| 1. |
- Abdel-Hameed, Amal Mohamed, et al.
(author)
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Estimation of Potato Water Footprint Using Machine Learning Algorithm Models in Arid Regions
- 2024
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In: Potato Research. - : Springer Nature. - 0014-3065 .- 1871-4528.
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Journal article (peer-reviewed)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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| 2. |
- Al-Ansari, Nadhir, 1947-, et al.
(author)
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Solving the Water Resource Problems in Iraq
- 2024
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In: Engineering. - : Scientific Research Publishing. - 1947-3931 .- 1947-394X. ; 16:08, s. 205-223
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Journal article (peer-reviewed)abstract
- Iraq covers an area of 437072 km2 in the northeastern part of the Middle East. Its population now is more than 40 million. It relies mainly on its water resources from the Tigris and Euphrates Rivers and their tributaries. Recently, Iraq has been experiencing a severe water scarcity problem. This is mainly due to climate change, increased hydrological projects in riparian countries, and water resources mismanagement inside Iraq itself. To overcome the problem, a new strategy should be implemented. Such strategy should consider two main courses of action: a) serious negotiations with riparian countries to reach an agreement giving Iraq equitable water shares from the Tigris and Euphrates Rivers and their tributaries. b) Prudent water management practices inside Iraq that consider adopting realistic distribution of water between the governorates, rational policies aiming at increased water use efficiencies within Irrigation networks, increased use of non-conventional sources of water, adjustment of water tariffs and their collection procedures, improving agricultural techniques, introduction of intensive guidance and public awareness programs, and promulgation of new legislations, in addition to creation of human resources development programs.
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| 3. |
- Al-Ansari, Nadhir, 1947-, et al.
(author)
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Tigris River Water Quality Quantifying Using the Iraq Water Quality Index (IraqWQI) and Some Statistical Techniques
- 2024
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In: Engineering. - : Scientific Research Publishing. - 1947-3931 .- 1947-394X. ; 16:06, s. 149-166
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Journal article (peer-reviewed)abstract
- Evaluation of water quality is important for the management of water resources. The current study is focused on the interpretation of the water quality monitoring data of the Tigris River in Iraq by the application of the principal component analysis (PCA), cluster analysis (CA), and water quality index (WQI). Twelve water quality parameters were taken from 14 stations along the river Ca2+, Mg2+, Na+, K+, Cl−, SO2−4SO42− , HCO−3HCO3− , NO−3NO3− , TH, TDS, BOD5, and EC to apply the PCA and CA. The results show that the mean of all the parameters was under the standards except Ca2+, EC, Mg2+, TH, and SO2−4SO42− . The amount of EC is the critical factor that affects the river water quality. The PCA obtained one principal component responsible for 97% of the variation caused by different pollution sources. The CA divided the river into three regions of sampling stations with similar water quality, the best in the north, and the worst in the far south. In this paper, the computer-automated tool (IraqWQI) was presented and evaluated, which has been developed by authors to classify and measure the quality of Iraqi surface water. The proposed index is of hundred degrees and includes six variables for drinking water quality Cl−, TH, TDS, COD, DO, and total coliform (TC) according to the Iraqi specifications. The result of the IraqWQI application showed a decrease in the water quality of the river and its suitability for drinking in the south of the country. The best value of the index was (81.48, Good) in Fishkhabour during winter, and the worst value was (46.23, Bad) in Qurnah during summer. The result of this study proved the success and importance of using statistical techniques and WQI as useful tools for the management, control, and conservation of surface water.
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| 4. |
- Alkaradaghi, Karwan, et al.
(author)
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Detection of Bisphenol A (BPA) in Plastic Bottles Using Vertical Cultivation at Various Temperatures
- 2024
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In: Journal of Environmental Protection. - : Scientific Research Publishing. - 2152-2197 .- 2152-2219. ; 15:06, s. 656-671
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Journal article (peer-reviewed)abstract
- Polycarbonate plastics containing bisphenol A (BPA) used to manufacture drinking water bottles. Kurdistan region in northern Iraq is a developed area with increased pollution from plastic bottles. Trace amounts of BPA have been detected in bottled water samples. The absorption of BPA was measured with HPLC using a vertical cultivation system with Bulbs of the Allium Cepa plant planted in these plastic bottles with monitored growth. Vertical cultivation was found to have a low level of BPA in the plant cells, making it a safe cultivation method under specific climate conditions. The mean concentration of BPA in vertical cultivation is 0.19 ug/ml (3.8 ng for a 20 uL injection), and the Limit of Quantification (LOQ) is 0.63 ug/ml (12.7 ng for 20 uL injection). While Scanning Electron Microscope (SEM) shows that the concentrations are relatively low in water samples stored at room temperature compared to those exposed to direct sunlight (40°C) and water bottle samples stored at (-4°C), The correlation coefficients were found to be good (0.9992). SEM is used for plastic bottle samples stored at different temperatures. The images identify compound decay and explore the morphology of BPA in manufactured plastic materials.
