def test_scenario_storage(): """Test the behaviour of Storage nodes with multiple scenarios The model defined has two inflow scenarios: 5 and 10. It is expected that the volume in the storage node should increase at different rates in the two scenarios. """ model = Model() i = Input(model, 'input', max_flow=999) s = Storage(model, 'storage', num_inputs=1, num_outputs=1, max_volume=1000, initial_volume=500) o = Output(model, 'output', max_flow=999) scenario_input = Scenario(model, 'Inflow', size=2) i.min_flow = ConstantScenarioParameter(model, scenario_input, [5.0, 10.0]) i.connect(s) s.connect(o) s_rec = NumpyArrayStorageRecorder(model, s) model.run() assert_allclose(i.flow, [5, 10]) assert_allclose(s_rec.data[0], [505, 510]) assert_allclose(s_rec.data[1], [510, 520])
def test_keating_aquifer(solver): model = Model( solver=solver, start=pandas.to_datetime('2016-01-01'), end=pandas.to_datetime('2016-01-01'), ) aqfer = KeatingAquifer( model, 'keating', num_streams, num_additional_inputs, stream_flow_levels, transmissivity, coefficient, levels, area=area, storativity=storativity, ) catchment = Input(model, 'catchment', max_flow=0) stream = Output(model, 'stream', max_flow=np.inf, cost=0) abstraction = Output(model, 'abstraction', max_flow=15, cost=-999) catchment.connect(aqfer) aqfer.connect(stream, from_slot=0) aqfer.connect(abstraction, from_slot=1) rec_level = NumpyArrayLevelRecorder(model, aqfer) rec_volume = NumpyArrayStorageRecorder(model, aqfer) rec_stream = NumpyArrayNodeRecorder(model, stream) rec_abstraction = NumpyArrayNodeRecorder(model, abstraction) model.check() assert(len(aqfer.inputs) == (num_streams + num_additional_inputs)) for initial_level in (50, 100, 110, 150): # set the inital aquifer level and therefor the initial volume aqfer.initial_level = initial_level initial_volume = aqfer.initial_volume assert(initial_volume == (area * storativity[0] * initial_level * 0.001)) # run the model (for one timestep only) model.run() # manually calculate keating streamflow and check model flows are OK Qp = 2 * transmissivity[0] * max(initial_level - stream_flow_levels[0][0], 0) * coefficient Qe = 2 * transmissivity[1] * max(initial_level - stream_flow_levels[0][1], 0) * coefficient delta_storage = initial_volume - rec_volume.data[0, 0] abs_flow = rec_abstraction.data[0, 0] stream_flow = rec_stream.data[0, 0] assert(delta_storage == (stream_flow + abs_flow)) assert(stream_flow == (Qp+Qe)) A_VERY_LARGE_NUMBER = 9999999999999 model.timestepper.end = pandas.to_datetime('2016-01-02') # fill the aquifer completely # there is no spill for the storage so it should find no feasible solution with pytest.raises(RuntimeError): catchment.max_flow = A_VERY_LARGE_NUMBER catchment.min_flow = A_VERY_LARGE_NUMBER model.run() # drain the aquifer completely catchment.min_flow = 0 catchment.max_flow = 0 abstraction.max_flow = A_VERY_LARGE_NUMBER model.run() assert(rec_volume.data[1, 0] == 0) abs_flow = rec_abstraction.data[1, 0] stream_flow = rec_stream.data[1, 0] assert(stream_flow == 0) assert(abs_flow == 0)