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M. M. Sherif
National Water and Energy Center, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates

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Journal article
Published: 24 May 2021 in Sustainability
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In planning and managing water resources, the implementation of optimization techniques in the operation of reservoirs has become an important focus. An optimal reservoir operating policy should take into consideration the uncertainty associated with uncontrolled reservoir inflows. The charged system search (CSS) algorithm model is developed in the present study to achieve optimum operating policy for the current reservoir. The aim of the model is to minimize the cost of system performance, which is the sum of square deviations from the distinction between the release of the target and the actual demand. The decision variable is the release of a reservoir with an initial volume of storage, reservoir inflow, and final volume of storage for a given period. Historical rainfall data is used to approximate the inflow volume. The charged system search (CSS) is developed by utilizing a spreadsheet model to simulate and perform optimization. The model gives the steady-state probabilities of reservoir storage as output. The model is applied to the reservoir of Klang Gates for the development of an optimal reservoir operating policy. The steady-state optimal operating system is used in this model.

ACS Style

Sarmad Latif; Suzlyana Marhain; Shabbir Hossain; Ali Ahmed; Mohsen Sherif; Ahmed Sefelnasr; Ahmed El-Shafie. Optimizing the Operation Release Policy Using Charged System Search Algorithm: A Case Study of Klang Gates Dam, Malaysia. Sustainability 2021, 13, 5900 .

AMA Style

Sarmad Latif, Suzlyana Marhain, Shabbir Hossain, Ali Ahmed, Mohsen Sherif, Ahmed Sefelnasr, Ahmed El-Shafie. Optimizing the Operation Release Policy Using Charged System Search Algorithm: A Case Study of Klang Gates Dam, Malaysia. Sustainability. 2021; 13 (11):5900.

Chicago/Turabian Style

Sarmad Latif; Suzlyana Marhain; Shabbir Hossain; Ali Ahmed; Mohsen Sherif; Ahmed Sefelnasr; Ahmed El-Shafie. 2021. "Optimizing the Operation Release Policy Using Charged System Search Algorithm: A Case Study of Klang Gates Dam, Malaysia." Sustainability 13, no. 11: 5900.

Journal article
Published: 09 April 2021 in Scientific Reports
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Rivers carry suspended sediments along with their flow. These sediments deposit at different places depending on the discharge and course of the river. However, the deposition of these sediments impacts environmental health, agricultural activities, and portable water sources. Deposition of suspended sediments reduces the flow area, thus affecting the movement of aquatic lives and ultimately leading to the change of river course. Thus, the data of suspended sediments and their variation is crucial information for various authorities. Various authorities require the forecasted data of suspended sediments in the river to operate various hydraulic structures properly. Usually, the prediction of suspended sediment concentration (SSC) is challenging due to various factors, including site-related data, site-related modelling, lack of multiple observed factors used for prediction, and pattern complexity.Therefore, to address previous problems, this study proposes a Long Short Term Memory model to predict suspended sediments in Malaysia's Johor River utilizing only one observed factor, including discharge data. The data was collected for the period of 1988–1998. Four different models were tested, in this study, for the prediction of suspended sediments, which are: ElasticNet Linear Regression (L.R.), Multi-Layer Perceptron (MLP) neural network, Extreme Gradient Boosting, and Long Short-Term Memory. Predictions were analysed based on four different scenarios such as daily, weekly, 10-daily, and monthly. Performance evaluation stated that Long Short-Term Memory outperformed other models with the regression values of 92.01%, 96.56%, 96.71%, and 99.45% daily, weekly, 10-days, and monthly scenarios, respectively.

ACS Style

Nouar AlDahoul; Yusuf Essam; Pavitra Kumar; Ali Najah Ahmed; Mohsen Sherif; Ahmed Sefelnasr; Ahmed Elshafie. Suspended sediment load prediction using long short-term memory neural network. Scientific Reports 2021, 11, 1 -22.

AMA Style

Nouar AlDahoul, Yusuf Essam, Pavitra Kumar, Ali Najah Ahmed, Mohsen Sherif, Ahmed Sefelnasr, Ahmed Elshafie. Suspended sediment load prediction using long short-term memory neural network. Scientific Reports. 2021; 11 (1):1-22.

Chicago/Turabian Style

Nouar AlDahoul; Yusuf Essam; Pavitra Kumar; Ali Najah Ahmed; Mohsen Sherif; Ahmed Sefelnasr; Ahmed Elshafie. 2021. "Suspended sediment load prediction using long short-term memory neural network." Scientific Reports 11, no. 1: 1-22.

Journal article
Published: 22 March 2021 in Water
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To study the temporal and spatial variations of the groundwater quantity and quality in response to intensive groundwater exploitation from the Quaternary aquifer in UAE, a water budget model with a cell size of one km2 was developed. The available historical records of groundwater levels and salinity have been used to develop the water table and salinity maps of UAE for the years 1969, 2005, 2010, and 2015. The available water resources and soil information system was used to facilitate validity, cogency, and consistency of the groundwater analysis. The spatial analysis module of GIS was used to define the aquifer setting, saturated thickness, aquifer base elevation, effective porosity, and groundwater salinity at each grid cell. The obtained results indicated that the volume of fresh groundwater resources in the Quaternary aquifer in UAE has decreased from 238 km3 in 1969 to around 10 km3 in 2015. A major part of these depleted fresh groundwater resources was replaced by brackish water, and, therefore, the total groundwater storage in this aquifer has only decreased from 977 in 1969 to 922 km3 in 2015, respectively. If the same groundwater exploitation continues, the freshwater storage in the surficial aquifer might be totally depleted in agricultural areas. Most probably, the brackish groundwater resources will be exploited. In such areas, more attention should be devoted to the management of brackish water resources to avoid the exacerbation of the saltwater intrusion problem. Despite the fact that the obtained results indicate the negative impacts of the improper water resources management in a small part of the arid area, the learned lessons are valid for other arid countries, in particular, using the proper steady state boundary conditions for the initial conditions in modeling the available future management alternatives.

ACS Style

Mohsen Sherif; Ahmed Sefelnasr; Abdel Ebraheem; Mohamed Al Mulla; Mohamed Alzaabi; Khaled Alghafli. Spatial and Temporal Changes of Groundwater Storage in the Quaternary Aquifer, UAE. Water 2021, 13, 864 .

AMA Style

Mohsen Sherif, Ahmed Sefelnasr, Abdel Ebraheem, Mohamed Al Mulla, Mohamed Alzaabi, Khaled Alghafli. Spatial and Temporal Changes of Groundwater Storage in the Quaternary Aquifer, UAE. Water. 2021; 13 (6):864.

Chicago/Turabian Style

Mohsen Sherif; Ahmed Sefelnasr; Abdel Ebraheem; Mohamed Al Mulla; Mohamed Alzaabi; Khaled Alghafli. 2021. "Spatial and Temporal Changes of Groundwater Storage in the Quaternary Aquifer, UAE." Water 13, no. 6: 864.

Journal article
Published: 23 January 2021 in Sustainable Computing: Informatics and Systems
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Evaporation from sub-surface reservoirs is a phenomenon that has drawn a considerable amount of attention, over recent years. An accurate prediction of the sub-surface evaporation rate is a vital step towards drawing better managing of the reservoir’ water system. In fact, the evaporation rate and more specifically from sub-surface is considered as highly stochastic and non-linear process that affected by several natural variables. In this research, a focuses on the development of an Artificial Intelligence (AI) model, to predict the evaporation rate has been proposed. The model’s input variables for this model include temperature, wind speed, humidity and water depth. In addition, two AI models have been employed to predict the sub-surface evaporation rate namely: Generalized Regression Neural Network (GRNN) and Radial Basis Function Neural Network (RBFNN) as a first attempt to utilize AI models in this topic. In order to substantiate the effectiveness of the AI model, the models have been applied utilizing actual hydrological and climatological in an arid region, for two soil types: fine gravel (F.G) and coarse gravel (C.G). The prediction accuracy of these models has been assessed through examining several statistical indicators. The results showed that the Artificial Neural Networks (ANN) model has the capacity for a highly accurate evaporation rate prediction, for the subsurface reservoir. The correlation coefficient for the fine gravel soil, and coarse gravel soil, was recorded as 0.936 and 0.959 respectively.

ACS Style

Ammar Hatem Kamel; Haitham Abdulmohsin Afan; Mohsen Sherif; Ali Najah Ahmed; Ahmed El-Shafie. RBFNN versus GRNN modeling approach for sub-surface evaporation rate prediction in arid region. Sustainable Computing: Informatics and Systems 2021, 30, 100514 .

AMA Style

Ammar Hatem Kamel, Haitham Abdulmohsin Afan, Mohsen Sherif, Ali Najah Ahmed, Ahmed El-Shafie. RBFNN versus GRNN modeling approach for sub-surface evaporation rate prediction in arid region. Sustainable Computing: Informatics and Systems. 2021; 30 ():100514.

Chicago/Turabian Style

Ammar Hatem Kamel; Haitham Abdulmohsin Afan; Mohsen Sherif; Ali Najah Ahmed; Ahmed El-Shafie. 2021. "RBFNN versus GRNN modeling approach for sub-surface evaporation rate prediction in arid region." Sustainable Computing: Informatics and Systems 30, no. : 100514.

Research article
Published: 01 January 2021 in Engineering Applications of Computational Fluid Mechanics
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To accurately predict tropospheric ozone concentration(O3), it is needed to investigate the variety of artificial intelligence techniques’ performance, such as machine learning, deep learning and hybrid models. This research aims to effectively predict the hourly ozone trend via fewer input variables. This ozone prediction attempt is performed on diversity data of air pollutants (NO2, NOx, CO, SO2) and meteorological parameters (wind-speed and humidity). The historical datasets are collected from 3 sites in Malaysia. The study’s methodology progressed in two paths: standalone and hybrid models where hourly-averaged datasets are applied based on 5-time horizon analysis scenario, with different inputs’ combinations. For evaluation, all models are tested throughout 5-performance indicator and illustrated on Modified Taylor diagram. Sensitivity analysis of input variables is quantified. Additionally, uncertainty analysis is conducted to assess their confidence level associated with Willmott Index. Based on R2, results indicated that XGBoost has higher accuracy compared to MLP and SVR; meanwhile, LSTM and CNN outweighs XGBoost. In terms of robustness and accuracy, the proposed hybrid model possesses superlative performance compared to all above-mentioned techniques. The proposed model achieved exceptional results as the highest R2, the highest 95% confidence degree, and narrower confidence interval width, are 93.48%, 98.16%, and 0.0014195, respectively.

