期刊
WATER
卷 12, 期 3, 页码 -出版社
MDPI
DOI: 10.3390/w12030797
关键词
extreme precipitation indices; Pakistan; Mann-Kendall; Sen's slope estimator
资金
- National Natural Science Foundation of China [41875094]
- National Key Research and Development Program of China [2017YFA0603701]
- Sino-German Cooperation Group Project [GZ1447]
Assessing the long-term precipitation changes is of utmost importance for understanding the impact of climate change. This study investigated the variability of extreme precipitation events over Pakistan on the basis of daily precipitation data from 51 weather stations from 1980-2016. The non-parametric Mann-Kendall, Sen's slope estimator, least squares method, and two-tailed simple t-test methods were used to assess the trend in eight precipitation extreme indices. These indices were wet days (R1 >= 1 mm), heavy precipitation days (R10 >= 10 mm), very heavy precipitation days (R20 >= 20 mm), severe precipitation (R50 >= 50 mm), very wet days (R95p) defining daily precipitation >= 95 percentile, extremely wet days (R99p) defining daily precipitation >= 99 percentile, annual total precipitation in wet days (PRCPTOT), and mean precipitation amount on wet days as simple daily intensity index (SDII). The study is unique in terms of using high stations' density, extended temporal coverage, advanced statistical techniques, and additional extreme indices. Furthermore, this study is the first of its kind to detect abrupt changes in the temporal trend of precipitation extremes over Pakistan. The results showed that the spatial distribution of trends in different precipitation extreme indices over the study region increased as a whole; however, the monsoon and westerlies humid regions experienced a decreasing trend of extreme precipitation indices during the study period. The results of the sequential Mann-Kendall (SqMK) test showed that all precipitation extremes exhibited abrupt dynamic changes in temporal trend during the study period; however, the most frequent mutation points with increasing tendency were observed during 2011 and onward. The results further illustrated that the linear trend of all extreme indices showed an increasing tendency from 1980- 2016. Similarly, for elevation, most of the precipitation extremes showed an inverse relationship, suggesting a decrease of precipitation along the latitudinal extent of the country. The spatiotemporal variations in precipitation extremes give a possible indication of the ongoing phenomena of climate change and variability that modified the precipitation regime of Pakistan. On the basis of the current findings, the study recommends that future studies focus on underlying physical and natural drivers of precipitation variability over the study region.
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