Understanding and accurately predicting the outflow hydrograph from embankment dam breaches is essential for managing the associated flood hazard and improving emergency preparedness. This work simulates the breaching process using a high-resolution 3D computational fluid dynamics (CFD) model, a critical natural hazard for earth-fill dams under overtopping conditions. The model was validated against the experimental data, showing high accuracy in predicting breach development and failure timing. A parametric analysis was performed to assess the influence of the initial breach geometry on erosion dynamics. The results indicated a high sensitivity, while increasing the breach width by 5% led to an average 11% increase in the erosion rate, and decreasing the depth by 5% caused an average 16.5% rise. To enhance predictive capabilities for this hazard, a multilayer neural network (MLNN) was trained on the CFD-generated dataset. The network utilized breach geometry and time as inputs to forecast the peak outflow and erosion rate, achieving excellent accuracy (RMSE = 0.019, R2 = 0.99). This integrated modeling strategy combines data-driven learning with physics-based simulation and demonstrates its effectiveness for laboratory-scale dam breach modeling. This approach is a step toward more efficient surrogate-based tools for flood risk analysis, though its extension to full-scale dams and varied material properties requires additional validation and scaling analyses beyond the scope of this work.

Climate change could have significant impacts on different sectors, specifically water and energy. The IPCC reports indicate that the average temperature is projected to increase by 1.4–4.8 °C by the year 2100, which could have extreme environmental impacts. Water scarcity is a significant barrier to the social and economic advancement of many nations, which requires adequate water resources management strategies. Reducing evaporation, which causes a significant quantity of water losses from lakes, is one method of conserving the available water resources. Rising global temperatures cause changes in atmospheric circulation and increase evaporation rates. Overall, 20

Reliable prediction of SWI is essential for protecting coastal groundwater. In this study, the SWI wedge length in a sloping coastal aquifer controlled by groundwater abstraction and a fractured underground dam is estimated. To achieve this, a dataset consisting of eight dimensionless inputs, derived from prior SEAWAT numerical scenarios, was used to train six machine learning models (linear, nonlinear, and ensemble) to predict the relative SWI wedge length (L/H). First, the dataset underwent thorough examination using hypothesis testing, multicollinearity analysis, and correlation analysis to assess the significance of predictors, their interdependencies, and their relationships with L/H. Specifically, statistical tests, including ANOVA and Z-tests, were employed to identify the key predictors. Furthermore, multicollinearity was assessed using the Variance Inflation Factor (VIF), which helped identify potential redundancies. Subsequently, a cosine amplitude sensitivity analysis was used to quantify the relative influence of each input on L/H. In addition, Bayesian optimization was applied to fine-tune the hyperparameters of each model for optimal performance. The performance of the models was then evaluated using 10-fold cross-validation, regression metrics, and external validation on independent numerical scenarios from the Akrotiri coastal aquifer (Zakaki, Cyprus). Additionally, explainable ML techniques viz Shapley-Additive-Explanations (SHAP) and Partial-Dependence-Plots (PDP), were used to interpret model behavior. Results showed that the ensemble models outperformed alternatives. Among them, the XGB model provided the most consistent accuracy during the testing stage, yielding R2=0.9978, RMSE=0.216, MAE=0.058, and MARE=0.098, while also maintaining strong training performance with RMSE=0.037. Moreover, independent validation against the Akrotiri coastal aquifer confirmed high fidelity and generalizability, with R2=0.997 and RMSE=0.157. The SHAP and PDP analyses revealed that the relative recharge well rate was the dominant predictor, followed by relative fracture height, with relative fracture diameter and relative well distance having significant roles. Finally, a lightweight desktop and web graphical-user-interface (GUI) was developed, enabling rapid, user-friendly prediction of L/H. In conclusion, this study demonstrates that data-driven models can closely replicate physics-based behavior, providing a powerful tool for SWI management and decision-making in coastal aquifers.

