Abstract

Despite the widespread use of agricultural best management practices (BMPs) to reduce watershed scale nutrient loads, there remain few studies that use directly observed data – instead of models – to evaluate BMP effectiveness at the watershed scale. In this study, we make use of extensive ambient water quality data, stream biotic health data, and BMP implementation data within the New York State portion of the Chesapeake Bay watershed to assess the role of BMPs on reducing nutrient loads and modifying biotic health in major rivers. The specific BMPs considered were riparian buffers and nutrient management planning. A simple mass balance approach was used to evaluate the role of wastewater treatment plant nutrient reductions, agricultural land use changes, and these two agricultural BMPs in matching observed downward trends in nutrient load. In the Eastern nontidal network (NTN) catchment – where BMPs have been more widely reported – the mass balance model suggested a small but discernible contribution of BMPs in matching the observed downward trend in total phosphorus. Contrastingly, BMP implementations did not show clear contributions towards total nitrogen reductions in the Eastern NTN catchment nor for the total nitrogen and phosphorus in the Western NTN catchment, where BMP implementation data are more limited. Assessment of the relationship between stream biotic health and BMP implementation using regression models found limited connection between extent of BMP implementation and biotic health. In this case, however, spatiotemporal mismatches between the datasets and the relatively stable biotic health, typically of moderate to good quality even before BMP implementation, may reflect the need for better monitoring design to assess BMP effects at the subwatershed scale. Additional studies, perhaps using citizen scientists, may be able to provide more suitable data within the existing frameworks of the long-term surveys. Given the preponderance of studies that rely only on modeling to understand nutrient loading reductions achieved by implementation of BMPs, it is essential to continue to collect empirical data to meaningfully evaluate whether there are actual measurable changes due to BMPs.

Full Text
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