ACS Style

Ayman Yafouz; Ali Najah Ahmed; Nur’Atiah Zaini; Mohsen Sherif; Ahmed Sefelnasr; Ahmed El-Shafie. Hybrid deep learning model for ozone concentration prediction: comprehensive evaluation and comparison with various machine and deep learning algorithms. Engineering Applications of Computational Fluid Mechanics 2021, 15, 902 -933.

AMA Style

Ayman Yafouz, Ali Najah Ahmed, Nur’Atiah Zaini, Mohsen Sherif, Ahmed Sefelnasr, Ahmed El-Shafie. Hybrid deep learning model for ozone concentration prediction: comprehensive evaluation and comparison with various machine and deep learning algorithms. Engineering Applications of Computational Fluid Mechanics. 2021; 15 (1):902-933.

Chicago/Turabian Style

Ayman Yafouz; Ali Najah Ahmed; Nur’Atiah Zaini; Mohsen Sherif; Ahmed Sefelnasr; Ahmed El-Shafie. 2021. "Hybrid deep learning model for ozone concentration prediction: comprehensive evaluation and comparison with various machine and deep learning algorithms." Engineering Applications of Computational Fluid Mechanics 15, no. 1: 902-933.

Research article
Published: 07 November 2020 in Alexandria Engineering Journal
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Developing water losses and reservoir final storage forecast has become an increasingly important task for reservoir operation. Accurate forecasts would lead to better monitoring of water quality and more efficient reservoir operation. Therefore, the flash flood and water crisis problems in Malaysia can be reduced. Artificial neural networks (ANN) models with radial basis function (RBF) have been determined for high efficiency and accuracy, especially in the dynamics system. In this study, the proposed ANN Prediction Model is being developed by using inflow, the release of dam, initial and final storage of the reservoir as input, whereas the water losses from the reservoir as output. All the data collected over 11 years (1997–2007) at Klang Gate reservoir has been used to develop and test model output. The results indicated that the proposed model could provide monthly forecasting with maximum root mean square error of ± 20.07%. The advantages of this ANN model are to provide information for water losses, final storage, and variation of water level for better reservoir operation.

ACS Style

Sarmad Dashti Latif; Ali Najah Ahmed; Mohsen Sherif; Ahmed Sefelnasr; Ahmed El-Shafie. Reservoir water balance simulation model utilizing machine learning algorithm. Alexandria Engineering Journal 2020, 60, 1365 -1378.

AMA Style

Sarmad Dashti Latif, Ali Najah Ahmed, Mohsen Sherif, Ahmed Sefelnasr, Ahmed El-Shafie. Reservoir water balance simulation model utilizing machine learning algorithm. Alexandria Engineering Journal. 2020; 60 (1):1365-1378.

Chicago/Turabian Style

Sarmad Dashti Latif; Ali Najah Ahmed; Mohsen Sherif; Ahmed Sefelnasr; Ahmed El-Shafie. 2020. "Reservoir water balance simulation model utilizing machine learning algorithm." Alexandria Engineering Journal 60, no. 1: 1365-1378.

Review
Published: 26 May 2020 in Sustainability
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The prediction of nitrogen not only assists in monitoring the nitrogen concentration in streams but also helps in optimizing the usage of fertilizers in agricultural fields. A precise prediction model guarantees the delivering of better-quality water for human use, as the operations of various water treatment plants depend on the concentration of nitrogen in streams. Considering the stochastic nature and the various hydrological variables upon which nitrogen concentration depends, a predictive model should be efficient enough to account for all the complexities of nature in the prediction of nitrogen concentration. For two decades, artificial neural networks (ANNs) and other models (such as autoregressive integrated moving average (ARIMA) model, hybrid model, etc.), used for predicting different complex hydrological parameters, have proved efficient and accurate up to a certain extent. In this review paper, such prediction models, created for predicting nitrogen concentration, are critically analyzed, comparing their accuracy and input variables. Moreover, future research works aiming to predict nitrogen using advanced techniques and more reliable and appropriate input variables are also discussed.

ACS Style

Pavitra Kumar; Sai Hin Lai; Jee Khai Wong; Nuruol Syuhadaa Mohd; Rowshon Kamal; Haitham Abdulmohsin Afan; Ali Najah Ahmed; Mohsen Sherif; Ahmed Sefelnasr; Ahmed El-Shafie. Review of Nitrogen Compounds Prediction in Water Bodies Using Artificial Neural Networks and Other Models. Sustainability 2020, 12, 4359 .

AMA Style

Pavitra Kumar, Sai Hin Lai, Jee Khai Wong, Nuruol Syuhadaa Mohd, Rowshon Kamal, Haitham Abdulmohsin Afan, Ali Najah Ahmed, Mohsen Sherif, Ahmed Sefelnasr, Ahmed El-Shafie. Review of Nitrogen Compounds Prediction in Water Bodies Using Artificial Neural Networks and Other Models. Sustainability. 2020; 12 (11):4359.

