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your HTML like this: + //

    + + // Fetch the JSON data + fetch("https://raw.githubusercontent.com/Deltares/Wflow.jl/gh-pages/switcher.json") + .then(response => response.json()) + .then(data => { + console.log('Data loaded:', data); // Log the loaded data + + const dropdown = document.querySelector('#nav-menu-version').nextElementSibling; + console.log('Dropdown element:', dropdown); // Log the dropdown element + + // Clear all existing dropdown items + dropdown.innerHTML = ''; + + data.forEach(item => { + console.log('Adding item:', item); // Log the item being added + + // Create a new li element + const li = document.createElement('li'); + + // Create a new a element + const a = document.createElement('a'); + a.className = 'dropdown-item'; + a.href = item.href; // Use the 'url' property as the href + a.textContent = item.name; // Use the 'name' property as the text + + // Add the a element to the li + li.appendChild(a); + + // Add the li to the dropdown + dropdown.appendChild(li); + }); + + console.log('Dropdown after adding items:', dropdown); // Log the dropdown after adding items + + // Get all dropdown items within the specific dropdown menu + var dropdownMenu = document.querySelector('#nav-menu-version').nextElementSibling; + + var dropdownItems = dropdownMenu.querySelectorAll('.dropdown-item'); + + // Get the current page in chunks + var currentPagePath = window.location.pathname.split('/'); + + for (var i = 0; i < dropdownItems.length; i++) { + // Get textcontent + var textContent = dropdownItems[i].textContent; + + // Get the index of the current version + var index = currentPagePath.indexOf(textContent); + + if (index !== -1) { + // Remove the active-item class from all items + for (var j = 0; j < dropdownItems.length; j++) { + dropdownItems[j].classList.remove('active-item'); + } + + dropdownItems[i].classList.add('active-item'); + break + } + } + + console.log('current page path', currentPagePath); + + // Loop through each dropdown item + for (var i = 0; i < dropdownItems.length; i++) { + // Add click event listener to each item + dropdownItems[i].addEventListener('click', function (event) { + // Prevent default action + event.preventDefault(); + + // Get the clicked item's text + var itemText = this.textContent; + var itemHref = this.getAttribute('href') + + // Loop through each dropdown item again to find a match in the current page's path + for (var j = 0; j < dropdownItems.length; j++) { + // Get the dropdown item's text + var dropdownText = dropdownItems[j].textContent; + console.log('Dropdown item:', dropdownText); + + window.location.href = itemHref; + + // The code below is taken from Delft-FIAT, and is in place to switch + // to the same page but on a different version (if that exists). This + // is currently overruled with the line above this comment, which + // redirects to the new URL (home page). + + // // Find the index of the dropdownText in the current page's path + // var index = currentPagePath.indexOf(dropdownText); + // // If the dropdownText is found in the current page's path + // if (index !== -1) { + // // Construct the new URL relative to the dropdownText and append the itemText + // addElements = currentPagePath.slice(index + 1,) + // var newUrl = itemHref + '/' + addElements.join('/') + // console.log('Clicked item:', newUrl); + // window.location.href = itemHref; + // // // Redirect to the new URL + // // checkPathExists(newUrl) + // // .then(exists => { + // // if (exists) { + // // window.location.href = newUrl; + // // } else { + // // console.log('Path does not exist, referring to home page'); + // // window.location.href = itemHref; + // // } + // // }) + + // // Exit the loop + // break; + // } + } + }); + } + + }) + .catch(error => console.error('Error:', error)); // Log any errors +} diff --git a/previews/PR448/changelog.html b/previews/PR448/changelog.html new file mode 100644 index 000000000..d5cce0b83 --- /dev/null +++ b/previews/PR448/changelog.html @@ -0,0 +1,1308 @@ + + + + + + + + + +Changelog – Wflow.jl + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    +

    Changelog

    +
    + + + +
    + + + + +
    + + + +
    + + +

    All notable changes to this project will be documented in this file.

    +

    The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

    +
    +

    Unreleased

    +
    +

    Fixed

    +
      +
    • Initialization of LateralSSF variables ssf and ssfmax with vertical hydraulic conductivity profile exponential_constant. Removed parameter khfrac from the computation, as it is already part of parameter kh_0.
    • +
    • Mutating BMI model control functions (update, update_until and finalize) and extended mutating BMI functions (load_state and save_state) should return nothing.
    • +
    +
    +
    +

    Changed

    +
      +
    • Removed vertical concepts HBV and FLEXTopo.
    • +
    • Removed metadata macros exchange and grid_type. The macro grid_type is not required because this functionality is already part of BMI. The macro exchange is replaced by a function used by BMI. Remaining metadata macros get_units and grid_loc are only used by BMI.
    • +
    • Refactor the vertical SBM concept: divide the long struct SBM into different model components for interception, snow, glacier, (open water) runoff, soil, water demand and allocation stored in the struct LandHydrologySBM. Additionally, the atmospheric forcing and a shared vegetation parameterset are stored as separate fields in struct LandHydrologySBM (with soil model SbmSoilModel). The model component structs have model variables, parameters and boundary_conditions (if applicable), including associated functions for initializing and updating these model components. The original long update function of the SBM soil part has been split into separate functions.
    • +
    +
    +
    +

    Added

    +
      +
    • Support direct output of snow and glacier melt, and add computation of snow water equivalent (SWE).
    • +
    +
    +
    +
    +

    v0.x releases

    +
    +

    v0.8.1 - 2024-08-27

    +
    +

    Fixed

    +
      +
    • Reduce allocations in update of vertical SBM concept.
    • +
    +
    +
    +
    +

    v0.8.0 - 2024-08-19

    +
    +

    Fixed

    +
      +
    • Added missing BMI function get_grid_size, it is used for unstructured grids, for example to get the length of arrays returned by BMI functions get_grid_x and get_grid_y.
    • +
    • Added a check for the solution of the quadratic equation as part of the Modified Puls approach for lake outflow. Lower limit should be zero (very small negative values can occur).
    • +
    • Limit lake evaporation (added variable actevap) and lake outflow to prevent negative lake storage. The variable actevap has also been added to the reservoir module.
    • +
    • The set_states function for model type sbm with local inertial routing for river and land component.
    • +
    • Inflow to reservoir and lake locations for local inertial routing: 1) with floodplain routing, the floodplain discharge was not added to the inflow of these locations, 2) the to_river variable from overland flow and lateral subsurface flow was not added to the inflow of these locations.
    • +
    • Close netCDF NCDataset with state variables in extended BMI function save_state.
    • +
    • For the computation of Gash interception model parameter e_r multiply the precipitation input with the canopy fraction (this was only done for the potential evapotranspiration input).
    • +
    • Function BMI.update_until could throw an InexactError: Int64 caused by a not whole number, representing how many times (steps) an update of a wflow model is required. This is fixed by using divrem for the computation of the number of steps in this function. An error is thrown when the absolute remainder of divrem is larger than eps(), or when the number of steps is negative.
    • +
    • Fixed internal and external broken links in docs.
    • +
    • The internal time step of the local inertial model (stable_timestep function) can get zero when LoopVectorization is applied (@tturbo) to the for loop of these functions. This issue occured on a virtual machine, Windows 10 Enterprise, with Intel(R) Xeon(R) Gold 6144 CPU (2 processors). This has been fixed by replacing @tturbo with reduction of Polyester.jl.
    • +
    • Fixed required states of the model type sbm_gwf: added h_av for the river and land domain.
    • +
    • For the constanthead boundary of GroundwaterFlow the head should not be changed (was set to top elevation of the aquifer if head > top), and exfiltwater should be 0 for these boundary cells.
    • +
    +
    +
    +

    Changed

    +
      +
    • Stop exposing scalar variables through BMI. The BMI.get_value_ptr function was not working correctly for scalar model variables (a view was applied). Only a few scalar model parameters are defined, and it is not expected that exposing these variables is required (e.g. for model coupling) while code changes for these variables (including struct fields) are required.
    • +
    • The local inertial routing (constant) river boundary condition depth at a ghost node (downstream river outlet) was set at 0.0 in the code and can now be provided through the model parameter netCDF file (riverdepth_bc). In addition, the boundary condition river length dl at a ghost node should be set through the model parameter netCDF file (riverlength_bc), providing this boundary condition through the [model] settings in the TOML file (model.riverlength_bc) has been deprecated.
    • +
    • As part of the vertical SBM concept: 1) add variable net_runoff (land runoff minus actual open water evaporation ae_openw_l) and 2) change the definition of variable runoff by removing the subtraction of ae_openw_l (total land runoff). The variable net_runoff is now input to the kinematic wave for overland flow (replaces the original runoff variable as input). The lower limit of the original runoff variable was set at zero, which may result in water balance errors. This lower limit was implemented in the Python version of wflow_sbm, to avoid a very slow kinematic wave solution for surface flow computation (no distinction between a kinematic wave for overland and river flow). When in the Python version of wflow_sbm the kinematic wave for surface flow was split into a river and land component, the lower limit was removed for river runoff (net_runoff_river), but not for land runoff.
    • +
    • Always use fractions for the computation of potential evapotranspiration (interception and transpiration) and potential evaporation (open water and soil). Replaced variable et_reftopot by crop coefficient kc (use of et_reftopot has been deprecated).
    • +
    • For improved code readability it is now discouraged to use non-ASCII characters for the names of variables, structs, functions and macros. Using the non-ASCII character for built-in operators is still allowed. This change in naming convention is now in effect and all invalid uses of non-ASCII characters have been replaced by ASCII equivalents. This change also impacts the TOML keys kv₀, θᵣ and θₛ. These keys have been replaced with the ASCII versions kv_0, theta_r and theta_s in v0.4.0 and the old keys are not supported anymore.
    • +
    • Docs: 1) improved description of different model configurations in model-setup.md, also in relation to hydromt_wflow in docs, 2) citing info related to wflow_sbm publication in Geosci. Model Dev. (from in review to published).
    • +
    • Root water uptake reduction (Feddes): 1) extend critical pressure head parameters with h3_low and h3_high, 2) all critical pressure head parameters can be set (values for h1, h2 and h3 were fixed) and 3) the root water uptake reduction coefficient \alpha can be set at 0 (default is 1) at critical pressure head h1 (through the model parameter alpha_h1).
    • +
    • For the actual transpiration computation in SBM, the potential transpiration is partitioned over the soil layers with roots according to the model parameter rootfraction (fraction of the total root length in a soil layer). Previously, for each soil layer (from top to bottom) the actual transpiration was computed, and the remaining potential transpiration was used in the next soil layer.
    • +
    +
    +
    +

