ABSTRACT. Surface water runoff, flash floods, and groundwater recharge in UAE.

ABSTRACT. Integrated Flood Management in the Middle East and North Africa (MENA) Region: Ten Years of Activities of the ISFF

ABSTRACT. Flash floods in Nyamugasani catchment, are recurrent and cause severe damage. However, well-documented scientific information on these flood events is scarce, hindering effective mitigation and management strategies. This study aims to assess and project flash floods in Kinshasa using the Rainfall-Runoff-Inundation (RRI) model, a sophisticated tool for simulating interactions between rainfall, runoff, and inundation. Leveraging high-resolution meteorological and topographical data, the RRI model will be calibrated and validated against historical flood events to predict flood extents and depths accurately. The research focuses on three objectives: (1) mapping flood-prone areas, (2) analyzing the frequency and intensity of projected flash flood events under various climate change scenarios, and (3) assessing the effectiveness of existing flood management infrastructure and proposing enhancements. Geographic Information Systems (GIS) will be employed to visualize flood risks and support decision-making. The Result will provide critical insights into urban flood dynamics, enabling the development of more resilient mitigation strategies. The outcomes will contribute to urban flood modeling knowledge in tropical region and specifically support local authorities and stakeholders in implementing robust flood management and mitigation measures, ultimately reducing the vulnerability of Rwenzori's population to flash flood hazards.

ABSTRACT. Remote Sensing applications in agricultural practices are comprehensively reliable and cover a multidisciplinary fundamental interest on a local and a regional level. Significantly, vegetation indices are the foremost essential remote sensing application in agricultural activities related to vegetation and/or water, particularly in an arid environment. Adequate water resources management plans are based on better fulfilling the water demand and supply equation. This equation is barely achieved in arid environments due to water resources limitations. Remote sensing techniques improve the water resources management schemes using five different water radiometric indices of Sentinel-2. Each of these plays a specific role in the quantification of soil/plant water content based on the interpretation of map surface water features and monitoring the dynamic of surface water. Water radiometric indices interpretation is exercised on the ratio between Red, Near Infra-Red, and Infra-Red bands of Sentinel-2 over the study acquired in 2016. The study areas are located within the main agricultural region of Wadi As-Sirhan. The area is characterized by flourishing agricultural activities. The expansion of the agricultural projects in the designated area demands additional water supply, which is already limited. Water radiometric indices as water indices may help the farmers as well as the decision maker to adopt a more efficient irrigational strategy that saves water and keeps the vegetation unstressed. This technique can be used in similar regions of the Kingdom of Saudi Arabia.

ABSTRACT. In semi-arid climate like the downstream-Mekkera Basin in Northwest Algeria, precipitation is a fundamental component of the hydrological cycle, significantly influencing water availability and ecosystem health. The increasing impacts of climate change on precipitation patterns necessitate a detailed understanding of how these patterns are shifting over time. Such insights are crucial for effective water resource management and planning, especially in regions where water is a limiting factor. This study employs the Innovative Polygon Trend Analysis (IPTA) method to rigorously examine daily rainfall data collected from 12 meteorological stations across the downstream-Mekkera Basin over a 36-year period from 1975 to 2011. The analysis focused on trends in average monthly rainfall, the number of rainy days, daily rainfall intensity, maximum daily rainfall, and the maximum number of dry days per month.The results reveal significant trends in precipitation characteristics. Monthly average rainfall showed contrasting trends between the dry and wet seasons. In spring, there was a marked decrease in precipitation, with maximum daily rainfall declining significantly. Winter months saw a less pronounced decrease in total rainfall but experienced an increase in the intensity of maximum daily rainfall events. Specifically, August and September demonstrated an increase in both total rainfall and the intensity of maximum daily precipitation. The average number of wet days increased, while the maximum number of dry days decreased, reflecting an inverse relationship between these two aspects. These findings highlight the shifting precipitation patterns in the region, underscoring the need for adaptive water management strategies to address the implications of these changes for water resources.

ABSTRACT. The Aflaj system, a subterranean irrigation gallery, utilizes natural techniques to channel water into domestic areas via gravity. This diverse water source is primarily used for domestic and irrigation purposes. However, climate change, characterized by reduced rainfall and increased evaporation, has led to significant surface and ground water shortages, adversely affecting the Aflaj system through drought-induced flow reductions. This research aims to evaluate the Aflaj system under the impact of dam operations, contributing to sustainable water resource management strategies in Oman. The study also considers the impact of significant temperature changes on Aflaj discharges. A comprehensive analysis of Aflaj hydrographs before and after dam construction is conducted, examining changes in flow patterns and their correlation with dam operations. Additionally, the effects of rainfall and rainwater recharge pre- and post-dam construction are assessed. Findings indicate that dam systems enhance the sustainability and consistency of Aflaj flows, even during drought conditions. Data analysis reveals a positive impact on Aflaj discharge rates following dam construction, while highlighting the significant impact of temperature shifts on Aflaj discharges. The study provides recommendations for optimizing dam gate operations and improving dam outlet facilities to maximize Aflaj recharge and minimize water loss. In conclusion, this research underscores the importance of integrated dam systems in maintaining the Aflaj irrigation network and offers scientific suggestions for future improvements and solutions.

ABSTRACT. Groundwater salinization and pollution are widespread processes that degrade water quality and endanger future water exploitation. The problem is intensified in coastal aquifers where human activities result in accelerating water quality deterioration, particularly in arid and semi-arid regions. The elevated salinity can also originate from other natural or anthropogenic processes, such as dissolution of halite and gypsum, evaporation of seawater, etc. In the Sahel region of Northern Tunisia, near the coast, water quantity and quality are major concerns. The Chott Meriem coastal aquifer system is no exception. It is located in a coastal saline wetland along the Mediterranean Sea surrounding the city of Sousse. The aquifer is mainly characterized by high salinity waters compared to the surrounding aquifers. This study applies geochemical analyses to distinguish between the different mechanisms of salinization in order to determine the origin of groundwater mineralization. The Chott Meriem aquifer system consists of a shallow main reservoir, with thickness between 30 and 60 m and consisting of Mio-Pliocene sandstone formations with interbedded gypsum lenses (Segui formation). This shallow groundwater aquifer has a flow direction from inland towards the coast (SW - NE).

ABSTRACT. Dubai is categorized as an arid region, and over the years with the increase of population, the built-up area is also increasing. Due to the specific type of dry climate, rainfall is very scarce. The rainfall event mainly occurs between January and March and intensity of these rainfall is so high that it causes floods. Floods accompanied by thunderstorms in developed cities are hazardous, causing damage to infrastructure. To secure infrastructures, it is important to employ an integrated approach, combining remote sensing, GIS and precipitation data. The model was based on the estimation of an event-based runoff and investigated the relationship between runoff and impervious surfaces. As a first step, the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model was fed with information about precipitation data, slope, soil type, and land use land cover. The results reveal that the subbasins of Deira, Nief and Jumeria have the largest impervious area and, thus, a higher probability of flood occurrence. The model was calibrated and validated based on runoff events and by comparing the observed and simulated streak flow and peak discharge against those reported in previous studies. The model is efficient and can apply in similar regions and can be of great help to hydrologists and decision-makers in Dubai Municipality.

ABSTRACT. Evidence-based research on the effects of rainfall, temperature, and relative humidity variability on maize yield is essential for understanding the climate dynamics and paving the way for in-formed adaptive solutions to future potential negative impacts in Dschang-Cameroon. This study employed the non-parametric Mann-Kendall and Sen’s slope method to detect trends in climate variables and maize yield in the period between 1990 to 2018. The Pearson correlation and Multi-Linear Regression (MLR) analyses were also used to establish the linear relationship between climate variables and maize yield and to explore the behavior of the response variable (maize yield) with the predictor variables (climatic variables), respectively. In addition, the perceptions of climate variability and its impact on maize yield from a hundred farmers were collected through a questionnaire and analyzed in SPSS, while twenty key informants’ interviews (KII) were conducted using a semi-structured interview and analyzed by thematic analysis. The results showed that the minimum temperature exhibited a decreasing trend at a rate of 0.039°C per annum whereas relative humidity had an increasing trend of 0.25% per annum with statistical significance at p= 0.001. In addition, rainfall reveals a decreasing trend at a rate of 4.94 mm per annum, however, with no statistical significance. Furthermore, MLR analysis disclosed that mean temperature and relative humidity have an inversely proportional but statistically significant relationship with maize yield (p= 0.046 and p= 0.001, respectively). The analysis of farmers’ perceptions confirmed the results of trend analyses of decreasing rainfall and increasing maximum temperatures. Moreover, the farmers asserted that the vulnerability of farmers to climate variability is also linked to gender and locality, where women's outputs are more assailable and farms in low-lying areas are more prone to floods. The high price of farm inputs has also been reported as a key factor other than climate variability that hinders the flourishing of the maize sector in Dschang. Finally, the analysis of the KII permitted to unveil the inadequate implementation of flagship agricultural programs in the locality.

ABSTRACT. The global hydropower sector relies on surface water flows of substantial and predictable volume, which makes it vulnerable to climate change. Over 95% of the electricity produced in Malawi is from hydropower in the Shire River, making it the most significant energy source. However, for more than 50 years, the Shire River Basin has experienced an increase in the amplitude and frequency of rainfall fluctuation and extreme weather events, in part, attributed to climate change. This study focused on assessing the risks posed by climatic factors on river flow regimes and their impact on future hydropower production in the Shire River Basin. The study employed Mann-Kendall test and Sen's slope estimator to detect climatic trends in time series data and estimate the magnitude of the trend. Future river flow regimes were analysed using HEC-HMS by integrating future climatic projections data from CMIP6 models under ssp2-4.5 and ssp5-8.5 scenarios. The performance of the climate models was evaluated using the Coefficient of Determination (R2), Nash Sutcliffe Efficiency (NSE), Root Mean Square Error (RMSE) and Percent Bias (PBIAS), Including a Pearson Matrix Scatter Plot for the historical data to check how well the models represented the study area. Similarly, the hydrological model’s performance was assessed using the NSE and R2 of the simulated flows against the observed flows. Flow Duration Curves were used to assess the future impacts of the river flow regimes on hydropower generation at low flow regimes. Mann-Kendall results showed a significant increasing rainfall trend for 68% of the stations in the basin. Minimum temperatures did not show any significant trends, whereas all stations showed a significant increasing trend for maximum temperatures. Both climate and hydrological models showed good performance in representing observed data. Future rainfall patterns indicated a general increase of 13-28% in wetter months, and a decrease in drier months of 3-8% under all scenarios, with a more notable increase in the 2030-2064 period under ssp5-8.5. Future river flow regimes took a similar pattern as rainfall, with a marked increase in all scenarios, but particularly very high under ssp5-8.5 but showing lowest flows in the drier months in the 2030-2064 period. High flows highlight the potential of flooding events in the basin which could affect the hydropower equipment, but could also increase the potential of the sector. Frequency analysis on the low flows, shows susceptibility of the hydropower sector to climate change as it is projected to cause low power generation. The findings from this study underscore the importance of diversifying the energy mix, while protecting the hydropower infrastructure from potential flooding events.

