Ribasim Delwaq coupling

In order to generate the Delwaq input files, we need a completed Ribasim simulation (typically one with a results folder) that ideally also includes some substances and initial concentrations. Let’s take the basic test model for example, which already has set some initial concentrations.

All testmodels can be downloaded from here.

1 Generating Delwaq input

from pathlib import Path

toml_path = Path("../../generated_testmodels/basic/ribasim.toml")

assert toml_path.is_file()

This Ribasim model already has substance concentrations for Cl and Tracer in the input tables, and we will use these to generate the Delwaq input files.

from ribasim import Model

model = Model.read(toml_path)

display(model.basin.concentration_state)  # basin initial state
display(model.basin.concentration)  # basin boundaries
display(model.flow_boundary.concentration)  # flow boundaries
display(model.level_boundary.concentration)  # level boundaries
model.plot();  # for later comparison
Basin / concentration_state
node_id substance concentration
fid
0 1 Cl 0.0
1 3 Cl 0.0
2 6 Cl 0.0
3 9 Cl 0.0
Basin / concentration
node_id time substance drainage precipitation surface_runoff
fid
0 1 2020-01-01 Cl 0.0 0.0 0.0
1 1 2020-01-02 Cl 1.0 1.0 1.0
2 1 2020-01-01 Tracer 1.0 1.0 1.0
3 3 2020-01-01 Cl 0.0 0.0 0.0
4 3 2020-01-02 Cl 1.0 1.0 1.0
5 3 2020-01-01 Tracer 1.0 1.0 1.0
6 6 2020-01-01 Cl 0.0 0.0 0.0
7 6 2020-01-02 Cl 1.0 1.0 1.0
8 6 2020-01-01 Tracer 1.0 1.0 1.0
9 9 2020-01-01 Cl 0.0 0.0 0.0
10 9 2020-01-02 Cl 1.0 1.0 1.0
11 9 2020-01-01 Tracer 1.0 1.0 1.0
FlowBoundary / concentration
node_id time substance concentration
fid
0 15 2020-01-01 Cl 0.0
1 15 2020-01-01 Tracer 1.0
2 16 2020-01-01 Cl 0.0
3 16 2020-01-01 Tracer 1.0
LevelBoundary / concentration
node_id time substance concentration
fid
0 11 2020-01-01 Cl 34.0
1 17 2020-01-01 Cl 34.0

model.basin.profile
Basin / profile
node_id area level storage
fid
0 1 0.01 0.0 NaN
1 1 1000.00 1.0 NaN
2 3 0.01 0.0 NaN
3 3 1000.00 1.0 NaN
4 6 0.01 0.0 NaN
5 6 1000.00 1.0 NaN
6 9 0.01 0.0 NaN
7 9 1000.00 1.0 NaN

Let’s add another tracer to the model, to setup a fraction calculation.

from ribasim.delwaq import add_tracer

add_tracer(model, 11, "Foo")
add_tracer(model, 15, "Bar")
display(model.flow_boundary.concentration)  # flow boundaries
display(model.level_boundary.concentration)  # flow boundaries

model.write(toml_path)
FlowBoundary / concentration
node_id time substance concentration
fid
0 15 2020-01-01 Cl 0.0
1 15 2020-01-01 Tracer 1.0
2 16 2020-01-01 Cl 0.0
3 16 2020-01-01 Tracer 1.0
4 15 2020-01-01 Bar 1.0
LevelBoundary / concentration
node_id time substance concentration
fid
0 11 2020-01-01 Cl 34.0
1 17 2020-01-01 Cl 34.0
2 11 2020-01-01 Foo 1.0
PosixPath('../../generated_testmodels/basic/ribasim.toml')

Given the path to a completed Ribasim simulation, we can call ribasim.delwaq.generate for generating the required input files for Delwaq from scratch. ribasim.delwaq.generate either takes a Model instance, or the path to a toml file, as well as an output_path keyword, where the input for Delwaq will be written. By default it is set to the delwaq folder next to the toml.

from ribasim.delwaq import generate

# The default path is the delwaq folder next to the toml
output_path = Path("../../generated_testmodels/basic/delwaq")

graph, substances = generate(model, output_path)
/home/runner/work/Ribasim/Ribasim/python/ribasim/ribasim/delwaq/generate.py:486: SettingWithCopyWarning:


A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy

This call produces a handful of files in the user defined folder. Let’s take a look at them:

list(output_path.iterdir())
[PosixPath('../../generated_testmodels/basic/delwaq/B5_bounddata.inc'),
 PosixPath('../../generated_testmodels/basic/delwaq/ribasim.atr'),
 PosixPath('../../generated_testmodels/basic/delwaq/ribasim.vel'),
 PosixPath('../../generated_testmodels/basic/delwaq/ribasim.vol'),
 PosixPath('../../generated_testmodels/basic/delwaq/delwaq.inp'),
 PosixPath('../../generated_testmodels/basic/delwaq/bndlist.csv'),
 PosixPath('../../generated_testmodels/basic/delwaq/ribasim.are'),
 PosixPath('../../generated_testmodels/basic/delwaq/ribasim.nc'),
 PosixPath('../../generated_testmodels/basic/delwaq/ribasim.poi'),
 PosixPath('../../generated_testmodels/basic/delwaq/dimr_config.xml'),
 PosixPath('../../generated_testmodels/basic/delwaq/ribasim_bndlist.inc'),
 PosixPath('../../generated_testmodels/basic/delwaq/ribasim.len'),
 PosixPath('../../generated_testmodels/basic/delwaq/ribasim.flo'),
 PosixPath('../../generated_testmodels/basic/delwaq/network.csv')]

These files form a complete Delwaq simulation, and can be run by either pointing DIMR to the dimr_config.xml file or pointing Delwaq to the delwaq.inp file.

Note that the call to generate produces two output variables; graph and substances that are required for parsing the results of the Delwaq model later on. Nonetheless, we can also inspect them here, and inspect the created Delwaq network.

substances  # list of substances, as will be present in the Delwaq netcdf output
{'Bar',
 'Cl',
 'Continuity',
 'Drainage',
 'FlowBoundary',
 'Foo',
 'Initial',
 'LevelBoundary',
 'Precipitation',
 'SurfaceRunoff',
 'Tracer',
 'UserDemand'}

As you can see, the complete substances list is a combination of user input (Cl and Tracer in the input tables), a Continuity tracer, and tracers for all nodetypes in the Ribasim model. The latter tracers allow for deeper inspection of the Ribasim model, such as debugging the mass balance by plotting fraction graphs. Let’s inspect the graph next, which is the Delwaq network that was created from the Ribasim model:

import matplotlib.pyplot as plt
import networkx as nx

# Let's draw the graph
fig, ax = plt.subplots(1, 2, figsize=(10, 5))
nx.draw(
    graph,
    pos={k: v["pos"] for k, v in graph.nodes(data=True)},
    with_labels=True,
    labels={k: k for k, v in graph.nodes(data=True)},
    ax=ax[0],
)
ax[0].set_title("Delwaq node IDs")
nx.draw(
    graph,
    pos={k: v["pos"] for k, v in graph.nodes(data=True)},
    with_labels=True,
    labels={k: v["id"] for k, v in graph.nodes(data=True)},
    ax=ax[1],
)
ax[1].set_title("Ribasim node IDs")
fig.suptitle("Delwaq network");

Here we plotted the Delwaq network twice, with the node IDs as used by Delwaq on the left hand side, and the corresponding Ribasim node IDs on the right hand side. As you can see, the Delwaq network is very similar to the Ribasim network, with some notable changes:

  • All non-Basin or non-boundary types are removed (e.g. no more Pumps or TabulatedRatingCurves)
  • Basin boundaries are split into separate nodes and links (drainage, precipitation, and evaporation, as indicated by the duplicated Basin IDs on the right hand side)
  • All node IDs have been renumbered, with boundaries being negative, and Basins being positive.