    Added

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      +
    • Total water storage as an export variable for SBM concept. This is the total water stored per grid cell in millimeters. Excluded from this variable are the floodplain, lakes and reservoirs.
    • +
    • Checks to see if all states are covered in the .toml file. If not all states are covered, an error is thrown. If there are more states specified than required, these states are ignored (with a warning in the logging), and the simulation will continue.
    • +
    • Support different vertical hydraulic conductivity profiles for the SBM concept. See also the following sections: The SBM soil water accounting scheme and Subsurface flow routing for a short description.
    • +
    • Local inertial routing to sbm_gwf model type.
    • +
    • Water demand and allocation computations for model types sbm and sbm_gwf.
    • +
    +
    +
    +
    +

    v0.7.3 - 2024-01-12

    +
    +

    Fixed

    +
      +
    • Documentation: add leakage term to the wflow_sbm figure, document external input parameter ksathorfrac and fix description of adding external inflow to the kinematic wave.
    • +
    • Fixed BMI functions (e.g. BMI.get_value) that deviated from BMI specifications (BasicModelInterface.jl), including function arguments, return types and the BMI specification that arrays are always flattened (this was not the case for variables stored as 2-dimensional arrays or as vector of SVectors).
    • +
    • Bump compat for NCDatasets to 0.13, 0.14.
    • +
    • The solution for lake outflow as part of the Modified Puls Approach. The inflow and outflow variables are defined for period Δt, and not at t1 and t2 (instantaneous) as in the original mass balance equation of the Modified Puls Approach. Because of this, the terms of the quadratic equation (and solution) were fixed.
    • +
    • Use kvfrac for the computation of vertical saturated hydraulic conductivity at the bottom of the soil layer, since kvfrac is also used for the computation of vertical unsaturated flow.
    • +
    +
    +
    +

    Changed

    +
      +
    • For cyclic parameters different cyclic time inputs are supported (only one common cyclic time (for example daily or monthly) was allowed).
    • +
    • BMI: 1) added grid information (type and location) and whether a variable can be exchanged to metadata Structs, 2) extend model grid functions for wflow components that store variables on edges (local inertial model) with get_grid_edge_count and get_grid_edge_nodes.
    • +
    +
    +
    +

    Added

    +
      +
    • Functions for loading and saving states and getting the starttime in Unix time format. This is convenient for coupling with OpenDA (and other external) software. The set states functionality from the initialization function has been moved to a separate set_states function for each Model type, to support loading states independent of initialization.
    • +
    +
    +
    +
    +

    v0.7.2 - 2023-09-27

    +
    +

    Fixed

    +
      +
    • Water balance of modified Rutter interception model. The sum of the stemflow partitioning coefficient pt and free throughfall coefficient p could get larger than 1, resulting in an overestimation of stemflow and throughfall amounts and negative net interception amounts. And the first drainage amount dd, controlled by a change over time in canopy storage capacity cmax, should not be subtracted from precipitation to compute net interception.
    • +
    • The netinterception (net interception) computed by the modified Rutter interception model was stored as interception in SBM, while this should be the interception (interception loss by evaporation) output of the modified Rutter interception model. The interception of SBM is used to compute the total actual evapotranspiration actevap.
    • +
    +
    +
    +
    +

    v0.7.1 - 2023-06-30

    +
    +

    Fixed

    +
      +
    • State initialization of 1D floodplain volume. In the initialization function the wrong field name of type FloodPlainProfile was used (area instead of a).
    • +
    +
    +
    +
    +

    v0.7.0 - 2023-06-12

    +
    +

    Fixed

    +
      +
    • BMI.get_time_units now gets called on the model rather than the type, like all other BMI functions, except BMI.initialize. Also it returns “s” instead of “seconds since 1970-01-01T00:00:00”, in line with the BMI specification.
    • +
    • Added the interception component to total actual evapotranspiration actevap of SBM (was defined as the sum of soil evaporation, transpiration and open water evaporation).
    • +
    +
    +
    +

    Changed

    +
      +
    • The time values returned in the BMI interface are no longer in seconds since 1970, but in seconds since the model start time. This is more in line with standard BMI practices.
    • +
    • The starttime was defined one model timestep Δt ahead of the actual model time (the initial conditions timestamp (state time)). As a consequence this was also the case for the current model time. To allow for an easier interpretation of wflow time handling, either through BMI or directly, the starttime is now equal to the state time, resulting in current model times without an offset.
    • +
    • Using more than 8 threads can result in too much overhead with Threads.@threads. After performance testing, this has been changed for kinematic wave routing and the vertical SBM concept to spawning tasks with Threads@spawn for number of threads <= 8, where each task iterates over a chunk of size basesize. For more than 8 threads the low overhead threading Polyester.@batch (including the minbatch argument) is used. For local inertial routing the use of Threads.@threads has been changed to threaded loop vectorization (river and 1D floodplain local inertial momentum equation) and Polyester.@batch.
    • +
    +
    +
    +

    Added

    +
      +
    • For (regulated) lakes with rating curve of type 1 (H-Q table), lake storage above the maximumstorage (based on maximum water level from the H-Q table) is spilled instantaneously (overflow) from the lake.
    • +
    • Added support to use sum as a reducer function for csv and scalar output options.
    • +
    +
    +
    +
    +

    v0.6.3 - 2023-03-01

    +
    +

    Fixed

    +
      +
    • Removed error when _FillValue is present in the time dimension of the forcing netCDF file. The simulation is allowed to continue with the attribute present, given that there are no missing values in the time dimension. This is checked by the code, and an error is thrown if this is the case.
    • +
    • Column index of daily lake rating curves. This was incorrectly based on dayofyear with a maximum of 365. The column index should be based on julian day (leap days are not counted).
    • +
    +
    +
    +

    Changed

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      +
    • NCDatasets version. Reading the time dimension of multifile netCDF file became very slow since NCDatasets v0.12.4, this issue has been solved in v0.12.11.
    • +
    • Store the time dimension of the forcing netCDF file as part of the struct NCreader instead of calling dataset["time"][:] each time step when loading forcing data.
    • +
    +
    +
    +

    Added

    +
      +
    • Show total duration of simulation in the log file (info), and show the current time at execution of each timestep (debug).
    • +
    • Support for exponential decline in horizontal conductivity in the sbm_gwf concept. This can be enabled using the conductivity_profile setting (either “uniform” or “exponential”). If set to “exponential”, it exponentially reduces the kh0 (or conductivity) based on the value of gwf_f to the actual horizontal conductivity (k).
    • +
    • An optional 1D floodplain schematization for the river flow inertial model, based on provided flood volumes as a function of flood depth per river cell. See also the following sections: SBM + Local inertial river and River and floodplain routing for a short description, and the following section for associated model parameters.
    • +
    +
    +
    +
    +

    v0.6.2 - 2022-09-01

    +
    +

    Fixed

    +
      +
    • Two issues related to reservoir and lake locations as part of local inertial model: 1) added as boundary points to the update of overland flow, 2) fixed check reservoir and lake location in update river flow.
    • +
    • Limit flow (qx, qy and q) in local inertial model when water is not available (set to zero).
    • +
    • In the grid output netCDFs, don’t set the _FillValue attribute, since the CF conventions don’t allow it.
    • +
    • Glacier parameter g_sifrac needs to be converted during initialization (time dependent).
    • +
    • The check that the sum of adaptive timesteps (Δt) of the local inertial model (1D and 2D) does not exceed the model timestep.
    • +
    +
    +
    +

    Changed

    +
      +
    • Changed depth h for reservoir and lake locations as part of the river local inertial model from bankfull_depth to zero.
    • +
    +
    +
    +

    Added

    + +
    +
    +
    +

    v0.6.1 - 2022-04-26

    +
    +

    Fixed

    +
      +
    • Fixed an error with the log file, when writing to a folder that does not (yet) exists. Now, the folder is created prior to writing the log file.
    • +
    • Fixed a MethodError for read_dims, thrown when reading netCDF data with NCDatasets.jl 0.12.3 or higher.
    • +
    +
    +
    +
    +

    v0.6.0 - 2022-04-14

    +
    +

    Added

    +
      +
    • The FLEXTopo model.
    • +
    • Set a (different) uniform value for each index of input parameters with an extra dimension. A list of values (instead of one uniform value) that should be equal to the length of the extra dimension can be provided in the TOML file. See also Modify parameters.
    • +
    • Modify input parameters with an extra dimension at multiple indices with different scale and offset values, through the TOML file. See also Modify parameters.
    • +
    • Added support for netCDF compression for gridded model output, through the option compressionlevel in the [output] section in the TOML file. The setting defaults to 0 (no compression), but all levels between 0 and 9 can be used.
    • +
    +
    +
    +

