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Input data processing tools for the integrated hydrologic model GSFLOW

Environmental Modelling and Software

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https://doi.org/10.1016/j.envsoft.2018.07.020

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Abstract

Integrated hydrologic modeling (IHM) encompasses a vast number of processes and specifications, variable in time and space, and development of models can be arduous. Model input construction techniques have not been formalized or made easily reproducible. Creating the input files for integrated hydrologic models requires complex GIS processing of raster and vector datasets from various sources. Developing stream network topology that is consistent with the model grid-scale digital elevation model (DEM) is important for robust simulation of surface water and groundwater exchanges. Distribution of meteorological data over the model domain is difficult in complex terrain at the model-grid scale, but is necessary for realistic simulations. As model development requires extensive GIS and computer programming expertise, the use of IHMs has mostly been limited to research groups with available financial, human, and technical resources. Here we present a series of open-source Python scripts that are combined with ESRI ArcGIS to provide a formalized technique for the parameterization and development of inputs for the readily available IHM called GSFLOW. This Python toolkit automates many of the necessary and laborious processes of parameterization, including stream network development, land coverages, and meteorological distribution over the model domain. The final products of the toolkit are PRMS ready Parameter Files, along with several input parameters for a MODFLOW model, including input for the Streamflow Routing Package. A demonstration of the toolkit is provided to illustrate its capabilities.

Additional publication details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Input data processing tools for the integrated hydrologic model GSFLOW
Series title:
Environmental Modelling and Software
DOI:
10.1016/j.envsoft.2018.07.020
Volume:
109
Year Published:
2018
Language:
English
Publisher:
Elsevier
Contributing office(s):
Nevada Water Science Center
Description:
13 p.
First page:
41
Last page:
53