A bootstrap method for estimating uncertainty of water quality trends
A bootstrap method for estimating uncertainty of water quality trends
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DOI：
10.1016/j.envsoft.2015.07.017
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发表时间：
2015-11-01
影响因子：
4.9
通讯作者：
De Cicco, Laura A.
中科院分区：
文献类型：
--
作者：
Hirsch, Robert M.;Archfield, Stacey A.;De Cicco, Laura A.
估计地表水质量趋势的方向和幅度仍然是一个具有重大科学和实际意义的问题。时间、流量和季节的加权回归（WRTDS）方法最近被引入，作为一种探索性的数据分析工具，以提供灵活和可靠的水质趋势估计。本文通过引入WRTDS Bootstrap测试（WBT），WRTDS的扩展，量化了WRTDS水质趋势估计的不确定性，并提供了各种方式来可视化和传达这些不确定性，从而增强了WRTDS方法。蒙特卡洛实验应用于估计该方法的I类错误概率。WBT相比，其他水质趋势测试方法适合于数据集的一至三十年的长度与采样频率为每年6-24观察。执行测试的软件在EGRETci R包中。爱思唯尔有限公司出版
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. Published by Elsevier Ltd.