Groundwater Resources Estimation

As the largest store of accessible freshwater on Earth, groundwater is under increasing pressure as a resource, currently underpinning a large proportion of irrigated agriculture worldwide and being the source of drinking water for around 2 billion people. The large storage capacity of aquifer systems offers exceptional drought resilience and can enhance water security, but aquifer overexploitation can hinder this capacity as well as harm groundwater-dependent ecosystems, cause groundwater salinization, land subsidence, and sea-level rise among other issues. Thus, robust quantification of groundwater resources is crucial, but in-situ measurements are rarely available due to the cost associated with drilling and maintaining wells, decentralized and/or non-digitalised measurements, or the non-disclosure of the data to the public for political reasons. In this sense, EO technology made an important breakthrough with the Gravity Recovery and Climate Experiment (GRACE) and its Follow-On GRACE-FO, which provide information on water content in the different layers of the soil based on changes in the Earth’s gravity field.

The proposed tool will help IFIs detect areas with significant ongoing groundwater depletion where the resilience of groundwater resources, and the dependent socioeconomic activities, are at stake. In this way, physically sustainable storage limits and extraction rates can be estimated for areas where aquifers present consistently low groundwater storage levels and/or are currently being overexploited. These areas can then be considered for the potential application of managed aquifer recharge practices. Large-scale assessments of groundwater recharge and storage variations can be derived from the combination of EO data and data assimilation systems (i.e., land surface models that incorporate EO information). More than 20 years of regional to national EO-based products on groundwater changes can be accessed to enhance our understanding of groundwater resource consumption for effective resource management and to improve groundwater models through EO data assimilation.