Development of monthly groundwater well observation dataset in India

The long-term continuous groundwater depth (GWD) data are essential for the sustainable management of groundwater resources and for groundwater modeling. The Central Ground Water Board (CGWB) provides quarterly GWD data for the Indian region through the India Water Resources Information System (India-WRIS). However, continuous records of GWD are largely incomplete due to a high number of missing values. To address this gap, we reconstructed quarterly and monthly GWD datasets covering 2002–2021 using the Extra Trees machine learning model and the Chow-Lin disaggregation method. The reconstruction was developed using hydroclimatic variables along with surface and subsurface geological properties. Evaluation of the predicted GWD against in-situ measurements shows that the reconstructed data effectively capture local groundwater depth behavior and can support water resources management, especially during drought periods.