Model-data comparisons are always challenging, especially when working at a large spatial scale and evaluating multiple response variables. We implemented the Soil and Water Assessment Tool (SWAT) to simulate water quantity and quality for the Tennessee River Basin. We developed three innovations to overcome hurdles associated with limited data for model evaluation: 1) we implemented an auto-calibration approach to allow simultaneous calibration against multiple responses, including synthetic response variables, such as the HUC8 runoff as an area-weighted average of runoff in multiple subbasins; 2) we identified empirical spatiotemporal datasets to use in our comparison; and 3) we compared functional patterns in landuse-nutrient relationships between SWAT and empirical data. In addition, twenty-two (22) reservoirs in the TRB were included in the SWAT setup, which is conducive to a more realistic modeling of runoff and water quality. We used the 2009 Cropland Data Layer (CDL-2009) (USDA-NASS, 2014) to represent the baseline (i.e., Scenario Base) land use/land cover. The SWAT model was calibrated and validated under Scenario Base. We further applied SWAT to project water quantity and quality under Scenario BC1 and HH3 by replacing the baseline landuse with corresponding future landuse map. This protocol created a total of 4026, 3702, and 4115 distinct HRUs in 55 subbasins under Scenario Base, BC1, and HH3, respectively.
Tennessee River Basin
1. GIS data:
1.1 River basin boundaries, subbasin boundaries, stream network data, landuse/cover, and soil: https://github.com/wanggangsheng/TRB_GIS_data.git
1.2 Additional data (e.g., DEM) can be obtained by contacting the author at email@example.com
2. SWAT input files for 3 landuse scenarios
2.1 baseline scenario: https://github.com/wanggangsheng/SWATIO_TRB_Base_updateAll.git
2.2 BC1 scenario: https://github.com/wanggangsheng/SWATIO_TRB_BC1_updateAll.git
2.3 HH3 scenario: https://github.com/wanggangsheng/SWATIO_TRB_HH3_updateAll.git
Wang G, Jager HI, Baskaran LM, Brandt CC. Hydrologic and water quality responses to biomass production in the Tennessee river basin. GCB Bioenergy. 2018;00:1–17. https://doi.org/10.1111/gcbb.12537.