Sustainable groundwater management depends on understanding the dynamic behaviour of seawater intrusion (SWI), a slow and persistent phenomenon that might go on for decades in coastal aquifers. A crucial element in regulating groundwater flow and solute transport in coastal aquifers is the freshwater-saltwater mixing zone. The hydrodynamic behaviour of the mixing zone under various coastal aquifer geometries with physical barriers like cutoff walls has not received much attention, despite its significance. The dynamics of the mixing zone are examined in this study by employing numerical simulations, with particular attention paid to the various bottom opening widths (S) beneath cutoff walls and the inclination angles of the sloping beach coastal aquifers (0°, 15°, 30°, and 45°). Regardless of the aquifer slope, findings demonstrate that smaller bottom opening widths result in greater mixing zones and faster inland SWI. The dynamics of the mixing zone were shown to be significantly impacted by the aquifer slope, with steeper slopes (30° and 45°) allowing for more rapid and extensive SWI than flatter slopes (0° and 15°). The largest and fastest-expanding mixing zones, especially over time, were created by a steep slope and a modest bottom opening size.

Floods are one of the major hazards that negatively affect human life. Computer-aided approaches are crucial to simulate flood events and minimize their negative effects on people's lives and properties. The flood simulation based on fluid flow calculations could help to understand the extensions and depth of previous floods, and it can be helpful to manage future plans regarding flood protection and mitigation scenarios. However, sensitive flood modeling is based on the accuracy of the data used, such as topography, discharge, precipitation, roughness coefficient, etc. In this study, the effect of the Manning Coefficient in 2D flood modeling was tested by using different constant Manning values. Additionally, a Manning Layer was defined based on the land cover data in the 2D model. Land cover data was clipped for the specified region. All models were created using HEC-RAS software. A part of the Hron River, Slovakia, was chosen as the study area. The location of the chosen river part is between the Ziar Nad Hronom and Ladomerska Vieska. The chosen area is a rapidly developing part of Slovakia. The generated models were tested under the same conditions: the same terrain model, the same geometry, and the same discharge values were used in each model. The results of each model were analyzed by using the flood extensions and depth information of the models. According to the outputs of the models, it is seen that the Manning Coefficient is one of the key parameters of 2D flood modeling, and the correct definition of the roughness increases the reliability of the flood models that could help in providing more adequate strategies for flood protection and mitigation. The study is in line with the goal of loss of flood-induced life and economic losses under the heading of sustainable cities and communities within the scope of SDG. In addition, this study has the potential to indirectly contribute to the SDG targets under the title of climate action, “strengthening the resistance and compliance capacity of climate-induced disasters”.

Seawater intrusion (SWI) is a continual challenge that threatens the sustainability of coastal groundwater resources. The behaviour of the seawater-freshwater mixing zone plays a critical role in controlling groundwater quality and solute transport; however, the combined impact of underground dams and sloping beach geometries on seawater-freshwater mixing-zone dynamics remains insufficiently understood. This study investigates the hydrodynamic response of SWI in sloping beach coastal aquifers using numerical simulations with beach inclination angles of 0°, 15°, 30°, and 45°, and under various underground dam heights (Hd). The outcomes indicate that the mixing zone initially expands during the transient stage before shrinking after the seawater intrusion wedge reaches the underground dam. Compared with no-dam conditions, underground dams reduced the final steady-state mixing-zone width and area, while only slightly affecting subsurface groundwater discharge and seawater intrusion length. Increasing dam height produced a narrower central mixing zone and lower subsurface groundwater discharge, whereas its effect on the bottom mixing-zone width was limited. In contrast, increasing the beach inclination angle significantly enhanced seawater intrusion and widened the mixing zone, particularly under steep slopes. Inclined beaches also delayed the time required for the seawater intrusion wedge to reach the dam because of the longer seawater intrusion pathway. The findings demonstrate that aquifer geometry and underground dam configuration strongly control the temporal evolution of seawater intrusion. Proper optimisation of underground dam height is therefore essential for reducing salinity expansion and improving groundwater protection in coastal aquifers. The study provides practical guidance for the design of physical barriers and sustainable groundwater management in vulnerable coastal regions.

