Precipitation Trend Assessment along the China Pakistan Economic Corridor (CPEC) Route in Baluchistan, Pakistan: Insights from Individual and Regional Perspectives

The present study highlights Trend Assessment along the China Pakistan Economic Corridor (CPEC) Route in Baluchistan, Pakistan. CPEC Corridor upon construction is expected to revolutionize the infrastructure, economy, trade, finance, demography, environment, culture, and socio-economic conditions, of Pakistan. Many of the western and central CPEC routes pass through it. However, Baluchistan, due to its topography and rugged terrain, is under constant risk of rainfall-driven flash floods. Flash floods are responsible for colossal damage to the infrastructure, especially roads, bridges, trade, and communication that ultimately badly affect humans, economy, and the environment. The intensity and frequency of rainfall are increasing due to climate change and flash floods put everything at high risk. In this view, the assessment of changes in rainfall has got significant importance. More or less no appreciable studies have been conducted on the precipitation trend analysis and in Baluchistan. This research is focused on assessment of trend analysis in precipitation of Baluchistan using 40 years (1977-2016) data from 13 stations in Baluchistan. The analysis and results can be employed as input for infrastructure planning of the area, which is going to be the financial hub of the country. The data has been obtained from the Pakistan Meteorological Department (PMD). Precipitation data sample is checked for normal distribution, abrupt changes, cycles, outliers and missing values. Normal distribution of precipitation data set is done by conducting tests for normality like the Shapiro-Wilk W test, Anderson–Darling, Lilliefors, and Jarque–Bera test. Statistical tests, being the most direct methods of detecting changes in extreme rainfall intensities, were adopted. Trend analysis is performed using non-parametric tests, specifically the Mann-Kendall (MK) and Spearman’s rho (SR) tests, at 5% and 10% significance levels for monthly rainfall time series data on an annual, monthly, and seasonal basis. The Theil and Sen’s (TSA) slope approach is employed to quantify the slope trend. Additionally, the seasonal and regional MK tests have also been applied to test the seasonal and regional trends. The findings of MK and SR tests for the annual time series on individual stations at the local level indicate that the number of statistically significant negative trends exceeds the statistically significant positive trends, suggesting a decreasing trend in rainfall. Similar trends are observed when applying the MK test to monthly and seasonal time series, corroborating the findings of the MK tests on annual rainfall time series at individual stations. Furthermore, the outcomes of the regional analysis consistently demonstrate significant negative trends, underscoring a prevalent and widespread decrease in rainfall across all four regions.