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| 5. |
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| 6. |
- Das, Sushil K., et al.
(author)
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Calibration, validation and uncertainty analysis of a SWAT water quality model
- 2024
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In: Applied water science. - : Springer Nature. - 2190-5487 .- 2190-5495. ; 14:4
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Journal article (peer-reviewed)abstract
- Sediment and nutrient pollution in water bodies is threatening human health and the ecosystem, due to rapid land use changes and improper agricultural practices. The impact of the nonpoint source pollution needs to be evaluated for the sustainable use of water resources. An ideal tool like the soil and water assessment tool (SWAT) can assess the impact of pollutant loads on the drainage area, which could be beneficial for developing a water quality management model. This study aims to evaluate the SWAT model’s multi-objective and multivariable calibration, validation, and uncertainty analysis at three different sites of the Yarra River drainage area in Victoria, Australia. The drainage area is split into 51 subdrainage areas in the SWAT model. The model is calibrated and validated for streamflow from 1990 to 2008 and sediment and nutrients from 1998 to 2008. The results show that most of the monthly and annual calibration and validation for streamflow, nutrients, and sediment at the three selected sites are found with Nash–Sutcliffe efficiency values greater than 0.50. Furthermore, the uncertainty analysis of the model shows satisfactory results where the p-factor value is reliable by considering 95% prediction uncertainty and the d-factor value is close to zero. The model's results indicate that the model performs well in the river's watershed, which helps construct a water quality management model. Finally, the model application in the cost-effective management of water quality might reduce pollution in water bodies due to land use and agricultural activities, which would be beneficial to water management managers.
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| 7. |
- El Jery, Atef, et al.
(author)
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Isotherms, kinetics and thermodynamic mechanism of methylene blue dye adsorption on synthesized activated carbon
- 2024
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In: Scientific Reports. - : Springer Nature. - 2045-2322. ; 14:1
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Journal article (peer-reviewed)abstract
- The treatment of methylene blue (MB) dye wastewater through the adsorption process has been a subject of extensive research. However, a comprehensive understanding of the thermodynamic aspects of dye solution adsorption is lacking. Previous studies have primarily focused on enhancing the adsorption capacity of methylene blue dye. This study aimed to develop an environmentally friendly and cost-effective method for treating methylene blue dye wastewater and to gain insights into the thermodynamics and kinetics of the adsorption process for optimization. An adsorbent with selective methylene blue dye adsorption capabilities was synthesized using rice straw as the precursor. Experimental studies were conducted to investigate the adsorption isotherms and models under various process conditions, aiming to bridge gaps in previous research and enhance the understanding of adsorption mechanisms. Several adsorption isotherm models, including Langmuir, Temkin, Freundlich, and Langmuir–Freundlich, were applied to theoretically describe the adsorption mechanism. Equilibrium thermodynamic results demonstrated that the calculated equilibrium adsorption capacity (qe) aligned well with the experimentally obtained data. These findings of the study provide valuable insights into the thermodynamics and kinetics of methylene blue dye adsorption, with potential applications beyond this specific dye type. The utilization of rice straw as an adsorbent material presents a novel and cost-effective approach for MB dye removal from wastewater.
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| 8. |
- Gupta, Rajeev Kumar, et al.
