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A bootstrap method for estimating uncertainty of water quality trends

November 1, 2015

Estimation of the direction and magnitude of trends in surface water quality remains a problem of great scientific and practical interest. The Weighted Regressions on Time, Discharge, and Season (WRTDS) method was recently introduced as an exploratory data analysis tool to provide flexible and robust estimates of water quality trends. This paper enhances the WRTDS method through the introduction of the WRTDS Bootstrap Test (WBT), an extension of WRTDS that quantifies the uncertainty in WRTDS-estimates of water quality trends and offers various ways to visualize and communicate these uncertainties. Monte Carlo experiments are applied to estimate the Type I error probabilities for this method. WBT is compared to other water-quality trend-testing methods appropriate for data sets of one to three decades in length with sampling frequencies of 6–24 observations per year. The software to conduct the test is in the EGRETci R-package.

Citation Information

Publication Year 2015
Title A bootstrap method for estimating uncertainty of water quality trends
DOI 10.1016/j.envsoft.2015.07.017
Authors Robert M. Hirsch, Stacey A. Archfield, Laura A. DeCicco
Publication Type Article
Publication Subtype Journal Article
Series Title Environmental Modelling and Software
Index ID 70176528
Record Source USGS Publications Warehouse
USGS Organization National Research Program - Eastern Branch