The need to assess the effects of variability in climate, biota, geology, and human activities on water availability and flow requires the development of models that couple two or more components of the hydrologic cycle. An integrated hydrologic model called GSFLOW (Groundwater and Surface-water FLOW) was developed to simulate coupled groundwater and surface-water resources. The new model is based on the integration of the U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) and the U.S. Geological Survey Modular Groundwater Flow Model (MODFLOW). Additional model components were developed, and existing components were modified, to facilitate integration of the models. Methods were developed to route flow among the PRMS Hydrologic Response Units (HRUs) and between the HRUs and the MODFLOW finite-difference cells. This report describes the organization, concepts, design, and mathematical formulation of all GSFLOW model components. An important aspect of the integrated model design is its ability to conserve water mass and to provide comprehensive water budgets for a location of interest. This report includes descriptions of how water budgets are calculated for the integrated model and for individual model components. GSFLOW provides a robust modeling system for simulating flow through the hydrologic cycle, while allowing for future enhancements to incorporate other simulation techniques.
Any questions about GSFLOW should be sent to GSFLOW Help.
Releases
The current GSFLOW execuatable, source code, documentation, and test problem is available from the GSFLOW software page
Documentation
Markstrom, S.L., Niswonger, R.G., Regan, R.S., Prudic, D.E., and Barlow, P.M., 2008, GSFLOW-Coupled Ground-water and Surface-water FLOW model based on the integration of the Precipitation-Runoff Modeling System (PRMS) and the Modular Ground-Water Flow Model (MODFLOW-2005): U.S. Geological Survey Techniques and Methods 6-D1, 240 p.
The presentations, handouts, and student data sets from the GSFLOW training course taught April 6-20, 2009 in the USGS National Training Center are available from the links below.
Instructions for Preparing Input Files and Running GSFLOW
An approach for preparing input files for GSFLOW is provided in the "Instructions" link below. The approach has been used by the USGS to prepare input files for the Sagehen Creek Watershed model described in the GSFLOW manual (USGS TM 6-D1). The approach is certainly not the only procedure that could be used to prepare input files for the code.
Allander, K.K., Niswonger, R.N., and Jeton, A.E., 2014, Simulation of the Lower Walker River Basin hydrologic system, west-central Nevada, Using PRMS and MODFLOW models <http://pubs.usgs.gov/sir/2014/5190/>: U.S. Geological Survey Scientific Investigations Report 2014-5190, 93 p., http://dx.doi.org/10.3133/sir20145190.
Doherty, John, and Hunt, R.J., 2009, Two statistics for evaluating parameter identifiability and error reduction: Journal of Hydrology, v. 366, p. 119-127.
Ely, D.M., and Kahle, S.C., 2012, Simulation of groundwater and surface-water resources and evaluation of water-management alternatives for the Chamokane Creek basin, Stevens County, Washington: U.S. Geological Survey Scientific Investigations Report 2012-5224, 74 p. http://pubs.er.usgs.gov/publication/sir20125224
Essaid, H. I., & Hill, B. R. (2014). Watershed-scale modeling of streamflow change in incised montane meadows. Water Resources Research, 50(3), 2657-2678.
Fulton, J.W., Risser, D.W., Regan, R.S., Walker, J.F., Hunt, R.J., Niswonger, R.G., Hoffman, S.A., and Markstrom, S.L., 2015, Water-budgets and recharge-area simulations for the Spring Creek and Nittany Creek Basins and parts of the Spruce Creek Basin, Centre and Huntingdon Counties, Pennsylvania, Water Years 2000-06: U.S. Geological Survey Scientific Investigations Report 2015-5073, 86 p, <http://dx.doi.org/10.3133/sir20155073>.
Hassan, T. S. M., Lubczynski, M. W., Niswonger, R. G., & Su, Z. (2014). Surfacegroundwater interactions in hard rocks in Sardon Catchment of western Spain: An integrated modeling approach. Journal of Hydrology, 517, 390-410. doi:10.1016/j.jhydrol.2014.05.026. <http://www.sciencedirect.com/science/article/pii/S0022169414003904>
Hevesi, J.A., Woolfenden, L.R., Niswonger, R.G., Regan, R.S., and Nishikawa, Tracy, 2011, Decoupled application of the integrated hydrologic model, GSFLOW, to estimate agricultural irrigation in the Santa Rosa Plain, California: Golden, CO, MODFLOW and More 2011 Conference Proceedings, p. 115-119.
