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<p>Drought is a natural hazard that occurs every year in the Mekong Delta of Vietnam (MDV). In recent years, drought has become more severe, increasing socio-economic risk. Climate change is one of the primary reasons aggravating the level of drought. Therefore, giving a drought risk assessment that integrates climate change impacts is crucial. This study contributes to a proof-of-concept comprehensive drought risk assessment under the impacts of climate change in the coastal provinces of the MDV. The risk of MDV for climate hazards has been assessed considering three key elements - hazards, exposure, and vulnerability. Three CMIP6 global climate model datasets – MIROC6, CESM2, and CNRM-CM6-1 – and two Shared Socioeconomic Pathways of SSP2-4.5 and SSP5-8.5 are selected to project climate change from 2025 to 2100. The Standardized Precipitation Evapotranspiration Index (SPEI) has been used to assess the future drought hazard. Drought exposure and vulnerability are derived using statistical data on natural and socioeconomic characteristics from provincial statistical yearbooks. The results of this study will benefit policymakers to develop risk management strategies in minimizing the drought risks in the coastal estuarine deltas under the long-term impacts of climate change.</p>

Considerable efforts have been devoted to the modeling of the results for the Leak-off Tests (LOT) in the past. Over the last decade, there are two major focuses in this field of research: the extended application of LOT models to horizontal wells and the theory of the fluid leakage during LOT. In the present study, an improved model has been proposed based on the original Altun's model: 1) the initial system volume is corrected after considering thermal and pressure effects as well as the geometry of the well path; 2) the casing expansion during LOT test is extended to directional wells with respect to pressure change; 3) a new leak volume model is developed to analyze the different flow behavior of fluid before and after the fracture initiation pressure (FIP). The data from a field example is used to validate the model. The predicted results demonstrate the improvement and accuracy of the model for the estimation of LOT values for horizontal wells.