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read_combine_runoff.py
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#!/home/fengxiang/anaconda3/envs/wrfout/bin/python
# -*- encoding: utf-8 -*-
'''
Description:
将地表产流和壤中流多时次数据进行合并处理
根据x,y的坐标进行插值处理，这里的x,y的值是从-290948到290951, 不是个数
-----------------------------------------
Time :2023/03/23 12:02:08
Author :Forxd
Version :1.0
'''
# %%
import xarray as xr
import os
import numpy as np
import pandas as pd
from scipy.interpolate import RegularGridInterpolator
# %%
class Runoff():
def __init__(self):
pass
# self.path = '/home/fengx20/project/hydro/test3/RUN/Grid_nolake/'
# self.flnm_latlon = '/home/fengx20/project/hydro/test3/DATA/gis_100m/wrfhydro_gis/latlon_big.nc'
self.path = '/home/fengx20/project/hydro/test_ground/RUN/2002/'
# self.flnm_latlon = '/home/fengx20/project/hydro/test_ground/Hydro_Routing/wrf_hydro_gis_preprocessor/wrfhydro_gis/latlon.nc'
self.flnm_latlon = '/home/fengx20/project/hydro/test_ground/Hydro_Routing/outputs/latlon.nc'
self.path_surface = self.path+'surface_runoff.nc'
self.path_subsurface = self.path+'subsurface_runoff.nc'
def get_latlon(self):
ds_latlon = xr.open_dataset(self.flnm_latlon)
self.lat = ds_latlon['LATITUDE']
self.lon = ds_latlon['LONGITUDE'][:,::-1]
return self.lon, self.lat
def read_surface_runoff_1time(self,flnm_LSM):
ds_LSM = xr.open_dataset(flnm_LSM)
lon, lat = self.get_latlon()
# lon1 = lon[::10, ::10]
# lat1 = lat[::10, ::10]
# lon1 = lon[::4, ::4]
# lat1 = lat[::4, ::4]
da = ds_LSM['sfcheadrt']
db = ds_LSM['infxsrt']
# db = xr.DataArray(
# da.values,
# coords={
# 'lon':(('y','x'),lon1.values),
# 'lat':(('y','x'),lat1.values),
# 'y':da.y.values,
# 'x':da.x.values,
# 'time':da.time.values,
# },
# dims=['time', 'y', 'x']
# )
# db = db.rename('surface_runoff')
ds = xr.Dataset(
{
"surface_runoff":(['time', 'y', 'x'],da.values),
"infiltration":(['time','y', 'x'],db.values),
},
coords={
'lon':(('y','x'),lon.values),
'lat':(('y','x'),lat.values),
'y':da.y.values,
'x':da.x.values,
'time':da.time.values,
},
# dims=['time', 'y', 'x']
)
# db = db.rename('surface_runoff')
# return db
return ds
def read_subsurface_runoff_1time(self,flnm_RT):
ds_RT= xr.open_dataset(flnm_RT)
lon, lat = self.get_latlon()
# lon1 = lon[::4, ::4]
# lat1 = lat[::4, ::4]
da = ds_RT['sfcheadsubrt']
db = xr.DataArray(
da.values,
coords={
'lon':(('y','x'),lon.values),
'lat':(('y','x'),lat.values),
'y':da.y.values,
'x':da.x.values,
'time':da.time.values,
},
dims=['time', 'y', 'x']
)
db = db.rename('subsurface_runoff')
return db
pass
def combine_surface_runoff(self,):
def get_file_list(path, keyvar):
fl_list= os.popen('ls {}/{}*'.format(path, keyvar)) # 打开一个管道
fl_list= fl_list.read().split()
return fl_list
# path = '/home/fengx20/project/hydro/test3/RUN/Grid_nolake/'
surface = '*.LSMOUT_DOMAIN1'
fl_list_surface = get_file_list(self.path, surface)
# fl_list_surface
# rf = Runoff()
dss_list = []
for fls in fl_list_surface:
print(fls[-20:-10])
dss = self.read_surface_runoff_1time(fls)
dss_list.append(dss)
das = xr.concat(dss_list, dim='time')