ABSTRACT. Efficient management of water resources is imperative for addressing water stress and mitigating potential conflicts in line with the Sustainable development Goals. This study employs geospatial analysis to assess surface water dynamics in the Ankobra basin of Ghana, estimating water budget components, consumption/withdrawal patterns and demand across all 17 districts and identifies potential conflicts in water-stressed areas using GIS Analytical Hierarchy Process Approach. Terrestrial Water Storage, water demand and consumption, Land use land cover, Soil, Population, and slope were weighted and overlayed to identify the areas where possible conflicts may arise. The average Terrestrial water storage was estimated at 3.87 billion cubic meters (BCM) during the wet seasons, while it decreased to 1.08 BCM during the dry seasons highlighting a substantial seasonal deficit of 2.79 BCM. As of 2022, water abstraction and demand analysis revealed that industrial water use accounts for 74.5% of surface water demand, followed by domestic consumption (16.4%), and agricultural purposes (9.1%), making industrial water withdrawal the highest consumer. Total water consumption and demand were estimated as 68.17Mm3/year and 81.70 Mm3/year respectively. Domestic water demand is expected to rise significantly, reaching 37.21 Mm³ by 2030 and 196 Mm³ by 2063. This is expected to continue in the next five decades, with a water deficit ranging between 15 and 114 Mm3/year. The studies also revealed the vulnerability of the basin in its ability to the pressures resulting from the increase of demand of the identified water users at the horizon of the forecasted period and suggests potential challenges due to high stress, particularly in upstream sub-basins, which might be an indication that grave water disputes are the result of significant land use changes, topographical characteristics, and low water availability, not merely because of water deficits due to upstream water withdrawal. Considerable water use for domestic and industrial uses is expected to occur in the context of tough competition between the other water users whilst potential conflicts between upstream and downstream users were identified.

ABSTRACT. This research mainly dwells on the relationship between methods of irrigation, efficient water use and the sustainability of productivity in selected countries over a period of 10 years from the year 2010 to 2020 in Western Australia and Punjab, Pakistan. We have been able to identify precipitation as one of the most important variables to analyze, given that changes in the volume of water supplied are essential for the development of irrigation in these zones. An investigation of precipitation data provides a lot of information regarding sustainability of water resources. The research also measures the effect of climate change on water availability and demand through an analysis of precipitation and temperature history and future water consumption. These are important findings in view of future outcomes and to recommend measures towards possible impacts of climate variability on sustainable water supply. Besides, prompt evaluation of the crop water requirement and evaporation rates have been made possible by CropWat software. It has also enabled the establishment of Recommended Crop Water Requirements RCWR which are irrigation overviews that also depend on climatic conditions of the planning region. This research does a comparison of flood irrigation, micro irrigation and other high efficiency irrigation practices and evaluates strategies for the reduction of crop water demands and increase in crop yields and thus economic returns. Therefore, the study calls for intensive research on the best practices in Irrigation in as much as the concerns of water resource management and the socio – economic life of the people in these regions are concerned. In that sense, this study adds to the international discussion on sustainable agriculture by identifying each of the areas of study and elucidating the subject matter for policymakers and developers to employ environmentally sustainable and economically feasible agricultural practices.

ABSTRACT. Arid and semi-arid regions show significant variability in rainfall amounts in space and time. Global warming is the key driver in the change of climate that consequently reflects on precipitation in terms of frequency and intensity, particularly in arid and semi-arid regions. This study aims to develop hazard maps over Saudi Arabia (KSA) based on different scenarios such as extreme events, historical maximum floods, and future maximum floods based on observation rainfall data and the D4PDF climate model. We considered different thresholds for rainfall frequency and magnitudes for observing spatial and temporal climatic shifting along with trend analysis using the Mann-Kendall statistic and the S-slope model over the whole Country of Saudi Arabia. The analysis reveals a significant spatiotemporal variability is expected in the future, indicating an increase in precipitation frequency and magnitudes during spring, autumn, and summer. Conversely, there is a significant decrease in precipitation in winter across most regions. In general, the expected monthly change ranges from 45% to 61% in the near and far future. Our important finding was detecting climate shifting with frequencies of extreme events in all seasons. During the wet season (winter and spring), where extreme precipitation shifts to the eastern part of KSA. However, in the dry season, mainly in the summer, the shift is towards the south, while in the autumn, a circular shifting linked with the appearance of drought is observed in the south of KSA. In addition, rainfall indices were generated by estimating the extreme characteristics associated with the intensity of daily precipitation. The analysis reveals that annual rainfall is decreasing in some regions in KSA and the highest decrease was in the Makkah region at (-5.33 mm/year at the 95% level) while Al-BAHA region was increased at (1.65 mm/year at 90% level). We considered different thresholds (10, 20, 30, 40, 50mm) to understand the extremeness of floods. The trend analysis was assessed for the extreme events historically and in the future scenarios. More extreme rainfall events are expected to occur in the central, eastern, and western regions of Saudi Arabia. The results of Hazard maps developed for three regions over KSA (Madinah, Central regions, and Jazan), showed that both Madina and Central regions are expected the same future hazard as historical, however, Jazan show an extreme increase in the hazard impacts more than 200%. Additionally, the RRI Model was applied over the whole KSA to develop a Flood hazard map of 3km spatial resolutions, this can be used as guidance for flood hazard for the decision makers to implement their mitigation measures. Such studies significantly enhance the accuracy of hydrological predictions supporting water resource management systems and a better understanding of the potential impacts of climate change resulting from climate shifting to address their challenges and integrate climate considerations into long-term development strategies aligning with Saudi Vision 2030.

ABSTRACT. Flooding is a natural disaster with extensive impacts, Floods are considered the most destructive natural disasters on the Earth. Recently, severe flash floods have been observed in numerous countries, with an observed increase in their frequency, intensity, and damage attributed to climate change. Floods can be quantified in a variety of methods, including simple empirical procedures, the rational method, the flood frequency method, simplified conceptual, multi-criteria decision analysis, and numerical and geographic information system (GIS)-based hydrodynamic modelling. Traditional flood prediction methods often struggle to accurately forecast flood events due to the complex and dynamic nature of hydrologic and hydrodynamic processes. There is a pressing need for advanced and integrated modelling approaches that can provide accurate, real-time flood predictions and effective risk management strategies. This study is to develop and implement an integrated hydrologic and hydrodynamic modelling framework for enhanced flood risk management. After the review process, two models were selected HEC-HMS and HEC-RAS based on given criteria. The integration of hydrologic and hydrodynamic models such as HEC-HMS and HEC-RAS significantly improves the accuracy and reliability of flood risk assessments. These case studies reviewed validate the models' effectiveness in predicting flood events and identifying vulnerable areas, underscoring the importance of tailored flood mitigation measures for specific regions. Leveraging emerging technologies such as Machine Learning (ML) and Artificial Intelligence (AI) can significantly enhance the precision of flood risk assessment.

ABSTRACT. A Life Cycle Assessment (LCA) study was conducted on a flood protection development project. LCA is a multi-criteria method used to evaluate environmental impacts. In Algeria, floods are considered extreme events, and hydraulic developments are designed to safeguard people and property. Existing literature on warning systems only allows for estimation of socio-economic damage and proposes site-specific technical solutions. This study aims to broaden the scope by considering various potential impacts associated with this damage and protection investments. Infiltration systems, such as Green Infrastructure (GBI) and Low Impact Development (LID), are employed for rainwater management in urban areas. These systems reduce peak flows and runoff volumes, thereby decreasing flood frequency and contributing to groundwater recharge. Methodological choices regarding the functional unit and attribution methods are made. The inventory analysis is conducted using OpenLCA software and the Ecoinvent database. Prospective impacts are assessed by considering both midpoint and endpoint of the cause-effect chain. The investigation concludes with a sensitivity and uncertainty analysis.

ABSTRACT. Flash floods have become increasingly recognized as a severe natural disaster caused by climate change in recent years. The escalation of flood risk is due to a combination of natural and human factors, highlighting the importance of gaining a comprehensive understanding of its spatial dimensions. Effective flood risk management is essential for reducing the impact of floods on both human lives and economic activities. The main aim of this study is to locate and map flood-prone regions in Al Ain City, United Arab Emirates. By analyzing parameters such as elevation, slope, drainage density, lithology, TWI, NDWI, NDVI, soil, land use, and land cover in a GIS environment, an accurate assessment of the risk of flash floods is achieved. Through the categorization of collected data into three classes and the assignment of different weights to each parameter using the analytic hierarchy process (AHP), we can successfully achieve the goals of this study. The AHP technique allows for the integration of various factors into the criteria of hazards and vulnerability. The AHP flood risk map highlights the existence of three distinct risk classes: High to very high, intermediate to high, and low to very low. This underscores the pressing need for the implementation of effective flood mitigation measures to combat future flood events. The findings of this study will be instrumental in informing flood hazard management and mitigation strategies.

ABSTRACT. In light of the escalating challenges posed by water scarcity, particularly in arid and semi-arid regions, the imperative of understanding and effectively managing irrigation needs for the sake of sustainable agriculture cannot be overstated. This study is centered on investigating the adequacy of water supply for meeting irrigation needs within Sudan's Gezira Scheme, a crucial agricultural region grappling with mounting agricultural demands, the impacts of climate change, and urban expansion. Utilizing the analytical capabilities of the Cropwat8.0 model, this research meticulously evaluates the crop water requirements (CWR) and irrigation water demands (IWR) for major crops—cotton, sorghum, sunflower, and tomato—across both summer and winter seasons. The findings underscore significant irrigation needs, such as 1141.9 mm for cotton, 715.6 mm for sorghum during summer, 854.9 mm for sunflower, and 1083.5 mm for tomato in winter. Assuming an irrigation system efficiency of 50%, irrigation schedules are devised to meet these demands. Despite an annual water supply of 11.16 billion cubic meters within the Gezira Scheme, two scenarios highlight varying levels of irrigation demands. In the current area of 169,563 hectares, actual irrigation requirements amount to 2.28 billion m³, with a total net irrigation of 3.22 billion m³ and a total gross irrigation demand of 6.43 billion m³. Expanding to encompass the entire area of 882,000 hectares, these figures notably escalate to actual irrigation requirements of 17.52 billion m³, total net irrigation of 16.73 billion m³, and total gross irrigation demand of 33.46 billion m³. The study underscores that while the current water supply adequately caters to the presently cultivated area, it falls short of meeting the needs of the entire project area. Addressing this disparity necessitates the enhancement of water management strategies, the adoption of modern irrigation techniques, and the implementation of robust conservation measures. These endeavours not only ensure the sustainability of the project but also pave the way for cultivating larger project areas whilst optimizing water usage. Ultimately, these strategies aspire to promote sustainable agricultural practices and fortify food security in Sudan. They furnish invaluable insights for stakeholders engaged in water resource management and agricultural development, directing efforts toward a more resilient and prosperous agricultural landscape.

