Science Articles

Western Lake Erie Basin: Soft-data-constrained, NHDPlus resolution watershed modeling and exploration of applicable conservation scenarios.

Science of the Total Environment
2016
Haw Yena, Michael J. Whiteb, Jeffrey G. Arnoldb, S. Conor Keitzerc, Mari-Vaughn V. Johnsond, Jay D. Atwoodd, Prasad Daggupatie, Matthew E. Herbertf, Scott P. Sowaf, Stuart A. Ludsinc, Dale M. Robertsong, Raghavan Srinivasane, Charles A. Rewah
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Volume / Issue569 - 570
Pages1265 - 1281
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Article Linkhttp://www.sciencedirect.com/science/article/pii/S0048969716313894
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DOI10.1016/j.scitotenv.2016.06.202
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TagsLake Erie; NHDPlus model; Soft data; Conservation practice; Swat-SAS; Model calibration
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AbstractComplex watershed simulation models are powerful tools that can help scientists and policy-makers address challenging topics, such as land use management and water security. In the Western Lake Erie Basin (WLEB), complex hydrological models have been applied at various scales to help describe relationships between land use and water, nutrient, and sediment dynamics. This manuscript evaluated the capacity of the current Soil and Water Assessment Tool (SWAT2012) to predict hydrological and water quality processes within WLEB at the finest resolution watershed boundary unit (NHDPlus) along with the current conditions and conservation scenarios. The process based SWAT model was capable of the fine-scale computation and complex routing used in this project, as indicated by measured data at five gaging stations. The level of detail required for fine-scale spatial simulation made the use of both hard and soft data necessary in model calibration, alongside other model adaptations. Limitations to the model's predictive capacity were due to a paucity of data in the region at the NHDPlus scale rather than due to SWAT functionality. Results of treatment scenarios demonstrate variable effects of structural practices and nutrient management on sediment and nutrient loss dynamics. Targeting treatment to acres with critical outstanding conservation needs provides the largest return on investment in terms of nutrient loss reduction per dollar spent, relative to treating acres with lower inherent nutrient loss vulnerabilities. Importantly, this research raises considerations about use of models to guide land management decisions at very fine spatial scales. Decision makers using these results should be aware of data limitations that hinder fine-scale model interpretation.
Created: 12/14/2017 10:31 AM (ET)
Modified: 12/14/2017 10:31 AM (ET)
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