Abstract

Assessment of groundwater resources is crucial for developing water management practices for its sustainable exploitation, both for current and future needs. Numerical models are useful tools for such purpose. However, the lack of continuous monitoring networks, mainly due to difficult access to some remote locations, poses a challenge in developing and calibrat-ing groundwater models. Remote sensing offers an alternative for acquiring information on hydrological and climatic var-iables at multiple spatiotemporal scales that has the potential to strengthen groundwater modeling. The aim of this study is to develop a methodology that uses remote sensing products to support model calibration. With this aim, we used the Pa-rameter Estimation software (PEST) to calibrate a hydrogeological model of an unexploited basin located in the arid Chilean Altiplano using observed groundwater levels and evapotranspiration (ET) derived from the Earth Engine Evapotranspira-tion Flux (EEFlux) tool as observations. Our results show that the best model calibration is achieved using both EEFlux-ET and heads as observations to calibrate the hydraulic properties (normalized root mean square error = 4.1 %). We an-alyzed the effect of EEFlux-ET on the calibration of these properties and found a direct effect on specific yield parameters, which regulate the fluctuations of the water table over time. Incorporating EEFlux-ET estimates in the calibration resulted in lower values of specific yield across the aquifer. Therefore, incorporating remotely sensed ET as observations in the calibra-tion of the groundwater model contributes to a better simulation of the spatiotemporal head variations in the basin.