODFLOW 6 via the Basic Model Interface (BMI) and Extended Model Interface (XMI) (Hughes et al. 2022). BMI describes the interface to initialize a model, get values from its memory, run a timestep, etc. XMI extends this interface to allow much finer control into MODFLOW 6’s solution procedures. We have written a Julia package (Deltares 2022) which implements this interface for the Julia programming language. In coupling, Ribasim uses this interface to get the head values, the boundary condition water levels, and the budgets term of the MODFLOW 6 groundwater model while MODFLOW 6 is running.\nAdditionally, links can be made with other (BMI/XMI-compliant) processes and models. One example of such a link is using the surface runoff and the agricultural irrigation demand calculated by an unsaturated zone model; in the Netherlands Hydrological Instrument MetaSWAP provides this demand."
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-    "text": "2 Example: Configuration\nAn example of the MODFLOW 6 section of TOML configuration required for a coupled run can be seen below:\n[modflow]\nsimulation = \"../data/hupsel/mfsim.nam\"\nmode = \"sequential\"\ntimestep = 86400.0\n\n[modflow.models]\n\n[modflow.models.gwf]\ntype = \"gwf\"\ndataset = \"../data/volume_level_profile-hupsel.nc\"\nbasins = \"basin_id\"\n\n[[modflow.models.gwf.bounds]]\nriver = \"RIV_P\"\ndrain = \"DRN_P\"\nprofile = \"profile_primary\"\n\n[[modflow.models.gwf.bounds]]\nriver = \"RIV_S\"\ndrain = \"DRN_S\"\nprofile = \"profile_secondary\"\n\n[[modflow.models.gwf.bounds]]\ndrain = \"DRN_T\"\nprofile = \"profile_tertiary\"\nThe section starts by stating the path to the MODFLOW 6 simulation name file (simulation). The next section contains the information regarding the MODFLOW 6 model(s) to couple to Ribasim’s basins. Per model, a path to the coupling parameter dataset is provided (dataset), along with the variable to use as the basin identification number (basins). Next, for every boundary condition that should be coupled to Ribasim, the package names (river, drain) used by MODFLOW 6 must be specified (as we look for these names in the MODFLOW 6 memory), along with the name of the variable in the coupling dataset which provides the volume-level relationship (profile).\nAs can be seen in the example, the coupling mechanism supports coupling of:\n\nA single drainage package (drain entry).\nA single river package (river entry).\nA combination of river and drainage package (when infiltration conductance does not equal drainage conductance) both (river and drain entry)."
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+    "text": "1.1 Drainage\nThe drainage package can be simulated to agricultural drains, ditches, or draining streams. The amount of water removed from the aquifer is proportional to the difference between the groundwater head and the drainage elevation. Drainage only occurs when the head is larger than the elevation; this boundary condition does not allow infiltration into the groundwater.\n\\[\nQ_{drain} = \\left\\{\n    \\begin{array}{ c l }\n        C_{drain} (\\phi - h_{drain}) & \\quad \\textrm{if } \\phi &gt; h_{drain} \\\\\n        0                            & \\quad \\textrm{otherwise}\n     \\end{array}\n\\right.\n\\]"
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-    "text": "3 Test case: Hupsel\nTo test the coupling, the following simulations have been setup and run:\n\nA standalone MODFLOW 6 run of sequential steady-states (i.e. no storage) with differing groundwater recharge values.\nA coupled run where the MODFLOW 6 stages are updated by the Ribasim coupler process, but without Ribasim. This results in volumes of 0.0, so all MODFLOW 6 water levels are set equal to bed elevation.\nA coupled run where the water levels are updated by Ribasim.\n\nFrom these tests, we expect the following behavior:\n\nDrainage terms should remain largely the same when the water level is lowered in a steady-state: the amount of recharge is fixed, and this is locally drained.\nIn case of negative recharge (evapotranspiration), infiltration occurs in the surface waters. Infiltration should be zero when the basin volume is 0.\n\n\n\n\nFigure 5: Water balance of the MODFLOW 6 boundary conditions for the Hupsel basin for a standalone MODFLOW 6 run. The four sequential steady states (01, 02, 03, 04) use net groundwater recharge values of 1.0, 0.5, -0.05 and -0.1 mm/d.\n\n\nFigure 5 shows the water balance of steady-state for submodel of the LHM that has been by selecting the cells belonging to the district containing the Hupsel catch, the Berkel.\nThe Hupsel basin show the expected behavior: for a net groundwater recharge of 1.0 mm/d, most is precipitation with a minor part lateral inflow from higher areas. In terms of outgoing flows, most of the precipitation ends up in the surface water, primarily in the many ditches of the tertiary system. Only a relatively small part of the water leaves the basin via the groundwater. Interbasin flows through the groundwater form such a minor role, as the aquifer is thin and transmissivity is limited.\nReducing groundwater recharge to 0.5 mm/d reduces all flows, with the tertiary system playing a less dominant role, relatively speaking: as its elevation is the highest compared to the primary and secondary system, the head difference is reduced strongest for the tertiary system.\nWith evapotranspiration (ET) excess (-0.05 and 0.1 mm/d; low values are chosen here since most ET would be drawn from storage, which is not available in a steady-state model), the surface waters provide mostly inflow, and recharge is a negative term. In this case, the secondary system provides a small amount of infiltration; most of the water is drawn from the surroundings instead.\n\n\n\nFigure 6: Water balance of the MODFLOW 6 boundary conditions for the Hupsel basin for a zero volume run. The four sequential steady states (01, 02, 03, 04) use net groundwater recharge values of 1.0, 0.5, -0.05 and -0.1 mm/d.\n\n\nFigure 6 shows the same model, with 0-basin volume which causes water levels to be set equal to bed elevation. Consequently, primary and secondary outflow terms are larger for positive groundwater recharge as they drain at a lower level and intercept the water before the tertiary system does. Secondly, with negative groundwater recharge, no infiltration occurs and the water is drawn from the surroundings instead. This shows the coupling mechanism adjusting MODFLOW 6 water levels successfully."
