Analysis of long term meteorological trends in the middle and lower Indus Basin of Pakistan—A non-parametric statistical approach

Abstract

The Indus basin of Pakistan is vulnerable to climate change which would directly affect the livelihoods of poor people engaged in irrigated agriculture. The situation could be worse in middle and lower part of this basin which occupies 90% of the irrigated area. The objective of this research is to analyze the long term meteorological trends in the middle and lower parts of Indus basin of Pakistan. We used monthly data from 1971 to 2010 and applied non-parametric seasonal Kendal test for trend detection in combination with seasonal Kendall slope estimator to quantify the magnitude of trends. The meteorological parameters considered were mean maximum and mean minimum air temperature, and rainfall from 12 meteorological stations located in the study region. We examined the reliability and spatial integrity of data by mass-curve analysis and spatial correlation matrices, respectively. Analysis was performed for four seasons (spring—March to May, summer—June to August, fall—September to November and winter—December to February). The results show that max. temperature has an average increasing trend of magnitude + 0.16, + 0.03, 0.0 and + 0.04 °C/decade during all the four seasons, respectively. The average trend of min. temperature during the four seasons also increases with magnitude of + 0.29, + 0.12, + 0.36 and + 0.36 °C/decade, respectively. Persistence of the increasing trend is more pronounced in the min. temperature as compared to the max. temperature on annual basis. Analysis of rainfall data has not shown any noteworthy trend during winter, fall and on annual basis. However during spring and summer season, the rainfall trends vary from − 1.15 to + 0.93 and − 3.86 to + 2.46 mm/decade, respectively. It is further revealed that rainfall trends during all seasons are statistically non-significant. Overall the study area is under a significant warming trend with no changes in rainfall.