Code
using Ribasim
@@ -597,27 +597,27 @@ println(p.allocation.allocation_models[1].problem)
-
Min F[(Basin #5, UserDemand #6)]² + F[(Basin #2, UserDemand #3)]²
+Min F[(Basin #2, UserDemand #3)]² + F[(Basin #5, UserDemand #6)]²
Subject to
flow_conservation[Basin #5] : -F[(Basin #5, TabulatedRatingCurve #7)] + F[(LinearResistance #4, Basin #5)] - F[(Basin #5, LinearResistance #4)] + F[(UserDemand #6, Basin #5)] - F[(Basin #5, UserDemand #6)] = 0
- flow_conservation[Basin #2] : -F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] + F[(UserDemand #3, Basin #2)] + F[(FlowBoundary #1, Basin #2)] - F[(Basin #2, UserDemand #3)] = 0
flow_conservation[Terminal #8] : F[(TabulatedRatingCurve #7, Terminal #8)] = 0
- flow_conservation[LinearResistance #4] : F[(Basin #2, LinearResistance #4)] - F[(LinearResistance #4, Basin #2)] - F[(LinearResistance #4, Basin #5)] + F[(Basin #5, LinearResistance #4)] = 0
+ flow_conservation[LinearResistance #4] : -F[(LinearResistance #4, Basin #5)] + F[(Basin #5, LinearResistance #4)] + F[(Basin #2, LinearResistance #4)] - F[(LinearResistance #4, Basin #2)] = 0
flow_conservation[TabulatedRatingCurve #7] : F[(Basin #5, TabulatedRatingCurve #7)] - F[(TabulatedRatingCurve #7, Terminal #8)] = 0
+ flow_conservation[Basin #2] : F[(UserDemand #3, Basin #2)] - F[(Basin #2, UserDemand #3)] - F[(Basin #2, LinearResistance #4)] + F[(LinearResistance #4, Basin #2)] + F[(FlowBoundary #1, Basin #2)] = 0
F[(Basin #5, TabulatedRatingCurve #7)] ≥ 0
- F[(Basin #2, LinearResistance #4)] ≥ 0
- F[(LinearResistance #4, Basin #2)] ≥ 0
+ F[(TabulatedRatingCurve #7, Terminal #8)] ≥ 0
+ F[(UserDemand #3, Basin #2)] ≥ 0
F[(LinearResistance #4, Basin #5)] ≥ 0
F[(Basin #5, LinearResistance #4)] ≥ 0
- F[(UserDemand #3, Basin #2)] ≥ 0
+ F[(Basin #2, UserDemand #3)] ≥ 0
F[(UserDemand #6, Basin #5)] ≥ 0
+ F[(Basin #2, LinearResistance #4)] ≥ 0
+ F[(LinearResistance #4, Basin #2)] ≥ 0
F[(Basin #5, UserDemand #6)] ≥ 0
F[(FlowBoundary #1, Basin #2)] ≥ 0
- F[(TabulatedRatingCurve #7, Terminal #8)] ≥ 0
- F[(Basin #2, UserDemand #3)] ≥ 0
source[(FlowBoundary #1, Basin #2)] : F[(FlowBoundary #1, Basin #2)] ≤ 172800
- source_user[UserDemand #6] : F[(UserDemand #6, Basin #5)] ≤ 0
source_user[UserDemand #3] : F[(UserDemand #3, Basin #2)] ≤ 0
+ source_user[UserDemand #6] : F[(UserDemand #6, Basin #5)] ≤ 0
Quick start guide
3 Modual 1 - Crys
-
+
Figure 1: Crystal Basin based on natural flow
@@ -483,7 +483,7 @@
-
+
Figure 2: Basin node concept for the confluence
@@ -575,7 +575,7 @@
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+
Figure 3: Discharge at corresponding water levels
@@ -622,7 +622,7 @@
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+
Figure 4: Schematization of the Crystal basin 1.1
@@ -703,7 +703,7 @@
-
+
Figure 5: Simulated basin level and storage
@@ -714,7 +714,7 @@
-
+
Figure 6: Simulated flows on each edge
@@ -729,7 +729,7 @@
-
+
Figure 7: Crystal basin with irrigation
@@ -838,7 +838,7 @@
-
+
Figure 8: Schematization of the Crystal basin with irrigation
@@ -921,7 +921,7 @@
-
+
Figure 9: Simulated basin levels and storages
@@ -947,7 +947,7 @@
-
+
Figure 10: Simulated flows of each edge
@@ -958,7 +958,7 @@
-
+
Figure 11: Supplied irrigation and return flow
@@ -969,7 +969,7 @@
-
+
Figure 12: Simulated flow to Terminal
@@ -985,7 +985,7 @@ 4 Modual 2 – Re
