The Changsha-Xiangtan-Zhuzhou City Group is a heavy industrial district and accepted as the serious pollution area in the Xiangjiang River basin.In this study,7 metals(Pb,Hg,Cd,As,Zn,Cu and Se)and the river water qual...The Changsha-Xiangtan-Zhuzhou City Group is a heavy industrial district and accepted as the serious pollution area in the Xiangjiang River basin.In this study,7 metals(Pb,Hg,Cd,As,Zn,Cu and Se)and the river water quality parameters including pH,dissolved oxygen(DO),Escherichia coli(E.coli),potassium permanganate index(CODMn),dichromate oxidizability(CODCr),five-day biochemical oxygen demand(BOD5),ammonia nitrogen(NH4+-N),total nitrogen(TN),total phosphorus(TP)and fluoride(F)in 18 sampling sites of the Changsha-Xiangtan-Zhuzhou section are monthly monitored in 2016,which is the year to step into the second stage of the“Xiangjiang River Heavy Metal Pollution Control Implementation Plan”.It is found that E.coli,TN and TP are the main pollutants in the Changsha-Zhuzhou-Xiangtan section,and the pollution of heavy metal is not serious but As with potential risk to local people especially children should be concerned.In addition,Xiangtan city is mainly featured with heavy metal pollution,while Zhuzhou and Changsha city are both featured with other pollutants from municipal domestic sewage.展开更多
The purpose of this research was to better understand the water quality status of the Xiangjiang River, China, and to evaluate the risks posed by the river water. Precisely, ten water quality parameters including p H,...The purpose of this research was to better understand the water quality status of the Xiangjiang River, China, and to evaluate the risks posed by the river water. Precisely, ten water quality parameters including p H, dissolved oxygen(DO), Escherichia coli(E. coli), potassium permanganate index(CODMn), dichromate oxidizability(CODCr), five-day biochemical oxygen demand(BOD5), ammonia nitrogen(NH4+-N), total phosphorus(TP) and fluoride(F-) as well as metal(loid)s(Pb, Hg, Cd, As, Zn, Cu and Se) were monitored monthly in 2016 at 12 sampling sites throughout the Hengyang section of the Xiangjiang River. Concentrations of all parameters were presented according to rainy and dry seasons. They were compared with Chinese surface water standards and WHO drinking water limits to assess the sustainability of the river water status. Principal component analysis(PCA) revealed different pollution sources in different seasons. Dual hierarchical cluster analysis(DHCA) was applied to further classify the water quality variables and sampling sites. Besides, a risk assessment was introduced to evaluate the carcinogenic and non-carcinogenic concerns of heavy metal(loid)s to human health. This research will help to optimize water monitoring locations and establish pollution reduction strategies on the preservation of public safety.展开更多
Multivariate statistical techniques,such as cluster analysis(CA),discriminant analysis(DA),principal component analysis(PCA) and factor analysis(FA),were applied to evaluate and interpret the surface water quality dat...Multivariate statistical techniques,such as cluster analysis(CA),discriminant analysis(DA),principal component analysis(PCA) and factor analysis(FA),were applied to evaluate and interpret the surface water quality data sets of the Second Songhua River(SSHR) basin in China,obtained during two years(2012-2013) of monitoring of 10 physicochemical parameters at 15 different sites.The results showed that most of physicochemical parameters varied significantly among the sampling sites.Three significant groups,highly polluted(HP),moderately polluted(MP) and less polluted(LP),of sampling sites were obtained through Hierarchical agglomerative CA on the basis of similarity of water quality characteristics.DA identified p H,F,DO,NH3-N,COD and VPhs were the most important parameters contributing to spatial variations of surface water quality.However,DA did not give a considerable data reduction(40% reduction).PCA/FA resulted in three,three and four latent factors explaining 70%,62% and 71% of the total variance in water quality data sets of HP,MP and LP regions,respectively.FA revealed that the SSHR water chemistry was strongly affected by anthropogenic activities(point sources:industrial effluents and wastewater treatment plants;non-point sources:domestic sewage,livestock operations and agricultural activities) and natural processes(seasonal effect,and natural inputs).PCA/FA in the whole basin showed the best results for data reduction because it used only two parameters(about 80% reduction) as the most important parameters to explain 72% of the data variation.Thus,this work illustrated the utility of multivariate statistical techniques for analysis and interpretation of datasets and,in water quality assessment,identification of pollution sources/factors and understanding spatial variations in water quality for effective stream water quality management.展开更多
To develop a better approach for spatial evaluation of drinking water quality, an intelligent evaluation method integrating a geographical information system(GIS) and an ant colony clustering algorithm(ACCA) was used....To develop a better approach for spatial evaluation of drinking water quality, an intelligent evaluation method integrating a geographical information system(GIS) and an ant colony clustering algorithm(ACCA) was used. Drinking water samples from 29 wells in Zhenping County, China, were collected and analyzed. 35 parameters on water quality were selected, such as chloride concentration, sulphate concentration, total hardness, nitrate concentration, fluoride concentration, turbidity, pH, chromium concentration, COD, bacterium amount, total coliforms and color. The best spatial interpolation methods for the 35 parameters were found and selected from all types of interpolation methods in GIS environment according to the minimum cross-validation errors. The ACCA was improved through three strategies, namely mixed distance function, average similitude degree and probability conversion functions. Then, the ACCA was carried out to obtain different water quality grades in the GIS environment. In the end, the result from the ACCA was compared with those from the competitive Hopfield neural network(CHNN) to validate the feasibility and effectiveness of the ACCA according to three evaluation indexes, which are stochastic sampling method, pixel amount and convergence speed. It is shown that the spatial water quality grades obtained from the ACCA were more effective, accurate and intelligent than those obtained from the CHNN.展开更多
A knowledge-based network for Section Yidong Bridge,Dongyang River,one tributary of Qiantang River,Zhejiang Province,China,is established in order to model water quality in areas under small data.Then,based on normal ...A knowledge-based network for Section Yidong Bridge,Dongyang River,one tributary of Qiantang River,Zhejiang Province,China,is established in order to model water quality in areas under small data.Then,based on normal transformation of variables with routine monitoring data and normal assumption of variables without routine monitoring data,a conditional linear Gaussian Bayesian network is constructed.A "two-constraint selection" procedure is proposed to estimate potential parameter values under small data.Among all potential parameter values,the ones that are most probable are selected as the "representatives".Finally,the risks of pollutant concentration exceeding national water quality standards are calculated and pollution reduction decisions for decision-making reference are proposed.The final results show that conditional linear Gaussian Bayesian network and "two-constraint selection" procedure are very useful in evaluating risks when there is limited data and can help managers to make sound decisions under small data.展开更多
In order to evaluate the quality of water environment, the conception of entropy is applied in information science, and the entropy weight model is built to evaluate comprehensively water quality. The indexes weights ...In order to evaluate the quality of water environment, the conception of entropy is applied in information science, and the entropy weight model is built to evaluate comprehensively water quality. The indexes weights of water quality are determined by value of entropy. This kind of method is applied on evaluating water quality in the new water to be built. The result shows that the water quality in it which supply water is between grade Ⅲ and Ⅳ, and the result is similar to that of gray related method.展开更多
Assessment of temporal and spatial variations in surface water quality is important to evaluate the health of a watershed and make necessary management decisions to control current and future pollution of receiving wa...Assessment of temporal and spatial variations in surface water quality is important to evaluate the health of a watershed and make necessary management decisions to control current and future pollution of receiving water bodies. In this work, surface water quality data for 12 physical and chemical parameters collected from 10 sampling sites in the Nenjiang River basin during the years(2012-2013) were analyzed. The results show that river water quality has significant temporal and spatial variations. Hierarchical cluster analysis(HCA) grouped 12 months into three periods(LF, MF and HF) and classified 10 monitoring sites into three regions(LP, MP and HP) based on the similarity of water quality characteristics. The principle component analysis(PCA)/factor analysis(FA) was used to recognize the factors or origins responsible for temporal and spatial water quality variations. Temporal and spatial PCA/FA revealed that the Nenjiang River water chemistry was strongly affected by rock/water interaction, hydrologic processes and anthropogenic activities. This work demonstrates that the application of HCA and PCA/FA has achieved meaningful classification based on temporal and spatial criteria.