Articles in press are presented at https://www.sciencedirect.com/journal/water-science-and-engineering/articles-in-press
2024, 17(4): 319-322.
doi: 10.1016/j.wse.2024.06.002
Abstract:
Flood control operation, a non-engineering measure, can efficiently manage flood disasters within a river basin. However, numerous uncertainties exit in the real-time operation of flood control systems, creating risks in decision-making. As an efficient tool to mitigate these risks, risk management has garnered increasing attention in real-time flood control operation. This communication offers a series of suggestions for future research concerning risk management in real-time flood control operation, including risk assessment, risk diagnosis, and risk control methods.
Flood control operation, a non-engineering measure, can efficiently manage flood disasters within a river basin. However, numerous uncertainties exit in the real-time operation of flood control systems, creating risks in decision-making. As an efficient tool to mitigate these risks, risk management has garnered increasing attention in real-time flood control operation. This communication offers a series of suggestions for future research concerning risk management in real-time flood control operation, including risk assessment, risk diagnosis, and risk control methods.
2024, 17(4): 323-335.
doi: 10.1016/j.wse.2023.12.003
Abstract:
The Ba Lang sand beaches, located north of the Nha Trang Bay in Central Vietnam, are famous tourist attractions. However, they are experiencing shoreline and coastal erosion retreat, which is attributed to natural causes (such as tropical depressions, storms, and monsoons) as well as human impacts (such as hydropower generation, sand dredging, and coastal works). According to the forecast of the Vietnam Ministry of Natural Resources and Environment, global climate change will cause the sea level to rise by 74 cm along the coast from the Dai Lanh Cape to the Ke Ga Cape (including the Ba Lang beaches) by the end of this century in the representative concentration pathway (RCP) 8.5 scenario. Sea level rise (SLR) due to global climate change is expected to aggravate the coastal erosion and shoreline retreat problems. In this study, coupled numerical models with the spectral wave module (MIKE 21 SW), hydrodynamic module (MIKE 21 HD), and sand transport module (MIKE 21 ST) in the MIKE 21 package were used to simulate waves, current fields, and sediment dynamics along the Ba Lang beaches considering the impact of SLR. These models were calibrated with the field data measured in December 2016. The results showed that SLR caused the wave height to increase and reduced the current speed and total sediment load in monsoon conditions. The increase in wave height was even intensified under the joint impact of SLR and extreme events.
The Ba Lang sand beaches, located north of the Nha Trang Bay in Central Vietnam, are famous tourist attractions. However, they are experiencing shoreline and coastal erosion retreat, which is attributed to natural causes (such as tropical depressions, storms, and monsoons) as well as human impacts (such as hydropower generation, sand dredging, and coastal works). According to the forecast of the Vietnam Ministry of Natural Resources and Environment, global climate change will cause the sea level to rise by 74 cm along the coast from the Dai Lanh Cape to the Ke Ga Cape (including the Ba Lang beaches) by the end of this century in the representative concentration pathway (RCP) 8.5 scenario. Sea level rise (SLR) due to global climate change is expected to aggravate the coastal erosion and shoreline retreat problems. In this study, coupled numerical models with the spectral wave module (MIKE 21 SW), hydrodynamic module (MIKE 21 HD), and sand transport module (MIKE 21 ST) in the MIKE 21 package were used to simulate waves, current fields, and sediment dynamics along the Ba Lang beaches considering the impact of SLR. These models were calibrated with the field data measured in December 2016. The results showed that SLR caused the wave height to increase and reduced the current speed and total sediment load in monsoon conditions. The increase in wave height was even intensified under the joint impact of SLR and extreme events.
2024, 17(4): 336-343.
doi: 10.1016/j.wse.2023.12.005
Abstract:
The Pussur River, an important river in Bangladesh, requires approximately 6 × 106 m3 of sediment to be dredged per year. At present, this dredged material is mainly dumped on the nearby agricultural and fish-cultivation lands, causing a reduction in productive land and producing negative impacts on people's livelihoods. This study aimed to investigate the engineering and environmental properties of the dredged sand of the Pussur River and evaluate the viability of its potential uses in different sectors. Bed sediments from the Pussur River and dredged material from disposal sites were collected, and laboratory investigations were performed. The test results showed that the dredged material of the Pussur River mainly consisted of fine sand with a fineness modulus ranging from 0.58 to 0.72 and could be classified as poorly graded sand according to the Unified Soil Classification System. This sand was also found suitable for land development, with a fair to poor suitability rating. Given the low concentration of heavy metals (at uncontaminated/slightly contaminated levels), the dredged sand might be safely used for land reclamation, landfill cover, and horticultural purposes, or else for other geotechnical applications without further treatment. After washing/leaching, the dredged sand could also be used as a partial replacement for local sand in concrete works. Moreover, there is a possibility of exporting the dredged sand to Singapore and the Maldives as filling material. These findings will help policymakers design dredging projects with a proper spoil management plan accounting for the dredged material's beneficial use.