Chicago/Turabian Style

Pavitra Kumar; Sai Hin Lai; Jee Khai Wong; Nuruol Syuhadaa Mohd; Rowshon Kamal; Haitham Abdulmohsin Afan; Ali Najah Ahmed; Mohsen Sherif; Ahmed Sefelnasr; Ahmed El-Shafie. 2020. "Review of Nitrogen Compounds Prediction in Water Bodies Using Artificial Neural Networks and Other Models." Sustainability 12, no. 11: 4359.

Journal article
Published: 14 May 2020 in Entropy
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In this study, the analysis of the extreme sea level was carried out by using 10 years (2007–2016) of hourly tide gauge data of Karachi port station along the Pakistan coast. Observations revealed that the magnitudes of the tides usually exceeded the storm surges at this station. The main observation for this duration and the subsequent analysis showed that in June 2007 a tropical Cyclone “Yemyin” hit the Pakistan coast. The joint probability method (JPM) and the annual maximum method (AMM) were used for statistical analysis to find out the return periods of different extreme sea levels. According to the achieved results, the AMM and JPM methods erre compatible with each other for the Karachi coast and remained well within the range of 95% confidence. For the JPM method, the highest astronomical tide (HAT) of the Karachi coast was considered as the threshold and the sea levels above it were considered extreme sea levels. The 10 annual observed sea level maxima, in the recent past, showed an increasing trend for extreme sea levels. In the study period, the increment rates of 3.6 mm/year and 2.1 mm/year were observed for mean sea level and extreme sea level, respectively, along the Karachi coast. Tidal analysis, for the Karachi tide gauge data, showed less dependency of the extreme sea levels on the non-tidal residuals. By applying the Merrifield criteria of mean annual maximum water level ratio, it was found that the Karachi coast was tidally dominated and the non-tidal residual contribution was just 10%. The examination of the highest water level event (13 June 2014) during the study period, further favored the tidal dominance as compared to the non-tidal component along the Karachi coast.

ACS Style

Faisal Ahmed Khan; Tariq Masood Ali Khan; Ali Najah Ahmed; Haitham Abdulmohsin Afan; Mohsen Sherif; Ahmed Sefelnasr; Ahmed El-Shafie. Complex Extreme Sea Levels Prediction Analysis: Karachi Coast Case Study. Entropy 2020, 22, 549 .

AMA Style

Faisal Ahmed Khan, Tariq Masood Ali Khan, Ali Najah Ahmed, Haitham Abdulmohsin Afan, Mohsen Sherif, Ahmed Sefelnasr, Ahmed El-Shafie. Complex Extreme Sea Levels Prediction Analysis: Karachi Coast Case Study. Entropy. 2020; 22 (5):549.

Chicago/Turabian Style

Faisal Ahmed Khan; Tariq Masood Ali Khan; Ali Najah Ahmed; Haitham Abdulmohsin Afan; Mohsen Sherif; Ahmed Sefelnasr; Ahmed El-Shafie. 2020. "Complex Extreme Sea Levels Prediction Analysis: Karachi Coast Case Study." Entropy 22, no. 5: 549.

Journal article
Published: 07 February 2020 in Sustainability
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This study aims to investigate the impact of meteorological parameters such as wind direction, wind speed, rainfall, and mean cloud cover on sea-level rise projections for different time horizons—2019, 2023, 2028, 2048, and 2068—at three stations located in Kudat, Sandakan, and Kota Kinabalu, which are districts in the state of Sabah, Malaysia. Herein, two different scenarios, scenario1 (SC1) and scenario2 (SC2), were investigated, with each scenario comprising a different combination of input parameters. This study proposes two artificial intelligence techniques: a multilayer perceptron neural network (MLP-ANN) and an adaptive neuro-fuzzy inference system (ANFIS). Furthermore, three evaluation indexes were adopted to assess the performance of the proposed models. These indexes are the correlation coefficient, root mean square error, and scatter index. The trial and error method were used to tune the hyperparameters: the number of neurons in the hidden layer, training algorithms, transfer and activation functions, and number and shape of the membership function for the proposed models. Results show that for the above mentioned three stations, the ANFIS model outperformed MLP-ANN by 0.740%, 6.23%, and 9.39%, respectively. To assess the uncertainties of the best model, ANFIS, the percentage of observed data bracketed by 95 percent predicted uncertainties (95PPUs) and the band width of 95 percent confidence intervals (d-factors) are selected. The obtained values bracketed by 95PPUs are show about 75.2%, 77.4%, 76.8% and the d-factor has a value of 0.27, 0.21 and 0.23 at Kudat, Sandakan and Kota Kinabalu stations, respectively. A comparison between the two scenarios shows that SC1 achieved a high level of accuracy on Kudat and Sandakan data, whereas SC2 outperformed SC1 on Kota Kinabalu data.

ACS Style

T. Olivia Muslim; Ali Najah Ahmed; M. A. Malek; Haitham Abdulmohsin Afan; Rusul Khaleel Ibrahim; Amr El-Shafie; Michelle Sapitang; Mohsen Sherif; Ahmed Sefelnasr; Ahmed El-Shafie. Investigating the Influence of Meteorological Parameters on the Accuracy of Sea-Level Prediction Models in Sabah, Malaysia. Sustainability 2020, 12, 1193 .

