Trend in Extreme Precipitation Indices Based on Long Term In Situ Precipitation Records over Pakistan

Abstract

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.

Spatial Distribution and Environmental Significance of Phosphorus Fractions in River Sediments and Its Influencing Factor from Hongze and Tiaoxi Watersheds, Eastern China

“…Rising human-induced operation coupled with current land use will enhance pollutant loads, such as nutrients and microbes, into water sources, which can threaten human health [ 52 ] and rainfall events [ 53 ]. This may further increase the loading of contaminants due to the emergence of runoff from both agricultural and residential areas as a result of livelihood activities, including the use of compost as fertilizer and animal grazing at river banks [ 54 ].…”

Intraseasonal Precipitation Variability over West Africa under 1.5 °C and 2.0 °C Global Warming Scenarios: Results from CORDEX RCMs

“…The three categories are (i) the mean and strong intensity indices; (ii) occurrence indices; and (iii) duration indices, herein represented by (a) simple precipitation intensity index (SDII); (b) R1mm, R10mm, and R30mm; and (c) CWD, respectively. The indices have been widely used to study precipitation over West Africa [10,50] and beyond [47,51,52]. The other two descriptors are the annual (ANN) and seasonal (JJAS) daily mean precipitation.…”

Spatial Distribution and Environmental Significance of Phosphorus Fractions in River Sediments and Its Influencing Factor from Hongze and Tiaoxi Watersheds, Eastern China

“…Rising human induced operation coupled with current land use will enhance pollutant loads, such as nutrients and microbes, into water sources which can threaten human health [47], whereas rainfall events [48]. This may further increase the loading of contaminants due to the emergence of runoff from both agricultural and residential areas as a result of livelihood activities, including the use of compost as fertilizer and animal grazing at river banks [49].…”