This study evaluates the ability of 21 Regional Climate Models (RCMs) from the Coordinated Regional Climate Downscaling Experiment (CORDEX) in simulating climate extremes in the fast growing Asian cities which are highly vulnerable to climate change. The three Asian cities have two different climate characteristics, namely Bangkok and its vicinity and Ho Chi Minh City in tropical climate region and Kathmandu in sub-tropical and tem-perate climate region. The RCMs were evaluated to simulate the six climate indices; Consecutive Dry Days (CDD), Simple Daily Intensity Index (SDII), Number of extremely heavy precipitation days (R50mm), Maximum 1-day precipitation amount (RX1day), Mean of daily maximum temperature (TX mean) and Mean of daily minimum temperature (TN mean). The performance indicators used were correlation coefficient, normalized root mean square deviation, absolute normalized root mean square deviation and average absolute relative deviation. The Entropy method was endorsed to acquire weights of these four indicators and weightage average techniques were used for ranking of 21 RCMs. The result demonstrated that the best model for one climate index is not the same best model for other climate indices. The 3 RCMs; WAS44_SMHI_RCA4_IPSL_CM5A_MR, WAS44_SMHI_RCA4_MIROC5, and WAS44_IITM_REGCM4-4_CSIRO_MK3-6-0 are the best performing RCMs for simulating future climate extremes in Bangkok and

Groundwater resources of Kathmandu Valley in Nepal are under immense pressure from multiple stresses, including climate change. Due to over-extraction, groundwater resources are depleting, leading to social, environmental, and economic problems. Climate change might add additional pressure by altering groundwater recharge rates and availability of groundwater. Mapping groundwater resilience to climate change can aid in understanding the dynamics of groundwater systems, facilitating the development of strategies for sustainable groundwater management. Therefore, this study aims to analyze the impact of climate change on groundwater resources and mapping the groundwater resiliency of Kathmandu Valley under different climate change scenarios. The future climate projected using the climate data of RCM’s namely ACCESS-CSIRO-CCAM, CNRM-CM5CSIRO-CCAM and MPI-ESM-LR-CSIRO-CCAM for three future periods: near future (2010–2039), mid future (2040–2069) and far future (2070–2099) under RCP 4.5 and RCP 8.5 scenarios were bias-corrected and fed into the Soil and Water Assessment Tool (SWAT), a hydrological model, to estimate future groundwater recharge. The results showed a decrease in groundwater recharge in future ranging from 3.3 to 50.7 mm/yr under RCP 4.5 and 19–102.1 mm/yr under RCP 8.5 scenario. The GMS-MODFLOW model was employed to estimate the future groundwater level of Kathmandu Valley. The model revealed that the groundwater level

Ho Chi Minh City (HCMC), Vietnam has undergone tremendous transformation in land-use practices in the past few decades. The groundwater-related issues have also been a major concern in the fast-growing southern city of Vietnam. Quantitative prediction of the impact on groundwater recharge due to changes in the land-use pattern of a watershed is crucial in developing sound groundwater management schemes. This study aims to evaluate the impacts of change in land-use patterns on the quantity of groundwater recharge in HCMC. An empirical land-use projection model (Conversion of Land-use and its Effects, Dyna-CLUE) and a hydrological model (Soil and Water Assessment Tool, SWAT) was used for the study. Three future land-use scenarios of Low Urbanization Scenario (LU), Medium Urbanization Scenario (MU) and High Urbanization Scenario (HU) were developed in Dyna-CLUE focusing on the increase of built-up area to generate land use maps of HCMC until the year 2100. The land-use maps for all three scenarios were then used in the calibrated hydrological model SWAT to get the future recharge in the near future (2016–2045), mid future (2046–2075) and far future (2076–2100). The recharge was observed to increase in the far future of LU by 10% while reduction of 30% and 52%