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%

Impacts of climate change on water resources, especially groundwater, can no longer be hidden. These impacts are further exacerbated under the integrated influence of climate variability, climate change and anthropogenic activities. The degree of impact varies according to geographical location and other factors leading systems and regions towards different levels of vulnerability. In the recent past, several attempts have been made in various regions across the globe to quantify the impacts and consequences of climate and non-climate factors in terms of vulnerability to groundwater resources. Firstly, this paper provides a structured review of the available literature, aiming to critically analyze and highlight the limitations and knowledge gaps involved in vulnerability (of groundwater to climate change) assessment methodologies. The effects of indicator choice and the importance of including composite indicators are then emphasized. A new integrated approach for the assessment of groundwater vulnerability to climate change is proposed to successfully address those limitations. This review concludes that the choice of indicator has a significant role in defining the reliability of computed results. The effect of an individual indicator is also apparent but the consideration of a combination (variety) of indicators may give more realistic results. Therefore, in future, depending upon the

Considerable uncertainty occurs in the parameter estimates of traditional rainfall–water level transfer function noise (TFN) models, especially with the models built using monthly time step datasets. This is due to the equal weights assigned for rainfall occurring during both water level rise and water level drop events while estimating the TFN model parameters using the least square technique. As an alternative to this approach, a threshold rainfall-based binary-weighted least square method was adopted to estimate the TFN model parameters. The efficacy of this binary-weighted approach in estimating the TFN model parameters was tested on 26 observation wells distributed across the Adyar River basin in Southern India. Model performance indices such as mean absolute error and coefficient of determination values showed that the proposed binary-weighted approach of fitting independent threshold-based TFN models for water level rise and water level drop scenarios considerably improves the model accuracy over other traditional TFN models.