Evaluation of the impact of climate change on the shallow aquifer of Grombalia (Tunisia)

Climate change presents a serious problem for water resources (WR) and the shallow aquifers are
strongly affected. This type of WR presents fundamental importance in certain regions, due to
their accessibility and sometimes, for their quality, it is preferred to surface water sources, often
polluted. It is also, affected by overexploitation problems, which contribute to the destruction of
the sustainability of the aquifer system. This study considers the Grombalia aquifer in Tunisia
which has suffered from climate change’s impact in recent years due to water resources scarcity.
Aim of the present research is to evaluate the impact of climate change on this aquifer that is one
of the pilot sites in the European project InTheMed. First, a collection of historical temperature,
precipitation and groundwater level data in the period 1976-2020 was carried out. Then, starting
from the few available geological cross sections, a two-dimensional numerical model of the aquifer
was developed in MODFLOW. The groundwater numerical model reproduces the whole basin,
from the recharge area to the outlet in the Mediterranean Sea. The area is characterized by
agricultural intensive activities and high-water demand. For this reason, the model required a
calibration of hydraulic parameters, recharge and pumping rate. After the calibration, the
numerical model was able to estimate the groundwater flow across the entire watershed of
Grombalia aquifer. To evaluate the impact of climate change on the future groundwater
availability, the model was driven using future precipitation and temperature projections. The
water abstractions were assumed to remain unchanged in the future and equal to the condition of
existing wells at 2020. To describe the future climate, 17 combinations of Regional Climate Models
(RCM) and General Circulation Models (GCMs), developed within the EURO-CORDEX initiative, were
used. The simulations were performed for the period 2006-2100, and according to the RCP4.5 and
RCP8.5 scenarios. Before their use, the climate projections were downscaled and bias corrected
with reference to the historical temperature and precipitation data. The results are evaluated in
terms of local variations of the groundwater level and their uncertainty is expressed with
reference to the variability of the 17 RCM-GCM combinations.
Acknowledgments
This work was developed under the scope of the InTheMED project. InTheMED is part of the PRIMA
program supported by the European Union’s Horizon 2020 research and innovation program
under grant agreement No 1923.