Effect of Short-Term and Long-Term Persistence on Identification of Temporal Trends

In this study, the trends in precipitation in the northwest (NW) of Iran were identified using the four different versions of the Mann-Kendall method, i.e., the conventional Mann-Kendall method (MK1); the Mann-Kendall method following the removal of the effect of significant lag-1 autocorrelation (MK2); the Mann-Kendall method after the removal of the effect of all significant autocorrelation coefficients (MK3); and the Mann-Kendall method by considering the Hurst coefficient (MK4). Identification of trends was carried out on different time scales (monthly, seasonal, and annual) using the precipitation data of 50 years from 1955 to 2004 of the sixteen stations selected from the NW region of Iran. The Theil-Sen method was used to estimate the slopes of trend lines of precipitation series. Results showed that: (1) on a monthly time scale, the statistically significant Z-statistics were negative for all but one (July) month; and the strongest negative (positive) precipitation trend-line slope among all the negative (positive) cases was found to be −0.89ð0.38Þ mm=year at Bijar (Kermanshah) station in NW Iran; (2) on a seasonal time scale, the median of trend-line slopes was found to be negative in all four seasons; the winter and spring season's precipitation series witnessed negative trends for almost all the stations using all four different versions of the MK test; and in the summer and autumn seasons, both upward and downward trends were observed for most of the sites of NW Iran; (3) in an annual time scale, all stations had witnessed negative trends using both the MK1 and the MK4 tests. However, application of the MK4 instead of the MK1 reduced the absolute value of the Z-statistic for most of the time series. The strongest negative annual trend-line slope was −4.04 mm=year at Bijar station. Therefore, the observed decreases in precipitation in NW Iran in the recent half of the past century may have serious implications for water resources management under the warming climate with probably a higher rate of the population growth and the higher consumption of freshwater as a result of the rise in standards of living of the population of NW Iran. DOI: 10.1061/(ASCE)HE.1943-5584.0000819. © 2014 American Society of Civil Engineers.

[1]  Demetris Koutsoyiannis,et al.  Statistical analysis of hydroclimatic time series: Uncertainty and insights , 2007 .

[2]  Ali Sarhadi,et al.  Rainfall trends analysis of Iran in the last half of the twentieth century , 2009 .

[3]  M. Kendall,et al.  Rank Correlation Methods , 1949 .

[4]  N. Muttil,et al.  Rainfall trend and its implications for water resource management within the Yarra River catchment, Australia , 2013 .

[5]  Leonard M. Lye,et al.  Long-term dependence in annual peak flows of Canadian rivers , 1994 .

[6]  M. Kendall Rank Correlation Methods , 1949 .

[7]  Jurgen D. Garbrecht,et al.  Trends in Precipitation, Streamflow, and Evapotranspiration in the Great Plains of the United States , 2004 .

[8]  Sheng Yue,et al.  Applicability of prewhitening to eliminate the influence of serial correlation on the Mann‐Kendall test , 2002 .

[9]  A Al Tabbaa,et al.  Trends in seasonal precipitation extremes – an indicator of 'climate change' , 2008 .

[10]  M. Bayazit,et al.  The Power of Statistical Tests for Trend Detection , 2003 .

[11]  S. Yue,et al.  Power of the Mann–Kendall and Spearman's rho tests for detecting monotonic trends in hydrological series , 2002 .

[12]  P. Sen Estimates of the Regression Coefficient Based on Kendall's Tau , 1968 .

[13]  H. B. Mann Nonparametric Tests Against Trend , 1945 .

[14]  A. Stohl,et al.  Forest climatology: estimation of missing values for Bavaria, Germany , 1999 .

[15]  H. Theil A Rank-Invariant Method of Linear and Polynomial Regression Analysis , 1992 .

[16]  Vijay P. Singh,et al.  Variability and Trend in Seasonal Precipitation in the Continental United States , 2013 .

[17]  H. Tabari,et al.  Temporal variability of precipitation over Iran: 1966-2005 , 2011 .

[18]  Sanjiv Kumar,et al.  Streamflow trends in Indiana: Effects of long term persistence, precipitation and subsurface drains , 2009 .

[19]  Khaled H. Hamed,et al.  A modified Mann-Kendall trend test for autocorrelated data , 1998 .

[20]  Demetris Koutsoyiannis,et al.  Climate change, the Hurst phenomenon, and hydrological statistics , 2003 .

[21]  Khaled H. Hamed Trend detection in hydrologic data: The Mann–Kendall trend test under the scaling hypothesis , 2008 .