AMA Style

T. Olivia Muslim, Ali Najah Ahmed, M. A. Malek, Haitham Abdulmohsin Afan, Rusul Khaleel Ibrahim, Amr El-Shafie, Michelle Sapitang, Mohsen Sherif, Ahmed Sefelnasr, Ahmed El-Shafie. Investigating the Influence of Meteorological Parameters on the Accuracy of Sea-Level Prediction Models in Sabah, Malaysia. Sustainability. 2020; 12 (3):1193.

Chicago/Turabian Style

T. Olivia Muslim; Ali Najah Ahmed; M. A. Malek; Haitham Abdulmohsin Afan; Rusul Khaleel Ibrahim; Amr El-Shafie; Michelle Sapitang; Mohsen Sherif; Ahmed Sefelnasr; Ahmed El-Shafie. 2020. "Investigating the Influence of Meteorological Parameters on the Accuracy of Sea-Level Prediction Models in Sabah, Malaysia." Sustainability 12, no. 3: 1193.

Articles
Published: 01 January 2020 in Engineering Applications of Computational Fluid Mechanics
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High level of tropospheric ozone concentration, exceeding allowable level has been frequently reported in Malaysia. This study proposes accurate model based on Machine Learning algorithms to predict Tropospheric ozone concentration in major cities located in Kuala Lumpur and Selangor, Malaysia. The proposed models were developed using three-year of historical data for different parameters as input to predict 24-hour and 12-hour of tropospheric ozone concentration. Different Machine Learning algorithms have been investigated, viz. Linear Regression, Neural Network and Boosted Decision Tree. The results revealed that wind speed, humidity, Nitrogen Oxide, Carbon Monoxide and Nitrogen Dioxide have significant influence on ozone formation. Boosted Decision Tree outperformed Linear regression and Neural Network algorithms for all stations. The performance of the proposed model improved by using 12-hours dataset instead of the 24-hour where R2 values were equal to 0.91, 0.88 and 0.87 for the three investigated stations. To assess the uncertainties of the Boosted Decision Tree model, 95% prediction uncertainties (95PPU) d-factors were introduced.95PPU showed about 94.4, 93.4, 96.7% and the d-factors were 0.001015, 0.001016 and 0.001124 which relate to S1, S2 and S3, respectively. The obtained results provide a reliable prediction model to mimic actual ozone concentration in different locations in Malaysia.

ACS Style

Ellysia Jumin; Nuratiah Zaini; Ali Najah Ahmed; Samsuri Abdullah; Marzuki Ismail; Mohsen Sherif; Ahmed Sefelnasr; Ahmed El-Shafie. Machine learning versus linear regression modelling approach for accurate ozone concentrations prediction. Engineering Applications of Computational Fluid Mechanics 2020, 14, 713 -725.

AMA Style

Ellysia Jumin, Nuratiah Zaini, Ali Najah Ahmed, Samsuri Abdullah, Marzuki Ismail, Mohsen Sherif, Ahmed Sefelnasr, Ahmed El-Shafie. Machine learning versus linear regression modelling approach for accurate ozone concentrations prediction. Engineering Applications of Computational Fluid Mechanics. 2020; 14 (1):713-725.

Chicago/Turabian Style

Ellysia Jumin; Nuratiah Zaini; Ali Najah Ahmed; Samsuri Abdullah; Marzuki Ismail; Mohsen Sherif; Ahmed Sefelnasr; Ahmed El-Shafie. 2020. "Machine learning versus linear regression modelling approach for accurate ozone concentrations prediction." Engineering Applications of Computational Fluid Mechanics 14, no. 1: 713-725.

Journal article
Published: 31 December 2019 in Hydrology
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The quality of groundwater resources in coastal aquifers is affected by saltwater intrusion. Over-abstraction of groundwater and seawater level rise due to climate change accelerate the intrusion process. This paper investigates the effects of aquifer bed slope and seaside slope on saltwater intrusion. The possible impacts of increasing seawater head due to sea level rise and decreasing groundwater level due to over-pumping and reduction in recharge are also investigated. A numerical model (SEAWAT) is applied to well-known Henry problem to assess the movement of the dispersion zone under different settings of bed and seaside slopes. The results showed that increasing seaside slope increased the intrusion of saltwater by 53.2% and 117% for slopes of 1:1 and 2:1, respectively. Increasing the bed slope toward the land decreased the intrusion length by 2% and 4.8%, respectively. On the other hand, increasing the bed slope toward the seaside increased the intrusion length by 3.6% and 6.4% for bed slopes of 20:1 and 10:1, respectively. The impacts of reducing the groundwater level at the land side and increasing the seawater level at the shoreline by 5% and 10% considering different slopes are studied. The intrusion length increased under both conditions. Unlike Henry problem, the current investigation considers inclined beds and sea boundaries and, hence, provides a better representation of the field conditions.

ACS Style

Hany F. Abd-Elhamid; Ismail Abd-Elaty; Mohsen M. Sherif. Effects of Aquifer Bed Slope and Sea Level on Saltwater Intrusion in Coastal Aquifers. Hydrology 2019, 7, 5 .

AMA Style

Hany F. Abd-Elhamid, Ismail Abd-Elaty, Mohsen M. Sherif. Effects of Aquifer Bed Slope and Sea Level on Saltwater Intrusion in Coastal Aquifers. Hydrology. 2019; 7 (1):5.