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+    "text": "1.2 River\nThe river package can both drain the groundwater, or infiltrate surface water to the groundwater. It limits the amount of water that can infiltrate when the groundwater head falls below the river bottom, in which cases it assumes atmospheric pressure conditions underneath the surface water.\n\\[\nQ_{river} = \\left\\{\n    \\begin{array}{ c l }\n        C_{river} (\\phi - h_{river}) & \\quad \\textrm{if } \\phi &gt; b_{river} \\\\\n        C_{river} (h_{river} - b_{river}) & \\quad \\textrm{if } \\phi &lt;= b_{river}\n     \\end{array}\n\\right.\n\\]\nIn the Netherlands, it is somewhat common to make a distinction between the drainage and infiltration conductance of surface waters. Drainage conductance is often larger than the infiltration conductance due to clogging processes, seepage through sides of the ditches, less contracted flow lines, etc.\n\\[\nQ_{river} = \\left\\{\n    \\begin{array}{ c l }\n        C_{river,drn} (\\phi - h_{river}) & \\quad \\textrm{if } \\phi &gt; h_{river} \\\\\n        C_{river,inf} (\\phi - h_{river}) & \\quad \\textrm{if } \\phi &lt;= h_{river} \\\\\n        C_{river,inf} (h_{river} - b_{river}) & \\quad \\textrm{if } \\phi &lt;= b_{river}\n     \\end{array}\n\\right.\n\\]\nMODFLOW 6 does not support this (currently), but an identical effect may be achieved by “stacking” a drainage package on top of a river package with these values:\n\\[\n\\begin{array}{ c l }\n  h_{drain} = h_{river} \\\\\n  C_{drain} = C_{river,drn} - C_{river,inf}\n\\end{array}\n\\]"
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-    "text": "4 Test case: de Tol\nTo test the coupling, the following simulations have been setup and run:\n\nA standalone MODFLOW 6 run of sequential steady-states (i.e. no storage) with differing groundwater recharge values.\nA coupled run where the MODFLOW 6 stages are updated by the Ribasim coupler process, but without Ribasim. This results in volumes of 0.0, so all MODFLOW 6 water levels are set equal to bed elevation.\nA coupled run where the water levels are updated by Ribasim.\n\n\n\n\nFigure 7: Water balance of the MODFLOW 6 boundary conditions for De Tol basin for a standalone MODFLOW 6 run. The four sequential steady states (01, 02, 03, 04) use net groundwater recharge values of 1.0, 0.5, -0.05 and -0.1 mm/d.\n\n\nFigure 7 shows the water balance of steady-state for a submodel of the LHM for the Polder de Tol and its surroundings. While groundwater recharge is the dominant ingoing flow, lateral groundwater flow (over the entire depth of the groundwater model) is a sizable inflow for the area; the larger lateral inflow shows that De Tol is a net receiver of groundwater which is mostly discharged through the secondary system. In contrast to the Hupsel, the tertiary system is almost entirely absent: drainage occurs not through ephemeral tertiary ditches, but by the permanently water-bearing ditches of the primary and secondary system. Unlike the Hupsel, the water balance does not shrink to very small discharges, as there is sizable regional groundwater flow.\n\n\n\nFigure 8: Water balance of the MODFLOW 6 boundary conditions for De Tol basin for a zero volume run. The four sequential steady states (01, 02, 03, 04) use net groundwater recharge values of 1.0, 0.5, -0.05 and -0.1 mm/d.\n\n\nFigure 8 shows the same model, with 0-basin volume which causes water levels to be set equal to bed elevation. The total discharge is larger: the primary and secondary systems are set to lower levels, and so the head difference is larger. While De Tol’s evapotranspiration excess can be fed by the regional groundwater, the primary and secondary ditches also provide some part; as expected, they do not feed when the coupling mechanism adjusts MODFLOW 6’s water levels."
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+    "text": "2.1 Numerical solution in MODFLOW\nMODFLOW uses a backward-in-time implicit solution scheme. This creates a large system of equations (a water balance for every cell), which it solves by repeatedly solving a linearized system of equations instead. In matrix form, this system of equations is expressed by:\n\\[\n\\mathbf{Ax} = \\mathbf{b}\n\\]\nWhere \\(\\mathbf{x}\\) is a vector containing the head of every cell.\nFor the boundary conditions, this requires linearization of the flow equations. Flow from outside of the aquifer (cell) may be represented by:\n\\[\na = p\\phi + q\n\\]\n(Equation 2-6 in the MODFLOW 6 documentation (Langevin et al. 2017).)\nFor e.g. a draining boundary condition, the flow is head dependent:\n\\[\na = C(h - \\phi) = -C\\phi + Ch\n\\]\nWith \\(C\\) the conductance, \\(h\\) the boundary head or elevation, and \\(\\phi\\) the groundwater head.\nIn MODFLOW’s internal formulation, the term in \\(\\mathbf{A}\\) is called “coefficient of head” or hcof. Terms in \\(\\mathbf{b}\\) are called “right hand side” or rhs. We can separate the equation above:\n\\[\n\\begin{aligned}\np = \\text{hcof} = -C \\\\\nq = \\textrm{rhs} = -Ch \\\\\na = -C\\phi + Ch = \\text{hcof} * \\phi - \\text{rhs}\n\\end{aligned}\n\\]\nFor every boundary condition, MODFLOW 6 stores the hcof and rhs values. This makes it quite convenient for us to compute the water budget for every boundary condition: we simply multiply the hcof value by the head of the cell and subtract the rhs.\nNote that hcof may have a value of 0! For example, when for a river boundary the \\(\\phi &lt;= b_{river}\\) condition occurs, the flow into the cell is controlled only by \\(h_{river}\\) and \\(b_{river}\\) (equal to recharge for the linear solution)."
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+    "text": "2.2 Sequential coupled solution\nA coupled run stars by initializing both models and creating the exchange information: which MODFLOW 6 boundary condition is connected to which Ribasim basin. While the model is running, the model proceeds through time as follows:\n\nRibasim solves the equations on a basin level; this occurs with adaptive timestepping via ModelingToolkit.\nAt a specified time (in accordance with the MODFLOW 6 time discretization), the volumes are converted to MODFLOW 6 boundary condition levels using a Callback function.\nMODFLOW 6 runs a timestep.\nThe drainage and infiltration budgets are computed from MODFLOW 6 using the equations described above and aggregated per basin.\nThe aggregated values are set as Ribasim boundary conditions, and Ribasim solves until the next preset exchange time.\n\nThese steps run until the final timestep is finished."
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+    "text": "2.3 Iterative coupled solution\n\n\n\n\n\n\nNote\n\n\n\nWe have not implemented an iterative coupled solution yet. The section below describes an approach.\n\n\nThe simplest form of a iterative solution occurs as follows:\n\nMODFLOW 6 computes drainage and infiltration flows.\nRibasim uses these flows to compute a storage volume for the basin.\nThe volume is translated to a water level for every MODFLOW 6 boundary condition in the basins.\nMODFLOW 6 recomputes drainage and infiltration flows with the updated water levels, etc.\n\nSuch a scheme is not maximally efficient: the discharge and infiltration terms are not constant, but are driven by a head difference. This head difference depends on the level of the boundary conditions and head of every cell of the groundwater model. If the surface waters of a basin empty, the water level will decrease and drainage and infiltration flows will change. Ideally, we can provide Ribasim with more information, so that it may estimate drainage and infiltration terms better.\nAs groundwater flow is often (approximately) linear, we can use linearization to more efficiently compute the flow from Ribasim’s side as well. In the iterative coupled solution, we are solving both MODFLOW 6 and Ribasim repeatedly, until they produce same drainage or infiltration (approximately). One of Ribasim’s basins contains many MODFLOW cells with boundary conditions. We could add every boundary condition to Ribasim’s equations, but this is costly and cumbersome. Fortunately, linearization allows us to “stack” (superpose) all the different boundary conditions into a single, simple equation. In linear form, every equation takes the form of:\n\\[\na = ph + q\n\\]\nNote the \\(h\\) rather than \\(\\phi\\), we are formulating from Ribasim’s perspective! We can sum all coefficients for p and q to provide a linear groundwater response to Ribasim.\n\n2.3.1 Drainage\nFrom Ribasim’s perspective, the groundwater head is constant given a timestep, so that:\n\\[\\begin{align}\np = -C \\\\\nq = -C\\phi\n\\end{align}\\]\nWhen the head falls below the drainage elevation, the coefficients are 0.\n\n\n2.3.2 River\nFrom Ribasim’s perspective, infiltration is never limited when the head falls below the bottom:\n\\[\\begin{align}\np = -C \\\\\nq = -Cb\n\\end{align}\\]\nOtherwise, infiltration and drainage occur with the same equation as for the drainage package:\n\\[\\begin{align}\np = -C \\\\\nq = -C\\phi\n\\end{align}\\]"
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+    "text": "3.1 Parametrization\nIn coupling Ribasim to MODFLOW 6, relations translating the Ribasim volume must be given for every every cell of every boundary condition. These consist of piecewise linear relationships between the basin volume and its associated water level for the boundary condition in the cell.\nThese values are stored in a netCDF dataset. This dataset must meet the following requirements:\n\nIt must contain a x and y coordinate. The extent and cell size of these coordinates must match the domain of the coupled MODFLOW 6 model exactly.\nIt must contain a variable (x, y) denoting the basin IDs.\nIt must contain a volume-level variable (x, y, row, column) for every coupled MODFLOW 6 boundary condition, describing the volume-level lookup table per cell.\n\n\n\n\n\n\n\nNote\n\n\n\nThe x and y coordinates are valid for structured MODFLOW 6 models (DIS). Discretized-by-vertices (DISV) and fully unstructured discretization (DISU). are not yet supported, but require no fundamental changes: one basin is connected to multiple MODFLOW 6 cells, and the coupling parameters must match the (structured, unstructured) grid of the MODFLOW 6 model exactly.\n\n\nThe MODFLOW 6 coupling example cases show examples of such a parametrization."
