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Prof. Dr. Nadhir Al-Ansari
Lulea University of Technology

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0 Sediment Transport
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Original paper
Published: 04 August 2021 in Arabian Journal of Geosciences
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Cylindrical weir shapes offer a steady-state overflow pattern, where the type of weirs can offer a simple design and provide the ease-to-pass floating debris. This study considers a coefficient of discharge (Cd) prediction for oblique cylindrical weir using three diameters, the first is of D1 = 0.11 m, the second is of D2 = 0.09 m, and the third is of D3 = 0.06.5 m, and three inclination angles with respect to channel axis, the first is of θ1 = 90 ͦ, the second is of θ2 = 45 ͦ, and the third is of θ3 = 30 ͦ. The Cd values for total of 56 experiments are estimated by using the radial basis function network (RBFN), in addition of comparing that with the back-propagation neural network (BPNN) and cascade-forward neural network (CFNN). Root mean square error (RMSE), mean square error (MSE), and correlation coefficient (CC) statics are used as metrics measurements. The RBFN attained superior performance comparing to the other neural networks of BPNN and CFNN. It is found that, for the training stage, the RBFN network benchmarked very small RMSE and MSE values of 1.35E-12 and 1.83E-24, respectively and for the testing stage, it also could benchmark very small RMSE and MSE values of 0.0082 and 6.80E-05, respectively.

ACS Style

Adnan A. Ismael; Saleh J. Suleiman; Raid Rafi Omar Al-Nima; Nadhir Al-Ansari. Predicting the discharge coefficient of oblique cylindrical weir using neural network techniques. Arabian Journal of Geosciences 2021, 14, 1 -8.

AMA Style

Adnan A. Ismael, Saleh J. Suleiman, Raid Rafi Omar Al-Nima, Nadhir Al-Ansari. Predicting the discharge coefficient of oblique cylindrical weir using neural network techniques. Arabian Journal of Geosciences. 2021; 14 (16):1-8.

Chicago/Turabian Style

Adnan A. Ismael; Saleh J. Suleiman; Raid Rafi Omar Al-Nima; Nadhir Al-Ansari. 2021. "Predicting the discharge coefficient of oblique cylindrical weir using neural network techniques." Arabian Journal of Geosciences 14, no. 16: 1-8.

Article
Published: 23 July 2021 in Water, Air, & Soil Pollution
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Iraq currently undergoing the problem of water shortage, although Iraq has two Rivers (Euphrates and Tigris) pass throughout most of its areas, and they have represented a major source of water supply. In the current research, to evaluate the quality of the Euphrates river in Iraq based on the values of total dissolved salts (TDS), the TDS concentrations were collected from sixteen sections along the river in the three succeeding years (2011, 2012, and 2013). The evaluation of the river was done depending on the classification of (W.H.O. (World Health Organization). (2003). Total Dissolved Salts in Drinking-water: Background document for development of W.H.O. Guidelines for Drinking-water Quality. World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland). of rivers for drinking uses. Inverse Distance Weighting Technique (IDWT) as a tool in the GIS was employed to establish the maps of the river that using interpolation/prediction for the TDS concentrations to each selected year and the average values of TDS for these 3 years. Based on the five categories of rivers’ classification of the TDS concentrations according to the (W.H.O. (World Health Organization). (2003). Total Dissolved Salts in Drinking-water: Background document for development of W.H.O. Guidelines for Drinking-water Quality. World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland), the Euphrates river was classified, and the maps of classification for the years 2011, 2012 and 2013 and the average values for 3 years were created. The average values for 3 years of TDS along the Euphrates river indicated that the sections from SC-1 to SC-4 as moderate-water-quality-Category-3, the sections from SC-5 to SC-10 as poor-water-quality-Category-4, while the sections between SC-11 to SC-16 as very poor-water-quality-Category-5. The interpolation maps showed that the Euphrates river in Iraq was ranged from moderate water quality (Category-3) to very poor water quality (Category-5).

ACS Style

Ali Chabuk; Zahraa Ali Hammood; Nadhir Al-Ansari; Salwan Ali Abed; Jan Laue. Classification Maps for TDS Concentrations in the GIS Along Euphrates River, Iraq. Water, Air, & Soil Pollution 2021, 232, 1 -15.

AMA Style

Ali Chabuk, Zahraa Ali Hammood, Nadhir Al-Ansari, Salwan Ali Abed, Jan Laue. Classification Maps for TDS Concentrations in the GIS Along Euphrates River, Iraq. Water, Air, & Soil Pollution. 2021; 232 (8):1-15.

Chicago/Turabian Style

Ali Chabuk; Zahraa Ali Hammood; Nadhir Al-Ansari; Salwan Ali Abed; Jan Laue. 2021. "Classification Maps for TDS Concentrations in the GIS Along Euphrates River, Iraq." Water, Air, & Soil Pollution 232, no. 8: 1-15.

Research article
Published: 22 July 2021 in Advances in Civil Engineering
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Landslides are one of the most devastating natural hazards causing huge loss of life and damage to properties and infrastructures and adversely affecting the socioeconomy of the country. Landslides occur in hilly and mountainous areas all over the world. Single, ensemble, and hybrid machine learning (ML) models have been used in landslide studies for better landslide susceptibility mapping and risk management. In the present study, we have used three single ML models, namely, linear discriminant analysis (LDA), logistic regression (LR), and radial basis function network (RBFN), for landslide susceptibility mapping at Pithoragarh district, as these models are easy to apply and so far they have not been used for landslide study in this area. The main objective of this study is to evaluate the performance of these single models for correctly identifying landslide susceptible zones for their further application in other areas. For this, ten important landslide affecting factors, namely, slope, aspect, curvature, elevation, land cover, lithology, geomorphology, distance to rivers, distance to roads, and overburden depth based on the local geoenvironmental conditions, were considered for the modeling. Landslide inventory of past 398 landslide events was used in the development of models. The data of past landslide events (locations) was randomly divided into a 70/30 ratio for training (70%) and validation (30%) of the models. Standard statistical measures, namely, accuracy (ACC), specificity (SPF), sensitivity (SST), positive predictive value (PPV), negative predictive value (NPV), Kappa, root mean square error (RMSE), and area under the receiver operating characteristic curve (AUC), were used to evaluate the performance of the models. Results indicated that the performance of all the models is very good (AUC > 0.90) and that of the LR model is the best (AUC = 0.926). Therefore, these single ML models can be used for the development of accurate landslide susceptibility maps. Our study demonstrated that the single models which are easy to use and can compete with the complex ensemble/hybrid models can be applied for landslide susceptibility mapping in landslide-prone areas.

ACS Style

Trinh Quoc Ngo; Nguyen Duc Dam; Nadhir Al-Ansari; Mahdis Amiri; Tran Van Phong; Indra Prakash; Hiep Van Le; Hanh Bich Thi Nguyen; Binh Thai Pham. Landslide Susceptibility Mapping Using Single Machine Learning Models: A Case Study from Pithoragarh District, India. Advances in Civil Engineering 2021, 2021, 1 -19.

AMA Style

Trinh Quoc Ngo, Nguyen Duc Dam, Nadhir Al-Ansari, Mahdis Amiri, Tran Van Phong, Indra Prakash, Hiep Van Le, Hanh Bich Thi Nguyen, Binh Thai Pham. Landslide Susceptibility Mapping Using Single Machine Learning Models: A Case Study from Pithoragarh District, India. Advances in Civil Engineering. 2021; 2021 ():1-19.

Chicago/Turabian Style

Trinh Quoc Ngo; Nguyen Duc Dam; Nadhir Al-Ansari; Mahdis Amiri; Tran Van Phong; Indra Prakash; Hiep Van Le; Hanh Bich Thi Nguyen; Binh Thai Pham. 2021. "Landslide Susceptibility Mapping Using Single Machine Learning Models: A Case Study from Pithoragarh District, India." Advances in Civil Engineering 2021, no. : 1-19.

Journal article
Published: 19 July 2021 in Molecules
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The evaluation of groundwater quality in the Dammam formation, Faddak farm, Karbala Governorate, Iraq proved that the sulfate (SO42−) concentrations have high values; so, this water is not suitable for livestock, poultry and irrigation purposes. For reclamation of this water, manufacturing of new sorbent for permeable reactive barrier was required through precipitation of Mg and Fe hydroxides nanoparticles on the activated carbon (AC) surface with best Mg/Fe molar ratio of 7.5/2.5. Mixture of 50% coated AC and 50% scrap iron was applied to eliminate SO42− from contaminated water with efficiency of 59% and maximum capacity of adsorption equals to 9.5 mg/g for a time period of 1 h, sorbent dosage 40 g/L, and initial pH = 5 at 50 mg/L initial SO42− concentration and 200 rpm shaking speed. Characterization analyses certified that the plantation of Mg and Fe nanoparticles onto AC was achieved. Continuous tests showed that the longevity of composite sorbent is increased with thicker bed and lower influent concentration and flow rate. Computer solution (COMSOL) software was well simulated for continuous measurements. The reclamation of real contaminated groundwater was achieved in column set-up with efficiency of 70% when flow rate was 5 mL/min, bed depth was 50 cm and inlet SO42− concentration was 2301 mg/L.

ACS Style

Waqed Hassan; Ayad Faisal; Enas Abed; Nadhir Al-Ansari; Bahaa Saleh. New Composite Sorbent for Removal of Sulfate Ions from Simulated and Real Groundwater in the Batch and Continuous Tests. Molecules 2021, 26, 4356 .

AMA Style

Waqed Hassan, Ayad Faisal, Enas Abed, Nadhir Al-Ansari, Bahaa Saleh. New Composite Sorbent for Removal of Sulfate Ions from Simulated and Real Groundwater in the Batch and Continuous Tests. Molecules. 2021; 26 (14):4356.

Chicago/Turabian Style

Waqed Hassan; Ayad Faisal; Enas Abed; Nadhir Al-Ansari; Bahaa Saleh. 2021. "New Composite Sorbent for Removal of Sulfate Ions from Simulated and Real Groundwater in the Batch and Continuous Tests." Molecules 26, no. 14: 4356.

Journal article
Published: 06 July 2021 in Journal of Ecological Engineering
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ACS Style

Hussein Janna; Mukhtar D. Abbas; Marwah M. Al-Khuzaie; Nadhir Al-Ansari. Energy Content Estimation of Municipal Solid Waste by Physical Composition in Al-Diwaniyah City, Iraq. Journal of Ecological Engineering 2021, 22, 11 -19.

AMA Style

Hussein Janna, Mukhtar D. Abbas, Marwah M. Al-Khuzaie, Nadhir Al-Ansari. Energy Content Estimation of Municipal Solid Waste by Physical Composition in Al-Diwaniyah City, Iraq. Journal of Ecological Engineering. 2021; 22 (7):11-19.

Chicago/Turabian Style

Hussein Janna; Mukhtar D. Abbas; Marwah M. Al-Khuzaie; Nadhir Al-Ansari. 2021. "Energy Content Estimation of Municipal Solid Waste by Physical Composition in Al-Diwaniyah City, Iraq." Journal of Ecological Engineering 22, no. 7: 11-19.

Journal article
Published: 02 July 2021 in Ain Shams Engineering Journal
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Phosphate (PO4) is a major component of most fertilizers, and when erosion and runoff occur, large amounts of it enter the water bodies, causing several problems such as eutrophication. Feitsui reservoir, the primary source of water supply to Taipei, reported half of the reservoir's pollutants from nonpoint-source pollution. The value of the PO4 in the water body fluctuates in highly nonlinear and stochastic patterns. However, conventional modeling techniques are no longer sufficiently effective in predicting accurately such stochastic patterns in the concentrations of PO4 in water. Therefore, this study proposes different machine learning algorithms: the artificial neural network (ANN), support vector machine (SVM), random forest (RF), and boosted trees (BT) to predict the concentration of PO4. Monthly measured data between 1986 and 2014 were used to train and test the accuracy of these models. The performances of these models were examined using different statistical indices. Hyperparameters optimization such as cross-validation was performed to enhance the precision of the models. Five water quality parameters were used as input to the proposed models. Different input combinations were explored to optimize the precision. The findings revealed that ANN outperformed the other three models to capture the changes in the concentrations of PO4 with high precision where RMSE is equal to 1.199, MAE is equal to 0.858, and R2 is equal to 0.979, MSE is equal to 1.439, and finally, CC is equal to 0.9909. The developed model could be used as a reliable means for managing eutrophication problems.

ACS Style

Sarmad Dashti Latif; Ahmed H. Birima; Ali Najah Ahmed; Dahan Mohammed Hatem; Nadhir Al-Ansari; Chow Ming Fai; Ahmed El-Shafie. Development of prediction model for phosphate in reservoir water system based machine learning algorithms. Ain Shams Engineering Journal 2021, 1 .

AMA Style

Sarmad Dashti Latif, Ahmed H. Birima, Ali Najah Ahmed, Dahan Mohammed Hatem, Nadhir Al-Ansari, Chow Ming Fai, Ahmed El-Shafie. Development of prediction model for phosphate in reservoir water system based machine learning algorithms. Ain Shams Engineering Journal. 2021; ():1.

Chicago/Turabian Style

Sarmad Dashti Latif; Ahmed H. Birima; Ali Najah Ahmed; Dahan Mohammed Hatem; Nadhir Al-Ansari; Chow Ming Fai; Ahmed El-Shafie. 2021. "Development of prediction model for phosphate in reservoir water system based machine learning algorithms." Ain Shams Engineering Journal , no. : 1.

Journal article
Published: 30 June 2021 in International Journal of Design & Nature and Ecodynamics
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Due to the limitation of water renewable resources on one hand and increasing growth in consuming water in different parts such as agriculture, industry, urban, and the environment in other hand, face management of these valuable resources to many challenges. Present study attempts to clarify recent condition of the problem and introduce effective management tools in water supply sector. In order to achieve this purpose, simulating model HEC-Res Sim was used for Dokan Dam to study the operational behavior of the reservoir and to investigate the model capability in representing and simulating the real system. The study based on monthly discharge data for the period from 1986 to 2016 measured at the inlet of Dokan Dam reservoir. The results of the current study were compared and evaluated against those counterparts observed data using two statistical metrics, correlation coefficient and Nash- Sutcliff coefficient efficiency. Moreover, an empirical formula was found linking the amount of inflow to the reservoir with the amount of outflow. The results showed that the HEC-ResSim 3.0 performed well in simulating the monthly discharges. Therefore, HEC-ResSim 3.0 could be used for better water system analysis in this study area.

ACS Style

Sadeq Oleiwi Sulaiman; Hasan Hussein Abdullah; Nadhir Al-Ansari; Jan Laue; Zaher Mundher Yaseen. Simulation Model for Optimal Operation of Dokan Dam Reservoir Northern of Iraq. International Journal of Design & Nature and Ecodynamics 2021, 16, 301 -306.

AMA Style

Sadeq Oleiwi Sulaiman, Hasan Hussein Abdullah, Nadhir Al-Ansari, Jan Laue, Zaher Mundher Yaseen. Simulation Model for Optimal Operation of Dokan Dam Reservoir Northern of Iraq. International Journal of Design & Nature and Ecodynamics. 2021; 16 (3):301-306.

Chicago/Turabian Style

Sadeq Oleiwi Sulaiman; Hasan Hussein Abdullah; Nadhir Al-Ansari; Jan Laue; Zaher Mundher Yaseen. 2021. "Simulation Model for Optimal Operation of Dokan Dam Reservoir Northern of Iraq." International Journal of Design & Nature and Ecodynamics 16, no. 3: 301-306.

Journal article
Published: 25 June 2021 in Groundwater for Sustainable Development
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Most rivers in developing countries are facing water contamination problem. Therefore, saving water quality by complying with the industrial, drinking, and agricultural allowable standard limits has been difficult. This study aims to assess Shatt Al-Kufa water quality as one branch of the Euphrates River by calculating three types of water quality indices in two cases, excluding and including the phosphate (PO4) consentration, as it was the parameter that most met the standard. The used water quality indices are the Weight Arithmetic Water Quality Index (WAWQI), the Canadian Council of Ministers of the Environment Water Quality Index (CCMEWQI) and the Oregon Water Quality Index (OWQI). Fifteen parameters were analyzed, including pH value, Biological Oxygen Demand, Turbidity, Total Hardness, Orthophosphate, Sulphate, Nitrate, Alkalinity, Potassium, Sodium, Magnesium, Chloride, Dissolved Oxygen, Calcium and Total Dissolved Solids. The results show that the average WAWQI for three stations, including PO4, were 33.79, 43.75 and 37.62, which is good water. However, in excluding PO4, the water quality was characterized as very poor depending on the resulting values (86.62, 88.86 and 91.91, respectively). The CCMEWQI values for three stations were 63.83, 60.40 and 55.69, including PO4, so the water quality was fair and marginal. According to OWQI, the water quality for three stations was very poor in two cases since the OWQI value less than 59. Pearson correlation shows a good link, especially total hardness and total dissolved solids with salt.

ACS Style

Sabreen L. Kareem; Wisam Shamkhi Jaber; Laheab A. Al-Maliki; Rasha A. Al-Husseiny; Sohaib K. Al-Mamoori; Nadhir Alansari. Water quality assessment and phosphorus effect using water quality indices: Euphrates River- Iraq as a case study. Groundwater for Sustainable Development 2021, 14, 100630 .

AMA Style

Sabreen L. Kareem, Wisam Shamkhi Jaber, Laheab A. Al-Maliki, Rasha A. Al-Husseiny, Sohaib K. Al-Mamoori, Nadhir Alansari. Water quality assessment and phosphorus effect using water quality indices: Euphrates River- Iraq as a case study. Groundwater for Sustainable Development. 2021; 14 ():100630.

Chicago/Turabian Style

Sabreen L. Kareem; Wisam Shamkhi Jaber; Laheab A. Al-Maliki; Rasha A. Al-Husseiny; Sohaib K. Al-Mamoori; Nadhir Alansari. 2021. "Water quality assessment and phosphorus effect using water quality indices: Euphrates River- Iraq as a case study." Groundwater for Sustainable Development 14, no. : 100630.

Journal article
Published: 22 June 2021 in International Journal of Sustainable Development and Planning
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ACS Style

Sadeq Oleiwi Sulaiman; Abu Baker A. Najm; Ammar Hatem Kamel; Nadhir Al-Ansari. Evaluate the Optimal Future Demand of Water Consumption in Al-Anbar Province in the West of Iraq. International Journal of Sustainable Development and Planning 2021, 16, 457 -462.

AMA Style

Sadeq Oleiwi Sulaiman, Abu Baker A. Najm, Ammar Hatem Kamel, Nadhir Al-Ansari. Evaluate the Optimal Future Demand of Water Consumption in Al-Anbar Province in the West of Iraq. International Journal of Sustainable Development and Planning. 2021; 16 (3):457-462.

Chicago/Turabian Style

Sadeq Oleiwi Sulaiman; Abu Baker A. Najm; Ammar Hatem Kamel; Nadhir Al-Ansari. 2021. "Evaluate the Optimal Future Demand of Water Consumption in Al-Anbar Province in the West of Iraq." International Journal of Sustainable Development and Planning 16, no. 3: 457-462.

Research article
Published: 21 June 2021 in Advances in Civil Engineering
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Currently, desertification is a major problem in the western desert of Iraq. The harsh nature, remoteness, and size of the desert make it difficult and expensive to monitor and mitigate desertification. Therefore, this study proposed a comprehensive and cost-effective method, via the integration of geographic information systems (GISs) and remote sensing (RS) techniques to estimate the potential risk of desertification, to identify the most vulnerable areas and determine the most appropriate sites for rainwater conservation. Two indices, namely, the Normalized Differential Vegetation Index (NDVI) and Land Degradation Index (LDI), were used for a cadastral assessment of land degradation. The findings of the combined rainwater harvesting appropriateness map, and the maps of NDVI and LDI changes found that 65% of highly suitable land for rainwater harvesting lies in the large change and 35% lies in the small change of NDVI, and 85% of highly suitable land lies in areas with a moderate change and 12% lies in strong change of LDI. The adoption of the weighted linear combination (WLC) and Boolean methods within the GIS environment, and the analysis of NDVI with LDI changes can allow hydrologists, decision-makers, and planners to quickly determine and minimize the risk of desertification and to prioritize the determination of suitable sites for rainwater harvesting.

ACS Style

Khamis Naba Sayl; Sadeq Oleiwi Sulaiman; Ammar Hatem Kamel; Nur Shazwani Muhammad; Jazuri Abdullah; Nadhir Al-Ansari. Minimizing the Impacts of Desertification in an Arid Region: A Case Study of the West Desert of Iraq. Advances in Civil Engineering 2021, 2021, 1 -12.

AMA Style

Khamis Naba Sayl, Sadeq Oleiwi Sulaiman, Ammar Hatem Kamel, Nur Shazwani Muhammad, Jazuri Abdullah, Nadhir Al-Ansari. Minimizing the Impacts of Desertification in an Arid Region: A Case Study of the West Desert of Iraq. Advances in Civil Engineering. 2021; 2021 ():1-12.

Chicago/Turabian Style

Khamis Naba Sayl; Sadeq Oleiwi Sulaiman; Ammar Hatem Kamel; Nur Shazwani Muhammad; Jazuri Abdullah; Nadhir Al-Ansari. 2021. "Minimizing the Impacts of Desertification in an Arid Region: A Case Study of the West Desert of Iraq." Advances in Civil Engineering 2021, no. : 1-12.

Original paper
Published: 05 June 2021 in Geotechnical and Geological Engineering
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Adopting a low spatial resolution remote sensing imagery to get an accurate estimation of Land Use Land Cover is a difficult task to perform. Image fusion plays a big role to map the Land Use Land Cover. Therefore, This study aims to find out a refining method for the Land Use Land Cover estimating using these steps; (1) applying a three pan-sharpening fusion approaches to combine panchromatic imagery that has high spatial resolution with multispectral imagery that has low spatial resolution, (2) employing five pixel-based classifier approaches on multispectral imagery and fused images; artificial neural net, support vector machine, parallelepiped, Mahalanobis distance and spectral angle mapper, (3) make a statistical comparison between image classification results. The Landsat-8 image was adopted for this research. There are twenty Land Use Land Cover thematic maps were generated in this study. A suitable and reliable Land Use Land Cover method was presented based on the most accurate results. The results validation was performed by adopting a confusion matrix method. A comparison made between the images classification results of multispectral imagery and all fused images levels. It proved the Land Use Land Cover map produced by Gram–Schmidt Pan-sharpening and classified by support vector machine method has the most accurate result among all other multispectral imagery and fused images that classified by the other classifiers, it has an overall accuracy about (99.85%) and a kappa coefficient of about (0.98). However, the spectral angle mapper algorithm has the lowest accuracy compared to all other adopted methods, with overall accuracy of 53.41% and the kappa coefficient of about 0.48. The proposed procedure is useful in the industry and academic side for estimating purposes. In addition, it is also a good tool for analysts and researchers, who could interest to extend the technique to employ different datasets and regions.

ACS Style

Hayder Dibs; Hashim Ali Hasab; Ammar Shaker Mahmoud; Nadhir Al-Ansari. Fusion Methods and Multi-classifiers to Improve Land Cover Estimation Using Remote Sensing Analysis. Geotechnical and Geological Engineering 2021, 1 -18.

AMA Style

Hayder Dibs, Hashim Ali Hasab, Ammar Shaker Mahmoud, Nadhir Al-Ansari. Fusion Methods and Multi-classifiers to Improve Land Cover Estimation Using Remote Sensing Analysis. Geotechnical and Geological Engineering. 2021; ():1-18.

Chicago/Turabian Style

Hayder Dibs; Hashim Ali Hasab; Ammar Shaker Mahmoud; Nadhir Al-Ansari. 2021. "Fusion Methods and Multi-classifiers to Improve Land Cover Estimation Using Remote Sensing Analysis." Geotechnical and Geological Engineering , no. : 1-18.

Journal article
Published: 05 June 2021 in Ain Shams Engineering Journal
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Solar radiation plays a pivotal role in the energy balance at the Earth's surface, evaporation, snow melting, water requirements of plants, and hydrological control of catchments. In this work, performance of ERA-Interim (a reanalysis dataset) was examined to estimate solar radiation at Ahvaz, BandarAbbas, and Kermanshah weather stations representing the even spatial distribution over Iran using eight empirical models and an artificial intelligence-based model (SVM: Support Vector Machine). In the calibration set, SVM exhibited the best performance with RMSEs of 249, 299 and 437 J.cm−2.day−1 at the aforementioned stations, respectively. In validation set, SVM reduced the errors in the estimates of solar radiation by 2.5 and 7.3 percent compared to the best empirical model at Ahvaz station (Abdallah model, RMSE = 242 J.cm−2.day−1) and Kermanshah station (Angstrom-Prescott model, RMSE = 315 J.cm−2.day−1), respectively. During the validation at BandarAbbas station, Bahel and Abdallah model (RMSE = 309 J.cm−2.day−1), Angstrom-Prescott model (RMSE = 310 J.cm−2.day−1) and SVM (RMSE = 312 J.cm−2.day−1) showed a relatively similar performance. The results also showed that the ERA-Interim dataset can be a comparatively suitable alternative to some of the empirical models, where radiation or the input parameters of empirical models are not directly measured, with RMSEs ​​of 382.81, 320.82 and 414.1 J.cm−2.day−1 at Ahvaz, BandarAbbas, and Kermanshah stations, respectively (in validation phase); although its error rates are significant compared with the SVM model, and substituting it for artificial intelligence-based models is not recommended.

ACS Style

Babak Mohammadi; Roozbeh Moazenzadeh; Quoc Bao Pham; Nadhir Al-Ansari; Khalil Ur Rahman; Duong Tran Anh; Zheng Duan. Application of ERA-Interim, empirical models, and an artificial intelligence-based model for estimating daily solar radiation. Ain Shams Engineering Journal 2021, 1 .

AMA Style

Babak Mohammadi, Roozbeh Moazenzadeh, Quoc Bao Pham, Nadhir Al-Ansari, Khalil Ur Rahman, Duong Tran Anh, Zheng Duan. Application of ERA-Interim, empirical models, and an artificial intelligence-based model for estimating daily solar radiation. Ain Shams Engineering Journal. 2021; ():1.

Chicago/Turabian Style

Babak Mohammadi; Roozbeh Moazenzadeh; Quoc Bao Pham; Nadhir Al-Ansari; Khalil Ur Rahman; Duong Tran Anh; Zheng Duan. 2021. "Application of ERA-Interim, empirical models, and an artificial intelligence-based model for estimating daily solar radiation." Ain Shams Engineering Journal , no. : 1.

