Articles in press are presented at https://www.sciencedirect.com/journal/water-science-and-engineering/articles-in-press
2025, 18(1): 1-10.
doi: 10.1016/j.wse.2024.05.003
Abstract:
The highly efficient electrochemical treatment technology for dye-polluted wastewater is one of hot research topics in industrial wastewater treatment. This study reported a three-dimensional electrochemical treatment process integrating graphite intercalation compound (GIC) adsorption, direct anodic oxidation, and ·OH oxidation for decolourising Reactive Black 5 (RB5) from aqueous solutions. The electrochemical process was optimised using the novel progressive central composite design-response surface methodology (CCD-NPRSM), hybrid artificial neural network-extreme gradient boosting (hybrid ANN-XGBoost), and classification and regression trees (CART). CCD-NPRSM and hybrid ANN-XGBoost were employed to minimise errors in evaluating the electrochemical process involving three manipulated operational parameters: current density, electrolysis (treatment) time, and initial dye concentration. The optimised decolourisation efficiencies were 99.30%, 96.63%, and 99.14% for CCD-NPRSM, hybrid ANN-XGBoost, and CART, respectively, compared to the 98.46% RB5 removal rate observed experimentally under optimum conditions: approximately 20 mA/cm2 of current density, 20 min of electrolysis time, and 65 mg/L of RB5. The optimised mineralisation efficiencies ranged between 89% and 92% for different models based on total organic carbon (TOC). Experimental studies confirmed that the predictive efficiency of optimised models ranked in the descending order of hybrid ANN-XGBoost, CCD-NPRSM, and CART. Model validation using analysis of variance (ANOVA) revealed that hybrid ANN-XGBoost had a mean squared error (MSE) and a coefficient of determination (R2) of approximately 0.014 and 0.998, respectively, for the RB5 removal efficiency, outperforming CCD-NPRSM with MSE and R2 of 0.518 and 0.998, respectively. Overall, the hybrid ANN-XGBoost approach is the most feasible technique for assessing the electrochemical treatment efficiency in RB5 dye wastewater decolourisation.
The highly efficient electrochemical treatment technology for dye-polluted wastewater is one of hot research topics in industrial wastewater treatment. This study reported a three-dimensional electrochemical treatment process integrating graphite intercalation compound (GIC) adsorption, direct anodic oxidation, and ·OH oxidation for decolourising Reactive Black 5 (RB5) from aqueous solutions. The electrochemical process was optimised using the novel progressive central composite design-response surface methodology (CCD-NPRSM), hybrid artificial neural network-extreme gradient boosting (hybrid ANN-XGBoost), and classification and regression trees (CART). CCD-NPRSM and hybrid ANN-XGBoost were employed to minimise errors in evaluating the electrochemical process involving three manipulated operational parameters: current density, electrolysis (treatment) time, and initial dye concentration. The optimised decolourisation efficiencies were 99.30%, 96.63%, and 99.14% for CCD-NPRSM, hybrid ANN-XGBoost, and CART, respectively, compared to the 98.46% RB5 removal rate observed experimentally under optimum conditions: approximately 20 mA/cm2 of current density, 20 min of electrolysis time, and 65 mg/L of RB5. The optimised mineralisation efficiencies ranged between 89% and 92% for different models based on total organic carbon (TOC). Experimental studies confirmed that the predictive efficiency of optimised models ranked in the descending order of hybrid ANN-XGBoost, CCD-NPRSM, and CART. Model validation using analysis of variance (ANOVA) revealed that hybrid ANN-XGBoost had a mean squared error (MSE) and a coefficient of determination (R2) of approximately 0.014 and 0.998, respectively, for the RB5 removal efficiency, outperforming CCD-NPRSM with MSE and R2 of 0.518 and 0.998, respectively. Overall, the hybrid ANN-XGBoost approach is the most feasible technique for assessing the electrochemical treatment efficiency in RB5 dye wastewater decolourisation.
2025, 18(1): 11-20.
doi: 10.1016/j.wse.2024.01.004
Abstract:
Bromocresol green (BCG) and malachite green (MG) are water-soluble toxic organic dyes with adverse health and environmental implications. This study presented a conjugate imprinted adsorbent (CIA) synthesized by incorporating trimethoprim vanillin ligand into a highly crosslinked polymer, designed for the efficient removal of BCG and MG from wastewater. Characterization of CIA involved X-ray powder diffraction, Fourier transform infrared, and scanning electron microscopic analyses. Batch adsorption processes were conducted to evaluate the adsorption characteristics of CIA, with focuses on the effects of contact time, initial dye concentration, pH, and temperature. The molecularly imprinted polymers (MIPs) achieved removal efficiencies of 99.27% and 98.99% at equilibrium for BCG and MG adsorption, respectively. The non-imprinted polymers (NIPs) demonstrated BCG and MG adsorption efficiencies of 51.52% and 62.90% at equilibrium, respectively. Kinetic and isotherm models were employed to elucidate the BCG and MG adsorption mechanisms. The thermodynamic results indicated non-spontaneous and spontaneous reactions for BCG and MG adsorption on MIPs under the examined temperature conditions. The adsorbent exhibited sustained high removal efficiency through five reuse cycles, with no apparent reduction in adsorption performance. Validation of the adsorbent using real textile wastewater samples achieved BCG and MG removal efficiencies of 85.5%-87.5%. The adsorbent outperformed previously reported materials in BCG and MG adsorption. The synthesized CIA is a promising adsorbent for BCG and MG dye removal, contributing to water sustainability.