ABSTRACT. Water resource management is critical for identifying areas at risk of flooding, sources of pollution, and implementing strategies for water quality protection and natural resource conservation. This study in the Wadi Ham watershed in the UAE aims to conduct a spatial analysis of runoff depth to facilitate efficient water management and sustainable planning. Wadi Ham, the largest and longest wadi in the UAE, extends over 30 km from Masafi in the northwest to the Wadi Ham Dam near Fujairah City in the southeast. Wadi Saham and Wadi Farfar also contribute to Wadi Ham Dam. The Soil and Water Assessment Tool (SWAT), a semi-distributed, continuous, physical-based model, was employed to calculate the spatially weighted average annual runoff depth contributions for each sub-basin within the Wadi Ham Dam watershed. Satellite image-derived data, including topographical data, soil data, land use and land cover (LULC), and meteorological data from NASA POWER and CHIRPS, were used to process the SWAT model. Further, the SWAT-CUP software, under the SUFI2 algorithm, identified the most sensitive parameters required for calibration and validation stages. GEOGLOWS ECMWF Streamflow data were incorporated for this analysis. Calibration was conducted for the 2003–2015 period, while validation was performed for 2016–2022. The model's performance wcd2WAas assessed using statistical parameters such as R², NSE, and PBIAS, with results indicating acceptable performance. The spatial distribution of the Annual runoff depth revealed maximum values of 37 mm in sub-basins 2, 9, 10, and 13, and minimal depth in sub-basin 1. These findings suggest that sub-basins with higher runoff depth require immediate water and soil conservation efforts to reduce erosion and improve water retention. The study's outcomes provide valuable insights for water managers aiming to achieve sustainable water resource management in the UAE. The results can inform future policy decisions and guide the implementation of effective water conservation strategies in the watersheds of the UAE.

ABSTRACT. Ground magnetic and Electrical Resistivity tomography (ERT) surveys were applied to investigate the Quaternary aquifer and the structural trends that affected the main characteristics of the aquifer at a pilot area, at Falaj Hazza, Al-Ain city, United Arab Emirates. The total magnetic field and its vertical gradient were recorded using a proton precession magnetometer to cover an area of about 401.122 m2. The acquired magnetic dataset covered 1582 observatory stations along the study area. The data is reduced to magnetic pole. Several magnetic techniques were applied for upward – downward continuation, tilt derivative, Analytical signal High pass and low pass filtering techniques, and spectral analysis to investigate the deep and shallower depths. Moreover, trend analysis for the resulted magnetic maps was carried out to investigate the magnetic anomalies dominant trends which reflected the tectonic and structural trends that affected the aquifer.

Eleven ERT profiles were constructed along the study area based on the results of the magnetic survey using different electrode arrays (Wenner, and Schlumberger) which reflected comparable results. The resultant subsurface true resistivity data were presented in the form of 2D inverted sections and 3D fence diagram. The findings of this study reflected four main dominant structural trends that controlled the study area and affected the main aquifer, these trends mainly trending NW-SE, NNW-SSE, NS and NE-SE respectively. The ERT-Magnetic study, integrated with information obtained from the measurements from the available five wells that projected on the ERT profiles confirmed the deep and shallow structural trends, which was easily interpreted at the same locations of the ERT profiles and accurately matched with magnetic anomalies. The aquifer characteristics reflected the variation of the water depth, water PH, conductivity, TDS and other parameters. The present study provides valuable information for the decision makers about groundwater monitoring and assessment.

ABSTRACT. The Oued Laya aquifer, situated in the Sahel region of Sousse, Tunisia, has faced significant challenges due to groundwater quality degradation and declining piezometric levels, exacerbated by climate change and intensive exploitation. This study provides a detailed analysis of the Oued Laya aquifer through a combination of geochemical and isotopic methods, aimed at understanding groundwater salinization, recharge processes, and vulnerability. The region’s geology, spanning from the Miocene to the Quaternary, reveals a complex structural framework with large synclines and anticlines. The Quaternary deposits dominate the synclines of Oued Laya, while Mio-Pliocene formations are present in the anticlines of Moureddine and Kalaa Kébira. The area is characterized by a stable tectonic platform crossed by the major Kairouan-Sousse fault, influencing the hydrogeological characteristics of the aquifer systems. Hydrogeological studies indicate the presence of two main aquifer types: a shallow unconfined aquifer within the Mio-Pliocene and Quaternary formations, and a deeper confined aquifer in the Miocene strata. Groundwater flows from the anticlines towards the plains and ultimately to the Mediterranean Sea. Piezometric data from 1965 onwards show an average decline of 2 meters, reflecting a 5% reduction in piezometric levels and leading to increased salinity and abandonment of some wells. Geochemical analysis reveals that shallow and semi-deep aquifers have acceptable water quality, whereas deeper aquifers are characterized by poor quality, suitable only for desalination or specialized agricultural use. The salinity in the Oued Laya aquifer is primarily attributed to mineral dissolution (halite and gypsum) and ion exchange processes rather than seawater intrusion. Stable isotope data (δ18O and δ2H) and the absence of significant correlation between Cl− and δ18O exclude major seawater intrusion. The use of isotopes 14C, 13C, and 37Cl has provided critical insights into groundwater age, recharge rates, and sources of salinization. 14C dating shows groundwater ages ranging from 1,750 to over 12,700 years, with recharge rates between 2 and 12 mm/year. δ13C values range from -10.02‰ to -14.6‰, reflecting different carbon sources and processes. The 37Cl isotopic variation (−0.6 to +0.3‰) indicates that near-coastal areas are influenced by seawater, while inland areas are affected by mineral dissolution and ion exchange. The tritium content is low, indicating that most groundwater is old and confirming the significant role of mineral dissolution and ion exchange in salinization processes. The study also highlights the importance of a multidisciplinary approach, combining geological, geochemical, microbiological, and isotopic methods, to accurately assess groundwater quality and vulnerability. A vulnerability assessment using the MI-CI-QI model, integrating quantity and quality controls, reveals that 31.9% of the Oued Laya basin is classified as moderately vulnerable and 68.1% as highly vulnerable. This assessment underscores the necessity of targeted groundwater management strategies that address both the quantity and quality challenges in light of climate change impacts.

ABSTRACT. Water scarcity is increasing due to climate change and rapid population growth. This is driving the need for innovative water resource management solutions. One such promising approach is bio-desalination. Bio-desalination is a biological process that uses algae or bacteria to reduce the salinity of water, offering a sustainable alternative to conventional techniques. In the United Arab Emirates (UAE), drinking water heavily relies on energy-intensive desalination processes such as multi-stage flash (MSF) distillation and reverse osmosis (RO). Therefore, bio-desalination presents a net-zero alternative that addresses both water scarcity and environmental concerns. Furthermore, bio-desalination research is significant for food security as it offers a sustainable solution for desalinating water used in agriculture especially in arid and semi-arid regions, where freshwater resources are limited. This process can support groundwater recharge by reducing the salinity of aquifers, thereby improving the quality of water available for irrigation and other uses. This has significant implications for food security, enabling stable crop production despite the challenges posed by climate change. Therefore, this research aims to be a preliminary study to test the ability of several algae in the desalination of saline groundwater within 3 hours. This study utilizes four distinct algae types: Chlamydomonas, Chlorella vulgaris, Phormidium keutzingianum and Picochlorum oklahomense. The process of determining the desalination rate of groundwater was carried out using immobilization of algae beads. The beads were created by mixing algae concentrate and 5% (w/v) sodium alginate solution in a 1:2 ratio. To stabilize the formed spherical beads, a 4% calcium chloride solution (40g/L) was prepared. The beads were added drop by drop into the calcium chloride solution using a syringe. The beads are left in the mixture for at least one day to ensure stabilization. On the following day, the beads are washed with deionized water and placed in a 250 mL reactor starting the experiment. Samples were taken at 10, 20, 30, 40, 50, 60, 75, 90, 120 and 180 minutes and salt uptake was tested using Ion Chromatography. Results show that the optimum chloride percentage removal was 5.009 and 5.617% at 40 minutes with Chlamydomonas, and Phormidium keutzingianum respectively. Moreover, the optimum chloride percentage removal was 8.693 at 60 minutes and 10.313% at 75 minutes with Chlorella vulgaris, and Picochlorum oklahomense respectively. The results show that the highest removal was achieved using Picochlorum oklahomense. It is noteworthy that the initial salinity of the groundwater significantly influenced the chloride removal rates, as Picochlorum oklahomense was operating at the highest initial chloride concentration of 34 g/L. Following this, Chlorella vulgaris achieved the second-highest removal at an initial chloride concentration of 21 g/L, followed by Phormidium keutzingianum at 17.6 g/L, and Chlamydomonas at 16.7 g/L. This study is the first step into determining the optimum conditions for bio-desalination for applications in water resource management, including enhancing groundwater recharge. Further studies focus on additional algae species, optimizing the starting conditions, scaling up and field trials, and economic and environmental impact assessments.

ABSTRACT. Flash floods are among the most severe natural disasters. With the increasing frequency of extreme rainfall events, more areas are becoming vulnerable to flash floods. Recently, there has been a growing interest in modelling flash floods within the arid regions of the Arabian Peninsula. This paper offers an in-depth bibliometric analysis of research on flash floods and rainfall within the Arabian Peninsula, with the goal of identifying current research trends and future directions. A total of 309 publications, sourced from Scopus between 1975 and 2024, were analyzed using Biblioshiny software. These publications, covering 138 distinct sources, were authored by 659 researchers. The analysis covers key metrics, including publication trends over time, types of publications, citation rates, keyword usage, institutional collaborations, and author contributions. This study identifies significant areas of focus and potential gaps in the literature. Findings reveal that the volume of publications significantly increased around 2010 and that the majority of research has been concentrated in Saudi Arabia. The results will help researchers identify influential studies and authors, understand the development of flash flood research in the Arabian Peninsula, and guide future research to address emerging challenges in this crucial area.