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-    "text": "The Model class represents an entire Ribasim model.\n\n\n\nModel\nA full Ribasim model schematisation with all input.\n\n\n\n\n\n\nThe Node and Edge database layers define the network layout.\n\n\n\nNode\nThe Ribasim nodes as Point geometries.\n\n\nEdge\nDefines the connections between nodes.\n\n\n\n\n\n\nAvailable node types to model different situations.\n\n\n\nBasin\n\n\n\nFractionalFlow\n\n\n\nTabulatedRatingCurve\n\n\n\nPump\n\n\n\nOutlet\n\n\n\nUser\n\n\n\nLevelBoundary\n\n\n\nFlowBoundary\n\n\n\nLinearResistance\n\n\n\nManningResistance\n\n\n\nTerminal\n\n\n\nDiscreteControl\n\n\n\nPidControl"
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-    "text": "The Model class represents an entire Ribasim model.\n\n\n\nModel\nA full Ribasim model schematisation with all input."
+    "text": "Model()\nA full Ribasim model schematisation with all input.\nRibasim model containing the location of the nodes, the edges between the nodes, and the node parametrization.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nstarttime\ndatetime.datetime\nStarting time of the simulation.\nrequired\n\n\nendtime\ndatetime.datetime\nEnd time of the simulation.\nrequired\n\n\nupdate_timestep\n\nThe output time step of the simulation in seconds (default of 1 day)\nrequired\n\n\ninput_dir\n\nThe directory of the input files.\nrequired\n\n\nresults_dir\n\nThe directory of the results files.\nrequired\n\n\nnetwork\n\nClass containing the topology (nodes and edges) of the model.\nrequired\n\n\nresults\n\nResults configuration options.\nrequired\n\n\nsolver\n\nSolver configuration options.\nrequired\n\n\nlogging\n\nLogging configuration options.\nrequired\n\n\nallocation\n\nThe allocation configuration.\nrequired\n\n\nbasin\nBasin\nThe waterbodies.\nrequired\n\n\nfractional_flow\nFractionalFlow\nSplit flows into fractions.\nrequired\n\n\nlevel_boundary\nLevelBoundary\nBoundary condition specifying the water level.\nrequired\n\n\nflow_boundary\nFlowBoundary\nBoundary conditions specifying the flow.\nrequired\n\n\nlinear_resistance\n\nLinear flow resistance.\nrequired\n\n\nmanning_resistance\nManningResistance\nFlow resistance based on the Manning formula.\nrequired\n\n\ntabulated_rating_curve\nTabulatedRatingCurve\nTabulated rating curve describing flow based on the upstream water level.\nrequired\n\n\npump\nPump\nPrescribed flow rate from one basin to the other.\nrequired\n\n\noutlet\nOutlet\nPrescribed flow rate from one basin to the other.\nrequired\n\n\nterminal\nTerminal\nWater sink without state or properties.\nrequired\n\n\ndiscrete_control\nDiscreteControl\nDiscrete control logic.\nrequired\n\n\npid_control\nPidControl\nPID controller attempting to set the level of a basin to a desired value using a pump/outlet.\nrequired\n\n\nuser\nUser\nUser node type with demand and priority.\nrequired\n\n\n\n\n\n\n\n\n\nName\nDescription\n\n\n\n\nplot\nPlot the nodes and edges of the model.\n\n\nread\nRead model from TOML file.\n\n\nvalidate_model\nValidate the model.\n\n\nvalidate_model_node_field_ids\nCheck whether the node IDs of the node_type fields are valid.\n\n\nvalidate_model_node_ids\nCheck whether the node IDs in the data tables correspond to the node IDs in the network.\n\n\nwrite\nWrite the contents of the model to disk and save it as a TOML configuration file.\n\n\n\n\n\nModel.plot(ax=None)\nPlot the nodes and edges of the model.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nax\nmatplotlib.pyplot.Artist\nAxes on which to draw the plot.\nNone\n\n\n\n\n\n\n\n\n\nType\nDescription\n\n\n\n\nmatplotlib.pyplot.Artist\n\n\n\n\n\n\n\n\nModel.read(filepath)\nRead model from TOML file.\n\n\n\nModel.validate_model()\nValidate the model.\nChecks: - Whether the node IDs of the node_type fields are valid - Whether the node IDs in the node field correspond to the node IDs on the node type fields\n\n\n\nModel.validate_model_node_field_ids()\nCheck whether the node IDs of the node_type fields are valid.\n\n\n\nModel.validate_model_node_ids()\nCheck whether the node IDs in the data tables correspond to the node IDs in the network.\n\n\n\nModel.write(filepath)\nWrite the contents of the model to disk and save it as a TOML configuration file.\nIf filepath.parent does not exist, it is created before writing.\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nfilepath\nPath | str\n\nrequired"
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-    "text": "The Node and Edge database layers define the network layout.\n\n\n\nNode\nThe Ribasim nodes as Point geometries.\n\n\nEdge\nDefines the connections between nodes."
+    "text": "Name\nType\nDescription\nDefault\n\n\n\n\nstarttime\ndatetime.datetime\nStarting time of the simulation.\nrequired\n\n\nendtime\ndatetime.datetime\nEnd time of the simulation.\nrequired\n\n\nupdate_timestep\n\nThe output time step of the simulation in seconds (default of 1 day)\nrequired\n\n\ninput_dir\n\nThe directory of the input files.\nrequired\n\n\nresults_dir\n\nThe directory of the results files.\nrequired\n\n\nnetwork\n\nClass containing the topology (nodes and edges) of the model.\nrequired\n\n\nresults\n\nResults configuration options.\nrequired\n\n\nsolver\n\nSolver configuration options.\nrequired\n\n\nlogging\n\nLogging configuration options.\nrequired\n\n\nallocation\n\nThe allocation configuration.\nrequired\n\n\nbasin\nBasin\nThe waterbodies.\nrequired\n\n\nfractional_flow\nFractionalFlow\nSplit flows into fractions.\nrequired\n\n\nlevel_boundary\nLevelBoundary\nBoundary condition specifying the water level.\nrequired\n\n\nflow_boundary\nFlowBoundary\nBoundary conditions specifying the flow.\nrequired\n\n\nlinear_resistance\n\nLinear flow resistance.\nrequired\n\n\nmanning_resistance\nManningResistance\nFlow resistance based on the Manning formula.\nrequired\n\n\ntabulated_rating_curve\nTabulatedRatingCurve\nTabulated rating curve describing flow based on the upstream water level.\nrequired\n\n\npump\nPump\nPrescribed flow rate from one basin to the other.\nrequired\n\n\noutlet\nOutlet\nPrescribed flow rate from one basin to the other.\nrequired\n\n\nterminal\nTerminal\nWater sink without state or properties.\nrequired\n\n\ndiscrete_control\nDiscreteControl\nDiscrete control logic.\nrequired\n\n\npid_control\nPidControl\nPID controller attempting to set the level of a basin to a desired value using a pump/outlet.\nrequired\n\n\nuser\nUser\nUser node type with demand and priority.\nrequired"
