|Yen, Haw - Texas Agrilife Research|
|Keitzer, S. Conor - The Ohio State University|
|Johnson, Mari-vaughn - Natural Resources Conservation Service (NRCS, USDA)|
|Atwood, Jay - Natural Resources Conservation Service (NRCS, USDA)|
|Daggupati, Prasad - University Of Guelph|
|Herbert, Matthew - Nature Conservancy|
|Sowa, Scott - Nature Conservancy|
|Ludsin, Stuart - The Ohio State University|
|Robertson, Dale - Us Geological Survey (USGS)|
|Srinivasan, Raghavan - Texas A&M University|
|Rewa, Charles - Natural Resources Conservation Service (NRCS, USDA)|
Submitted to: Science of the Total Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/25/2016
Publication Date: 7/5/2016
Citation: Yen, H., White, M.J., Arnold, J.G., Keitzer, S., Johnson, M.V., Atwood, J.D., Daggupati, P., Herbert, M.E., Sowa, S.P., Ludsin, S.A., Robertson, D.M., Srinivasan, R., Rewa, C.A. 2016. Western Lake Erie Basin: Soft-data-constrained, NHDPlus resolution watershed modeling and exploration of applicable conservation scenarios. Science of the Total Environment. 569-570:1265-1281.
Interpretive Summary: Excessive amounts of nitrogen and phosphorus entering Western Lake Erie are causing harmful algal blooms, making drinking water unsafe for people in Toledo and surrounding areas. In the Western Lake Erie drainage basin, hydrologic models have been used to determine the impact of land management on nutrient loading to the lake. In this study, the Soil and Water Assessment Tool (SWAT2012) was utilized to model the entire Western Lake Erie basin at an extremely fine spatial resolution. We chose to model every square mile of landscape and every mile of stream channel. Modeled stream flow, sediment, nitrogen and phosphorus loads compared closely to monitored data at five stream gage locations. Several land management scenarios were simulated by the model to determine the effects of nutrient management and structural practices on loadings of nutrients into Lake Erie. Results of the management scenarios showed which practices were successful in lowering lake nutrient loads to acceptable levels and determined the optimum location of practices on the landscape. Targeting management to areas with severe conservation needs provided the optimum load reduction per dollar spent. Results from this study provide a framework for decision makers to determine management options for reducing nutrient loads into Western Lake Erie to acceptable levels. Results also showed the benefits to policy makers of modeling the basin in fine spatial detail.
Technical Abstract: Complex 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.