Floods represent highly destructive hydrometeorological hazards characterized by unpredictability and severe socio-economic impacts. Flood susceptibility assessment is a primary tool for decision makers and stakeholders in the current climate change context. The main objective of this review study is to conduct a systematic review of flood susceptibility research based on bibliometric analysis. This study uses the Web of Science (WoS) database as a source for bibliometric analysis, and analyzed 618 research articles on flood susceptibility published in this database from 2000 to 2025 to answer the research questions. According to a cumulative analysis of publication volume, an average 14

Regeneration of Slana River flows after and during mining activities involves a combination of environmental restoration practices aimed at restoring the hydrology, water quality, and ecological integrity of river systems that have been degraded by environmental disaster caused by discharge of mine water. The Slana watercourse is a significant landscape forming factor determining the overall development of the natural environment, which has become susceptible to the presence of heavy metals, which are a potential risk factor for aquatic organisms and humans, and therefore it needs to be restored and protected. By restoration of Slana watercourse we mean: (1) restoration of the natural flow regime, (2) improvement of water quality, (3) rehabilitation of aquatic and riparian habitats and (4) stabilization of river banks and sediment control. We consider the protection of the watercourse to include the control of discharged mining waters, as well as regular monitoring of the quality of the watercourse and its sediments. The article presents potential polluters along the Slana River, which can have a significant impact on correct regeneration of Slana River. The environmental situation after the 2022 ecological disaster on the Slana River is alarming even now, and the need for regeneration of the river is increasing more and more.

The evaporation from Lake Nasser is about 12.0 x109 m3/year that could increase due to climate change. Decreasing evaporation losses using floating photovoltaic (FPV) is an important method of conserving water resources and producing energy. This study aims to assess the environmental impact assessment of using FPV to generate electricity and reduce the evaporation losses. The environmental impacts from the installation of solar panels were examined on local microclimate and ecosystems. The key advantages of FPV are the water's cooling effect, helping in maintaining the temperature of photovoltaic panels, the effective reduction in water evaporation caused by photovoltaic system's coverage, and the utilization of excess power production from the light reflected from the water. As a result, FPV systems provide environmental and energy efficiency benefits. Therefore, covering parts of lake Nasser using FPV could be an appropriate solution to decrease the evaporation losses and produce energy.

Integrated hydrological and hydrodynamic models could help in understanding the dynamics of floods and developing effective strategies for flood management and mitigation to diminish the risk to people, communities, and the environment. This study aims to develop integrated hydrological and hydrodynamic models using HEC-HMS and HEC-RAS for flood modeling in the Radiša catchment at Western Slovakia. First, the design flood hydrographs for the Radiša catchment were generated using hydrologic modeling (HEC-HMS). Curve Number (CN) was used as the loss method, and its initial values were estimated based on Corine Land Cover (CLC) data. Design hyetographs were generated with the alternating block technique from intensity duration frequency (IDF) curves, which were estimated by annual maxima analysis (AMA) and simple downscaling of daily precipitation. The results were compared with the hyetographs produced by the regional method and EBA4SUB modelling and AMA of discharge measurements at Bánovce and Bebravou. Afterward, by using the obtained hydrographs, 2D hydrodynamic modeling (HEC-RAS) was performed to analyze the flood extensions of various peak discharge hydrographs. The hydrological results showed that the developed methodology can generate realistic design flood hydrographs for higher return periods, while peak discharges for low return periods are underestimated. In addition, the comparison of different methodologies showed an overestimation of peak discharges when using the AMCIII CN class. Moreover, the regional method was found to give the most consistent results in terms of peak discharges when considering both low and high return periods. The HEC-RAS outputs showed that the area is safe for the 2 and 5-year peak obtained discharge values. However, for higher frequency income discharge values, the dimensions of the river are insufficient to safely transfer the water downstream. Results indicated that accurate hydrological and hydrodynamic flood modeling can help to minimize life and property losses of the catchment.