Bromocresol green (BCG) and malachite green (MG) are water-soluble toxic organic dyes with adverse health and environmental implications. This study presented a conjugate imprinted adsorbent (CIA) synthesized by incorporating trimethoprim vanillin ligand into a highly crosslinked polymer, designed for the efficient removal of BCG and MG from wastewater. Characterization of CIA involved X-ray powder diffraction, Fourier transform infrared, and scanning electron microscopic analyses. Batch adsorption processes were conducted to evaluate the adsorption characteristics of CIA, with focuses on the effects of contact time, initial dye concentration, pH, and temperature. The molecularly imprinted polymers (MIPs) achieved removal efficiencies of 99.27% and 98.99% at equilibrium for BCG and MG adsorption, respectively. The non-imprinted polymers (NIPs) demonstrated BCG and MG adsorption efficiencies of 51.52% and 62.90% at equilibrium, respectively. Kinetic and isotherm models were employed to elucidate the BCG and MG adsorption mechanisms. The thermodynamic results indicated non-spontaneous and spontaneous reactions for BCG and MG adsorption on MIPs under the examined temperature conditions. The adsorbent exhibited sustained high removal efficiency through five reuse cycles, with no apparent reduction in adsorption performance. Validation of the adsorbent using real textile wastewater samples achieved BCG and MG removal efficiencies of 85.5%-87.5%. The adsorbent outperformed previously reported materials in BCG and MG adsorption. The synthesized CIA is a promising adsorbent for BCG and MG dye removal, contributing to water sustainability.
2025, 18(1): 21-29.
doi: 10.1016/j.wse.2024.03.004
Abstract:
Degrading ciprofloxacin (CIP)-polluted water has recently emerged as an urgent environmental issue. This study introduced mechanochemical treatment (MCT) as an innovative and underexplored approach for the degradation of CIP in water. The influence of various additives (CaO, Fe2O3, SiO2, Al, and Fe) on CIP degradation efficiency was investigated. Additionally, six types of composite additives (Fe-CaO, Fe-Fe2O3, Fe-SiO2, Fe-Al, Al-SiO2, and Al-CaO) were explored, with the composite of 20% Fe and 80% SiO2 exhibiting notable performance. The impacts of additive content, pH value, and co-existing ions on CIP degradation efficiency were investigated. Furthermore, the effectiveness of MCT in degrading other medical pollutants (norfloxacin, ofloxacin, and enrofloxacin) was verified. The transformations and changes in the crystal structure, oxidation state, microstructure, and morphology of the Fe-SiO2 composite additive were characterized using X-ray diffraction, X-ray photoelectron spectroscopy, and scanning electron microscopy techniques. This study proposed a sigmoid trend kinetic model (the Delogu model) that better elucidates the MCT process. Three plausible degradation pathways were discussed based on intermediate substance identification and pertinent literature. This study not only establishes a pathway for the facile degradation of CIP pollutants through MCT but also contributes to advancements in wastewater treatment methodologies.
Degrading ciprofloxacin (CIP)-polluted water has recently emerged as an urgent environmental issue. This study introduced mechanochemical treatment (MCT) as an innovative and underexplored approach for the degradation of CIP in water. The influence of various additives (CaO, Fe2O3, SiO2, Al, and Fe) on CIP degradation efficiency was investigated. Additionally, six types of composite additives (Fe-CaO, Fe-Fe2O3, Fe-SiO2, Fe-Al, Al-SiO2, and Al-CaO) were explored, with the composite of 20% Fe and 80% SiO2 exhibiting notable performance. The impacts of additive content, pH value, and co-existing ions on CIP degradation efficiency were investigated. Furthermore, the effectiveness of MCT in degrading other medical pollutants (norfloxacin, ofloxacin, and enrofloxacin) was verified. The transformations and changes in the crystal structure, oxidation state, microstructure, and morphology of the Fe-SiO2 composite additive were characterized using X-ray diffraction, X-ray photoelectron spectroscopy, and scanning electron microscopy techniques. This study proposed a sigmoid trend kinetic model (the Delogu model) that better elucidates the MCT process. Three plausible degradation pathways were discussed based on intermediate substance identification and pertinent literature. This study not only establishes a pathway for the facile degradation of CIP pollutants through MCT but also contributes to advancements in wastewater treatment methodologies.
2025, 18(1): 30-40.
doi: 10.1016/j.wse.2024.04.001
Abstract:
Fluoride (F-) and arsenic, present as As(III) and As(V), are widespread toxins in groundwater across India, as well as in other countries or regions like Pakistan, China, Kenya, Africa, Thailand, and Latin America. Their presence in water resources poses significant environmental and health risks, including fluorosis and arsenicosis. To address this issue, this study developed an integrated process combining biosorbents and ultrafiltration (UF) for the removal of F-, As, and turbidity from contaminated water. Laboratory-scale adsorption experiments were conducted using low-cost biosorbents with different biosorbent dosages, specifically Moringa oleifera seed powder (MSP) and sorghum bicolor husk (SBH), along with sand as a binding medium. F- and As concentrations ranging from 2 to 10 mg/L and 3 to 12 mg/L, respectively, were investigated. Biosorbents and their different combinations were tested to determine their efficacy in removing dissolved F- and As. The results showed that a blend of 10-g/L MSP with SBH achieved the highest F- (97.20%) and As (78.63%) removal efficiencies. Subsequent treatment with a UF membrane effectively reduced turbidity and colloidal impurities in the treated water, achieving a maximum turbidity removal efficiency of 95.40%. Equilibrium kinetic and isotherm models were employed to analyze the experimental data, demonstrating good fit. Preliminary cost analysis indicated that the hybrid technology is economically viable and suitable for the separation of hazardous contaminants from aqueous solutions. This study underscores the potential of inexpensive biosorption technologies in providing clean and safe drinking water, particularly in industrial, rural, and urban areas.
Fluoride (F-) and arsenic, present as As(III) and As(V), are widespread toxins in groundwater across India, as well as in other countries or regions like Pakistan, China, Kenya, Africa, Thailand, and Latin America. Their presence in water resources poses significant environmental and health risks, including fluorosis and arsenicosis. To address this issue, this study developed an integrated process combining biosorbents and ultrafiltration (UF) for the removal of F-, As, and turbidity from contaminated water. Laboratory-scale adsorption experiments were conducted using low-cost biosorbents with different biosorbent dosages, specifically Moringa oleifera seed powder (MSP) and sorghum bicolor husk (SBH), along with sand as a binding medium. F- and As concentrations ranging from 2 to 10 mg/L and 3 to 12 mg/L, respectively, were investigated. Biosorbents and their different combinations were tested to determine their efficacy in removing dissolved F- and As. The results showed that a blend of 10-g/L MSP with SBH achieved the highest F- (97.20%) and As (78.63%) removal efficiencies. Subsequent treatment with a UF membrane effectively reduced turbidity and colloidal impurities in the treated water, achieving a maximum turbidity removal efficiency of 95.40%. Equilibrium kinetic and isotherm models were employed to analyze the experimental data, demonstrating good fit. Preliminary cost analysis indicated that the hybrid technology is economically viable and suitable for the separation of hazardous contaminants from aqueous solutions. This study underscores the potential of inexpensive biosorption technologies in providing clean and safe drinking water, particularly in industrial, rural, and urban areas.
2025, 18(1): 41-50.
doi: 10.1016/j.wse.2024.05.002
Abstract:
Cresyl diphenyl phosphate (CDP), an emerging aryl organophosphate ester (OPE), exhibits potential toxic effects and is frequently found in diverse environmental media, thereby raising concerns about environmental pollution. Biodegradation demonstrates substantial potential for CDP removal from the environment. This study investigated the biodegradation mechanisms of CDP using anaerobic activated sludge (AnAS). The biodegradation of 1-mg/L CDP followed a first-order kinetic model with a degradation kinetic constant of 0.943 d-1, and the addition of different electron acceptors affected the degradation rate. High-resolution mass spectrometry identified seven transformation products (TPs) of CDP. The pathways of CDP degradation in anaerobic conditions were proposed, with carboxylation products being the most dominant intermediate products. The structure of the anaerobic microbial community at different degradation time points in CDP-amended microcosms was examined. The linear discriminant analysis (LDA) of effect size (LEfSe) potentially underscored the pivotal role of Methyloversatilis in CDP biodegradation. Zebrafish embryotoxicity experiments revealed both lethal and morphogenetic impacts of CDP on zebrafish embryos. The survival rate, hatching rate, and body length indicators of zebrafish embryos underscored the detoxification of CDP and its resultant intermediates by AnAS. This study offers new insights into the fate and biodegradation mechanisms of CDP in wastewater treatment plants.
Cresyl diphenyl phosphate (CDP), an emerging aryl organophosphate ester (OPE), exhibits potential toxic effects and is frequently found in diverse environmental media, thereby raising concerns about environmental pollution. Biodegradation demonstrates substantial potential for CDP removal from the environment. This study investigated the biodegradation mechanisms of CDP using anaerobic activated sludge (AnAS). The biodegradation of 1-mg/L CDP followed a first-order kinetic model with a degradation kinetic constant of 0.943 d-1, and the addition of different electron acceptors affected the degradation rate. High-resolution mass spectrometry identified seven transformation products (TPs) of CDP. The pathways of CDP degradation in anaerobic conditions were proposed, with carboxylation products being the most dominant intermediate products. The structure of the anaerobic microbial community at different degradation time points in CDP-amended microcosms was examined. The linear discriminant analysis (LDA) of effect size (LEfSe) potentially underscored the pivotal role of Methyloversatilis in CDP biodegradation. Zebrafish embryotoxicity experiments revealed both lethal and morphogenetic impacts of CDP on zebrafish embryos. The survival rate, hatching rate, and body length indicators of zebrafish embryos underscored the detoxification of CDP and its resultant intermediates by AnAS. This study offers new insights into the fate and biodegradation mechanisms of CDP in wastewater treatment plants.
2019, 12(4): 274-283.
doi: 10.1016/j.wse.2019.12.004
摘要：
Increased urbanisation, economic growth, and long-term climate variability have made both the UK and China more susceptible to urban and river flooding, putting people and property at increased risk. This paper presents a review of the current flooding challenges that are affecting the UK and China and the actions that each country is undertaking to tackle these problems. Particular emphases in this paper are laid on (1) learning from previous flooding events in the UK and China, and (2) which management methodologies are commonly used to reduce flood risk. The paper concludes with a strategic research plan suggested by the authors, together with proposed ways to overcome identified knowledge gaps in flood management. Recommendations briefly comprise the engagement of all stakeholders to ensure a proactive approach to land use planning, early warning systems, and water-sensitive urban design or redesign through more effective policy, multi-level flood models, and data driven models of water quantity and quality.
