EvaluatingFuture Climate Projections in Upper Indus Basin through GFDL-ESM2M Model

This study aimsto examine the future climate projections in the Upper Indus Basin (UIB). The Global Climate Model (GFDL-ESM2M) data was utilized to analyze two variables, namely precipitation and temperatures. The study focused on three distinct time periods: near century (2020-2040), mid-century (2041-2070), and end of century (2071-2099). This process involved the utilization of a downscaling technique that relied on the RCP4.5 scenario. The Mann-Kendall (MK)and Sen's slope estimate test will be employed to analyze the parameters of temperature and precipitation, enabling the identification of yearly, seasonal, and monthly patterns. The application of the MKand Sen's slope estimate approaches revealed a lack of statistical significance in the observed upward trend in yearly precipitation and temperature. Over the course of nearly a century, the average Coefficient of Variation for temperature exhibited a range of -67.5% to 308.9%. During the midcentury period, there was observed variation in the mean monthly rainfall across all months. Notably, the month of March exhibited the highest average rainfall of 274.2mm, while September had the lowest average rainfall of 31.9mm. The data exhibited a positive skewness, suggesting that there was a tendency for higher levels of rainfall towards the end of each month compared to the beginning. The data indicates that there is an upward trend in precipitation throughout the midcentury period in comparison to the near century, but a downward trend is observed towards the conclusion ofthe century. The temperature readings exhibit a constant upward trend from the early part of the century to the middle of the century, followed by a subsequent increase from the middle of the century to the end of the century. Furthermore, the data revealedthat the highest amount of precipitation is experienced during the spring season, whereas the lowest amount of rainfall is recorded during autumn throughout all temporal intervals.