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-    "text": "Available node types to model different situations.\n\n\n\nBasin\n\n\n\nFractionalFlow\n\n\n\nTabulatedRatingCurve\n\n\n\nPump\n\n\n\nOutlet\n\n\n\nUser\n\n\n\nLevelBoundary\n\n\n\nFlowBoundary\n\n\n\nLinearResistance\n\n\n\nManningResistance\n\n\n\nTerminal\n\n\n\nDiscreteControl\n\n\n\nPidControl"
+    "text": "Name\nDescription\n\n\n\n\nplot\nPlot the nodes and edges of the model.\n\n\nread\nRead model from TOML file.\n\n\nvalidate_model\nValidate the model.\n\n\nvalidate_model_node_field_ids\nCheck whether the node IDs of the node_type fields are valid.\n\n\nvalidate_model_node_ids\nCheck whether the node IDs in the data tables correspond to the node IDs in the network.\n\n\nwrite\nWrite the contents of the model to disk and save it as a TOML configuration file.\n\n\n\n\n\nModel.plot(ax=None)\nPlot the nodes and edges of the model.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nax\nmatplotlib.pyplot.Artist\nAxes on which to draw the plot.\nNone\n\n\n\n\n\n\n\n\n\nType\nDescription\n\n\n\n\nmatplotlib.pyplot.Artist\n\n\n\n\n\n\n\n\nModel.read(filepath)\nRead model from TOML file.\n\n\n\nModel.validate_model()\nValidate the model.\nChecks: - Whether the node IDs of the node_type fields are valid - Whether the node IDs in the node field correspond to the node IDs on the node type fields\n\n\n\nModel.validate_model_node_field_ids()\nCheck whether the node IDs of the node_type fields are valid.\n\n\n\nModel.validate_model_node_ids()\nCheck whether the node IDs in the data tables correspond to the node IDs in the network.\n\n\n\nModel.write(filepath)\nWrite the contents of the model to disk and save it as a TOML configuration file.\nIf filepath.parent does not exist, it is created before writing.\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nfilepath\nPath | str\n\nrequired"
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-    "text": "1 LevelBoundary\nLevelBoundary()"
+    "text": "Edge()\nDefines the connections between nodes.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nstatic\npandas.DataFrame\nTable describing the flow connections.\nrequired"
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-    "text": "Node()\nThe Ribasim nodes as Point geometries.\n\n\n\n\n\nName\nDescription\n\n\n\n\nconnectivity_from_geometry\nDerive from_node_id and to_node_id for every edge in lines. LineStrings\n\n\ngeometry_from_connectivity\nCreate edge shapely geometries from connectivities.\n\n\nplot\nPlot the nodes. Each node type is given a separate marker.\n\n\n\n\n\nNode.connectivity_from_geometry(lines)\nDerive from_node_id and to_node_id for every edge in lines. LineStrings may be used to connect multiple nodes in a sequence, but every linestring vertex must also a node.\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nnode\nNode\n\nrequired\n\n\nlines\nnp.ndarray\nArray of shapely linestrings.\nrequired\n\n\n\n\n\n\n\n\n\nType\nDescription\n\n\n\n\nnp.ndarray of int\n\n\n\nnp.ndarray of int\n\n\n\n\n\n\n\n\nNode.geometry_from_connectivity(from_id, to_id)\nCreate edge shapely geometries from connectivities.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nnode\nRibasim.Node\n\nrequired\n\n\nfrom_id\nSequence[int]\nFirst node of every edge.\nrequired\n\n\nto_id\nSequence[int]\nSecond node of every edge.\nrequired\n\n\n\n\n\n\n\n\n\nType\nDescription\n\n\n\n\nnp.ndarray\nArray of shapely LineStrings.\n\n\n\n\n\n\n\nNode.plot(ax=None, zorder=None)\nPlot the nodes. Each node type is given a separate marker.\n\n\n\n\n\n\n\n\n\n\n\nName\nType\nDescription\nDefault\n\n\n\n\nax\nOptional\nThe axis on which the nodes will be plotted.\nNone\n\n\n\n\n\n\n\n\n\nType\nDescription\n\n\n\n\nNone"
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+    "text": "1 TabulatedRatingCurve\nTabulatedRatingCurve()"
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-    "text": "The Ribasim Python package (named ribasim) aims to make it easy to build, update and analyze Ribasim models programmatically.\nThe Ribasim QGIS plugin allows users to construct a model from scratch without programming. For specific tasks, like adding observed rainfall timeseries, it can be faster to use Python instead.\nOne can also use Ribasim Python to build entire models from base data, such that your model setup is fully reproducible.\nThe package is registered in PyPI and can therefore be installed with pip:\npip install ribasim\nFor wheel (.whl) downloads, including nightly builds, see the download section. After downloading wheels can be installed by referring to the correct path:\npip install path/to/ribasim-*.whl\nFor documentation please see the examples and API reference."
+    "text": "1 Basic model with static forcing\n\nfrom pathlib import Path\n\nimport geopandas as gpd\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nimport ribasim\n\nSetup the basins:\n\nprofile = pd.DataFrame(\n    data={\n        \"node_id\": [1, 1, 3, 3, 6, 6, 9, 9],\n        \"area\": [0.01, 1000.0] * 4,\n        \"level\": [0.0, 1.0] * 4,\n    }\n)\n\n# Convert steady forcing to m/s\n# 2 mm/d precipitation, 1 mm/d evaporation\nseconds_in_day = 24 * 3600\nprecipitation = 0.002 / seconds_in_day\nevaporation = 0.001 / seconds_in_day\n\nstatic = pd.DataFrame(\n    data={\n        \"node_id\": [0],\n        \"drainage\": [0.0],\n        \"potential_evaporation\": [evaporation],\n        \"infiltration\": [0.0],\n        \"precipitation\": [precipitation],\n        \"urban_runoff\": [0.0],\n    }\n)\nstatic = static.iloc[[0, 0, 0, 0]]\nstatic[\"node_id\"] = [1, 3, 6, 9]\n\nbasin = ribasim.Basin(profile=profile, static=static)\n\nSetup linear resistance:\n\nlinear_resistance = ribasim.LinearResistance(\n    static=pd.DataFrame(\n        data={\"node_id\": [10, 12], \"resistance\": [5e3, (3600.0 * 24) / 100.0]}\n    )\n)\n\nSetup Manning resistance:\n\nmanning_resistance = ribasim.ManningResistance(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [2],\n            \"length\": [900.0],\n            \"manning_n\": [0.04],\n            \"profile_width\": [6.0],\n            \"profile_slope\": [3.0],\n        }\n    )\n)\n\nSet up a rating curve node:\n\n# Discharge: lose 1% of storage volume per day at storage = 1000.0.