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Aquifers recharge faster than past estimates

January 3, 2024

A new model suggests that surface water and agriculture are more dependent on groundwater. Findings published in the Geophysical Research Letter Journal estimate that groundwater basin recharge rates may be double previous estimates.

Climate aridity was identified as a single factor to accurately estimate infiltration.

Last January, North American and European scientists presented a new climate-based model that uses a global synthesis of regional groundwater data. The calculation model was developed based on available regional groundwater measurement data and precipitation data from six continents.

The aridity-based model results closely mirrored field measurements. Not surprisingly, arid locations have lower recharge rates than humid places. However, the research indicates that previous models “vastly underestimate recharge rates.”

Higher correlation with evapotranspiration

Findings also show a higher dependence between groundwater and river flow or vegetation, via evapotranspiration (ET). The correlation became evident with the study of other surface fluxes — such as overland flow, shallow subsurface flows and soil-moisture-fed evapotranspiration.

“Strengthening the groundwater connection to surface fluxes in these models is essential, given that models are the foundation of our understanding of our planet and underpin present-day environmental science and policymaking,” wrote lead author Wouter Berghuijs of the Department of Earth Sciences at Free University Amsterdam.

Aquifers might recharge more quickly than estimated. Unfortunately, the rate is slower in arid regions where groundwater overdraft remain too common.

Monitoring groundwater resources and aquifer recharge

KISTERS provides groundwater level sensors as well as groundwater data management software. Users can view, analyze, and process an array of data. Add rainfall, ET and any open data to analyze trends in surface water and well monitoring data. Long-term access to quality water data and lithologic meta data supports groundwater planning and decisions. Accurate data inform current water balance calculations and future forecasts. The same software offers options to monitor groundwater quality, soil health, and more. In addition, a web portal enhances public education about local groundwater conditions.