Articles in press are presented at https://www.sciencedirect.com/journal/water-science-and-engineering/articles-in-press
Abstract:
2025, 18(3): 262-273.
doi: 10.1016/j.wse.2025.04.006
Abstract:
As urban areas expand and water demand intensifies, the need for efficient and reliable water distribution systems becomes increasingly critical. A widely used infrastructure management approach involves partitioning water distribution networks (WDNs) into district metered areas (DMAs). However, suboptimal designs of DMA partitioning can lead to inefficiencies and increased costs. This study presents a core-periphery-informed approach for DMA design that explicitly utilises the natural division between a densely connected core and a sparsely connected periphery. Incorporating this structural framework enhances network resilience, improves water pressure stability, and optimises boundary device placement. The proposed core-periphery-informed DMA design integrates hydraulic and topological analyses to identify central and peripheral network areas, applies a community structure detection algorithm conditioned by these areas, and uses an optimisation model to determine the optimal placement of boundary devices, enhancing network resilience and reducing costs. When applied to the Modena WDN in Italy, this approach demonstrates improved pressure stability and significant cost reductions compared to traditional methods. Overall, the findings highlight the practical benefits of the core-periphery-based DMA design, offering a scalable and data-driven solution for urban water distribution systems.
As urban areas expand and water demand intensifies, the need for efficient and reliable water distribution systems becomes increasingly critical. A widely used infrastructure management approach involves partitioning water distribution networks (WDNs) into district metered areas (DMAs). However, suboptimal designs of DMA partitioning can lead to inefficiencies and increased costs. This study presents a core-periphery-informed approach for DMA design that explicitly utilises the natural division between a densely connected core and a sparsely connected periphery. Incorporating this structural framework enhances network resilience, improves water pressure stability, and optimises boundary device placement. The proposed core-periphery-informed DMA design integrates hydraulic and topological analyses to identify central and peripheral network areas, applies a community structure detection algorithm conditioned by these areas, and uses an optimisation model to determine the optimal placement of boundary devices, enhancing network resilience and reducing costs. When applied to the Modena WDN in Italy, this approach demonstrates improved pressure stability and significant cost reductions compared to traditional methods. Overall, the findings highlight the practical benefits of the core-periphery-based DMA design, offering a scalable and data-driven solution for urban water distribution systems.
2025, 18(3): 274-287.
doi: 10.1016/j.wse.2025.04.007
Abstract:
Understanding the evolution and lag effects of droughts is critical to effective drought warning and water resources management. However, due to limited hydrological data, few studies have examined hydrological droughts and their lag time from meteorological droughts at a daily scale. In this study, precipitation data were collected to calculate the standardized precipitation index (SPI), and runoff data simulated by the variable infiltration capacity (VIC) model were utilized to compute the standardized runoff index (SRI). The three-threshold run theory was used to identify drought characteristics in China. These drought characteristics were utilized to investigate spatiotemporal variations, seasonal trends, and temporal changes in areas affected by meteorological and hydrological droughts. Additionally, the interconnections and lag effects between meteorological and hydrological droughts were explored. The results indicated that (1) drought occurred during approximately 28% of the past 34 years in China; (2) drought conditions tended to worsen in autumn and weaken in winter; (3) drought-affected areas shifted from northwest to northeast and finally to southern China; and (4) the correlation between meteorological and hydrological droughts was lower in the northwest and higher in the southeast, with all correlation coefficients exceeding 0.7. The lag times between meteorological and hydrological droughts were longest (5 d) in the Yangtze River, Yellow River, and Hai River basins, and shortest (0 d) in the Tarim River Basin. This study provides a scientific basis for effective early warning of droughts.
Understanding the evolution and lag effects of droughts is critical to effective drought warning and water resources management. However, due to limited hydrological data, few studies have examined hydrological droughts and their lag time from meteorological droughts at a daily scale. In this study, precipitation data were collected to calculate the standardized precipitation index (SPI), and runoff data simulated by the variable infiltration capacity (VIC) model were utilized to compute the standardized runoff index (SRI). The three-threshold run theory was used to identify drought characteristics in China. These drought characteristics were utilized to investigate spatiotemporal variations, seasonal trends, and temporal changes in areas affected by meteorological and hydrological droughts. Additionally, the interconnections and lag effects between meteorological and hydrological droughts were explored. The results indicated that (1) drought occurred during approximately 28% of the past 34 years in China; (2) drought conditions tended to worsen in autumn and weaken in winter; (3) drought-affected areas shifted from northwest to northeast and finally to southern China; and (4) the correlation between meteorological and hydrological droughts was lower in the northwest and higher in the southeast, with all correlation coefficients exceeding 0.7. The lag times between meteorological and hydrological droughts were longest (5 d) in the Yangtze River, Yellow River, and Hai River basins, and shortest (0 d) in the Tarim River Basin. This study provides a scientific basis for effective early warning of droughts.
