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Sci Total Environ ; 569-570: 1265-1281, 2016 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-27387796


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 (SWAT) 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.

Environ Manage ; 33(4): 496-506, 2004 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-15453403


Agricultural lands have the potential to contribute to greenhouse gas mitigation by sequestering organic carbon within the soil. Credible and consistent estimates will be necessary to design programs and policies to encourage management practices that increase carbon sequestration. Because a nationwide survey of soil carbon by the wide range of natural resources and management conditions of the United States is prohibitively expensive, a simulation modeling approach must be used. The National Nutrient Loss Database (NNLD) is a modeling and database system designed and built jointly by the USDA- Natural Resources Conservation Service (NRCS) and Texas A&M University to provide science-based inferences on environmental impacts from changes in agricultural management practices and programs at the regional and national level. Currently, the NNLD simulates 16 crops and covers approximately 1.35 x 10(8) ha. For estimating soil carbon sequestration, the database will be populated with approximately 1.5 x 10(6) field-level model runs using the EPIC (Environmental Policy Impact Calculator) model, which includes newly incorporated carbon equations consistent with those in the Century model. Each run will represent a unique situation defined by state, crop, climate, soil, irrigation type, conservation practice, tillage system, and nutrient management treatment (nutrient rate, application frequency, application timing, and manure category). Results are to be assigned to specific National Resource Inventory points (NRI) to simulate regional and national baselines. In this article we present the modeling approach and discuss the strengths and limitations.

Agricultura , Carbono/análise , Bases de Dados Factuais , Efeito Estufa , Solo , Meio Ambiente , Fertilizantes , Previsões , Esterco , Medição de Risco , Estados Unidos