Mohamed Elgamal’s research while affiliated with Imam Mohammad ibn Saud Islamic University and other places

This study examines the scour depth induced by turbulent wall jets and proposes novel mathematical formulations to predict the depth of scouring. Through a comprehensive gamma test, key parameters influencing the scour depth are identified, including the apron length, densimetric Froude number, median sediment size, tailwater level, Reynolds number, and Froude number of the jet. Regression analysis is subsequently conducted to establish relationships between the dependent parameter and the aforementioned independent variables. A comparative analysis is then undertaken between the measured scour depths and those predicted by existing equations from previous studies. Furthermore, predictive models leveraging the support vector machine, artificial neural network with particle swarm optimization, M5 tree algorithm, gene expression programming, and adaptive neuro-fuzzy inference system (ANFIS) are developed using the collected data. Statistical metrics are employed to evaluate the performance of each model and the regression equation. The effectiveness of each model in predicting scour depth is demonstrated. Notably, ANFIS yields a coefficient of determination of 0.809 and a root mean square error (RMSE) of 1.585. Multi-nonlinear regression analysis exhibits a coefficient of determination of 0.752 and an RMSE of 0.421, while the M5 tree achieves a coefficient of determination of 0.739 and an RMSE of 1.874, demonstrating superior performance compared to other machine learning techniques and regression equations employed in this study.

This research aims to examine the performance indicators that are crucial for assessing the implementation of environmental management plans (EMPs) in water projects. To achieve this aim, a questionnaire survey, integrating a systematic literature review (SLR), was used to identify the initial performance indicators. Subsequently, ten interviews with environmental professionals were carried out to uncover additional indicators not identified by the SLR. Following the survey design and pilot study of the survey, the data collection resulted in 112 valid responses from environmental professionals engaged in water projects in Saudi Arabia. The data analysis encompassed reliability tests, mean ranking, normalized mean analysis, exploratory factor analysis (EFA), and partial least squares structural equation modeling (PLS-SEM). The normalized mean analysis highlighted 13 critical parameters among 39 for further investigation. The EFA disclosed three underlying constructs: environmental impact indicators, operational and safety indicators, waste management, and public safety indicators. PLS-SEM was used to validate the relationship between these indicators and the successful implementation of EMPs. The results indicate that all three underlying constructs positively influence the effective execution of such plans. This is the first study to model the relationships of the performance indicators in water projects. The study’s findings underscore the importance of developing precise performance indicators tailored to diverse construction projects that are mainly focused on water facility construction. The identified performance indicators offer significant insights for policymakers, practitioners, and researchers and provide a solid foundation for the advancement of knowledge in the field of environmental management.

Arid regions are susceptible to flash floods and severe drought periods, therefore there is a need for accurate and gap-free rainfall data for the design of flood mitigation measures and water resource management. Nevertheless, arid regions may suffer from a shortage of precipitation gauge data, whether due to improper gauge coverage or gaps in the recorded data. Several alternatives are available to compensate for deficiencies in terrestrial rain gauge records, such as satellite data or utilizing geostatistical interpolation. However, adequate assessment of these alternatives is mandatory to avoid the dramatic effect of using improper data in the design of flood protection works and water resource management. The current study covers 75% of the Kingdom of Saudi Arabia’s area and spans the period from 1967 to 2014. Seven satellite precipitation datasets with daily, 3-h, and 30-min temporal resolutions, along with 43 geostatistical interpolation techniques, are evaluated as supplementary data to address the gaps in terrestrial gauge records. The Normalized Root Mean Square Error by the mean value of observation (NRMSE) is selected as a ranking criterion for the evaluated datasets. The geostatistical techniques outperformed the satellite datasets with 0.69 and 0.8 NRMSE for the maximum and total annual records, respectively. The best performance was found in the areas with the highest gauge density. PERSIANN-CDR and GPM IMERG V7 satellite datasets performed better than other satellite datasets, with 0.8 and 0.82 NRMSE for the maximum and total annual records, respectively. The spatial distributions of maximum and total annual precipitation for every year from 1967 to 2014 are generated using geostatistical techniques. Eight Probability Density Functions (PDFs) belonging to the Gamma, Normal, and Extreme Value families are assessed to fit the gap-filled datasets. The PDFs are ranked according to the Chi-square test results and Akaike information criterion (AIC). The Gamma, Extreme Value, and Normal distribution families had the best fitting over 56%, 34%, and 10% of the study area gridded data, respectively. Finally, the selected PDF at each grid point is utilized to generate the maximum annual precipitation for 2, 5, 10, 25, 50, and 100-year rasters that can be used directly as a gridded precipitation input for hydrological studies.