Hunt, R.J., Prudic, D.E., Walker, J.F., and Anderson, M.P., 2008, Importance of unsaturated zone flow for simulating recharge in a humid climate: Ground Water, v. 46, no. 4, p. 551-560. doi: 10.1111/j.1745-6584.2007.00427.x
Hunt, R.J., Walker, J.F., Selbig, W.R., Westenbroek, S.M., and Regan, R.S., 2013, Simulation of climate-change effects on streamflow, lake water budgets, and stream temperature using GSFLOW and SNTEMP, Trout Lake Watershed, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2013-5159, 118 p. http://pubs.er.usgs.gov/publication/sir20135159
Huntington, J.L., and Niswonger, R.G., 2012, Role of surface-water and groundwater interactions on projected summertime streamflow in snow dominated regions: An integrated modeling approach: Water Resources Research, v. 48, W11524, doi: 10.1029/2012WR012319.
Huntington, J.L., R.G. Niswonger, S. Rajagopal, Y. Zhang, M. Gardner, C.G. Morton, D. M. Reeves, D. McGraw, G.M. Pohll, 2013. Integrated Hydrologic Modeling of Lake Tahoe and Martis Valley Mountain Block and Alluvial Systems, Nevada and California. Proceedings Paper, MODFLOW and More 2013, June 2-5, 2013, Golden, Colorado, 5 pp. http://www.dri.edu/images/stories/divisions/das/dasfaculty/Huntington_et_al._2013.pdf
Kassenaar, Dirk, Wexler, E.J., Marchildon, Mason, and Li, Qing, 2011, GSFLOW modeling of surface water and groundwater flow for source water protection, regional municipality of York, Ontario, Canada: Golden, CO, MODFLOW and More 2011 Conference Proceedings, p. 150-154.
Mejia, J.F., Huntington, Justin, Hatchett, Benjamin, Koracin, Darko, and Niswonger, R.G., 2012, Linking global climate models to an integrated hydrologic model: Using an individual station downscaling approach: Journal of Contemporary Water Research and Education, issue 147, p. 17-27.
Surfleet, C.G. and Tullos, Desiree, 2012, Uncertainty in hydrologic modeling for estimating hydrologic response due to climate change (Santiam River, Oregon): Hydrological Processes, DOI: 10.1002/hyp.9485.
Surfleet, C.G., Tullos, Desiree, Chang, Heejun, and Jun, Il-Won, 2012, Selection of hydrologic modeling approaches for climate change assessment: A comparison of model scale and structures: Journal of Hydrology, v. 464-465, p. 233-248 http://dx.doi.org/10.1016/j.jhydrol.2012.07.012
Tian, Yong, Zheng, Yi, Wu, Bin, Wu, Xin, Liu, Jie, and Zheng, Chunmiao, 2015, Modeling surface water-groundwater interaction in arid and semi-arid regions with intensive agriculture. Environmental Modelling & Software, 63, p. 170-184, <http://dx.doi.org/10.1016/j.envsoft.2014.10.011>.
Tian, Yong, Zheng, Yi, Zheng, Chunmiao, Xiao, Honglang, Fan, Wenjie, Zou, Songbing, Wu, Bin, Yao, Yingying, Zhang, Aijing, and Liu, Jie, 2015, Exploring scale‐dependent ecohydrological responses in a large endorheic river basin through integrated surface water‐groundwater modeling: Water Resources Research, v. 51, p. 4065-4085, doi:10.1002/2015WR016881.
Woolfenden, L.R., and Nishikawa, Tracy, eds., 2014, Simulation of groundwater and surface-water resources of the Santa Rosa Plain watershed, Sonoma County, California <http://pubs.usgs.gov/sir/2014/5052/>: U.S. Geological Survey Scientific Investigations Report 2014-5052, 258 p., http://dx.doi.org/10.3133/sir20145052.
Woolfenden, L.R., Hevesi, J.A., Niswonger, R.G., and Nishikawa, Tracy, 2011, Modeling a complex hydrologic system with an integrated hydrologic model: Preliminary results: Golden, CO, MODFLOW and More 2011 Conference Proceedings, p. 134-138.
Wu, Bin, Zheng, Yi, Tian, Yong, Wu, Xin, Yao, Yingying, Han, Feng, Liu, Jie, and Zheng, Chunmiao, 2014, Systematic assessment of the uncertainty in integrated surface water-groundwater modeling based on the probabilistic collocation method: Water Resources Research, DOI: 10.1002/2014WR015366.
Wu, Bin, Zheng, Yi, Wu, Xin, Tian, Yong, Han, Feng, Liu, Jie, and Zheng, Chunmiao, 2015, Optimizing water resources management in large river basins with integrated surface water‐groundwater modeling: A surrogate‐based approach: Water Resources Research, v. 51, p. 2153-2173, doi:10.1002/2014WR016653.
Wu, Xin, Zheng, Yi, Wu, Bin, Tian, Yong, Han, Feng, and Zheng, Chunmiao, 2015, Optimizing conjunctive use of surface water and groundwater for irrigation to address human-nature water conflicts: A surrogate modeling approach: Agricultural Water Management, <http://dx.doi.org/10.1016/j.agwat.2015.08.022>.
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