Trends in hydrological and climatic variables affected by four variations of the Mann-Kendall approach in Urmia Lake basin, Iran

Abstract

The trends in hydrological and climatic time series data of Urmia Lake basin in Iran were examined using the four different versions of the Mann-Kendall (MK) approach: (i) the original MK test; (ii) the MK test considering the effect of lag-1 autocorrelation; (iii) the MK test considering the effect of all autocorrelation or sample size; and (iv) the MK test considering the Hurst coefficient. Identification of hydrological and climatic data trends was carried out at monthly and annual time scales for 25 temperature, 35 precipitation and 35 streamflow gauging stations selected from the Urmia Lake basin. Mann-Kendall and Pearson tests were also applied to explore the relationships between temperature, precipitation and streamflow trends. The results show statistically significant upward and downward trends in the annual and monthly hydrological and climatic variables. The upward trends in temperature, unlike streamflow, are much more pronounced than the downward trends, but for precipitation the behaviour of trend is different on monthly and annual time scales. Furthermore, the trend results were affected by the different approaches. Specifically, the number of stations showing trends in hydrological and climatic variables decreased significantly (up to 50%) when the fourth test was considered instead of the first and the absolute value of the Z statistic for most of the time series was reduced. The results of correlations between streamflow and climatic variables showed that the streamflow in Urmia Lake basin is more sensitive to changes in temperature than those of precipitation. The observed decreases in streamflow and increases in temperature in the Urmia Lake basin in recent decades may thus have serious implications for water resources management under the warming climate with the expected population growth and increased freshwater consumption in this region.

Spatial distribution of secular trends in rainfall indices of Peninsular Malaysia in the presence of long‐term persistence

“…A number of recent studies have revealed the difference in trends obtained using the MK and MMK tests due to LTP (Kumar et al, ; Shahid et al, ; Fathian et al, ; Khan et al , 2018a). The large difference in the number of significant trends in rainfall indices obtained in this study using the MK and MMK tests indicates that the significant changes estimated by the MK test at many grid points in Peninsular Malaysia may be due to the lack of consideration of LTP in time series during trend analysis.…”

Reduced Runoff Due to Anthropogenic Intervention in the Loess Plateau, China

“…The rank-based non-parametric Mann-Kendall statistical test [38] is commonly used for trend detection due to its robustness for non-normally distributed data, hence it is frequently applied to hydro-climatic time series [39,40]. Assuming a normal distribution at the significant level of p = 0.05, a positive Mann-Kendall statistic Z larger than 1.96 indicates an significant increasing trend, whereas a negative Z lower than −1.96 indicates a significant decreasing trend.…”

OMI-measured increasing SO<sub>2</sub> emissions due to energy industry expansion and relocation in northwestern China

“…The MK test is a nonparametric statistical test (Mann, 1945;Kendall and Charles, 1975) that is useful for assessing the significance of trends in time series data (Waked et al, 2016;Fathian et al, 2016). The MK test is often used to detect a step change point in the long-term trend of a time series dataset (Moraes et al, 1998;Li et al, 2016;Zhao et al, 2015).…”