    Changed

    +
      +
    • Re-organized the documentation: moved explanation of different model concepts to a model documentation section, added a user guide to explain setting up the model, added new figures to the description of wflow_sbm.
    • +
    • The unit of lateral subsurface flow ssf of LateralSSF is now m^3 d^{-1}. The unit was m^3 t^{-1}, where t is the model timestep. Other flow variables are already stored independently from t, this allows for easier interpretation and to use states independently of t.
    • +
    • Changed the reference level of water depth h and h_av of 2D overland flow (ShallowWaterLand) for cells containing a river from river bed elevation zb to cell elevation z.
    • +
    +
    +
    +

    Fixed

    +
      +
    • Fixed calculation of average water depth h_av of 2D overland flow (ShallowWaterLand) with the local inertial approach. The summation of h was not correct, resulting in too low values for h_av. For river cells of 2D overland flow h_av was only updated as part of the river domain (ShallowWaterRiver), this value is now also updated as part of the land domain (ShallowWaterLand).
    • +
    • Fixed the following two flow width issues for 2D overland flow of the local inertial model: 1) The flow widths xwidth and ywidth were mapped incorrectly (reversed) to the flow calculation in x and y direction, respectively. 2) For river cells the effective flow width for overland flow was not determined correctly: the riverwidth vector supplied to the function set_effective_flowwidth! covered the complete model domain and should have covered the river domain, resulting in incorrect river widths and thus incorrect effective flow widths for river cells.
    • +
    +
    +
    +
    +

    v0.5.2 - 2022-02-03

    +
    +

    Changed

    +
      +
    • Model types sbm_gwf and hbv use the same approach for the calculation of the drain width dw as model type sbm.
    • +
    • Renamed h_bankfull parameter to bankfull_depth for consistency between kinematic-wave and local-inertial river routing. When using the old name under the [input.lateral.river] section of the TOML file, it will work but it is suggested to update the name.
    • +
    +
    +
    +

    Added

    + +
    +
    +

    Fixed

    +
      +
    • Model type hbv: the surface width for overland flow was not corrected with the river width.
    • +
    • Fixed use of absolute path for path_forcing in TOML file, which gave an error in wflow v0.5.1.
    • +
    • Fixed a crash when glacier processes are simulated as part of the hbv concept (Δt was not defined).
    • +
    • When the surface flow width for overland flow is zero, the water level h of the kinematic wave should not be calculated, otherwise this results in NaN values. When the model is initialized from state files, q and h are set to zero for indices with a zero surface flow width.
    • +
    • Fixed how number of iterations its for kinematic wave river flow are calculated during initialization when using a fixed sub-timestep (specified in the TOML file). For a model timestep smaller than the fixed sub-timestep an InexactError was thrown.
    • +
    • Fixed providing a cyclic parameter when the netCDF variable is read during model initialization with ncread, this gave an error about the size of the netCDF time dimension.
    • +
    • Fixed CSV and netCDF scalar output of variables with dimension layer (SVector).
    • +
    +
    +
    +
    +

    v0.5.1 - 2021-11-24

    +
    +

    Fixed

    +
      +
    • Fixed calculation of exfiltwater as part of the sbm_gwf model type. This was based directly on groundwater head above the surface level, without multiplying by the specific_yield, resulting in an overestimation of exfiltwater. This is required since the groundwater model estimates the head by dividing the volume by the specific yield or storativity of the aquifer. So, should the groundwater table rise above surface level, the head above surface level does not represent a water column one to one. (This also means the groundwater model (slightly) overestimates heads when the head rises above the surface level. However, this water is immediately removed, and the head will be set to surface level.)
    • +
    +
    +
    +

    Added

    +
      +
    • Optional dir_input and dir_output keys in the TOML, which can be used to quickly change the path for all input or output files that are given as a relative path.
    • +
    +
    +
    +
    +

    v0.5.0 - 2021-11-12

    +
    +

    Changed

    +
      +
    • Scaling of potential capillary rise is replaced by a common approach found in literature, based on the water table depth zi, a maximum water depth cap_hmax beyond which capillary rise ceases, and a coefficient cap_n. See also Capillary rise. Multiplying the scaling factor with the ratio of model time step and basetimestep in the original approach resulted in (much) smaller capillary fluxes at sub-daily model time steps compared to daily model time steps, and is not used in the new approach. Parameters cap_hmax and cap_n can be set through the TOML file, parameter capscale of the previous approach is not used anymore.
    • +
    +
    +
    +

    Fixed

    +
      +
    • Conversion of GroundwaterFlow boundaries \(\SIb{}{m^3 d^{-1}}\) as part of model concept sbm_gwf to \(\SI{m^3 s^{-1}}\) for sub-daily model time steps. For the conversion the basetimestep (86400 s) should be used (and not the model time step).
    • +
    +
    +
    +
    +

    v0.4.1 - 2021-11-04

    +
    +

    Changed

    +
      +
    • The \alpha parameter of the kinematic wave has a fixed value now and is not updated because of changes in water height (this could result in large water balance errors). See also Surface routing.
    • +
    • Cyclic input for other structs than vertical are also now supported (for example cyclic inflow to the river).
    • +
    • Moved update_forcing! and update_cyclic! functions to the run function. It is now easier to implement a custom run function with custom loading of input data (forcing and cyclic parameters).
    • +
    +
    +
    +

    Added

    +
      +
    • Check if reservoirs and lakes have downstream nodes. Without downstream nodes is not supported and in that case an error message is thrown that is easier to understand than the previous one: “ArgumentError: Collection is empty, must contain exactly 1 element.”
    • +
    • For the input.path_forcing TOML setting we use Glob.jl to expand strings like "data/forcing-year-*.nc" to a set of netCDF files that are split in time.
    • +
    • External water inflow (supply/abstractions) added to the kinematic wave inflow in m3/s. It is added/removed to sf.qlat[v] before computing the new q[v] with the kinematic wave equation.
    • +
    • Fixed values for forcing parameters are supported, see also Fixed forcing values.
    • +
    +
    +
    +

    Added

    + +
    +
    +

    Fixed

    +
      +
    • River inflow for reservoirs and lakes in the kinematic wave. This inflow was based on sf.q[v] at the previous time step, and this has been fixed to the current time step.
    • +
    +
    +
    +
    +

    v0.4.0 - 2021-09-02

    +
    +

    Changed

    +
      +
    • Changed length units for lateral subsurface flow component from millimeter to meter. This means that state netCDF files from previous versions can only be reused if ssf is divided by 10^9.
    • +
    • Add snow and glacier processes to wflow_sbm figure of the documentation.
    • +
    +
    +
    +

    Added

    +
      +
    • Multi-threading of vertical SBM concept and lateral kinematic wave components (overland, river and subsurface flow) of wflow_sbm model SBM + Kinematic wave.
    • +
    • Improved error message for CSV Reducer.
    • +
    • The TOML keys kv₀, θᵣ and θₛ have been replaced with the ASCII versions kv_0, theta_r and theta_s, to avoid encoding issues with certain text editors. The old keys still work as well.
    • +
    +
    +
    +

    Fixed

    +
      +
    • Calculation of volumetric water content of vertical SBM (soil layers and root zone).
    • +
    • Update of satwaterdepth in SBM (evaporation was only subtracted from a local variable, and not from sbm.satwaterdepth).
    • +
    • Fixed the index lowerlake_ind of NaturalLake. Linked lakes were not simulated correctly (flows between upstream and downstream lake).
    • +
    • Interpolation function interpolate_linear(x, xp, fp) for CSV tables lakes. When x was larger or smaller than xp, maximum(xp) or minimum(xp) was returned instead of maximum(fp) or minimum(fp).
    • +
    • Fixed model timestep of reservoirs (SimpleReservoir) and lakes (NaturalLake) in relation to precipitation and evapotranspiration fluxes. This was set to the fixed wflow basetimestep of 86400 s, and should be set to the actual model time step from the TOML configuration file.
    • +
    • Add flux from Drainage (GroundwaterFlow) in the sbm_gwf_model to the overland flow component instead of the river component of the kinematic wave.
    • +
    • Fixed option constanthead = false (TOML file), constant_head field of GroundwaterFlow was not defined in this case. Fixed this by initializing empty fields (Vector) for struct ConstantHead.
    • +
    • Fixed return max(0, boundary.flux[index]) to return max(0, flux) the flux should be returned when cell is dry, no negative value allowed.
    • +
    • Fixed path to initialize lake to: dirname(static_path)
    • +
    • Fixed outflow = 0, when lake level is below lake threshold. Before a negative value could enter the log function and model would fail.
    • +
    • Fixed the lake storage initialization. For continuation runs (reinit = false), this caused the lake to be reset to the initial conditions instead of the saved state.
    • +
    +
    +
    +
    +

    v0.3.1 - 2021-05-19

    +
    +

    Fixed

    +
      +
    • Ignore extra dimensions in input netCDFs if they are size 1
    • +
    +
    +
    +
    +

    v0.3.0 - 2021-05-10

    +
    +

    Changed

    +
      +
    • New deposition process for coarse sediment in the reservoirs with a new parameter restrapefficiency in the sediment model.
    • +
    • New variables added to the LandSediment and RiverSediment structs in order to save more output from the sediment model.
    • +
    • Added variables volume and inwater to SurfaceFlow struct, this is convenient for the coupling with the water quality model Delwaq.
    • +
    • River water level (h) and discharge (q) forced directly into the RiverSediment struct (instead of using the OverlandFlowSediment struct first).
    • +
    • Require Julia 1.6 or later.
    • +
    +
    +
    +

