Spatiotemporal Dynamics of Precipitation in Southwest Arid-Agriculture Zones of Pakistan

Muhammad Waseem, Ijaz Ahmad, Ahmad Mujtaba, Muhammad Tayyab, Chen Si, Haishen Lü and Xiaohua Dong
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Muhammad Waseem: Centre of Excellence in Water Resources Engineering, University of Engineering and Technology, Lahore 54890, Pakistan
Ijaz Ahmad: Centre of Excellence in Water Resources Engineering, University of Engineering and Technology, Lahore 54890, Pakistan
Ahmad Mujtaba: Centre of Excellence in Water Resources Engineering, University of Engineering and Technology, Lahore 54890, Pakistan
Muhammad Tayyab: College of Hydraulic and Environmental Engineering, China Three Gorges University, Yichang 443002, China
Chen Si: Hubei Key Laboratory of Regional Development and Environmental Response, Wuhan 430062, China
Haishen Lü: State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
Xiaohua Dong: College of Hydraulic and Environmental Engineering, China Three Gorges University, Yichang 443002, China

Sustainability, 2020, vol. 12, issue 6, 1-18

Abstract: Investigation of spatiotemporal precipitation trends from a climate change perspective is essential, especially in those regions with rainfed agriculture in order to propose sustainable adaptation schemes. Some restrictive assumptions may hinder the efficacy of trend detection methods, so it could be supported with variability analysis to have a clear picture of the spatiotemporal precipitation dynamics rather than focusing on a single approach. Hence, in the current study, a spatiotemporal dynamic analysis of precipitation was carried out using trend detection methods (the innovative trend analysis method and Mann–Kendall test) and statistical indices (the consecutive disparity index, entropy-based variability index and absolute inter-variability index) in the southwest arid region of Pakistan. The results indicated that based on the monthly, annual and seasonal time series, no systematic precipitation pattern was observed across the whole study region. However, on average, an increasing trend was observed in the east plateau while decreasing in the west plateau. The variability analysis also signposted the higher variability in the case of the western plateau and coastal area compared to the east plateau. Based on the seasonal analysis, it was concluded that, on average, precipitation in the winter and spring season goes on decreasing with higher variability while a mixture of increasing and decreasing trends resulted for summer and autumn. Conclusively the study found that precipitation in the study area is more erratic and its behaviour abruptly changed over a short distance. Moreover, discrepancies and inconstancies were found in the selected trend detection approaches and variability indices. The results also indicated that climate change is going to seriously affect the region as a decreasing trend prevails in most of the cases and stations.

Keywords: innovative trend analysis; variability indices; precipitation; arid region (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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