ABSTRACT. Water scarcity and access to safe drinking water are pressing global challenges aggravated by climate change. This research addressed the specific case of Nyala City in West Sudan, where water shortages occur during the summer due to declining groundwater levels. The study was aimed at developing a comprehensive rainwater harvesting system as a potential solution to alleviate water scarcity in the city. The research objectives involved investigating the social and cultural factors that influence the acceptance and adoption of rainwater collection, designing an efficient sand filtration system to ensure water quality, evaluating the effectiveness of the filtration system in eliminating contaminants and pathogens, and analyzing the economic viability of implementing the proposed system. Data for this study were collected through structured questionnaires and interviews conducted with the local community experiencing water scarcity and the relevant staff of the Water Corporation responsible for water supply. Additionally, rainfall data spanning the period of 2011-2020 were obtained from Climatic Research Units (CRU data) and Nyala Shape file from Data-Interpolating Variational Analysis Geographic Information System (DIVA-GIS). The research findings indicate significant variations in rainfall patterns across different regions of Nyala City. These findings were instrumental in informing the design of the rainwater harvesting system, which incorporates five filtration layers, including coarse sand, charcoal, and gravel, to effectively filter and enhance the quality of collected rainwater. To provide practical insights, two case studies were presented: Elshahid Hamza Basic School and a residential house. These case studies illustrated the layout and components of the rainwater harvesting system, emphasizing the integration of plastic tanks and PVC pipes for efficient collection, storage, and distribution of rainwater. Furthermore, calculations were performed to estimate the annual water harvesting potential for the case study buildings based on the roof area and average rainfall. The economic viability of the proposed rainwater harvesting system was analyzed, taking into account the costs associated with materials, installation, and maintenance.

ABSTRACT. Arid regions, characterized by sandy desert terrains, pose significant challenges for accurate flood mapping due to their unique environmental conditions. The extraction of critical satellite data parameters, such as the Backscatter coefficient from Sentinel-1 Synthetic Aperture Radar (SAR) image, is particularly difficult in these areas. This study aims to develop an accurate flood map for the Ain Guezzam region in southern Algeria by utilizing SAR data from Sentinel-1. Satellite images from Sentinel-1 during a flood event was processed using SNAP, including radiometric calibration, speckle filtering, and terrain correction. The initial approach involved extracting histograms for the Backscatter coefficient to differentiate between flooded and non-flooded areas. An alternative approach using an unsupervised classification was implemented, generating clusters to delineate flooded areas. The classical approach of using the Backscatter coefficient to separate water from non-water areas failed due to the sand issue. However, the unsupervised classification method yielded an Intersection over Union (IoU) metric of 60%. This method proved to be more reliable for the region's specific terrain. The study demonstrates the effectiveness of using unsupervised classification methods for flood mapping in sandy desert regions and highlights the need for further refinement in Backscatter coefficient extraction for enhanced accuracy in future analyses

ABSTRACT. This study delves into bio-photolytic hydrogen (H₂) production, focusing on combining indigenous bacteria with microalgae to revolutionize clean energy creation. By effectively regulating oxygen (O₂) levels through bacterial interaction, the research amplifies H₂ production, pivotal in tackling issues associated with sustainable energy, climate change, and greenhouse gas (GHG) emissions. The process's success heavily relies on managing oxygen concentrations to optimize H₂ generation. Through co-culturing indigenous bacteria from activated sludge with Chlamydomonas reinhardtii microalgae, excess oxygen produced by algal cells is efficiently absorbed, triggering the activation of the hydrogenase enzyme in the microalgae, crucial for H₂ production. Leveraging microalgal biomass for hydrogen (H2) production emerges as a leading strategy for generating environmentally friendly, carbon-free energy. The study experimented with various algae-to-bacteria volume ratios, pinpointing the optimal ratio at 1:1.5, resulting in the highest H₂ gas volume of 1162.08 mL L⁻¹ and the lowest O₂ content of 183.3 mL L⁻¹ over a six-day span. Gas production halted as the pH dropped to approximately 4. Initial gas composition analyses at different ratios indicated that H₂ accounted for 25–46% of the total gas volume, CO₂ ranged from 20–40%, N₂ from 5–30%, and O₂ from 1–10%, with no methane (CH₄) detected in any co-culture conditions. The findings highlighted a significant inverse correlation between H₂ production and O₂ consumption, showcasing how the algae-activated sludge co-culture method significantly enhances H₂ gas generation compared to prior studies utilizing fewer bacterial cultures. This research contributes by demonstrating a sustainable pathway to clean energy production that also holds promise for improving water quality and preserving resources. By measuring the COD concentration before and after the process, there was a slight removal efficiency of 6.92% at the best ratio of 1:1.5. Efficiently generating H₂ through microalgae-bacteria co-culturing not only helps reduce GHG emissions but also opens avenues for integrated solutions in energy and water management amidst evolving climate patterns. By stressing the importance of this co-culture technique in optimizing H₂ production effectiveness, the study underscores its potential in advancing clean energy technologies critical for sustainable water management practices amidst climate change uncertainties.

ABSTRACT. Wastewater is heavily loaded with pollutants and various contaminants, which is a problem of the health risks associated with the reuse of purified wastewater, so it must be routed through sewers to wastewater treatment plants in order to be treated. In undertaking this study, an assessment of the chemical physics and bacteriological quality of the raw and purified wastewater at the level of the wastewater treatment plant at L’Allalik (activated sludge process) was identified. The results obtained enabled us to say that the drawdown of pollution parameters such as DBO5, DCO and MES indicate that the aerobic treatment system is very effective, however bacteriological analyses have revealed the presence of fecal coliforms and total coliforms at levels indicating the absence of fecal contamination in the processes of the wastewater treatment plant. Comparison of the results of the analyses of the treated water with the standards revealed that the chemical physics values are acceptable, as well as the bacteriological values are compliant. This indicates that these waters can be used for irrigation. In the light of these results, these wastewater treatment processes can eliminate as much as possible water pollution, in particular bacteriological and chemical pollution, in order to reduce the impact of these nuisances on the environment.

ABSTRACT. The Atlantic plain called “Abda” is an endorheic zone characterized by a weak, undeveloped hydrographic network. The surface water resource is confined to topographic depressions called “DAYA”. The groundwater resource is very deep and generally brackish.The climate is semi-arid with great irregularity in precipitation. Agriculture relies exclusively on rainfall, the annual average of which is around 330 mm. To overcome the problem of drinking water supply, the population uses rainwater collection using underground cisterns commonly called “Metfias”. They are underground cisterns generally having a cylindrical shape with a diameter which decreases from bottom to top, and ends with a coping. The latter protects the “Metfia” and ensures its supply with runoff water through an opening located at its base. However, they have different statuses, dimensions and designs. The study carried out on this old rainwater collection system in the area made it possible to differentiate 3 types according to their locations and that each of them produces a particular quality of water intended for a particular use. We distinguish: •The “Metfias” located outside homes. The water collected there is considered of good quality and reserved almost exclusively for drinking and cooking. It is the water most prized by the population • The “Metfias” which collect roof water. The water is of average quality and is intended for household chores. • The “Metfias” collect rainwater which has washed the soil from homes. The water is of poor quality. It is intended for watering livestock. Water management is a matter for men and women. Men are responsible for maintaining the “Metfia”, cleaning it before each rainy season, and purchasing water during periods of drought. Women are responsible for managing the water in these “Metfias”. This system in no way penalizes the woman or the schooling of the girl. In fact, the quantities brought back from outside “Metfia” (distance not exceeding 200m) are minimal and do not exceed two shuttles per day for a total of 40 liters on average. In terms of hygiene, we note the absence of systematic water treatment leading to health risks for both humans and livestock (the water is loaded with fertilizers, pesticides, heavy metals, germs, etc.) depending on the location of the “Metfias”. We also note that there is a chronological order in the use of rainwater. The populations start by using the waters of the “Daya”, then those of the public “Metfias” and finally their own. The “Metfias” have played a role in stabilizing the population, however there is a lack of effort to raise awareness among the population about the precautions and measures to take before consuming the water.

ABSTRACT. Investigating the hydrogeological condition, the groundwater aquifer and the assessment of the dam efficiency and estimating the probable water leakage through the dam body at Wadi Hadhf area, Hatta city, United Arab Emirates are considered as main objectives of this study. To achieve these goals geophysical Surveys were acquired using ground magnetic method and Electrical Resistivity tomography (ERT) profiles. The magnetic survey covered about 435,457 m2 with total of 615 stations. Magnetic dataset was processed using several techniques, Reduced to pole (RTP), Analytical Signal (AS), Residual- Regional separation (RES-REG), upward and downward continuation, Tilt Derivative (TDR) and others. Interpretation was carried out using all resulted maps. Trend analysis statistics were conducted for all resulted magnetic maps, Indicated the main structural trends along the study area. These trends are oriented as follows NW-SE, N-S, E-W and NE-SW respectively. The magnetic anomalies reflected the structural lineaments. These trends are extended and crossing below the dam site which may cause water leakage below the dam and through the dam body. This will have effects on the dam body and will reduce its efficiency. The geological observation indicated that the fractures, structures, and mineralization lineaments, are showing that the infiltration pathways also through fractures and which are associated with the magnetic anomalies’ lineaments. ERT profile was surveyed behind the dam site to investigate any water leakage through dam using dipole-dipole arrays. The 2D inverted ERT section indicated the water leakage below the dam and confirm the locations of magnetic subsurface faults. Moreover, Four Ground Penetrating Radar (GPR) profiles (Radiograms) were acquired above the dam to investigate through the dam body. It also confirms the dam leakage sites. The magnetic geophysical survey was integrated with ERT profiles surveys that have been acquired behind the dam sides to investigate the groundwater infiltration through the dam. These results will help the decision makers to have a strategic action plan concerning the assessment of the dam and may be applied for many other similar dams’ sites for geophysical assessment of the dam’s efficiency and finding the optimum geometrical design and the taken actions to protect and maintain it.

ABSTRACT. Arid and semi-arid regions are areas characterised by scarce water resources and extreme and variable hydrological conditions in space and time. Furthermore, there is little knowledge available, combined with data scarcity, that can support water resource management in such areas.

The accurate and spatial characterisation of soil is an important element that affects hydrological processes and influences the hydrological response of a watershed. The objective of this study was to produce a digital soil map (DSM) that can support the determination of the hydrological response to spatial extent. The DSM was developed based on a combination of various methodologies including soil auger samples, Landsat surface reflected soil information, remote sensing, digital elevation model, available conventional national soil map, land cover, and expert knowledge.

The research site is a large semi-arid seasonal ephemeral stream ungauged (Wadi) with a catchment area of 7587 km2, named Wadi El Hawad, located within the arid region of central Sudan. We construct a DSM for the catchment with an accuracy of about 73% using scorpan model under a GIS environment. Then, conceptual hydrological soil groups (HSGs) were generated for the Wadi on the basis of the constructed DSM and these soil groups remain beneficial for further hydrological investigations. The constructed DSM has shown good qualitative and quantitative leverage to understand the hydrology of Wadi El Hawad and has provided a good method that could be adopted for other similar catchments.

