Fatma Trabelsi

The estimation of groundwater exploitation in arid and semi-arid countries such as Tunisia remains a challenging issue. In the Medjerda lower basin, water resources are overexploited due to Climate Change, anthropogenic pressures, and the intensification of irrigated areas. To address this, estimating spatially distributed crop water consumption is crucial for promoting efficient water management. This study aims to estimate volumes of groundwater pumping for irrigation in a citrus orchard area of the Medjerda Lower Valley basin using earth observation data as input of the SAtellite Monitoring of Irrigation (SAMIR) model based on the FAO-56 dual crop coefficient water balance model. The SAMIR model's simulated irrigation volumes were compared with the actual volumes of water that were supplied by farmers. The results showed significant difference between the simulated required volumes of 1252074 m3 and the declared amount of 663 882 m3 , indicating an estimated groundwater irrigation pumping of about 239 813 m3/year . These findings confirm the feasibility of earth observation data for estimating irrigation groundwater pumping in water-scarce areas, and that they can be useful for decision-makers.

Anticipatory approaches are increasingly used to guide decision-making on environmental issues. A number of these approaches, particularly in the field of anticipatory governance, promote the participation of users in anticipatory thinking. Various tools are already used for this purpose. Nevertheless, most of these tools focus on the present and the future, rarely on the past. This article introduces a tool for the participatory modeling of past, current and future governance of groundwater in a territory. This tool was coupled with the Futures Triangle to foster dialog among the actors of Aousja Ghar El Melh territory in Tunisia. The tool allowed opening up dialog on what stakeholders in Aousja Ghar El Melh wanted to keep or change in past and current governance, and what future they envisioned for their territory. This article highlights the need for further methodological developments in order to be more dynamic and better integrate the three governance temporalities. Several avenues are discussed, including a dynamic presentation of the model and the use of role-playing games. This experiment also highlights the need not only to identify the different approaches to anticipatory governance at hand, but also to think ahead about how to articulate them, especially in an inter-disciplinary and multi-actor process.

Water scarcity is a severe problem in Tunisia, particularly in the northern region crossed by the Medjerda River, where groundwater is a conjoint water resource that is increasingly exploited. The aim of this study is to delineate the groundwater potential zones (GWPZs) in the Lower Valley of the Medjerda basin by using single benchmark machine learning models based on artificial neural network (ANN), random forest (RF), and support vector regression (SVR), and by developing a novel hybrid method, NB-RF-SVR, to reach the highest accuracy of groundwater potential prediction. Each model produced a spatial groundwater potential map (GPM) with the input of 26 groundwater-related factors (GRF) selected by the frequency ratio model and 70% of the transmissivity training data. The models’ effectiveness was assessed using the AUC-ROC curve, sensitivity, specificity, MAE, and RMSE metric indicators. The validation findings revealed that all the models performed successfully for the GWPZ mapp...

The water quality of aquifer is conditioned by geological formations crossed by water during its flow. So water crossing calcareous rocks becomes rich in bicarbonates; also water crossing saliferous rocks becomes rich of sulphates or chlorides. This affirmation can be applied to water of the karst aquifer of Taoura. The recharge of this aquifer comes from rainfall or by water of different draining zones of the watershed cross-border of Medjerda-Mellegue in south part of the city of Souk Ahras. The geological studies showed that the outcrop formations in the syncline contain groundwater in low level, which make the aquifer captive. This last is exploited by several wells (T1, T3, T7, D3, D5).

The mine is situated in the East Algerian near the frontiers of Tunisia. The exploitation of iron is stopped until 1967.The water samples were collected from groundwater and surface water. Physicochemical parameters were measured during fieldwork. Water samples were analyzed for major ions and metallic trace element.