Increased urbanisation, economic growth, and long-term climate variability have made both the UK and China more susceptible to urban and river flooding, putting people and property at increased risk. This paper presents a review of the current flooding challenges that are affecting the UK and China and the actions that each country is undertaking to tackle these problems. Particular emphases in this paper are laid on (1) learning from previous flooding events in the UK and China, and (2) which management methodologies are commonly used to reduce flood risk. The paper concludes with a strategic research plan suggested by the authors, together with proposed ways to overcome identified knowledge gaps in flood management. Recommendations briefly comprise the engagement of all stakeholders to ensure a proactive approach to land use planning, early warning systems, and water-sensitive urban design or redesign through more effective policy, multi-level flood models, and data driven models of water quantity and quality.
2020, 13(3): 202-213.
doi: 10.1016/j.wse.2020.09.007
摘要：
In this experiment, cobalt ferrite-supported activated carbon (CF-AC) was developed and characterized via the wet impregnation method for the removal of Cr and Pb(II) ions from tannery wastewater. Batch adsorption was carried out to evaluate the effect of experimental operating conditions (pH of solution, contact time, adsorbent dose, and temperature), and the removal efficiencies of Cr and Pb(II) ions by the developed adsorbents were calculated and recorded for all experimental conditions. These variables were estimated and reported as removal efficiencies of 98.2% for Cr and 96.4% for Pb(II) ions at the optimal conditions of 5, 0.8 g, 80 min, and 333 K for pH, adsorbent dose, contact time, and temperature, respectively. The equilibrium for the sorption of Cr and Pb(II) ions was studied using four widely used isotherm models (the Langmuir, Freundlich, Dubinin-Radushkevich, and Temkin isotherm models). It was found that the Freundlich isotherm model fit better with the coefficient of determination (R2) of 0.948 4 and a small sum of square error of 0.000 6. The maximum adsorption capacities (Qm) of Pb(II) and Cr adsorbed onto CF-AC were determined to be 6.27 and 23.6 mg/g, respectively. The adsorption process conformed well to pseudo-second order kinetics as revealed by the high R2 values obtained for both metals. The thermodynamic parameters showed that adsorption of Cr and Pb(II) ions onto CF-AC was spontaneous, feasible, and endothermic under the studied conditions. The mean adsorption energy (E) values revealed that the adsorption mechanism of Cr and Pb(II) by CF-AC is physical in nature. The results of the study showed that adsorbent developed from CF-AC can be efficiently used as an environmentally friendly alternative adsorbent, for removal of Cr and Pb(II) ions in tannery wastewater.
In this experiment, cobalt ferrite-supported activated carbon (CF-AC) was developed and characterized via the wet impregnation method for the removal of Cr and Pb(II) ions from tannery wastewater. Batch adsorption was carried out to evaluate the effect of experimental operating conditions (pH of solution, contact time, adsorbent dose, and temperature), and the removal efficiencies of Cr and Pb(II) ions by the developed adsorbents were calculated and recorded for all experimental conditions. These variables were estimated and reported as removal efficiencies of 98.2% for Cr and 96.4% for Pb(II) ions at the optimal conditions of 5, 0.8 g, 80 min, and 333 K for pH, adsorbent dose, contact time, and temperature, respectively. The equilibrium for the sorption of Cr and Pb(II) ions was studied using four widely used isotherm models (the Langmuir, Freundlich, Dubinin-Radushkevich, and Temkin isotherm models). It was found that the Freundlich isotherm model fit better with the coefficient of determination (R2) of 0.948 4 and a small sum of square error of 0.000 6. The maximum adsorption capacities (Qm) of Pb(II) and Cr adsorbed onto CF-AC were determined to be 6.27 and 23.6 mg/g, respectively. The adsorption process conformed well to pseudo-second order kinetics as revealed by the high R2 values obtained for both metals. The thermodynamic parameters showed that adsorption of Cr and Pb(II) ions onto CF-AC was spontaneous, feasible, and endothermic under the studied conditions. The mean adsorption energy (E) values revealed that the adsorption mechanism of Cr and Pb(II) by CF-AC is physical in nature. The results of the study showed that adsorbent developed from CF-AC can be efficiently used as an environmentally friendly alternative adsorbent, for removal of Cr and Pb(II) ions in tannery wastewater.
2021, 14(2): 139-148.
doi: 10.1016/j.wse.2021.06.006
摘要：
To assess the magnitude of water quality decline in the Turag River of Bangladesh, this study examined the seasonal variation of physicochemical parameters of water, identified potential pollution sources, and clustered the monitoring months with similar characteristics. Water samples were collected in four distinct seasons to evaluate temperature, pH, dissolved oxygen (DO) concentration, five-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), electrical conductivity (EC), chloride ion (Cl−) concentration, total alkalinity (TA), turbidity, total dissolved solids (TDS) concentration, total suspended solids (TSS) concentration, and total hardness (TH) using standard methods. The analytical results revealed that 40% of water quality indices were within the permissible limits suggested by different agencies, with the exception of EC, Cl− concentration, TA, turbidity, DO concentration, BOD5, and COD in all seasons. Statistical analyses indicated that 52% of the contrasts were significantly different at a 95% confidence interval. The factor analysis presented the best fit among the parameters, with four factors explaining 94.29% of the total variance. TDS, BOD5, COD, EC, turbidity, DO, and Cl− were mainly responsible for pollution loading and were caused by the significant amount of industrial discharge and toxicological compounds. The cluster analysis showed the seasonal change in surface water quality, which is usually an indicator of pollution from rainfall or other sources. However, the values of different physicochemical properties varied with seasons, and the highest values of pollutants were recorded in the winter. With the change in seasonal temperature and increase in rainfall, the seasonal Turag River water followed a self-refining trend as follows: rainy season > pre-winter > summer > winter.