展开更多
The present study is aimed at calculating domestic solid waste water in Sari city,Mazandaran.Solid waste management mainly involves management of activities that are engineering oriented such as waste generation,stora...The present study is aimed at calculating domestic solid waste water in Sari city,Mazandaran.Solid waste management mainly involves management of activities that are engineering oriented such as waste generation,storage,collection,transportation,operation of processing and disposal facilities.A small composting unit is suggested for the composting of solid waste in community or colony level so that the community committee itself can maintain the composting unit.The study is to analyze the solid waste disposal system and suggest suitable modification in the present system to improve the展开更多
Tank Cascade Systems(TCS)are the back bone of the dry zone prosperity in Sri Lanka and supply water throughout the year to agricultural lands since the 2nd century BC.The main aim of this study was to understand the n...Tank Cascade Systems(TCS)are the back bone of the dry zone prosperity in Sri Lanka and supply water throughout the year to agricultural lands since the 2nd century BC.The main aim of this study was to understand the nutrient dynamics of small TCS and find out evidence for the sustainability of the system for thousands of years.Malagane tank cascade in the Deduru Oya Basin(the 5th largest river basin展开更多
Water Quality Model System( WQMS) is an important approach to analyzing aquatic situation and supporting environmental decision. However,the usage and promotion of WQMS is largely limited by amounts of parameters,comp...Water Quality Model System( WQMS) is an important approach to analyzing aquatic situation and supporting environmental decision. However,the usage and promotion of WQMS is largely limited by amounts of parameters,complex conditions and enormous operations. A GIS integrated system of urban water environment coupled with SWMM( storm runoff model),ECOM( hydrodynamic model) and RCA( water quality model) was constructed in this study,with the production and transformation of contaminants in large scale taken into consideration. This integrated system guaranteed an independent calculation and multi-model coupling calculation,including convenient pre-processing,fast and efficient model running and results visualization in different spatial and temporal scales,in the purpose of simplifying the usage and promotion of complex models and providing necessary understanding required in water resource managing and water pollution controlling,and ultimately improving decision making capability. The functionality of the proposed system was illustrated by a case of Wuhan city.展开更多
Projection Pursuit (PP) model is a technique of falling high dimension. Real coding based on Accelerating Genetic Algorithm (RAGA) is a method of optimum. Through combining the PP model and RAGA, the paper applies the...Projection Pursuit (PP) model is a technique of falling high dimension. Real coding based on Accelerating Genetic Algorithm (RAGA) is a method of optimum. Through combining the PP model and RAGA, the paper applies the model in the water environment quality evaluation. The writer takes the water quality evaluated indexes of each sample as projection direction and turns high dimension data into low dimension projection value. Thus, the writer achieves on evaluating the grade of water samples and its optimum order. Based on this, the writer overcomes the jamming of weights calculated on fuzzy synthesize judge and gray system valuation. The paper can provide a new thought for water environment quality evaluation and other falling high dimension and optimum issue.展开更多
Chaos theory was introduced for water quality, prediction, and the model of water quality prediction was established by combining phase space reconstruction theory and BP neural network forecasting method. Through the...Chaos theory was introduced for water quality, prediction, and the model of water quality prediction was established by combining phase space reconstruction theory and BP neural network forecasting method. Through the phase space reconstruction, the one-dimensional water quality time series were mapped to be multi-dimensional sequence, which enriched the spatial information of water quality change and expanded mapping region of training samples of BP neural network. Established model of combining chaos theory and BP neural network were applied to forecast turbidity time series of a certain reservoir. Contrast to BP neural network method, the relative error and the mean squared error of the combined method had all varying degrees of lower. Results indicated the neural network model with chaos theory had the higher prediction accuracy, at the same time, it had better fault-tolerant capability and generalization performance .展开更多
Background Water deficit is an important problem in agricultural production in arid regions.With the advent of wholly mechanized technology for cotton planting in Xinjiang,it is important to determine which planting m...Background Water deficit is an important problem in agricultural production in arid regions.With the advent of wholly mechanized technology for cotton planting in Xinjiang,it is important to determine which planting mode could achieve high yield,fiber quality and water use efficiency(WUE).This study aimed to explore if chemical topping affected cotton yield,quality and water use in relation to row configuration and plant densities.Results Experiments were carried out in Xinjiang China,in 2020 and 2021 with two topping method,manual topping and chemical topping,two plant densities,low and high,and two row configurations,i.e.,76 cm equal rows and 10+66 cm narrow-wide rows,which were commonly applied in matching harvest machine.Chemical topping increased seed cotton yield,but did not affect cotton fiber quality comparing to traditional manual topping.Under equal row spacing,the WUE in higher density was 62.4%higher than in the lower one.However,under narrow-wide row spacing,the WUE in lower density was 53.3%higher than in higher one(farmers’practice).For machine-harvest cotton in Xinjiang,the optimal row configuration and plant density for chemical topping was narrow-wide rows with 15 plants m-2 or equal rows with 18 plants m-2.Conclusion The plant density recommended in narrow-wide rows was less than farmers’practice and the density in equal rows was moderate with local practice.Our results provide new knowledge on optimizing agronomic managements of machine-harvested cotton for both high yield and water efficient.展开更多
During the storage of water and the initial running of a reservoir, part of the dissolved nutrients released from the soil in water will effect water quality. Taking Qinglongshan Reservoir as an example, estimating th...During the storage of water and the initial running of a reservoir, part of the dissolved nutrients released from the soil in water will effect water quality. Taking Qinglongshan Reservoir as an example, estimating the value of the contribution of dissolved nutrients to the water quality and analyzing the trend or level of the dissolved nutrients effecting on the water quality under the soil nutrient inquiring, the soil nutrient monitoring, and the dissolving experiment of nutrients released from soil, also according to the capacity curve of Qinglongshan Reservoir.展开更多
基金Projects(2018YFC1903301,2018YFC1801805)supported by the National Key R&D Program of China
文摘The Changsha-Xiangtan-Zhuzhou City Group is a heavy industrial district and accepted as the serious pollution area in the Xiangjiang River basin.In this study,7 metals(Pb,Hg,Cd,As,Zn,Cu and Se)and the river water quality parameters including pH,dissolved oxygen(DO),Escherichia coli(E.coli),potassium permanganate index(CODMn),dichromate oxidizability(CODCr),five-day biochemical oxygen demand(BOD5),ammonia nitrogen(NH4+-N),total nitrogen(TN),total phosphorus(TP)and fluoride(F)in 18 sampling sites of the Changsha-Xiangtan-Zhuzhou section are monthly monitored in 2016,which is the year to step into the second stage of the“Xiangjiang River Heavy Metal Pollution Control Implementation Plan”.It is found that E.coli,TN and TP are the main pollutants in the Changsha-Zhuzhou-Xiangtan section,and the pollution of heavy metal is not serious but As with potential risk to local people especially children should be concerned.In addition,Xiangtan city is mainly featured with heavy metal pollution,while Zhuzhou and Changsha city are both featured with other pollutants from municipal domestic sewage.
