Method for Recharge and Sustainable Groundwater Use Estimation Using Soil Moisture Time-Series Analysis

Abstract

Accurately estimating groundwater recharge is essential for sustainable aquifer management, yet remains difficult to measure directly, especially at large spatial scales. This thesis presents a method to estimate recharge using soil moisture drydown dynamics—the period following precipitation during which soil water is lost to evaporation and drainage. A two-component continuous loss function was developed to model this moisture loss, separating evaporation and drainage processes in a physically consistent, mathematically tractable framework. Using high temporal resolution in situ data from the ARM Southern Great Plains site, the method was calibrated and validated, showing that daily or sub-daily data capture the full shape of the loss function. A key outcome was the derivation of a hydrologic length scale (λ) from precipitation and soil moisture data, enabling conversion of unitless drainage estimates into physically meaningful recharge fluxes (mm/day). The methodology was then applied to satellite-based soil moisture data from the SMAP mission and the combined SMAPSMOS product. Despite resolution and noise limitations, these datasets produced reasonable drainage estimates, and the combined product showed particular promise for capturing drydowns at global scale. The findings demonstrate that soil moisture observations—when analyzed with appropriate temporal resolution and physical modeling—can provide a scalable, remote sensing-based approach to estimating groundwater recharge worldwide.