Statistical Techniques for Assessing water‐quality effects of BMPs

Journal of Irrigation and Drainage Engineering
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Abstract

Little has been published on the effectiveness of various management practices in small rural lakes and streams at the watershed scale. In this study, statistical techniques were used to test for changes in water‐quality data from watersheds where best management practices (BMPs) were implemented. Reductions in data variability due to climate and seasonality were accomplished through the use of regression methods. This study discusses the merits of using storm‐mass‐transport data as a means of improving the ability to detect BMP effects on stream‐water quality. Statistical techniques were applied to suspended‐sediment records from three rural watersheds in Illinois for the period 1981–84. None of the techniques identified changes in suspended sediment, primarily because of the small degree of BMP implementation and because of potential errors introduced through the estimation of storm‐mass transport. 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.


Read More: http://ascelibrary.org/doi/abs/10.1061/(ASCE)0733-9437(1994)120:2(334)

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Statistical Techniques for Assessing water‐quality effects of BMPs
Series title Journal of Irrigation and Drainage Engineering
DOI 10.1061/(ASCE)0733-9437(1994)120:2(334)
Volume 120
Issue 2
Year Published 1994
Language English
Publisher American Society of Civil Engineers
Description 4 p.
First page 334
Last page 337
Online Only (Y/N) N
Additional Online Files (Y/N) N
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