To assess the magnitude of water quality decline in the Turag River of Bangladesh, this study examined the seasonal variation of physicochemical parameters of water, identified potential pollution sources, and clustered the monitoring months with similar characteristics. Water samples were collected in four distinct seasons to evaluate temperature, pH, dissolved oxygen (DO) concentration, five-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), electrical conductivity (EC), chloride ion (Cl−) concentration, total alkalinity (TA), turbidity, total dissolved solids (TDS) concentration, total suspended solids (TSS) concentration, and total hardness (TH) using standard methods. The analytical results revealed that 40% of water quality indices were within the permissible limits suggested by different agencies, with the exception of EC, Cl− concentration, TA, turbidity, DO concentration, BOD5, and COD in all seasons. Statistical analyses indicated that 52% of the contrasts were significantly different at a 95% confidence interval. The factor analysis presented the best fit among the parameters, with four factors explaining 94.29% of the total variance. TDS, BOD5, COD, EC, turbidity, DO, and Cl− were mainly responsible for pollution loading and were caused by the significant amount of industrial discharge and toxicological compounds. The cluster analysis showed the seasonal change in surface water quality, which is usually an indicator of pollution from rainfall or other sources. However, the values of different physicochemical properties varied with seasons, and the highest values of pollutants were recorded in the winter. With the change in seasonal temperature and increase in rainfall, the seasonal Turag River water followed a self-refining trend as follows: rainy season > pre-winter > summer > winter.
2016, 9(1): 58-66.
doi: 10.1016/j.wse.2016.02.002
摘要：
This paper presents a study on the improvement of wind field hindcasts for two typical tropical cyclones, i.e., Fanapi and Meranti, which occurred in 2010. The performance of the three existing models for the hindcasting of cyclone wind fields is first examined, and then two modification methods are proposed to improve the hindcasted results. The first one is the superposition method, which superposes the wind field calculated from the parametric cyclone model on that obtained from the Cross-Calibrated Multi-Platform (CCMP) reanalysis data. The radius used for the superposition is based on an analysis of the minimum difference between the two wind fields. The other one is the direct modification method, which directly modifies the CCMP reanalysis data according to the ratio of the measured maximum wind speed to the reanalyzed value as well as the distance from the cyclone center. Using these two methods, the problem of underestimation of strong winds in reanalysis data can be overcome. Both methods show considerable improvements in the hindcasting of tropical cyclone wind fields, compared with the cyclone wind model and the reanalysis data.
This paper presents a study on the improvement of wind field hindcasts for two typical tropical cyclones, i.e., Fanapi and Meranti, which occurred in 2010. The performance of the three existing models for the hindcasting of cyclone wind fields is first examined, and then two modification methods are proposed to improve the hindcasted results. The first one is the superposition method, which superposes the wind field calculated from the parametric cyclone model on that obtained from the Cross-Calibrated Multi-Platform (CCMP) reanalysis data. The radius used for the superposition is based on an analysis of the minimum difference between the two wind fields. The other one is the direct modification method, which directly modifies the CCMP reanalysis data according to the ratio of the measured maximum wind speed to the reanalyzed value as well as the distance from the cyclone center. Using these two methods, the problem of underestimation of strong winds in reanalysis data can be overcome. Both methods show considerable improvements in the hindcasting of tropical cyclone wind fields, compared with the cyclone wind model and the reanalysis data.
2019, 12(1): 11-18.
doi: 10.1016/j.wse.2019.03.001
摘要：
Hydraulic models for the generation of ?ood inundation maps are not commonly applied in mountain river basins because of the dif?culty in modeling the hydraulic behavior and the complex topography. This paper presents a comparative analysis of the performance of four twodimensional hydraulic models (HEC-RAS 2D, Iber 2D, Flood Modeller 2D, and PCSWMM 2D) with respect to the generation of ?ood inundation maps. The study area covers a 5-km reach of the Santa Barbara River located in the Ecuadorian Andes, at 2330 masl, in Gualaceo. The model's performance was evaluated based on the water surface elevation and ?ood extent, in terms of the mean absolute difference and measure of ?t. The analysis revealed that, for a given case, Iber 2D has the best performance in simulating the water level and inundation for ?ood events with 20- and 50-year return periods, respectively, followed by Flood Modeller 2D, HEC-RAS 2D, and PCSWMM 2D in terms of their performance. Grid resolution, the way in which hydraulic structures are mimicked, the model code, and the default value of the parameters are considered the main sources of prediction uncertainty.
