Journal article
Determination of accurate baseline representation for three Central Iowa watersheds within a HAWQS-based SWAT analyses
The Science of the total environment, Vol.839, pp.156302-156302
09/15/2022
DOI: 10.1016/j.scitotenv.2022.156302
PMID: 35640760
Abstract
Improving food systems to address food insecurity and minimize environmental impacts is still a challenge in the 21st century. Ecohydrological models are a key tool for accurate system representation and impact measurement. We used a multi-phase testing approach to represent baseline hydrologic conditions across three agricultural basins that drain parts of north central and central Iowa, U.S.: the Des Moines River Basin (DMRB), the South Skunk River Basin (SSRB), and the North Skunk River Basin (NSRB). The Soil and Water Assessment Tool (SWAT) ecohydrological model was applied using a framework consisting of the Hydrologic and Water Quality System (HAWQS) online platform, 40 streamflow gauges, the alternative runoff curve number method, additional tile drainage and fertilizer application. In addition, ten SWAT baselines were created to analyze both the HAWQS parameters (baseline 1) and nine alternative baseline configurations (considering the framework). Most of the models achieved acceptable statistical replication of measured (close to the outlet) streamflows, with Nash-Sutcliffe (NS) values ranging up to 0.80 for baseline 9 in the DMRB and SSRB, and 0.78 for baseline 7 in the NSRB. However, water balance and other hydrologic indicators revealed that careful selection of management data and other inputs are essential for obtaining the most accurate representation of baseline conditions for the simulated stream systems. Using cumulative distribution curves as a criterion, baselines 7 to 10 showed the best fit for the SSRB and NSRB, but none of the baselines accurately represented 20% of low flows for the DMRB. Analysis of snowmelt and growing season periods showed that baselines 3 and 4 resulted in poor simulations across all three basins using four common statistical measures (NS, KGE, Pbias, and R2), and that baseline 9 was characterized by the most satisfactory statistical results, followed by baselines 5, 7 and 1.
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•The number of monitoring gauges is novel compared to previous SWAT applications.•The RCN method improved the estimation rate between baseflow and surface runoff.•The quantity and spatial variability of monitoring gauges improved model confidence.•Statistical optimum (e.g., NS > 0.50) does not necessarily mean hydrological optimum.
Details
- Title: Subtitle
- Determination of accurate baseline representation for three Central Iowa watersheds within a HAWQS-based SWAT analyses
- Creators
- Tássia Mattos Brighenti - Iowa State UniversityPhilip W. Gassman - Iowa State UniversityKeith E. Schilling - United States Geological SurveyRaghavan Srinivasan - Texas A&M UniversityMatt Liebman - Iowa State UniversityJan R. Thompson - Iowa State University
- Resource Type
- Journal article
- Publication Details
- The Science of the total environment, Vol.839, pp.156302-156302
- Publisher
- Elsevier B.V
- DOI
- 10.1016/j.scitotenv.2022.156302
- PMID
- 35640760
- ISSN
- 0048-9697
- eISSN
- 1879-1026
- Grant note
- DOI: 10.13039/100000001, name: National Science Foundation, award: 1855902
- Language
- English
- Date published
- 09/15/2022
- Academic Unit
- Earth and Environmental Sciences; IIHR--Hydroscience and Engineering
- Record Identifier
- 9984383906702771
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