基金Projects(2018YFC1801805,2018YFC1903301)supported by National Key R&D Program of ChinaProject(51825403)supported by National Science Fund for Distinguished Young Scholars,ChinaProject(2019SK2281)supported by Key R&D Program of Hunan Province,China。
文摘The purpose of this research was to better understand the water quality status of the Xiangjiang River, China, and to evaluate the risks posed by the river water. Precisely, ten water quality parameters including p H, dissolved oxygen(DO), Escherichia coli(E. coli), potassium permanganate index(CODMn), dichromate oxidizability(CODCr), five-day biochemical oxygen demand(BOD5), ammonia nitrogen(NH4+-N), total phosphorus(TP) and fluoride(F-) as well as metal(loid)s(Pb, Hg, Cd, As, Zn, Cu and Se) were monitored monthly in 2016 at 12 sampling sites throughout the Hengyang section of the Xiangjiang River. Concentrations of all parameters were presented according to rainy and dry seasons. They were compared with Chinese surface water standards and WHO drinking water limits to assess the sustainability of the river water status. Principal component analysis(PCA) revealed different pollution sources in different seasons. Dual hierarchical cluster analysis(DHCA) was applied to further classify the water quality variables and sampling sites. Besides, a risk assessment was introduced to evaluate the carcinogenic and non-carcinogenic concerns of heavy metal(loid)s to human health. This research will help to optimize water monitoring locations and establish pollution reduction strategies on the preservation of public safety.
基金Project (2012ZX07501002-001) supported by the Ministry of Science and Technology of China
文摘Multivariate statistical techniques,such as cluster analysis(CA),discriminant analysis(DA),principal component analysis(PCA) and factor analysis(FA),were applied to evaluate and interpret the surface water quality data sets of the Second Songhua River(SSHR) basin in China,obtained during two years(2012-2013) of monitoring of 10 physicochemical parameters at 15 different sites.The results showed that most of physicochemical parameters varied significantly among the sampling sites.Three significant groups,highly polluted(HP),moderately polluted(MP) and less polluted(LP),of sampling sites were obtained through Hierarchical agglomerative CA on the basis of similarity of water quality characteristics.DA identified p H,F,DO,NH3-N,COD and VPhs were the most important parameters contributing to spatial variations of surface water quality.However,DA did not give a considerable data reduction(40% reduction).PCA/FA resulted in three,three and four latent factors explaining 70%,62% and 71% of the total variance in water quality data sets of HP,MP and LP regions,respectively.FA revealed that the SSHR water chemistry was strongly affected by anthropogenic activities(point sources:industrial effluents and wastewater treatment plants;non-point sources:domestic sewage,livestock operations and agricultural activities) and natural processes(seasonal effect,and natural inputs).PCA/FA in the whole basin showed the best results for data reduction because it used only two parameters(about 80% reduction) as the most important parameters to explain 72% of the data variation.Thus,this work illustrated the utility of multivariate statistical techniques for analysis and interpretation of datasets and,in water quality assessment,identification of pollution sources/factors and understanding spatial variations in water quality for effective stream water quality management.
基金Projects(41161020,41261026) supported by the National Natural Science Foundation of ChinaProject(BQD2012013) supported by the Research starting Funds for Imported Talents,Ningxia University,China+1 种基金Project(ZR1209) supported by the Natural Science Funds,Ningxia University,ChinaProject(NGY2013005) supported by the Key Science Project of Colleges and Universities in Ningxia,China
文摘To develop a better approach for spatial evaluation of drinking water quality, an intelligent evaluation method integrating a geographical information system(GIS) and an ant colony clustering algorithm(ACCA) was used. Drinking water samples from 29 wells in Zhenping County, China, were collected and analyzed. 35 parameters on water quality were selected, such as chloride concentration, sulphate concentration, total hardness, nitrate concentration, fluoride concentration, turbidity, pH, chromium concentration, COD, bacterium amount, total coliforms and color. The best spatial interpolation methods for the 35 parameters were found and selected from all types of interpolation methods in GIS environment according to the minimum cross-validation errors. The ACCA was improved through three strategies, namely mixed distance function, average similitude degree and probability conversion functions. Then, the ACCA was carried out to obtain different water quality grades in the GIS environment. In the end, the result from the ACCA was compared with those from the competitive Hopfield neural network(CHNN) to validate the feasibility and effectiveness of the ACCA according to three evaluation indexes, which are stochastic sampling method, pixel amount and convergence speed. It is shown that the spatial water quality grades obtained from the ACCA were more effective, accurate and intelligent than those obtained from the CHNN.
