STATISTICAL TECHNIQUES FOR ASSESSING WATER-QUALITY EFFECTS OF BMPS

Little has been published on the effectiveness of various management p ractices in small rural lakes and streams at the watershed scale. In t his study, statistical techniques were used to test for changes in wat er-quality data from watersheds where best management practices (BMPs) were implemented. Reductions in data variability due to climate and s easonality were accomplished through the use of regression methods. Th is study discusses the merits of using storm-mass-transport data as a means of improving the ability to detect BMP effects on stream-water q uality. Statistical techniques were applied to suspended-sediment reco rds from three rural watersheds in Illinois for the period 1981-84. No ne of the techniques identified changes in suspended sediment, primari ly because of the small degree of BMP implementation and because of po tential errors introduced through the estimation of storm-mass transpo rt. A Monte Carlo sensitivity analysis was used to determine the level of discrete change that could be detected for each watershed. In all cases, the use of regressions improved the ability to detect trends.