\nq1000 = 1000.0 * 0.01 / seconds_in_day\n\nrating_curve = ribasim.TabulatedRatingCurve(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [4, 4],\n            \"level\": [0.0, 1.0],\n            \"discharge\": [0.0, q1000],\n        }\n    )\n)\n\nSetup fractional flows:\n\nfractional_flow = ribasim.FractionalFlow(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [5, 8, 13],\n            \"fraction\": [0.3, 0.6, 0.1],\n        }\n    )\n)\n\nSetup pump:\n\npump = ribasim.Pump(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [7],\n            \"flow_rate\": [0.5 / 3600],\n        }\n    )\n)\n\nSetup level boundary:\n\nlevel_boundary = ribasim.LevelBoundary(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [11, 17],\n            \"level\": [0.5, 1.5],\n        }\n    )\n)\n\nSetup flow boundary:\n\nflow_boundary = ribasim.FlowBoundary(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [15, 16],\n            \"flow_rate\": [1e-4, 1e-4],\n        }\n    )\n)\n\nSetup terminal:\n\nterminal = ribasim.Terminal(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [14],\n        }\n    )\n)\n\nSet up the nodes:\n\nxy = np.array(\n    [\n        (0.0, 0.0),  # 1: Basin,\n        (1.0, 0.0),  # 2: ManningResistance\n        (2.0, 0.0),  # 3: Basin\n        (3.0, 0.0),  # 4: TabulatedRatingCurve\n        (3.0, 1.0),  # 5: FractionalFlow\n        (3.0, 2.0),  # 6: Basin\n        (4.0, 1.0),  # 7: Pump\n        (4.0, 0.0),  # 8: FractionalFlow\n        (5.0, 0.0),  # 9: Basin\n        (6.0, 0.0),  # 10: LinearResistance\n        (2.0, 2.0),  # 11: LevelBoundary\n        (2.0, 1.0),  # 12: LinearResistance\n        (3.0, -1.0),  # 13: FractionalFlow\n        (3.0, -2.0),  # 14: Terminal\n        (3.0, 3.0),  # 15: FlowBoundary\n        (0.0, 1.0),  # 16: FlowBoundary\n        (6.0, 1.0),  # 17: LevelBoundary\n    ]\n)\nnode_xy = gpd.points_from_xy(x=xy[:, 0], y=xy[:, 1])\n\nnode_id, node_type = ribasim.Node.node_ids_and_types(\n    basin,\n    manning_resistance,\n    rating_curve,\n    pump,\n    fractional_flow,\n    linear_resistance,\n    level_boundary,\n    flow_boundary,\n    terminal,\n)\n\n# Make sure the feature id starts at 1: explicitly give an index.\nnode = ribasim.Node(\n    df=gpd.GeoDataFrame(\n        data={\"type\": node_type},\n        index=pd.Index(node_id, name=\"fid\"),\n        geometry=node_xy,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup the edges:\n\nfrom_id = np.array(\n    [1, 2, 3, 4, 4, 5, 6, 8, 7, 9, 11, 12, 4, 13, 15, 16, 10], dtype=np.int64\n)\nto_id = np.array(\n    [2, 3, 4, 5, 8, 6, 7, 9, 9, 10, 12, 3, 13, 14, 6, 1, 17], dtype=np.int64\n)\nlines = node.geometry_from_connectivity(from_id, to_id)\nedge = ribasim.Edge(\n    df=gpd.GeoDataFrame(\n        data={\n            \"from_node_id\": from_id,\n            \"to_node_id\": to_id,\n            \"edge_type\": len(from_id) * [\"flow\"],\n        },\n        geometry=lines,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup a model:\n\nmodel = ribasim.Model(\n    network=ribasim.Network(\n        node=node,\n        edge=edge,\n    ),\n    basin=basin,\n    level_boundary=level_boundary,\n    flow_boundary=flow_boundary,\n    pump=pump,\n    linear_resistance=linear_resistance,\n    manning_resistance=manning_resistance,\n    tabulated_rating_curve=rating_curve,\n    fractional_flow=fractional_flow,\n    terminal=terminal,\n    starttime=\"2020-01-01 00:00:00\",\n    endtime=\"2021-01-01 00:00:00\",\n)\n\nLet’s take a look at the model:\n\nmodel.plot()\n\n&lt;Axes: &gt;\n\n\n\n\n\nWrite the model to a TOML and GeoPackage:\n\ndatadir = Path(\"data\")\nmodel.write(datadir / \"basic/ribasim.toml\")\n\nPosixPath('data/basic/ribasim.toml')\n\n\n\n\n2 Update the basic model with transient forcing\nThis assumes you have already created the basic model with static forcing.\n\nimport numpy as np\nimport pandas as pd\nimport ribasim\nimport xarray as xr\n\n\nmodel = ribasim.Model(filepath=datadir / \"basic/ribasim.toml\")\n\n\ntime = pd.date_range(model.starttime, model.endtime)\nday_of_year = time.day_of_year.to_numpy()\nseconds_per_day = 24 * 60 * 60\nevaporation = (\n    (-1.0 * np.cos(day_of_year / 365.0 * 2 * np.pi) + 1.0) * 0.0025 / seconds_per_day\n)\nrng = np.random.default_rng(seed=0)\nprecipitation = (\n    rng.lognormal(mean=-1.0, sigma=1.7, size=time.size) * 0.001 / seconds_per_day\n)\n\nWe’ll use xarray to easily broadcast the values.\n\ntimeseries = (\n    pd.DataFrame(\n        data={\n            \"node_id\": 1,\n            \"time\": pd.date_range(model.starttime, model.endtime),\n            \"drainage\": 0.0,\n            \"potential_evaporation\": evaporation,\n            \"infiltration\": 0.0,\n            \"precipitation\": precipitation,\n            \"urban_runoff\": 0.0,\n        }\n    )\n    .set_index(\"time\")\n    .to_xarray()\n)\n\nbasin_ids = model.basin.static.df[\"node_id\"].to_numpy()\nbasin_nodes = xr.DataArray(\n    np.ones(len(basin_ids)), coords={\"node_id\": basin_ids}, dims=[\"node_id\"]\n)\nforcing = (timeseries * basin_nodes).to_dataframe().reset_index()\n\n\nstate = pd.DataFrame(\n    data={\n        \"node_id\": basin_ids,\n        \"level\": 1.4,\n    }\n)\n\n\nmodel.basin.time.df = forcing\nmodel.basin.state.df = state\n\n\nmodel.write(datadir / \"basic_transient/ribasim.toml\")\n\nPosixPath('data/basic_transient/ribasim.toml')\n\n\nNow run the model with ribasim basic_transient/ribasim.toml. After running the model, read back the results:\n\ndf_basin = pd.read_feather(datadir / \"basic_transient/results/basin.arrow\")\ndf_basin_wide = df_basin.pivot_table(\n    index=\"time\", columns=\"node_id\", values=[\"storage\", \"level\"]\n)\ndf_basin_wide[\"level\"].plot()\n\n&lt;Axes: xlabel='time'&gt;\n\n\n\n\n\n\ndf_flow = pd.read_feather(datadir / \"basic_transient/results/flow.arrow\")\ndf_flow[\"edge\"] = list(zip(df_flow.from_node_id, df_flow.to_node_id))\ndf_flow[\"flow_m3d\"] = df_flow.flow * 86400\nax = df_flow.pivot_table(index=\"time\", columns=\"edge\", values=\"flow_m3d\").plot()\nax.legend(bbox_to_anchor=(1.3, 1), title=\"Edge\")\n\n&lt;matplotlib.legend.Legend at 0x7f8f0637bd10&gt;\n\n\n\n\n\n\ntype(df_flow)\n\npandas.core.frame.DataFrame\n\n\n\n\n3 Model with discrete control\nThe model constructed below consists of a single basin which slowly drains trough a TabulatedRatingCurve, but is held within a range around a target level (setpoint) by two connected pumps. These two pumps behave like a reversible pump. When pumping can be done in only one direction, and the other direction is only possible under gravity, use an Outlet for that direction.