The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Zhenyao Shen - One of the best experts on this subject based on the ideXlab platform.
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influence of rainfall data scarcity on non Point Source Pollution prediction implications for physically based models
Journal of Hydrology, 2018Co-Authors: Lei Chen, Guobo Wang, Hongbin Liu, Limei Zhai, Cheng Sun, Zhenyao ShenAbstract:Abstract Hydrological and non-Point Source Pollution (H/NPS) predictions in ungagged basins have become the key problem for watershed studies, especially for those large-scale catchments. However, few studies have explored the comprehensive impacts of rainfall data scarcity on H/NPS predictions. This study focused on: 1) the effects of rainfall spatial scarcity (by removing 11%–67% of stations based on their locations) on the H/NPS results; and 2) the impacts of rainfall temporal scarcity (10%–60% data scarcity in time series); and 3) the development of a new evaluation method that incorporates information entropy. A case study was undertaken using the Soil and Water Assessment Tool (SWAT) in a typical watershed in China. The results of this study highlighted the importance of critical-site rainfall stations that often showed greater influences and cross-tributary impacts on the H/NPS simulations. Higher missing rates above a certain threshold as well as missing locations during the wet periods resulted in poorer simulation results. Compared to traditional indicators, information entropy could serve as a good substitute because it reflects the distribution of spatial variability and the development of temporal heterogeneity. This paper reports important implications for the application of Distributed Hydrological Models and Semi-distributed Hydrological Models, as well as for the optimal design of rainfall gauges among large basins.
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assessment of effects of best management practices on agricultural non Point Source Pollution in xiangxi river watershed
Agricultural Water Management, 2013Co-Authors: Ruimin Liu, Peipei Zhang, Xiujuan Wang, Yaxin Chen, Zhenyao ShenAbstract:Agricultural non-Point Source Pollution (ANSP) is considered a major contributor to local water degradation in the Three Gorges Reservoir Area (TGRA) of China. The Xiangxi River, which is a first level anabranch of the Yangtze River, was selected for investigation of the effectiveness of selected best management measures (BMPs) to alleviate water Pollution through analysis of several scenarios by SWAT (Soil and Water Assessment Tool). Specifically, changes in land use, fertilizer management and tillage management measures were simulated in SWAT because they were shown to be the primary factors influencing non-Point Source (NPS) Pollution in the Xiangxi River watershed. The results revealed that when farmland was returned to forests, both runoff and NPS Pollution loads showed a clear downward trend and the NPS Pollution loads in the Xiangxi River watershed decreased by 20% or more when compared with the status of 2007. Furthermore, conservation tillage and contour farming can help reduce runoff by 15.99% and 9.16%, total nitrogen (TN) by 8.99% and 8%, and total phosphorus (TP) by 7% and 5%, respectively. Conservation tillage has a greater effect in controlling the losses of soil, water and nutrients than contour farming. Based on the fertilizer conditions of 2007, changing the fertilizer application resulted in little change in local runoff; however, for NPS Pollution loads, various forms of nitrogen (N) and phosphorus (P) Pollution loads were directly proportional to the amount of chemical fertilizer applied. Overall, the results of this study can facilitate development of environmental friendly land use plans by local managers, and enable farmers to manage agriculture and fertilizer more efficiently, ultimately achieve the goal of reduce water Pollution.
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an overview of research on agricultural non Point Source Pollution modelling in china
Separation and Purification Technology, 2012Co-Authors: Zhenyao Shen, Qian Hong, Qian Liao, Yongwei GongAbstract:Abstract With the development of technology for controlling Point Source Pollution, non-Point Source (NPS) Pollution issues have become increasingly prominent worldwide. Because of the wide range, difficult control and complex uncertainties involved in simulation processes, NPS Pollution control has become a hotspot in the area of water Pollution control. In China, NPS Pollution control will be one of the most important issues in water environmental protection in the next several decades. To control NPS Pollution, it is important to know how much there is. In this paper, the authors provide an overview of the current NPS Pollution modelling technology in China. We first compared several methods used for estimation of the NPS Pollution load in China. We next discussed the advantages and disadvantages of these methods in detail, both from the method itself and the simulation results. We found that most of these methods are derived directly from models developed by several developed countries, especially the USA. Although these models may be suitable to the situation of the country they were designed in, they may not be suitable to the actual situation of China. Other methods have been developed by scholars in China, but these are all very simple and may not provide a good estimation. Finally, we Point out that we can only determine if a NPS model is good or bad according to the actual conditions of the study area and the available data for this area. Overall, the results of this study indicated that digesting and absorbing foreign NPS models, modifying the related processes and using related key parameters with Chinese characteristics are the future research direction for NPS Pollution modelling in China.
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parameter uncertainty analysis of non Point Source Pollution from different land use types
Science of The Total Environment, 2010Co-Authors: Zhenyao Shen, Qian Hong, Junfeng NiuAbstract:Land use type is one of the most important factors that affect the uncertainty in non-Point Source (NPS) Pollution simulation. In this study, seventeen sensitive parameters were screened from the Soil and Water Assessment Tool (SWAT) model for parameter uncertainty analysis for different land use types in the Daning River Watershed of the Three Gorges Reservoir area, China. First-Order Error Analysis (FOEA) method was adopted to analyze the effect of parameter uncertainty on model outputs under three types of land use, namely, plantation, forest and grassland. The model outputs selected in this study consisted of runoff, sediment yield, organic nitrogen (N), and total phosphorus (TP). The results indicated that the uncertainty conferred by the parameters differed among the three land use types. In forest and grassland, the parameter uncertainty in NPS Pollution was primarily associated with runoff processes, but in plantation, the main uncertain parameters were related to runoff process and soil properties. Taken together, the study suggested that adjusting the structure of land use and controlling fertilizer use are helpful methods to control the NPS Pollution in the Daning River Watershed.
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parameter uncertainty analysis of the non Point Source Pollution in the daning river watershed of the three gorges reservoir region china
Science of The Total Environment, 2008Co-Authors: Zhenyao Shen, Qian Hong, Ruimin LiuAbstract:The generation and formation of non-Point Source Pollution involves great uncertainty, and this uncertainty makes monitoring and controlling Pollution very difficult. Understanding the main parameters that affect non-Point Source Pollution uncertainty is necessary to provide the basis for the planning and design of control measures. In this study, three methods were adopted to do the parameter uncertainty analysis with the Soil and Water Assessment Tool (SWAT). Based on the results of parameter sensitivity analysis by the Morris screening method, the ten parameters that most affect runoff, sediment, organic N, nitrate, and total phosphorous (TP) were chosen for further uncertainty analysis. First-order error analysis (FOEA) and the Monte Carlo method (MC) were used to analyze the effect of parameter uncertainty on model outputs. FOEA results showed that only a few parameters had significantly affected the uncertainty of the final simulation results, and many parameters had little or no effect. The SCS curve number was the parameter with significant uncertainty impact on runoff, sediment, organic N, nitrate and TP, and it showed that the runoff process was mainly responsible for the uncertainty of non-Point Source Pollution load. The uncertainty of sediment was the biggest among the five model output results described above. MC results indicated that neglecting the parameter uncertainty of the model would underestimate the non-Point Source Pollution load, and that the relationship between model input and output was non-linear. The uncertainty of non-Point Source Pollution exhibited a temporal pattern: It was greater in summer than in winter. The uncertainty of runoff was smaller compared to that of sediment, organic N, nitrate, and TP, and the Source of uncertainty was mainly affected by parameters associated with runoff.
Zhi Zhou - One of the best experts on this subject based on the ideXlab platform.
