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ProcessSurfaceFlow.py
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ProcessSurfaceFlow.py
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###############################################################################
# Hydrologic Processing for GSFLOW GRID - surface flow routing
# Cap Wallace Modeling project
# W. Payton Gardner
# University of Montana
# School of Forestry and Conservation
###############################################################################
#calculate flow accumulation and flow directions for the Cap Wallace GSFLOW model
#imports
import os
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
import numpy as np
import pdb
import flopy
from gsflow.builder import GenerateFishnet
from gsflow.builder import FlowAccumulation
##################################################
# Input path management
##################################################
# set our cell size in meters. #I'll start out with 100m for now, but will likely refine
cellsize=100
method = "nearest"
#model name
model_name = "Elkcreek_%3im"%cellsize+method
#toplevel ouput path
model_path = os.path.join("models",model_name)
#derived gis output path
gis_derived_path = os.path.join(model_path,"gis_deriv")
# define the modelgrid and resampled DEM data paths
mg_file = os.path.join(model_path, "grid.bin")
# I had to reprocess the resampled DEM with SAGA - this is now the resulting, filled/burned .tif
dem_data = os.path.join(gis_derived_path, "DEMResampledSAGA.tif")
# No Reprocessing with Q
#dem_data = os.path.join(gis_derived_path, "DEMResampled.tif")
#######################################################
#PROCESS FLOW ACCUMULATION
#######################################################
# load modelgrid
modelgrid = GenerateFishnet.load_from_file(mg_file)
#dem_data = np.genfromtxt(dem_data) #not using the raw dem_data from the previous script, using the post processed stuff.
#load the post processed SAGA file
# at some point the SAGA post processing aught to be included in the builder stuff.
dem_data = flopy.utils.Raster.load(dem_data)
dem_data = dem_data.get_array(1)
# instatiate the FlowAccumulation object
fa = FlowAccumulation(
dem_data,
modelgrid.xcellcenters,
modelgrid.ycellcenters,
verbose=True
)
# use a small breaching tolerance and dijkstra's algorithm in this example
flow_directions = fa.flow_directions(dijkstra=True, breach=.001)
qx, qy = fa.get_vectors
# plot the flow directions as a quiver map
fig = plt.figure(figsize=(10, 8))
ax = fig.add_subplot(1, 1, 1, aspect="equal")
pmv = flopy.plot.PlotMapView(modelgrid=modelgrid, ax=ax)
pmv.plot_array(
dem_data, vmin=dem_data.min(), vmax=dem_data.max()
)
plt.quiver(modelgrid.xcellcenters, modelgrid.ycellcenters, qx, qy,scale=100)
plt.title("Cap Wallace 100m flow direction vectors")
plt.tight_layout()
plt.show()
# run flow accumulation
flow_accumulation = fa.flow_accumulation()
# plot the flow accumulation array
fig = plt.figure(figsize=(10, 8))
ax2 = fig.add_subplot(1, 1, 1, aspect="equal")
pmv = flopy.plot.PlotMapView(modelgrid=modelgrid, ax=ax2)
pmv.plot_array(
dem_data, vmin=dem_data.min(), vmax=dem_data.max(), cmap='Greys'
)
pc = pmv.plot_array(flow_accumulation,alpha=0.4)
plt.title("Elk Creek 100m flow accumulation array")
plt.colorbar(pc, shrink=0.7)
plt.show()
##############################################
#Save GIS for later
##############################################
#flow dir
np.savetxt(
os.path.join(gis_derived_path, "flowdir.txt"),
flow_directions.astype(int),
delimiter=" ",
fmt="%d")
np.savetxt(
os.path.join(gis_derived_path, "flowacc.txt"),
flow_accumulation,
delimiter=" "
)
dfname = "DEMResampledFA.txt"
dem_file = os.path.join(gis_derived_path, dfname)
np.savetxt(dem_file, dem_data, delimiter=" ")