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In the present study, trends and variations in climatic variables (i.e. rainfall, wet day frequency, surface temperature, diurnal temperature, cloud cover, and reference and potential evapotranspiration) were analyzed on seasonal (monsoon and non-monsoon) and annual time scales for the Ajmer District of Rajasthan, India. This was done using non-parametric statistical techniques, i.e. the Mann–Kendall (MK) and Modified Mann–Kendall (MMK) tests, over a period of 100 years. The MK test with prewhitening (MK–PW) of climatic series was also applied to climatic variables and the results were compared to those obtained through the MK and MMK tests in order to assess the performance of trend detection methods. The Pettitt–Mann–Whitney (PMW) test was applied to detect the temporal shift in climatic series. The trend analysis revealed that annual and seasonal rainfall did not show any statistically significant trend at a 10% significant level. A noticeable trend increase was found in wet day frequency, surface temperature and reference evapotranspiration (ET) during the non-monsoon season from the three non-parametric statistical tests at a 10% significance level. A statistically significant decrease in maximum temperature was found during the non-monsoon season by the MK–PW test alone. This analysis of several climatic variables at the district scale is helpful for the planning and management of water resources and the development of adaptation strategies in adverse climatic conditions.

In the present study, an ArcSWAT model was utilized to simulate the hydrological responses due to land use and climatic changes in the Omo-Gibe river basin, Ethiopia. The performance of the model was evaluated through sensitivity, uncertainty analysis, calibration and validation. The most sensitive parameters were identified which are governing on surface runoff generation processes in the selected basin. The calibration and validation of the model was done using SWAT-2005. Also, the sensitivity and uncertainty analysis was performed using the SUFI-2 and SWAT-CUP algorithm. The model results revealed that a good performance during the calibration (R 2 = 72.4%, NSE = 62.6% and D = 14.37%) and validation (R 2 = 68.1%, NSE = 68% and D = 4.57%). SUFI-2 algorithm gave good results in minimizing the differences between observed and simulated flow in the Great Gibe sub-basin. The studies show that there is an overall increasing trend in future annual temperature and significant variation of monthly and seasonal precipitation from the base period 1985-2005. Also, the annual potential evapotranspiration shown increasing trend for future climate change scenarios. Similarly, the surface water decreases in terms of mean monthly discharge in the dry season and increases in the wet season. The percentage change in future seasonal and annual hydrological variables was shown increasing trends. Therefore, this study found that SWAT can be effectively used for assessing the water balance components of a river basin in Omo-Gibe basin, Ethiopia.