Characterizing the river water quality in China: Recent progress and on-going challenges

•Patterns and drivers of China's river water quality during 2003–2018 were characterized.•Total phosphorus and ammonia are collectively responsible for >85% of poor water quality.•Water quality impairments are predominantly shaped by anthropogenic drivers (>75%).•Bayesian model is robust...

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Vydané v:	Water research (Oxford) Ročník 201; s. 117309
Hlavní autori:	Huang, Jiacong, Zhang, Yinjun, Bing, Haijian, Peng, Jian, Dong, Feifei, Gao, Junfeng, Arhonditsis, George B.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.08.2021
Predmet:	ammonium nitrogen Bayesian modelling Bayesian theory China data collection Eutrophication food production heavy metals landscapes light intensity nonpoint source pollution riparian areas river water River water quality rivers surface water total phosphorus Urbanization water quality Watershed management watersheds China River water quality Urbanization Watershed management Bayesian modelling Eutrophication
ISSN:	0043-1354, 1879-2448, 1879-2448
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Abstract	•Patterns and drivers of China's river water quality during 2003–2018 were characterized.•Total phosphorus and ammonia are collectively responsible for >85% of poor water quality.•Water quality impairments are predominantly shaped by anthropogenic drivers (>75%).•Bayesian model is robust in linking river water quality and watershed landscape characteristics. Food production systems, urbanization, and other anthropogenic activities dramatically alter natural hydrological and nutrient cycles, and are primarily responsible for water quality impairments in China's rivers. This study compiled a 16-year (2003–2018) dataset of river water quality (161,337 records from 2424 sites), watershed/landscape features, and meteorological conditions to investigate the spatial water quality patterns and underlying drivers of river impairment (defined as water quality worse than Class V according to China's Environmental Quality Standards for Surface Waters, GB3838-2002) at a national scale. Our analysis provided evidence of a distinct water quality improvement with a gradual decrease in the frequency of prevalence of anoxic conditions, an alleviation of the severity of heavy metal pollution, whereas the cultural eutrophication has only been moderately mitigated between 2003 and 2018. We also identified significant spatial variation with relatively poorer water quality in eastern China, where 17.2% of the sampling sites registered poor water quality conditions, compared with only 4.6% in western China. Total phosphorus (TP) and ammonia-nitrogen (NH3-N) are collectively responsible for >85% of the identified incidences of impaired conditions. Bayesian modelling was used to delineate the most significant covariates of TP/NH3-N riverine levels in six large river basins (Liao, Hai, Yellow, Yangtze, Huai, and Pearl). Water quality impairments are predominantly shaped by anthropogenic drivers (82.5% for TP, 79.5% for NH3-N), whereas natural factors appear to play a secondary role (20.5% for TP, 17.5% for NH3-N). Two indicator variables of urbanization (urban areal extent and nighttime light intensity) and farmland areal extent were the strongest predictors of riverine TP/NH3-N levels and collectively accounted for most of the ambient nutrient variability. We concluded that there is still a long way to go in order to eradicate eutrophication and realize acceptable ecological conditions. The design of the remedial measures must be tailored to the site-specific landscape characteristics, meteorological conditions, and should also consider the increasing importance of non-point source pollution and internal nutrient loading. [Display omitted]
AbstractList	Food production systems, urbanization, and other anthropogenic activities dramatically alter natural hydrological and nutrient cycles, and are primarily responsible for water quality impairments in China's rivers. This study compiled a 16-year (2003-2018) dataset of river water quality (161,337 records from 2424 sites), watershed/landscape features, and meteorological conditions to investigate the spatial water quality patterns and underlying drivers of river impairment (defined as water quality worse than Class V according to China's Environmental Quality Standards for Surface Waters, GB3838-2002) at a national scale. Our analysis provided evidence of a distinct water quality improvement with a gradual decrease in the frequency of prevalence of anoxic conditions, an alleviation of the severity of heavy metal pollution, whereas the cultural eutrophication has only been moderately mitigated between 2003 and 2018. We also identified significant spatial variation with relatively poorer water quality in eastern China, where 17.2% of the sampling sites registered poor water quality conditions, compared with only 4.6% in western China. Total phosphorus (TP) and ammonia-nitrogen (NH3-N) are collectively responsible for >85% of the identified incidences of impaired conditions. Bayesian modelling was used to delineate the most significant covariates of TP/NH3-N riverine levels in six large river basins (Liao, Hai, Yellow, Yangtze, Huai, and Pearl). Water