The article presents the results of a bibliometric analysis of scientific publications on the application of artificial intelligence (AI) in forecasting for renewable energy sources. The analysis covered 2659 publications from 2000–2024 available in the Web of Science database, and the data were processed using the CiteSpace software. The aim of the study was to identify key research trends, authors, institutions and countries that have the greatest impact on the development of this field. The results indicate a growing interest in AI in the energy sector, with an intensive increase in the number of publications after 2010. Key research topics include photovoltaic power forecasting, solar radiation intensity and short-term wind forecasting, and the dominant methods are hybrid models and machine learning algorithms. The analysis highlights countries such as China, the USA and Germany as research leaders. The conclusions emphasize the importance of AI in improving the precision of forecasts, which are crucial for the stability of energy systems in the context of global climate transformation.

This study evaluates the agricultural land suitability of the Guder River Basin, Ethiopia, employing Geographic Information Systems (GIS) to enhance land use planning and agricultural productivity. The assessment focuses on key determinants, including slope gradient, elevation, soil type, soil water content, and proximity to rivers, roads, and towns. Several thematic maps were created, and each map class was assigned weights based on agricultural suitability. Using the “Weighted Overlay Analysis” tool in ArcGIS 10.3.1, these weighted themes were combined to generate a comprehensive suitability map. Results indicate that 2474.08 Km2 (36.42

The changing climatic conditions brought on by global climate change make it crucial to analyze hydrometeorological variations over several decades. Traditional methods of trend investigation may sometimes fall short in identifying current trends in hydroclimatological time series. This research focused on weather stations across Slovakia, specifically in Kosremoveice, Spisske Vlachy, Cremoveerven & yacute; Klaremovesremovetor, and Bardejov. Monthly records of precipitation and maximum and minimum air temperatures from 1971 to 2021 were examined. The Innovative S,en Trend test, a relatively new approach, was applied to analyze trends across the country. The analysis was conducted on monthly, seasonal, and annual scales. Investigations based solely on single stations are often insufficient for accurately determining regional trends. Furthermore, incorporating new yearly data into prior studies may alter recently observed trends. Considering these factors, the study analyzed four separate Slovakian stations using the Innovative S,en Trend test. When mixed trends were observed in the monthly and seasonal analyses for all three parameters, a generally significant increase in annual air temperature trends was noted. For precipitation, stations observed annual increases exceeding 10 % in the higher classes. In terms of maximum air temperature, a 6 % increase was recorded annually at both Kosremoveice and Spisske Vlachy stations. Likewise, Bardejov and Spisske Vlachy showed a 10 % annual increase in minimum air temperature at higher classes, while no significant trends were noted for Kosremoveice.