2025, 18(3): 288-300.
doi: 10.1016/j.wse.2025.07.003
Abstract:
Addressing the growing challenge of water contamination, this study comparatively evaluated a persulfate (PDS) system activated by non-radical nitrogen-doped carbon nanotubes (N-CNTs) versus a PDS system activated by radical-based iron (Fe2+), both used for the degradation of bisphenol A (BPA). The N-CNTs/PDS system, driven by the electron transfer mechanism, achieved remarkable 90.9% BPA removal within 30 min at high BPA concentrations, significantly outperforming the Fe2+/PDS system, which attained only 38.9% removal. The N-CNTs/PDS system maintained robust degradation efficiency across a wide range of BPA concentrations and exhibited a high degree of resilience in diverse water matrices. By directly abstracting electrons from BPA molecules, the N-CNTs/PDS system effectively minimised oxidant wastage and mitigated the risk of secondary pollution, ensuring efficient utilisation of active sites on N-CNTs and sustaining a high catalytic rate. The formation of the N-CNTs-PDS* complex significantly enhanced BPA degradation and mineralisation, thereby optimising PDS consumption. These findings highlight the unparalleled advantages of the N-CNTs/PDS system in managing complex wastewater, offering a promising and innovative solution for treating complex industrial wastewater and advancing environmental remediation efforts.
Addressing the growing challenge of water contamination, this study comparatively evaluated a persulfate (PDS) system activated by non-radical nitrogen-doped carbon nanotubes (N-CNTs) versus a PDS system activated by radical-based iron (Fe2+), both used for the degradation of bisphenol A (BPA). The N-CNTs/PDS system, driven by the electron transfer mechanism, achieved remarkable 90.9% BPA removal within 30 min at high BPA concentrations, significantly outperforming the Fe2+/PDS system, which attained only 38.9% removal. The N-CNTs/PDS system maintained robust degradation efficiency across a wide range of BPA concentrations and exhibited a high degree of resilience in diverse water matrices. By directly abstracting electrons from BPA molecules, the N-CNTs/PDS system effectively minimised oxidant wastage and mitigated the risk of secondary pollution, ensuring efficient utilisation of active sites on N-CNTs and sustaining a high catalytic rate. The formation of the N-CNTs-PDS* complex significantly enhanced BPA degradation and mineralisation, thereby optimising PDS consumption. These findings highlight the unparalleled advantages of the N-CNTs/PDS system in managing complex wastewater, offering a promising and innovative solution for treating complex industrial wastewater and advancing environmental remediation efforts.
2025, 18(3): 301-311.
doi: 10.1016/j.wse.2025.06.001
Abstract:
Bromate (BrO3-) is a toxic disinfection byproduct frequently formed during ozonation in water treatment processes and is classified as a potential human carcinogen. Its effective removal from drinking water is therefore a pressing concern for public health and environmental safety. This study investigated the removal of BrO3-from water using the synthesized zeolite imidazolate framework (ZIF)-67 and ZIF-67/graphene oxide (GO) nanocomposites through a comparative approach. The morphology, composition, and crystallinity of both ZIFs were characterized. The effects of four independent parameters (initial BrO3-concentration, pH, adsorbent dose, and contact time) on BrO-3 removal efficiency were examined. A strong correlation was observed between experimental and predicted values. GO enhanced BrO-3 removal not only through synergistic interactions with ZIF-67 but also by improving dispersion and providing additional functional groups that facilitate electrostatic interactions and adsorption. The Box—Behnken design was employed to evaluate both individual and interactive effects of the parameters on BrO3-removal, achieving an optimum removal efficiency of approximately 99.6% using 1.5 g/L of ZIF-67/GO at a pH value of 4 with an initial BrO3-concentration of 2 mg/L. The optimization process was further supported by desirability analysis. The BrO-3 removal mechanisms are primarily attributed to porosity, electrostatic interactions, and adsorption onto active sites. Compared to ZIF-67 alone, ZIF-67/GO demonstrated superior anion removal efficiency, highlighting its potential for water treatment applications.
