Water scarcity in arid and semi‐arid regions represents a significant obstruction to social and economic development. Also, flood hazards affect the life of many people in these areas. This study aims to develop a new model for integrated management of surface water and groundwater, which involves rainwater harvesting and recharge to groundwater aquifers. Integrated hydrological models, including geographic information system (GIS), watershed modelling system (WMS) and groundwater modelling system (GMS) were used. This research provides an integrated vision for exploiting the rainwater in Wadi Watier, South Sinai, Egypt and shows new insights on how to protect these areas from flood risks and store water to solve the water scarcity in this region. Based on physical properties of sub‐basins and soil properties, fourteen dams were suggested and designed to protect the study area from flood risks; five dams were used for storage and nine dams for groundwater recharge. The results showed that the dams could collect about 160.72 million m³ of rainwater which can be stored or recharged into groundwater aquifers. This will increase the national income and provide stability for residents in these areas that suffer from water shortage. Decision‐makers can use these models for sustainable flood management in similar areas.

The shortage of water is a major obstruction to the social and economic development of many countries, including Egypt. Therefore, there is an urgent need to properly manage water resources to achieve optimum water use. One way of saving available water resources is to reduce evaporation that leads to the loss of a large amount of water from reservoirs and open lakes. This paper aims to use a floating photovoltaic system (FPVS) to cover a lake’s water surface to reduce evaporation and also for energy production. This methodology was applied to Lake Nasser as one of the largest lakes in the world where much evaporation happens due to its large area, arid environments, and the shallow depths of some parts of the lake. The estimated evaporation from the lake was 12.0 × 10⁹ m³/year. The results show that covering 25%, 50%, 75%, and 100% of the lake can save about 2.1, 4.2, 6.3, 7.0, and 8.4 × 10⁹ m³/year and produce energy of 2.85 × 10⁹, 5.67 × 10⁹, 8.54 × 10⁹, and 11.38 × 10⁹ MWh/year, respectively. Covering areas of shallow water depth was more efficient and economical. The results show that covering 15% of the lake’s area (depths from 0.0 to 3.0 m) can save 2.66 × 10⁹ m³/year and produce 1.7 MWh/year. Covering 25% of the lake’s area (depths from 0.0 to 7.0) can save 3.5 × 10⁹ m³/year and produce 2.854 MWh/year. Using an FPVS to cover parts of Lake Nasser could help manage water resources and energy production for Egypt to overcome the likely shortage of water resources due to population growth. This system could be applied in different locations of the world which could help in increasing water resources and energy production, especially in arid and semi-arid regions.

Water quality assessment is paramount for environmental monitoring and resource management, particularly in regions experiencing rapid urbanization and industrialization. This study introduces Artificial Neural Networks (ANN) and its hybrid machine learning models, namely ANN-RF (Random Forest), ANN-SVM (Support Vector Machine), ANN-RSS (Random Subspace), ANN-M5P (M5 Pruned), and ANN-AR (Additive Regression) for water quality assessment in the rapidly urbanizing and industrializing Bagh River Basin, India. The Relief algorithm was employed to select the most influential water quality input parameters, including Nitrate (NO₃⁻), Magnesium (Mg²⁺), Sulphate (SO₄²⁻), Calcium (Ca²⁺), and Potassium (K⁺). The comparative analysis of developed ANN and its hybrid models was carried out using statistical indicators (i.e., Nash-Sutcliffe Efficiency (NSE), Pearson Correlation Coefficient (PCC), Coefficient of Determination (R²), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Relative Root Square Error (RRSE), Relative Absolute Error (RAE), and Mean Bias Error (MBE)) and graphical representations (i.e., Taylor diagram). Results indicate that the integration of support vector machine (SVM) with ANN significantly improves performance, yielding impressive statistical indicators: NSE (0.879), R² (0.904), MAE (22.349), and MBE (12.548). The methodology outlined in this study can serve as a template for enhancing the predictive capabilities of ANN models in various other environmental and ecological applications, contributing to sustainable development and safeguarding natural resources.

Climate change in desert areas and semi-arid watersheds may offer a promising solution for the water scarcity problem that Bedouins and local inhabitants face. This study investigated the integrated water resources management in arid and semi-arid regions using rainwater harvesting in combination with the managed aquifer recharge (RWH-MAR) technique. The study also used recharge wells and storage dams to achieve the sustainability of groundwater supplies in the context of climate change and management of the flow to the Gulf of Suez. Therefore, different return periods of 10, 25, 50, and 100 years were considered for the annual flood volume resulting from those watersheds. Moreover, hydrologic modeling was carried out for the El Qaa plain area, South Sinai, Egypt, using the Watershed Modeling System (WMS) and the groundwater modeling of SEAWAT code. Our findings show that for different scenarios of climate change based on return periods of 10, 25, 50, and 100 years, the aquifer potentiality reached 24.3 MCM (million cubic meters) per year, 28.8 MCM, 36.7 MCM, and 49.4 MCM compared to 21.7 MCM at 2014 with storage of groundwater ranges 11.8%, 32.1%, 69%, and 127.4%, respectively. These findings have significant implications for the system of RWH-MAR and groundwater sustainability in El Qaa Plain, South Sinai. The RWH-MAR proved to be an effective approach that can be applied in different water-stressed and arid regions to support freshwater resources for sustainable future development and food security, as well as protect communities from extreme flash flood events.

This research investigated the transient saltwater upconing in response to pumping from a well in a laboratory-scale coastal aquifer. Laboratory experiments were completed in a 2D flow tank for a homogeneous aquifer where the time evolution of the saltwater wedge was analysed during the upconing and the receding phase. The SEAWAT code was used for validation purposes and to thereafter examine the sensitivity of the critical pumping rate and the critical time (the time needed for the saltwater to reach the well) to the well design and hydrogeological parameters. Results showed that the critical pumping rate and the critical time were more sensitive to the variations of the well location than the well depth. The critical time increased with increasing the location and depth ratios following a relatively linear equation. For all the configurations tested, the lowest critical pumping rate was found for the lower hydraulic conductivity, which reflects the vulnerability of low permeability aquifers to salinization of pumping wells. In addition, higher saltwater densities led to smaller critical pumping rate and shorter critical time. The influence of the saltwater density on the critical time was more significant for wells located farther away from the initial position of the interface. Moreover, increasing the dispersivity induced negligible effects on the critical pumping rate, but reduced the critical time for a fixed pumping rate.

Subsurface physical barriers are amongst the most effective methods to mitigate seawater intrusion in coastal aquifers. The main objective of this study was to examine the impact of cutoff walls on saltwater upconing using laboratory and numerical modelling experiments. Physical experiments were first completed to reproduce the saltwater upconing process in a laboratory-scale coastal aquifer model incorporating an impermeable cutoff wall. Numerical modelling was used for validation purposes and to perform additional simulations to explore the protective effect of cutoff walls against saltwater upconing. The results suggest that the cutoff wall did not substantially delay the saltwater upconing mechanism in the investigated configurations. Laboratory and numerical observations showed the existence of some residual saline water, which remained on the upper part of the aquifer on the seaward side of the wall following the retreat of the saltwater. The protective effect of cutoff walls was noticeably sensitive to the design parameters. Specifically, cutoff walls installed close to the pumping well enabled the implementation of higher pumping rates, therefore a more optimal use of the freshwater, especially for deeper wells. The results highlighted that the penetration depth of the cutoff walls may not necessarily need to exceed the depth of the pumping well to ensure effectiveness, which is of great importance from construction and economic perspectives.