Chicago/Turabian Style

Hany F. Abd-Elhamid; Ismail Abd-Elaty; Mohsen M. Sherif. 2019. "Effects of Aquifer Bed Slope and Sea Level on Saltwater Intrusion in Coastal Aquifers." Hydrology 7, no. 1: 5.

Review
Published: 24 November 2019 in Water
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Seawater intrusion (SWI) is one of the most challenging and widespread environmental problems that threaten the quality and sustainability of fresh groundwater resources in coastal aquifers. The excessive pumping of groundwater, associated with the lack of natural recharge, has exacerbated the SWI problem in arid and semi-arid regions. Therefore, appropriate management strategies should be implemented in coastal aquifers to control the impacts of SWI problems, considering acceptable limits of economic and environmental costs. The management of coastal aquifers involves the identification of an acceptable ultimate landward extent of the saline water body and the calculation of the amount of seaward discharge of freshwater that is necessary to keep the saline–freshwater interface in a seacoast position. This paper presents a comprehensive review of available hydraulic and physical management strategies that can be used to reduce and control SWI in coastal aquifers. Advantages and disadvantages of the different approaches are presented and discussed.

ACS Style

Mohammed S. Hussain; Hany F. Abd-Elhamid; Akbar A. Javadi; Mohsen M. Sherif. Management of Seawater Intrusion in Coastal Aquifers: A Review. Water 2019, 11, 2467 .

AMA Style

Mohammed S. Hussain, Hany F. Abd-Elhamid, Akbar A. Javadi, Mohsen M. Sherif. Management of Seawater Intrusion in Coastal Aquifers: A Review. Water. 2019; 11 (12):2467.

Chicago/Turabian Style

Mohammed S. Hussain; Hany F. Abd-Elhamid; Akbar A. Javadi; Mohsen M. Sherif. 2019. "Management of Seawater Intrusion in Coastal Aquifers: A Review." Water 11, no. 12: 2467.

Conference paper
Published: 18 May 2017 in World Environmental and Water Resources Congress 2017
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ACS Style

Mohsen Sherif; Abdelazim Ebraheem; Ampar Shetty; Christopher N. Dunn; Brian Van Weele. Groundwater Recharge from Dams in United Arab Emirates. World Environmental and Water Resources Congress 2017 2017, 139 -146.

AMA Style

Mohsen Sherif, Abdelazim Ebraheem, Ampar Shetty, Christopher N. Dunn, Brian Van Weele. Groundwater Recharge from Dams in United Arab Emirates. World Environmental and Water Resources Congress 2017. 2017; ():139-146.

Chicago/Turabian Style

Mohsen Sherif; Abdelazim Ebraheem; Ampar Shetty; Christopher N. Dunn; Brian Van Weele. 2017. "Groundwater Recharge from Dams in United Arab Emirates." World Environmental and Water Resources Congress 2017 , no. : 139-146.

Journal article
Published: 01 May 2014 in Journal of Hydrologic Engineering
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Arid coastal regions are more vulnerable to groundwater deterioration problems. Intensive groundwater abstraction from the coastal aquifer of Wadi Ham, United Arab Emirates, caused a severe saltwater intrusion problem. Given the deterioration of groundwater quality, domestic water supply from well fields have been terminated and replaced by desalinated seawater. In addition, many farms in southeast Fujairah city have been abandoned. This paper develops a two-dimensional finite element groundwater flow and solute transport model to simulate the spatial and temporal variations of the salinity distribution in the coastal aquifer of Wadi Ham, taking into account the transition zone between freshwater and seawater bodies. All simulations were conducted in the horizontal view under transient conditions. The available historical records of the water table levels were used to calibrate and validate the developed model. Emphasis was placed on the response of the transition zone to different pumping scenarios in Wadi Ham. The results indicated that the seawater intrusion problem has evolved rapidly during the last two decades. Unlike previous investigations, this study presents the most accurate quantitative and qualitative assessment of available groundwater in the Wadi Ham aquifer under different pumping scenarios.

ACS Style

Mohsen Sherif; Ahmed Sefelnasr; Abdel Azim Ebraheem; Akbar Javadi. Quantitative and Qualitative Assessment of Seawater Intrusion in Wadi Ham under Different Pumping Scenarios. Journal of Hydrologic Engineering 2014, 19, 855 -866.

AMA Style

Mohsen Sherif, Ahmed Sefelnasr, Abdel Azim Ebraheem, Akbar Javadi. Quantitative and Qualitative Assessment of Seawater Intrusion in Wadi Ham under Different Pumping Scenarios. Journal of Hydrologic Engineering. 2014; 19 (5):855-866.

Chicago/Turabian Style

Mohsen Sherif; Ahmed Sefelnasr; Abdel Azim Ebraheem; Akbar Javadi. 2014. "Quantitative and Qualitative Assessment of Seawater Intrusion in Wadi Ham under Different Pumping Scenarios." Journal of Hydrologic Engineering 19, no. 5: 855-866.

