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Evaluation of the effectiveness of conservation practices under implementation site uncertainty

机译:在实施地点不确定的情况下评估保护措施的有效性

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摘要

Agricultural nonpoint source pollution is the leading source of water quality degradation in United States, which has led to the development of programs that aim to mitigate this pollution. One common approach to mitigating nonpoint source pollution is the use of best management practices (BMPs). However, it can be challenging to evaluate the effectiveness of implemented BMPs due to polices that limit data sharing. In this study, the uncertainty introduced by data sharing limitations is quantified through the use of a watershed model. Results indicated that BMP implementation improved the overall water quality in the region (up to - 15% pollution reduction) and that increasing the area of BMP implementation resulted in higher pollution reduction. However, the model outputs also indicated that uncertainty caused by data sharing limitations resulted in variabilities ranging from -160% to 140%. This shows the importance of data sharing among agencies to better guide current and future conservation programs.
机译:农业面源污染是美国水质下降的主要原因,这导致制定了旨在减轻这种污染的计划。减轻面源污染的一种常用方法是使用最佳管理规范(BMP)。但是,由于政策限制了数据共享,因此评估已实施的BMP的有效性可能具有挑战性。在这项研究中,通过使用分水岭模型来量化由数据共享限制引起的不确定性。结果表明,实施BMP改善了该地区的总体水质(减少了-15%的污染),而BMP实施面积的增加导致了更高的污染减少。但是,模型输出还表明,由于数据共享限制而导致的不确定性导致变化范围为-160%至140%。这表明了在机构之间共享数据以更好地指导当前和将来的保护计划的重要性。

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