\nSet up the nodes:\n\nxy = np.array(\n    [\n        (0.0, 0.0),  # 1: Basin\n        (1.0, 1.0),  # 2: Pump\n        (1.0, -1.0),  # 3: Pump\n        (2.0, 0.0),  # 4: LevelBoundary\n        (-1.0, 0.0),  # 5: TabulatedRatingCurve\n        (-2.0, 0.0),  # 6: Terminal\n        (1.0, 0.0),  # 7: DiscreteControl\n    ]\n)\n\nnode_xy = gpd.points_from_xy(x=xy[:, 0], y=xy[:, 1])\n\nnode_type = [\n    \"Basin\",\n    \"Pump\",\n    \"Pump\",\n    \"LevelBoundary\",\n    \"TabulatedRatingCurve\",\n    \"Terminal\",\n    \"DiscreteControl\",\n]\n\n# Make sure the feature id starts at 1: explicitly give an index.\nnode = ribasim.Node(\n    df=gpd.GeoDataFrame(\n        data={\"type\": node_type},\n        index=pd.Index(np.arange(len(xy)) + 1, name=\"fid\"),\n        geometry=node_xy,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup the edges:\n\nfrom_id = np.array([1, 3, 4, 2, 1, 5, 7, 7], dtype=np.int64)\nto_id = np.array([3, 4, 2, 1, 5, 6, 2, 3], dtype=np.int64)\n\nedge_type = 6 * [\"flow\"] + 2 * [\"control\"]\n\nlines = node.geometry_from_connectivity(from_id, to_id)\nedge = ribasim.Edge(\n    df=gpd.GeoDataFrame(\n        data={\"from_node_id\": from_id, \"to_node_id\": to_id, \"edge_type\": edge_type},\n        geometry=lines,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup the basins:\n\nprofile = pd.DataFrame(\n    data={\n        \"node_id\": [1, 1],\n        \"area\": [1000.0, 1000.0],\n        \"level\": [0.0, 1.0],\n    }\n)\n\nstatic = pd.DataFrame(\n    data={\n        \"node_id\": [1],\n        \"drainage\": [0.0],\n        \"potential_evaporation\": [0.0],\n        \"infiltration\": [0.0],\n        \"precipitation\": [0.0],\n        \"urban_runoff\": [0.0],\n    }\n)\n\nstate = pd.DataFrame(data={\"node_id\": [1], \"level\": [20.0]})\n\nbasin = ribasim.Basin(profile=profile, static=static, state=state)\n\nSetup the discrete control:\n\ncondition = pd.DataFrame(\n    data={\n        \"node_id\": 3 * [7],\n        \"listen_feature_id\": 3 * [1],\n        \"variable\": 3 * [\"level\"],\n        \"greater_than\": [5.0, 10.0, 15.0],  # min, setpoint, max\n    }\n)\n\nlogic = pd.DataFrame(\n    data={\n        \"node_id\": 5 * [7],\n        \"truth_state\": [\"FFF\", \"U**\", \"T*F\", \"**D\", \"TTT\"],\n        \"control_state\": [\"in\", \"in\", \"none\", \"out\", \"out\"],\n    }\n)\n\ndiscrete_control = ribasim.DiscreteControl(condition=condition, logic=logic)\n\nThe above control logic can be summarized as follows: - If the level gets above the maximum, activate the control state “out” until the setpoint is reached; - If the level gets below the minimum, active the control state “in” until the setpoint is reached; - Otherwise activate the control state “none”.\nSetup the pump:\n\npump = ribasim.Pump(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": 3 * [2] + 3 * [3],\n            \"control_state\": 2 * [\"none\", \"in\", \"out\"],\n            \"flow_rate\": [0.0, 2e-3, 0.0, 0.0, 0.0, 2e-3],\n        }\n    )\n)\n\nThe pump data defines the following:\n\n\n\nControl state\nPump #2 flow rate (m/s)\nPump #3 flow rate (m/s)\n\n\n\n\n“none”\n0.0\n0.0\n\n\n“in”\n2e-3\n0.0\n\n\n“out”\n0.0\n2e-3\n\n\n\nSetup the level boundary:\n\nlevel_boundary = ribasim.LevelBoundary(\n    static=pd.DataFrame(data={\"node_id\": [4], \"level\": [10.0]})\n)\n\nSetup the rating curve:\n\nrating_curve = ribasim.TabulatedRatingCurve(\n    static=pd.DataFrame(\n        data={\"node_id\": 2 * [5], \"level\": [2.0, 15.0], \"discharge\": [0.0, 1e-3]}\n    )\n)\n\nSetup the terminal:\n\nterminal = ribasim.Terminal(static=pd.DataFrame(data={\"node_id\": [6]}))\n\nSetup a model:\n\nmodel = ribasim.Model(\n    network=ribasim.Network(\n        node=node,\n        edge=edge,\n    ),\n    basin=basin,\n    pump=pump,\n    level_boundary=level_boundary,\n    tabulated_rating_curve=rating_curve,\n    terminal=terminal,\n    discrete_control=discrete_control,\n    starttime=\"2020-01-01 00:00:00\",\n    endtime=\"2021-01-01 00:00:00\",\n)\n\nLet’s take a look at the model:\n\nmodel.plot()\n\n&lt;Axes: &gt;\n\n\n\n\n\nListen edges are plotted with a dashed line since they are not present in the “Edge / static” schema but only in the “Control / condition” schema.\n\ndatadir = Path(\"data\")\nmodel.write(datadir / \"level_setpoint_with_minmax/ribasim.toml\")\n\nPosixPath('data/level_setpoint_with_minmax/ribasim.toml')\n\n\nNow run the model with level_setpoint_with_minmax/ribasim.toml. After running the model, read back the results:\n\nfrom matplotlib.dates import date2num\n\ndf_basin = pd.read_feather(datadir / \"level_setpoint_with_minmax/results/basin.arrow\")\ndf_basin_wide = df_basin.pivot_table(\n    index=\"time\", columns=\"node_id\", values=[\"storage\", \"level\"]\n)\n\nax = df_basin_wide[\"level\"].plot()\n\ngreater_than = model.discrete_control.condition.df.greater_than\n\nax.hlines(\n    greater_than,\n    df_basin.time[0],\n    df_basin.time.max(),\n    lw=1,\n    ls=\"--\",\n    color=\"k\",\n)\n\ndf_control = pd.read_feather(\n    datadir / \"level_setpoint_with_minmax/results/control.arrow\"\n)\n\ny_min, y_max = ax.get_ybound()\nax.fill_between(df_control.time[:2], 2 * [y_min], 2 * [y_max], alpha=0.2, color=\"C0\")\nax.fill_between(df_control.time[2:4], 2 * [y_min], 2 * [y_max], alpha=0.2, color=\"C0\")\n\nax.set_xticks(\n    date2num(df_control.time).tolist(),\n    df_control.control_state.tolist(),\n    rotation=50,\n)\n\nax.set_yticks(greater_than, [\"min\", \"setpoint\", \"max\"])\nax.set_ylabel(\"level\")\nplt.show()\n\n\n\n\nThe highlighted regions show where a pump is active.\nLet’s print an overview of what happened with control:\n\nmodel.print_discrete_control_record(\n    datadir / \"level_setpoint_with_minmax/results/control.arrow\"\n)\n\n0. At 2020-01-01 00:00:00 the control node with ID 7 reached truth state TTT:\n    For node ID 1 (Basin): level &gt; 5.0\n    For node ID 1 (Basin): level &gt; 10.0\n    For node ID 1 (Basin): level &gt; 15.0\n\n   This yielded control state \"out\":\n    For node ID 2 (Pump): flow_rate = 0.0\n    For node ID 3 (Pump): flow_rate = 0.002\n\n1. At 2020-02-08 19:02:21.861000 the control node with ID 7 reached truth state TFF:\n    For node ID 1 (Basin): level &gt; 5.0\n    For node ID 1 (Basin): level &lt; 10.0\n    For node ID 1 (Basin): level &lt; 15.0\n\n   This yielded control state \"none\":\n    For node ID 2 (Pump): flow_rate = 0.0\n    For node ID 3 (Pump): flow_rate = 0.0\n\n2. At 2020-07-05 08:56:10.319000 the control node with ID 7 reached truth state FFF:\n    For node ID 1 (Basin): level &lt; 5.0\n    For node ID 1 (Basin): level &lt; 10.0\n    For node ID 1 (Basin): level &lt; 15.0\n\n   This yielded control state \"in\":\n    For node ID 2 (Pump): flow_rate = 0.002\n    For node ID 3 (Pump): flow_rate = 0.0\n\n3. At 2020-08-11 06:05:15.592000 the control node with ID 7 reached truth state TTF:\n    For node ID 1 (Basin): level &gt; 5.0\n    For node ID 1 (Basin): level &gt; 10.0\n    For node ID 1 (Basin): level &lt; 15.0\n\n   This yielded control state \"none\":\n    For node ID 2 (Pump): flow_rate = 0.0\n    For node ID 3 (Pump): flow_rate = 0.0\n\n\n\nNote that crossing direction specific truth states (containing “U”, “D”) are not present in this overview even though they are part of the control logic. This is because in the control logic for this model these truth states are only used to sustain control states, while the overview only shows changes in control states.