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occurrence and distribution of trace levels of antibiotics in surface waters and soils driven by non Point Source Pollution and anthropogenic pressure
Chemosphere, 2019Co-Authors: Chenghui Lin, Eugene Jie Li Ong, Mian Wang, Zhi ZhouAbstract:Abstract Antibiotics in surface waters and soils are growing public health concerns and treated wastewater has often been identified as the main Source of antibiotics. However, few studies have been conducted to evaluate the occurrence and concentrations of antibiotics in coastal cities without direct impact of wastewater discharge. In this study, the occurrence of 14 antibiotics including four macrolides, three sulfonamides, three β-lactams, lincomycin, chloramphenicol, furazolidon, and monensin in surface waters and soils in Singapore were analyzed with SPE-LC-ESI-MS/MS. The detected concentrations of antibiotics were all below 82.5 ng/L in surface waters and below 80.6 ng/g dry wt in soils. These concentrations were significantly lower than other cities that were under the impact of treated wastewater discharge, suggesting that reduction of treated wastewater discharge reduces occurrence of antibiotics in the environment. However, the wide occurrence of trace levels of antibiotics suggest that other factors may have contributed to detected environmental antibiotics. Population density was positively correlated with concentrations of clarithromycin, lincomycin, azithromycin, and sulfamethoxazole in surface waters, suggesting that non-Point Source Pollution due to anthropogenic pressure may contribute to the wide detection of trace levels of antibiotics. The potential impact of antibiotic use, natural production, and half-lives of antibiotics were further discussed. Further studies are needed to evaluate how anthropogenic activities other than wastewater discharge may contribute to the occurrence of trace level antibiotics and their associated health risks in urban environments.
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occurrence and distribution of trace levels of antibiotics in surface waters and soils driven by non Point Source Pollution and anthropogenic pressure
Chemosphere, 2019Co-Authors: Xinzhu Yi, Mian Wang, Zhi ZhouAbstract:Abstract Antibiotics in surface waters and soils are growing public health concerns and treated wastewater has often been identified as the main Source of antibiotics. However, few studies have been conducted to evaluate the occurrence and concentrations of antibiotics in coastal cities without direct impact of wastewater discharge. In this study, the occurrence of 14 antibiotics including four macrolides, three sulfonamides, three β-lactams, lincomycin, chloramphenicol, furazolidon, and monensin in surface waters and soils in Singapore were analyzed with SPE-LC-ESI-MS/MS. The detected concentrations of antibiotics were all below 82.5 ng/L in surface waters and below 80.6 ng/g dry wt in soils. These concentrations were significantly lower than other cities that were under the impact of treated wastewater discharge, suggesting that reduction of treated wastewater discharge reduces occurrence of antibiotics in the environment. However, the wide occurrence of trace levels of antibiotics suggest that other factors may have contributed to detected environmental antibiotics. Population density was positively correlated with concentrations of clarithromycin, lincomycin, azithromycin, and sulfamethoxazole in surface waters, suggesting that non-Point Source Pollution due to anthropogenic pressure may contribute to the wide detection of trace levels of antibiotics. The potential impact of antibiotic use, natural production, and half-lives of antibiotics were further discussed. Further studies are needed to evaluate how anthropogenic activities other than wastewater discharge may contribute to the occurrence of trace level antibiotics and their associated health risks in urban environments.
Longfei Han - One of the best experts on this subject based on the ideXlab platform.
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zonation on non Point Source Pollution risk in the lower reaches of zijiang river based on the Source sink theory
Journal of Applied Ecology, 2020Co-Authors: Yuxue Jia, Hong Shuai, Longfei HanAbstract:Non-Point Source Pollution risk assessment and zonation research are of great significance for the eco-environmental protection and optimization of land use structure. We identified the "Source" and "sink" landscape using the "Source-sink" landscape pattern theory based on the two phases of land use data in the lower reaches of Zijiang River in 2010 and 2018. We comprehensively considered the non-Point Source Pollution occurrence and migration factors, and used location-weighted landscape contrast index (LCI) and non-Point Source Pollution load index (NPPRI) to analyze non-Point Source Pollution risk spatio-temporal characteristics in the study area. Zonation on non-Point Source Pollution in the lower reaches of Zijiang River was studied by identifying the key factors of non-Point Source Pollution risk. The results showed that the overall risk of non-Point Source Pollution was relatively low. The sub-basin with "sink" landscape was the main type, accounting for 61.2%. Non-Point Source Pollution risk was low in the southwest and was high along the banks of Zhixi River, Taohua River and main stream of Zijiang River, as well as plain in the northeast of the lower Zijiang River. The risk of non-Point Source Pollution from 2010 to 2018 showed an increasing trend. The changes in landscape pattern, especially the expansion of rural settlement, arable land and the shrinkage of forest land had positive and negative responses to the risk of non-Point Source Pollution, respectively. LCI, slope, and distance were the key factors affecting the change of the risk index of non-Point Source Pollution. The lower reaches of the Zijiang River could be divided into four control regions: Pollution treatment area near river, low slope Pollution control area, ecological restoration-risk prevention and control area, and ecological priority protection area.
Jianfeng Zhang - One of the best experts on this subject based on the ideXlab platform.
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discussing on Source sink landscape theory and phytoremediation for non Point Source Pollution control in china
Environmental Science and Pollution Research, 2020Co-Authors: Rongjia Wang, Ying Wang, Shiyong Sun, Chunju Cai, Jianfeng ZhangAbstract:Water Pollution is exacerbated due to irrational human activities in China. Restoring and rebuilding river basin ecosystems are major ecological strategies at present. Controlling the non-Point Source Pollution (NPSP) by reasonable management of land use in the basin and phytoremediation of contaminated waters is the optimum approach. Thus, it is significant to study on the relationship that between landscape change and the aquatic environment, as well as further to analyze on the combined effect of the landscape and water quality. This paper describes the application and development of the “Source–sink” landscape theory in China, and the role of the theory in controlling NPSP. From this perspective, a landscape capable of generating NPSP would be a “Source” landscape, such as farmland, while another capable of preventing NPSP would be a “sink” landscape, such as forests and wetland. Applying the Source-sink landscape theory, it is possible to exert the ecological benefits of the landscape while playing the esthetic value of the landscape. Also, the purification mechanism of plants in contaminated water is discussed. Besides, it is vital that research on water body restoration should focus not only on single discipline but also on integration and coordination between various ones such as ecology, environmental science, and geography to jointly push up researches related to water body phytoremediation. Hopefully, this paper could help to control water Pollution from a new perspective, also to improve water environment and benefit human lives.
Ruimin Liu - One of the best experts on this subject based on the ideXlab platform.
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application of genetic algorithm to land use optimization for non Point Source Pollution control based on clue s and swat
Journal of Hydrology, 2018Co-Authors: Qingrui Wang, Ruimin Liu, Cong Men, Lijia GuoAbstract:Abstract The genetic algorithm (GA) was combined with the Conversion of Land Use and its Effect at Small regional extent (CLUE-S) model to obtain an optimized land use pattern for controlling non-Point Source (NPS) Pollution. The performance of the combination was evaluated. The effect of the optimized land use pattern on the NPS Pollution control was estimated by the Soil and Water Assessment Tool (SWAT) model and an assistant map was drawn to support the land use plan for the future. The Xiangxi River watershed was selected as the study area. Two scenarios were used to simulate the land use change. Under the historical trend scenario (Markov chain prediction), the forest area decreased by 2035.06 ha, and was mainly converted into paddy and dryland area. In contrast, under the optimized scenario (genetic algorithm (GA) prediction), up to 3370 ha of dryland area was converted into forest area. Spatially, the conversion of paddy and dryland into forest occurred mainly in the northwest and southeast of the watershed, where the slope land occupied a large proportion. The organic and inorganic phosphorus loads decreased by 3.6% and 3.7%, respectively, in the optimized scenario compared to those in the historical trend scenario. GA showed a better performance in optimized land use prediction. A comparison of the land use patterns in 2010 under the real situation and in 2020 under the optimized situation showed that Shennongjia and Shuiyuesi should convert 1201.76 ha and 1115.33 ha of dryland into forest areas, respectively, which represented the greatest changes in all regions in the watershed. The results of this study indicated that GA and the CLUE-S model can be used to optimize the land use patterns in the future and that SWAT can be used to evaluate the effect of land use optimization on non-Point Source Pollution control. These methods may provide support for land use plan of an area.
