## 3 Results and Discussion
### Climate Change Scenarios  
Mann-Kendall's test results show an increasing trend in the mean monthly temperature and a decreasing trend in the monthly total precipitation. The positive value of \(S\) (1975) indicates an upward trend for monthly mean temperature. The positive _tau_ value (0.017) denotes a positive correlation between time and temperature (Figure 7). On the other hand, the negative value of \(S\) (\(-\)17169) indicates a downward trend for monthly total precipitation, whereas the negative value of tau (\(-\)0.156) suggests a negative correlation between time and precipitation. \(p\)-values for monthly temperature and precipitation were found smaller than the alpha value (0.050), rejecting the null hypothesis H0 in favor of hypothesis H1. The acceptance of hypothesis H1 is even substantiated by the trend in temperature and precipitation time-series data. Conversely, [PERSON]'s time series analysis for seasonal temperature rejected the null hypothesis H0 for all seasons (Table 2). The increase in minimum temperature indices was found superior to 2 \({}^{\circ}\)C over the past 40 years. This result is consistent with the work of [55] that conducted research on extreme temperature indices in Pakistan and found that the increase in mean minimum temperature in Punjab province was about 1.9 \({}^{\circ}\)C over the past 54 years. However, the increment in maximum temperature indices was less significant than that of minimum temperature since a relatively slight variation was observed. After the 2000s, 2010 was the warmest year, with a maximum temperature of 50 \({}^{\circ}\)C around the end of May. In the late 1990s, precipitation reduced to its minimum (83 mm/year) over the previous four decades, \begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline \multicolumn{6}{c}{**Seasonal Mean for Max Temperature (\({}^{\circ}\)C)**} & \multicolumn{6}{c}{**Mann–Kendall’s Test Results**} \\ \hline
**Season** & **Minimum** & **Maximum** & **Mean** & **Std. Deviation** & **Kendall’s _Tun_ & \(S\) & \(p\)-Value** & **Alpha** & **Interpretation** \\ \hline Summer & 37.50 & 41.10 & 39.521 & 0.788 & \(-\)0.328 & \(-\)242.000 & 0.004 & 0.050 & Reject H0 \\ Winter & 20.66 & 23.96 & 22.174 & 0.868 & \(-\)0.263 & \(-\)193.000 & 0.020 & 0.050 & Reject H0 \\ Spring & 32.13 & 38.20 & 35.135 & 1.577 & 0.130 & 96.000 & 0.040 & 0.050 & Reject H0 \\ Autumn & 30.46 & 34.46 & 33.091 & 0.786 & \(-\)0.301 & \(-\)222.000 & 0.007 & 0.050 & Reject H0 \\ \multicolumn{6}{c}{Seasonal total precipitation (mm)} & \multicolumn{6}{c}{Mann–Kendall’s test results} \\ Summer & 3.200 & 277.400 & 106.266 & 63.816 & 0.069 & 51.000 & 0.545 & 0.050 & Accept H0 \\ Winter & 0.000 & 115.000 & 29.405 & 27.649 & 0.011 & 8.000 & 0.933 & 0.050 & Accept H0 \\ Spring & 0.600 & 125.600 & 46.608 & 28.999 & \(-\)0.050 & \(-\)37.000 & 0.663 & 0.050 & Accept H0 \\ Autumn & 0.000 & 214.700 & 33.172 & 49.709 & 0.126 & 93.000 & 0.266 & 0.050 & Accept H0 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary statistics for seasonal temperature and precipitation along with Mann–Kendall’s test results. Figure 7: Climograph along with Mann–Kendall’s test results showing trends for monthly average temperature and monthly total precipitation. and droughts occurred in the region. Moreover, a decrease in air humidity and increased wind speed was observed. Predicted Temperature and Precipitation  
The analysis of GCM predictors reveals an increase in rainfall from March to June and a decline from July to February. The spring season (March-May) shows high precipitation for all three-time scenarios as compared with the other three seasons (winter, summer, and autumn). The predicted maximum monthly rainfall was found to vary between 20.42 and 31.50 mm. Although monthly variations differed from one-time scenario to another, the 2080s scenario was found dominant in monthly mean rainfall in March, April, June, July, October, and November. As depicted in Figure 8, the months of April and May 2060s show maximum precipitation.