Development of monthly groundwater well observation dataset in India

Accurate, reliable, and continuous groundwater level observations are essential for assessing sustainable water management in India. However, the absence of quality-controlled and high-frequency groundwater datasets has significantl hindered large-scale groundwater assessments. The existing groundwater levels data in India are available at a quarterly time scale (January, May, August, and November), but with substantial data gaps. Here, we developed a monthly groundwater level dataset for India, covering the period from 1996 to 2021, by combining quarterly observations from 4514 wells. We first employed a combination of Quantile Regression Forests and K-means clustering to impute the missing quarterly groundwater levels using topographical, climatological, and hydrogeological variables. Subsequently, a Chow-Lin disaggregation method was employed to convert quarterly data into monthly data, ensuring temporal consistency with observed values. The developed monthly groundwater level data enable the analysis of groundwater storage changes, identification of potential recharge zones, water budget studies, groundwater-surface water interactions, and the calibration of hydrological models, thereby supporting sustainable groundwater management across India.