Hydraulic models for the generation of ?ood inundation maps are not commonly applied in mountain river basins because of the dif?culty in modeling the hydraulic behavior and the complex topography. This paper presents a comparative analysis of the performance of four twodimensional hydraulic models (HEC-RAS 2D, Iber 2D, Flood Modeller 2D, and PCSWMM 2D) with respect to the generation of ?ood inundation maps. The study area covers a 5-km reach of the Santa Barbara River located in the Ecuadorian Andes, at 2330 masl, in Gualaceo. The model's performance was evaluated based on the water surface elevation and ?ood extent, in terms of the mean absolute difference and measure of ?t. The analysis revealed that, for a given case, Iber 2D has the best performance in simulating the water level and inundation for ?ood events with 20- and 50-year return periods, respectively, followed by Flood Modeller 2D, HEC-RAS 2D, and PCSWMM 2D in terms of their performance. Grid resolution, the way in which hydraulic structures are mimicked, the model code, and the default value of the parameters are considered the main sources of prediction uncertainty.
2019, 12(1): 27-36.
doi: 10.1016/j.wse.2019.04.003
摘要：
This study aimed to investigate the biosorption potential of Na2CO3-modified Aloe barbadensis Miller (Aloe vera) leaf (MABL) powder for removal of Ni(II) ions from a synthetic aqueous solution. Effects of various process parameters (pH, equilibrium time, and temperature) were investigated in order to optimize the biosorptive removal. The maximum biosorption capacity of MABL was observed to be 28.986 mg/g at a temperature of 303 K, a biosorbent dose of 0.6 g, a contact time of 90 min, and a pH value of 7. Different kinetic models (the pseudo-first-order, pseudo-second-order, Elovich, and intraparticle diffusion models) were evaluated. The pseudo-second-order kinetic model was found to be the best fitted model in this study, with a coefficient of determination of R2 = 0.974. Five different isotherm models (the Langmuir, Freundlich, Temkin, Dubinin-Radushkevich, and Brunauer-Emmett-Teller (BET) models) were investigated to identify the best-suited isotherm model for the present system. Based on the minimum chi-square value (χ2 = 0.027) and the maximum coefficient of determination (R2 = 0.996), the Langmuir isotherm model was found to represent the system well, indicating the possibility of monolayer biosorption. The sticking probability (S*) was found to be 0.41, suggesting a physisorption mechanism for biosorption of Ni(II) on MABL. The biosorbent was characterized using Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), zeta potential, and BET surface area, in order to understand its morphological and functional characteristics.
This study aimed to investigate the biosorption potential of Na2CO3-modified Aloe barbadensis Miller (Aloe vera) leaf (MABL) powder for removal of Ni(II) ions from a synthetic aqueous solution. Effects of various process parameters (pH, equilibrium time, and temperature) were investigated in order to optimize the biosorptive removal. The maximum biosorption capacity of MABL was observed to be 28.986 mg/g at a temperature of 303 K, a biosorbent dose of 0.6 g, a contact time of 90 min, and a pH value of 7. Different kinetic models (the pseudo-first-order, pseudo-second-order, Elovich, and intraparticle diffusion models) were evaluated. The pseudo-second-order kinetic model was found to be the best fitted model in this study, with a coefficient of determination of R2 = 0.974. Five different isotherm models (the Langmuir, Freundlich, Temkin, Dubinin-Radushkevich, and Brunauer-Emmett-Teller (BET) models) were investigated to identify the best-suited isotherm model for the present system. Based on the minimum chi-square value (χ2 = 0.027) and the maximum coefficient of determination (R2 = 0.996), the Langmuir isotherm model was found to represent the system well, indicating the possibility of monolayer biosorption. The sticking probability (S*) was found to be 0.41, suggesting a physisorption mechanism for biosorption of Ni(II) on MABL. The biosorbent was characterized using Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), zeta potential, and BET surface area, in order to understand its morphological and functional characteristics.
2016, 9(1): 33-41.
doi: 10.1016/j.wse.2016.02.003
摘要：
The southern coast of the Gulf of Maine in the United States is prone to flooding caused by nor’easters. A state-of-the-art fully-coupled model, the Simulating WAves Nearshore (SWAN) model with unstructured grids and the ADvanced CIRCulation (ADCIRC) model, was used to study the hydrodynamic response in the Gulf of Maine during the Patriot’s Day storm of 2007, a notable example of nor’easters in this area. The model predictions agree well with the observed tide-surges and waves during this storm event. Waves and circulation in the Gulf of Maine were analyzed. The Georges Bank plays an important role in dissipating wave energy through the bottom friction when waves propagate over the bank from offshore to the inner gulf due to its shallow bathymetry. Wave energy dissipation results in decreasing significant wave height (SWH) in the cross-bank direction and wave radiation stress gradient, which in turn induces changes in currents. While the tidal currents are dominant over the Georges Bank and in the Bay of Fundy, the residual currents generated by the meteorological forcing and waves are significant over the Georges Bank and in the coastal area and can reach 0.3 m/s and 0.2 m/s, respectively. In the vicinity of the coast, the longshore current generated by the surface wind stress and wave radiation stress acting parallel to the coastline is inversely proportional to the water depth and will eventually be limited by the bottom friction. The storm surge level reaches 0.8 m along the western periphery of the Gulf of Maine while the wave set-up due to radiation stress variation reaches 0.2 m. Therefore, it is significant to coastal flooding.