基金Project(50809058)supported by the National Natural Science Foundation of China
文摘A knowledge-based network for Section Yidong Bridge,Dongyang River,one tributary of Qiantang River,Zhejiang Province,China,is established in order to model water quality in areas under small data.Then,based on normal transformation of variables with routine monitoring data and normal assumption of variables without routine monitoring data,a conditional linear Gaussian Bayesian network is constructed.A "two-constraint selection" procedure is proposed to estimate potential parameter values under small data.Among all potential parameter values,the ones that are most probable are selected as the "representatives".Finally,the risks of pollutant concentration exceeding national water quality standards are calculated and pollution reduction decisions for decision-making reference are proposed.The final results show that conditional linear Gaussian Bayesian network and "two-constraint selection" procedure are very useful in evaluating risks when there is limited data and can help managers to make sound decisions under small data.
文摘In order to evaluate the quality of water environment, the conception of entropy is applied in information science, and the entropy weight model is built to evaluate comprehensively water quality. The indexes weights of water quality are determined by value of entropy. This kind of method is applied on evaluating water quality in the new water to be built. The result shows that the water quality in it which supply water is between grade Ⅲ and Ⅳ, and the result is similar to that of gray related method.
基金Project(2012ZX07501002-001)supported by Major Science and Technology Program for Water Pollution Control and Treatment of the Ministry of Science and Technology,China
文摘Assessment of temporal and spatial variations in surface water quality is important to evaluate the health of a watershed and make necessary management decisions to control current and future pollution of receiving water bodies. In this work, surface water quality data for 12 physical and chemical parameters collected from 10 sampling sites in the Nenjiang River basin during the years(2012-2013) were analyzed. The results show that river water quality has significant temporal and spatial variations. Hierarchical cluster analysis(HCA) grouped 12 months into three periods(LF, MF and HF) and classified 10 monitoring sites into three regions(LP, MP and HP) based on the similarity of water quality characteristics. The principle component analysis(PCA)/factor analysis(FA) was used to recognize the factors or origins responsible for temporal and spatial water quality variations. Temporal and spatial PCA/FA revealed that the Nenjiang River water chemistry was strongly affected by rock/water interaction, hydrologic processes and anthropogenic activities. This work demonstrates that the application of HCA and PCA/FA has achieved meaningful classification based on temporal and spatial criteria.
文摘The present study is aimed at calculating domestic solid waste water in Sari city,Mazandaran.Solid waste management mainly involves management of activities that are engineering oriented such as waste generation,storage,collection,transportation,operation of processing and disposal facilities.A small composting unit is suggested for the composting of solid waste in community or colony level so that the community committee itself can maintain the composting unit.The study is to analyze the solid waste disposal system and suggest suitable modification in the present system to improve the
文摘Tank Cascade Systems(TCS)are the back bone of the dry zone prosperity in Sri Lanka and supply water throughout the year to agricultural lands since the 2nd century BC.The main aim of this study was to understand the nutrient dynamics of small TCS and find out evidence for the sustainability of the system for thousands of years.Malagane tank cascade in the Deduru Oya Basin(the 5th largest river basin
基金Science and Technology Program of the Ministry of Housing and Urban-Rural Development(2015-K8-009)
文摘Water Quality Model System( WQMS) is an important approach to analyzing aquatic situation and supporting environmental decision. However,the usage and promotion of WQMS is largely limited by amounts of parameters,complex conditions and enormous operations. A GIS integrated system of urban water environment coupled with SWMM( storm runoff model),ECOM( hydrodynamic model) and RCA( water quality model) was constructed in this study,with the production and transformation of contaminants in large scale taken into consideration. This integrated system guaranteed an independent calculation and multi-model coupling calculation,including convenient pre-processing,fast and efficient model running and results visualization in different spatial and temporal scales,in the purpose of simplifying the usage and promotion of complex models and providing necessary understanding required in water resource managing and water pollution controlling,and ultimately improving decision making capability. The functionality of the proposed system was illustrated by a case of Wuhan city.