2 Parsing the results

With Delwaq having run, we can now parse the results using ribasim.delwaq.parse. This function requires either a path to a toml file, or a Model instance, as well as the graph and substances variables that were output by ribasim.delwaq.generate. You can optionally set the path to the results folder of the Delwaq simulation, if you overrode the default during ribasim.delwaq.generate.

from ribasim.delwaq import parse

nmodel = parse(model, graph, substances)

The parsed model is identical to the Ribasim model, with the exception of the added concentration_external table that contains all tracer results from Delwaq.

display(nmodel.basin.concentration_external)
print(substances)
t = nmodel.basin.concentration_external.df
t[t.time == t.time.unique()[2]]
Basin / concentration_external
time node_id concentration substance
fid
0 2020-01-01 1 0.000000 SurfaceRunoff
1464 2020-01-01 1 0.000000 Bar
2928 2020-01-01 1 0.000000 FlowBoundary
4392 2020-01-01 1 1.000000 Initial
5856 2020-01-01 1 0.000000 Precipitation
... ... ... ... ...
11711 2020-12-31 9 0.980566 Tracer
13175 2020-12-31 9 0.000000 Drainage
14639 2020-12-31 9 0.009058 Foo
16103 2020-12-31 9 0.657784 Cl
17567 2020-12-31 9 0.000000 UserDemand

17568 rows × 4 columns

{'SurfaceRunoff', 'Bar', 'FlowBoundary', 'Initial', 'Precipitation', 'LevelBoundary', 'Continuity', 'Tracer', 'Drainage', 'Foo', 'Cl', 'UserDemand'}
time node_id concentration substance
fid
8 2020-01-03 1 0.083137 SurfaceRunoff
1472 2020-01-03 1 0.000000 Bar
2936 2020-01-03 1 0.618849 FlowBoundary
4400 2020-01-03 1 0.044320 Initial
5864 2020-01-03 1 0.083137 Precipitation
7328 2020-01-03 1 0.170558 LevelBoundary
8792 2020-01-03 1 1.000000 Continuity
10256 2020-01-03 1 0.785122 Tracer
11720 2020-01-03 1 0.000000 Drainage
13184 2020-01-03 1 0.170558 Foo
14648 2020-01-03 1 5.798967 Cl
16112 2020-01-03 1 0.000000 UserDemand
9 2020-01-03 3 0.059426 SurfaceRunoff
1473 2020-01-03 3 0.000000 Bar
2937 2020-01-03 3 0.000000 FlowBoundary
4401 2020-01-03 3 0.026624 Initial
5865 2020-01-03 3 0.059426 Precipitation
7329 2020-01-03 3 0.854524 LevelBoundary
8793 2020-01-03 3 1.000000 Continuity
10257 2020-01-03 3 0.118852 Tracer
11721 2020-01-03 3 0.000000 Drainage
13185 2020-01-03 3 0.854524 Foo
14649 2020-01-03 3 29.053822 Cl
16113 2020-01-03 3 0.000000 UserDemand
10 2020-01-03 6 0.091422 SurfaceRunoff
1474 2020-01-03 6 0.782941 Bar
2938 2020-01-03 6 0.782941 FlowBoundary
4402 2020-01-03 6 0.022596 Initial
5866 2020-01-03 6 0.091422 Precipitation
7330 2020-01-03 6 0.011620 LevelBoundary
8794 2020-01-03 6 1.000000 Continuity
10258 2020-01-03 6 0.965784 Tracer
11722 2020-01-03 6 0.000000 Drainage
13186 2020-01-03 6 0.011620 Foo
14650 2020-01-03 6 0.395090 Cl
16114 2020-01-03 6 0.000000 UserDemand
11 2020-01-03 9 0.015870 SurfaceRunoff
1475 2020-01-03 9 0.061339 Bar
2939 2020-01-03 9 0.061339 FlowBoundary
4403 2020-01-03 9 0.008331 Initial
5867 2020-01-03 9 0.015870 Precipitation
7331 2020-01-03 9 0.898591 LevelBoundary
8795 2020-01-03 9 1.000000 Continuity
10259 2020-01-03 9 0.093079 Tracer
11723 2020-01-03 9 0.000000 Drainage
13187 2020-01-03 9 0.000696 Foo
14651 2020-01-03 9 30.552090 Cl
16115 2020-01-03 9 0.000000 UserDemand

We can use this table to plot the results of the Delwaq model, both spatially as over time.

from ribasim.delwaq import plot_fraction

plot_fraction(nmodel, 1)  # default tracers, should add up to 1
plot_fraction(nmodel, 9, ["Foo", "Bar"])  # custom tracers
plot_fraction(nmodel, 9, ["Continuity"])  # mass balance check

from ribasim.delwaq import plot_spatial

plot_spatial(nmodel, "Bar")
plot_spatial(nmodel, "Foo", versus="Bar")