Journal article
Published: 26 June 2013 in International Journal of Climatology
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Spatial and temporal characteristics of rainfall in the United Arab Emirates (UAE) were investigated. The region is divided into four climate zones (East Coast, Mountains, Gravel Plains and Desert Foreland) of distinguished rainfall distribution. The rainfall patterns, rainfall probability of occurrences, rainfall intensity‐duration‐frequency (IDF) relationship, probable maximum precipitation (PMP) and drought scenarios were investigated. Daily rainfall data from a network of stations across the UAE were used. Standard statistical techniques were applied for data analyses. The Gumbel, log Pearson, generalized extreme value, log normal, Wakeby and Weibull probability distributions were tested to fit extreme rainfalls. Both Gumbel and Weibull distributions were found adequate. Measures of dispersion and symmetry of rainfall patterns were found relatively high. The estimated PMP values were found highest in the East Coast region and lowest in the Gravel Plains region. Estimated drought severity index showed that the regions have similar trends of drought patterns over the years. The study is useful for sustainable water resources planning and management in the region.

ACS Style

Mohsen Sherif; Mohamed Almulla; Ampar Shetty; Rezaul K. Chowdhury. Analysis of rainfall, PMP and drought in the United Arab Emirates. International Journal of Climatology 2013, 34, 1318 -1328.

AMA Style

Mohsen Sherif, Mohamed Almulla, Ampar Shetty, Rezaul K. Chowdhury. Analysis of rainfall, PMP and drought in the United Arab Emirates. International Journal of Climatology. 2013; 34 (4):1318-1328.

Chicago/Turabian Style

Mohsen Sherif; Mohamed Almulla; Ampar Shetty; Rezaul K. Chowdhury. 2013. "Analysis of rainfall, PMP and drought in the United Arab Emirates." International Journal of Climatology 34, no. 4: 1318-1328.

Proceedings article
Published: 28 May 2013 in World Environmental and Water Resources Congress 2013
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In this paper, MODFLOW was used to investigate the long-term injection and recovery of freshwater in the brackish aquifer of Wadi Ham, United Arab Emirates. The simulations were conducted for six successive cycles of injection and recovery with constant recharge and recovery rates and also constant durations. The simulations were also performed for various rates of injection and recovery and the recovery efficiency of the system was evaluated. The recovery efficiency varied between 32% and 88% and increased significantly during the first three cycles and then slightly in the following runs. The effect of the injection and recovery rates and the duration of the recharge were also investigated.

ACS Style

Mohsen Sherif; Ampar Shetty. Freshwater Storage in Brackish Aquifers. World Environmental and Water Resources Congress 2013 2013, 440 -449.

AMA Style

Mohsen Sherif, Ampar Shetty. Freshwater Storage in Brackish Aquifers. World Environmental and Water Resources Congress 2013. 2013; ():440-449.

Chicago/Turabian Style

Mohsen Sherif; Ampar Shetty. 2013. "Freshwater Storage in Brackish Aquifers." World Environmental and Water Resources Congress 2013 , no. : 440-449.

Book chapter
Published: 20 April 2013 in Coastal Wetlands: Alteration and Remediation
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The United Arab Emirates (UAE) typifies an arid environment with limited freshwater resources and harsh climatic conditions. Rainfall is scarce, random and can be regarded as an integral element of the water resources at UAE. Groundwater resources, although non-renewable, contribute by more than 50 % of the total water demand in the country. Due to the excessive pumping of groundwater to meet the agriculture demands, groundwater levels have declined in the coastal aquifer of Wadi Ham and the quality of the water has deteriorated due to the seawater intrusion problem. In this study, MODFLOW and MT3D are employed to simulate the groundwater flow and assess the seawater intrusion problem in Wadi Ham and possible mitigation measures. The flow model was calibrated and validated through comparisons with two independent sets of data collected over periods of 5 and 11 years, respectively. The results of the transport model were calibrated against available groundwater concentrations at some locations. The developed model is then used to study the effects of pumping and artificial recharge on seawater intrusion. Results indicated that reducing the pumping from Khalba well field will retard the seawater intrusion in the southeastern part of the aquifer. Applying artificial recharge through a surface basin of 100 × 100 m at a rate of 1 m/day will cause equi-concentration contour line 10,000 mg/l to retreat about 1.25 km towards the coast within a period of 12 years.

ACS Style

Mohsen Sherif; Mohamed Almulla; Ampar Shetty. Seawater Intrusion Assessment and Mitigation in the Coastal Aquifer of Wadi Ham. Coastal Wetlands: Alteration and Remediation 2013, 271 -294.

AMA Style

Mohsen Sherif, Mohamed Almulla, Ampar Shetty. Seawater Intrusion Assessment and Mitigation in the Coastal Aquifer of Wadi Ham. Coastal Wetlands: Alteration and Remediation. 2013; ():271-294.

Chicago/Turabian Style

Mohsen Sherif; Mohamed Almulla; Ampar Shetty. 2013. "Seawater Intrusion Assessment and Mitigation in the Coastal Aquifer of Wadi Ham." Coastal Wetlands: Alteration and Remediation , no. : 271-294.