Groundwater potential mapping and its sustainable development are an important aspect in the Lower Valley of Medjerda (LVM) river sub-basin due to increased water demand for irrigation and domestic use. The main goal of this study is to investigate the application of the probabilistic-based frequency ratio (FR) model in groundwater potential mapping at LVM river in Tunisia using GIS. This study includes the analysis of the spatial relationships between Transmissivity and various hydrological conditioning factors such as elevation, slope, curvature, river, lineament, geology, soil, rainfall, and land use. Eighteen groundwater-related factors were collected and extracted from topographic data, geological data, satellite imagery, and published maps. About 60 groundwater data of transmissivity were randomly split into a training dataset, 70% was used for training the model and the remaining 30% for validation purposes. Finally, the FR coefficients of the hydrological factors were used t...

This paper investigates the feasibility of predicting nitrate contamination from agricultural sources using multi-layer perceptron artificial neural networks (MLP-ANNs). The approach consists in training an MLP-ANN to predict nitrate concentrations based on a set of indirect measurements, such as pH, electrical conductivity, temperature and groundwater level. These are simpler and more economical than direct measurements, and they can be continuously collected on-site, rather than by performing laboratory tests. The approach has been validated in the nitrate vulnerable zone of the Arborea plain (central western Sardinia, Italy) by comparing the results obtained with different MLP-ANN models in order to find the most efficient model. The results show that the MLP-ANN-based model is a time- and cost-efficient method for predicting nitrate concentration.

Over the last years, the global application of machine learning (ML) models in groundwater quality studies has proved to be a robust alternative tool to produce highly accurate results at a low cost. This research aims to evaluate the ability of machine learning (ML) models to predict the quality of groundwater for irrigation purposes in the downstream Medjerda river basin (DMB) in Tunisia. The random forest (RF), support vector regression (SVR), artificial neural networks (ANN), and adaptive boosting (AdaBoost) models were tested to predict the irrigation quality water parameters (IWQ): total dissolved solids (TDS), potential salinity (PS), sodium adsorption ratio (SAR), exchangeable sodium percentage (ESP), and magnesium adsorption ratio (MAR) through low-cost, in situ physicochemical parameters (T, pH, EC) as input variables. In view of this, seventy-two (72) representative groundwater samples have been collected and analysed for major cations and anions during pre-and post-monso...

... The oldest outcrops are allotted to the lower Eocene; the most recent are allotted to the old and recent Quaternary (Ben Salem 1992). The study area shows four main landscapes separated by an expressed scarp (Fig. 1): ... 1971; Ben Salem 1991; Colleuil and Ben Salem 1991). ...

The time domain electromagnetic method (TDEM) is applied to monitor, to delineate and to map the saltwater intrusion zones in
the Mediterranean Plio-Quaternary aquifer. Forty-two TDEM soundings were carried out in the coastal plain of Nabeul–
Hammamet region (NE Tunisia). TDEM resistivity data were correlated with the existing borehole logging data to assign them to
a particular lithology and to provide information about the position of the freshwater–seawater transition zone. The geoelectric
sections showing the vertical configuration of seawater intrusion, with the brackish-salty-saturated zones, have a resistivity
ranging from ~0.1 to 5 Ω
m and are detected at a depth lower than 1.5 m. The salinized zones are located at Nabeul (Sidi Moussa,
Sidi El Mahrsi, Al Gasba and Mrazgua) and at Hammamet (Touristic zone of Hammamet north and south, Baraket Essahel) and
reached a distance of 4 km from the coastline, indicating a severe state for the aquifer in these zones. These TDEM results are
confirmed by the increase of chloride concentration content in the analysed water samples of monitoring wells. Moreover, in the
northeastern part, the presence of a saltwater front located far from the coast and along the NW–SE major surface fault can be
explained by two hypothesis: (i) this fault seems to provide a conduit for seawater to move readily towards the water wells and
(ii) the clay and gypsum infiltration of marine Messinian deposits through the fault plane leads to low resistivities. Finally, it
comes out from this study that TDEM survey has successfully depicted salinized zones of this coastal aquifer. Copyright © 2012
John Wiley & Sons, Ltd.
KEY WORDS TDEM; saltwater intrusion; Plio-Quaternary aquifer; Nabeul–Hammamet; Tunisia