Global warming induces spatially heterogeneous changes in precipitation patterns, highlighting the need to assess these changes at regional scales. This assessment is particularly critical for Afghanistan, where agriculture serves as the primary livelihood for the population. New global climate model (GCM) simulations have recently been released for the recently established shared socioeconomic pathways (SSPs). This requires evaluating projected precipitation changes under these new scenarios and subsequent policy updates. This research employed six GCMs from the CMIP6 to project spatial and temporal precipitation changes across Afghanistan under all SSPs, including SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The employed GCMs were bias-corrected using the Global Precipitation Climatological Center's (GPCC) monthly gridded precipitation data with a 1.0° spatial resolution. Subsequently, the climate change factor was calculated to assess precipitation changes for both the near future (2020–2059) and the distant future (2060–2099). The bias-corrected projections' multi-model ensemble (MME) revealed increased precipitation across most of Afghanistan for SSPs with higher emissions scenarios. The bias-corrected simulations showed a substantial increase in summer precipitation of around 50%, projected under SSP1-1.9 in the southwestern region, while a decline of over 50% is projected in the northwestern region until 2100. The annual precipitation in the northwest region was projected to increase up to 15% for SSP1-2.6. SSP2-4.5 showed a projected annual precipitation increase of around 20% in the southwestern and certain eastern regions in the far future. Furthermore, a substantial rise of approximately 50% in summer precipitation under SSP3-7.0 is expected in the central and western regions in the far future. However, it is crucial to note that the projected changes exhibit considerable uncertainty among different GCMs.

Increasing water consumption and climate change are putting countries all over the world at risk of running out of water supply. The provision of groundwater helped reduce global food scarcity, but overexploitation resulted in the depletion of groundwater resources in many regions worldwide. In this study, the concept of reliability, resiliency and vulnerability has been applied to determine the spatial distribution of sustainability in groundwater resources over the intensive groundwater irrigated region of South Asia and China. The satellite-based Global Land Data Assimilation System (GLDAS) data of groundwater storage for 2003‒2020 were acquired and used for this reason. The findings showed a decrease in groundwater storage in Northern China, Western India, and Eastern Pakistan, with the highest declination rate in western India by -50 to -200 mm per decade. The groundwater reliability, resiliency and vulnerability were noticed to decrease in some regions of the study area, with the highest decrease in west India by -0.2 to -0.3 per decade. This caused a decrease in groundwater sustainability in the area at a rate of -0.1 to -0.3 per decade. The reduction in groundwater sustainability in western India may be due to intensive groundwater abstraction in those regions.