The Pussur River, an important river in Bangladesh, requires approximately 6 × 106 m3 of sediment to be dredged per year. At present, this dredged material is mainly dumped on the nearby agricultural and fish-cultivation lands, causing a reduction in productive land and producing negative impacts on people's livelihoods. This study aimed to investigate the engineering and environmental properties of the dredged sand of the Pussur River and evaluate the viability of its potential uses in different sectors. Bed sediments from the Pussur River and dredged material from disposal sites were collected, and laboratory investigations were performed. The test results showed that the dredged material of the Pussur River mainly consisted of fine sand with a fineness modulus ranging from 0.58 to 0.72 and could be classified as poorly graded sand according to the Unified Soil Classification System. This sand was also found suitable for land development, with a fair to poor suitability rating. Given the low concentration of heavy metals (at uncontaminated/slightly contaminated levels), the dredged sand might be safely used for land reclamation, landfill cover, and horticultural purposes, or else for other geotechnical applications without further treatment. After washing/leaching, the dredged sand could also be used as a partial replacement for local sand in concrete works. Moreover, there is a possibility of exporting the dredged sand to Singapore and the Maldives as filling material. These findings will help policymakers design dredging projects with a proper spoil management plan accounting for the dredged material's beneficial use.
2024, 17(4): 344-351.
doi: 10.1016/j.wse.2024.01.002
Abstract:
Oyster aquaculture in Oualidia Lagoon, Morocco, has suffered from poor water quality and water confinement in its upstream region. Tidal asymmetry (TA) has been suggested as a possible cause, and a sediment trap was dredged in 2011 to mitigate this condition. This study addresses TA in the lagoon using field measurements and numerical modeling in the presence of the sediment trap. Results indicate that the lagoon is flood-dominated mostly in its upstream end, where frictional forces exceed inertia accelerations during the tidal cycle and fine sediments settle on the tidal flats and inside the sediment trap. However, this study shows that a large mass of suspended sediments is exported to the ocean, which is contrary to expectations in flood-dominated lagoons. Defining the sediment trap as the rehabilitation scenario S1, the impacts of three additional scenarios on TA are examined. These are scenario S2 (dredging the upstream section of the main channel), scenario S3 (dredging the channels surrounding the flood delta near the inlets), and scenario S4 (raising the ocean level by 0.5 m following climate change predictions). Results show that none of these scenarios modify the tidal flood dominance in the lagoon, although scenarios S2 and S4 decrease its intensity in the upstream region. Nevertheless, all scenarios still contribute to a significant export of sediments to the ocean. This suggests that lagoon management activities should not rely on tidal asymmetry analyses that normally predict upstream sediment transport in flood-dominated lagoons.
Oyster aquaculture in Oualidia Lagoon, Morocco, has suffered from poor water quality and water confinement in its upstream region. Tidal asymmetry (TA) has been suggested as a possible cause, and a sediment trap was dredged in 2011 to mitigate this condition. This study addresses TA in the lagoon using field measurements and numerical modeling in the presence of the sediment trap. Results indicate that the lagoon is flood-dominated mostly in its upstream end, where frictional forces exceed inertia accelerations during the tidal cycle and fine sediments settle on the tidal flats and inside the sediment trap. However, this study shows that a large mass of suspended sediments is exported to the ocean, which is contrary to expectations in flood-dominated lagoons. Defining the sediment trap as the rehabilitation scenario S1, the impacts of three additional scenarios on TA are examined. These are scenario S2 (dredging the upstream section of the main channel), scenario S3 (dredging the channels surrounding the flood delta near the inlets), and scenario S4 (raising the ocean level by 0.5 m following climate change predictions). Results show that none of these scenarios modify the tidal flood dominance in the lagoon, although scenarios S2 and S4 decrease its intensity in the upstream region. Nevertheless, all scenarios still contribute to a significant export of sediments to the ocean. This suggests that lagoon management activities should not rely on tidal asymmetry analyses that normally predict upstream sediment transport in flood-dominated lagoons.
2024, 17(4): 352-360.
doi: 10.1016/j.wse.2024.01.001
Abstract:
Simultaneous nitrification and denitrification (SND) is an efficient method to remove nitrogen in municipal wastewater treatment. However, low dissolved oxygen (DO) concentrations are generally required, leading to serious membrane fouling in membrane bioreactors (MBRs). This study aimed to clarify the synergistic effect of biomass and DO on nitrogen removal and membrane fouling. To achieve this goal, four submerged MBRs equipped with ceramic membranes were operated with different biomass (mixed liquor suspended solids (MLSS)) concentrations (3 000 mg/L, 5 000 mg/L, 7 500 mg/L, and 12 000 mg/L) under various DO concentrations (2.0 mg/L, 1.0 mg/L, and 0.5 mg/L). As a result, increasing biomass in the MBRs enhanced total nitrogen (TN) removal via SND, and excellent TN removal efficiencies of 60.7% and 75.8% were obtained using the MBR with an MLSS concentration of 12 000 mg/L and DO concentrations of 2.0 mg/L and 1.0 mg/L. However, a further decrease in DO deteriorated TN removal due to the inhibition of nitrification. Moreover, high MLSS concentrations were beneficial to membrane fouling control for ceramic membranes in MBRs. The lowest transmembrane pressure development rate was observed for the MBR with an MLSS concentration of 12 000 mg/L. High biomass offset the adverse effect of DO decrease on membrane fouling to some extent, and improved the stability of the reactor. Therefore, biomass might be an important parameter for membrane fouling reduction in ceramic MBRs. Overall, optimal biomass and DO concentrations for TN removal were identified, providing useful information for the successful operation of MBRs with efficient TN removal and membrane fouling control.