quality impairments are predominantly shaped by anthropogenic drivers (82.5% for TP, 79.5% for NH3-N), whereas natural factors appear to play a secondary role (20.5% for TP, 17.5% for NH3-N). Two indicator variables of urbanization (urban areal extent and nighttime light intensity) and farmland areal extent were the strongest predictors of riverine TP/NH3-N levels and collectively accounted for most of the ambient nutrient variability. We concluded that there is still a long way to go in order to eradicate eutrophication and realize acceptable ecological conditions. The design of the remedial measures must be tailored to the site-specific landscape characteristics, meteorological conditions, and should also consider the increasing importance of non-point source pollution and internal nutrient loading.Food production systems, urbanization, and other anthropogenic activities dramatically alter natural hydrological and nutrient cycles, and are primarily responsible for water quality impairments in China's rivers. This study compiled a 16-year (2003-2018) dataset of river water quality (161,337 records from 2424 sites), watershed/landscape features, and meteorological conditions to investigate the spatial water quality patterns and underlying drivers of river impairment (defined as water quality worse than Class V according to China's Environmental Quality Standards for Surface Waters, GB3838-2002) at a national scale. Our analysis provided evidence of a distinct water quality improvement with a gradual decrease in the frequency of prevalence of anoxic conditions, an alleviation of the severity of heavy metal pollution, whereas the cultural eutrophication has only been moderately mitigated between 2003 and 2018. We also identified significant spatial variation with relatively poorer water quality in eastern China, where 17.2% of the sampling sites registered poor water quality conditions, compared with only 4.6% in western China. Total phosphorus (TP) and ammonia-nitrogen (NH3-N) are collectively responsible for >85% of the identified incidences of impaired conditions. Bayesian modelling was used to delineate the most significant covariates of TP/NH3-N riverine levels in six large river basins (Liao, Hai, Yellow, Yangtze, Huai, and Pearl). Water quality impairments are predominantly shaped by anthropogenic drivers (82.5% for TP, 79.5% for NH3-N), whereas natural factors appear to play a secondary role (20.5% for TP, 17.5% for NH3-N). Two indicator variables of urbanization (urban areal extent and nighttime light intensity) and farmland areal extent were the strongest predictors of riverine TP/NH3-N levels and collectively accounted for most of the ambient nutrient variability. We concluded that there is still a long way to go in order to eradicate eutrophication and realize acceptable ecological conditions. The design of the remedial measures must be tailored to the site-specific landscape characteristics, meteorological conditions, and should also consider the increasing importance of non-point source pollution and internal nutrient loading. Food production systems, urbanization, and other anthropogenic activities dramatically alter natural hydrological and nutrient cycles, and are primarily responsible for water quality impairments in China's rivers. This study compiled a 16-year (2003–2018) dataset of river water quality (161,337 records from 2424 sites), watershed/landscape features, and meteorological conditions to investigate the spatial water quality patterns and underlying drivers of river impairment (defined as water quality worse than Class V according to China's Environmental Quality Standards for Surface Waters, GB3838-2002) at a national scale. Our analysis provided evidence of a distinct water quality improvement with a gradual decrease in the frequency of prevalence of anoxic conditions, an alleviation of the severity of heavy metal pollution, whereas the cultural eutrophication has only been moderately mitigated between 2003 and 2018. We also identified significant spatial variation with relatively poorer water quality in eastern China, where 17.2% of the sampling sites registered poor water quality conditions, compared with only 4.6% in western China. Total phosphorus (TP) and ammonia-nitrogen (NH₃-N) are collectively responsible for >85% of the identified incidences of impaired conditions. Bayesian modelling was used to delineate the most significant covariates of TP/NH₃-N riverine levels in six large river basins (Liao, Hai, Yellow, Yangtze, Huai, and Pearl). Water quality impairments are predominantly shaped by anthropogenic drivers (82.5% for TP, 79.5% for NH₃-N), whereas natural factors appear to play a secondary role (20.5% for TP, 17.5% for NH₃-N). Two indicator variables of urbanization (urban areal extent and nighttime light intensity) and farmland areal extent were the strongest predictors of riverine TP/NH₃-N levels and collectively accounted for most of the ambient nutrient variability. We concluded that there is still a long way to go in order to eradicate eutrophication and realize acceptable ecological conditions. The design of the remedial measures must be tailored to the site-specific landscape characteristics, meteorological conditions, and should also consider the increasing importance of non-point source pollution and internal nutrient loading. •Patterns and drivers of China's river water quality during 2003–2018 were characterized.