Trend Analysis of Climate Variables and Extremes Over Maner River Basin, India

Long-term trend analysis of meteorological variables is required for implementing any hydrological model or a basin. Spatio-temporal variations in precipitation and temperature of a basin are helpful for meteorologists, agriculturists, and policymakers to make appropriate decisions. It is necessary to understand the changes in rainfall characteristics using gridded precipitation data and robust statistical analysis for making decisions. In this study, the long-term trend of climate variables, i.e., precipitation, temperature over the Maner basin is studied during 1951-2020 at seasonal and annual timesteps. The non-parametric statistical methods of Mann-Kendall (MK) tests was performed using IMD daily gridded (0.25 x 0.25) data for 70 years. The magnitudes in the rainfall, temperature, and their extremes (CDD, CWD, PRCPTOT, R10, R20, R95, RX1DAY, RX5DAY, TNN, TNX, TXN, and TXX) are analyzed using Sen's slope method. The increase trend was noticed at the upper and lower Maner basins successively during the winter and pre-monsoon seasons. At the upper Maner basin, a decline in monsoon precipitation is visible. In terms of annual precipitation and post-monsoon, no significant trend was found. In the Maner basin, there was an upward trend in both the maximum and minimum annual temperature trends. According to an analysis of extreme indices, the annual total rainfall days (wet days) (R95PTOT) were on the rise across the basin, despite the fact that the consecutive wet days (CWD) and dry days (CDD) showed a decreasing trend. While the extreme indices for minimum and maximum temperatures (TNX and TNN) showed no discernible trend, respectively. The TXX and TXN of maximum temperature indices showed an increasing trend. These increasing trends in wet days and extreme temperatures in the Maner basin may be majorly attributed to changes in urbanization in the city of Karimnagar and land use changes in the basin. These all changes experience changes in precipitation patterns, which could have implications for water availability and management in the region.