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Island effect #2

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Island effect #2

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a56a00b
Update weight.py
mjshaw1 Dec 6, 2018
c57b04f
Using mask for addressing island effect
mjshaw1 Nov 13, 2020
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69 changes: 50 additions & 19 deletions RAPIDpy/gis/weight.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@
from shapely.geos import TopologicalError
import rtree # http://toblerity.org/rtree/install.html
from osgeo import gdal, ogr, osr
import array

# local
from .voronoi import pointsToVoronoiGridArray
Expand Down Expand Up @@ -80,7 +81,7 @@ def find_nearest(array, value):
return (np.abs(array-value)).argmin()


def rtree_create_weight_table(lsm_grid_lat, lsm_grid_lon,
def rtree_create_weight_table(lsm_grid_lat, lsm_grid_lon, lsm_grid_mask,
in_catchment_shapefile, river_id,
in_rapid_connect, out_weight_table,
file_geodatabase=None, area_id=None):
Expand All @@ -103,7 +104,6 @@ def rtree_create_weight_table(lsm_grid_lat, lsm_grid_lon,
else:
ogr_catchment_shapefile = ogr.Open(in_catchment_shapefile)
ogr_catchment_shapefile_lyr = ogr_catchment_shapefile.GetLayer()

ogr_catchment_shapefile_lyr_proj = \
ogr_catchment_shapefile_lyr.GetSpatialRef()
original_catchment_proj = \
Expand Down Expand Up @@ -149,6 +149,7 @@ def rtree_create_weight_table(lsm_grid_lat, lsm_grid_lon,
enumerate(ogr_catchment_shapefile_lyr):
catchment_rivid_list[feature_idx] = \
catchment_feature.GetField(river_id)

log("Reading in RAPID connect file ...")
rapid_connect_rivid_list = np.loadtxt(in_rapid_connect,
delimiter=",",
Expand Down Expand Up @@ -184,7 +185,7 @@ def rtree_create_weight_table(lsm_grid_lat, lsm_grid_lon,
proj_transform = \
osr.CoordinateTransformation(ogr_catchment_shapefile_lyr_proj,
osr_geographic_proj)
print(catchment_rivid_list)

for rapid_connect_rivid in rapid_connect_rivid_list:
intersect_grid_info_list = []
try:
Expand All @@ -194,9 +195,12 @@ def rtree_create_weight_table(lsm_grid_lat, lsm_grid_lon,
# if it is not in the catchment, add dummy row in its place
connectwriter.writerow([rapid_connect_rivid] + dummy_row_end)
continue


get_catchment_feature = \
ogr_catchment_shapefile_lyr.GetFeature(catchment_pos)
feat_geom = get_catchment_feature.GetGeometryRef()

# make sure coordinates are geographic
if proj_transform:
feat_geom.Transform(proj_transform)
Expand Down Expand Up @@ -240,22 +244,40 @@ def rtree_create_weight_table(lsm_grid_lat, lsm_grid_lon,
lsm_grid_lon,
lsm_grid_feature_list[sub_lsm_grid_pos]['lat'],
lsm_grid_feature_list[sub_lsm_grid_pos]['lon'])
intersect_grid_info_list.append({
'rivid': rapid_connect_rivid,
'area': poly_area,
'lsm_grid_lat':
lsm_grid_feature_list[sub_lsm_grid_pos]['lat'],
'lsm_grid_lon':
lsm_grid_feature_list[sub_lsm_grid_pos]['lon'],
'index_lsm_grid_lon': index_lsm_grid_lon,
'index_lsm_grid_lat': index_lsm_grid_lat
})
# If ocean/water point, ECMWF sets ro to very negative number.
# This resulted at times in "island effect", i.e., large
# grid cell overlaying rivid and thus weird results. So,
# use land mask field to address these ECMWF points.
# There are arguments for and against division by land fraction. E.g.,
# it's arguable that division by mask might overemphasis some
# pixels that contain fine grained islands with runoff.
if lsm_grid_mask[int(index_lsm_grid_lat), int(index_lsm_grid_lon)] > 0:
intersect_grid_info_list.append({
'rivid': rapid_connect_rivid,
'area': poly_area/lsm_grid_mask[int(index_lsm_grid_lat), int(index_lsm_grid_lon)],
'lsm_grid_lat':
lsm_grid_feature_list[sub_lsm_grid_pos]['lat'],
'lsm_grid_lon':
lsm_grid_feature_list[sub_lsm_grid_pos]['lon'],
'index_lsm_grid_lon': index_lsm_grid_lon,
'index_lsm_grid_lat': index_lsm_grid_lat
})
# Prior weight table write without addressing land mask.
# intersect_grid_info_list.append({
# 'rivid': rapid_connect_rivid,
# 'area': poly_area,
# 'lsm_grid_lat':
# lsm_grid_feature_list[sub_lsm_grid_pos]['lat'],
# 'lsm_grid_lon':
# lsm_grid_feature_list[sub_lsm_grid_pos]['lon'],
# 'index_lsm_grid_lon': index_lsm_grid_lon,
# 'index_lsm_grid_lat': index_lsm_grid_lat
# })