Bromate (BrO3-) is a toxic disinfection byproduct frequently formed during ozonation in water treatment processes and is classified as a potential human carcinogen. Its effective removal from drinking water is therefore a pressing concern for public health and environmental safety. This study investigated the removal of BrO3-from water using the synthesized zeolite imidazolate framework (ZIF)-67 and ZIF-67/graphene oxide (GO) nanocomposites through a comparative approach. The morphology, composition, and crystallinity of both ZIFs were characterized. The effects of four independent parameters (initial BrO3-concentration, pH, adsorbent dose, and contact time) on BrO-3 removal efficiency were examined. A strong correlation was observed between experimental and predicted values. GO enhanced BrO-3 removal not only through synergistic interactions with ZIF-67 but also by improving dispersion and providing additional functional groups that facilitate electrostatic interactions and adsorption. The Box—Behnken design was employed to evaluate both individual and interactive effects of the parameters on BrO3-removal, achieving an optimum removal efficiency of approximately 99.6% using 1.5 g/L of ZIF-67/GO at a pH value of 4 with an initial BrO3-concentration of 2 mg/L. The optimization process was further supported by desirability analysis. The BrO-3 removal mechanisms are primarily attributed to porosity, electrostatic interactions, and adsorption onto active sites. Compared to ZIF-67 alone, ZIF-67/GO demonstrated superior anion removal efficiency, highlighting its potential for water treatment applications.
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.
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.
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.
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.
2023, 16(4): 333-344.
doi: 10.1016/j.wse.2023.04.003
摘要：
Clean drinking water is one of the United Nations Sustainable Development Goals. Despite significant progress in the water purification technology, many regions still lack access to clean water. This paper provides a review of selected water contaminants and their impacts on human health. The World Health Organization (WHO) guidelines and regional standards for key contaminants were used to characterise water quality in the European Union and UK. The concept of safe drinking water was explained based on the non-observed adverse effect level, threshold concentrations for toxic chemicals, and their total daily intake. Various techniques for monitoring water contaminants and the drinking water standards from five different countries, including the UK, USA, Canada, Pakistan and India, were compared to WHO recommended guidelines. The literature on actual water quality in these regions and its potential health impacts was also discussed. Finally, the role of public water suppliers in identifying and monitoring drinking water contaminants in selected developed countries was presented as a potential guideline for developing countries. This review emphasised the need for a comprehensive understanding of water quality and its impacts on human health to ensure access to clean drinking water worldwide.
Clean drinking water is one of the United Nations Sustainable Development Goals. Despite significant progress in the water purification technology, many regions still lack access to clean water. This paper provides a review of selected water contaminants and their impacts on human health. The World Health Organization (WHO) guidelines and regional standards for key contaminants were used to characterise water quality in the European Union and UK. The concept of safe drinking water was explained based on the non-observed adverse effect level, threshold concentrations for toxic chemicals, and their total daily intake. Various techniques for monitoring water contaminants and the drinking water standards from five different countries, including the UK, USA, Canada, Pakistan and India, were compared to WHO recommended guidelines. The literature on actual water quality in these regions and its potential health impacts was also discussed. Finally, the role of public water suppliers in identifying and monitoring drinking water contaminants in selected developed countries was presented as a potential guideline for developing countries. This review emphasised the need for a comprehensive understanding of water quality and its impacts on human health to ensure access to clean drinking water worldwide.
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.
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.
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.
2022, 15(1): 29-39.
doi: 10.1016/j.wse.2021.12.006
摘要：
In this article, current research findings of local scour at offshore windfarm monopile foundations are presented. The scour mechanisms and scour depth prediction formulas under different hydrodynamic conditions are summarized, including the current-only condition, wave-only condition, combined wave-current condition, and complex dynamic condition. Furthermore, this article analyzes the influencing factors on the basis of classical equations for predicting the equilibrium scour depth under specific conditions. The weakness of existing researches and future prospects are also discussed. It is suggested that future research shall focus on physical experiments under unsteady tidal currents or other complex loadings. The computational fluid dynamics-discrete element method and artificial intelligence technique are suggested being adopted to study the scour at offshore windfarm foundations.
In this article, current research findings of local scour at offshore windfarm monopile foundations are presented. The scour mechanisms and scour depth prediction formulas under different hydrodynamic conditions are summarized, including the current-only condition, wave-only condition, combined wave-current condition, and complex dynamic condition. Furthermore, this article analyzes the influencing factors on the basis of classical equations for predicting the equilibrium scour depth under specific conditions. The weakness of existing researches and future prospects are also discussed. It is suggested that future research shall focus on physical experiments under unsteady tidal currents or other complex loadings. The computational fluid dynamics-discrete element method and artificial intelligence technique are suggested being adopted to study the scour at offshore windfarm foundations.
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
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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
4
2010, 3(1): 1-13.
doi: 10.3882/j.issn.1674-2370.2010.01.001
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2010, 3(4): 418-430.
doi: 10.3882/j.issn.1674-2370.2010.04.005
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2012, 5(1): 105-119.
doi: 10.3882/j.issn.1674-2370.2012.01.010
Volume 18，Issue 3，
Sep. 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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