文摘Projection Pursuit (PP) model is a technique of falling high dimension. Real coding based on Accelerating Genetic Algorithm (RAGA) is a method of optimum. Through combining the PP model and RAGA, the paper applies the model in the water environment quality evaluation. The writer takes the water quality evaluated indexes of each sample as projection direction and turns high dimension data into low dimension projection value. Thus, the writer achieves on evaluating the grade of water samples and its optimum order. Based on this, the writer overcomes the jamming of weights calculated on fuzzy synthesize judge and gray system valuation. The paper can provide a new thought for water environment quality evaluation and other falling high dimension and optimum issue.
文摘Chaos theory was introduced for water quality, prediction, and the model of water quality prediction was established by combining phase space reconstruction theory and BP neural network forecasting method. Through the phase space reconstruction, the one-dimensional water quality time series were mapped to be multi-dimensional sequence, which enriched the spatial information of water quality change and expanded mapping region of training samples of BP neural network. Established model of combining chaos theory and BP neural network were applied to forecast turbidity time series of a certain reservoir. Contrast to BP neural network method, the relative error and the mean squared error of the combined method had all varying degrees of lower. Results indicated the neural network model with chaos theory had the higher prediction accuracy, at the same time, it had better fault-tolerant capability and generalization performance .
基金Key Research and Development Program of Xinjiang(2022B02001-1)National Natural Science Foundation of China(42105172,41975146).
文摘Background Water deficit is an important problem in agricultural production in arid regions.With the advent of wholly mechanized technology for cotton planting in Xinjiang,it is important to determine which planting mode could achieve high yield,fiber quality and water use efficiency(WUE).This study aimed to explore if chemical topping affected cotton yield,quality and water use in relation to row configuration and plant densities.Results Experiments were carried out in Xinjiang China,in 2020 and 2021 with two topping method,manual topping and chemical topping,two plant densities,low and high,and two row configurations,i.e.,76 cm equal rows and 10+66 cm narrow-wide rows,which were commonly applied in matching harvest machine.Chemical topping increased seed cotton yield,but did not affect cotton fiber quality comparing to traditional manual topping.Under equal row spacing,the WUE in higher density was 62.4%higher than in the lower one.However,under narrow-wide row spacing,the WUE in lower density was 53.3%higher than in higher one(farmers’practice).For machine-harvest cotton in Xinjiang,the optimal row configuration and plant density for chemical topping was narrow-wide rows with 15 plants m-2 or equal rows with 18 plants m-2.Conclusion The plant density recommended in narrow-wide rows was less than farmers’practice and the density in equal rows was moderate with local practice.Our results provide new knowledge on optimizing agronomic managements of machine-harvested cotton for both high yield and water efficient.
文摘During the storage of water and the initial running of a reservoir, part of the dissolved nutrients released from the soil in water will effect water quality. Taking Qinglongshan Reservoir as an example, estimating the value of the contribution of dissolved nutrients to the water quality and analyzing the trend or level of the dissolved nutrients effecting on the water quality under the soil nutrient inquiring, the soil nutrient monitoring, and the dissolving experiment of nutrients released from soil, also according to the capacity curve of Qinglongshan Reservoir.