(author)
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Biochar influences nitrogen and phosphorus dynamics in two texturally different soils
- 2024
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In: Scientific Reports. - : Springer Nature. - 2045-2322. ; 14
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Journal article (peer-reviewed)abstract
- Nitrogen (N) and phosphorus (P) are vital for crop growth. However, most agricultural systems have limited inherent ability to supply N and P to crops. Biochars (BCs) are strongly advocated in agrosystems and are known to improve the availability of N and P in crops through different chemical transformations. Herein, a soil-biochar incubation experiment was carried out to investigate the transformations of N and P in two different textured soils, namely clay loam and loamy sand, on mixing with rice straw biochar (RSB) and acacia wood biochar (ACB) at each level (0, 0.5, and 1.0% w/w). Ammonium N (NH4-N) decreased continuously with the increasing incubation period. The ammonium N content disappeared rapidly in both the soils incubated with biochars compared to the unamended soil. RSB increased the nitrate N (NO3–N) content significantly compared to ACB for the entire study period in both texturally divergent soils. The nitrate N content increased with the enhanced biochar addition rate in clay loam soil until 15 days after incubation; however, it was reduced for the biochar addition rate of 1% compared to 0.5% at 30 and 60 days after incubation in loamy sand soil. With ACB, the net increase in nitrate N content with the biochar addition rate of 1% remained higher than the 0.5% rate for 60 days in clay loam and 30 days in loamy sand soil. The phosphorus content remained consistently higher in both the soils amended with two types of biochars till the completion of the experiment.
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| 9. |
- Gupta, Sanjeev, et al.
(author)
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Sensitivity of daily reference evapotranspiration to weather variables in tropical savanna: a modelling framework based on neural network
- 2024
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In: Applied water science. - : Springer Nature. - 2190-5487 .- 2190-5495. ; 14:6
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Journal article (peer-reviewed)abstract
- Accurate prediction of reference evapotranspiration (ETo) is crucial for many water-related fields, including crop modelling, hydrologic simulations, irrigation scheduling and sustainable water management. This study compares the performance of different soft computing models such as artificial neural network (ANN), wavelet-coupled ANN (WANN), adaptive neuro-fuzzy inference systems (ANFIS) and multiple nonlinear regression (MNLR) for predicting ETo. The Gamma test technique was adopted to select the suitable input combination of meteorological variables. The performance of the models was quantitatively and qualitatively evaluated using several statistical criteria. The study showed that the ANN-10 model performed superior to the ANFIS-06, WANN-11 and MNLR models. The proposed ANN-10 model was more appropriate and efficient than the ANFIS-06, WANN-11 and MNLR models for predicting daily ETo. Solar radiation was found to be the most sensitive input variable. In contrast, actual vapour pressure was the least sensitive parameter based on sensitivity analysis.
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| 10. |
- Hameed, Mohammed Majeed, et al.
(author)
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Introducing high-order response surface method for improving scour depth prediction downstream of weirs
- 2024
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In: Applied water science. - : Springer Nature. - 2190-5487 .- 2190-5495. ; 14
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Journal article (peer-reviewed)abstract
- Scour depth downstream of weirs is considered one of the most important hydraulic problems, which greatly influences the stability of weirs. Recently, artificial intelligence (AI) methods have become increasingly popular in modeling hydraulic variables, especially scour depth, because they can capture nonlinear relationships between input variables and their associated objectives. Despite their importance, these models have problems with hyperparameter tuning in scour depth modeling due to their structures, so algorithms must be used to tune the hyperparameters. Moreover, these algorithms are usually tuned by using the trial-and-error method to select the hyperparameters such as the number of hidden nodes, transfer function, and learning rate, and in this case, the main problem is overfitting during the training phase. To solve these problems, the high-order response surface method (HORSM), an improved version of the response surface method (RSM), is used as an alternative approach for the first time in this study to predict the scour depth. The HORSM model is based on high-order polynomial functions (from two to six) compared with the artificial neural network model (ANN). The findings indicate that the fifth order of the HORSM polynomial function yields the most precise predictions, with a higher coefficient of determination (R2) of 0.912 and Willmott Index (WI) of 0.972 compared to the values obtained using ANN (R2 = 0.886 and WI = 0.927). Moreover, the accuracy of the predictions is represented by a reduction of the mean square error by up to 44.17 and 29.01% compared to the classical RSM and ANN, respectively. The suggested model established an excellent correlation and accuracy with experimental values.
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| 11. |
- Isam, Mubeen, et al.