Journal article
Published: 18 April 2013 in Groundwater
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Several investigations have recently considered the possible impacts of climate change and seawater level rise on seawater intrusion in coastal aquifers. All have revealed the severity of the problem and the significance of the landward movement of the dispersion zone under the condition of seawater level rise. Most of the studies did not consider the possible effects of the seawater rise on the inland movement of the shoreline and the associate changes in the boundary conditions at the seaside and the domain geometry. Such effects become more evident in flat, low land, coastal alluvial plans where large areas might be submerged with seawater under a relatively small increase in the seawater level. None of the studies combined the effect of increased groundwater pumping, due to the possible decline in precipitation and shortage in surface water resources, with the expected landward shift of the shore line. In this article, the possible effects of seawater level rise in the Mediterranean Sea on the seawater intrusion problem in the Nile Delta Aquifer are investigated using FEFLOW. The simulations are conducted in horizontal view while considering the effect of the shoreline landward shift using digital elevation models. In addition to the basic run (current conditions), six different scenarios are considered. Scenarios one, two, and three assume a 0.5 m seawater rise while the total pumping is reduced by 50%, maintained as per the current conditions and doubled, respectively. Scenarios four, five, and six assume a 1.0 m seawater rise and the total pumping is changed as in the first three scenarios. The shoreline is moved to account for the seawater rise and hence the study domain and the seaside boundary are modified accordingly. It is concluded that, large areas in the coastal zone of the Nile Delta will be submerged by seawater and the coast line will shift landward by several kilometers in the eastern and western sides of the Delta. Scenario six represents the worst case under which the volume of freshwater will be reduced to about 513 km3 (billion m3).

ACS Style

Ahmed Sefelnasr; Mohsen Sherif. Impacts of Seawater Rise on Seawater Intrusion in the Nile Delta Aquifer, Egypt. Groundwater 2013, 52, 264 -276.

AMA Style

Ahmed Sefelnasr, Mohsen Sherif. Impacts of Seawater Rise on Seawater Intrusion in the Nile Delta Aquifer, Egypt. Groundwater. 2013; 52 (2):264-276.

Chicago/Turabian Style

Ahmed Sefelnasr; Mohsen Sherif. 2013. "Impacts of Seawater Rise on Seawater Intrusion in the Nile Delta Aquifer, Egypt." Groundwater 52, no. 2: 264-276.

Conference paper
Published: 17 May 2012 in World Environmental and Water Resources Congress 2012
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The Nile Delta aquifer in Egypt is one of the largest groundwater reservoirs in the world and has been severely affected by the seawater intrusion problem from the Mediterranean sea. Due to the huge exposure of the aquifer to the seawater, the seawater and the dispersion zone migrated tens of kilometers inland causing a major deterioration in the groundwater quality. In this paper, FEFLOW, a finite element model, is used to simulated the seawater intrusion problem in the Nile Delta aquifer in the areal view at the seawater level. A fine mesh with smaller elements near the boundaries and along the two River Nile branches was implemented to ensure the accurate representation of the groundwater flow and solute transport. The model was calibrated against available measurements of groundwater levels and salinity. A good agreement between the resulted dispersion zone and the observed one.

ACS Style

M. M. Sherif; A. Sefelnasr; A. Javadi. Areal Simulation of Seawater Intrusion in the Nile Delta Aquifer. World Environmental and Water Resources Congress 2012 2012, 1 .

AMA Style

M. M. Sherif, A. Sefelnasr, A. Javadi. Areal Simulation of Seawater Intrusion in the Nile Delta Aquifer. World Environmental and Water Resources Congress 2012. 2012; ():1.

Chicago/Turabian Style

M. M. Sherif; A. Sefelnasr; A. Javadi. 2012. "Areal Simulation of Seawater Intrusion in the Nile Delta Aquifer." World Environmental and Water Resources Congress 2012 , no. : 1.

Journal article
Published: 24 January 2012 in Environmental Earth Sciences
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Drilling information, historical water table levels, groundwater salinity records of the existing water wells in Wadi Al Bih area, United Arab Emirates, were stored in a geodatabase and used to characterize the geological and hydrogeological settings of this area. A 2D earth resistivity imaging survey was conducted for the first time in the Northern UAE to determine the potential of the Quaternary aquifer and its groundwater quality in the areas where there are no monitoring wells. The results of the chemical analyses of the collected groundwater samples together with the inversion results of the resistivity data were used to draw a total salinity map and determine the spatial variations in groundwater quality. The inversion results of the 2D earth resistivity imaging data indicated that the Quaternary aquifer in the study area is in a good connection with the underlying carbonate aquifer. It also indicated that the carbonate aquifer is of major regional and vertical extension and it contains the fresh water in this area. The data stored in the developed database were used to produce different types of geopotential maps.

ACS Style

A. M. Ebraheem; Mohsen Sherif; M. M. Al Mulla; S. F. Akram; A. V. Shetty. A geoelectrical and hydrogeological study for the assessment of groundwater resources in Wadi Al Bih, UAE. Environmental Earth Sciences 2012, 67, 845 -857.

AMA Style

A. M. Ebraheem, Mohsen Sherif, M. M. Al Mulla, S. F. Akram, A. V. Shetty. A geoelectrical and hydrogeological study for the assessment of groundwater resources in Wadi Al Bih, UAE. Environmental Earth Sciences. 2012; 67 (3):845-857.

Chicago/Turabian Style

A. M. Ebraheem; Mohsen Sherif; M. M. Al Mulla; S. F. Akram; A. V. Shetty. 2012. "A geoelectrical and hydrogeological study for the assessment of groundwater resources in Wadi Al Bih, UAE." Environmental Earth Sciences 67, no. 3: 845-857.