Technical Notes
Aug 30, 2018

Critical Values for Şen’s Trend Analysis

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Publication: Journal of Hydrologic Engineering
Volume 23, Issue 11

Abstract

Trends in measured hydrologic data can greatly influence projected values; therefore, trends need to be identified and quantitatively modeled. First, it is necessary to verify whether or not a trend actually exists in the sample data. Tests of significance are most often used to verify whether or not a trend is statistically significant. Şen provided an easy-to-apply method of identifying the presence of trends in time series, but did not provide a quantitative method of verifying the statistical likelihood of an assumed trend in a measured time series [Şen, Z. 2012. “Innovative trend analysis methodology.” J. Hydrol. Eng. 17 (9): 1042–1046]. A method of quantifying Şen’s approach is developed herein, with critical values of the test statistic developed to provide a means of making objective decisions. Critical values are presented for rejection probabilities from 10% to 0.1%. The power of the test, which is similar to that of other trend tests, is also approximated; analyses indicate powers from 10% to 30% for small samples.

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References

Dempsey, C. R. 1968. The effects of geographic and climatic setting on the economic advantages of alternative flood control measures. Lexington, KY: Univ. of Kentucky.
McCuen, R. H., and L. D. James. 1972. “Nonparametric statistical methods in urban hydrologic research.” Water Resour. Bull. 8 (5): 965–975. https://doi.org/10.1111/j.1752-1688.1972.tb05984.x.
Şen, Z. 2012. “Innovative trend analysis methodology.” J. Hydrol. Eng. 17 (9): 1042–1046. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000556.

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Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 23Issue 11November 2018

History

Received: Jan 29, 2018
Accepted: Jun 14, 2018
Published online: Aug 30, 2018
Published in print: Nov 1, 2018
Discussion open until: Jan 30, 2019

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Richard H. McCuen [email protected]
Ben Dyer Professor, Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park, MD 20742-3021. Email: [email protected]

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