The southern coast of the Gulf of Maine in the United States is prone to flooding caused by nor’easters. A state-of-the-art fully-coupled model, the Simulating WAves Nearshore (SWAN) model with unstructured grids and the ADvanced CIRCulation (ADCIRC) model, was used to study the hydrodynamic response in the Gulf of Maine during the Patriot’s Day storm of 2007, a notable example of nor’easters in this area. The model predictions agree well with the observed tide-surges and waves during this storm event. Waves and circulation in the Gulf of Maine were analyzed. The Georges Bank plays an important role in dissipating wave energy through the bottom friction when waves propagate over the bank from offshore to the inner gulf due to its shallow bathymetry. Wave energy dissipation results in decreasing significant wave height (SWH) in the cross-bank direction and wave radiation stress gradient, which in turn induces changes in currents. While the tidal currents are dominant over the Georges Bank and in the Bay of Fundy, the residual currents generated by the meteorological forcing and waves are significant over the Georges Bank and in the coastal area and can reach 0.3 m/s and 0.2 m/s, respectively. In the vicinity of the coast, the longshore current generated by the surface wind stress and wave radiation stress acting parallel to the coastline is inversely proportional to the water depth and will eventually be limited by the bottom friction. The storm surge level reaches 0.8 m along the western periphery of the Gulf of Maine while the wave set-up due to radiation stress variation reaches 0.2 m. Therefore, it is significant to coastal flooding.
2019, 12(1): 45-54.
doi: 10.1016/j.wse.2018.11.001
摘要：
Water quality is always one of the most important factors in human health. Artificial intelligence models are respected methods for modeling
water quality. The evolutionary algorithm (EA) is a new technique for improving the performance of artificial intelligence models such as the
adaptive neuro fuzzy inference system (ANFIS) and artificial neural networks (ANN). Attempts have been made to make the models more
suitable and accurate with the replacement of other training methods that do not suffer from some shortcomings, including a tendency to being
trapped in local optima or voluminous computations. This study investigated the applicability of ANFIS with particle swarm optimization (PSO)
and ant colony optimization for continuous domains (ACOR) in estimating water quality parameters at three stations along the Zayandehrood
River, in Iran. The ANFIS-PSO and ANFIS-ACOR methods were also compared with the classic ANFIS method, which uses least squares and
gradient descent as training algorithms. The estimated water quality parameters in this study were electrical conductivity (EC), total dissolved
solids (TDS), the sodium adsorption ratio (SAR), carbonate hardness (CH), and total hardness (TH). Correlation analysis was performed using
SPSS software to determine the optimal inputs to the models. The analysis showed that ANFIS-PSO was the better model compared with
ANFIS-ACOR. It is noteworthy that EA models can improve ANFIS' performance at all three stations for different water quality parameters.
Water quality is always one of the most important factors in human health. Artificial intelligence models are respected methods for modeling
water quality. The evolutionary algorithm (EA) is a new technique for improving the performance of artificial intelligence models such as the
adaptive neuro fuzzy inference system (ANFIS) and artificial neural networks (ANN). Attempts have been made to make the models more
suitable and accurate with the replacement of other training methods that do not suffer from some shortcomings, including a tendency to being
trapped in local optima or voluminous computations. This study investigated the applicability of ANFIS with particle swarm optimization (PSO)
and ant colony optimization for continuous domains (ACOR) in estimating water quality parameters at three stations along the Zayandehrood
River, in Iran. The ANFIS-PSO and ANFIS-ACOR methods were also compared with the classic ANFIS method, which uses least squares and
gradient descent as training algorithms. The estimated water quality parameters in this study were electrical conductivity (EC), total dissolved
solids (TDS), the sodium adsorption ratio (SAR), carbonate hardness (CH), and total hardness (TH). Correlation analysis was performed using
SPSS software to determine the optimal inputs to the models. The analysis showed that ANFIS-PSO was the better model compared with
ANFIS-ACOR. It is noteworthy that EA models can improve ANFIS' performance at all three stations for different water quality parameters.
2020, 13(2): 136-144.
doi: 10.1016/j.wse.2020.06.005
摘要：
Based on conventional particle swarm optimization (PSO), this paper presents an efficient and reliable heuristic approach using PSO with an adaptive random inertia weight (ARIW) strategy, referred to as the ARIW-PSO algorithm, to build a multi-objective optimization model for reservoir operation. Using the triangular probability density function, the inertia weight is randomly generated, and the probability density function is automatically adjusted to make the inertia weight generally greater in the initial stage of evolution, which is suitable for global searches. In the evolution process, the inertia weight gradually decreases, which is beneficial to local searches. The performance of the ARIW-PSO algorithm was investigated with some classical test functions, and the results were compared with those of the genetic algorithm (GA), the conventional PSO, and other improved PSO methods. Then, the ARIW-PSO algorithm was applied to multi-objective optimal dispatch of the Panjiakou Reservoir and multi-objective flood control operation of a reservoir group on the Luanhe River in China, including the Panjiakou Reservoir, Daheiting Reservoir, and Taolinkou Reservoir. The validity of the multi-objective optimization model for multi-reservoir systems based on the ARIW-PSO algorithm was verified.
Based on conventional particle swarm optimization (PSO), this paper presents an efficient and reliable heuristic approach using PSO with an adaptive random inertia weight (ARIW) strategy, referred to as the ARIW-PSO algorithm, to build a multi-objective optimization model for reservoir operation. Using the triangular probability density function, the inertia weight is randomly generated, and the probability density function is automatically adjusted to make the inertia weight generally greater in the initial stage of evolution, which is suitable for global searches. In the evolution process, the inertia weight gradually decreases, which is beneficial to local searches. The performance of the ARIW-PSO algorithm was investigated with some classical test functions, and the results were compared with those of the genetic algorithm (GA), the conventional PSO, and other improved PSO methods. Then, the ARIW-PSO algorithm was applied to multi-objective optimal dispatch of the Panjiakou Reservoir and multi-objective flood control operation of a reservoir group on the Luanhe River in China, including the Panjiakou Reservoir, Daheiting Reservoir, and Taolinkou Reservoir. The validity of the multi-objective optimization model for multi-reservoir systems based on the ARIW-PSO algorithm was verified.
2016, 9(2): 87-96.
doi: 10.1016/j.wse.2016.06.002
摘要：
The main objective of this study was to evaluate four latest global high-resolution satellite precipitation products (TMPA 3B42RT, CMORPH, TMPA 3B42V7, and CMORPH_adj) against gauge observations of the Yellow River Basin from March 2000 to December 2012. The assessment was conducted with several commonly used statistical indices at daily and monthly scales. Results indicate that 3B42V7 and CMORPH_adj perform better than the near real-time products (3B42RT and CMORPH), particularly the 3B42V7 product. The adjustment by gauge data significantly reduces the systematic biases in the research products. Regarding the near real-time datasets, 3B42RT overestimates rainfall over the whole basin, while CMORPH presents a mixed pattern with negative and positive values of relative bias in low- and high-latitude regions, respectively, and CMORPH performs better than 3B42RT on the whole. According to the spatial distribution of statistical indices, these values are optimized in the southeast and decrease toward the northwest, and the trend is similar for the spatial distribution of the mean annual precipitation during the period from 2000 to 2012. This study also reveals that all the four products can effectively detect rainfall events. This study provides useful information about four mainstream satellite products in the Yellow River Basin, and the findings can facilitate the use of global precipitation measurement (GPM) data in the future.
The main objective of this study was to evaluate four latest global high-resolution satellite precipitation products (TMPA 3B42RT, CMORPH, TMPA 3B42V7, and CMORPH_adj) against gauge observations of the Yellow River Basin from March 2000 to December 2012. The assessment was conducted with several commonly used statistical indices at daily and monthly scales. Results indicate that 3B42V7 and CMORPH_adj perform better than the near real-time products (3B42RT and CMORPH), particularly the 3B42V7 product. The adjustment by gauge data significantly reduces the systematic biases in the research products. Regarding the near real-time datasets, 3B42RT overestimates rainfall over the whole basin, while CMORPH presents a mixed pattern with negative and positive values of relative bias in low- and high-latitude regions, respectively, and CMORPH performs better than 3B42RT on the whole. According to the spatial distribution of statistical indices, these values are optimized in the southeast and decrease toward the northwest, and the trend is similar for the spatial distribution of the mean annual precipitation during the period from 2000 to 2012. This study also reveals that all the four products can effectively detect rainfall events. This study provides useful information about four mainstream satellite products in the Yellow River Basin, and the findings can facilitate the use of global precipitation measurement (GPM) data in the future.
2008, 1(1): 37-43 .
doi: 10.3882/j.issn.1674-2370.2008.01.005
Abstract:
2011, 4(1): 101-109.
doi: 10.3882/j.issn.1674-2370.2011.01.010
Abstract:
2011, 4(3): 258-269.
doi: 10.3882/j.issn.1674-2370.2011.03.003
Abstract:
2012, 5(3): 243-258.
doi: 10.3882/j.issn.1674-2370.2012.03.001
Abstract:
2010, 3(3): 321-330.
doi: 10.3882/j.issn.1674-2370.2010.03.008
Abstract:
2012, 5(1): 26-33.
doi: 10.3882/j.issn.1674-2370.2012.01.003
Abstract:
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2008, 1(1): 37-43 .
doi: 10.3882/j.issn.1674-2370.2008.01.005
2
2011, 4(1): 101-109.
doi: 10.3882/j.issn.1674-2370.2011.01.010
3
2011, 4(3): 258-269.
doi: 10.3882/j.issn.1674-2370.2011.03.003
4
2012, 5(3): 243-258.
doi: 10.3882/j.issn.1674-2370.2012.03.001
5
2010, 3(3): 321-330.
doi: 10.3882/j.issn.1674-2370.2010.03.008
6
2012, 5(1): 26-33.
doi: 10.3882/j.issn.1674-2370.2012.01.003
1
2010, 3(2): 132-143.
doi: 10.3882/j.issn.1674-2370.2010.02.002
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2010, 3(3): 241-256.
doi: 10.3882/j.issn.1674-2370.2010.03.001
3
2011, 4(1): 101-109.
doi: 10.3882/j.issn.1674-2370.2011.01.010
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2010, 3(4): 418-430.
doi: 10.3882/j.issn.1674-2370.2010.04.005
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2010, 3(1): 1-13.
doi: 10.3882/j.issn.1674-2370.2010.01.001
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2012, 5(1): 105-119.
doi: 10.3882/j.issn.1674-2370.2012.01.010
Volume 18，Issue 1，
Mar. 2025
Editor-in-ChiefChao Wang
Edited byEditorial Board of Water Science and Engineering
Distributed byEditorial Office of Water Science and Engineering
News
- WSE Special Issue on Security and Sustainability for Hydraulic Structures November 01，2021
- WSE Special Issue on Water Security and Sustainability April 14，2021
- WSE Special Issue for CORE2021 March 09，2021
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