ABSTRACT. In areas with limited ground-based climate data, such as the Beni–Irumu region in eastern DR Congo, this study utilizes reanalysis data from the CHIRPS database alongside projections from CMIP6 models under the SSP5-8.5 scenario to estimate future rainfall trends. By employing reanalysis methods, the research addresses significant gaps in historical and predictive climate understanding in data-scarce regions. Selected general circulation models (GCMs) were downscaled to a spatial resolution of 0.05° to synchronize with CHIRPS data. The analysis of 32 years of historical rainfall data reveals significant spatial differences, with higher altitudes like Mount Stanley receiving more annual rainfall compared to lower regions, highlighting the influence of orographic factors. Future projections under the SSP5-8.5 scenario predict considerable reductions in rainfall for certain areas, with the most significant near-term decrease expected in Oicha. In contrast, regions like Kasindi/Yihunga are projected to experience more moderate declines. Mid-term projections suggest some areas may stabilize, with slight decreases observed in Bulongo, alongside increases in regions such as Kasindi/Yihunga and Kyavinyonge. Long-term projections indicate overall improvements in rainfall across much of the region, though Oicha remains particularly vulnerable to ongoing challenges. These findings underscore the complex and varied impacts of climate change on rainfall distribution in the Beni–Irumu region, highlighting the pressing need for targeted adaptation strategies, especially in vulnerable areas like Oicha.

ABSTRACT. Precise estimation of precipitation is difficult in areas with intricate orographic terrain, like Fujairah, UAE. The mountainous areas are more susceptible to intense rainfall and flash floods, therefore, there always exists a need to understand the intricate rainfall patterns and their relationship with the geography. Remote sensing applications present a reliable alternative to the scarce rain gauges in such areas. However, their comprehensive validation is essential to ensure their dependability and to accurately represent both the regional variations and temporal changes of precipitation occurrences. The objective of this study is to assess and authenticate three remote sensing precipitation products namely PDIR-Now, ERA5, and IMERG in Fujairah, an area that has not been extensively studied and has distinctive geographical characteristics. The study period spans from 2010 through 2023. Various statistical methodologies were utilized to evaluate the accuracy and preciseness of satellite products such as the Correlation Coefficient (CC), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). In addition, we employed contingency measures, including the Probability of Detection (POD) and False Alarm Ratio (FAR), and extreme indices including Rx1day which is the maximum occurred rainfall in any given day. The investigation demonstrated that ERA5 exhibited the highest level of accuracy, with a correlation coefficient of 0.79 when compared to gauge data. Additionally, ERA5 effectively captured the bulk of rainfall events. IMERG had a correlation coefficient of 0.61, while PDIR-Now had a correlation coefficient of 0.57. Remarkably, with the exception of PDIR-Now, which achieved a success rate of only 37%, the other two products demonstrated a likelihood of more than 74% of accurately detecting rainfall. Nevertheless, the significant False Alarm Ratios (exceeding 75%) seen in all products indicate that they frequently identified false precipitation events. PDIR-Now has shown enhanced accuracy in capturing extreme rainfall indices such as Rx1day. These observations are essential for comprehending the depiction of severe weather phenomena in satellite imagery, particularly in Fujairah's desert mountainous area, where violent, brief storms can result in substantial flash floods and economic damages. Enhancing the precision of satellite precipitation estimates will improve the management of water resources and plans for preparing for floods. This study also offers valuable information to the stakeholders engaged in climate monitoring and disaster prevention in arid areas.

ABSTRACT. This study comprehensively assessed and geospatially analyzed surface water dynamics, including demand, consumption, withdrawal, and availability across all 28 districts in the Tano River Basin of Ghana (TRB). Hydrologic records, site interviews, population census data, and spatial datasets were employed in combination with a geographic information system (GIS) to manually and spatially determine water demand. Several water-use factors were analyzed within the basin, including water yield, Land Use Land Cover Change (LULC), soil, slope, temperature, rainfall, human populations, livestock populations, total water demand, and total water abstraction using the Soil Water Analysis Tool (SWAT) and ArcGIS tools. These factors were weighted and scaled by the analytical hierarchy process (AHP) technique, highlighting their influence on surface water stress potential. The results of the study show that the total current domestic water demand within the basin does not appear to reflect water supplied by the Ghana Water Company Limited. Domestic water demand accounted for 63.87 million cubic meters annually, while the available supply was only 4.8 million cubic meters per year. Additionally, the study uncovered a total estimated water demand of 225.748 million cubic meters per annum in the Tano River Basin, distributed across sectors including irrigation, domestic use, industry, and livestock. Domestic demand is set to increase in the coming years due to population growth in the Tano River Basin. Furthermore, projections for domestic water demand in the years 2030, 2053, and 2063, under various climate scenarios, revealed the substantial influence of climate change on water demand, particularly in relation to temperature variations. With R-squared values of 0.98 and 0.97 for temperature under the RCP 8.5 and RCP 4.5 scenarios, respectively, it is clear that temperature exerts a dominant influence on domestic demand. The Soil and Water Assessment Tool (SWAT) model estimated water yield in the basin with an average water yield of 5 billion cubic meters per year over the past decade. The resulting potential surface water stress maps were derived using a weighted overlay for AHP to classify potential stress zones as having very low (4%), low (15%), moderate (42%), and high stress (40%). The absence of areas classified as "Very High Stress" was a positive indication, suggesting that crisis levels had not been reached.

ABSTRACT. Harvested rainwater is often considered a sustainable water source for various purposes, including domestic use, and has gained increasing attention worldwide, particularly in regions faced with water scarcity. This practice contributes significantly to sustainable development by providing essentially 'free' water to many people. The safety and acceptance of harvested rainwater among consumers in these regions are largely unknown although they are essential for its widespread adoption. This research investigated the public perception of harvested rainwater in Sunyani, examining both users and non-users of rainwater harvesting (RWH) to assess its suitability for potable and non-potable uses. Additionally, it assessed the practices of harvested rainwater users and the quality of the harvested rainwater. Questionnaires were administered to users and non-users of harvested rainwater. Also, samples of harvested rainwater were analyzed for their physicochemical and microbial qualities. The findings revealed that while users of harvested rainwater think it is safe, non-users had counter-views. Most respondents among the users (75.4%) and non-users (47.3%) have heard about the potential risk of harvested rainwater but have in-depth knowledge about it. However, these groups are open to education on RWH. Harvested rainwater users use it for both potable and non-potable purposes. The general physicochemical characteristics of the sampled harvested rainwater were good while microbial qualities were above national standards for potable use. Overall, the results offer significant evidence supporting the advantages of rainwater harvesting and advocate for its increased adoption, particularly in regions lacking or with limited access to public water supplies.

ABSTRACT. Climate change has led to significant increases in global sea levels, which have risen by 21-24 cm from 1880 to 2021. Projections from NOAA suggest that sea levels could rise an additional 25-30 cm by 2050, posing severe risks, especially to coastal areas. This study delves into methods for analyzing sea-level changes, with a particular focus on Geographic Information System (GIS) techniques. GIS has emerged as a powerful tool for integrating spatial data, modeling coastal processes, and assessing the impacts of rising sea levels. This research connects sustainability with sea-level rise by exploring factors such as thermal expansion and ice mass loss, and highlights the importance of using scenarios like Representative Concentration Pathways (RCP) to make accurate forecasts. The study reviews various data sources and index variables, including the Coastal Vulnerability Index, and applies GIS solutions to simulate the effects of sea-level rise. A comprehensive global summary of the number of studies published worldwide is provided, offering insights into the distribution and focus of sea-level rise research. A case study on the Gulf Cooperation Council (GCC) region is included due to its vulnerability as a low-lying coastal area that has experienced significant increases in summer temperatures. The findings of this study enhance the understanding of GIS methods in sea-level rise research, providing valuable information for policymakers and researchers to develop effective strategies for mitigating the impacts of sea-level rise and improving coastal resilience. The global analysis also highlights the pivotal roles of major countries such as the United States and China in advancing research on sea-level change and GIS applications. The study emphasizes the need for targeted strategies in vulnerable regions like the GCC, where rising temperatures and extreme weather events worsen the challenges posed by sea-level rise, highlighting the urgency of addressing these issues.

ABSTRACT. Due to recurrent droughts and a lack of surface and groundwater resources, the semi-arid region of the Borena zone in Southern Ethiopia faces a serious water shortage. This study employs integrated approaches of GIS, Remote Sensing, and climate modeling to evaluate groundwater potential zones and susceptibility to climate change. The research defines groundwater potential zones, identifies critical factors affecting groundwater occurrence and distribution, and examines trends in future precipitation and temperature. Based on the relative contributions of each parameter to groundwater potential, eight thematic layers, such as geology, slope, soil, drainage density, land use land cover, lineament density, drainage density, and topographic wetness Index, were used. With the help of the AHP technique, the groundwater potential zones were delineated by utilizing the model builder tool of ArcGIS 10.8. To understand theimpact of climate change on groundwater resources, the study utilized the Ensemble mean of coordinated regional climate downscaling experiment (CORDEX) Africa regional climate models operating under biascorrected two alternative scenarios of representative concentration pathways (RCP 4.5 and RCP 8.5) for periods spanning from 1990 to 2022 (baseline) and 2031 to 2060 for midterm future scenarios analysis. GCM climate model and ArcGIS were employed for impact assessment and CMhyd tools were used for bias correction and downscaling regional climate models to specific study areas. Results of the groundwater potential assessment indicated that the majority of the study area falls under a good groundwater potential zone which covers 3599.42 km2 or (51.6%) followed by moderate 3311.74 km2 (47.47%), very good 48.80 km2 (0.69%), and poor 15.41 km2 (0.22%) respectively. The southern part of the study area especially, the South-western region, is generally better than the northern and eastern parts in terms of groundwater potential. Geology and rainfall emerge as pivotal factors governing groundwater occurrence and distribution in the study area. Future projections revealed logical increases in temperature and decreased precipitation compared to the baseline under both scenarios. Mean monthly precipitation is found to decrease by 2.82 mm and 2.9 mm in RCP 4.5 and 8.5 scenarios and temperature could increase by 22.9 0c and 23.19 0c in RCP 4.5 and 8.5 scenarios, respectively. This research provides crucial insights for policymakers and water resource managers, within the Borena Zone and Ethiopia as a whole.