Simultaneous nitrification and denitrification (SND) is an efficient method to remove nitrogen in municipal wastewater treatment. However, low dissolved oxygen (DO) concentrations are generally required, leading to serious membrane fouling in membrane bioreactors (MBRs). This study aimed to clarify the synergistic effect of biomass and DO on nitrogen removal and membrane fouling. To achieve this goal, four submerged MBRs equipped with ceramic membranes were operated with different biomass (mixed liquor suspended solids (MLSS)) concentrations (3 000 mg/L, 5 000 mg/L, 7 500 mg/L, and 12 000 mg/L) under various DO concentrations (2.0 mg/L, 1.0 mg/L, and 0.5 mg/L). As a result, increasing biomass in the MBRs enhanced total nitrogen (TN) removal via SND, and excellent TN removal efficiencies of 60.7% and 75.8% were obtained using the MBR with an MLSS concentration of 12 000 mg/L and DO concentrations of 2.0 mg/L and 1.0 mg/L. However, a further decrease in DO deteriorated TN removal due to the inhibition of nitrification. Moreover, high MLSS concentrations were beneficial to membrane fouling control for ceramic membranes in MBRs. The lowest transmembrane pressure development rate was observed for the MBR with an MLSS concentration of 12 000 mg/L. High biomass offset the adverse effect of DO decrease on membrane fouling to some extent, and improved the stability of the reactor. Therefore, biomass might be an important parameter for membrane fouling reduction in ceramic MBRs. Overall, optimal biomass and DO concentrations for TN removal were identified, providing useful information for the successful operation of MBRs with efficient TN removal and membrane fouling control.
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.
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.
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.
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.
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.
2019, 12(2): 85-97.
doi: 10.1016/j.wse.2019.06.001
摘要:
The objective of this study was to retrieve daily composite soil moisture by jointly using brightness temperature observations from multiple operating satellites for near real-time application with better coverage and higher accuracy. Our approach was to first apply the single-channel brightness radiometric algorithm to estimate soil moisture from the respective brightness temperature observations of the SMAP, SMOS, AMSR2, FY3B, and FY3C satellites on the same day and then produce a daily composite dataset by averaging the individual satellite-retrieved soil moisture. We further evaluated our product, the official soil moisture products of the five satellites, and the ensemble mean (i.e., arithmetic mean) of the five official satellite soil moisture products against ground observations from two networks in Central Tibet and Anhui Province, China. The results show that our product outperforms the individual released products of the five satellites and their ensemble means in the two validation areas. The root mean square error (RMSE) values of our product were 0.06 and 0.09 m3/m3 in Central Tibet and Anhui Province, respectively. Relative to the ensemble mean of the five satellite products, our product improves the accuracy by 9.1% and 57.7% in Central Tibet and Anhui Province, respectively. This demonstrates that jointly using brightness temperature observations from multiple satellites to retrieve soil moisture not only improves the spatial coverage of daily observations but also produces better daily composite products.
The objective of this study was to retrieve daily composite soil moisture by jointly using brightness temperature observations from multiple operating satellites for near real-time application with better coverage and higher accuracy. Our approach was to first apply the single-channel brightness radiometric algorithm to estimate soil moisture from the respective brightness temperature observations of the SMAP, SMOS, AMSR2, FY3B, and FY3C satellites on the same day and then produce a daily composite dataset by averaging the individual satellite-retrieved soil moisture. We further evaluated our product, the official soil moisture products of the five satellites, and the ensemble mean (i.e., arithmetic mean) of the five official satellite soil moisture products against ground observations from two networks in Central Tibet and Anhui Province, China. The results show that our product outperforms the individual released products of the five satellites and their ensemble means in the two validation areas. The root mean square error (RMSE) values of our product were 0.06 and 0.09 m3/m3 in Central Tibet and Anhui Province, respectively. Relative to the ensemble mean of the five satellite products, our product improves the accuracy by 9.1% and 57.7% in Central Tibet and Anhui Province, respectively. This demonstrates that jointly using brightness temperature observations from multiple satellites to retrieve soil moisture not only improves the spatial coverage of daily observations but also produces better daily composite products.
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
2
2010, 3(3): 241-256.
doi: 10.3882/j.issn.1674-2370.2010.03.001
3
2010, 3(4): 418-430.
doi: 10.3882/j.issn.1674-2370.2010.04.005
4
2011, 4(1): 101-109.
doi: 10.3882/j.issn.1674-2370.2011.01.010
5
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 17,Issue 4,
Nov. 2024
Editor-in-ChiefChao Wang
Edited byEditorial Board of Water Science and Engineering
Distributed byEditorial Office of Water Science and Engineering
News
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- WSE Special Issue for CORE2021 March 09,2021