Modelling groundwater futures under climatic uncertainty for local policy and planning: a case of quantification of groundwater resources at sub-regional level in the Ganges basin

Mizan, S.A., Sikka, A., Chakraborty, S., Laing, A., Urfels, A., & Krupnik, T.J. (2024) Modelling groundwater futures under climatic uncertainty for local policy and planning: a case of quantification of groundwater resources at sub-regional level in the Ganges basin. https://ssrn.com/abstract=5063096

Demand for water has increased sixfold globally over the past century due to changes in consumption patterns, economic development, and population growth. This trend is predicted to continue. This rise puts immense strain on groundwater supplies, particularly in highly groundwater dependent countries like India, endangering their food and water availability. Assessing the impacts of climate change on aquifers' seasonal replenishment is thus crucial for planning for future local food and water security. This study looks at how future groundwater levels will be affected by climate change in relation to important functioning thresholds that are typical for aquifers that replenish periodically. For this we use a case study from the Nalanda district in the Lower Ganges River Basin in India, using in situ observed data to build a conceptual hydrogeological model. This model is then numerically simulated for 18 years (2000-2018) using the MODFLOW-NWT model, calibrated and validated within 5% root mean square error (RMSE). We project future groundwater levels from 2018 to 2060 using the CMIP6 global climate model, using precipitation data from three GCMs selected based on their different projected scenarios of levels of high intensity rainfall. Given the key role of low intensity rainfall in groundwater recharge, we find that incorporating rainfall intensity in groundwater models can be crucial for more robust projections. Our findings show that higher total rainfall does not necessarily equate to higher recharge or lesser groundwater declines. Instead, the least groundwater declines were found in projections where relatively higher total rainfall was also associated with lower high-intensity rainfall periods, highlighting the need for combining and comparing varied SSPs and climate models for accurate future trends. At the sub-regional level, we find that climate change could lead to maximum groundwater loss of ~ 0.8 km3 in 42 years in Nalanda district. Current trend analysis (2000–2018) already shows a negative annual groundwater balance. Even assuming no changes to current groundwater extraction rates, climate change will result in decreased groundwater levels and storage. The projection trends also reveal distinct short-term, medium-term, and long-term shifts which offer different policy windows for managing and governing the groundwater resources.