ABSTRACT. Coral reefs are a crucial component of ocean ecology and have been increasingly studied for their potential to reduce high-energy flows primarily due to climate change. However, a lack of scientific validation of their ability to do so limits their engineering applications for civilization. In this research, extensive experimental studies were carried out to investigate the capabilities of coral reefs, to reduce high-energy flows caused by climate change impacts such as flash floods, tsunamis, hurricanes, etc. To investigate the mitigative potential of coral reefs, we conducted an experimental study, where our primary objective was to assess the energy reduction of Acropora corals, which are most prevalent in the Arabian Sea, for the reduction in flow energy. Due to marine life preservation, an alternative method was used to mimic real coral reefs by 3-D printing which ensured the accuracy of the surface roughness and the structure of the coral. To investigate the flow characteristics through the coral reef we measured flow velocity and flow depth in front, in between, and at the end of the coral extent using electromagnetic current meters and point gauges. This experiment was carried out on a large-scale flume with steady flow conditions in the Fluids Lab at the United Arab Emirates University. Froude number (Fr) was established as a non–dimensional parameter for test cases. The findings showed that corals reduced flow depth and flow velocity by up to 27.5% and 25%, respectively, near the end of the coral extent. It shows that the total energy head was more influenced by shallower flows for Fr – 1.05 where there is a significant difference between the start and end of coral. The results also showed that the energy loss gradient was highest (-0.5) with shallow flow conditions as Fr – 1.05.The research shows that 3D-printed Acropora corals reduce flow energy effectively, revealing their potential to moderate high-energy marine events in shallow flow contexts.

ABSTRACT. Studying the influence of vegetation dynamics on water storage is crucial for managing ecosystems efficiently in dryland areas. This research employs remote sensing and statistical methods, including multiple linear regression, random forest, the Mann-Kendall test, Sen's slope, and Pearson's correlation to investigate the impact of vegetation growth on Terrestrial Water Storage (TWS) along the China-Pakistan Economic Corridor (CPEC). The results reveal a consistent increase in vegetation cover in semi-arid and dry sub-humid regions, particularly in croplands, from 1986 to 2020. However, a significant finding is the approximately 39.65% decline in TWS in the study area. Conversely, forests have shown resilience by mitigating the effects of climate change and human activities through hydraulic memory effects. Additionally, soil moisture has decreased across various land cover types, with croplands experiencing the most substantial reduction. Increased vegetation growth in greening drylands has significantly negatively impacted TWS, with correlations of -0.31 for terrestrial water storage anomaly (TWSA), -0.26 for root zone soil moisture (RZSM), and -0.29 for surface soil moisture (SSM). Similarly, evapotranspiration (ET) exhibited negative correlations with TWSA, RZSM, and SSM, with standardized coefficients of -0.23, -0.16, and -0.11, respectively. These findings highlight the interaction between the study area's vegetation, land cover, and hydrological dynamics. Addressing these hydrological imbalances is essential for ensuring sustainable ecological management in the region.

ABSTRACT. Understanding the impacts of climate change on snow/glacier cover dynamics is essential for climate adaptation and hydrological management. Despite extensive research, significant gaps remain in understanding snow dynamics in the Rwenzori Mountains due to scarce ground-based data. This study addresses these gaps by integrating MODIS satellite data, CHIRPS and CHIRTS climate reanalyses, and the J2000 model. The objectives were to assess snow cover dynamics from 2000-2022 and validate the J2000 model for future projections under SSP2-4.5 and SSP5-8.5 scenarios. Historical analysis revealed Mount Stanley consistently had higher mean snow cover, with significant temporal and spatial variations. In June, snow cover increases as rainfall decreases on both Mount Baker and Mount Stanley, while in February, there is a significant decrease in snow cover on Mount Stanley with increasing minimum temperature. The J2000 model demonstrated strong agreement with MODIS data (R² = 0.90, RMSE = 0.163, PBias = 1.2%). Future projections indicate notable decreases in snow cover across the mountains, with a modest increase for Mount Baker in the near term. These findings underscore the sensitivity of Rwenzori's snow cover to climate change, providing vital insights for climate adaptation and hydrological management strategies.

ABSTRACT. In light of the escalating challenges posed by water scarcity, particularly in arid and semi-arid regions, the imperative of understanding and effectively managing irrigation needs for the sake of sustainable agriculture cannot be overstated. This study is centered on investigating the adequacy of water supply for meeting irrigation needs within Sudan's Gezira Scheme, a crucial agricultural region grappling with mounting agricultural demands, the impacts of climate change, and urban expansion. Utilizing the analytical capabilities of the Cropwat8.0 model, this research meticulously evaluates the crop water requirements (CWR) and irrigation water demands (IWR) for major crops—cotton, sorghum, sunflower, and tomato—across both summer and winter seasons. The findings underscore significant irrigation needs, such as 1141.9 mm for cotton, 715.6 mm for sorghum during summer, 854.9 mm for sunflower, and 1083.5 mm for tomato in winter. Assuming an irrigation system efficiency of 50%, irrigation schedules are devised to meet these demands. Despite an annual water supply of 11.16 billion cubic meters within the Gezira Scheme, two scenarios highlight varying levels of irrigation demands. In the current area of 169,563 hectares, actual irrigation requirements amount to 2.28 billion m³, with a total net irrigation of 3.22 billion m³ and a total gross irrigation demand of 6.43 billion m³. Expanding to encompass the entire area of 882,000 hectares, these figures notably escalate to actual irrigation requirements of 17.52 billion m³, total net irrigation of 16.73 billion m³, and total gross irrigation demand of 33.46 billion m³. The study underscores that while the current water supply adequately caters to the presently cultivated area, it falls short of meeting the needs of the entire project area. Addressing this disparity necessitates the enhancement of water management strategies, the adoption of modern irrigation techniques, and the implementation of robust conservation measures. These endeavours not only ensure the sustainability of the project but also pave the way for cultivating larger project areas whilst optimizing water usage. Ultimately, these strategies aspire to promote sustainable agricultural practices and fortify food security in Sudan. They furnish invaluable insights for stakeholders engaged in water resource management and agricultural development, directing efforts toward a more resilient and prosperous agricultural landscape.

ABSTRACT. Hydrological modeling plays a crucial role in understanding and managing water resources, and the accurate estimation of river discharge is essential for effective water resource planning and management. The study presents an innovative approach that combines the Soil and Water Assessment tool model with the Machine Learning techniques to generate high-resolution, data assimilated 5km scale precipitation product for the Lower Mahanadi River basin. The study involves the corporation of multiple precipitation datasets i.e., Aphrodite (25km), CHIRPS (25km, 5 km), IMD (25km) and IMDAA (12.5 km) and develop a data assimilated 5 km scale dataset using ML techniques i.e., Random Forest and Support Vector machine. This dataset act as an input in the SWAT model to generate the discharge. To validate the accuracy of the generated precipitation data, a comprehensive statistical analysis has been done in comparison with IMDAA dataset. The results demonstrate the high-level agreement between the both the discharges. The R2 value of 0.80 indicates a strong correlation between the two datasets, implying that the model adequately captures the spatial distribution of the precipitation. Moreover, RMSE value of 20m and NSE value of 0.85 signify the model’s capability to estimate discharge with satisfactory precision. The findings of the study highlight successful integration of machine learning techniques with the SWAT model for improving the accuracy of the precipitation data, consequently enhancing the estimation of river discharge in the Lower Mahanadi River basin. Such enhanced hydrological model can significantly contribute to the better water resource management, flood forecasting and climate change impact assessment in the region. Further advancements in hydrological modeling and machine learning methodologies hold great potential for addressing the water related challenges faced by river basins worldwide.

ABSTRACT. The Kingdom of Saudi Arabia is arid, and rainfall is generally rare. However, the country has recently been facing extremely rare events due to the risks of climate change. The rainfall density is reported to increase in some kingdom places. One of these places is AL-Madinah City, located in the western region of Saudi Arabia. The city has traditionally been dry, and the recent rainfall is a good event for the residents. However, the high rate of rainfall leads to the floods. The drainage systems are crucial for managing rainwater and preventing floods. The city already has catchment areas, some channels, valleys, and drainage networks. These facilities may provide a good base for an effective infrastructure system. In the city, there are many mountains and valleys due to the natural configuration of the ground. For example, one of the largest valleys is Al-Aqiq Valley. The drainage basin of the valley covers an area of 5,130.8 square kilometers. This area extends along a perimeter of 534 kilometers from south to north, with a length of 108.5 kilometers. The elevations within the basin vary, ranging from 2,393 meters at the mountains to 581 meters at the outlet. The drainage basin of the valley has a sufficiently large capacity to handle the water quantities from normal rainfall. However, it should be noted that exceptional weather conditions such as heavy and continuous rainfall can still lead to flooding in valleys, even if they have a large drainage area. This paper collected and analyzed historical rainfall data for AL-Madinah city over decades to determine the factors contributing to rainfall change and flood causes and the required improvements for the current drainage system. PCSWMM software was adopted to analysis the collected data to understand the catchment aeras in the city and to improve the design of the current drainage, infrastructure, floodplain, and sewer network. Analysis results showed inadequate capacity of the current system and recommended some actions to be taken to improve the storm drainage system.

ABSTRACT. Accurate flood risk assessment is crucial for effective disaster management and mitigation, particularly in arid and semiarid environments where water scarcity and extreme rainfall patterns can lead to significant flooding events. Traditional methods for flood risk assessment often rely on limited ground data and coarse-resolution digital elevation models, which can be inadequate for capturing the fine-scale topographic features influencing flood dynamics. This study explores the application of Unmanned Aerial Vehicles (UAVs) equipped with high-resolution cameras to generate detailed 3D topographic models for improved flood risk assessment in semiarid regions.

Using UAV technology, we conducted aerial surveys across an example semiarid river segment located near Pretoria, South Africa to capture high-resolution imagery. Advanced photogrammetric techniques were employed to create accurate 3D topographic models, incorporating both Digital Elevation Models (DEMs) and high-definition orthophotos. These models offer unprecedented detail and precision, facilitating a more nuanced understanding of terrain features such as slopes, drainage patterns, and surface roughness that are critical for flood 2D simulation.

The 3D topographic models were integrated with hydrodynamic simulation tools to assess the flood inundation area under different flow scenarios. Comparative analysis was performed against traditional topographic data sources to evaluate improvements in risk predictions. Preliminary results indicate that UAV-derived models significantly enhance the accuracy of flood risk assessments, particularly in capturing micro-topographic variations that influence water flow and accumulation.

This study highlights the potential of UAV technology to revolutionize flood simulation in semiarid environments, providing more detailed and reliable data for emergency planning and management. The improved resolution of topographic models enables better prediction of flood-prone areas, ultimately contributing to more effective risk mitigation strategies and resilience-building in vulnerable communities.