•Total phosphorus and ammonia are collectively responsible for >85% of poor water quality.•Water quality impairments are predominantly shaped by anthropogenic drivers (>75%).•Bayesian model is robust in linking river water quality and watershed landscape characteristics. Food production systems, urbanization, and other anthropogenic activities dramatically alter natural hydrological and nutrient cycles, and are primarily responsible for water quality impairments in China's rivers. This study compiled a 16-year (2003–2018) dataset of river water quality (161,337 records from 2424 sites), watershed/landscape features, and meteorological conditions to investigate the spatial water quality patterns and underlying drivers of river impairment (defined as water quality worse than Class V according to China's Environmental Quality Standards for Surface Waters, GB3838-2002) at a national scale. Our analysis provided evidence of a distinct water quality improvement with a gradual decrease in the frequency of prevalence of anoxic conditions, an alleviation of the severity of heavy metal pollution, whereas the cultural eutrophication has only been moderately mitigated between 2003 and 2018. We also identified significant spatial variation with relatively poorer water quality in eastern China, where 17.2% of the sampling sites registered poor water quality conditions, compared with only 4.6% in western China. Total phosphorus (TP) and ammonia-nitrogen (NH3-N) are collectively responsible for >85% of the identified incidences of impaired conditions. Bayesian modelling was used to delineate the most significant covariates of TP/NH3-N riverine levels in six large river basins (Liao, Hai, Yellow, Yangtze, Huai, and Pearl). Water quality impairments are predominantly shaped by anthropogenic drivers (82.5% for TP, 79.5% for NH3-N), whereas natural factors appear to play a secondary role (20.5% for TP, 17.5% for NH3-N). Two indicator variables of urbanization (urban areal extent and nighttime light intensity) and farmland areal extent were the strongest predictors of riverine TP/NH3-N levels and collectively accounted for most of the ambient nutrient variability. We concluded that there is still a long way to go in order to eradicate eutrophication and realize acceptable ecological conditions. The design of the remedial measures must be tailored to the site-specific landscape characteristics, meteorological conditions, and should also consider the increasing importance of non-point source pollution and internal nutrient loading. [Display omitted]
ArticleNumber	117309
Author	Zhang, Yinjun Bing, Haijian Dong, Feifei Arhonditsis, George B. Huang, Jiacong Gao, Junfeng Peng, Jian
Author_xml	– sequence: 1 givenname: Jiacong orcidid: 0000-0003-4296-5823 surname: Huang fullname: Huang, Jiacong email: jchuang@niglas.ac.cn organization: Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 73 East Beijing Road, Nanjing, 210008, China – sequence: 2 givenname: Yinjun surname: Zhang fullname: Zhang, Yinjun organization: China National Environmental Monitoring Centre, 8(B) Dayangfang Beiyuan Road, Chaoyang District, Beijing, 100012, China – sequence: 3 givenname: Haijian surname: Bing fullname: Bing, Haijian organization: Key Laboratory of Mountain Surface Process and Ecological Regulation, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, 9, Block 4, Renminnanlu Road, Chengdu, 610041, China – sequence: 4 givenname: Jian surname: Peng fullname: Peng, Jian organization: Department of Remote Sensing, Helmholtz Centre for Environmental Research−UFZ, Permoserstrasse 15, 04318, Leipzig, Germany – sequence: 5 givenname: Feifei surname: Dong fullname: Dong, Feifei organization: Institute of Groundwater and Earth Sciences, Jinan University, 601 Huangpu Avenue, Guangzhou, 510630, China – sequence: 6 givenname: Junfeng surname: Gao fullname: Gao, Junfeng organization: Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 73 East Beijing Road, Nanjing, 210008, China – sequence: 7 givenname: George B. orcidid: 0000-0001-5359-8737 surname: Arhonditsis fullname: Arhonditsis, George B. email: george.arhonditsis@utoronto.ca organization: Ecological Modelling Laboratory, Department of Physical & Environmental Sciences, University of Toronto, Toronto, ON, M1C 1A4, Canada
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Snippet	•Patterns and drivers of China's river water quality during 2003–2018 were characterized.•Total phosphorus and ammonia are collectively responsible for >85% of... Food production systems, urbanization, and other anthropogenic activities dramatically alter natural hydrological and nutrient cycles, and are primarily...
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SubjectTerms	ammonium nitrogen Bayesian modelling Bayesian theory China data collection Eutrophication food production heavy metals landscapes light intensity nonpoint source pollution riparian areas river water River water quality rivers surface water total phosphorus Urbanization water quality Watershed management watersheds
Title	Characterizing the river water quality in China: Recent progress and on-going challenges
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