Assessing the implementation of environmental management plans (EMPs) in construction projects is crucial for meeting environmental sustainability goals and reducing potential adverse impacts. By using performance indicators (PIs), stakeholders can objectively measure the performance of EMP implementation, identifying areas of success and areas that may require improvement. Therefore, this study aims to examine the PIs for assessing EMP implementation in water supply construction projects, using Saudi Arabia as a case study. Data from semi-structured interviews and a systematic literature review were used to develop a potential list of PIs. Then, the PIs were used to create a survey and distributed to industry professionals. Data from 112 respondents were analyzed using mean ranking analysis, the normalization method, exploratory factor analysis (EFA), and fuzzy synthetic evaluation (FSE). Eighteen critical PIs for assessing EMP implementation in water supply construction projects were identified, including public safety, road safety hazards, construction waste, clogged drainage, irregular flooding, the spilling of chemical substances, slope failures, soil erosion, landslide occurrence, increased schedule waste, changes in the color of bodies of water, oil/fuel spills, restricted site accessibility, the smell of run-off water, traffic accidents on construction sites, the spread of disease, changes in the color of run-off water, and overflowing silt traps. The EFA revealed that PIs can be grouped into three underlying constructs: fluid-related indicators, health and safety-related indicators, and site environment-related indicators. The FSE results confirmed that all PIs are between moderately critical to critical. This study’s significance lies in its examination of PIs that aim to improve the environmental performance of water supply construction projects. Understanding which indicators are most effective allows for targeted improvements, helping to minimize negative environmental impacts and ensuring sustainable practices. Finally, this study is a pioneer in examining the critical PIs for assessing EMP implementation in water supply construction projects.

Applying bypass (parallel) flexible tubes made of rubber was studied for the first time, affixed on an uPVC pipeline upstream of a regulation valve, to mitigate water hammer effects by employing simple and readily available tools. Ninety-two experiments were conducted to analyze the influence of the flexible tubes' elasticity Modulus, lengths, and inner volumes. The results demonstrate that implementing bypass rubber tubes substantially reduces the head rise (ΔH), even for shorter tube lengths. The reduction rate of ΔH shows an initial rapid decline followed by a gradual decrease as the tube length increases. Besides, the bypass rubber tube utilization significantly reduced the hammer celerity and increased both the water hammer's characteristic time and the damping rate of the hammer. The elasticity Modulus of the rubber tube exhibits a significant effect on ΔH, displaying a reverse relationship. Finally, ΔH decreases as the inner volume of the rubber tubes increases.

This study deals with the free-surface supercritical flow through a double-right-angled bend (DRAB), which can be found in storm drainage networks in steep terrains. Laboratory experiments showed that strong backwater effects and water-surface oscillations are generated upstream of the DRAB, especially in supercritical flow conditions. This paper investigated the DRAB hydraulic behavior and water-surface heading up (backwater), and oscillations under supercritical flow conditions. Thirty-four lab experiments were conducted with Froude numbers ranging between 1.03 and 2.63. Dye injection and video analysis were used to visually capture the flow structure and to record water-surface oscillations. A tracker package was utilized to analyze the collected visual data. Time series and spectral analysis were used to identify the statistical characteristics of recorded water level time series and the dominant frequencies. It was found that the dominant frequencies of water-surface oscillations upstream of the DRAB range between 1.6 and 4.6 Hz with an average value of about 3 Hz. The Strouhal number of the water-surface oscillations is more sensitive to the Froude number than to the Reynolds number. The Strouhal number ranged between 0.03 and 0.3 for Froude numbers ranging from 2.63 to 1.03. The study confirms that near critical flow conditions exhibit the highest water oscillation, and that the maximum nondimensional water depth upstream of the DRAB is underestimated by both the Grashof formula and Knapp and Ippen (1939) model. A new formula is proposed to estimate the maximum water depth upstream of the DRAB.

Providing an accurate spatiotemporal distribution of rainfall and filling data gaps are pivotal for effective water resource management. This study focuses on the Asir region in the southwest of Saudi Arabia. Given the limited accuracy of satellite data in this arid/mountain-dominated study area, geospatial interpolation has emerged as a viable alternative approach for filling terrestrial records data gaps. Furthermore, the irregularity in rain gauge data and the yearly spatial variation in data gaps hinder the creation of a coherent distribution pattern. To address this, the Centered Root Mean Square Error (CRMSE) is employed as a criterion to select the most appropriate geospatial interpolation technique among 51 evaluated methods for maximum and total yearly precipitation data. This study produced gap-free maps of total and maximum yearly precipitation from 1966 to 2013. Beyond 2013, it is recommended to utilize ordinary Kriging with a J-Bessel semivariogram and simple Kriging with a K-Bessel semivariogram to estimate the spatial distribution of maximum and total yearly rainfall depth, respectively. Additionally, a proposed methodology for allocating additional rain gauges to improve the accuracy of rainfall spatial distribution is introduced based on a cross-validation error (CVE) assessment. Newly proposed gauges in the study area resulted in a significant 21% CVE reduction.