npoints = len(intersect_grid_info_list)
# If no intersection found, add dummy row
if npoints <= 0:
connectwriter.writerow([rapid_connect_rivid] + dummy_row_end)

for intersect_grid_info in intersect_grid_info_list:
connectwriter.writerow([
intersect_grid_info['rivid'],
Expand All @@ -266,7 +288,6 @@ def rtree_create_weight_table(lsm_grid_lat, lsm_grid_lon,
intersect_grid_info['lsm_grid_lon'],
intersect_grid_info['lsm_grid_lat']
])

time_end_all = datetime.utcnow()
log(time_end_all - time_end_lsm_grid_rtree)
log("TOTAL TIME: {0}".format(time_end_all - time_start_all))
Expand Down Expand Up @@ -299,7 +320,7 @@ def CreateWeightTableECMWF(in_ecmwf_nc,
The path to the output weight table file.
area_id: str, optional
The name of the field with the area of each catchment stored in meters
squared. Default is to calculate the area.
squared. Default is it calculate the area.
file_geodatabase: str, optional
Path to the file geodatabase. If you use this option, in_drainage_line
is the name of the stream network feature class.
Expand Down Expand Up @@ -330,15 +351,24 @@ def CreateWeightTableECMWF(in_ecmwf_nc,
in_ecmwf_lon_var = 'lon'
if 'longitude' in variables_list:
in_ecmwf_lon_var = 'longitude'
in_ecmwf_mask_var = 'mask'
# in_ecmwf_mask_var = 'lsm'
# if 'lsm' in variables_list:
# in_ecmwf_mask_var = 'lsm'
# in_ecmwf_mask_var = 'LAND_P0_L1_GLL0'
if 'mask' in variables_list:
in_ecmwf_mask_var = 'mask'

# convert [0, 360] to [-180, 180]
ecmwf_lon = \
(data_ecmwf_nc.variables[in_ecmwf_lon_var][:] + 180) % 360 - 180
# assume [-90, 90]
ecmwf_lat = data_ecmwf_nc.variables[in_ecmwf_lat_var][:]
ecmwf_mask = data_ecmwf_nc.variables[in_ecmwf_mask_var][0,:,:]

data_ecmwf_nc.close()

rtree_create_weight_table(ecmwf_lat, ecmwf_lon,
rtree_create_weight_table(ecmwf_lat, ecmwf_lon, ecmwf_mask,
in_catchment_shapefile, river_id,
in_connectivity_file, out_weight_table,
file_geodatabase, area_id)
Expand Down Expand Up @@ -371,6 +401,8 @@ def CreateWeightTableLDAS(in_ldas_nc,
The name of the field with the river ID (Ex. 'DrainLnID' or 'LINKNO').
in_connectivity_file: str
The path to the RAPID connectivity file.
is the name of the stream network feature class.
(WARNING: Not always stable with GDAL.)
out_weight_table: str
The path to the output weight table file.
area_id: str, optional
Expand All @@ -381,7 +413,6 @@ def CreateWeightTableLDAS(in_ldas_nc,
is the name of the stream network feature class.
(WARNING: Not always stable with GDAL.)


Example:

.. code:: python
Expand All @@ -396,7 +427,7 @@ def CreateWeightTableLDAS(in_ldas_nc,
river_id='LINKNO',
in_connectivity_file='/path/to/rapid_connect.csv',
out_weight_table='/path/to/ldas_weight.csv',
)
)
"""
# extract LDAS GRID
data_ldas_nc = Dataset(in_ldas_nc)
Expand Down