Dataset on the global distribution of shallow groundwater

Shallow groundwater (GW), defined as the water table of unconfined or perched aquifers that is near enough to the land surface to influence the vadose zone and the surface soil moisture, impacts land surface water, energy, and carbon cycles by providing additional moisture to the root zone via capillary fluxes. Although the interactions of shallow GW and the terrestrial land surface are widely recognized, incorporating shallow GW into the land surface, climate, and agroecosystem models is not yet possible due to the lack of groundwater data. Groundwater systems are affected by various factors, including climate, land use/land cover, ecosystems, GW extractions, and lithology. Although GW wells are the most direct and accurate way of monitoring water table depths at point scales, upscaling GW levels from point scale to areal or regional scale poses significant challenges. Here, we provide high spatiotemporal resolution global maps of the terrestrial land surface areas influenced by shallow GW from mid-2015 to 2021 (a separate NetCDF file for each year) in a 9 km spatial and daily temporal resolution. We derived this data from NASA's Soil Moisture Active Passive (SMAP) mission spaceborne soil moisture observations with a temporal resolution of 3 days and approximately 9 km grid resolution. This spatial scale corresponds to SMAP's "Equal Area Scalable Earth" (EASE) grids. The central assumption is that the monthly moving average of soil moisture observations and their coefficient of variation are sensitive to shallow GW regardless of the prevailing climate. We process the Level-2 enhanced passive soil moisture SMAP (SPL2SMP_E) product to detect shallow GW signals. The presence of shallow GW data is calculated by an ensemble machine learning model, which is trained using simulations from a variably saturated soil moisture flow model (Hydrus-1D). The simulations span various climates, soil textures, and lower boundary conditions. The spatiotemporal distribution of shallow GW data based on SMAP soil moisture observations is provided for the first time with this dataset. The data are of value in a wide variety of applications. The most direct use is in climate and land surface models as lower boundary conditions or as a diagnostic tool to verify model results. Some other applications may include flood risk analyses and regulation, identifying geotechnical issues such as shallow GW-triggered liquefaction, global food security, ecosystem services, watershed management, crop yield, vegetation health, water storage trends, and tracking mosquito-borne diseases by identifying wetlands, among other applications.