The main water resources for Egypt are the River of the Nile and groundwater. Evaluating and assessing these vital resources is crucial for liable usage and meeting the growing demand for water. In Assiut area, groundwater stands as the second most significant freshwater source, serving all sectors including industrial sector, agricultural sector, and lastly domestic sector. Unfortunately, the groundwater in Assiut governorate face the imminent threat of contamination, primarily due to agricultural and other activities. A hydrochemical investigation was conducted graphically and spatially within GIS environment in the limestone Eocene aquifer of the designated study area. This research involved the collection and analysis of twelve groundwater samples to realize the physiochemical characteristics, providing insights into the hydrochemistry of the water. The assessment of water quality involved evaluating 16 parameter and comparing them to drinking water and irrigation standards set by both the Organization of World Health (WHO) and the Egyptian Specifications (ES). In this study 8 main parameters are selected due to their importance which are; Electrical Conductivity (EC), pH, Total Dissolved Solids (TDS), Nitrate (NO3-) and Fluoride (F-). The analysis indicates that the groundwater is not entirely suitable for drinking, particularly concerning TDS, Chemical Oxygen Demand (COD), and Total Organic Carbon (TOC). In certain samples, the parameters concentrations surpass the allowable limits defined by both WHO and ES. This is due to the increase in domestic and industrial wastewater discharge the stretch, as well as other harmful anthropogenic activities, and human interventions. GIS-based spatial analysis successfully identified vulnerable areas where groundwater contamination is most severe. Elevated levels of TDS, COD, and TOC were found in several locations, posing risks for domestic use and irrigation. The Piper diagram analysis indicated that the predominant water type is calcium-chloride-bicarbonate, suggesting groundwater is influenced by precipitation and water–rock interactions with carbonate rocks. The Water Quality Index (WQI) analysis was applied, showing that the northern part near the New Assiut Barrage (samples 10 and 11) exhibits a high degree of contamination, making the water unsuitable for drinking according to WHO and Egyptian standards. The findings of this study could help the policymakers to take the suitable action to protect people and animals’ health form contaminated water.

Due to climate change, many towns will face more extreme events like heat waves and heavy rainfall that will affect urban populations. Green roofs and facades offer a promising green infrastructure system to help cities adapt by creating beneficial microclimate. They reduce excessive sunlight, lower temperatures, minimize air and noise pollution and absorb storm water. Urban planners are using more green roofs because European social climate funds make them more affordable despite some limitations such as: maintenance challenges or scalability. The environmental effectiveness of extensive green roofs and facades is presented in temperate climate zone, specifically in Kosice, on building at the Technical University of Kosice TUKE highlighting their energy efficiency and contribution to building sustainability Extensive green roofs at main building of TUKE have a shallow soil substrate with low – growing plants like sedums and mosses. The green facade is installed on the CO storage facility and measures about 4 by 4 m. It uses a hydroponic system for plant growth. The extensive green roof and facade also will serve research and educational purposes for the general public to get to know and experience its environmental and aesthetic benefits firsthand.

Reliable modeling of saltwater intrusion (SWI) into freshwater aquifers is essential for the sustainable management of coastal groundwater resources and the protection of water quality. This study evaluates the performance of four Bayesian-optimized gradient boosting models in predicting the SWI wedge length ratio (L/La) in coastal sloping aquifers with underground barriers. A dataset of 456 samples was generated through numerical simulations using SEAWAT, incorporating key variables such as bed slope, hydraulic gradient, relative density, relative hydraulic conductivity, barrier wall depth ratio, and distance ratio. The dataset was divided into 70% for training and 30% for testing. Model performance was assessed using both visual and quantitative metrics. Among the models, Light Gradient Boosting (LGB) achieved the highest predictive accuracy, with RMSE values of 0.016 and 0.037 for the training and testing sets, respectively, and the highest coefficient of determination (R²). Stochastic Gradient Boosting (SGB) followed closely, while Categorical Gradient Boosting (CGB) and eXtreme Gradient Boosting (XGB) showed slightly higher error rates. SHapley Additive exPlanations (SHAP) analysis identified relative barrier wall distance and bed slope as the most influential features affecting model predictions. To support practical application, an interactive graphical user interface (GUI) was developed, allowing users to input key variables and easily estimate L/La values. Finally, the best-performing model was validated against the Akrotiri coastal aquifer in Cyprus, a realistic benchmark case derived from numerical simulations. The model’s predictions showed strong agreement with reference results, achieving an RMSE of 0.04, thereby confirming its practical applicability. This study highlights the potential of interpretable, optimized ML models to enhance SWI prediction and support informed decision-making in coastal aquifer management.