ABSTRACT. The flow of water through earth dams is of high practical importance for the stability of the structure in case of rising water levels in the upstream reservoir. Of particular interest is the location of water table separating the saturated from the unsaturated zone within the dam, and especially the position, where the water table meets the downstream surface of the dam. The size of the discharge zone below this position is crucial for the dam stability. Dealing with the problem of dam break it is crucial to determine the size of the outflow zone. The problem of the flow through an earth dam is a classical topic for modelling of porous media flow. For 2D cross-sections analytical solutions have been developed for idealized settings concerning geometry and geology. Graphical methods for the construction of flow-nets have been proposed. For complex real-world cases numerical methods have the advantage that specific factors and circumstances, anisotropy and inhomogeneity, can be taken into account. However, analytical solutions are crucial for the verification of numerical models. Various numerical approaches have been used for the problem: finite differences, finite volumes, finite elements and boundary elements. The extended pressure (EP) method modifies Darcy's Law in a way that marginally small values pressure result for positions above the water table. Using the Baiocchi transformation the head distribution in the saturated zone is obtained from a function that obeys modified boundary conditions. Recently authors outline the use the level sets (LS) and extensions, conservative (CLS) and improved conservation (ICLS) for simulation. The numerical manifold method (NMM) is basically a special finite element approach, On can take the entire dam cross-section as model region or restrict the domain to the saturated part only. In the latter case the position of the water table is a free boundary that is a-priori unknown and has to be determined. Various boundary conditions for the free surface have been used: Dirichlet type for hydraulic head or Cauchy type for normal fluxes. In Finite Elements moving adaptive meshes are a common technique for finding the position of the free boundary. If the entire dam is modeled the domain is fixed, but assumptions have to be made concerning the unsaturated zone. Many authors make the assumption that the unsaturated zone is completely dry, while others let the model manipulate the relative permeability directly or indirectly via the water saturation. Recently one finds publications combining Artificial Intelligence (AI) with numerical models. We give a critical review in how far these approaches can be viewed as an advancement of the field. For illustration of some results we present numerical results obtained using COMSOL Multiphysics comparing FE simulations with fixed and with moving geometry. The comparison of the approaches gives important clues for the selection of an appropriate method to model dam through flow. Such models can be important already in the design phase of a dam project. They could also be used for real-time simulations using the varying water table in a reservoir as input parameter.

ABSTRACT. International Commission on Large Dams (ICOLD) has been discussed rehabilitation of aging dams and measures to improve dam safety. On the other hand, there are other important issues such as improving flood mitigation effects under climate change, dealing with extreme droughts, and energy transitions, as well as the introduction of sedimentation countermeasures to extend reservoir life. These can be organized into three S's: dam safety, smart use, and sustainability. Japan Commission on Large Dams (JCOLD) has proposed the necessity of dam upgrading, which encompasses all of these issues, as a way to strengthen dam functionality. In Japan, the number of suitable sites for new dam construction is limited due to various economic, social, and environmental constraints, so the need for effective utilization of existing dams has increased dramatically. One of the effective means of dam upgrading is to expand discharge facilities to increase flood control capacity. Under these circumstances, new technologies have been developed in Japan to drill holes in existing dam body and add discharge facilities. This is usually applied to gravity concrete dams. Naturally, the expansion of discharge facilities was not planned from the initial design, and the additional placement is restricted by existing facilities and their operation. In Japan, it may be difficult to lower the reservoir water level to maintain reservoir water use during dam upgrading work, and construction at higher depths is necessary. Therefore, it is necessary to consider the installation of large-scale underwater temporary cofferdams to regulate floods during dam upgrading work. For this purpose, technology related to the temporary cofferdams on the upstream side is important, and many efforts have been made so far. This is one example to show engineering challenges on dam upgrading. Other methodologies such as dam heightening, modification of existing gates, introducing flood and/or sediment bypass tunnels etc. should be also studied. However, there are still technological gaps to carry out future dam upgrading projects under larger and deeper conditions. At the 2024 ICOLD Annual Meeting in New Delhi, member countries in the Asia Pacific Group discussed these concepts and good practices. This presentation provides a summary of the discussion.

ABSTRACT. Context: The city of Derna, Libya, recently experienced catastrophic flooding resulting from cascading dam failures exacerbated by the rare medicane event, Daniel. This disaster highlights the region's vulnerability to extreme weather phenomena and underscores the need for robust flood management strategies.

Scientific Questions: This study addresses several critical questions: 1- How did the rare Medicane event contribute to the cascading failures of the dams in Derna? 2- What factors influenced the formation and evolution of flash floods in this region? 3- How can post-disaster surveys and numerical modelling findings inform future flood risk mitigation strategies?

Method and Approach: We integrated post-disaster field surveys with advanced numerical modelling. The surveys involved direct interactions with affected citizens and detailed measurements of flash floods in Derna's city centre. The numerical models simulated the dam failures and flood propagation to understand the disaster dynamics comprehensively. Methods included: • Data collection from local authorities and field observations. • Hydrological and hydraulic modelling to simulate dam failure scenarios. • Analysis of sedimentation effects and urban planning deficiencies.

Results and Discussion: Findings indicate that Mmedicane Daniel induced extreme rainfall, leading to the failure of the Wadi Derna Dam and the Mansour Dam. Reservoir sedimentation and inadequate urban planning significantly worsened the flooding, resulting in extensive mud deposits. Numerical models showed peak discharges nearly ten times the dams' designed capacities, highlighting the urgent need for improved dam infrastructure and urban planning to mitigate future flood risks.

Conclusions and Perspectives: The study underscores the critical need for enhanced prediction and monitoring systems, including advanced sensors and community education on flood behaviour and evacuation protocols. Future research should focus on comprehensive flood risk assessments and resilient infrastructure designs to protect urban areas from extreme weather events. This research contributes to the scientific understanding of flood dynamics and emphasizes the urgent need for preparedness and resilient infrastructure.

ABSTRACT. One of the most catastrophic natural hazards around the world is flooding, as they were constantly associated with very high levels of damage. This natural hazard is reported to have a greater reoccurring possibility in recent times. However, flooding in arid and semi-arid climates has received a relatively limited attention in the literature, which means there is a scarcity in data and understanding relating to floods and hydrological processes in arid and semi-arid areas. Such processes include ephemeral river systems, flash flooding, high channel infiltrations and high evaporation rates. Therefore, the aim of this research is focused on studying the effect of channel bed infiltration on flood wave progression in ephemeral systems, where this process is most important. This investigation can lead to a more profound understanding of the flood wave progression, and hence, can support conducting more robust flood risk assessments in both, temporal and spatial terms. Additionally, this realization of ephemeral systems can be essential for local authorities to make highly informed predictions of flood warning systems, effective emergency response, and resilience measures. In order to achieve this aim, a Green-Ampt infiltration model was implemented within the LISFLOODFP hydrodynamic model. The evaluation of the effectiveness of the updated version of the hydrodynamic model was assessed through 4 testing levels of increasing complexity. The case study of the area has been chosen for this research, due to several occurrence of flood that hit the city of Hafr Al-Batin, which caused numerous losses in human life, damage to the public and private properties. Various model scenarios were constructed for the ephemeral wadi system upstream of Hafr Al-Batin, which including different infiltration process representations (none, steady state and variable) and these were used to evaluate the importance of infiltration on the flood wave characteristics. The outcome of this research shows that the Infiltration losses have significant implications on the flood wave propagation characteristics in ephemeral river systems. These includes the extent of the flooded area, the water volume and the flow travel time. These were demonstrated in the study catchment area of Wadi Al Batin in Saudi Arabia. The conclusion from this study is that applying the spatial variable Green-Ampt infiltration losses is necessary in ephemeral systems and will provide more robust hydrodynamic modelling for use in the flood risk assessments in these systems.

ABSTRACT. Recent, 2024, flash floods in GCC countries and Russia caused numerous failures of earthworks (levees, embankments) with multibillion damage to the areas protected by these hydraulic structures. Forensic studies of earlier collapsed earth-filled dams provide evidence of significant alteration to the porous matrix of earth-filled embankments, especially of their Terzaghi’s type drains, which are originally designed and constructed for preventing the outcrop of the phreatic surface on the slope of the tailwater. Moreover, the designed safety factors of earth dams did not consider a dramatic change of the heterogeneity pattern in aged structures as compared with juvenile ones. The morphing of hydraulic properties of old dikes and levees is driven by suffusion, colmation, and piping, which are physically like the process of lessivage, illuviation, and eluviation in morphogenesis of soil profiles. The difference is in the time scale (years in man-made dams versus decades-centuries in natural soils), dimensionality (always 2,3-D translocation of fine soil fractions in dams versus often 1-D one in soil profiles), and consequences (always negative for dam engineers). In our presentation, we investigate a toe (blanket) drain, which is originally made of unclogged gravel. Geometrically (in a vertical cross-section), the unclogged gravel makes a thin rectangle (the so-called Zhukovskii’s slot), which is placed on an impermeable foundation of the dam. The slot acts as a perfect drain (Numerov’s flow regime). In an aged dam, the toe drain gets coated (clogged) by fine particles. The sheath of these particles is deposited on top of the drain creating a hydraulic barrier to seepage. Also, high hydraulic gradients in the vicinity of the slot drive the fine particles into the body of the coarse filter material such that “internal colmation” takes place. We model the seepage flow using HYDRUS2D and illustrate the difference in the position of a phreatic surface and the seepage flow rate between a “perfect” toe drain and a clogged one. We also detect zones of very high magnitudes of Darcian velocities in the vicinity of “triple points” (e.g. contacts between the embankment soil, the filter material and embankment’s base). In simulations, a FEM-meshed Richards’ equation for a saturated-unsaturated 2-D flow is used in a composite polygon. The flow domain consists of 2, 3 and 4 materials with contrasting Van Genuchten soil hydraulic properties. Clogging causes a seepage face on the downstream boundary that is accompanied by a decrease in the flow rate and of the magnitudes of the specific discharge vector on the interfaces of the Terzaghi’s layered filter. Near the “sharp wedges” inside the flow domain “concentrated” gradients remain high, similarly to non-standard layering in hydromorphic soil profiles examined by Kacimov and Al-Ismaili (2023) for descending infiltration fluxes.

Acknowledgement. This work was supported by Sultan Qaboos University grants DR\RG\17, IG/AGR/SWAE/22/02, IG/AGR/SWAE/22/1 and by the Russian Scientific Foundation, interdisciplinary project no. 23-64-10002.