\n\n\n4 Model with PID control\nSet up the nodes:\n\nxy = np.array(\n    [\n        (0.0, 0.0),  # 1: FlowBoundary\n        (1.0, 0.0),  # 2: Basin\n        (2.0, 0.5),  # 3: Pump\n        (3.0, 0.0),  # 4: LevelBoundary\n        (1.5, 1.0),  # 5: PidControl\n        (2.0, -0.5),  # 6: outlet\n        (1.5, -1.0),  # 7: PidControl\n    ]\n)\n\nnode_xy = gpd.points_from_xy(x=xy[:, 0], y=xy[:, 1])\n\nnode_type = [\n    \"FlowBoundary\",\n    \"Basin\",\n    \"Pump\",\n    \"LevelBoundary\",\n    \"PidControl\",\n    \"Outlet\",\n    \"PidControl\",\n]\n\n# Make sure the feature id starts at 1: explicitly give an index.\nnode = ribasim.Node(\n    df=gpd.GeoDataFrame(\n        data={\"type\": node_type},\n        index=pd.Index(np.arange(len(xy)) + 1, name=\"fid\"),\n        geometry=node_xy,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup the edges:\n\nfrom_id = np.array([1, 2, 3, 4, 6, 5, 7], dtype=np.int64)\nto_id = np.array([2, 3, 4, 6, 2, 3, 6], dtype=np.int64)\n\nlines = node.geometry_from_connectivity(from_id, to_id)\nedge = ribasim.Edge(\n    df=gpd.GeoDataFrame(\n        data={\n            \"from_node_id\": from_id,\n            \"to_node_id\": to_id,\n            \"edge_type\": 5 * [\"flow\"] + 2 * [\"control\"],\n        },\n        geometry=lines,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup the basins:\n\nprofile = pd.DataFrame(\n    data={\"node_id\": [2, 2], \"level\": [0.0, 1.0], \"area\": [1000.0, 1000.0]}\n)\n\nstatic = pd.DataFrame(\n    data={\n        \"node_id\": [2],\n        \"drainage\": [0.0],\n        \"potential_evaporation\": [0.0],\n        \"infiltration\": [0.0],\n        \"precipitation\": [0.0],\n        \"urban_runoff\": [0.0],\n    }\n)\n\nstate = pd.DataFrame(\n    data={\n        \"node_id\": [2],\n        \"level\": [6.0],\n    }\n)\n\nbasin = ribasim.Basin(profile=profile, static=static, state=state)\n\nSetup the pump:\n\npump = ribasim.Pump(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [3],\n            \"flow_rate\": [0.0],  # Will be overwritten by PID controller\n        }\n    )\n)\n\nSetup the outlet:\n\noutlet = ribasim.Outlet(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [6],\n            \"flow_rate\": [0.0],  # Will be overwritten by PID controller\n        }\n    )\n)\n\nSetup flow boundary:\n\nflow_boundary = ribasim.FlowBoundary(\n    static=pd.DataFrame(data={\"node_id\": [1], \"flow_rate\": [1e-3]})\n)\n\nSetup flow boundary:\n\nlevel_boundary = ribasim.LevelBoundary(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [4],\n            \"level\": [1.0],  # Not relevant\n        }\n    )\n)\n\nSetup PID control:\n\npid_control = ribasim.PidControl(\n    time=pd.DataFrame(\n        data={\n            \"node_id\": 4 * [5, 7],\n            \"time\": [\n                \"2020-01-01 00:00:00\",\n                \"2020-01-01 00:00:00\",\n                \"2020-05-01 00:00:00\",\n                \"2020-05-01 00:00:00\",\n                \"2020-07-01 00:00:00\",\n                \"2020-07-01 00:00:00\",\n                \"2020-12-01 00:00:00\",\n                \"2020-12-01 00:00:00\",\n            ],\n            \"listen_node_id\": 4 * [2, 2],\n            \"target\": [5.0, 5.0, 5.0, 5.0, 7.5, 7.5, 7.5, 7.5],\n            \"proportional\": 4 * [-1e-3, 1e-3],\n            \"integral\": 4 * [-1e-7, 1e-7],\n            \"derivative\": 4 * [0.0, 0.0],\n        }\n    )\n)\n\nNote that the coefficients for the pump and the outlet are equal in magnitude but opposite in sign. This way the pump and the outlet equally work towards the same goal, while having opposite effects on the controlled basin due to their connectivity to this basin.\nSetup a model:\n\nmodel = ribasim.Model(\n    network=ribasim.Network(\n        node=node,\n        edge=edge,\n    ),\n    basin=basin,\n    flow_boundary=flow_boundary,\n    level_boundary=level_boundary,\n    pump=pump,\n    outlet=outlet,\n    pid_control=pid_control,\n    starttime=\"2020-01-01 00:00:00\",\n    endtime=\"2020-12-01 00:00:00\",\n)\n\nLet’s take a look at the model:\n\nmodel.plot()\n\n&lt;Axes: &gt;\n\n\n\n\n\nWrite the model to a TOML and GeoPackage:\n\ndatadir = Path(\"data\")\nmodel.write(datadir / \"pid_control/ribasim.toml\")\n\nPosixPath('data/pid_control/ribasim.toml')\n\n\nNow run the model with ribasim pid_control/ribasim.toml. After running the model, read back the results:\n\nfrom matplotlib.dates import date2num\n\ndf_basin = pd.read_feather(datadir / \"pid_control/results/basin.arrow\")\ndf_basin_wide = df_basin.pivot_table(\n    index=\"time\", columns=\"node_id\", values=[\"storage\", \"level\"]\n)\nax = df_basin_wide[\"level\"].plot()\nax.set_ylabel(\"level [m]\")\n\n# Plot target level\ntarget_levels = model.pid_control.time.df.target.to_numpy()[:4]\ntimes = date2num(model.pid_control.time.df.time)[:4]\nax.plot(times, target_levels, color=\"k\", ls=\":\", label=\"target level\")\npass\n\n\n\n\n\n\n5 Model with allocation\nSetup the nodes:\n\nxy = np.array(\n    [\n        (0.0, 0.0),  # 1: FlowBoundary\n        (1.0, 0.0),  # 2: Basin\n        (1.0, 1.0),  # 3: User\n        (2.0, 0.0),  # 4: LinearResistance\n        (3.0, 0.0),  # 5: Basin\n        (3.0, 1.0),  # 6: User\n        (4.0, 0.0),  # 7: TabulatedRatingCurve\n        (4.5, 0.0),  # 8: FractionalFlow\n        (4.5, 0.5),  # 9: FractionalFlow\n        (5.0, 0.0),  # 10: Terminal\n        (4.5, 0.25),  # 11: DiscreteControl\n        (4.5, 1.0),  # 12: Basin\n        (5.0, 1.0),  # 13: User\n    ]\n)\nnode_xy = gpd.points_from_xy(x=xy[:, 0], y=xy[:, 1])\n\nnode_type = [\n    \"FlowBoundary\",\n    \"Basin\",\n    \"User\",\n    \"LinearResistance\",\n    \"Basin\",\n    \"User\",\n    \"TabulatedRatingCurve\",\n    \"FractionalFlow\",\n    \"FractionalFlow\",\n    \"Terminal\",\n    \"DiscreteControl\",\n    \"Basin\",\n    \"User\",\n]\n\n# All nodes belong to allocation network id 1\nnode = ribasim.Node(\n    df=gpd.GeoDataFrame(\n        data={\"type\": node_type, \"allocation_network_id\": 1},\n        index=pd.Index(np.arange(len(xy)) + 1, name=\"fid\"),\n        geometry=node_xy,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup the edges:\n\nfrom_id = np.array(\n    [1, 2, 2, 4, 5, 5, 7, 3, 6, 7, 8, 9, 12, 13, 11, 11],\n    dtype=np.int64,\n)\nto_id = np.array(\n    [2, 3, 4, 5, 6, 7, 8, 2, 5, 9, 10, 12, 13, 10, 8, 9],\n    dtype=np.int64,\n)\n# Denote the first edge, 1 =&gt; 2, as a source edge for\n# allocation network 1\nallocation_network_id = len(from_id) * [None]\nallocation_network_id[0] = 1\nlines = node.geometry_from_connectivity(from_id, to_id)\nedge = ribasim.Edge(\n    df=gpd.GeoDataFrame(\n        data={\n            \"from_node_id\": from_id,\n            \"to_node_id\": to_id,\n            \"edge_type\": (len(from_id) - 2) * [\"flow\"] + 2 * [\"control\"],\n            \"allocation_network_id\": allocation_network_id,\n        },\n        geometry=lines,\n        crs=\"EPSG:28992\",\n    )\n)\n\nSetup the basins:\n\nprofile = pd.DataFrame(\n    data={\n        \"node_id\": [2, 2, 5, 5, 12, 12],\n        \"area\": 300_000.0,\n        \"level\": 3 * [0.0, 1.0],\n    }\n)\n\nstatic = pd.DataFrame(\n    data={\n        \"node_id\": [2, 5, 12],\n        \"drainage\": 0.0,\n        \"potential_evaporation\": 0.0,\n        \"infiltration\": 0.0,\n        \"precipitation\": 0.0,\n        \"urban_runoff\": 0.0,\n    }\n)\n\nstate = pd.DataFrame(data={\"node_id\": [2, 5, 12], \"level\": 1.0})\n\nbasin = ribasim.Basin(profile=profile, static=static, state=state)\n\nSetup the flow boundary:\n\nflow_boundary = ribasim.FlowBoundary(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [1],\n            \"flow_rate\": 2.0,\n        }\n    )\n)\n\nSetup the linear resistance:\n\nlinear_resistance = ribasim.LinearResistance(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [4],\n            \"resistance\": 0.06,\n        }\n    )\n)\n\nSetup the tabulated rating curve:\n\ntabulated_rating_curve = ribasim.TabulatedRatingCurve(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": 7,\n            \"level\": [0.0, 0.5, 1.0],\n            \"discharge\": [0.0, 0.0, 2.0],\n        }\n    )\n)\n\nSetup the fractional flow:\n\nfractional_flow = ribasim.FractionalFlow(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [8, 8, 9, 9],\n            \"fraction\": [0.6, 0.9, 0.4, 0.1],\n            \"control_state\": [\"divert\", \"close\", \"divert\", \"close\"],\n        }\n    )\n)\n\nSetup the terminal:\n\nterminal = ribasim.Terminal(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [10],\n        }\n    )\n)\n\nSetup the discrete control:\n\ncondition = pd.DataFrame(\n    data={\n        \"node_id\": [11],\n        \"listen_feature_id\": 5,\n        \"variable\": \"level\",\n        \"greater_than\": 0.52,\n    }\n)\n\nlogic = pd.DataFrame(\n    data={\n        \"node_id\": 11,\n        \"truth_state\": [\"T\", \"F\"],\n        \"control_state\": [\"divert\", \"close\"],\n    }\n)\n\ndiscrete_control = ribasim.DiscreteControl(condition=condition, logic=logic)\n\nSetup the users:\n\nuser = ribasim.User(\n    static=pd.DataFrame(\n        data={\n            \"node_id\": [6, 13],\n            \"demand\": [1.5, 1.0],\n            \"return_factor\": 0.0,\n            \"min_level\": -1.0,\n            \"priority\": [1, 3],\n        }\n    ),\n    time=pd.DataFrame(\n        data={\n            \"node_id\": [3, 3, 3, 3],\n            \"demand\": [0.0, 1.0, 1.2, 1.2],\n            \"priority\": [1, 1, 2, 2],\n            \"return_factor\": 0.0,\n            \"min_level\": -1.0,\n            \"time\": 2 * [\"2020-01-01 00:00:00\", \"2020-01-20 00:00:00\"],\n        }\n    ),\n)\n\nSetup the allocation:\n\nallocation = ribasim.Allocation(use_allocation=True, timestep=86400)\n\nSetup a model:\n\nmodel = ribasim.Model(\n    network=ribasim.Network(\n        node=node,\n        edge=edge,\n    ),\n    basin=basin,\n    flow_boundary=flow_boundary,\n    linear_resistance=linear_resistance,\n    tabulated_rating_curve=tabulated_rating_curve,\n    terminal=terminal,\n    user=user,\n    discrete_control=discrete_control,\n    fractional_flow=fractional_flow,\n    allocation=allocation,\n    starttime=\"2020-01-01 00:00:00\",\n    endtime=\"2020-01-20 00:00:00\",\n)\n\nLet’s take a look at the model:\n\nmodel.plot()\n\n&lt;Axes: &gt;\n\n\n\n\n\nWrite the model to a TOML and GeoPackage:\n\ndatadir = Path(\"data\")\nmodel.write(datadir / \"allocation_example/ribasim.toml\")\n\nPosixPath('data/allocation_example/ribasim.toml')\n\n\nNow run the model with ribasim allocation_example/ribasim.toml. After running the model, read back the results:\n\nimport matplotlib.ticker as plticker\n\ndf_allocation = pd.read_feather(datadir / \"allocation_example/results/allocation.arrow\")\ndf_allocation_wide = df_allocation.pivot_table(\n    index=\"time\",\n    columns=[\"user_node_id\", \"priority\"],\n    values=[\"demand\", \"allocated\", \"abstracted\"],\n)\ndf_allocation_wide = df_allocation_wide.loc[:, (df_allocation_wide != 0).any(axis=0)]\n\nfig, axs = plt.subplots(1, 3, figsize=(8, 5))\nfig.suptitle(f\"Objective type: {model.allocation.objective_type}\", fontweight=\"bold\")\n\ndf_allocation_wide[\"demand\"].plot(ax=axs[0], ls=\":\")\ndf_allocation_wide[\"allocated\"].plot(ax=axs[1], ls=\"--\")\ndf_allocation_wide[\"abstracted\"].plot(ax=axs[2])\n\nfig.tight_layout()\nloc = plticker.MultipleLocator(2)\n\naxs[0].set_ylabel(\"level [m]\")\n\nfor ax, title in zip(axs, [\"Demand\", \"Allocated\", \"Abstracted\"]):\n    ax.set_title(title)\n    ax.set_ylim(0.0, 1.6)\n    ax.xaxis.set_major_locator(loc)\n\n\n\n\nSome things to note about this plot:\n\nAbstraction behaves somewhat erratically at the start of the simulation. This is because allocation is based on flows computed in the physical layer, and at the start of the simulation these are not known yet.\nAlthough there is a plotted line for abstraction per priority, abstraction is actually accumulated over all priorities per user.\n\n\ndf_basin = pd.read_feather(datadir / \"allocation_example/results/basin.arrow\")\ndf_basin_wide = df_basin.pivot_table(\n    index=\"time\", columns=\"node_id\", values=[\"storage\", \"level\"]\n)\n\nax = df_basin_wide[\"level\"].plot()\nax.set_title(\"Basin levels\")\nax.set_ylabel(\"level [m]\")\n\nText(0, 0.5, 'level [m]')"
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