Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/gmd-2017-321
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Model description paper
30 Jan 2018
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).
GSFLOW-GRASS v1.0.0: GIS-enabled hydrologic modeling of coupled groundwater–surface-water systems
G.-H. Crystal Ng1,2, Andrew D. Wickert1,2, Lauren D. Somers3, Leila Saberi1, Collin Cronkite-Ratcliff4, Richard G. Niswonger5, and Jeffrey M. McKenzie3 1Department of Earth Sciences, University of Minnesota, Minneapolis, Minnesota, USA
2Saint Anthony Falls Laboratory, University of Minnesota, Minneapolis, Minnesota, USA
3Department of Earth and Planetary Sciences, McGill University, Montreal, Quebec, Canada
4Geology, Minerals, Energy and Geophysics Science Center, United States Geological Survey, Menlo Park, California USA
5Earth Systems Modeling Branch, United States Geological Survey, Menlo Park, California, USA
Abstract. Water flow through catchments sustains ecosystems and human activity, shapes landscapes, and links climate to the outermost layers of the solid Earth. The profound 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, and 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 straightforward set of open-source tools that develops inputs for and runs GSFLOW, the U.S. Geological Survey's coupled groundwater-surface-water flow model. 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. GSFLOW-GRASS is written in Python as a set of (1) GRASS GIS extensions, (2) input-file-builder scripts, and (3) visualization scripts. We developed a set of custom GRASS GIS commands that generate "hydrologic response units" for surface water, discretized topologically as sub-basins of the tributary network; build the MODFLOW grid; and add necessary attributes to each of these geospatial units. These GIS outputs are interpreted by a second set of Python scripts, which link them to hydrologic variables, build inputs to GSFLOW, and run GSFLOW. Lastly, GSFLOW output files are used to produce figures and time-lapse movies of simulation results using a third set of post-processing Python scripts. We demonstrate the broad applicability of these tools to diverse settings through examples based on: the high Peruvian Andes, the Channel Islands of California, and the formerly-glaciated Upper Mississippi valley in Minnesota.
Citation: Ng, G.-H. C., Wickert, A. D., Somers, L. D., Saberi, L., Cronkite-Ratcliff, C., Niswonger, R. G., and McKenzie, J. M.: GSFLOW-GRASS v1.0.0: GIS-enabled hydrologic modeling of coupled groundwater–surface-water systems, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-321, in review, 2018.
G.-H. Crystal Ng et al.
G.-H. Crystal Ng et al.
G.-H. Crystal Ng et al.

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Short summary
The profound importance of water has led to the development of increasingly complex hydrological models. However, implementing these models is usually time-consuming and requires specialized expertise, stymieing their widespread use to support science-driven decision-making. In response, we have developed GSFLOW-GRASS, a straightforward set of software tools that can be readily used to set up and execute GSFLOW, the U.S. Geological Survey's coupled groundwater-surface-water flow model.
The profound importance of water has led to the development of increasingly complex hydrological...
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