hstream_v1

Version 1 of The HydPy-H-Stream model is a straightforward routing approach. It applies the working equation of the Muskingum method on some river segments of the same length. The number of segments (parameter NmbSegments) controls translation (parameter Lag), the Muskingum coefficients (parameters C1, C2, and C3) control attenuation (parameter Damp). For NmbSegments only integer values are allowed, which is why the translation time cannot be varied continuously.

Integration tests

Note

When new to HydPy, consider reading section How to understand integration tests? first.

We perform the following examples over a simulation period of 20 hours:

>>> from hydpy import pub, Nodes, Element
>>> pub.timegrids = "01.01.2000 00:00", "01.01.2000 20:00", "1h"

We also set the time step size of the parameter values defined below to one hour:

>>> from hydpy.models.hstream_v1 import *
>>> parameterstep("1h")

The hstream_v1 model, handled by Element stream, queries its inflow from two Node objects (input1 and input2) and passes its outflow to a single Node object (output):

>>> nodes = Nodes("input1", "input2", "output")
>>> stream = Element("stream",
...                  inlets=["input1", "input2"],
...                  outlets="output")
>>> stream.model = model

The test function object sets the initial inflow of all segments junctions (QJoints) to zero before each simulation run:

>>> from hydpy.core.testtools import IntegrationTest
>>> test = IntegrationTest(stream,
...                        inits=((states.qjoints, 0.),))
>>> test.dateformat = "%H:%M"

We define two flood events, one for each inflow node:

>>> nodes.input1.sequences.sim.series = [
...                     0., 0., 1., 3., 2., 1., 0., 0., 0., 0.,
...                     0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]
>>> nodes.input2.sequences.sim.series = [
...                     0., 1., 5., 9., 8., 5., 3., 2., 1., 0.,
...                     0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]

Example 1

With zero Lag time, there are no river segments. Hence, there is only one “virtual” junction, which is both the start and the end point of the whole channel. Accordingly, outflow is always equal to inflow:

>>> lag(0.0)
>>> damp(0.0)
>>> test("hstream_v1_ex1")
|  date | qjoints | input1 | input2 | output |
----------------------------------------------
| 00:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 01:00 |     1.0 |    0.0 |    1.0 |    1.0 |
| 02:00 |     6.0 |    1.0 |    5.0 |    6.0 |
| 03:00 |    12.0 |    3.0 |    9.0 |   12.0 |
| 04:00 |    10.0 |    2.0 |    8.0 |   10.0 |
| 05:00 |     6.0 |    1.0 |    5.0 |    6.0 |
| 06:00 |     3.0 |    0.0 |    3.0 |    3.0 |
| 07:00 |     2.0 |    0.0 |    2.0 |    2.0 |
| 08:00 |     1.0 |    0.0 |    1.0 |    1.0 |
| 09:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 10:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 11:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 12:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 13:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 14:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 15:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 16:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 17:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 18:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 19:00 |     0.0 |    0.0 |    0.0 |    0.0 |

Click here to see the graph

Example 2

Parameter Damp controls the attenuation of flood waves within a single river segment. With a zero Lag time, there are no river segments and thus not damping even for the highest possible value of Damp:

>>> lag(0.0)
>>> damp(1.0)
>>> test("hstream_v1_ex2")
|  date | qjoints | input1 | input2 | output |
----------------------------------------------
| 00:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 01:00 |     1.0 |    0.0 |    1.0 |    1.0 |
| 02:00 |     6.0 |    1.0 |    5.0 |    6.0 |
| 03:00 |    12.0 |    3.0 |    9.0 |   12.0 |
| 04:00 |    10.0 |    2.0 |    8.0 |   10.0 |
| 05:00 |     6.0 |    1.0 |    5.0 |    6.0 |
| 06:00 |     3.0 |    0.0 |    3.0 |    3.0 |
| 07:00 |     2.0 |    0.0 |    2.0 |    2.0 |
| 08:00 |     1.0 |    0.0 |    1.0 |    1.0 |
| 09:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 10:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 11:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 12:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 13:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 14:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 15:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 16:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 17:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 18:00 |     0.0 |    0.0 |    0.0 |    0.0 |
| 19:00 |     0.0 |    0.0 |    0.0 |    0.0 |

Click here to see the graph

Example 3

With a lag time of three hours and zero damping, hstream_v1 passes the flow values from one junction to the next one within each simulation time step. Three segments give an overall time shift of three hours:

>>> lag(3.0)
>>> damp(0.0)
>>> test("hstream_v1_ex3")
|  date |                   qjoints | input1 | input2 | output |
----------------------------------------------------------------
| 00:00 |  0.0   0.0   0.0      0.0 |    0.0 |    0.0 |    0.0 |
| 01:00 |  1.0   0.0   0.0      0.0 |    0.0 |    1.0 |    0.0 |
| 02:00 |  6.0   1.0   0.0      0.0 |    1.0 |    5.0 |    0.0 |
| 03:00 | 12.0   6.0   1.0      0.0 |    3.0 |    9.0 |    0.0 |
| 04:00 | 10.0  12.0   6.0      1.0 |    2.0 |    8.0 |    1.0 |
| 05:00 |  6.0  10.0  12.0      6.0 |    1.0 |    5.0 |    6.0 |
| 06:00 |  3.0   6.0  10.0     12.0 |    0.0 |    3.0 |   12.0 |
| 07:00 |  2.0   3.0   6.0     10.0 |    0.0 |    2.0 |   10.0 |
| 08:00 |  1.0   2.0   3.0      6.0 |    0.0 |    1.0 |    6.0 |
| 09:00 |  0.0   1.0   2.0      3.0 |    0.0 |    0.0 |    3.0 |
| 10:00 |  0.0   0.0   1.0      2.0 |    0.0 |    0.0 |    2.0 |
| 11:00 |  0.0   0.0   0.0      1.0 |    0.0 |    0.0 |    1.0 |
| 12:00 |  0.0   0.0   0.0      0.0 |    0.0 |    0.0 |    0.0 |
| 13:00 |  0.0   0.0   0.0      0.0 |    0.0 |    0.0 |    0.0 |
| 14:00 |  0.0   0.0   0.0      0.0 |    0.0 |    0.0 |    0.0 |
| 15:00 |  0.0   0.0   0.0      0.0 |    0.0 |    0.0 |    0.0 |
| 16:00 |  0.0   0.0   0.0      0.0 |    0.0 |    0.0 |    0.0 |
| 17:00 |  0.0   0.0   0.0      0.0 |    0.0 |    0.0 |    0.0 |
| 18:00 |  0.0   0.0   0.0      0.0 |    0.0 |    0.0 |    0.0 |
| 19:00 |  0.0   0.0   0.0      0.0 |    0.0 |    0.0 |    0.0 |

Click here to see the graph

Example 4

The last example shows the highest possible attenuation for three river segments:

>>> lag(3.0)
>>> damp(1.0)
>>> test("hstream_v1_ex4")
|  date |                            qjoints | input1 | input2 |   output |
---------------------------------------------------------------------------
| 00:00 |  0.0       0.0       0.0       0.0 |    0.0 |    0.0 |      0.0 |
| 01:00 |  1.0       0.5      0.25     0.125 |    0.0 |    1.0 |    0.125 |
| 02:00 |  6.0      3.25      1.75    0.9375 |    1.0 |    5.0 |   0.9375 |
| 03:00 | 12.0     7.625    4.6875    2.8125 |    3.0 |    9.0 |   2.8125 |
| 04:00 | 10.0    8.8125      6.75   4.78125 |    2.0 |    8.0 |  4.78125 |
| 05:00 |  6.0   7.40625  7.078125  5.929688 |    1.0 |    5.0 | 5.929688 |
| 06:00 |  3.0  5.203125  6.140625  6.035156 |    0.0 |    3.0 | 6.035156 |
| 07:00 |  2.0  3.601562  4.871094  5.453125 |    0.0 |    2.0 | 5.453125 |
| 08:00 |  1.0  2.300781  3.585938  4.519531 |    0.0 |    1.0 | 4.519531 |
| 09:00 |  0.0  1.150391  2.368164  3.443848 |    0.0 |    0.0 | 3.443848 |
| 10:00 |  0.0  0.575195   1.47168  2.457764 |    0.0 |    0.0 | 2.457764 |
| 11:00 |  0.0  0.287598  0.879639  1.668701 |    0.0 |    0.0 | 1.668701 |
| 12:00 |  0.0  0.143799  0.511719   1.09021 |    0.0 |    0.0 |  1.09021 |
| 13:00 |  0.0  0.071899  0.291809   0.69101 |    0.0 |    0.0 |  0.69101 |
| 14:00 |  0.0   0.03595  0.163879  0.427444 |    0.0 |    0.0 | 0.427444 |
| 15:00 |  0.0  0.017975  0.090927  0.259186 |    0.0 |    0.0 | 0.259186 |
| 16:00 |  0.0  0.008987  0.049957  0.154572 |    0.0 |    0.0 | 0.154572 |
| 17:00 |  0.0  0.004494  0.027225  0.090899 |    0.0 |    0.0 | 0.090899 |
| 18:00 |  0.0  0.002247  0.014736  0.052817 |    0.0 |    0.0 | 0.052817 |
| 19:00 |  0.0  0.001123   0.00793  0.030374 |    0.0 |    0.0 | 0.030374 |