-
+
Figure 13: Crystal basin with demands and a reservoir
@@ -1055,7 +1055,7 @@
-
+
Figure 14: Simulated basin storages and levels
@@ -1133,7 +1133,7 @@
-
+
Figure 15: Simulated flows to and from the city
@@ -1143,7 +1143,7 @@
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
-
+
Figure 2: Basin node concept for the confluence
@@ -575,7 +575,7 @@
-
+
Figure 3: Discharge at corresponding water levels
@@ -622,7 +622,7 @@
-
+
Figure 4: Schematization of the Crystal basin 1.1
@@ -703,7 +703,7 @@
-
+
Figure 5: Simulated basin level and storage
@@ -714,7 +714,7 @@
-
+
Figure 6: Simulated flows on each edge
@@ -729,7 +729,7 @@
-
+
Figure 7: Crystal basin with irrigation
@@ -838,7 +838,7 @@
-
+
Figure 8: Schematization of the Crystal basin with irrigation
@@ -921,7 +921,7 @@
-
+
Figure 9: Simulated basin levels and storages
@@ -947,7 +947,7 @@
-
+
Figure 10: Simulated flows of each edge
@@ -958,7 +958,7 @@
-
+
Figure 11: Supplied irrigation and return flow
@@ -969,7 +969,7 @@
-
+
Figure 12: Simulated flow to Terminal
@@ -985,7 +985,7 @@ 4 Modual 2 – Re
-
+
Figure 13: Crystal basin with demands and a reservoir
@@ -1055,7 +1055,7 @@
-
+
Figure 14: Simulated basin storages and levels
@@ -1133,7 +1133,7 @@
-
+
Figure 15: Simulated flows to and from the city
@@ -1143,7 +1143,7 @@
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
-
+
Figure 3: Discharge at corresponding water levels
@@ -622,7 +622,7 @@
-
+
Figure 4: Schematization of the Crystal basin 1.1
@@ -703,7 +703,7 @@
-
+
Figure 5: Simulated basin level and storage
@@ -714,7 +714,7 @@
-
+
Figure 6: Simulated flows on each edge
@@ -729,7 +729,7 @@
-
+
Figure 7: Crystal basin with irrigation
@@ -838,7 +838,7 @@
-
+
Figure 8: Schematization of the Crystal basin with irrigation
@@ -921,7 +921,7 @@
-
+
Figure 9: Simulated basin levels and storages
@@ -947,7 +947,7 @@
-
+
Figure 10: Simulated flows of each edge
@@ -958,7 +958,7 @@
-
+
Figure 11: Supplied irrigation and return flow
@@ -969,7 +969,7 @@
-
+
Figure 12: Simulated flow to Terminal
@@ -985,7 +985,7 @@ 4 Modual 2 – Re
-
+
Figure 13: Crystal basin with demands and a reservoir
@@ -1055,7 +1055,7 @@
-
+
Figure 14: Simulated basin storages and levels
@@ -1133,7 +1133,7 @@
-
+
Figure 15: Simulated flows to and from the city
@@ -1143,7 +1143,7 @@
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
-
+
Figure 4: Schematization of the Crystal basin 1.1
@@ -703,7 +703,7 @@
-
+
Figure 5: Simulated basin level and storage
@@ -714,7 +714,7 @@
-
+
Figure 6: Simulated flows on each edge
@@ -729,7 +729,7 @@
-
+
Figure 7: Crystal basin with irrigation
@@ -838,7 +838,7 @@
-
+
Figure 8: Schematization of the Crystal basin with irrigation
@@ -921,7 +921,7 @@
-
+
Figure 9: Simulated basin levels and storages
@@ -947,7 +947,7 @@
-
+
Figure 10: Simulated flows of each edge
@@ -958,7 +958,7 @@
-
+
Figure 11: Supplied irrigation and return flow
@@ -969,7 +969,7 @@
-
+
Figure 12: Simulated flow to Terminal
@@ -985,7 +985,7 @@ 4 Modual 2 – Re
-
+
Figure 13: Crystal basin with demands and a reservoir
@@ -1055,7 +1055,7 @@
-
+
Figure 14: Simulated basin storages and levels
@@ -1133,7 +1133,7 @@
-
+
Figure 15: Simulated flows to and from the city
@@ -1143,7 +1143,7 @@
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
-
+
Figure 5: Simulated basin level and storage
@@ -714,7 +714,7 @@
