Trend detection in hydrologic data: The Mann–Kendall trend test under the scaling hypothesis
By Khaled H. Hamed. 2008
1,350 citations recorded by the source corpus.
Subfields: Global and Planetary Change, Water Science and Technology
View Paper: https://www.semanticscholar.org/paper/8d54e12d518f05da1a9c297ae224e1898689364f
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In Global and Planetary Change
In Water Science and Technology
Citations in the corpus
- Trend analysis of water quality series based on regression models with correlated errors (2011, background): “Other recent interesting references 59 on this topic are Hamed (2008), who developed a new version of the Mann60 Kendall test designed to account for the effect of scaling, and Bouza-Deaño et 61 al. (2008), who analyzed the WQ trends in the Ebro river.”
- Comparative study of wavelet-ARIMA and wavelet-ANN models for temperature time series data in northeastern Bangladesh (2017, methodology): “K) test can be used to detect trends in time-series analyses (Hamed, 2008; Hamed and Rao, 1998; Yue et al., 2002; Yue and Wang, 2004; Shadmani et al., 2012).”
- Stationarity: Wanted Dead or Alive? 1 (2011, result): “The findings of Hamed (2008) are, perhaps, of greater relevance as he notes that LTP ‘‘may offer an explanation for inconsistencies in the results from several trend studies, known as ‘regional inconsistency,’ or ‘spatial nonuniformity,’ where neighboring stations may have significant, yet opposite…”
- The distribution of Kendall's tau for testing the significance of cross-correlation in persistent data (2011, methodology): “Previous studies have investigated the effect of autocorrelation on the variance of Kendall’s τ (Hamed 2009b) as well as the distribution of the MannKendall trend test statistic (Hamed 2008, 2009a), which is a special case of Kendall’s τ .”
- Re-evaluation of the Power of the Mann-Kendall Test for Detecting Monotonic Trends in Hydrometeorological Time Series (2020, methodology): “Two main approaches have been proposed to eliminate the influence of serial correlation, the first is applying pretreatment to the data, and the second is modifying the MK test to account for serial correlation (Hamed, 2008).”
- Assessment of drought trend and variability in India using wavelet transform (2020, methodology): “If there exists a positive (negative) autocorrelation in time-series, the variance is estimated less (more) than the actual value (Hamed and Rao 1998, Hamed 2008). To counter this effect, a modified MK test was given by Hamed and Rao (1998), in which the variance of the test was modified to take int”