Journal article
Published: 30 May 2021 in Atmosphere
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In the present study, estimating pan evaporation (Epan) was evaluated based on different input parameters: maximum and minimum temperatures, relative humidity, wind speed, and bright sunshine hours. The techniques used for estimating Epan were the artificial neural network (ANN), wavelet-based ANN (WANN), radial function-based support vector machine (SVM-RF), linear function-based SVM (SVM-LF), and multi-linear regression (MLR) models. The proposed models were trained and tested in three different scenarios (Scenario 1, Scenario 2, and Scenario 3) utilizing different percentages of data points. Scenario 1 includes 60%: 40%, Scenario 2 includes 70%: 30%, and Scenario 3 includes 80%: 20% accounting for the training and testing dataset, respectively. The various statistical tools such as Pearson’s correlation coefficient (PCC), root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), and Willmott Index (WI) were used to evaluate the performance of the models. The graphical representation, such as a line diagram, scatter plot, and the Taylor diagram, were also used to evaluate the proposed model’s performance. The model results showed that the SVM-RF model’s performance is superior to other proposed models in all three scenarios. The most accurate values of PCC, RMSE, NSE, and WI were found to be 0.607, 1.349, 0.183, and 0.749, respectively, for the SVM-RF model during Scenario 1 (60%: 40% training: testing) among all scenarios. This showed that with an increase in the sample set for training, the testing data would show a less accurate modeled result. Thus, the evolved models produce comparatively better outcomes and foster decision-making for water managers and planners.

ACS Style

Manish Kumar; Anuradha Kumari; Deepak Kumar; Nadhir Al-Ansari; Rawshan Ali; Raushan Kumar; Ambrish Kumar; Ahmed Elbeltagi; Alban Kuriqi. The Superiority of Data-Driven Techniques for Estimation of Daily Pan Evaporation. Atmosphere 2021, 12, 701 .

AMA Style

Manish Kumar, Anuradha Kumari, Deepak Kumar, Nadhir Al-Ansari, Rawshan Ali, Raushan Kumar, Ambrish Kumar, Ahmed Elbeltagi, Alban Kuriqi. The Superiority of Data-Driven Techniques for Estimation of Daily Pan Evaporation. Atmosphere. 2021; 12 (6):701.

Chicago/Turabian Style

Manish Kumar; Anuradha Kumari; Deepak Kumar; Nadhir Al-Ansari; Rawshan Ali; Raushan Kumar; Ambrish Kumar; Ahmed Elbeltagi; Alban Kuriqi. 2021. "The Superiority of Data-Driven Techniques for Estimation of Daily Pan Evaporation." Atmosphere 12, no. 6: 701.

Journal article
Published: 13 May 2021 in Ain Shams Engineering Journal
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In the current research, a newly developed ensemble intelligent predictive model called Bagging Regression (BGR) is proposed to predict the compressive strength of a hollow concrete masonry prism (fp). A matrix of input combinations is constructed based on several predictive variables, including mortar compressive strength (fm), concrete block compressive strength (fb), and height to thickness ratio (h/t). Three modeling scenarios based on the different data divisions (i.e., 80–20%, 75–25%, and 70–30%) for training-testing phases are evaluated. The proposed model is validated against classical support vector regression (SVR) and decision tree regression (DTR) models using statistical indicators and graphical presentations. Results indicate the superiority of the BGR over the other models. In quantitative terms, BGR attains minimum root mean square error (RMSE = 1.51 MPa) using the data division scenario of 80–20% in the testing phase, while DTR and standalone SVR models offer RMSE = 2.55 and 2.33 MPa, respectively.

ACS Style

Ahmad Sharafati; Seyed Babak Haji Seyed Asadollah; Nadhir Al-Ansari. Application of bagging ensemble model for predicting compressive strength of hollow concrete masonry prism. Ain Shams Engineering Journal 2021, 1 .

AMA Style

Ahmad Sharafati, Seyed Babak Haji Seyed Asadollah, Nadhir Al-Ansari. Application of bagging ensemble model for predicting compressive strength of hollow concrete masonry prism. Ain Shams Engineering Journal. 2021; ():1.

Chicago/Turabian Style

Ahmad Sharafati; Seyed Babak Haji Seyed Asadollah; Nadhir Al-Ansari. 2021. "Application of bagging ensemble model for predicting compressive strength of hollow concrete masonry prism." Ain Shams Engineering Journal , no. : 1.

Original paper
Published: 05 May 2021 in Arabian Journal of Geosciences
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Sediment transport in rivers is an important and complex process. It is very important to know the nature and quantities of sediments transported in course of rivers to achieve prudent water management. Due to the presence of most of the important projects on or near the banks of the river in the study area, so there is always a fear that these projects will be affected by the processes of erosion, transport, and sedimentation among the decision makers. Therefore, there is a need to develop our knowledge of the suitable equations that can be applied with acceptable accuracy to obtain satisfactory results for monitoring the processes of erosion, sedimentation, and transport that occur in River path to monitor and anticipate the changes taking place in the areas of the riverbanks. This study was carried out to check the reliability of different sediment transport formulas using data collected from the Euphrates River at the thermal power station in Al Anbar province, Iraq. The study also aimed to select the best formula for this site. Hydrological data have been collected. These were used for computing the total sediment load in the river at a specified cross-section using common sediment transport formulas ascribed to Ackers-White, Bagnold, Yang, Colby, Shen and Hung, and Engelund-Hansen. The performance of these formulas was assessed based on the accuracy of the predictions of the observed sediment load within a limited discrepancy ratio. The evaluations showed that the Engelund-Hansen formula represented the best formula for this river reach.

ACS Style

Sadeq Oleiwi Sulaiman; Nadhir Al-Ansari; Ahmed Shahadha; Rasha Ismaeel; Sura Mohammad. Evaluation of sediment transport empirical equations: case study of the Euphrates River West Iraq. Arabian Journal of Geosciences 2021, 14, 1 -11.

AMA Style

Sadeq Oleiwi Sulaiman, Nadhir Al-Ansari, Ahmed Shahadha, Rasha Ismaeel, Sura Mohammad. Evaluation of sediment transport empirical equations: case study of the Euphrates River West Iraq. Arabian Journal of Geosciences. 2021; 14 (10):1-11.

Chicago/Turabian Style

Sadeq Oleiwi Sulaiman; Nadhir Al-Ansari; Ahmed Shahadha; Rasha Ismaeel; Sura Mohammad. 2021. "Evaluation of sediment transport empirical equations: case study of the Euphrates River West Iraq." Arabian Journal of Geosciences 14, no. 10: 1-11.

Journal article
Published: 20 April 2021 in IEEE Access
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Accurate estimation of drought events is vital for the mitigation of their adverse consequences on water resources, agriculture and ecosystems. Machine learning algorithms are promising methods for drought prediction as they require less time, minimal inputs, and are relatively less complex than dynamic or physical models. In this study, a combination of machine learning with the Standardized Precipitation Evapotranspiration Index (SPEI) is proposed for analysis of drought within a representative case study in the Tibetan Plateau, China, for the period of 1980–2019. Two timescales of 3 months (SPEI-3) and 6 months (SPEI-6) aggregation were considered. Four machine learning models of Random Forest (RF), the Extreme Gradient Boost (XGB), the Convolutional neural network (CNN) and the Long-term short memory (LSTM) were developed for the estimation of the SPEIs. Seven scenarios of various combinations of climate variables as input were adopted to build the models. The best models were XGB with scenario 5 (precipitation, average temperature, minimum temperature, maximum temperature, wind speed and relative humidity) and RF with scenario 6 (precipitation, average temperature, minimum temperature, maximum temperature, wind speed, relative humidity and sunshine) for estimating SPEI-3. LSTM with scenario 4 (precipitation, average temperature, minimum temperature, maximum temperature, wind speed) was relatively better for SPEI-6 estimation. The best model for SPEI-6 was XGB with scenario 5 and RF with scenario 7 (all input climate variables, i.e., scenario 6 + solar radiation). Based on the NSE index, the performances of XGB and RF models are classified as good fits for scenarios 4 to 7 for both timescales. The developed models produced satisfactory results and they could be used as a rapid tool for decision making by water-managers.

ACS Style

Ali Mokhtar; Mohammadnabi Jalali; Hongming He; Nadhir Al-Ansari; Ahmed Elbeltagi; Karam Alsafadi; Hazem Ghassan Abdo; Saad Sh. Sammen; Yeboah Gyasi-Agyei; Jesus Rodrigo-Comino. Estimation of SPEI Meteorological Drought Using Machine Learning Algorithms. IEEE Access 2021, 9, 65503 -65523.

AMA Style

Ali Mokhtar, Mohammadnabi Jalali, Hongming He, Nadhir Al-Ansari, Ahmed Elbeltagi, Karam Alsafadi, Hazem Ghassan Abdo, Saad Sh. Sammen, Yeboah Gyasi-Agyei, Jesus Rodrigo-Comino. Estimation of SPEI Meteorological Drought Using Machine Learning Algorithms. IEEE Access. 2021; 9 ():65503-65523.

Chicago/Turabian Style

Ali Mokhtar; Mohammadnabi Jalali; Hongming He; Nadhir Al-Ansari; Ahmed Elbeltagi; Karam Alsafadi; Hazem Ghassan Abdo; Saad Sh. Sammen; Yeboah Gyasi-Agyei; Jesus Rodrigo-Comino. 2021. "Estimation of SPEI Meteorological Drought Using Machine Learning Algorithms." IEEE Access 9, no. : 65503-65523.

Conference paper
Published: 10 April 2021 in Soil and Recycling Management in the Anthropocene Era
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As the world’s population has grown, waste generation has increased rapidly. Solid waste management requires a greater knowledge of the composition, generation quantity, physical properties, and impacts of economic aspects. This paper clarified the status of municipal solid waste management across Sulaimaniyah governorate and presented a comprehensive overview and implication of poor solid waste management in the study area. The core aspects covered were the future estimations of the cumulative solid waste amount with population growth by 2040 using brief calculations of the waste generation rate from 2016. The results revealed that the daily per capita waste generation in the Sulaimaniyah governorate is 1.32 kg by 2040, a cumulative solid waste of about 10,445,829 tons, and an estimated volume of 9,146,368 m3 which will be required for the disposal site in the future.

ACS Style

Karwan Alkaradaghi; Salahalddin Saeed Ali; Nadhir Al-Ansari; Tara Ali; Jan Laue. Quantitative Estimation of Municipal Solid Waste in Sulaimaniyah Governorate, Iraq. Soil and Recycling Management in the Anthropocene Era 2021, 265 -270.

AMA Style

Karwan Alkaradaghi, Salahalddin Saeed Ali, Nadhir Al-Ansari, Tara Ali, Jan Laue. Quantitative Estimation of Municipal Solid Waste in Sulaimaniyah Governorate, Iraq. Soil and Recycling Management in the Anthropocene Era. 2021; ():265-270.

Chicago/Turabian Style

Karwan Alkaradaghi; Salahalddin Saeed Ali; Nadhir Al-Ansari; Tara Ali; Jan Laue. 2021. "Quantitative Estimation of Municipal Solid Waste in Sulaimaniyah Governorate, Iraq." Soil and Recycling Management in the Anthropocene Era , no. : 265-270.