(author)
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Optimization and modelling of Pb (II) and Cu (II) adsorption onto red algae (Gracilaria changii)-based activated carbon by using response surface methodology
- 2024
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In: Biomass Conversion and Biorefinery. - : Springer Nature. - 2190-6815 .- 2190-6823. ; 14:15, s. 16799-16818
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Journal article (peer-reviewed)abstract
- Activated carbon obtained from red algae Gracilaria changii was used as an adsorbent to remove Pb (II) and Cu (II) from an aqueous solution. The raw red algae were first impregnated with phosphoric acid, followed by thermal activation. The Box–Behnken design was used to optimize the activation process. The optimum activation parameters were 84%, 650 °C, and 175 min for acid concentration, activation temperature, and activation time, respectively. The obtained activated carbon had a high surface area of 867 m2/g. The removal of Pb (II) and Cu (II) was evaluated using a batch adsorption study. The effect of solution pH on the removal of metal ions was investigated within the range of 2–7. The effect of three important adsorption parameters (initial metal ion concentration, adsorbent dosage, and contact time) was analyzed using central composite design. The optimum removal of Pb (II) and Cu (II) was 76% and 36%, respectively. The adsorption kinetics obeyed the pseudo-second-order model, while the adsorption isotherm obeyed the Langmuir model.
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| 12. |
- Joshi, Bhupendra, et al.
(author)
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A comparative survey between cascade correlation neural network (CCNN) and feedforward neural network (FFNN) machine learning models for forecasting suspended sediment concentration
- 2024
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In: Scientific Reports. - : Springer Nature. - 2045-2322. ; 14
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Journal article (peer-reviewed)abstract
- Suspended sediment concentration prediction is critical for the design of reservoirs, dams, rivers ecosystems, various operations of aquatic resource structure, environmental safety, and water management. In this study, two different machine models, namely the cascade correlation neural network (CCNN) and feedforward neural network (FFNN) were applied to predict daily-suspended sediment concentration (SSC) at Simga and Jondhara stations in Sheonath basin, India. Daily-suspended sediment concentration and discharge data from 2010 to 2015 were collected and used to develop the model to predict suspended sediment concentration. The developed models were evaluated using statistical indices like Nash and Sutcliffe efficiency coefficient (NES), root mean square error (RMSE), Willmott’s index of agreement (WI), and Legates–McCabe’s index (LM), supplemented by a scatter plot, density plots, histograms and Taylor diagram for graphical representation. The developed model was evaluated and compared with CCNN and FFNN. Nine input combinations were explored using different lag-times for discharge (Qt-n) and suspended sediment concentration (St-n) as input variables, with the current suspended sediment concentration as the desired output, to develop CCNN and FFNN models. The CCNN4 model with 4 lagged inputs (St-1, St-2, St-3, St-4) outperformed the other developed models with the lowest RMSE = 95.02 mg/l and the highest NES = 0.0.662, WI = 0.890 and LM = 0.668 for the Jondhara Station while the same CCNN4 model secure as the best with the lowest RMSE = 53.71 mg/l and the highest NES = 0.785, WI = 0.936 and LM = 0.788 for the Simga Station. The result shows the CCNN model was better than the FFNN model for predicting daily-suspended sediment at both stations in the Sheonath basin, India. Overall, CCNN showed better forecasting potential for suspended sediment concentration compared to FFNN at both stations, demonstrating their applicability for hydrological forecasting with complex relationships.
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| 13. |
- Murad, Sadia, et al.
(author)
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Efficacy of DAP coated with bacterial strains and their metabolites for soil phosphorus availability and maize growth
- 2024
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In: Scientific Reports. - : Springer Nature. - 2045-2322. ; 14
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Journal article (peer-reviewed)abstract
- Phosphorus (P) use efficiency in alkaline/calcareous soils is only 20% due to precipitation of P2O5 with calcium and magnesium. However, coating Diammonium Phosphate (DAP) with phosphorus solubilizing bacteria (PSB) is more appropriate to increase fertilizer use efficiency. Therefore, with the aim to use inorganic fertilizers more effectively present study was conducted to investigate comparative effect of coated DAP with PSB strains Bacillus subtilis ZE15 (MN003400), Bacillus subtilis ZR3 (MN007185), Bacillus megaterium ZE32 (MN003401) and Bacillus megaterium ZR19 (MN007186) and their extracted metabolites with uncoated DAP under axenic conditions. Gene sequencing was done against various sources of phosphorus to analyze genes responsible for phosphatase activity. Alkaline phosphatase (ALP) gene amplicon of 380bp from all tested strains was showed in 1% w/v gel. Release pattern of P was also improved with coated fertilizer. The results showed that coated phosphatic fertilizer enhanced shoot dry weight by 43 and 46% under bacterial and metabolites coating respectively. Shoot and root length up to 44 and 42% with metabolites coated DAP and 41% with bacterial coated DAP. Physiological attributes also showed significant improvement with coated DAP over conventional. The results supported the application of coated DAP as a useful medium to raise crop yield even at lower application rates i.e., 50 and 75% DAP than non-coated 100% DAP application which advocated this coating technique a promising approach for advancing circular economy and sustainable development in modern agriculture.
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| 14. |
- Rauf, Lanja F., et al.
(author)
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Sustainability indicator for evaluating the ATES system in Halabja-Khurmal sub-basin NE-Iraq using GIS-based MCDA method
- 2024
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In: Applied water science. - : Springer Nature. - 2190-5487 .- 2190-5495. ; 14:6
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Journal article (peer-reviewed)abstract
- Thermal energy is utilized as an environmentally friendly energy source for seasonal heat and cold storage on a global scale. Specifically, the aquifer thermal energy storage system is highlighted for being cost-effective in cooling and heating applications. The study assesses the sustainability of the aquifer thermal energy storage in the Halabja-Khurmal sub-basin by evaluating six critical criteria: groundwater transmissivity, groundwater temperature, groundwater discharge, groundwater chemistry, population density, and per capita GDP. A multi-criteria decision analysis judgment is applied to analyze all criteria, resulting in a consistency ratio of 0.3% in the analytical hierarchy process. Consequently, the sustainability map for Aquifer Thermal Energy Storage in the Halabja-Khurmal sub-basin for heating reveals that 26.45% of the area is strongly sustainable located in the north and southwestern part of the sub-basin, 73.53% is moderate in the east, central, southeast, and southern regions, 0.02% is weakly sustainable as a tiny area in the southwestern. On the other hand, the sustainability map for Aquifer Thermal Energy Storage in the Halabja-Khurmal sub-basin for cooling reveals that 19% of the area is strongly sustainable located in the north, and southwestern parts of the sub-basin, 78% is moderate in the northeast, east, southeast, west, central, and southern regions, 3% is weakly sustainable as spots in the west and southwestern areas.
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| 15. |
- Raza, Ali, et al.
(author)
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Use of gene expression programming to predict reference evapotranspiration in different climatic conditions
- 2024
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In: Applied water science. - : Springer Nature. - 2190-5487 .- 2190-5495. ; 14
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Journal article (peer-reviewed)abstract
- Evapotranspiration plays a pivotal role in the hydrological cycle. It is essential to develop an accurate computational model for predicting reference evapotranspiration (RET) for agricultural and hydrological applications, especially for the management of irrigation systems, allocation of water resources, assessments of utilization and demand and water use allocations in rural and urban areas. The limitation of climatic data to estimate RET restricted the use of standard Penman–Monteith method recommended by food and agriculture organization (FAO-PM56). Therefore, the current study used climatic data such as minimum, maximum and mean air temperature (Tmax, Tmin, Tmean), mean relative humidity (RHmean), wind speed (U) and sunshine hours (N) to predict RET using gene expression programming (GEP) technique. In this study, a total of 17 different input meteorological combinations were used to develop RET models. The obtained results of each GEP model are compared with FAO-PM56 to evaluate its performance in both training and testing periods. The GEP-13 model (Tmax, Tmin, RHmean, U) showed the lowest errors (RMSE, MAE) and highest efficiencies (R2, NSE) in semi-arid (Faisalabad and Peshawar) and humid (Skardu) conditions while GEP-11 and GEP-12 perform best in arid (Multan, Jacobabad) conditions during training period. However, GEP-11 in Multan and Jacobabad, GEP-7 in Faisalabad, GEP-1 in Peshawar, GEP-13 in Islamabad and Skardu outperformed in testing period. In testing phase, the GEP models R2 values reach 0.99, RMSE values ranged from 0.27 to 2.65, MAE values from 0.21 to 1.85 and NSE values from 0.18 to 0.99. The study findings indicate that GEP is effective in predicting RET when there are minimal climatic data. Additionally, the mean relative humidity was identified as the most relevant factor across all climatic conditions. The findings of this study may be used to the planning and management of water resources in practical situations, as they demonstrate the impact of input variables on the RET associated with different climatic conditions.
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