This is a demonstration of the WC-WAVE simplified, open source version of the CASiMiR model. The model operates on a yearly timescale. The inputs required are a vegetation map, a map of shear stress casued by flooding, and a JSON lookup file that maps vegetation codes to resistance to shear stress. If the shear stress exceeds the resistance at a grid cell, the vegetation is set to "age zero" at that cell. This means that the same vegetation that was once there will still "grow", but from a "seedling".
In practice, there are six different vegetation types currently. There is still some generalization work to be done since this has been developed specifically for the Jemez River.
Below we show how to run the code and visualize the results using a simple 4x5 grid using file paths as input. After that we'll show how to load the files into ESRIAsc objects, which will be useful for demonstrating what's going on.
In [7]:
%matplotlib inline
import matplotlib.pyplot as plt
import sys
# enable import of vwpy objects
sys.path.append('../../')
from vwpy.dflow_casimir import casimir, ESRIAsc
# set up paths to files
veg_ascii_file = 'vegcode.asc'
shear_ascii_file = 'shear.asc'
veg_resistance_lookup = 'resistance.json'
# run CASiMiR
veg_output = casimir(veg_ascii_file, shear_ascii_file, veg_resistance_lookup)
print "The output type is " + veg_output.__class__.__name__
plt.figure(figsize=(5,6))
plt.matshow(veg_output.as_matrix(replace_nodata_val=0.0))
plt.title('Output after one CASiMiR run year')
plt.xlabel('easting direction index')
plt.ylabel('westing direction index')
plt.colorbar()
Out[7]:
The ESRIAsc type contains all the information an ESRI .asc has in its header as attributes:
So you can use cellsize and the corners to make better x and y ticks and labels that are more physically meaningful using the matplotlib.pyplot.xticks and matplotlib.pyplot.yticks methods.
Now we'll show another way to use CASiMiR--by first loading the vegetation ans shear data into an ESRIAsc object and loading the resistance.json file into a Python dictionary using the standard library's json module
In [10]:
import json
veg_map = ESRIAsc(veg_ascii_file)
shear_map = ESRIAsc(shear_ascii_file)
shear_resistance_dict = json.load(open(veg_resistance_lookup))
plt.figure()
plt.matshow(veg_map.as_matrix(replace_nodata_val=0.0))
plt.title('Initial Vegetation Map')
plt.colorbar()
plt.figure()
plt.matshow(shear_map.as_matrix(replace_nodata_val=0.0))
plt.title('Shear Stress Map')
plt.colorbar()
veg_output = casimir(veg_map, shear_map, shear_resistance_dict)
plt.figure()
plt.matshow(veg_output.as_matrix(replace_nodata_val=0.0))
plt.title('Post-process Vegetation Map')
plt.colorbar()
Out[10]: