Soil erosion remains one of the principal environmental problems in arid regions. This study aims to assess and quantify the variability of soil erosion in the Koutine catchment using the RUSLE (Revised Universal Soil Loss Equation) model. The Koutine catchment is located in an arid area in southeastern Tunisia and is characterized by an annual mean precipitation of less than 200 mm. The model was used to examine the influence of topography, extreme rainstorm intensity and soil texture on soil loss. The data used for model validation were obtained from field measurements by monitoring deposited sediment in settlement basins of 25 cisterns (a traditional water harvesting and storage technique) over 4 years, from 2015 to 2018. Results showed that slope is the most controlling factor of soil loss. The average annual soil loss in monitoring sites varies between 0.01 and 12.5 t/ha/y. The storm events inducing the largest soil losses occurred in the upstream part of the Koutine catchment with a maximum value of 7.3 t/ha per event. Soil erosion is highly affected by initial and preceding soil conditions. The RUSLE model reasonably reproduced (R² = 0.81) the spatiotemporal variability of measured soil losses in the study catchment during the observation period. This study revealed the importance of using the cisterns in the data-scarce dry areas as a substitute for the classic soil erosion monitoring fields. Besides, combining modeling of outputs and field measurements could improve our physical understanding of soil erosion processes and their controlling factors in an arid catchment. The study results are beneficial for decision-makers to evaluate the existing soil conservation and water management plans, which can be further adjusted using appropriate soil erosion mitigation options based on scientific evidence.

Flash floods are a significant threat to arid and semi-arid regions, causing considerable loss of life and damage, including roads, bridges, check dams and dikes, reservoir filling, and mudslides in populated areas as well as agricultural fields. Flood risk is a complex process linked to numerous morphological, pedological, geological, anthropic, and climatic factors. In arid environments such as where Bayech basin is located in southwestern Tunisia, the hydrometric data are insufficient due to the absence of measuring points. Using the hybrid fuzzy Analytical Hierarchy Process (F-AHP) and the frequency ratio statistical methods, this study aims to map flooding risks in an ungauged basin that is extremely prone to flooding. Data related to soil texture, slope, land use, altitude, rainfall, drainage density, and distance from the river were used in the risk analysis. The obtained flood risk maps from both F-AHP and FR models were validated on the basis of the Receiver Operating Characteristic (ROC), the Area Under the Curve (AUC), and the inventory map. Results revealed that areas of high and very high susceptibility to flooding are mainly located in the downstream part of the basin, where the town of Gafsa is located. Other upstream sites are also at risk. In this basin, slope is predominantly behind runoff accumulation, whereas soil type plays a major role in amplifying waterproofing and therefore overflow. The results derived from both methods clearly demonstrate a viable and efficient assessment in flood-prone areas. The F-AHP and FR methods have ROC values of 95% and 97%, respectively. Considering these results in the decision-making process, these outputs would enable the implementation of the necessary measures to mitigate flood risk impacts ensure sustainable development along with an effective management in Tunisian arid environments, for the well-being of local communities at risk.

Water management in arid regions faces significant challenges due to limited water resources and increasing competition among sectors. Climate change (CC) exacerbates these issues, highlighting the need for advanced modeling tools to predict trends and guide sustainable resource management. This study employs Water Evaluation And Planning (WEAP) software to develop a Decision Support System (DSS) to evaluate the impact of climate change and water management strategies on the Triassic aquifer of “Sahel El Ababsa” in southeast Tunisia up to 2050. The reference scenario (SC0) assumes constant climatic and socio-economic conditions as of 2020. CC is modeled under RCP4.5 (SC1.0) and RCP8.5 (SC2.0). Additional scenarios include Seawater Desalination Plants (SDPs) (SC3.0 and SC4.0), water harvesting techniques (SC5.0) to highlight their impact on the recharge, and irrigation management strategies (SC6.0). All these scenarios were further developed under the “SC1.0” scenario to assess the impact of moderate CC. The initial aquifer storage is estimated at 100 Million cubic meters (Mm³). Under (SC0), storage would decrease by 76%, leaving only 23.7 Mm³ by 2050. CC scenarios (SC1.0, SC2.0) predict about a 98% reduction. The implementation of the Zarat SDP (SC3.0) would lead to a 45% improvement compared to reference conditions by the end of the simulation period, while its extension (SC4.0) would result in a 69.5% improvement. Under moderate CC, these improvements would be reduced, with SC3.1 showing a 59% decline and SC4.1 a 35% decline compared to the reference scenario. The WHT scenario (SC5.0) demonstrated a 104% improvement in Triassic aquifer storage by 2050 compared to the reference scenario. However, under CC (SC5.1), this improvement would be partially offset, leading to a 29% decline in aquifer storage. The scenario maintaining stable agricultural demand from the Triassic aquifer under CC (SC6.1) projected an 83% decrease in storage. Conversely, the total “Irrigation Cancellation” scenario (SC7.1) under CC showed a significant increase in aquifer storage, reaching 59.3 Mm³ by 2050—an improvement of 250% compared to the reference scenario. The study underscores the critical need for alternative water sources for irrigation and integrated management strategies to mitigate future water scarcity.

In recent years, non-conventional water (NCW) has been providing a promising alternative against increasing water scarcity in the Mediterranean. However, little work is available regarding the socioeconomic effects of its use. The purpose of this study is to present the effects of different levels of availability of irrigation water on four different Mediterranean areas relevant to the valorization of NCW. The analysis is based on technical and economic data from four Mediterranean Living Labs (LLs): one in Italy, one in Spain, one in Egypt and one transboundary between Tunisia and Algeria. The methodological approach is based on different versions of mathematical programming (linear programming, parametric programming, multi-objective programming). The results of the analysis showed that future scenarios of water deficiencies will have serious implications on the cropping pattern and will severely affect certain farm types, equally affecting employment, incomes and input use.

This study investigated land degradation sensitivity in Southern Tunisia’s Jeffara region and examined the effectiveness of water harvesting techniques (WHTs) as countermeasures. Land Degradation Sensitivity Index was calculated using a modified MEDALUS framework, in which thematic quality indices were derived from normalized indicators (climate, soil, vegetation, and management) and combined through a geometric mean within a GIS environment. The model is validated with field observations. The research found that almost the entire study area (≈99%) was classified as critically sensitive under the baseline scenario. Contributing factors include extreme aridity, limited vegetation cover, significant soil erosion, and human pressures. The most severely degraded areas are found in mountainous zones, desert plains, and mining areas, whereas regions dominated by olive orchards showed moderate sensitivity levels. This lower sensitivity is associated with the drought tolerance and deep root systems of olive trees, which enhance resistance to prolonged dry periods. This study modeled the impact of implementing traditional WHTs, notably Jessour and Tabias. Under this scenario, a clear qualitative improvement was observed, with the proportion of land classified as critical decreasing from 99% to 77.3%, indicating a measurable reduction in land degradation sensitivity associated with the implementation of WHTs. Despite their environmental benefits, such as enhancing soil moisture and stabilizing agricultural yields, the spatial expansion of WHTs remains limited.

Soil erosion is a significant environmental concern in arid regions, particularly in dam-regulated watersheds, where intermittent flows from sprinkler irrigation can exacerbate land degradation. This study assesses soil erosion susceptibility in the Sidi Aich watershed using a combined approach of the Revised Universal Soil Loss Equation (RUSLE) and the Analytic Hierarchy Process (AHP), enabling the integration of both regional characteristics and expert-driven weighting. The RUSLE model accounts for natural and human-induced factors, whereas AHP provides a hierarchical weighting system that highlights rainfall erosivity and the local impacts of dam-regulated discharges. Results show that 26.12% of the area falls into the very high susceptibility category, 25.45% into high, 23.91% into moderate, and 24.51% into low susceptibility. Model validation demonstrates satisfactory predictive performance, with Area Under the Curve (AUC) values of 0.85 for AHP and 0.78 for RUSLE. Overall, the findings emphasize the critical role of dam-controlled releases in increasing soil vulnerability, a factor that may not be fully captured when using RUSLE alone. By combining RUSLE and AHP, this research provides a more realistic and regionally tailored assessment of erosion risk, offering valuable guidance for watershed management and erosion mitigation strategies in arid environments.