期刊
SCIENCE OF THE TOTAL ENVIRONMENT
卷 759, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.scitotenv.2020.143920
关键词
Soil and Water Assessment Tool (SWAT); Ensemble modeling; Calibration/validation; Nutrient loading; Field scale; Subsurface drainage
资金
- National Science Foundation Coastal SEES grant [OCE-1600012]
- Harmful Algal Bloom Research Initiative grant from the Ohio Department of Higher Education
- U.S. Department of Agriculture, Agricultural Research Service Soil Drainage Unit
Effective water quality models are needed to guide management and policy, and extend monitoring information. While models perform well at the watershed outlet, care should be taken when applying them upstream.
The need for effective water quality models to help guide management and policy, and extend monitoring information, is at the forefront of recent discussions related to watershed management. These models are often calibrated and validated at the basin outlet, which ensures that models are capable of evaluating basin scale hydrology and water quality. However, there is a need to understand where these models succeed or fail with respect to internal process representation, as these watershed-scale models are used to inform management practices and mitigation strategies upstream. We evaluated an ensemble of models-each calibrated to in stream observations at the basin outlet-against discharge and nutrient observations at the farm field scale to determine the extent to which these models capture field-scale dynamics. While all models performed well at the watershed outlet, upstream performance varied. Models tended to over-predict discharge through surface runoff and subsurface drainage, while under-predicting phosphorus loading through subsurface drainage and nitrogen loading through surface runoff. Our study suggests that while models may be applied to predict impacts of management at the basin scale, care should be taken in applying the models to evaluate field-scale management and processes in the absence of data that can be incorporated at that scale, even with the use of multiple models. (C) 2020 Elsevier B.V. All rights reserved.
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