Groundwater assessment in the Mediterranean region: Regional modelling and in-situ data across scales

Groundwater is a valuable resource throughout the world. It supplies the needs of many sectors
everywhere. Providing high spatial resolution groundwater data is important for climatic,
hydrological and agricultural applications, to ensure sustainable groundwater management. The
scarcity of high-resolution groundwater data over large scales at the required accuracy is a
significant limitation for such applications. This study was undertaken in the Mediterranean
region, which is recognized as one of the world's most sensitive regions to water scarcity due to
both climate change and consistently increasing anthropogenic pressures. Groundwater is
considered a strategic freshwater reserve in the Mediterranean region; however, its status
remains poorly characterized. This study investigates the feasibility of downscaling outputs of
three global groundwater models (Reinecke et al. (2019), de Graaf et al. (2017) and Fan et al.
(2013)) to higher resolution.
Steady-state results of the three models were compared with in-situ groundwater level
observations, and an aggregation method was developed for downscaling. Observations from a
long-term groundwater monitoring network over different regional studies around the
Mediterranean were employed. Results showed that there is a significant discrepancy between the
three compared model outputs. More specifically, the de Graaf et al. (2017) model presents a
deeper water table than Reinecke et al. (2019) and Fan et al. (2013), while de Graaf et al. (2017)
generally shows more significant variability in simulated water table depth. A detailed comparison
between simulated and measured water table depth of different Mediterranean aquifers having
different climatic, geologic and anthropogenic conditions will be presented.
The results of this work will contribute to advance the understanding of how to combine largescale
groundwater modelling with local in-situ data as a crucial tool to improve groundwater
management in data-scarce regions.