    Added

    +
      +
    • Modify model parameters and forcing through the TOML file (see Modify parameters).
    • +
    • Run wflow_sbm (SBM + kinematic wave) in two parts (until recharge and after subsurface flow) from BMI, including the option to switch off the lateral subsurface component of wflow_sbm.
    • +
    • Support more netCDF dimension and axis order variants.
    • +
    +
    +
    +

    Fixed

    +
      +
    • Corrected a bug in sediment deposition in the river (case when incoming sediment load is more than the river transport capacity).
    • +
    • Fixed update of snow and glacierstore fields of HBV and SBM concepts by the glacier_hbv module.
    • +
    +
    +
    +
    +

    v0.2.0 - 2021-03-26

    +
    +

    Changed

    +
      +
    • Removed dependency of the f model parameter of wflow_sbm on the parameters \theta_{s}, \theta_{r} and M. This approach is used in Topog_SBM, but not applicable for wflow_sbm. The f parameter needs to be provided as part of the netCDF model parameter file.
    • +
    • Grid properties as cell length and elevation now stored as part of the model.land.network component and not as part of the vertical model components, as it is not used by these components. altitude (elevation) should now be provided as part of the [input] section of the TOML configuration file, and not as part of the [input.vertical] section.
    • +
    • Removed parameter \theta_{e} from SBM struct (not used in update). Parameters \theta_{s} and \theta_{r} included separately (instead of \theta_{e}) in LateralSSF struct, now directly linked to SBM parameters.
    • +
    • Improve error messages (netCDF and cyclic flow graph).
    • +
    +
    +
    +

    Added

    +
      +
    • Export of netCDF scalar timeseries (separate netCDF file from gridded timeseries). This also allows for importing these timeseries by Delft-FEWS (General Adapter).
    • +
    +
    +
    +

    Fixed

    +
      +
    • Model parameter Manning’s n now used during the update of the struct SurfaceFlow, to change the related \alpha parameter of the kinematic wave for channel flow.
    • +
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    Developers guide

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    Contributions and reporting issues

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    We welcome reporting of issues on our GitHub page. Please provide a minimum working example so we are able to reproduce the issue. Furthermore, we welcome contributions. We follow the ColPrac guide for collaborative practices. New contributors should make sure to read that guide.

    +
    +
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    Style/decisions

    +
      +
    • For improved code readability, we decided to avoid non-ASCII characters for naming variables, structs, functions and macros. Using the non-ASCII character for built-in operators is still allowed. This change in naming convention is now in effect and all invalid uses of non-ASCII characters have been replaced by ASCII equivalents.
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    Developments

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    Julia structures

    +
    + + + +
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    + + + +
    + + +
    +

    Model

    +

    Below the composite type that represents all different aspects of a Wflow.Model, such as the network, parameters, clock, model type, configuration and input and output.

    +
    struct Model{N,L,V,R,W,T}
    +    config::Config  # all configuration options
    +    network::N      # connectivity information, directed graph
    +    lateral::L      # lateral model that holds lateral state, moves along network
    +    vertical::V     # vertical model that holds vertical state, independent of each other
    +    clock::Clock    # to keep track of simulation time
    +    reader::R       # provides the model with dynamic input
    +    writer::W       # writes model output
    +    type::T         # model type
    +end
    +

    The lateral field of the struct Model can contain different lateral concepts. For each wflow model these different lateral concepts are mapped through the use of a NamedTuple. The vertical field of the struct Model always contains one vertical concept, for example the SBM vertical concept.

    +

    Below an example how lateral concepts are mapped for the SBM model through a NamedTuple:

    +
    (subsurface = ssf, land = olf, river = rf)
    +

    The subsurface part is mapped to the lateral subsurface flow kinematic wave concept, the land part is mapped the overland flow kinematic wave concept and the river part is mapped to the river flow kinematic wave concept. Knowledge of this specific mapping is required to understand and correctly set input, output and state variables in the TOML configuration file, see also Config and TOML. This mapping is described in more detail for each model in the section Models. Also the struct of each mapped concept is provided, so one can check the internal variables in the code. These structs are defined as a parametric composite type, with type parameters between curly braces after the struct name. See also the next paragraph Vertical and lateral models for a more detailed description.

    +
    +
    +

    Vertical and lateral models

    +

    The different model concepts used in wflow are defined as parametric composite types. For example the vertical SBM concept is defined as follows: struct SBM{T,N,M}. T, N and M between curly braces after the struct name refer to type parameters, for more information about type parameters you can check out Type parameters. Since these parameters can be of any type, it is possible to declare an unlimited number of composite types. The type parameters are used to set the type of struct fields, below an example with a part of the SBM struct:

    +
    @get_units @with_kw struct SBM{T,N,M}
    +    # Model time step [s]
    +    dt::T | "s"
    +    # Maximum number of soil layers
    +    maxlayers::Int | "-"
    +    # number of cells
    +    n::Int | "-"
    +    # Number of soil layers
    +    nlayers::Vector{Int} | "-"
    +    # Number of unsaturated soil layers
    +    n_unsatlayers::Vector{Int} | "-"
    +    # Fraction of river [-]
    +    riverfrac::Vector{T} | "-"
    +    # Saturated water content (porosity) [mm mm⁻¹]
    +    theta_s::Vector{T} | "mm mm-1"
    +    # Residual water content [mm mm⁻¹]
    +    theta_r::Vector{T} | "mm mm-1"
    +    # Vertical hydraulic conductivity [mm Δt⁻¹] at soil surface
    +    kv_0::Vector{T} | "mm dt-1"
    +    # Muliplication factor [-] applied to kv_z (vertical flow)
    +    kvfrac::Vector{SVector{N,T}} | "-"
    +

    The type parameter T is used in wflow as a subtype of AbstractFloat, allowing to store fields with a certain floating point precision (e.g. Float64 or Float32) in a flexible way. N refers to the maximum number of soil layers of the SBM soil column, and M refers to the maximum number of soil layers + 1. See also part of the following instance of SBM:

    +
    sbm = SBM{Float,maxlayers,maxlayers + 1}(
    +    dt = tosecond(dt),
    +    maxlayers = maxlayers,
    +    n = n,
    +

    For the other model concepts, we refer to the code to check these type parameters.

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    + + + + + \ No newline at end of file diff --git a/previews/PR448/examples/index.html b/previews/PR448/examples/index.html new file mode 100644 index 000000000..6f9e1d3c6 --- /dev/null +++ b/previews/PR448/examples/index.html @@ -0,0 +1,781 @@ + + + + + + + + + +To be added in the future – Wflow.jl + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    To be added in the future

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    + + + + + \ No newline at end of file diff --git a/previews/PR448/getting_started/building_a_model.html b/previews/PR448/getting_started/building_a_model.html new file mode 100644 index 000000000..0928ada55 --- /dev/null +++ b/previews/PR448/getting_started/building_a_model.html @@ -0,0 +1,896 @@ + + + + + + + + + +Building a model from scratch – Wflow.jl + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    Building a model from scratch

    +
    + + + +
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    + + + +
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    +

    HydroMT-wflow

    +

    hydroMT is a Python package, developed by Deltares, to build and analyze hydro models. It provides a generic model api with attributes to access the model schematization, (dynamic) forcing data, results and states.

    +

    The wflow plugin hydroMT-wflow of hydroMT can be used to build and analyze the following model configurations:

    + +

    To learn more about the wflow plugin of this Python package, we refer to the hydroMT-wflow documentation.

    +

    To inspect or modify (for example in QGIS) the netCDF static data of these wflow models it is convenient to export the maps to a raster format. This can be done as part of the hydroMT-wflow plugin, see also the following example. It is also possible to create again the netCDF static data file based on the modified raster map stack.

    +
    +
    +

    Data requirements

    +

    The actual data requirements depend on the application of the Model and the Model type. Both forcing and static data should be provided in netCDF format, with the same grid definition for forcing and static data. The only exception is storage and rating curves for lakes, that should be provided in CSV format, see also Additional settings for waterbodies.

    +
      +
    • Forcing data: +
        +
      • Precipitation
      • +
      • Potential evapotranspiration
      • +
      • Temperature (optional, only needed for snow and glacier modelling)
      • +
    • +
    +

    The requirements for static data (including model parameters) depend on the Model type. The following data is required for all Model types, but not directly part of a Model component:

    +
      +
    • flow direction data (D8)
    • +
    • river map (location of the river)
    • +
    • sub-catchment map (model domain)
    • +
    +

    For the flow direction (D8) data, the PCRaster ldd convention is used, see also PCRaster ldd. An approach to generate ldd data is to make use of the Python package pyflwdir:

    + +

    see also Eilander et al. (2021) for more information. Pyflwdir is also used by the hydroMT Python package described in the next paragraph. Another approach to generate ldd data is to make use of PCRaster functionality, see for example lddcreate.

    +

    Optionally, but also not directly part of a model component are gauge locations, that are used to extract gridded data from certain locations.

