Journal ArticleDOI
The Mann-Kendall test modified by effective sample size to detect trend in serially correlated hydrological series
Sheng Yue,ChunYuan Wang +1 more
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TLDR
In this paper, effective sample size (ESS) has been proposed to modify the nonparametric Mann-Kendall (MK) statistical test to assess the significance of trend in hydrological time series.Abstract:
The non-parametric Mann-Kendall (MK) statistical test has been popularly used to assess the significance of trend in hydrological time series The test requires sample data to be serially independent When sample data are serially correlated, the presence of serial correlation in time series will affect the ability of the test to correctly assess the significance of trend To eliminate the effect of serial correlation on the MK test, effective sample size (ESS) has been proposed to modify the MK statistic This study investigates the ability of ESS to eliminate the influence of serial correlation on the MK test by Monte Carlo simulation Simulation demonstrates that when no trend exists within time series, ESS can effectively limit the effect of serial correlation on the MK test When trend exists within time series, the existence of trend will contaminate the estimate of the magnitude of sample serial correlation, and ESS computed from the contaminated serial correlation cannot properly eliminate the effect of serial correlation on the MK test However, if ESS is computed from the sample serial correlation that is estimated from the detrended series, ESS can still effectively reduce the influence of serial correlation on the MK testread more
Citations
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The Millennium Drought in southeast Australia (2001–2009): Natural and human causes and implications for water resources, ecosystems, economy, and society
Albert van Dijk,Hylke E. Beck,Russell Crosbie,Richard de Jeu,Yi Y. Liu,Yi Y. Liu,Geoff Podger,Bertrand Timbal,Neil R. Viney +8 more
TL;DR: In this article, the authors used climate, water, economic, and remote sensing data combined with biophysical modeling to understand the drivers of the "Millennium Drought" and its impacts.
Journal ArticleDOI
Trend detection in hydrologic data: The Mann–Kendall trend test under the scaling hypothesis
TL;DR: In this article, the Mann-Kendall test is modified to account for the effect of scaling in hydrologic data, and the results show a considerable reduction in the number of stations with significant trends when the effects of scaling are taken into account.
Journal ArticleDOI
Review of trend detection methods and their application to detect temperature changes in India
P. Sonali,D. Nagesh Kumar +1 more
TL;DR: In this article, the spatial and temporal trend analysis of annual, monthly and seasonal maximum and minimum temperatures (t(max), t(min)) in India has been performed for three time slots: 1901-2003,1948-2003 and 1970-2003.
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Stream flow in Minnesota : Indicator of climate change
Eric V. Novotny,Heinz G. Stefan +1 more
TL;DR: In this article, the Mann-Kendal nonparametric test was used to detect significant trends over time windows from 90 to 10 years in combination with the Trend Free Pre-Whitening (TFPW) method for correcting time series data for serial correlation.
Journal ArticleDOI
Temporal variability of precipitation over Iran: 1966-2005
TL;DR: In this paper, the authors analyzed the annual and seasonal precipitation trends of 41 stations in Iran for the period 1966-2005 using the Mann-Kendall test, the Sen's slope estimator and the linear regression.
References
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Journal ArticleDOI
Estimates of the Regression Coefficient Based on Kendall's Tau
TL;DR: In this article, a simple and robust estimator of regression coefficient β based on Kendall's rank correlation tau is studied, where the point estimator is the median of the set of slopes (Yj - Yi )/(tj-ti ) joining pairs of points with ti ≠ ti.
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Techniques of trend analysis for monthly water quality data
TL;DR: The seasonal Kendall test as discussed by the authors is a nonparametric test for trend applicable to data sets with seasonality, missing values, or values reported as "less than" or values below the limit of detection.
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A modified Mann-Kendall trend test for autocorrelated data
TL;DR: In this paper, the effect of autocorrelation on the variance of the Mann-Kendall trend test statistic is discussed, and a modified non-parametric trend test is proposed.