GSFLOW-GRASS v1.0.0: GIS-enabled hydrologic modeling of coupled groundwater-surface-water systems

G. H. Crystal Ng, Andrew D. Wickert, Lauren D. Somers, Leila Saberi, Collin Cronkite-Ratcliff, Richard G. Niswonger, Jeffrey M. McKenzie

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The importance of water moving between the atmosphere and aquifers has led to efforts to develop and maintain coupled models of surface water and groundwater. However, developing inputs to these models is usually time-consuming and requires extensive knowledge of software engineering, often prohibiting their use by many researchers and water managers, thus reducing these models' potential to promote science-driven decision-making in an era of global change and increasing water resource stress. In response to this need, we have developed GSFLOW-GRASS, a bundled set of open-source tools that develops inputs for, executes, and graphically displays the results of GSFLOW, the U.S. Geological Survey's coupled groundwater and surface-water flow model. In order to create a robust tool that can be widely implemented over diverse hydro(geo)logic settings, we built a series of GRASS GIS extensions that automatically discretizes a topological surface-water flow network that is linked with an underlying gridded groundwater domain. As inputs, GSFLOW-GRASS requires at a minimum a digital elevation model, a precipitation and temperature record, and estimates of channel parameters and hydraulic conductivity. We demonstrate the broad applicability of the toolbox by successfully testing it in environments with varying degrees of drainage integration, landscape relief, and grid resolution, as well as the presence of irregular coastal boundaries. These examples also show how GSFLOW-GRASS can be implemented to examine the role of groundwater-surface-water interactions in a diverse range of water resource and land management applications.

Original languageEnglish (US)
Pages (from-to)4755-4777
Number of pages23
JournalGeoscientific Model Development
Volume11
Issue number12
DOIs
StatePublished - Nov 30 2018

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