    +

    The different supported model configurations are described in the section Model configurations. Wflow_sbm models have the vertical concept SBM in common and input parameters for this component are described in the SBM model parameters table. For wflow_sbm models there are two ways to include subsurface flow:

    +
      +
    1. The kinematic wave approach (see section Subsurface flow routing) as part of the sbm model type. Parameters that are part of this component are described in the Lateral subsurface flow section of Model parameters. Input parameters for this component are derived from the SBM vertical concept and the land slope. One external parameter (ksathorfrac) is used to calculate the horizontal hydraulic conductivity at the soil surface kh_0.
    2. +
    3. Groundwater flow (see section Groundwater flow component) as part of the sbm_gwf model type. For the unconfined aquifer the input parameters are described in the section Unconfined aquifer of Model parameters. The bottom (bottom) of the groundwater layer is derived from from the soilthickness [mm] parameter of SBM and the provided surface elevation altitude [m] as part of the static input. The area parameter is derived from the model grid. Parameters that are part of the boundary conditions of the unconfined aquifer are listed under Constant Head and Boundary conditions of the Model parameters section.
    4. +
    +

    Most hydrological model configurations make use of the kinematic wave surface routing (river flow, overland flow or both) and input data required for the river and overland flow components is described in Surface flow. There is also the option to use the local inertial model as part of the wflow_sbm models (model types sbm and sbm_gwf):

    + +

    Input parameters for this approach are described in River flow (local inertial), including the optional 1D floodplain schematization, and Overland flow (local inertial) of the Model parameters section.

    +

    Reservoirs or lakes can be part of the kinematic wave or local inertial model for river flow and input parameters are described in Reservoirs and Lakes.

    +

    The wflow_sediment model configuration consists of the vertical Soil Erosion concept and the input parameters for this concept are described in the Sediment section of the Model parameters. The parameters of the lateral Sediment Flux in overland flow concept are described in the Overland flow section of the Model parameters. Parameters of this component are not directly set by data from static input. The input parameters of the lateral concept River Sediment Model are listed in River flow of the Model parameters section.

    +

    The Model parameters section lists all the parameters per Model component and these Tables can also be used to check which parameters can be part of the output, see also Output netCDF section and Output CSV section.

    +

    Example models can be found in the Example models section.

    +
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    +

    References

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      +
    • Yamazaki, D., Ikeshima, D., Sosa, J., Bates, P. D., Allen, G. H. and Pavelsky, T. M.: MERIT Hydro: A high‐resolution global hydrography map based on latest topography datasets, Water Resour. Res., 2019WR024873, doi:10.1029/2019WR024873, 2019.
    • +
    • Eilander, D., van Verseveld, W., Yamazaki, D., Weerts, A., Winsemius, H. C., and Ward, P. J.: A hydrography upscaling method for scale-invariant parametrization of distributed hydrological models, Hydrol. Earth Syst. Sci., 25, 5287–5313, https://doi.org/10.5194/hess-25-5287-2021, 2021.
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    Download example models

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    For each wflow Model a test model is available that can help to understand the data requirements and the usage of each Model. The TOML configuration file per available model are listed in the Table below:

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    modelTOML configuration file
    wflow_sbm + kinematic wavesbm_config.toml
    wflow_sbm + groundwater flowsbm_gwf_config.toml
    wflow_sedimentsediment_config.toml
    +

    The associated Model files (input static, forcing and state files) can easily be downloaded and for this we share the following Julia code (per Model) that downloads the required files to your current working directory. For running these test model see also Usage and Command Line Interface.

    +
    +

    wflow_sbm + kinematic wave

    +
    # urls to TOML and netCDF of the Moselle example model
    +toml_url = "https://raw.githubusercontent.com/Deltares/Wflow.jl/master/test/sbm_config.toml"
    +staticmaps = "https://github.com/visr/wflow-artifacts/releases/download/v0.2.9/staticmaps-moselle.nc"
    +forcing = "https://github.com/visr/wflow-artifacts/releases/download/v0.2.6/forcing-moselle.nc"
    +instates = "https://github.com/visr/wflow-artifacts/releases/download/v0.2.6/instates-moselle.nc"
    +
    +# create a "data" directory in the current directory
    +datadir = joinpath(@__DIR__, "data")
    +mkpath(datadir)
    +toml_path = joinpath(@__DIR__, "sbm_config.toml")
    +
    +# download resources to current and data dirs
    +download(staticmaps, joinpath(datadir, "staticmaps-moselle.nc"))
    +download(forcing, joinpath(datadir, "forcing-moselle.nc"))
    +download(instates, joinpath(datadir, "instates-moselle.nc"))
    +download(toml_url, toml_path)
    +
    +
    +

    wflow_sbm + groundwater flow

    +
    # urls to TOML and netCDF of the Moselle example model
    +toml_url = "https://raw.githubusercontent.com/Deltares/Wflow.jl/master/test/sbm_gwf_config.toml"
    +staticmaps = "https://github.com/visr/wflow-artifacts/releases/download/v0.2.3/staticmaps-sbm-groundwater.nc"
    +forcing = "https://github.com/visr/wflow-artifacts/releases/download/v0.2.1/forcing-sbm-groundwater.nc"
    +
    +# create a "data" directory in the current directory
    +datadir = joinpath(@__DIR__, "data")
    +mkpath(datadir)
    +toml_path = joinpath(@__DIR__, "sbm_gwf_config.toml")
    +
    +# download resources to current and data dirs
    +download(staticmaps, joinpath(datadir, "staticmaps-sbm-groundwater.nc"))
    +download(forcing, joinpath(datadir, "forcing-sbm-groundwater.nc"))
    +download(toml_url, toml_path)
    +
    +
    +

    wflow_sediment

    +
    # urls to TOML and netCDF of the Moselle example model
    +toml_url = "https://raw.githubusercontent.com/Deltares/Wflow.jl/master/test/sediment_config.toml"
    +staticmaps = "https://github.com/visr/wflow-artifacts/releases/download/v0.2.3/staticmaps-moselle-sed.nc"
    +forcing = "https://github.com/visr/wflow-artifacts/releases/download/v0.2.3/forcing-moselle-sed.nc"
    +instates = "https://github.com/visr/wflow-artifacts/releases/download/v0.2.0/instates-moselle-sed.nc"
    +
    +# create a "data" directory in the current directory
    +datadir = joinpath(@__DIR__, "data")
    +mkpath(datadir)
    +toml_path = joinpath(@__DIR__, "sediment_config.toml")
    +
    +# download resources to current and data dirs
    +download(staticmaps, joinpath(datadir, "staticmaps-moselle-sed.nc"))
    +download(forcing, joinpath(datadir, "forcing-moselle-sed.nc"))
    +download(instates, joinpath(datadir, "instates-moselle-sed.nc"))
    +download(toml_url, toml_path)
    + + +
    + + Back to top
    + +
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    + +
    + + + + + \ No newline at end of file diff --git a/previews/PR448/getting_started/index.html b/previews/PR448/getting_started/index.html new file mode 100644 index 000000000..c766e85cd --- /dev/null +++ b/previews/PR448/getting_started/index.html @@ -0,0 +1,919 @@ + + + + + + + + + +Getting started – Wflow.jl + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    Getting started

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    Installing wflow

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    Wflow can be used in two different ways, depending on the required use of the code:

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      +
    • If you want to stay up-to-date with the latest version, explore and modify the model code, and write your own Julia scripts around the wflow package, we recommend installing wflow as a Julia package.
    • +
    • If you don’t need extra features, but just want to run simulations, a compiled executable version is available. This version includes a single executable, wflow_cli, which allows you to run the model via the command line.
    • +
    +

    Below we describe how to install both versions of wflow.

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    Installing as Julia package

    +

    Wflow is a Julia package that can be installed in several ways. Below, we show how to install wflow from Julia’s package repository and how to install the latest version from GitHub.

    +

    First, download and install the current stable release of Julia. If you have any issues installing Julia, please see platform specific instructions for further instructions.

    +

    If you are new to Julia, it might be a good idea to check out the Getting Started section of the Julia Manual. You can also find additional learning resources at julialang.org/learning.

    +
    +

    Install from Julia’s package repository

    +

    To access Julia’s package manager, press ] in the Julia REPL. To get back to the Julia REPL, press backspace or ^C.

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    +Tip +
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    If you haven’t used Julia in a while, it’s a good idea to run up to update your packages.

    +
    pkg> up
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    +
    +

    To access Julia’s package manager and install wflow, use:

    +
    pkg> add Wflow
    +

    This process can take a while, especially on the first run, as compatible dependencies are automatically resolved and installed from the Pkg General registry.

    +
    +
    +

    Install from GitHub

    +

    You can also install wflow from the master branch on the repository as follows:

    +
    pkg> add Wflow#master
    +

    This command tracks the master branch and updates to the latest commit on that branch when you run update, or simply up, in the Pkg REPL. The add installs wflow in your home directory under .julia/packages/Wflow. Note that packages installed under packages by add should not be changed in the directory, as the change could disrupt Pkg’s automatic dependency handling.

    +

    If you want to modify any files in the repository, you need to do a development install. This can be done using:

    +
    pkg> dev Wflow
    +

    This will clone the git repository, place it under your home directory in .julia/dev/Wflow, and add the wflow package to your project environment. To receive updates, you’ll need to pull the latest changes manually using git pull.

    +
    +
    +

    Check installation of wflow

    +

    Finally, go back to the Julia REPL and try to load wflow:

    +
    julia> using Wflow
    +

    The first time you do this, it may take longer as any new or changed packages need to be precompiled to enable faster loading on subsequent uses. No error messages should appear, which indicates that you have successfully installed wflow.

    +

    Before concluding this section, we recommend a few tools that can make using and developing Julia code easier.

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    +Tip +
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    There is a section on editors and IDEs for Julia on https://julialang.org/, scroll down to see it. We use and recommend Microsoft’s free and open source Visual Studio Code. When combined with the Julia extension it provides a powerful and interactive development experience.