-
+
Figure 6: Simulated flows on each edge
@@ -729,7 +729,7 @@
-
+
Figure 7: Crystal basin with irrigation
@@ -838,7 +838,7 @@
-
+
Figure 8: Schematization of the Crystal basin with irrigation
@@ -921,7 +921,7 @@
-
+
Figure 9: Simulated basin levels and storages
@@ -947,7 +947,7 @@
-
+
Figure 10: Simulated flows of each edge
@@ -958,7 +958,7 @@
-
+
Figure 11: Supplied irrigation and return flow
@@ -969,7 +969,7 @@
-
+
Figure 12: Simulated flow to Terminal
@@ -985,7 +985,7 @@ 4 Modual 2 – Re
-
+
Figure 13: Crystal basin with demands and a reservoir
@@ -1055,7 +1055,7 @@
-
+
Figure 14: Simulated basin storages and levels
@@ -1133,7 +1133,7 @@
-
+
Figure 15: Simulated flows to and from the city
@@ -1143,7 +1143,7 @@
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
-
+
Figure 6: Simulated flows on each edge
@@ -729,7 +729,7 @@
-
+
Figure 7: Crystal basin with irrigation
@@ -838,7 +838,7 @@
-
+
Figure 8: Schematization of the Crystal basin with irrigation
@@ -921,7 +921,7 @@
-
+
Figure 9: Simulated basin levels and storages
@@ -947,7 +947,7 @@
-
+
Figure 10: Simulated flows of each edge
@@ -958,7 +958,7 @@
-
+
Figure 11: Supplied irrigation and return flow
@@ -969,7 +969,7 @@
-
+
Figure 12: Simulated flow to Terminal
@@ -985,7 +985,7 @@ 4 Modual 2 – Re
-
+
Figure 13: Crystal basin with demands and a reservoir
@@ -1055,7 +1055,7 @@
-
+
Figure 14: Simulated basin storages and levels
@@ -1133,7 +1133,7 @@
-
+
Figure 15: Simulated flows to and from the city
@@ -1143,7 +1143,7 @@
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
-
+
Figure 7: Crystal basin with irrigation
@@ -838,7 +838,7 @@
-
+
Figure 8: Schematization of the Crystal basin with irrigation
@@ -921,7 +921,7 @@
-
+
Figure 9: Simulated basin levels and storages
@@ -947,7 +947,7 @@
-
+
Figure 10: Simulated flows of each edge
@@ -958,7 +958,7 @@
-
+
Figure 11: Supplied irrigation and return flow
@@ -969,7 +969,7 @@
-
+
Figure 12: Simulated flow to Terminal
@@ -985,7 +985,7 @@ 4 Modual 2 – Re
-
+
Figure 13: Crystal basin with demands and a reservoir
@@ -1055,7 +1055,7 @@
-
+
Figure 14: Simulated basin storages and levels
@@ -1133,7 +1133,7 @@
-
+
Figure 15: Simulated flows to and from the city
@@ -1143,7 +1143,7 @@
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
-
+
Figure 8: Schematization of the Crystal basin with irrigation
@@ -921,7 +921,7 @@
-
+
Figure 9: Simulated basin levels and storages
@@ -947,7 +947,7 @@
-
+
Figure 10: Simulated flows of each edge
@@ -958,7 +958,7 @@
-
+
Figure 11: Supplied irrigation and return flow
@@ -969,7 +969,7 @@
-
+
Figure 12: Simulated flow to Terminal
@@ -985,7 +985,7 @@ 4 Modual 2 – Re
-
+
Figure 13: Crystal basin with demands and a reservoir
@@ -1055,7 +1055,7 @@
-
+
Figure 14: Simulated basin storages and levels
@@ -1133,7 +1133,7 @@
-
+
Figure 15: Simulated flows to and from the city
@@ -1143,7 +1143,7 @@
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
-
+
Figure 9: Simulated basin levels and storages
@@ -947,7 +947,7 @@
-
+
Figure 10: Simulated flows of each edge
@@ -958,7 +958,7 @@
-
+
Figure 11: Supplied irrigation and return flow
@@ -969,7 +969,7 @@
-
+
Figure 12: Simulated flow to Terminal
@@ -985,7 +985,7 @@ 4 Modual 2 – Re
-
+
Figure 13: Crystal basin with demands and a reservoir
@@ -1055,7 +1055,7 @@
-
+
Figure 14: Simulated basin storages and levels