Conference paper
Published: 10 April 2021 in Soil and Recycling Management in the Anthropocene Era
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For understanding and prediction of transport in different groundwater aquifers media, the groundwater flow velocity (magnitude and direction) has to be considered. Halabja Saidsadiq Basin is located in the northeast part of Iraq, which covers an area of 1278 square kilometers with population of more than 200,000 inhabitants. The climate of this area is hot in the summers and cold in the winters. Groundwater aquifers in this area provide approximately 90% of whole water requirements. Therefore, it is important to understand some groundwater features in the area such as groundwater flow velocity, to prevent contaminant transport toward the groundwater aquifers. The main aim of this study was to apply geographic information system technique to estimate the magnitude and direction of the groundwater seepage velocity based on several hydrological and hydrogeological data in the region. The results revealed that the seepage velocity magnitude ranged from (0 to 51) m/d, while the flow direction is from the eastern to the western part of the study area.

ACS Style

Twana Abdullah; Salahalddin Saeed Ali; Nadhir Al-Ansari; Sven Knutsson. Seepage Velocity of Different Groundwater Aquifers in Halabja Saidsadiq Basin—NE of Iraq. Soil and Recycling Management in the Anthropocene Era 2021, 1683 -1687.

AMA Style

Twana Abdullah, Salahalddin Saeed Ali, Nadhir Al-Ansari, Sven Knutsson. Seepage Velocity of Different Groundwater Aquifers in Halabja Saidsadiq Basin—NE of Iraq. Soil and Recycling Management in the Anthropocene Era. 2021; ():1683-1687.

Chicago/Turabian Style

Twana Abdullah; Salahalddin Saeed Ali; Nadhir Al-Ansari; Sven Knutsson. 2021. "Seepage Velocity of Different Groundwater Aquifers in Halabja Saidsadiq Basin—NE of Iraq." Soil and Recycling Management in the Anthropocene Era , no. : 1683-1687.

Conference paper
Published: 10 April 2021 in Soil and Recycling Management in the Anthropocene Era
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Groundwater flows from high to low hydraulic head regions. This flow is controlled by Darcy velocity equation. Darcy velocity represents the flow velocity within the cross-sectional area of the soil. Actually, however, groundwater flows at a higher velocity than that of Darcy’s, called seepage velocity. Seepage velocity considers the real area (pores area) that is available for groundwater flow in calculations. There are many applications which are affected by the seepage/Darcy velocity, e.g., underground thermal energy storage systems and contaminants transfer in soil. In spite of the importance of Darcy/seepage velocity in many applications, there is no specific method to depict these velocities on a large-scale map. This paper proposed a tool that can be used to depict the seepage velocity on a large scale. The considered tool is offered by ArcMap/GIS software. To explain how this tool works, Babylon (Iraq) was considered as a study area.

ACS Style

Qais Al-Madhlom; Nadhir Al-Ansari; Hussain Musa Hussain; Jan Laue. Seepage Velocity Mapping Using ArcMap/GIS Software. Soil and Recycling Management in the Anthropocene Era 2021, 1689 -1695.

AMA Style

Qais Al-Madhlom, Nadhir Al-Ansari, Hussain Musa Hussain, Jan Laue. Seepage Velocity Mapping Using ArcMap/GIS Software. Soil and Recycling Management in the Anthropocene Era. 2021; ():1689-1695.

Chicago/Turabian Style

Qais Al-Madhlom; Nadhir Al-Ansari; Hussain Musa Hussain; Jan Laue. 2021. "Seepage Velocity Mapping Using ArcMap/GIS Software." Soil and Recycling Management in the Anthropocene Era , no. : 1689-1695.

Conference paper
Published: 10 April 2021 in Soil and Recycling Management in the Anthropocene Era
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The Governorate of Sulaymaniyah is located in the north of Iraq with a population of 856 990 in 2016. The process of selecting a landfill site is considered as a complicated task with several factors and regulations to take into account. Currently, there are no landfill sites in the Sulaymaniyah Governorate that Governorate that respect the prerequisites of the scientific and environmental criteria. Therefore, in this study, thirteen suitable criteria were selected. These criteria are: groundwater depth, urban area, rivers, villages, soil types, elevation, roads, slope, land use, archaeological sites, power lines, oil and gas field, and geology. These criteria were used in the GIS (Geographic Information System), due to its high ability to manage and analyze various data. In addition, the AHP (Analytical Hierarchy Process) method was used to derive the weightings of criteria, through a matrix of pairwise comparison. In this work, the study site was classified into four different areas according to the Suitability Index for landfill sites, where they all satisfied the scientific and environmental criteria.

ACS Style

Karwan Alkaradaghi; Salahalddin Saeed Ali; Nadhir Al-Ansari; Jan Laue. Combining GIS Applications and Analytic Hierarchy Process Method for Landfill Siting in Sulaimaniyah, Iraq. Soil and Recycling Management in the Anthropocene Era 2021, 1811 -1815.

AMA Style

Karwan Alkaradaghi, Salahalddin Saeed Ali, Nadhir Al-Ansari, Jan Laue. Combining GIS Applications and Analytic Hierarchy Process Method for Landfill Siting in Sulaimaniyah, Iraq. Soil and Recycling Management in the Anthropocene Era. 2021; ():1811-1815.

Chicago/Turabian Style

Karwan Alkaradaghi; Salahalddin Saeed Ali; Nadhir Al-Ansari; Jan Laue. 2021. "Combining GIS Applications and Analytic Hierarchy Process Method for Landfill Siting in Sulaimaniyah, Iraq." Soil and Recycling Management in the Anthropocene Era , no. : 1811-1815.