Code
using Ribasim
@@ -648,44 +648,44 @@ println(p.allocation.allocation_models[1].problem)
Min F_abs_user_demand[UserDemand #6] + F_abs_user_demand[UserDemand #3] + F_abs_user_demand[UserDemand #13] + F_abs_basin[Basin #5] + F_abs_basin[Basin #2] + F_abs_basin[Basin #12]
+Min F_abs_user_demand[UserDemand #13] + F_abs_user_demand[UserDemand #3] + F_abs_user_demand[UserDemand #6] + F_abs_basin[Basin #2] + F_abs_basin[Basin #5] + F_abs_basin[Basin #12]
Subject to
- flow_conservation[Basin #5] : -F[(Basin #2, Basin #5)] + F[(Basin #5, TabulatedRatingCurve #7)] + F[(Basin #5, UserDemand #6)] + F[(Basin #5, Basin #2)] + F_basin_in[Basin #5] - F_basin_out[Basin #5] = 0
- flow_conservation[Basin #2] : F[(Basin #2, Basin #5)] + F[(Basin #2, UserDemand #3)] - F[(Basin #5, Basin #2)] - F[(FlowBoundary #1, Basin #2)] + F_basin_in[Basin #2] - F_basin_out[Basin #2] = 0
- flow_conservation[Basin #12] : -F[(TabulatedRatingCurve #7, Basin #12)] + F[(Basin #12, UserDemand #13)] + F_basin_in[Basin #12] - F_basin_out[Basin #12] = 0
- abs_positive_user_demand[UserDemand #6] : -F[(Basin #5, UserDemand #6)] + F_abs_user_demand[UserDemand #6] ≥ -1.5
- abs_positive_user_demand[UserDemand #3] : -F[(Basin #2, UserDemand #3)] + F_abs_user_demand[UserDemand #3] ≥ 0
+ flow_conservation[Basin #2] : F[(Basin #2, UserDemand #3)] - F[(FlowBoundary #1, Basin #2)] + F[(Basin #2, Basin #5)] - F[(Basin #5, Basin #2)] + F_basin_in[Basin #2] - F_basin_out[Basin #2] = 0
+ flow_conservation[Basin #5] : F[(Basin #5, TabulatedRatingCurve #7)] + F[(Basin #5, UserDemand #6)] - F[(Basin #2, Basin #5)] + F[(Basin #5, Basin #2)] + F_basin_in[Basin #5] - F_basin_out[Basin #5] = 0
+ flow_conservation[Basin #12] : F[(Basin #12, UserDemand #13)] - F[(TabulatedRatingCurve #7, Basin #12)] + F_basin_in[Basin #12] - F_basin_out[Basin #12] = 0
abs_positive_user_demand[UserDemand #13] : -F[(Basin #12, UserDemand #13)] + F_abs_user_demand[UserDemand #13] ≥ 0
- abs_negative_user_demand[UserDemand #6] : F[(Basin #5, UserDemand #6)] + F_abs_user_demand[UserDemand #6] ≥ 1.5
- abs_negative_user_demand[UserDemand #3] : F[(Basin #2, UserDemand #3)] + F_abs_user_demand[UserDemand #3] ≥ 0
+ abs_positive_user_demand[UserDemand #3] : -F[(Basin #2, UserDemand #3)] + F_abs_user_demand[UserDemand #3] ≥ 0
+ abs_positive_user_demand[UserDemand #6] : -F[(Basin #5, UserDemand #6)] + F_abs_user_demand[UserDemand #6] ≥ -1.5
abs_negative_user_demand[UserDemand #13] : F[(Basin #12, UserDemand #13)] + F_abs_user_demand[UserDemand #13] ≥ 0
- abs_positive_basin[Basin #5] : -F_basin_in[Basin #5] + F_abs_basin[Basin #5] ≥ 0
+ abs_negative_user_demand[UserDemand #3] : F[(Basin #2, UserDemand #3)] + F_abs_user_demand[UserDemand #3] ≥ 0
+ abs_negative_user_demand[UserDemand #6] : F[(Basin #5, UserDemand #6)] + F_abs_user_demand[UserDemand #6] ≥ 1.5
abs_positive_basin[Basin #2] : -F_basin_in[Basin #2] + F_abs_basin[Basin #2] ≥ 0
+ abs_positive_basin[Basin #5] : -F_basin_in[Basin #5] + F_abs_basin[Basin #5] ≥ 0
abs_positive_basin[Basin #12] : -F_basin_in[Basin #12] + F_abs_basin[Basin #12] ≥ 0
- abs_negative_basin[Basin #5] : F_basin_in[Basin #5] + F_abs_basin[Basin #5] ≥ 0
abs_negative_basin[Basin #2] : F_basin_in[Basin #2] + F_abs_basin[Basin #2] ≥ 0
+ abs_negative_basin[Basin #5] : F_basin_in[Basin #5] + F_abs_basin[Basin #5] ≥ 0
abs_negative_basin[Basin #12] : F_basin_in[Basin #12] + F_abs_basin[Basin #12] ≥ 0
source[(FlowBoundary #1, Basin #2)] : F[(FlowBoundary #1, Basin #2)] ≤ 1
