SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Progress toward evaluating the sustainability of switchgrass as a bioenergy crop using the SWAT model 
Authors:Baskaran, L., H.I. Jager, P.E. Schweizer and R. Srinivasan 
Journal:Transactions of the ASABE 
Article ID: 
URL (non-DOI journals):https://elibrary.asabe.org/abstract.asp?aid=34905&t=1 
Broad Application Category:hydrologic only 
Primary Application Category:crop growth/yield or plant parameters 
Secondary Application Category:hydrologic assessment 
Watershed Description:Switchgrass growth analysis performed for 12 major U.S water resource regions (New England, Mid-Atlantic, South Atlantic-Gulf, Great Lakes, Ohio, Lower Mississippi, Texas-Gulf, Arkansas-White-Red, Missouri, Upper Mississippi, Souris-Red-Rainy, and Rio-Grand) and hydrologic analysis for the Arkansas White-Red system in south Central U.S. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:Adding bioenergy to the U.S. energy portfolio requires long‐term profitability for bioenergy producers and long‐term protection of affected ecosystems. In this study, we present steps along the path toward evaluating both sides of the sustainability equation (production and environmental) for switchgrass (Panicum virgatum) using the Soil and Water Assessment Tool (SWAT). We modeled production of switchgrass and river flow using SWAT for current landscapes at a regional scale. To quantify feedstock production, we compared lowland switchgrass yields simulated by SWAT with estimates from a model based on empirical data for the eastern U.S. The two produced similar geographic patterns. Average yields reported in field trials tended to be higher than average SWAT‐predicted yields, which may nevertheless be more representative of production‐scale yields. As a preliminary step toward quantifying bioenergy‐related changes in water quality, we evaluated flow predictions by the SWAT model for the Arkansas‐White‐Red river basin. We compared monthly SWAT flow predictions to USGS measurements from 86 subbasins across the region. Although agreement was good, we conducted an analysis of residuals (functional validation) seeking patterns to guide future model improvements. The analysis indicated that differences between SWAT flow predictions and field data increased in downstream subbasins and in subbasins with higher percentage of water. Together, these analyses have moved us closer to our ultimate goal of identifying areas with high economic and environmental potential for sustainable feedstock production. 
Keywords:Bioenergy, Functional validation, River flow, Sensitivity analysis, Sustainability, Switchgrass, Water quality