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    If you plan to modify the code of wflow, we recommend installing the Revise.jl package. This package allows you to modify code and use the changes without restarting Julia. Install it with add Revise from the Pkg REPL. Then create a file called .julia/config/startup.jl, and put using Revise there. This will load Revise every time you start a Julia session.

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    Installing the compiled executable

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    Binaries of wflow_cli can be downloaded from our website download.deltares.nl, and are currently available for Windows. Download and install the .msi file. After installation, you will see two folders in the installation directory. Only the bin/wflow_cli is used. The artifacts folder contains binary dependencies such as netCDF.

    +
    artifacts\
    +bin\wflow_cli
    +

    To verify whether the installation was completed successfully, run wflow_cli with no arguments in the command line. This will display the following message:

    +
    Usage: wflow_cli 'path/to/config.toml'
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    + +
    +
    +Note +
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    +
    +

    The old version of wflow, based on Python and PCRaster libraries is also available to download from our website download.deltares.nl. We recommend installing the Julia version, as this documentation is written to support this version.

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    + + Back to top
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    + + + + + \ No newline at end of file diff --git a/previews/PR448/getting_started/running_wflow.html b/previews/PR448/getting_started/running_wflow.html new file mode 100644 index 000000000..9721a8af8 --- /dev/null +++ b/previews/PR448/getting_started/running_wflow.html @@ -0,0 +1,902 @@ + + + + + + + + + +Running a simulation – Wflow.jl + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    Running a simulation

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    Using Julia

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    Once you installed Julia and Wflow.jl, a simulation can be started from the command line as follows:

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    julia -e 'using Wflow; Wflow.run()' path/to/config.toml
    +

    Furthermore, it is possible to write a Julia script to run a simulation. Example data to explore how this works can be found here.

    +
    using Wflow
    +Wflow.run(toml_path)
    +

    Julia can also be used to modify settings after reading the settings file. In the example below, we show how to adjust the end date of the simulation.

    +
    using Dates
    +config = Wflow.Config(toml_path)
    +config.endtime = DateTime("2000-01-03T00:00:00")
    +Wflow.run(config)
    +
    +
    +

    Using the command line interface

    +

    If you don’t need the extra features of using wflow as a library, but just want to run simulations, the command line interface makes it easier to do so. It consists of a single executable, wflow_cli that accepts a single argument, the path to a TOML configuration file.

    +

    Binaries of wflow_cli can be downloaded from our website download.deltares.nl, and are currently available for Windows.

    +

    After installing you can see three folders in the installation directory. It is only the bin/wflow_cli that is directly used. All three folders need to stay together however. The share folder contains TOML files with more information about the build.

    +
    bin\wflow_cli
    +lib
    +share
    +

    Simply running wflow_cli with no arguments will give the following message:

    +
    Usage: wflow_cli 'path/to/config.toml'
    +

    When starting a run, you will see basic run information on the screen, as well as a progress bar, that gives an estimate of how much time is needed to finish the simulation:

    +
     Info: Run information
    +   model_type = "sbm"
    +   starttime = CFTime.DateTimeStandard(2000-01-01T00:00:00)
    +   dt = 86400 seconds
    +   endtime = CFTime.DateTimeStandard(2000-12-31T00:00:00)
    +   nthreads() = 4
    +
    +Progress: 100%|██████████████████████████████████████████████████| Time: 0:00:27
    + + +
    + + Back to top
    + +
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    + + + + + \ No newline at end of file diff --git a/previews/PR448/home/case_studies.html b/previews/PR448/home/case_studies.html new file mode 100644 index 000000000..28b41111d --- /dev/null +++ b/previews/PR448/home/case_studies.html @@ -0,0 +1,852 @@ + + + + + + + + + +Case studies – Wflow.jl + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    Case studies

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    Wflow models for the Meuse and Rhine

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    Reliable hydrological models for the Rhine and the Meuse river basins are necessary for short-term forecasting of river flows and long-term predictions for strategic water management planning. In collaboration with Rijkswaterstaat, Deltares is developing a new line of models for the Rhine and the Meuse basins. The models will be used for forecasting and to estimate the impact of climate change on water resources and extreme streamflow. In the model development, we aim to improve hydrological predictions by including relevant processes in the model schematization. The modularity of the wflow framework is ideal for this as we can easily evaluate the combination of different vertical and lateral model components. For example, the local inertial routing for river and overland flow enables us to consider retention of water in the floodplains, which is likely to improve extreme streamflow predictions.

    +

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    Operational flood forecasting in Australia

    +

    In Australia, there was a need for high-resolution, fast and accurate rainfall-runoff models to provide boundary conditions for a fast and detailed flood inundation model (SFINCS). The domain of the flood model covers the entire North and East Coast of Australia. Although many gauging stations are available to provide real-time information, many rivers are not covered. For these locations, wflow_sbm models are used to provide this real-time information. Additionally, these models are used to provide projections for potential future scenarios. Using the HydroMT library, all wflow_sbm models were automatically built. The high level of flexibility in spatial and temporal resolution, combined with the physics-based nature of the concept, makes Wflow_sbm particularly suitable for ungauged basins. Furthermore, the model is detailed and computationally efficient enough for coupling with the fast flood inundation model SFINCS.

    +

    +

    The results of this proof of concept are very promising. Technically, we were able to quickly set up the wflow_sbm models, couple them to the flood inundation models (SFINCS), and run the models operationally under the Delft-FEWS platform. Model validation was conducted for two basins by comparing the results of Wflow_sbm against observations and the results of calibrated URBS models. This validation demonstrated that the uncalibrated Wflow_sbm model results were already quite satisfactory, especially given the complex nature of these basins, which include several small and large reservoirs. We could also show the potential for further calibration by adjusting the KsatHorFrac parameter.

    +

    De Kleermaeker, S., Leijnse, T., Morales, Y., Druery, C., & Maguire, S. (2022). Developing a real-time data and modelling framework for operational flood inundation forecasting in Australia. In Hydrology & Water Resources Symposium 2022 (HWRS 2022): The Past, the Present, the Future. Engineers Australia. https://search.informit.org/doi/10.3316/informit.916755150845355

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    +
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    +

    Simulating plastic transport in Thailand

    +

    For the Pollution Control Board of the Government of Thailand and the World Bank, we supported a material flow analysis of plastics in Thailand using wflow. Plastic pollution is a growing global issue. Plastic waste enters rivers and is transported to the ocean where it persists and threatens the health of the ocean, seas and coasts. The initial movement of plastic waste is in many cases triggered by runoff from (heavy) rainfall and transported by water flow towards small streams and rivers. Therefore there is strong relation to rainfall-runoff processes, which can be modeled using high-resolution rainfall-runoff models.

    +

    In this study we applied the wflow_sbm model in combination with a fate-and-transport and water quality model (DelWaq) to simulate the movement of plastics through five large river basins and on three island and coastal zones (Krabi, Phuket, and Ko Samui; see screenshot of the model below) in Thailand. Together with our partners Panya Consultants and HII, we were able to identify hotspots of plastic pollution, estimate how much plastic waste would end up in the Gulf of Thailand and recommend priority areas for reducing plastic waste reaching the sea.

    +

    +

    The wflow_sbm models for the five large basins were calibrated. The presence of large dams and reservoirs complicated calibration, but with the input for the dam operation, the model performance for these basins could be largely improved. The figure below shows the calibrated model results for the Chao Phraya, just upstream of Bangkok. The input from the hydrological wflow_sbm model was used as input for the fate and transport model to assess the amount of plastic transported to the ocean.

    +

    +

    Link to World Bank report: https://www.worldbank.org/en/country/thailand/publication/plastic-waste-material-flow-analysis-for-thailand

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    + + Back to top
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    + + + + + \ No newline at end of file diff --git a/previews/PR448/home/publications.html b/previews/PR448/home/publications.html new file mode 100644 index 000000000..cfb1f963d --- /dev/null +++ b/previews/PR448/home/publications.html @@ -0,0 +1,914 @@ + + + + + + + + + +Publications – Wflow.jl + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    Publications

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    Citing wflow

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    For publications, please cite the following paper introducing Wflow.jl and describing the wflow_sbm concept, together with some case studies:

    +

    van Verseveld, W. J., Weerts, A. H., Visser, M., Buitink, J., Imhoff, R. O., Boisgontier, H., Bouaziz, L., Eilander, D., Hegnauer, M., ten Velden, C., and Russell, B., 2024. Wflow_sbm v0.7.3, a spatially distributed hydrological model: from global data to local applications. Geosci. Model Dev., 17, 3199–3234. https://doi.org/10.5194/gmd-17-3199-2024.

    +

    To cite a specific software version please use the DOI provided in the Zenodo badge DOI, that points to the latest release. The DOIs of previous versions are also available at Zenodo. If you use a snapshot of the development (without a DOI) please cite as follows:

    +

    van Verseveld, Willem, Visser, Martijn, Buitink, Joost, Bouaziz, Laurène, Boisgontier, Hélène, Bootsma, Huite, Weerts, Albrecht, Baptista, Carlos Fernando, Pronk, Maarten, Eilander, Dirk, Hartgring, Sebastian, Dalmijn, Brendan, Hofer, Julian, Hegnauer, Mark, & Mendoza, Raul, (YEAR). Deltares/Wflow.jl: unstable-master. https://github.com/Deltares/Wflow.jl, obtained: DATE_OF_DOWNLOAD.

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    Publications using wflow

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    Peer reviewed journal papers

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    Aerts, J. P. M., Hut, R. W., van de Giesen, N. C., Drost, N., van Verseveld, W. J., Weerts, A. H., and Hazenberg, P., 2022. Large-sample assessment of varying spatial resolution on the streamflow estimates of the wflow_sbm hydrological model. Hydrol. Earth Syst. Sci., 26, 4407–4430. https://doi.org/10.5194/hess-26-4407-2022.

    +

    de Boer-Euser, T., Bouaziz, L., De Niel, J., Brauer, C., Dewals, B., Drogue, G., Fenicia, F., Grelier, B., Nossent, J., Pereira, F., Savenije, H., Thirel, G., Willems, P., 2017. Looking beyond general metrics for model comparison – lessons from an international model intercomparison study. Hydrol. Earth Syst. Sci. 21, 423–440. https://doi:10.5194/hess-21-423-2017.

    +

    Bouaziz, L.J.E., Fenicia, F., Thirel, G., de Boer-Euser, T., Buitink, J., Brauer, C.C., De Niel, J., Dewals, B.J., Drogue, G., Grelier, B., Melsen, L. A., Moustakas, S., Nossent, J., Pereira, F., Sprokkereef, E., Stam, J., Weerts, A.H., Willems, P., Savenije, H.H.G., Hrachowitz, M., 2021. Behind the scenes of streamflow model performance. Hydrol. Earth Syst. Sci., 25, 1069–1095. https://doi.org/10.5194/hess-25-1069-2021.

    +

    Bouaziz, L. J. E., Aalbers, E. E., Weerts, A. H., Hegnauer, M., Buiteveld, H., Lammersen, R., Stam, J., Sprokkereef, E., Savenije, H. H. G., and Hrachowitz, M., 2022. Ecosystem adaptation to climate change: the sensitivity of hydrological predictions to time-dynamic model parameters, Hydrol. Earth Syst. Sci., 26, 1295–1318. https://doi.org/10.5194/hess-26-1295-2022.

    +

    Casson, D. R., Werner, M., Weerts, A., and Solomatine, D., 2018. Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed. Hydrol. Earth Syst. Sci., 22, 4685–4697. https://doi.org/10.5194/hess-22-4685-2018.

    +

    Droppers, B., Rakovec, O., Avila, L., Azimi, S., Cortés-Torres N., De León Pérez, D., Imhoff, R., Francés, F., Kollet, S., Rigon, R., Weerts, A. & Samaniego, L, 2024. Multi-model hydrological reference dataset over continental Europe and an African basin. Sci Data, 11, 1009. https://doi.org/10.1038/s41597-024-03825-9.

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    Droppers, B., Rakovec, O., Avila, L., Azimi, S., Cortés-Torres N., De León Pérez, D., Imhoff, R., Francés, F., Kollet, S., Rigon, R., Weerts, A. & Samaniego, L, 2024. Multi-model hydrological reference dataset over continental Europe and an African basin. Sci Data, 11, 1009. https://doi.org/10.1038/s41597-024-03825-9.

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    Emerton, R.E., Stephens, E.M., Pappenberger, F., Pagano, T.C., Weerts, A.H., Wood, A.W., Salamon, P., Brown, J.D., Hjerdt, N., Donnelly, C., Baugh, C.A., Cloke, H.L., 2016. Continental and global scale flood forecasting systems. WIREs Water 3, 391–418. https://doi.org/10.1002/wat2.1137.

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    Gebremicael, T.G., Mohamed, Y.A., Van der Zaag, P., 2019. Attributing the hydrological impact of different land use types and their long-term dynamics through combining parsimonious hydrological modelling, alteration analysis and PLSR analysis. Science of The Total Environment, 660, 1155-1167, https://doi.org/10.1016/jscitotenv.2019.01.085.

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    Giardino, A., Schrijvershof, R., Nederhoff, C.M., de Vroeg, H., Brière, C., Tonnon, P.-K., Caires, S., Walstra, D.J., Sosa, J., van Verseveld, W., Schellekens, J., Sloff, C.J., 2018. A quantitative assessment of human interventions and climate change on the West African sediment budget, Ocean & Coastal Management, 156, 249-265. https://doi.org/10.1016/j.ocecoaman.2017.11.008.

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    Hally, A., Caumont, O., Garrote, L., Richard, E., Weerts, A., Delogu, F., Fiori, E., Rebora, N., Parodi, A., Mihalović, A., Ivković, M., Dekić, L., van Verseveld, W., Nuissier, O., Ducrocq, V., D’Agostino, D., Galizia, A., Danovaro, E., Clematis, A., 2015. Hydrometeorological multi-model ensemble simulations of the 4 November 2011 flash flood event in Genoa, Italy, in the framework of the DRIHM project. Nat. Hazards Earth Syst. Sci. 15, 537–555. https://doi:10.5194/nhess-15-537-2015.

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    Hassaballah, K., Mohamed, Y., Uhlenbrook, S., and Biro, K., 2017. Analysis of streamflow response to land use and land cover changes using satellite data and hydrological modelling: case study of Dinder and Rahad tributaries of the Blue Nile (Ethiopia–Sudan), Hydrol. Earth Syst. Sci., 21, 5217–5242. https://doi.org/10.5194/hess-21-5217-2017.

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    Imhoff, R.O., Buitink, J., van Verseveld, W.J., Weerts, A.H., 2024. A fast high resolution distributed hydrological model for forecasting, climate scenarios and digital twin applications using wflow_sbm. Environmental Modelling & Software, 179, 106099. https://doi.org/10.1016/j.envsoft.2024.106099

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    Imhoff, R.O, van Verseveld, W.J., van Osnabrugge, B., Weerts, A.H., 2020. Scaling Point-Scale (Pedo)transfer Functions to Seamless Large-Domain Parameter Estimates for High-Resolution Distributed Hydrologic Modeling: An Example for the Rhine River. Water Resources Research, 56, e2019WR026807. https://doi.org/10.1029/2019WR026807.

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    Imhoff, R.O., van Verseveld, W., van Osnabrugge, B., Weerts, A.H., 2020. Ruimtelijk schaalbare hydrologische modelparameters uit open-source omgevingsdata: een voorbeeld voor de Rijn. Stromingen: vakblad voor hydrologen, 26(3), 19-36 https://edepot.wur.nl/540682.

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    Jeuken, A., Bouaziz, L., Corzo, G., Alfonso, L., 2016. Analyzing Needs for Climate Change Adaptation in the Magdalena River Basin in Colombia, in: Filho, W.L., Musa, H., Cavan, G., O’Hare, P., Seixas, J. (Eds.), Climate Change Adaptation, Resilience and Hazards, Climate Change Management. Springer International Publishing, pp. 329–344 https://doi.org/10.1007/978-3-319-39880-8.

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    López López, P., Wanders, N., Schellekens, J., Renzullo, L.J., Sutanudjaja, E.H., Bierkens, M.F.P., 2016. Improved large-scale hydrological modelling through the assimilation of streamflow and downscaled satellite soil moisture observations. Hydrol. Earth Syst. Sci., 20, 3059–3076. https://doi.org/10.5194/hess-20-3059-2016.

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    Pranoto, B., Soekarno, H., Hartulistiyoso, E., Nur Aidi, M., Sutrisno, D., Pohan, D., Radhika, Sutejo, B., Heru Kuncoro, A., Nahib, I., 2024. Integrating Flood Early Warning System (FEWS) for Optimizing Small Hydropower Sites: A West Java Case Study. EVERGREEN Joint Journal of Novel Carbon Resource Sciences & Green Asia Strategy, 11, 3, 2691-2699. https://www.tj.kyushu-u.ac.jp/evergreen/contents/EG2024-11_3_content/pdf/p2691-2699.pdf

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    Rakovec, O., Weerts, A.H., Sumihar, J., Uijlenhoet, R., 2015. Operational aspects of asynchronous filtering for flood forecasting. Hydrol. Earth Syst. Sci., 19, 2911–2924, https://doi.org/10.5194/hess-19-2911-2015.

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    Ratri, D.N., A.H. Weerts, R. Muharsyah, K. Whan, A. Klein Tank, E. Aldrian, M. H. Hariadi, Calibration of ECMWF SEAS5 based streamflow forecast in Seasonal hydrological forecasting for Citarum river basin, West Java, Indonesia, Journal of Hydrology: Regional Studies,45,101305, https://doi.org/10.1016/j.ejrh.2022.101305.

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    Rusli, S.R., A.H. Weerts, A. Taufiq, V. Bense, 2021. Estimating water balance components and their uncertainty bounds in highly groundwater-dependent and data-scarce area: An example for the Upper Citarum basin, J. Hydrol. Regional Studies, https://doi.org/10.1016/j.ejrh.2021.100911.

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    Rusli, S.R., V.F. Bense, A. Taufiq, A.H. Weerts,2023. Quantifying basin-scale changes in groundwater storage using GRACE and one-way coupled hydrological and groundwater flow model in the data-scarce Bandung groundwater Basin, Indonesia, Groundwater for Sustainable Development,22, 100953, https://doi.org/10.1016/j.gsd.2023.100953.

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    Rusli, S.R., A.H. Weerts, S.M.T. Mustafa, D.E. Irawan, A. Taufiq, V.F. Bense, 2023. Quantifying aquifer interaction using numerical groundwater flow model evaluated by environmental water tracer data: Application to the data-scarce area of the Bandung groundwater basin, West Java, Indonesia, Journal of Hydrology: Regional Studies, 50, https://doi.org/10.1016/j.ejrh.2023.101585.

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    Schaller, N., Sillmann, J., Müller, M., Haarsma, R., Hazeleger, W., Hegdahl, T.J., Kelder, T., van den Oord, G., Weerts, A., Whan, K., 2020. The role of spatial and temporal model resolution in a flood event storyline approach in western Norway. Weather and Climate Extremes, doi: https://doi.org/10.1016/j.wace.2020.100259.