return_flow[UserDemand #13] : F[(UserDemand #13, Terminal #10)] ≤ 0
- fractional_flow[(TabulatedRatingCurve #7, Basin #12)] : F[(TabulatedRatingCurve #7, Basin #12)] - 0.4 F[(Basin #5, TabulatedRatingCurve #7)] ≤ 0
- basin_outflow[Basin #5] : F_basin_out[Basin #5] ≤ 0
+ fractional_flow[(TabulatedRatingCurve #7, Basin #12)] : -0.4 F[(Basin #5, TabulatedRatingCurve #7)] + F[(TabulatedRatingCurve #7, Basin #12)] ≤ 0
basin_outflow[Basin #2] : F_basin_out[Basin #2] ≤ 0
+ basin_outflow[Basin #5] : F_basin_out[Basin #5] ≤ 0
basin_outflow[Basin #12] : F_basin_out[Basin #12] ≤ 0
- F[(TabulatedRatingCurve #7, Basin #12)] ≥ 0
- F[(Basin #2, Basin #5)] ≥ 0
F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0
F[(Basin #12, UserDemand #13)] ≥ 0
F[(Basin #2, UserDemand #3)] ≥ 0
F[(Basin #5, UserDemand #6)] ≥ 0
- F[(TabulatedRatingCurve #7, Terminal #10)] ≥ 0
- F[(Basin #5, Basin #2)] ≥ 0
F[(FlowBoundary #1, Basin #2)] ≥ 0
+ F[(Basin #2, Basin #5)] ≥ 0
+ F[(TabulatedRatingCurve #7, Basin #12)] ≥ 0
+ F[(Basin #5, Basin #2)] ≥ 0
+ F[(TabulatedRatingCurve #7, Terminal #10)] ≥ 0
F[(UserDemand #13, Terminal #10)] ≥ 0
- F_basin_in[Basin #5] ≥ 0
F_basin_in[Basin #2] ≥ 0
+ F_basin_in[Basin #5] ≥ 0
F_basin_in[Basin #12] ≥ 0
- F_basin_out[Basin #5] ≥ 0
F_basin_out[Basin #2] ≥ 0
+ F_basin_out[Basin #5] ≥ 0
F_basin_out[Basin #12] ≥ 0
Here \(p > 0\) is the threshold value which determines the interval \([0,p]\) of the smooth transition between \(0\) and \(1\), see the plot below.
-
+
Code
import numpy as np
diff --git a/core/validation.html b/core/validation.html
index 474d387c2..0b8663bfc 100644
--- a/core/validation.html
+++ b/core/validation.html
@@ -262,7 +262,7 @@ Validation
1 Connectivity
In the table below, each column shows which node types are allowed to be downstream (or ‘down-control’) of the node type at the top of the column.
-
+
Code
using Ribasim
@@ -546,7 +546,7 @@ 1 Connectivity
2 Neighbor amounts
The table below shows for each node type between which bounds the amount of in- and outneighbors must be, for both flow and control edges.
-
+
Code
= Vector{String}()
diff --git a/python/examples_files/figure-html/cell-71-output-1.png b/python/examples_files/figure-html/cell-71-output-1.png
index 933e31732e59c8c4fbb04f446c5eac7e3da2d350..3ef67556a4b1daf5bd1e46703b82c70452f4ebdb 100644
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Here \(p > 0\) is the threshold value which determines the interval \([0,p]\) of the smooth transition between \(0\) and \(1\), see the plot below.
-Code
import numpy as np
diff --git a/core/validation.html b/core/validation.html
index 474d387c2..0b8663bfc 100644
--- a/core/validation.html
+++ b/core/validation.html
@@ -262,7 +262,7 @@ Validation
1 Connectivity
In the table below, each column shows which node types are allowed to be downstream (or ‘down-control’) of the node type at the top of the column.
-
+
Code
using Ribasim
@@ -546,7 +546,7 @@ 1 Connectivity
2 Neighbor amounts
The table below shows for each node type between which bounds the amount of in- and outneighbors must be, for both flow and control edges.
-
+
Code
= Vector{String}()
diff --git a/python/examples_files/figure-html/cell-71-output-1.png b/python/examples_files/figure-html/cell-71-output-1.png
index 933e31732e59c8c4fbb04f446c5eac7e3da2d350..3ef67556a4b1daf5bd1e46703b82c70452f4ebdb 100644
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