Selecting six indexs of pH, DO, COD, BOD5, ammonia nitrogen and petroleum hydrocarbons in Haihe River Basin of four seasons in 2012 - 2013 for factor analysis, appling Water Quality Pollution Index （API） to evaluate...Selecting six indexs of pH, DO, COD, BOD5, ammonia nitrogen and petroleum hydrocarbons in Haihe River Basin of four seasons in 2012 - 2013 for factor analysis, appling Water Quality Pollution Index （API） to evaluate DO, COD, BOD5 and ammonia nitrogen, aims for systematic evluation to water quality of Haihe River Basin The results showed that two stations of B J1 and HB2 were the 1V type of water, others were the V type; Water Quality Pollution Index （API） was 1.44, which illustrated Haihe River Basin in the state of contamination that the degree of pollution exceeded the standard of functional areas. Factor Analysis explained that between COD, DO and NH3-N were significant difference （P〈0.05）; principal component analysis showed that, in addition to pH and BOD5, the other indicators were above 0.70; the contribution rate of COD, DO, NH3-N and TPH were higher, petroleum hydrocarbons was 100%, it can be considered that the waters type of pollution was organic pollution, and petroleum hydrocarbon contamination was more prominent.展开更多
River water plays a key role in human health, and in social and economic development, and is often affected by both natural factors and human activities. An in-depth understanding of the role of these factors can help...River water plays a key role in human health, and in social and economic development, and is often affected by both natural factors and human activities. An in-depth understanding of the role of these factors can help in developing an effective catchment management strategy to protect precious water resources. This study analyzed river water quality, patterns of terrestrial and riparian ecosystems, intensity of agricultural activities, industrial structure, and spatial distribution of pollutant emissions in the Haihe River Basin in China for the year of 2010, identifying the variables that have the greatest impact on river water quality. The area percentage of farmland in study area, the percentage of natural vegetation cover in the 1000-m riparian zone, rural population density, industrial Gross Domestic Product(GDP)/km^2, and industrial amino nitrogen emissions were all significantly correlated with river water quality(P < 0.05). Farming had the largest impact on river water quality, explaining 43.0% of the water quality variance, followed by the coverage of natural vegetation in the 1000-m riparian zone, which explained 36.2% of the water quality variance. Industrial amino nitrogen emissions intensity and rural population density explained 31.6% and 31.4% of the water quality variance, respectively, while industrial GDP/km^2 explained 26.6%. Together, these five indicators explained 67.3% of the total variance in water quality. Consequently, water environmental management of the Haihe River Basin should focus on adjusting agricultural activities, conserving riparian vegetation, and reducing industrial pollutant emissions by optimizing industrial structure. The results demonstrate how human activities drive the spatial pattern changes of river water quality, and they can provide reference for developing land use guidelines and for prioritizing management practices to maintain stream water quality in a large river basin.展开更多
基金supported by the Key Laboratory of Marine Oil Spill Identification and Damage Assessment Technology, State Oceanic Administration (201214)
文摘Selecting six indexs of pH, DO, COD, BOD5, ammonia nitrogen and petroleum hydrocarbons in Haihe River Basin of four seasons in 2012 - 2013 for factor analysis, appling Water Quality Pollution Index （API） to evaluate DO, COD, BOD5 and ammonia nitrogen, aims for systematic evluation to water quality of Haihe River Basin The results showed that two stations of B J1 and HB2 were the 1V type of water, others were the V type; Water Quality Pollution Index （API） was 1.44, which illustrated Haihe River Basin in the state of contamination that the degree of pollution exceeded the standard of functional areas. Factor Analysis explained that between COD, DO and NH3-N were significant difference （P〈0.05）; principal component analysis showed that, in addition to pH and BOD5, the other indicators were above 0.70; the contribution rate of COD, DO, NH3-N and TPH were higher, petroleum hydrocarbons was 100%, it can be considered that the waters type of pollution was organic pollution, and petroleum hydrocarbon contamination was more prominent.
基金Under the auspices of National Natural Science Foundation of China(No.41371538)Independent Project of State Key Laboratory of Urban and Regional Ecology,Research Center for Eco-Environmental Sciences,Chinese Academy of Sciences(No.SKLURE2008-1-02)
文摘River water plays a key role in human health, and in social and economic development, and is often affected by both natural factors and human activities. An in-depth understanding of the role of these factors can help in developing an effective catchment management strategy to protect precious water resources. This study analyzed river water quality, patterns of terrestrial and riparian ecosystems, intensity of agricultural activities, industrial structure, and spatial distribution of pollutant emissions in the Haihe River Basin in China for the year of 2010, identifying the variables that have the greatest impact on river water quality. The area percentage of farmland in study area, the percentage of natural vegetation cover in the 1000-m riparian zone, rural population density, industrial Gross Domestic Product(GDP)/km^2, and industrial amino nitrogen emissions were all significantly correlated with river water quality(P < 0.05). Farming had the largest impact on river water quality, explaining 43.0% of the water quality variance, followed by the coverage of natural vegetation in the 1000-m riparian zone, which explained 36.2% of the water quality variance. Industrial amino nitrogen emissions intensity and rural population density explained 31.6% and 31.4% of the water quality variance, respectively, while industrial GDP/km^2 explained 26.6%. Together, these five indicators explained 67.3% of the total variance in water quality. Consequently, water environmental management of the Haihe River Basin should focus on adjusting agricultural activities, conserving riparian vegetation, and reducing industrial pollutant emissions by optimizing industrial structure. The results demonstrate how human activities drive the spatial pattern changes of river water quality, and they can provide reference for developing land use guidelines and for prioritizing management practices to maintain stream water quality in a large river basin.
