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
def RunCalibration(ConceptualModel,
Paths,
Basic_inputs,
SpatialVarFun,
SpatialVarArgs,
OF,
OF_args,
Q_obs,
OptimizationArgs,
printError=None):
"""
=======================================================================
RunCalibration(Paths, p2, Q_obs, UB, LB, SpatialVarFun, lumpedParNo, lumpedParPos, objective_function, printError=None, *args):
=======================================================================
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)
2-Basic_inputs:
1-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
2-init_st:
[list] initial values for the state variables [sp,sm,uz,lz,wc] in mm
3-UB:
[Numeric] upper bound of the values of the parameters
4-LB:
[Numeric] Lower bound of the values of the parameters
3-Q_obs:
[Numeric] Observed values of discharge
6-lumpedParNo:
[int] nomber of lumped parameters, you have to enter the value of
the lumped parameter at the end of the list, default is 0 (no lumped parameters)
7-lumpedParPos:
[List] list of order or position of the lumped parameter among all
the parameters of the lumped model (order starts from 0 to the length
of the model parameters), default is [] (empty), the following order
of parameters is used for the lumped HBV model used
[ltt, utt, rfcf, sfcf, ttm, cfmax, cwh, cfr, fc, beta, e_corr, etf, lp,
c_flux, k, k1, alpha, perc, pcorr, Kmuskingum, Xmuskingum]
8-objective_function:
[function] objective function to calculate the performance of the model
and to be used in the calibration
9-*args:
other arguments needed on the objective function
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"
FlowAccPath = "GIS/4000/acc4000.tif"
FlowDPath = "GIS/4000/fd4000.tif"
ParPath = "meteodata/4000/"+"parameters.txt"
p2=[1, 227.31]
st, q_out, q_uz_routed = RunModel(PrecPath,Evap_Path,TempPath,DemPath,
FlowAccPath,FlowDPath,ParPath,p2)
"""
### inputs validation
# data type
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]
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"
# 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"
# basic inputs
# check if all inputs are included
assert all(
["p2", "init_st", "UB", "LB", "snow "][i] in Basic_inputs.keys()
for i in range(
4)), "Basic_inputs should contain ['p2','init_st','UB','LB'] "
p2 = Basic_inputs['p2']
init_st = Basic_inputs["init_st"]
UB = Basic_inputs['UB']
LB = Basic_inputs['LB']
snow = Basic_inputs['snow']
assert len(UB) == len(LB), "length of UB should be the same like LB"
# check objective_function
assert callable(OF), "second argument should be a function"
if OF_args == None:
OF_args = []
# 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")
### optimization
# get arguments
store_history = OptimizationArgs[0]
history_fname = OptimizationArgs[1]
# check optimization arguement
assert store_history != 0 or store_history != 1, "store_history should be 0 or 1"
assert type(
history_fname) == str, "history_fname should be of type string "
assert history_fname[
-4:] == ".txt", "history_fname should be txt file please change extension or add .txt ad the end of the history_fname"
print('Calibration starts')
### calculate the objective function
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
### define the optimization components
opt_prob = Optimization('HBV Calibration', opt_fun)
for i in range(len(LB)):
opt_prob.addVar('x{0}'.format(i), type='c', lower=LB[i], upper=UB[i])
print(opt_prob)
opt_engine = ALHSO(etol=0.0001,
atol=0.0001,
rtol=0.0001,
stopiters=10,
hmcr=0.5,
par=0.5) #,filename='mostafa.out'
Optimizer.__init__(
opt_engine,
def_options={
'hms': [int, 9], # Memory Size [1,50]
'hmcr': [float, 0.95
], # Probability rate of choosing from memory [0.7,0.99]
'par': [float, 0.99], # Pitch adjustment rate [0.1,0.99]
'dbw': [int, 2000], # Variable Bandwidth Quantization
'maxoutiter':
[int, 2e3
], # Maximum Number of Outer Loop Iterations (Major Iterations)
'maxinniter':
[int, 2e2
], # Maximum Number of Inner Loop Iterations (Minor Iterations)
'stopcriteria': [int, 1], # Stopping Criteria Flag
'stopiters': [
int, 20
], # Consecutively Number of Outer Iterations for which the Stopping Criteria must be Satisfied
'etol': [float,
0.0001], # Absolute Tolerance for Equality constraints
'itol': [float,
0.0001], # Absolute Tolerance for Inequality constraints
'atol': [float,
0.0001], # Absolute Tolerance for Objective Function 1e-6
'rtol': [float,
0.0001], # Relative Tolerance for Objective Function
'prtoutiter':
[int,
0], # Number of Iterations Before Print Outer Loop Information
'prtinniter':
[int,
0], # Number of Iterations Before Print Inner Loop Information
'xinit':
[int,
0], # Initial Position Flag (0 - no position, 1 - position given)
'rinit': [float, 1.0], # Initial Penalty Factor
'fileout': [int,
store_history], # Flag to Turn On Output to filename
'filename': [
str, 'parameters.txt'
], # We could probably remove fileout flag if filename or fileinstance is given
'seed':
[float,
0.5], # Random Number Seed (0 - Auto-Seed based on time clock)
'scaling': [
int, 1
], # Design Variables Scaling Flag (0 - no scaling, 1 - scaling between [-1,1])
})
res = opt_engine(opt_prob)
return res