ABSTRACT. This study discusses the current issues associated with dam sedimentation and presents our achievements in overcoming these obstacles for the long-term sustainable management of sediments in dry reservoirs. Sedimentation in Wadi systems poses multiple issues, including as reducing the storage capacity of reservoirs, impacting groundwater recharge, elevating the risk of flash floods, and causing environmental consequences downstream. Two field investigations were done, one in November 2023 and another in May 2024, to investigate sedimentation issues and their effects on the reservoir's capacity. Evidently, the majority of the dams in Fujairah city are experiencing overflow of water as a result of sediment accumulation. The Revised Universal Soil Loss Equation (RUSLE) model was employed to calculate the amount of soil loss in the catchment area caused by erosion. The model was utilized in combination with GIS, remotely sensed data and ground observations. The anticipated annual soil loss in the catchment ranges from 0 to 50 tons per hectare per year (t/ha/year). The annual deposition into the dams of Fujairah City has led to a significant reduction in their capacity due to sedimentation. Analyzed metrics for water quality in the dams were pH, total dissolved solids (TDS), electrical conductivity (EC), and salinity. A robust positive correlation between sediment yield and water quality measures has been confirmed. The sediment production at the Wadi Ham dam location indicates that the total dissolved solids (TDS) levels in both the water and sediment are elevated. The water quality data obtained from Wadi Ham dam indicates a progressive decline in water quality, primarily attributed to the deposition of sediment within the dam. The study determined that sedimentation has an impact on the water quality of water sources.

ABSTRACT. The utilization of remote sensing technologies for the observation of land cover characteristics plays a crucial role in the management of natural resources. This study was conducted along the coastline of Umluj City, located in the western region of Saudi Arabia, which is recognized as one of the country's most vulnerable wetland ecosystems. The mapping of sedimentation in shallow coastal areas proves inadequate when relying solely on passive remote sensing imagery, primarily due to the necessary image corrections and the impact of weather conditions. In this research, Sentinel-1 imagery from the European Space Agency was employed to analyze and delineate the sedimentation processes. The synthetic aperture radar (SAR) images utilized were sourced from the S1-A satellite, characterized by an Interferometric Wide (IW) acquisition mode and a spatial resolution of 10 × 10 meters. The images obtained were ground range detected and featured dual-polarization in both vertical-vertical (VV) and vertical-horizontal (VH) configurations. An archival image was captured in August 2018, while a subsequent image, taken in March 2019, documented the aftermath of an atypical rainfall event in the area. The study applied remote sensing methodologies for sedimentation mapping and change detection to assess the sedimentation dynamics and their effects on wetland ecosystems. Findings indicated a significant reduction of approximately 87% in wetland habitats due to flash floods occurring between November 2018 and March 2019, alongside a notable increase of around 171% in sediment deposits along the shoreline. Consequently, the ongoing monitoring of shoreline sedimentation and wetland habitats through temporal remote sensing data emerges as a critical priority for informed decision-making aimed at conserving natural resources in similar arid regions.

ABSTRACT. This study uses remote sensing and machine learning to classify buildings according to their age and integrate this information into the generation of a comprehensive flood-hazard map. Knowledge about building age is crucial for taking preventive measures to reduce the impact of natural disasters such as earthquakes and floods. Traditional field methods for obtaining these data are time-consuming, costly, and inefficient. In addition, although cadastral records often include information about the construction dates of buildings, some dates may have been missed and some buildings may have been demolished or rebuilt. Moreover, accessing these records is sometimes problematic. In contrast, remote sensing provides a viable alternative for deriving the ages of buildings with sufficient accuracy for many applications, such as the generation of hazard maps. The availability of free historical satellite images from and the United States Geological Survey and the European Space Agency’s Copernicus Programme facilitates the generation of building age maps. In the present study, we coupled building age with elevation, topographic wetness index, topographic positioning index, land use and cover, curve number, population density, valley locations, and geology to produce a comprehensive flood-hazard map. We combined all these parameters using weighted overlays, and the resulting flood-hazard map clearly identified the regions of high flooding risk in Al Ain city. The overall pattern of flood-risk reveals that a considerable portion of the area (61%) is classified as low risk, with 32% falling into the medium-risk category, 5% falling into the high risk category, and the rest being either very high or very low. The resulting ability to identify vulnerable buildings in advance can help significantly in mitigating their natural-hazards risks, retrofitting buildings as appropriate, and saving lives and money.

ABSTRACT. Excessive scour around the bridge piers during flood leads to tilting and sinking of the pier foundation and finally its failure. The collapse of a bridge over the Kosi River in Bihar on July 24, 2020, was due to severe scouring around its piers. It also worsened the flood due to obstruction of the river flow. Similarly, the Silver Bridge which had collapsed on December 15, 1967, was due to scouring and instability of the piers. Flood can thus trigger the souring by undermining the structural integrity of bridges and other hydraulic structures. The present study focused on the scour around wide piers. The National Highways Authority of India (NHAI) is constructing Delhi-Dehradun Economic Corridor, a major infrastructure project aimed at enhancing connectivity between the two cities. This corridor passes through the Shiwalik Reserve Forest in Saharanpur District, where an elevated section is being built over the Mohand Rao River. The alignment of this elevated corridor follows the riverbed or runs along its banks. A key aspect of this construction involves ensuring the stability and safety of the bridge piers, with a particular focus on the issue of scour. This study covers measurement of scour around the wide piers of the corridor. Systematic data collection was carried out to assess the extent of scour under various flow conditions using advanced instrumentation. The measured scoured depth around the piers was compared with computed one by the existing equations of the scour depth. The analysis revealed the computed scour depth by various equations are comparable to the observed value. However, there is a needful of further improvements in the existing equations as some equations overestimate and some equations under-estimate the scour depth. These findings contribute to a better understanding of scour dynamics and offer valuable insights for the design and maintenance of bridges within the Delhi-Dehradun Economic Corridor.

ABSTRACT. Groundwater storage (GWS) is a vital water resource in arid regions such as Northern Oman, where precipitation is both scarce and unpredictable. This study utilizes Remote Sensing (RS) technologies to estimate groundwater recharge using data from the Gravity Recovery and Climate Experiment (GRACE), the Global Land Data Assimilation System (GLADS), and the Global Precipitation Measurement (GPM) mission, covering the period from January 2003 to April 2024. GRACE monitors changes in terrestrial water storage (ΔTWS) while GLADS offers crucial information on land surface water processes, such as soil moisture, and GPM tracks rainfall patterns. A major flash flood event over Al Hajar Mountains on April 2024, significantly increased GWS from 298.67 mm to 377.05 mm, marking a rise of 78.32 mm, according to GLADS. The analysis reveals that GWS tends to increase following significant precipitation events but gradually declines during extended dry spells due to limited recharge and potential over-extraction. Furthermore, the ΔTWS estimation from GRACE demonstrated a declining trend over time. This research supports the understanding of the relationship between precipitation and groundwater dynamics in the area, providing valuable insights for groundwater resources management in Oman. The findings highlight the effectiveness of integrating remote sensing datasets such as GRACE, GLADS, and GPM to manage groundwater in arid environments, presenting a model approach for addressing water scarcity challenges

ABSTRACT. This paper introduces a method for early forecasting of heavy rainfall that causes flash floods, particularly in arid regions. By creating heatmaps to visually represent the rainfall intensity and uncertainty of each ensemble member, this method enables the detection of heavy rainfall events five days in advance with low uncertainty.

In Japan, the Global Ensemble Prediction System (GEPS) is utilized to effectively conduct hydropower generation in dam reservoirs. The need for longer-term forecasts beyond the traditionally used 84-hour model (GSM) has driven this development. While GSM is effective for short-term predictions, its practicality decreases significantly over longer periods due to increased uncertainty. To address this, GEPS is employed.

Rainfall intensity time series values of ensemble members are visualized in the form of heatmaps, enhancing the understanding of rainfall intensity and its uncertainty for dam management officials. The effectiveness of this method was demonstrated in April 2024 when GEPS accurately predicted heavy rainfall leading to a flash flood in the UAE five days in advance. The capability for early detection of heavy rainfall events is crucial for managing flood risks and improving response times.

The application range of this system extends beyond Japan, proving useful for predicting flash floods in the Middle East and North Africa, as well as heavy rainfall due to monsoons in South Asia. Additionally, we have developed a web-based system to monitor rainfall forecasts and actual rainfall worldwide. This system integrates GEPS rainfall forecasts with real-time satellite precipitation observations (GSMaP), providing data for approximately 600 locations worldwide, including major cities and capitals.

ABSTRACT. Oman has been under the threat of severe storms and cyclones over the past two decades, such as the Mekunu Cyclone in 2018 and the Shaheen Cyclone in 2021 that caused destructive effects on both human lives and the country's economy. Wilayat Al-Khabourah was the city most impacted by Shaheen Cyclone in Oman and received destructive flash floods that affected the region's residents for weeks by flooding entire homes where only rooftops could be seen. These reoccurring natural disasters illustrate the need for effective and urgent management strategies in Oman that are based on accurate flood hazard assessment. This study utilizes Machine Learning (ML) as a main tool for flood hazard assessment in Al-Huwasinah basin in Al-Khabourah, Oman (about 945 km2). The flood inventory data (113 flood points and 50 non-flood points) has been mainly collected from the Omani Government in addition to open-source satellite data. Spatial analysis and GIS tools have been used to extract the critical topographical and geomorphological indices well-known as controlling factors of flash floods in arid regions. Those parameters, in addition to the training and testing data, were integrated to evaluate 42 different ML models. The accuracy of the models ranged from 41.7% for the Gaussian Naive Bayes model to 85.3% for the GentleBoost Optimizable Ensemble model. The most accurate model was then applied to the whole basin to predict a flood risk map that shows flooded and non-flooded areas across the whole basin. The flood map showed consistent results at upper and lower streams when compared to actual images of the flooding that the state experienced during the 2021 Shaheen floods. The results of this study highlight the potential of machine learning and geospatial data in predicting flood-prone areas. By identifying the critical factors influencing the occurrence of flash floods and their severity using advanced computational tools, more timely and accurate warnings could be provided, making Oman more prepared for disasters and aiding in the evaluation of the condition and what action to take.

ABSTRACT. Desert environments are predominantly shaped by wind rather than water. They lack the defined watercourses and flow gauging stations typically used for calibrating rainfall/runoff models. This study leverages rainfall data from the 16 April 2024 flood event in Dubai, United Arab Emirates (UAE), to evaluate alternative calibration techniques in a mesh based hydrodynamic model called ANUGA. During this flood event, rainfall distribution was uneven across the contributing catchments, as observed by the data published by National Center of Meteorology (NCM) in UAE. Bias corrected satellite-based rainfall data (GsMAP from JAXA) is used to set up a regional ANUGA 2d hydraulic model. The model assesses two alternate digital elevation datasets: the AW3D30 dataset from JAXA and the FABDEM1.2 datasets from the University of Bristol. The model predicted flow paths and ponding areas across the catchment. Calibration targets include the flood inundated areas extracted from Landsat 9 and Sentinel-2 true color and Normalized Difference Water Index (NDWI) imagery indicating ponded areas and eroded overland flow paths, together with photographs and reports from social media and news agencies. The study compares two calibration methods: a simple initial-continuing loss model applied to rainfall and the Horton infiltration method applied to the runoff, adjusting the model to match observed surface water extents and durations.