SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Comparative analysis of bioenergy crop impacts on water quality using static and dynamic land use change modeling approach 
Authors:Kumar, E., D. Saraswat and G. Singh 
Year:2020 
Journal:Water 
Volume (Issue):12(2) 
Pages: 
Article ID:410 
DOI:10.3390/w12020410 
URL (non-DOI journals): 
Model:SWAT 
Broad Application Category:hydrologic & pollutant 
Primary Application Category:bioenergy crop, tree and/or vegetation assessment 
Secondary Application Category:nutrient cycling/loss and transport 
Watershed Description:5,066 km^2 Cache River, a tributary of the White River located in northeast Arkansas, U.S. 
Calibration Summary: 
Validation Summary: 
General Comments: 
Abstract:Researchers and federal and state agency officials have long been interested in evaluating location‐specific impact of bioenergy energy crops on water quality for developing policy interventions. This modeling study examines long‐term impact of giant miscanthus and switchgrass on water quality in the Cache River Watershed (CRW) in Arkansas, United States. The bioenergy crops were simulated on marginal lands using two variants of a Soil and Watershed Assessment Tool (SWAT) model. The first SWAT variant was developed using a static (single) land‐use layer (regular‐SWAT) and forthe second, a dynamic land‐use change feature was used with multiple land use layers (location‐SWAT). Results indicated that the regular‐SWAT predicted larger losses for sediment, total phosphorus and total nitrogen when compared to location‐SWAT at the watershed outlet. The lower predicted losses from location‐SWAT were attributed to its ability to vary marginal land area between 3% and 11% during the 20‐year modeling period as opposed to the regular‐SWAT that used a fixed percentage of marginal land area (8%) throughout the same period. Overall, this study demonstrates that environmental impacts of bioenergy crops were better assessed using the dynamic land‐use representation approach, which would eliminate any unintended prediction bias in the model due to the use of a single land use layer. 
Language:English 
Keywords:water quality; bioenergy crops; SWAT; marginal lands; dynamic land use change; watershed modeling