This study investigates the spatial variability of surface water balance within the Semen Omo Zone in Ethiopia, leveraging data from the Global Land Data Assimilation System (GLDAS) and Empirical Bayesian Kriging (EBK) techniques. The primary parameters analyzed include total precipitation rate (TPR), evapotranspiration (ET), storm surface runoff (SRO), and baseflow groundwater runoff (BF). The study focuses on two scenarios: Scenario I, which considers only surface water components (TPR-ET-SRO), and Scenario II, which incorporates partial groundwater (TPR-ET-SRO-BF). In Scenario I, significant variations in water balance were identified across different watersheds. Watersheds such as WS16, WS15, and WS14 exhibited surplus water, while WS3 showed a notable deficit, indicating insufficient precipitation compared to evapotranspiration and runoff. Scenario II provided a more comprehensive analysis, revealing that watersheds WS17, WS14, and WS6 experienced substantial water deficits when both surface and groundwater components were considered. Conversely, watersheds like WS21 and WS19 were identified as water-efficient areas. The geological context significantly influenced the water balance outcomes. Regions underlain by old crystalline granite schist diorite and marine sediments demonstrated higher water budgets in Scenario I. Scenario II indicated the crucial role these formations play in groundwater recharge and storage. The findings underscore the necessity of integrated water management practices that consider both surface and groundwater resources alongside geological variability. This comprehensive analysis offers valuable insights for policymakers and water resource managers in developing targeted strategies for sustainable water management, ensuring long-term water resource sustainability in the Semen Omo Zone and potentially other similar regions.

Study region: Lake Tana, Ethiopia’s largest freshwater lake, has experienced a notable increase in water turbidity. This issue highlights the need for an in-depth understanding of how human activities and environmental changes are impacting its ecological balance. Addressing these turbidity challenges is crucial for safeguarding the sustainability of this vital resource. Study focus: This research utilized Landsat 8 satellite imagery to examine turbidity levels in Lake Tana. Six bands from Landsat OLI—band 2, band 3, band 4, band 5, band 6, and band 7—were analyzed both individually and in combination. Ordinary least squares (OLS) regression modeling was applied to investigate the relationships between these bands and in-situ turbidity data. New hydrological insights: Our findings reveal that the combined use of specific bands—particularly band 2 + band 5 - band 6—accounted for 87 % of the variance in turbidity as explained by the OLS regression model. Additionally, the Koenker- (Breusch-Pagan) statistic indicated no conflicting relationships (p > 0.005) within the model, affirming its reliability. To further validate the model’s impartiality, the Jarque-Bera test was performed. Polynomial and exponential regression analyses were also conducted, leading to the identification of an optimal regression equation for predicting the spatial distribution of turbidity in Lake Tana.

Expectations for a change in precipitation patterns due to climate change effects make floods one of the main concerns of water authorities. The minimization of the negative effects of floods for a particular region depends on the success of hydrologic and hydrodynamic modeling approaches. In this study, the abilities of two of the most popular flood modeling software, namely, HEC-RAS and MIKE+, were used for flood modeling in the Hron River in Slovakia. For modeling purposes, various discharge values of the River from one year to hundred years peak discharge were considered. The vulnerability of the catchment for each period was modeled and visualized using both software. The HEC-RAS and MIKE + outputs showed that the study area is vulnerable to flood for high-frequency peak discharge values. The outputs of both 2D hydrodynamic approaches were found to be close to each other in various flow conditions. The comparisons of the MIKE + and HEC-RAS showed that Hron River dimensions for the given catchment are only sufficient to transfer a one-year peak discharge value safely. The outputs of the models exhibited that the study area is not safe in case of ten-year peak discharge value and the risk of the floods getting the highest level in case of hundred-year peak discharge. Due to the models’ findings, it is seen that the area is vulnerable to flood, and three different mitigation scenarios were proposed and analyzed including change in river bed dimensions and rise of the levee on the right and left river bank to protect the area from flood risks. After applying these scenarios, the whole area around the river for length of five kilometers is protected from flood risks. The mitigation measures and the proposed scenarios can have significant effects on saving lives and protecting the properties, industrial areas and agricultural lands.