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    Seizarwati, W. and M. Syahidah, 2021. Rainfall-Runoff Simulation for Water Availability Estimation in Small Island Using Distributed Hydrological Model wflow. IOP Conf. Ser.: Earth Environ. Sci., 930,012050, doi:10.1088/1755-1315/930/1/012050. https://iopscience.iop.org/article/10.1088/1755-1315/930/1/012050/pdf

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    Sperna Weiland, F.C., R.D. Visser, P. Greve, B. Bisselink, L. Brunner and A.H. Weerts, 2021. Estimating Regionalized Hydrological Impacts of Climate Change Over Europe by Performance-Based Weighting of CORDEX Projections, Frontiers of Water, https://doi.org/10.3389/frwa.2021.713537.

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    Tangdamrongsub, N., Steele-Dunne, S.C., Gunter, B.C., Ditmar, P.G., Weerts, A.H., 2015. Data assimilation of GRACE terrestrial water storage estimates into a regional hydrological model of the Rhine River basin. Hydrol. Earth Syst. Sci. 19, 2079–2100. https://doi:10.5194/hess-19-2079-2015.

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    van der Laan, E., P. Hazenberg, A.H. Weerts, 2024. Simulation of long-term storage dynamics of headwater reservoirs across the globe using public cloud computing infrastructure. Science of The Total Environment, 172678, https://doi.org/10.1016/j.scitotenv.2024.172678.

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    Pranoto, B., Soekarno, H., Hartulistiyoso, E., Nur Aidi, M., Sutrisno, D., Pohan, D., Radhika, Sutejo, B., Heru Kuncoro, A., Nahib, I., 2024. Integrating Flood Early Warning System (FEWS) for Optimizing Small Hydropower Sites: A West Java Case Study. EVERGREEN Joint Journal of Novel Carbon Resource Sciences & Green Asia Strategy, 11, 3, 2691-2699. https://www.tj.kyushu-u.ac.jp/evergreen/contents/EG2024-11_3_content/pdf/p2691-2699.pdf

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    van Osnabrugge, B., Weerts, A.H., Uijlenhoet, R., 2017. genRE: A method to extend gridded precipitation climatology data sets in near real-time for hydrological forecasting purposes. Water Resources Research, 53. https://doi.org/10.1002/2017WR021201.

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    van Osnabrugge, B., Uijlenhoet, R., Weerts, A., 2019. Contribution of potential evaporation forecasts to 10-day streamflow forecast skill for the Rhine River, Hydrol. Earth Syst. Sci., 23, 1453–1467, https://doi.org/10.5194/hess-23-1453-2019.

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    van der Vat, M., Boderie, P., Bons, K.A., Hegnauer, M., Hendriksen, G., van Oorschot, M., Ottow, B., Roelofsen, F., Sankhua, R.N., Sinha, S.K., Warren, A., Young, W., 2019. Participatory Modelling of Surface and Groundwater to Support Strategic Planning in the Ganga Basin in India. Water, 11, 2443. https://doi.org/10.3390/w11122443.

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    Wannasin, C., Brauer, C. C., Uijlenhoet, R., van Verseveld, W. J., Weerts, A. H., 2021. Daily flow simulation in Thailand Part I: Testing a distributed hydrological model with seamless parameter maps based on global data. Journal of Hydrology: Regional Studies, 34, 1-19. https://doi.org/10.1016/j.ejrh.2021.100794.

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    Wannasin, C., Brauer, C. C., Uijlenhoet, R., van Verseveld, W. J., Weerts, A. H., 2021. Daily flow simulation in Thailand Part II: Unraveling effects of reservoir operation. Journal of Hydrology: RegionalStudies, 34, 1-17. https://doi.org/10.1016/j.ejrh.2021.100792.

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    Wang, X., Zhang, J., Babovic, V., 2016. Improving real-time forecasting of water quality indicators with combination of process-based models and data assimilation technique. Ecological Indicators 66, 428–439. https://doi:10.1016/j.ecolind.2016.02.016.

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    PhD, MSc, BSc Theses & Internship reports

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    Abdelnour, A., 2022. Bias Correction of Climate Simulations to Assess Climate Change Impacts on Low Flows in the Rhine River, MSc thesis, Delft Universitry of technology, https://repository.tudelft.nl/islandora/object/uuid:50489399-cbd2-467f-9b82-98e5f3e371e9.

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    Ali, M.A., 2023. Machine learning for predicting spatially variable lateral hydraulic conductivity: a step towards efficient hydrological model calibration and global applicability, Intersnhip report, Deltares.

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    Arnal, L., 2014. An intercomparison of flood forecasting models for the Meuse River basin, MSc Thesis, Vrije Universiteit, Amsterdam, https://hal.inrae.fr/hal-02600749.

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    Alkemade, G., 2019. Routing and calibration of distributed hydrological models, MSc Thesis, Vrije Universiteit, Amsterdam, Faculty of Science, Hydrology.

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    Azadeh Karami Fard, 2015. Modeling runoff of an Ethiopian catchment with WFLOW, MSc. Thesis, Vrije Universiteit, Amsterdam.

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    Benschop, J., 2023. The application of hybrid lateral routing in hydrological simulations of the Rhine catchment, MSc Thesis, Hydrology and Environmental Hydraulics Group, Wageningen University.

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    Beusen, B., 2021. The effect of rooting depth on discharge and evapotranspiration in (semi-)arid areas, MSc Thesis, Hydrology and Quantitative Water Management Group, Wageningen University.

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    Beusen, B., 2021. Plastic transport and the effect of climate change in the Rhine, Internship report, Deltares.

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    Bouaziz, L. J. E., 2021. Internal processes in hydrological models: A glance at the Meuse basin from space. Delft University of Technology, Delft, the Netherlands, Doctoral dissertation, https://doi.org/10.4233/uuid:09d84cc1-27e2-4327-a8c7-207a75952061.

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    Hartgring, S., 2023. On Forecasting the Rur River: Using hindcasts and forecasts of the 2021 flood event to improve understanding of flood forecasting in the Rur catchment. Delft University of Technology, Delft, the Netherlands, MSc thesis, http://resolver.tudelft.nl/uuid:2909d997-a983-490a-a588-87119998543a.

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    Jaime, D.E.V, 2021. Ensemble hydrological forecasts to derive extreme return periods: Case Study of the Overijsselse Vecht River using the wflow_sbm model, MSc thesis, Unesco IHE, Delft.

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    López López, P., 2018. Application of Global Hydrological Datasets for River Basin Modelling Utrecht University, Utrecht, the Netherlands, pp. 1-214, Doctoral dissertation, http://dspace.library.uu.nl/handle/1874/364148.

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    Maat, W.H., 2015. Simulating discharges and forecasting floods using a conceptual rainfall-runoff model for the Bolivian Mamoré basin, MSc Thesis, University of Twente, Enschede. https://essay.utwente.nl/67046/.

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    van Osnabrugge, B., 2020. Interpolate, simulate, assimilate: operational aspects of improving hydrological forecasts in the Rhine basin. Wageningen University, Doctoral dissertation, https://doi.org/10.18174/513157.

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    Rohrmueller, I., 2019. BENCHMARKING THE NEW WFLOW DISTRIBUTED HYDROLOGICAL MODEL, MSc Thesis, School of Engineering - Newcastle University.

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    Rusli, S.R., 2024. Deepening the quantitative understanding of groundwater systems in data-scarce areas: application in the Bandung Groundwater Basin, Indonesia. Wageningen University, Doctoral dissertation, https://doi.org/10.18174/640983.

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    Tretjakova, D., 2015. Investigating the effect of using fully-distributed model and data assimilation on the performance of hydrological forecasting in the Karasu catchment, Turkey, MSc thesis, Wageningen University.

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    van der Gaast, R.H., 2024. Evaluating the transferability of data-driven pedo-transfer functions for the wflow_sbm parameter KsatHorFrac in central and Western Europe. Universiteit Twente, Enschede, The Netherlands, https://essay.utwente.nl/103634/1/vandergaast_MA_ET.pdf.

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    Verbrugge, M., 2019. Reservoir Operation Optimization, a case study in the Chao Phraya Basin, BSc thesis, Hydrology and Quantitative Water Management Group, Wageningen University.

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    Verbrugge, M., 2023. Bias-correcting meteorological forcing to improve seasonal discharge forecasting of the Rhine, Internship report, Deltares.

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    Viguures, P., 2020. Modelling of flash floods in current and future climate with high resolution convection permitting regional climate models in the European Alps, MSc Thesis, Wageningen University.

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    Visser, B., 2020. Impact of climate change on local water resources of European catchments, Intersnhip report, Deltares.

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    Wannasin, C., 2023. Modelling and forecasting daily streamflow with reservoir operation in the upper Chao Phraya River basin, Thailand. Wageningen University, Doctoral dissertation, https://doi.org/10.18174/584572.

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    Reports

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    World Bank. 2021. Plastic Waste Discharges from Rivers and Coastlines in Indonesia. Marine Plastics Series;. World Bank, Washington, DC. © World Bank, https://openknowledge.worldbank.org/handle/10986/35607, License: CC BY 3.0 IGO.

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    World Meteorological Organization (WMO), 2023. State of Global Water Resources report 2022, WMO-No. 1333, https://library.wmo.int/idurl/4/68473.

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    World Meteorological Organization (WMO), 2024. State of Global Water Resources report 2023, WMO-No. 1362, https://library.wmo.int/idurl/4/69033.

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