Multivariate Analysis of Paired Watershed Data to Evaluate Agricultural Best Management Practice Effects on Stream Water Phosphorus

Abstract

Quantification of the effects of management programs on water quality is critical to agencies responsible for water resource protection. This research documents reductions in stream water phosphorus (P) loads resulting from agricultural best management practices (BMPs) implemented as part of an effort to control eutrophication of Cannonsville Reservoir, a drinking water supply for New York City. Dairy farms in the upstate New York reservoir basin were the target of BMPs designed to reduce P losses. A paired watershed study was established on one of these farms in 1993 to evaluate changes in P loading attributable to implementation of BMPs that included manure management, rotational grazing, and improved infrastructure. Intensive stream water monitoring provided data to calculate P loads from the 160‐ha farm watershed for all runoff events during a two‐year pre‐treatment period and a four‐year post‐treatment period. Statistical control for inter‐annual climatic variability was provided by matched P loads from a nearby 86‐ha forested watershed, and by several event flow variables measured at the farm. A sophisticated multivariate analysis of covariance (ANCOVA) provided estimates of both seasonal and overall load reductions. Statistical power and the minimum detectable treatment effect (MDTE) were also calculated. The results demonstrated overall event load reductions of 43% for total dissolved phosphorus (TDP) and 29% for particulate phosphorus (PP). Changes in farm management practices and physical infrastructure clearly produced decreases in event P losses measurable at the small watershed scale.