How to use BDWS¶

Input files¶

Before using the BDWS classes, some input data are required. Below is a brief description of these input files. For more information visit the preparing input data page of the documentation. Note: it is recommended that all inputs be clipped to the valley-bottom extent. This extent can be determined with the V-BET tool.

brat.shp

Shapefile created by the BRAT model. Must contain single-part features. Multi-part features will not be processed by BDLoG.

dem.tif

Digital Elevation Model (DEM) for area of interest. Spatial resoultion of 10 meters or less is recommended.

fac.tif

Rasterized stream network raster. Generally created by applying a threshold to a flow accumulation raster. It is recommended to represent stream network cells with a value of 1 and all other cells with a value less than 1.

fdir.tif

Flow direction raster (D8) derived from the input DEM. Both ESRI and TauDEM D8 flow direction rasters are supported.

General usage¶

Currently, it is recommended to use BDWS to create python scripts to model beaver dam water storage. BDWS has been developed and tested using the PyCharm IDE. Below are brief examples describing how to use BDWS classes. For more detailed examples of BDWS implementation visit the tutorials page of the documentation.

BDWS code is hosted at https://github.com/konradhafen/beaver-dam-water-storage in the bdws.py and bdflopy.py files. Classes can be imported as follows.

from bdws import*
from bdflopy import *

BDLoG takes a vector stream network created by BRAT and generates locations of individual dams on a rasterized stream network.

Initialization of BDLoG requires a shapefile created by BRAT, a DEM, a rasterized stream network, path to output directory, and a proportion of maximum dam capacity to model. The following code will initialize BDLoG, generate dam locations and dam heights, and save output files for a maximum capacity (1.0) scenario.

model = BDLoG('path/to/brat.shp', 'path/to/dem.tif', 'path/to/fac.tif', 'out/dir', 1.0)
model.run()
model.close()

BDSWEA uses dam locations and dam heights generated by BDLoG to estimate the area and surface volume created by beaver dam construction.

BDSWEA requires output files (see below) from BDLoG for initialization. BDSWEA initialization requires a DEM, a flow direction raster derived from the DEM, a rasterized stream network, the dam ID raster created by BDLoG, an output directory, the dam location and attribute shapefile created by BDLoG. The following code will estimate beaver pond inundation and write files necessary for parameterization of MODFLOW.

model = BDSWEA('path/to/dem.tif', 'path/to/fdir.tif', 'path/to/fac.tif', 'path/to/id.tif',
                'out/dir', 'path/to/pts.shp')
model.run()
model.writeModflowFiles()
model.close()

BDflopy implements the existing FloPy module to automatically parameterize MODFLOW-2005 to estimate changes to goundwater storage resulting from beaver dam construction.

BDflopy requires the path to a MODFLOW-2005 executable, path to directory of input rasters, path to directory of BDSWEA outputs, path to directory to write outputs, and name of DEM file in inputs directory for initialization. The following code will initialize BDflopy.

model = BDflopy('path/to/modflow.exe', 'input/dir', 'bdswea/out/dir', 'out/dir', 'dem.tif')

BDflopy.run() requires additional parameters. Horizontal and vertical hydraulic conductivity (as a raster, numpy array, or single value), a factor to convert conductivity values to meters per second, the fraction of soil available for water storage (e.g. field capacity or porosity), and a factor to convert the soil fraction to a proportion. This will write MODFLOW’s input files, run MODFLOW, and generate output raster files. BDflopy.run() can be implemented as follows.

model.run('path/to/hk.tif', 'path/to/vk.tif', 1.0, 'path/to/frac.tif', 1.0)
#or
model.run(1.0, 1.0, 0.000001, 20.0, 0.01)

Then close the class object.

model.close()

Output files¶