def FW1Withlake(Model, Lake, ll_temp=None, q_0=None):
"""
==============================================================
FW1Withlake(Model, Lake,ll_temp=None, q_0=None)
==============================================================
FW1 connects two module :
1- The distributed rainfall-runoff module
2- Triangular function-1 routing method
3- Lake module
Parameters
----------
Model : TYPE
DESCRIPTION.
Lake : TYPE
DESCRIPTION.
ll_temp : TYPE, optional
DESCRIPTION. The default is None.
q_0 : TYPE, optional
DESCRIPTION. The default is None.
Returns
-------
None.
"""
plake = Lake.MeteoData[:, 0]
et = Lake.MeteoData[:, 1]
t = Lake.MeteoData[:, 2]
tm = Lake.MeteoData[:, 3]
# lake simulation
Lake.Qlake, _ = hbv_lake.simulate(
plake,
t,
et,
Lake.Parameters, [Model.Timef, Lake.CatArea, Lake.LakeArea],
Lake.StageDischargeCurve,
0,
init_st=Lake.InitialCond,
ll_temp=tm,
lake_sim=True)
# qlake is in m3/sec
# lake routing
Lake.QlakeR = routing.muskingum(Lake.Qlake, Lake.Qlake[0],
Lake.Parameters[11],
Lake.Parameters[12], Model.Timef)
# subcatchment
distrrm.RunLumpedRRM(Model)
distrrm.DistMAXBAS(Model)
qlz1 = np.array([
np.nansum(Model.qlz[:, :, i])
for i in range(Model.Parameters.shape[2] + 1)
]) # average of all cells (not routed mm/timestep)
quz1 = np.array([
np.nansum(Model.quz[:, :, i])
for i in range(Model.Parameters.shape[2] + 1)
]) # average of all cells (routed mm/timestep)
qout = qlz1 + quz1
# qout = (qlz1 + quz1) * Model.CatArea / (Model.Timef* 3.6)
Model.qout = qout[:-1] + Lake.QlakeR
def FW1Withlake(ConceptualModel,
FPL,
sp_prec,
sp_et,
sp_temp,
parameters,
p2,
snow,
init_st,
lakeCalibArray,
StageDischargeCurve,
LakeParameters,
lakecell,
lake_initial,
ll_temp=None,
q_0=None):
plake = lakeCalibArray[:, 0]
et = lakeCalibArray[:, 1]
t = lakeCalibArray[:, 2]
tm = lakeCalibArray[:, 3]
# lake simulation
q_lake, _ = hbv_lake.simulate(plake,
t,
et,
LakeParameters[:-1],
p2,
StageDischargeCurve,
0,
init_st=lake_initial,
ll_temp=tm,
lake_sim=True)
# qlake is in m3/sec
# lake routing
qlake_r = routing.TriangularRouting(q_lake, LakeParameters[-1])
# subcatchment
AdditionalParameters = p2[0:2]
st, q_lz, q_uz = distrrm.RunLumpedRRP(ConceptualModel,
FPL,
sp_prec=sp_prec,
sp_et=sp_et,
sp_temp=sp_temp,
sp_pars=parameters,
p2=AdditionalParameters,
snow=snow,
init_st=init_st)
SPMAXBAS = parameters[:, :, -1]
q_uz = distrrm.DistMAXBAS(FPL, SPMAXBAS, q_uz)
#
q_lz1 = np.array([
np.nansum(q_lz[:, :, i]) for i in range(sp_prec.shape[2] + 1)
]) # average of all cells (not routed mm/timestep)
q_uz1 = np.array([
np.nansum(q_uz[:, :, i]) for i in range(sp_prec.shape[2] + 1)
]) # average of all cells (routed mm/timestep)
q_out = (q_lz1 + q_uz1) * p2[1] / (p2[0] * 3.6)
q_out = q_out[:-1] + qlake_r
return st, q_out, q_uz, q_lz
def HapiWithlake(Model, Lake, ll_temp=None, q_0=None):
"""
============================================================
HapiWithlake(Model, Lake,ll_temp=None, q_0=None)
============================================================
HapiWithlake connects three modules the lake, the distributed
ranfall-runoff module and spatial routing module
Parameters
----------
Model : [Catchment object]
DESCRIPTION.
