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.

The Bayech basin is located in southwestern Tunisia, a highly prone region to flooding risks. The Bayech basin is characterized by wadis that adopt a wide, sometimes ill-defined bed, often intersected by low-lying areas, resulting in a semi-endoreismo, greatly disrupting the flow regimes. The Bayech basin drains the slopes of the Nementchas and Tebessa mountains in Algeria, collecting water from the Medjen Bel Abbes plain in its middle course before crossing the Gafsa djebls chain at the Gafsa gap. In this basin, flooding is generally caused by high-intensity storms and is often relatively limited in extent. The slope shape and soil type can promote rapid surface runoff during intense rainfall. Therefore, the purpose of creating a web application, labeled ClimInonda, is to respond to a critical need of readily available information on climatic, environmental, and land use data collected in this basin and its morphometric characteristics using recent methods. The application consists of three essential components: the front-end, back-end, and database. The front-end focuses on the user interface, allowing users to interact with the application’s features. It communicates with the back-end through Hypertext Transfer Protocol requests for data processing and retrieval. The back-end handles the server-side operations, processes requests, and provides responses by retrieving data from the database. The database stores and manages the application’s data, ensuring integrity and efficient access. This modular architecture ensures a user-friendly interface, seamless data processing, and reliable data storage. Visualizations can include different types of data, such as satellite imagery, weather data, and terrain data, and can be displayed using various techniques, such as heat maps, contour maps, and 3D models, by providing easy-to-understand visualizations. ClimInonda is an application developed to expand upon existing platforms by providing a suite of exploratory data analysis features, including the ability to calculate the total precipitation depth recorded for any period, interpolate the annual recurrence interval for rainfall events, etc. A simple evaluation of the platform was performed to assess the usefulness and user satisfaction of the tool by professional users, and positive feedback was received. There is clear evidence that ClimInonda would provide the necessary basis for informed decision making by stakeholders and development agencies in arid and semi-arid Tunisia.

Climate data are important in building a hydrological risk assessment model. The ClimInonda web application enables interactive and dynamic visualizations of different data collected from different weather stations in the study area on a single platform, allowing users to explore and analyze data in an easy way. This can assist decision-makers and stakeholders in understanding the current state of the environment and in identifying areas of flooding risk. Visualizations can include different types of data, such as satellite imagery, weather data, and terrain data, and can be displayed using various techniques, such as heat maps, contour maps, and 3D models by providing easy-to-understand visualizations. The different stations of the Gafsa and Kasserine governorates in the study area are included and other stations of the Algerian territory (Tebessa governorate) are incorporated. This web application also provides the capability to include each user's stations.

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.