def opt_fun(par):
try:
# parameters
klb=float(par[-2])
kub=float(par[-1])
par=par[:-2]
par_dist=SpatialVarFun(par,*SpatialVarArgs,kub=kub,klb=klb)
#run the model
_, q_out, q_uz_routed, q_lz_trans=Wrapper.Dist_model(ConceptualModel,
acc, fd, prec, evap,
temp, par_dist, p2,
snow , init_st)
# calculate performance of the model
try:
error=OF(Q_obs,q_out,q_uz_routed,q_lz_trans,*OF_args)
except TypeError: # if no of inputs less than what the function needs
assert 1==5, "the objective function you have entered needs more inputs please enter then in a list as *args"
# print error
if printError != 0:
print(error)
print(par)
fail = 0
except:
error = np.nan
fail = 1
return error, [], fail
def run_Distributed_model():
performance.text = str("<h2>processing...<h2>")
# read values of parameters
# data validation
# _area = float(w_area.value)
# pars222222 = [_k1, _k2, _k3, _k4, _d1, _d2, _s1, _s2]
# extra_pars22222 = [_dt, _area]
performance_Q = {}
calc_Q = pd.DataFrame(index=index)
calc_Q['Q'], _, _, _, _, _ = Wrapper.Dist_model(
lake_data_A,
extra_pars,
curve,
lakecell,
DEM,
flow_acc_table,
flow_acc,
sp_prec_c,
sp_et_c,
sp_temp_c,
pars,
kub,
klb,
jiboa_initial=jiboa_initial,
lake_initial=lake_initial,
ll_temp=None,
q_0=None)
# Calculate model performance
performance.text = str("<h2>calculating model performance..<h2>")
WS = {
} #------------------------------------------------------------------------
WS['type'] = 1 #------------------------------------------------------------------------
WS['N'] = 3 #------------------------------------------------------------------------
performance_Q['c_error_hf'] = Performance_criteria.rmseHF(
lake_data['Q'], calc_Q['Q'], WS['type'], WS['N'], 0.75
) #------------------------------------------------------------------------
performance_Q['c_error_lf'] = Performance_criteria.rmseLF(
lake_data['Q'], calc_Q['Q'], WS['type'], WS['N'], 0.75
) #------------------------------------------------------------------------
performance_Q['c_nsehf'] = Performance_criteria.nse(
lake_data_A[:, -1], calc_Q['Q']
) #------------------------------------------------------------------------
performance_Q['c_rmse'] = Performance_criteria.rmse(
lake_data_A[:, -1], calc_Q['Q']
) #------------------------------------------------------------------------
performance_Q['c_nself'] = Performance_criteria.nse(
np.log(lake_data_A[:, -1]), np.log(calc_Q['Q'])
) #------------------------------------------------------------------------
performance_Q['c_KGE'] = Performance_criteria.KGE(
lake_data_A[:, -1], calc_Q['Q']
) #------------------------------------------------------------------------
performance_Q['c_wb'] = Performance_criteria.WB(
lake_data_A[:, -1], calc_Q['Q']
) #------------------------------------------------------------------------
# update data source
ds_sim.data = (dict(q_sim=calc_Q['Q'].tolist(), ds_time=index))
performance.text = str("<h2>Model perfomance(RMSE) is %s<h2>" %
round(performance_Q['c_rmse'], 3))
def RunModel(ConceptualModel, Paths, ParPath, p2, init_st, snow):
"""
=======================================================================
RunModel(PrecPath, Evap_Path, TempPath, DemPath, FlowAccPath, FlowDPath, ParPath, p2)
=======================================================================
this function runs the conceptual distributed hydrological model
Inputs:
1-Paths:
1-PrecPath:
[String] path to the Folder contains precipitation rasters
2-Evap_Path:
[String] path to the Folder contains Evapotranspiration rasters
3-TempPath:
[String] path to the Folder contains Temperature rasters
4-FlowAccPath:
[String] path to the Flow Accumulation raster of the catchment (it should
include the raster name and extension)
5-FlowDPath:
[String] path to the Flow Direction raster of the catchment (it should
include the raster name and extension)
7-ParPath:
[String] path to the Folder contains parameters rasters of the catchment
8-p2:
[List] list of unoptimized parameters
p2[0] = tfac, 1 for hourly, 0.25 for 15 min time step and 24 for daily time step
p2[1] = catchment area in km2
Outputs:
1- st:
[4D array] state variables
2- q_out:
[1D array] calculated Discharge at the outlet of the catchment
3- q_uz:
[3D array] Distributed discharge for each cell
Example:
PrecPath = prec_path="meteodata/4000/calib/prec"
Evap_Path = evap_path="meteodata/4000/calib/evap"
TempPath = temp_path="meteodata/4000/calib/temp"
DemPath = "GIS/4000/dem4000.tif"
FlowAccPath = "GIS/4000/acc4000.tif"
FlowDPath = "GIS/4000/fd4000.tif"
ParPath = "meteodata/4000/parameters"
p2=[1, 227.31]
st, q_out, q_uz_routed = RunModel(PrecPath,Evap_Path,TempPath,DemPath,
FlowAccPath,FlowDPath,ParPath,p2)
"""
# input data validation
assert len(Paths) == 5, "Paths should include 5 folder pathes " +str(len(Paths))+" paths are only provided"
PrecPath=Paths[0]
Evap_Path=Paths[1]
TempPath=Paths[2]
# DemPath=Paths[3]
FlowAccPath=Paths[3]
FlowDPath=Paths[4]
# data type
assert type(PrecPath)== str, "PrecPath input should be string type"
assert type(Evap_Path)== str, "Evap_Path input should be string type"
assert type(TempPath)== str, "TempPath input should be string type"
# assert type(DemPath)== str, "DemPath input should be string type"
assert type(FlowAccPath)== str, "FlowAccPath input should be string type"
assert type(FlowDPath)== str, "FlowDPath input should be string type"
assert type(ParPath)== str, "ParPath input should be string type"
# input values
# dem_ext=DemPath[-4:]
# assert dem_ext == ".tif", "please add the extension at the end of the DEM raster path input"
acc_ext=FlowAccPath[-4:]
assert acc_ext == ".tif", "please add the extension at the end of the Flow accumulation raster path input"
fd_ext=FlowDPath[-4:]
assert fd_ext == ".tif", "please add the extension at the end of the Flow Direction path input"
# check wether the path exists or not
assert os.path.exists(PrecPath), PrecPath + " you have provided does not exist"
assert os.path.exists(Evap_Path), Evap_Path+" path you have provided does not exist"
assert os.path.exists(TempPath), TempPath+" path you have provided does not exist"
# assert os.path.exists(DemPath), DemPath+ " you have provided does not exist"
assert os.path.exists(FlowAccPath), FlowAccPath + " you have provided does not exist"
assert os.path.exists(FlowDPath), FlowDPath+ " you have provided does not exist"
# check wether the folder has the rasters or not
assert len(os.listdir(PrecPath)) > 0, PrecPath+" folder you have provided is empty"
assert len(os.listdir(Evap_Path)) > 0, Evap_Path+" folder you have provided is empty"
assert len(os.listdir(TempPath)) > 0, TempPath+" folder you have provided is empty"
# read data
### meteorological data
prec=GIS.ReadRastersFolder(PrecPath)
evap=GIS.ReadRastersFolder(Evap_Path)
temp=GIS.ReadRastersFolder(TempPath)
print("meteorological data are read successfully")
#### GIS data
# dem= gdal.Open(DemPath)
acc=gdal.Open(FlowAccPath)
fd=gdal.Open(FlowDPath)
print("GIS data are read successfully")
# parameters
parameters=GIS.ReadRastersFolder(ParPath)
print("Parameters are read successfully")
#run the model
st, q_out, q_uz, q_lz = Wrapper.Dist_model(ConceptualModel, acc, fd, prec, evap,
temp, parameters, p2, snow, init_st)
return st, q_out, q_uz, q_lz