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assessment of effects of best management practices on agricultural non Point Source Pollution in xiangxi river watershed
Agricultural Water Management, 2013Co-Authors: Ruimin Liu, Peipei Zhang, Xiujuan Wang, Yaxin Chen, Zhenyao ShenAbstract:Agricultural non-Point Source Pollution (ANSP) is considered a major contributor to local water degradation in the Three Gorges Reservoir Area (TGRA) of China. The Xiangxi River, which is a first level anabranch of the Yangtze River, was selected for investigation of the effectiveness of selected best management measures (BMPs) to alleviate water Pollution through analysis of several scenarios by SWAT (Soil and Water Assessment Tool). Specifically, changes in land use, fertilizer management and tillage management measures were simulated in SWAT because they were shown to be the primary factors influencing non-Point Source (NPS) Pollution in the Xiangxi River watershed. The results revealed that when farmland was returned to forests, both runoff and NPS Pollution loads showed a clear downward trend and the NPS Pollution loads in the Xiangxi River watershed decreased by 20% or more when compared with the status of 2007. Furthermore, conservation tillage and contour farming can help reduce runoff by 15.99% and 9.16%, total nitrogen (TN) by 8.99% and 8%, and total phosphorus (TP) by 7% and 5%, respectively. Conservation tillage has a greater effect in controlling the losses of soil, water and nutrients than contour farming. Based on the fertilizer conditions of 2007, changing the fertilizer application resulted in little change in local runoff; however, for NPS Pollution loads, various forms of nitrogen (N) and phosphorus (P) Pollution loads were directly proportional to the amount of chemical fertilizer applied. Overall, the results of this study can facilitate development of environmental friendly land use plans by local managers, and enable farmers to manage agriculture and fertilizer more efficiently, ultimately achieve the goal of reduce water Pollution.
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parameter uncertainty analysis of the non Point Source Pollution in the daning river watershed of the three gorges reservoir region china
Science of The Total Environment, 2008Co-Authors: Zhenyao Shen, Qian Hong, Ruimin LiuAbstract:The generation and formation of non-Point Source Pollution involves great uncertainty, and this uncertainty makes monitoring and controlling Pollution very difficult. Understanding the main parameters that affect non-Point Source Pollution uncertainty is necessary to provide the basis for the planning and design of control measures. In this study, three methods were adopted to do the parameter uncertainty analysis with the Soil and Water Assessment Tool (SWAT). Based on the results of parameter sensitivity analysis by the Morris screening method, the ten parameters that most affect runoff, sediment, organic N, nitrate, and total phosphorous (TP) were chosen for further uncertainty analysis. First-order error analysis (FOEA) and the Monte Carlo method (MC) were used to analyze the effect of parameter uncertainty on model outputs. FOEA results showed that only a few parameters had significantly affected the uncertainty of the final simulation results, and many parameters had little or no effect. The SCS curve number was the parameter with significant uncertainty impact on runoff, sediment, organic N, nitrate and TP, and it showed that the runoff process was mainly responsible for the uncertainty of non-Point Source Pollution load. The uncertainty of sediment was the biggest among the five model output results described above. MC results indicated that neglecting the parameter uncertainty of the model would underestimate the non-Point Source Pollution load, and that the relationship between model input and output was non-linear. The uncertainty of non-Point Source Pollution exhibited a temporal pattern: It was greater in summer than in winter. The uncertainty of runoff was smaller compared to that of sediment, organic N, nitrate, and TP, and the Source of uncertainty was mainly affected by parameters associated with runoff.
