Improving satellite-based evaporation estimates by incorporating plant access to groundwater

Evaporation is one of the major fluxes in the hydrological cycle, yet there are still unresolved issues in its estimation. As a result, many different land surface models and satellite-based algorithms currently exist, each with their own strengths and weaknesses. One major assumption typically applied in these models/algorithms is that groundwater levels are deep enough so that there is free vertical drainage across the root zone. As a result, it is assumed that groundwater dynamics do not influence evaporation. However, in many regions, the groundwater table is shallow, such that vegetation does have access to the groundwater system. This interaction with the groundwater system may increase evaporation, particularly during dry seasons and in some regions more significantly than in others. Therefore, the common assumption of a deep groundwater system may result in underestimated evaporation estimates. This applies to land surface models and satellite-based algorithms relying on plant available water for the computation of evaporative stress. In this study, the inclusion of a groundwater module is explored in a commonly used satellite-based algorithm, namely the Global Land Evaporation Amsterdam Model (GLEAM), by assuming that the groundwater system can be represented with a linear reservoir. This simple approach was selected for its limited data requirements, global applicability and for being compatible with the structure of GLEAM. To assess the reliability of this new groundwater model, analyses were carried out for The Netherlands due to groundwater data availability. For this purpose, groundwater level predictions were compared to in situ data and a national groundwater model based on MODFLOW (Modular Three-Dimensional Finite-Difference Groundwater Flow Model). In addition, the new evaporation estimates were compared to those by the original GLEAM and to in situ eddy covariance data. This study sets a new step towards understanding the impact of groundwater on evaporation using satellite data at a global scale.