Lake : TYPE
DESCRIPTION.
ll_temp : TYPE, optional
DESCRIPTION. The default is None.
q_0 : TYPE, optional
DESCRIPTION. The default is None.
Returns
-------
None.
"""
plake = Lake.MeteoData[:, 0]
et = Lake.MeteoData[:, 1]
t = Lake.MeteoData[:, 2]
tm = Lake.MeteoData[:, 3]
# lake simulation
Lake.Qlake, _ = hbv_lake.simulate(
plake,
t,
et,
Lake.Parameters, [Model.Timef, Lake.CatArea, Lake.LakeArea],
Lake.StageDischargeCurve,
0,
init_st=Lake.InitialCond,
ll_temp=tm,
lake_sim=True)
# qlake is in m3/sec
# lake routing
Lake.QlakeR = routing.Muskingum_V(Lake.Qlake, Lake.Qlake[0],
Lake.Parameters[11],
Lake.Parameters[12], Model.Timef)
# subcatchment
distrrm.RunLumpedRRM(Model)
# routing lake discharge with DS cell k & x and adding to cell Q
qlake = routing.Muskingum_V(
Lake.QlakeR, Lake.QlakeR[0],
Model.Parameters[Lake.OutflowCell[0], Lake.OutflowCell[1], 10],
Model.Parameters[Lake.OutflowCell[0], Lake.OutflowCell[1],
11], Model.Timef)
qlake = np.append(qlake, qlake[-1])
# both lake & Quz are in m3/s
Model.quz[Lake.OutflowCell[0], Lake.OutflowCell[1], :] = Model.quz[
Lake.OutflowCell[0], Lake.OutflowCell[1], :] + qlake
# run the GIS part to rout from cell to another
distrrm.SpatialRouting(Model)
Model.qout = Model.qout[:-1]
def HapiWithlake(ConceptualModel,
flow_acc,
flow_direct,
sp_prec,
sp_et,
sp_temp,
parameters,
p2,
snow,
init_st,
lakeCalibArray,
StageDischargeCurve,
LakeParameters,
lakecell,
lake_initial,
ll_temp=None,
q_0=None):
plake = lakeCalibArray[:, 0]
et = lakeCalibArray[:, 1]
t = lakeCalibArray[:, 2]
tm = lakeCalibArray[:, 3]
# lake simulation
q_lake, _ = hbv_lake.simulate(plake,
t,
et,
LakeParameters,
p2,
StageDischargeCurve,
0,
init_st=lake_initial,
ll_temp=tm,
lake_sim=True)
# qlake is in m3/sec
# lake routing
qlake_r = routing.muskingum(q_lake, q_lake[0], LakeParameters[11],
LakeParameters[12], p2[0])
# subcatchment
AdditionalParameters = p2[0:2]
st, q_lz, q_uz = distrrm.RunLumpedRRP(ConceptualModel,
flow_acc,
sp_prec=sp_prec,
sp_et=sp_et,
sp_temp=sp_temp,
sp_pars=parameters,
p2=AdditionalParameters,
snow=snow,
init_st=init_st)
# routing lake discharge with DS cell k & x and adding to cell Q
q_lake = routing.muskingum(qlake_r, qlake_r[0],
parameters[lakecell[0], lakecell[1], 10],
parameters[lakecell[0], lakecell[1], 11], p2[0])
q_lake = np.append(q_lake, q_lake[-1])
# both lake & Quz are in m3/s
q_uz[lakecell[0],
lakecell[1], :] = q_uz[lakecell[0], lakecell[1], :] + q_lake
# run the GIS part to rout from cell to another
q_out, q_uz_routed, q_lz_trans = distrrm.SpatialRouting(
q_lz, q_uz, flow_acc, flow_direct, parameters, p2)
q_out = q_out[:-1]
return st, q_out, q_uz_routed, q_lz_trans