@@ -1133,7 +1133,7 @@
-
+
Figure 15: Simulated flows to and from the city
@@ -1143,7 +1143,7 @@
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
-
+
Figure 10: Simulated flows of each edge
@@ -958,7 +958,7 @@
-
+
Figure 11: Supplied irrigation and return flow
@@ -969,7 +969,7 @@
-
+
Figure 12: Simulated flow to Terminal
@@ -985,7 +985,7 @@ 4 Modual 2 – Re
-
+
Figure 13: Crystal basin with demands and a reservoir
@@ -1055,7 +1055,7 @@
-
+
Figure 14: Simulated basin storages and levels
@@ -1133,7 +1133,7 @@
-
+
Figure 15: Simulated flows to and from the city
@@ -1143,7 +1143,7 @@
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
-
+
Figure 11: Supplied irrigation and return flow
@@ -969,7 +969,7 @@
-
+
Figure 12: Simulated flow to Terminal
@@ -985,7 +985,7 @@ 4 Modual 2 – Re
-
+
Figure 13: Crystal basin with demands and a reservoir
@@ -1055,7 +1055,7 @@
-
+
Figure 14: Simulated basin storages and levels
@@ -1133,7 +1133,7 @@
-
+
Figure 15: Simulated flows to and from the city
@@ -1143,7 +1143,7 @@
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
-
+
Figure 12: Simulated flow to Terminal
@@ -985,7 +985,7 @@ 4 Modual 2 – Re
-
+
Figure 13: Crystal basin with demands and a reservoir
@@ -1055,7 +1055,7 @@
-
+
Figure 14: Simulated basin storages and levels
@@ -1133,7 +1133,7 @@
-
+
Figure 15: Simulated flows to and from the city
@@ -1143,7 +1143,7 @@
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
4 Modual 2 – Re
-
+
Figure 13: Crystal basin with demands and a reservoir
@@ -1055,7 +1055,7 @@
-
+
Figure 14: Simulated basin storages and levels
@@ -1133,7 +1133,7 @@
-
+
Figure 15: Simulated flows to and from the city
@@ -1143,7 +1143,7 @@
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
-
+
Figure 14: Simulated basin storages and levels
@@ -1133,7 +1133,7 @@
-
+
Figure 15: Simulated flows to and from the city
@@ -1143,7 +1143,7 @@
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
-
+
Figure 15: Simulated flows to and from the city
@@ -1143,7 +1143,7 @@
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
-
+
Figure 16: Simulated basin storages and levels
diff --git a/reference/node/basin.html b/reference/node/basin.html
index 44512d47b..504f6a682 100644
--- a/reference/node/basin.html
+++ b/reference/node/basin.html
@@ -472,7 +472,7 @@
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
-
+
+
1.2.1 Interpolation
At the given timestamps the values are set in the simulation, such that the timeseries can be seen as forward filled.
-
+
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-
Code
import numpy as np
@@ -671,7 +671,7 @@
1.4.1.1 Level to area
The level to area relationship is defined with the Basin / profile data using linear interpolation. An example of such a relationship is shown below.
-
+
Code
fig, ax = plt.subplots()
@@ -754,7 +754,7 @@ \[
S(h) = \int_{h_0}^h A(h')\text{d}h'.
\]
-
+
Code
storage = np.diff(level) * area[:-1] + 0.5 * np.diff(area) * np.diff(level)
@@ -799,7 +799,7 @@
1.4.1.3 Interactive basin example
The profile data is not detailed enough to create a full 3D picture of the basin. However, if we assume the profile data is for a stretch of canal of given length, the following plot shows a cross section of the basin.
-
+
Code
import plotly.graph_objects as go
@@ -914,9 +914,9 @@ fig.show()
-