pywfm.IWFMModel.get_stream_flows#

IWFMModel.get_stream_flows(flow_conversion_factor=1.0)#

Return stream flows at every stream node for the current timestep

Parameters:: flow_conversion_factor (float, default=1.0) – conversion factor for stream flows from the simulation units of volume to a desired unit of volume
Returns:: flows for all stream nodes for the current simulation timestep
Return type:: np.ndarray

Note

This method is designed for use when is_for_inquiry=0 to return stream flows at the current timestep during a simulation.

See also

IWFMModel.get_stream_inflows_at_some_locations: Return stream boundary inflows at a specified set of inflow locations listed by their indices for the current simulation timestep
IWFMModel.get_stream_flow_at_location: Return stream flow at a stream node for the current time step in a simulation
IWFMModel.get_stream_stages: Return stream stages at every stream node for the current timestep

Example

>>> from pywfm import IWFMModel
>>> pp_file = '../Preprocessor/PreProcessor_MAIN.IN'
>>> sim_file = 'Simulation_MAIN.IN'
>>> model = IWFMModel(pp_file, sim_file, is_for_inquiry=0)
>>> while not model.is_end_of_simulation():
...     # advance the simulation time one time step forward
...     model.advance_time()
...
...     # read all time series data from input files
...     model.read_timeseries_data()
...
...     # Simulate the hydrologic process for the timestep
...     model.simulate_for_one_timestep()
...
...     # get stream flows
...     stream_flows = model.get_stream_flows()
...     stream_node_ids = model.get_stream_node_ids()
...
...     # print the results to the user-specified output files
...     model.print_results()
...
...     # advance the state of the hydrologic system in time
...     model.advance_state()
>>> for i, flow in enumerate(stream_flows):
...     print(stream_node_ids[i], flow)
*   TIME STEP 3653 AT 09/30/2000_24:00
1 85301292.67626143
2 83142941.70620254
3 81028792.9071748
4 78985517.65754062
5 77081104.67763746
6 75724877.72101441
7 74440170.86435351
8 73367874.87547392
9 71735544.16731748
10 70995694.52663273
11 53285997.91790043
12 44.84964866936207
13 0.0
14 0.0
15 0.0
16 0.0
17 0.0
18 2553191.7510338724
19 1948997.4229038805
20 1487781.3046951443
21 2345774.2345003784
22 1599258.8286072314
23 2495579.2758224607
>>> model.kill()
>>> model.close_log_file()