Click here to see the graph

class hydpy.models.hstream_v1.Model

Bases: hydpy.core.modeltools.AdHocModel

The HBV96 version of HydPy-H-Stream (hstream_v1).

The following “inlet update methods” are called in the given sequence at the beginning of each simulation step:

• Pick_Q_V1 Assign the actual value of the inlet sequence to the upper joint of the subreach upstream.

The following “run methods” are called in the given sequence during each simulation step:

• Calc_QJoints_V1 Apply the routing equation.

The following “outlet update methods” are called in the given sequence at the end of each simulation step:

• Pass_Q_V1 Assing the actual value of the lower joint of of the subreach downstream to the outlet sequence.

class hydpy.models.hstream_v1.Masks

Bases: hydpy.core.masktools.Masks

Masks applicable to hstream_v1.

The following classes are selected:

• Complete() Mask including a stream segments.

class hydpy.models.hstream_v1.ControlParameters(master: hydpy.core.parametertools.Parameters, cls_fastaccess: Optional[Type[hydpy.core.parametertools.FastAccessParameter]] = None, cymodel: Optional[hydpy.core.typingtools.CyModelProtocol] = None)

Bases: hydpy.core.variabletools.SubVariables[hydpy.core.parametertools.Parameters, Parameter, hydpy.core.parametertools.FastAccessParameter]

Control parameters of model hstream_v1.

The following classes are selected:

• Lag() Time lag between inflow and outflow [T].

• Damp() Damping of the hydrograph [-].

class hydpy.models.hstream_v1.DerivedParameters(master: hydpy.core.parametertools.Parameters, cls_fastaccess: Optional[Type[hydpy.core.parametertools.FastAccessParameter]] = None, cymodel: Optional[hydpy.core.typingtools.CyModelProtocol] = None)

Bases: hydpy.core.variabletools.SubVariables[hydpy.core.parametertools.Parameters, Parameter, hydpy.core.parametertools.FastAccessParameter]

Derived parameters of model hstream_v1.

The following classes are selected:

• NmbSegments() Number of river segments [-].

• C1() First coefficient of the Muskingum working formula [-].

• C3() Third coefficient of the muskingum working formula [-].

• C2() Second coefficient of the muskingum working formula [-].

class hydpy.models.hstream_v1.InletSequences(master: hydpy.core.sequencetools.Sequences, cls_fastaccess: Optional[Type[FastAccessType]] = None, cymodel: Optional[hydpy.core.typingtools.CyModelProtocol] = None)

Bases: hydpy.core.sequencetools.LinkSequences[InletSequence]

Inlet sequences of model hstream_v1.

The following classes are selected:

• Q() Runoff [m³/s].

class hydpy.models.hstream_v1.OutletSequences(master: hydpy.core.sequencetools.Sequences, cls_fastaccess: Optional[Type[FastAccessType]] = None, cymodel: Optional[hydpy.core.typingtools.CyModelProtocol] = None)

Bases: hydpy.core.sequencetools.LinkSequences[OutletSequence]

Outlet sequences of model hstream_v1.

The following classes are selected:

• Q() Runoff [m³/s].

class hydpy.models.hstream_v1.StateSequences(master: hydpy.core.sequencetools.Sequences, cls_fastaccess: Optional[Type[FastAccessType]] = None, cymodel: Optional[hydpy.core.typingtools.CyModelProtocol] = None)

Bases: hydpy.core.sequencetools.OutputSequences[StateSequence]

State sequences of model hstream_v1.

The following classes are selected:

• QJoints() Runoff at the segment junctions [m³/s].