das.to_netcdf(self.path_surface)
def combine_subsurface_runoff(self,):
def get_file_list(path, keyvar):
fl_list= os.popen('ls {}/{}*'.format(path, keyvar)) # 打开一个管道
fl_list= fl_list.read().split()
return fl_list
# path = '/home/fengx20/project/hydro/test3/RUN/Grid_nolake/'
subsurface = '*.RTOUT_DOMAIN1'
fl_list = get_file_list(self.path, subsurface)
# fl_list
# rf = Runoff()
ds_list = []
for fls in fl_list:
print(fls[-20:-10])
dss = self.read_subsurface_runoff_1time(fls)
ds_list.append(dss)
das = xr.concat(ds_list, dim='time')
das.to_netcdf(self.path_subsurface)
return dss
def regrid_coarse2fine2d(self,da, db):
"""
将河道网格的数据插值到陆面模式网格点
da: 需要输出的较粗的网格分辨率的数据, xr.DataArray (y:417,x:582)
db: 输入的精细网格分辨率的数据,xr.DataArray (y:4170,x:5820)
return :
dc: 同da网格
"""
data = db.values
y = db.y.values
x = db.x.values
## 输入的格点
interp = RegularGridInterpolator((y, x), data,
bounds_error=False, fill_value=None)
## 输出的格点
Y,X = np.meshgrid(da.y.values, da.x.values, indexing='ij')
## 插值
ii = interp((Y,X))
# dc = xr.DataArray(ii)
dc = xr.DataArray(
ii,
coords=da.coords,
dims= da.dims,
)
return dc
def regrid_coarse2fine3d(self,da_subsurface, da_surface):
## 输入的格点
data = da_subsurface.values
y = da_subsurface.y.values
x = da_subsurface.x.values
tt = da_subsurface.time.values
z = np.arange(len(tt))
## 规则网格的值
interp = RegularGridInterpolator((z, y, x), data,
bounds_error=True, fill_value=np.nan, method='linear')
## 输出的格点
Z,Y,X = np.meshgrid(z, da_surface.y.values, da_surface.x.values, indexing='ij', sparse=True)
# Z
## 插值
da = interp((Z,Y,X))
db = xr.DataArray(
da,
coords={
'lon':(('y','x'),da_surface.lon.values),
'lat':(('y','x'),da_surface.lat.values),
'y':da_surface.y.values,
'x':da_surface.x.values,
'time':da_surface.time.values,
},
dims=['time', 'y', 'x']
)
db.rename('sub_surface')
return db
def combine_runoff(self,):
# rf = Runoff()
# da_subsurface = xr.open_dataarray(self.path_subsurface) # 细网格
ds_surface = xr.open_dataset(self.path_surface) # 细网格
# ds = ds_surface
ds_subsurface = xr.open_dataset(self.path_subsurface)
# ds1 = xr.open_dataset(flnm1)
# ds2 = xr.open_dataset(flnm2)
da_subsurface = ds_subsurface['subsurface_runoff']
da_surface= ds_surface['surface_runoff']
# rf = Runoff()
dc = self.regrid_coarse2fine3d(da_subsurface, da_surface)
dd = dc.rename('subsurface_runoff')
ds_surface['subsurface_runoff'] = dd
# ds['runoff_subsurface'] = da_subsurface
# dc = rf.regrid_coarse2fine3d(da_subsurface, da_surface)
# ds = xr.concat([da_surface, dc], pd.Index(['runoff_surface', 'runoff_subsurface'], name="model")).to_dataset(dim='model')
self.path_runoff = '/home/fengx20/project/hydro/data/output/runoff_small.nc'
ds_surface.to_netcdf(self.path_runoff)
return ds_surface
# %%
rf = Runoff()
# rf.combine_subsurface_runoff()
rf.combine_surface_runoff()
# rf.combine_runoff()
# rf.regrid_coarse2fine3d()
# dss
# %%
# flnm = '/home/fengx20/project/hydro/test3/RUN/Grid_nolake/202207140000.LSMOUT_DOMAIN1'
# ds = xr.open_dataset(flnm)
# ds.y.values
# ds['']
# ds['sfcheadrt'].time.values
#%%
# fl_list_subsurface
# dds_list = []
# %%
# lon1