Next Article in Journal
A Comparison and Validation of Saturated Hydraulic Conductivity Models
Next Article in Special Issue
Using UAV Visible Images to Estimate the Soil Moisture of Steppe
Previous Article in Journal
Forecasting Urban Water Demand Using Cellular Automata
Article

Improving SWAT Model Calibration Using Soil MERGE (SMERGE)

Center for Earth and Environmental Studies, Texas A&M International University, Laredo, TX 78045, USA
*
Author to whom correspondence should be addressed.
Water 2020, 12(7), 2039; https://doi.org/10.3390/w12072039
Received: 13 May 2020 / Revised: 13 July 2020 / Accepted: 14 July 2020 / Published: 18 July 2020
(This article belongs to the Special Issue Contributions of Remote Sensing to Hydrologic Flux Quantification)
This study examined eight Great Plains moderate-sized (832 to 4892 km2) watersheds. The Soil and Water Assessment Tool (SWAT) autocalibration routine SUFI-2 was executed using twenty-three model parameters, from 1995 to 2015 in each basin, to identify highly sensitive parameters (HSP). The model was then run on a year-by-year basis, generating optimal parameter values for each year (1995 to 2015). HSP were correlated against annual precipitation (Parameter-elevation Regressions on Independent Slopes Model—PRISM) and root zone soil moisture (Soil MERGE—SMERGE 2.0) anomaly data. HSP with robust correlation (r > 0.5) were used to calibrate the model on an annual basis (2016 to 2018). Results were compared against a baseline simulation, in which optimal parameters were obtained by running the model for the entire period (1992 to 2015). This approach improved performance for annual simulations generated from 2016 to 2018. SMERGE 2.0 produced more robust results compared with the PRISM product. The main virtue of this approach is that it constrains parameter space, minimizesing equifinality and promotesing modeling based on more physically realistic parameter values. View Full-Text
Keywords: SMERGE 2.0; PRISM; root zone soil moisture; SWAT; US Great Plains; mass balance SMERGE 2.0; PRISM; root zone soil moisture; SWAT; US Great Plains; mass balance
Show Figures

Figure 1

MDPI and ACS Style

Tobin, K.J.; Bennett, M.E. Improving SWAT Model Calibration Using Soil MERGE (SMERGE). Water 2020, 12, 2039. https://doi.org/10.3390/w12072039

AMA Style

Tobin KJ, Bennett ME. Improving SWAT Model Calibration Using Soil MERGE (SMERGE). Water. 2020; 12(7):2039. https://doi.org/10.3390/w12072039

Chicago/Turabian Style

Tobin, Kenneth J., and Marvin E. Bennett 2020. "Improving SWAT Model Calibration Using Soil MERGE (SMERGE)" Water 12, no. 7: 2039. https://doi.org/10.3390/w12072039

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop