| 1. |
- Abba, S. I., et al.
(författare)
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Effluents quality prediction by using nonlinear dynamic block-oriented models : A system identification approach
- 2021
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Ingår i: Desalination and Water Treatment. - : Desalination Publications. - 1944-3994 .- 1944-3986. ; 218, s. 52-62
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Tidskriftsartikel (refereegranskat)abstract
- The dynamic and complex municipal wastewater treatment plant (MWWTP) process should be handled efficiently to safeguard the excellent quality of effluents characteristics. Most of the available mathematical models do not efficiently capture the MWWTP process, in such cases, the data-driven models are reliable and indispensable for effective modeling of effluents characteristics. In the present research, two nonlinear system identification (NSI) models namely; Hammerstein-Wiener model (HW) and nonlinear autoregressive with exogenous (NARX) neural network model, and a classical autoregressive (AR) model were proposed to predict the characteristics of the effluent of total suspended solids (TSSeff) and pHeff from Nicosia MWWTP in Cyprus. In order to attain the optimal models, two different combinations of input variables were cast through auto-correla-tion function and partial auto-correlation analysis. The prediction accuracy was evaluated using three statistical indicators the determination coefficient (DC), root mean square error (RMSE) and correlation coefficient (CC). The results of the appraisal indicated that the HW model outperformed NARX and AR models in predicting the pHeff, while the NARX model performed better than the HW and AR models for TSSeff prediction. It was evident that the accuracy of the HW increased averagely up to 18% with regards to the NARX model for pHeff . Likewise, the TSSeff performance increased averagely up to 25% with regards to the HW model. Also, in the validation phase, the HW model yielded DC, RMSE, and CC of 0.7355, 0.1071, and 0.8578 for pHeff, while the NARX model yielded 0.9804, 0.0049 and 0.9902 for TSSeff, respectively. For comparison with the traditional AR, the results showed that both HW and NARX models outperformed in (TSSeff) and pHeff prediction at the study location. Hence, the outcomes determined that the NSI model (i.e., HW and NARX) are reliable and resilient modeling tools that could be adopted for pHeff and TSSeff prediction.
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| 2. |
- Abba, S.I., et al.
(författare)
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Integrating feature extraction approaches with hybrid emotional neural networks for water quality index modeling
- 2022
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Ingår i: Applied Soft Computing. - : Elsevier. - 1568-4946 .- 1872-9681. ; 114
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Tidskriftsartikel (refereegranskat)abstract
- The establishment of water quality prediction models is vital for aquatic ecosystems analysis. The traditional methods of water quality index (WQI) analysis are time-consuming and associated with a high degree of errors. These days, the application of artificial intelligence (AI) based models are trending for capturing nonlinear and complex processes. Therefore, the present study was conducted to predict the WQI in the Kinta River, Malaysia by employing the hybrid AI model i.e., GA-EANN (genetic algorithm-emotional artificial neural network). The extreme gradient boosting (XGB) and neuro-sensitivity analysis (NSA) approaches were utilized for feature extraction, and six different model combinations were derived to examine the relationship among the WQI with water quality (WQ) variables. The efficacy of the proposed hybrid GA-EANN model was evaluated against the backpropagation neural network (BPNN) and multilinear regression (MLR) models during calibration, and validation periods based on Nash–Sutcliffeefficiency (NSE), mean square error (MSE), root mean square error (RMSE), mean absolute percentage error (MAPE), and correlation coefficient (CC) indicators. According to results of appraisal the hybrid GA-EANN model produced better outcomes (NSE = 0.9233/ 0.9018, MSE = 10.5195/ 9.7889 mg/L, RMSE = 3.2434/ 3.1287 mg/L, MAPE = 3.8032/ 3.0348 mg/L, CC = 0.9609/ 0.9496) in calibration/ validation phases than BPNN and MLR models. In addition, the results indicate the better performance and suitability of the hybrid GA-EANN model with five input parameters in predicting the WQI for the study site.
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| 3. |
- Abbas, Nahla, et al.
(författare)
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Flow Variation of the Major Tributaries of Tigris River Due to Climate Change
- 2019
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Ingår i: Engineering. - : Scientific Research Publishing. - 1947-3931 .- 1947-394X. ; 11:8, s. 437-442
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Tidskriftsartikel (refereegranskat)abstract
- Iraq relies greatly on the flow of the Euphrates and Tigris Rivers and their tributaries. Five tributaries namely Khabour, Greater Zab, Lesser Zab, AlAd- hiam and Daylia, which are the major tributaries of Tigris River, sustain Northern Iraq Region, a semi-arid, mainly a pastureland. These tributaries contribute about 24 km3 of water annually. The discharge in the tributaries, in recent times, has been suffering increasing variability contributing to more severe droughts and floods apparently due to climate change. This is because there were no dams constructed outside Iraq previously. For an appropriate appreciation, Soil Water Assessment Tool (SWAT) model was used to evaluate the impact of climate change on their discharge for a half-centennial lead time to 2046-2064 and a centennial lead time to 2080-2100. The suitability of the model was first evaluated, and then, outputs from six GCMs were incorporated to evaluate the impacts of climate change on water resources under three emission scenarios: A1B, A2 and B1. The results showed that wa-ter resources are expected to decrease with time.
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| 4. |
- Abbas, Nahla, et al.
(författare)
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Impacts of Climate Change on Water Resources in Diyala River Basin, Iraq
- 2016
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Ingår i: Journal of Civil Engineering and Architecture. - New York : David Publishing Company. - 1934-7359 .- 1934-7367. ; 10:9, s. 1059-1074
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Tidskriftsartikel (refereegranskat)abstract
- Diyala River is the third largest tributary of the Tigris River running 445 km length and draining an area of 32,600 km2. The river is the major source of water supply for Diyala City for municipal, domestic, agriculture and other purposes. Diyala River Basin currently is suffering from water scarcity and contamination problems. Up-to-date studies have shown that blue and green waters of a basin have been demonstrating increasing variability contributing to more severe droughts and floods seemingly due to climate change. To obtain better understanding of the impacts of climate change on water resources in Diyala River Basin in near 2046~2064 and distant future 2080~2100, SWAT (soil and water assessment tool) was used. The model is first examined for its capability of capturing the basin characteristics, and then, projections from six GCMs (general circulation models) are incorporated to assess the impacts of climate change on water resources under three emission scenarios: A2, A1B and B1. The results showed deteriorating water resources regime into the future.
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| 5. |
- Abbas, Nahlah, et al.
(författare)
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Recent Trends and Long-Range Forecasts of Water Resources of Northeast Iraq and Climate Change Adaptation Measures
- 2018
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Ingår i: Water. - Switzerland : MDPI. - 2073-4441. ; 10:11, s. 1-19
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Tidskriftsartikel (refereegranskat)abstract
- Iraq has been experiencing water resources scarcity, and is vulnerable to climate change. Analysis of historical data revealed that the region is experiencing climate change to a degree higher than generally reported elsewhere. The relationship between climate change and its effect on water resources of a region has been sparsely addressed in published literature. To fill that gap this research work first investigates if there has been a significant change in climate in the region, which has been found to be true. In the next stage, the research projects future climatic scenarios of the region based on six oft-used General CirculationModel (GCM) ensembles, namely CCSM4, CSIRO-Mk3.6.0, GFDL-ESM2M, MEROC5, HadGEM2-ES, and IPSL-CM5A-LR. The relationship between climate change and its impact on water resources is explored through the application of the popular, widely used SWAT model. The model depicts the availability of water resources, classified separately as blue and green waters, for near and distant futures for the region. Some of the findings are foreboding and warrants urgent attention of planners and decision makers. According to model outputs, the region may experience precipitation reduction of about 12.6% and 21% in near (2049–2069) and distant (2080–2099) futures, respectively under RCP8.5. Those figures under RCP4.5 are 15% and 23.4%, respectively and under RCP2.6 are 12.2% and 18.4%, respectively. As a consequence, the blue water may experience decreases of about 22.6% and 40% under RCP8.5, 25.8% and 46% under RCP4.5, and 34.4% and 31% under RCP2.6 during the periods 2049–2069 and 2080–2099, respectively. Green water, by contrast, may reduce by about 10.6% and 19.6% under RCP8.5, by about 14.8% and 19.4% under RCP4.5, and by about 15.8% and 14.2% under RCP2.6 during the periods 2049–2069 and 2080–2099, respectively. The research further investigates how the population are adapting to already changed climates and how they are expected to cope in the future when the shift in climate is expected to be much greater.
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| 6. |
- Abbas, Nahlah, et al.
(författare)
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The Impacts of Sea Level Rise on Basrah City,Iraq : The Impacts of Sea Level Rise on Basrah City,Iraq
- 2020
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Ingår i: Open Journal of Geology. - USA : Scientific Research Publishing. - 2161-7570 .- 2161-7589. ; 10:12, s. 1189-1197
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Tidskriftsartikel (refereegranskat)abstract
- Sea Level Rise (SLR) above the Mean Sea Level (MSL) is more likely to cause a significant risk to the coastal regions. This research explores the potential impact of sea level rise, due to climate change, on coastal areas. It examines the impact of sea level rise on Basrah city and adjacent cities in Iraq. A digital elevation model (DEM) was used to create a model of Potentially Inundated Areas, manipulated and processed in Geographical Information System version 10.7 (ArcGIS 10.7). Through this model, the impact of sea level rise was assessed on the surface area. After the susceptible areas were delineated, it was estimated that at worst case scenario of 5 m sea level rise will impact Basrah city by losing 38 percent of its total surface area.
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| 7. |
- Abbas, Zainab Dekan, et al.
(författare)
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Locating Dam Sites For Water Harvesting : Case Study Of Najaf Province, Iraq
- 2019
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Ingår i: Journal of Environmental Hydrology. - Canada : The International Association of Environmental Hydrology. - 1058-3912 .- 1996-7918. ; 27, s. 1-8
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Tidskriftsartikel (refereegranskat)abstract
- The Middle East is considered as an arid area. Iraq was an exception due to the presence of the Tigris and Euphrates Rivers. After 1970, the flow of these rivers started to decrease due to climate change and building of dams in the upper parts of the catchments of the rivers. Now, Iraq is experiencing water shortage problems. Rain water harvesting will definitely minimize the effect of water shortage problems. In this research an arid area was selected (al Najaf) to find out the best sites for water harvesting using GIS techniques. The good agreement between the results from a simple GIS model and observations in cases such as al Najaf Sea is indicating a promising future for GIS application in hydrological modeling. The present study proposed a function formula of estimating suitable dam site using existing geographic information map such as the digital elevation maps. It is expected that it will save time, cost and work force. Finally, through the contour map of the study area, the lowest three elevation values at the governorate level were observed (20, 40, 60m). Based on these values, three possibilities were suggested to select the dam sites.
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| 8. |
- Abdel-Hameed, Amal Mohamed, et al.
(författare)
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Estimation of Potato Water Footprint Using Machine Learning Algorithm Models in Arid Regions
- 2024
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Ingår i: Potato Research. - : Springer Nature. - 0014-3065 .- 1871-4528.
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Tidskriftsartikel (refereegranskat)abstract
- Precise assessment of water footprint to improve the water consumption and crop yield for irrigated agricultural efficiency is required in order to achieve water management sustainability. Although Penman-Monteith is more successful than other methods and it is the most frequently used technique to calculate water footprint, however, it requires a significant number of meteorological parameters at different spatio-temporal scales, which are sometimes inaccessible in many of the developing countries such as Egypt. Machine learning models are widely used to represent complicated phenomena because of their high performance in the non-linear relations of inputs and outputs. Therefore, the objectives of this research were to (1) develop and compare four machine learning models: support vector regression (SVR), random forest (RF), extreme gradient boost (XGB), and artificial neural network (ANN) over three potato governorates (Al-Gharbia, Al-Dakahlia, and Al-Beheira) in the Nile Delta of Egypt and (2) select the best model in the best combination of climate input variables. The available variables used for this study were maximum temperature (Tmax), minimum temperature (Tmin), average temperature (Tave), wind speed (WS), relative humidity (RH), precipitation (P), vapor pressure deficit (VPD), solar radiation (SR), sown area (SA), and crop coefficient (Kc) to predict the potato blue water footprint (BWF) during 1990–2016. Six scenarios (Sc1–Sc6) of input variables were used to test the weight of each variable in four applied models. The results demonstrated that Sc5 with the XGB and ANN model gave the most promising results to predict BWF in this arid region based on vapor pressure deficit, precipitation, solar radiation, crop coefficient data, followed by Sc1. The created models produced comparatively superior outcomes and can contribute to the decision-making process for water management and development planners.
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| 9. |
- Abdel-Hameed, Amal Mohamed, et al.
(författare)
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Winter Potato Water Footprint Response to Climate Change in Egypt
- 2022
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Ingår i: Atmosphere. - : MDPI. - 2073-4433. ; 13:7
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Tidskriftsartikel (refereegranskat)abstract
- The limited amount of freshwater is the most important challenge facing Egypt due to increasing population and climate change. The objective of this study was to investigate how climatic change affects the winter potato water footprint at the Nile Delta covering 10 governorates from 1990 to 2016. Winter potato evapotranspiration (ETC) was calculated based on daily climate variables of minimum temperature, maximum temperature, wind speed and relative humidity during the growing season (October–February). The Mann–Kendall test was applied to determine the trend of climatic variables, crop evapotranspiration and water footprint. The results showed that the highest precipitation values were registered in the northwest governorates (Alexandria followed by Kafr El-Sheikh). The potato water footprint decreased from 170 m3 ton−1 in 1990 to 120 m3 ton−1 in 2016. The blue-water footprint contributed more than 75% of the total; the remainder came from the green-water footprint. The findings from this research can help government and policy makers better understand the impact of climate change on potato crop yield and to enhance sustainable water management in Egypt’s major crop-producing regions to alleviate water scarcity.
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| 10. |
- Abdulhameed, Isam Mohammed, et al.
(författare)
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Optimising water resources management by Using Water Evaluation and Planning (WEAP) in the West of Iraq
- 2022
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Ingår i: Journal of Water and Land Development. - : Polish Academy of Sciences (PAN). - 1429-7426. ; :53, s. 176-186
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Tidskriftsartikel (refereegranskat)abstract
- Iraq has been suffering from decreasing Euphrates discharge due to the construction of dams within upstream countries and the use of surface irrigation systems. The country is facing a problem with meeting the increasing demand for water as a result of population growth and development in the industrial and agricultural sectors. Therefore, a simulation modelling was applied for western Iraq (Ramadi city as a case study) using the Water Evaluation and Planning System (WEAP) for the period 2018–2035. This research follows a four-step approach that involves: (i) evaluating the available water of the Euphrates River under declined water imports caused by the construction of dams in Turkey and Syria, (ii) assessing present and future water demands of the domestic, industrial, and agricultural sectors, (iii) improving water productivity (WP) by means of saving more water, (iv) estimating the economic returns under improved water use. The results showed that Iraq would face a serious problem in the coming years, represented by the limited storage of Haditha Dam, which is considered the strategic water storage site for the central and southern regions of Iraq. The study indicated the necessity of finding alternative sources of water supply by adopting new water management strategies to reduce the water deficit.
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