Assessment of Water Quality and Identification of Polluted Risky Regions Based on Field Observations & GIS in the Honghe River Watershed, China

被引:66
|
作者
Yan, Chang-An [1 ,2 ]
Zhang, Wanchang [3 ]
Zhang, Zhijie [4 ]
Liu, Yuanmin [1 ,3 ]
Deng, Cai [1 ,3 ]
Nie, Ning [1 ,3 ]
机构
[1] Nanjing Univ, Sch Environm, State Key Lab Pollut Control & Resource Reuse, Nanjing 210093, Jiangsu, Peoples R China
[2] Kunming Inst Environm Sci, Kunming 650032, Peoples R China
[3] Chinese Acad Sci, Inst Remote Sensing & Digital Earth RADI, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
[4] Nanjing Univ Posts & Telecommun, Coll Automat, Nanjing 210093, Jiangsu, Peoples R China
来源
PLOS ONE | 2015年 / 10卷 / 03期
基金
中国国家自然科学基金;
关键词
SYSTEMS; INDEX; BASIN; INDIA;
D O I
10.1371/journal.pone.0119130
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Water quality assessment at the watershed scale requires not only an investigation of water pollution and the recognition of main pollution factors, but also the identification of polluted risky regions resulted in polluted surrounding river sections. To realize this objective, we collected water samplings from 67 sampling sites in the Honghe River watershed of China with Grid GIS method to analyze six parameters including dissolved oxygen (DO), ammonia nitrogen (NH3-N), nitrate nitrogen (NO3-N), nitrite nitrogen (NO2-N), total nitrogen (TN) and total phosphorus (TP). Single factor pollution index and comprehensive pollution index were adopted to explore main water pollutants and evaluate water quality pollution level. Based on two evaluate methods, Geo-statistical analysis and Geographical Information System (GIS) were used to visualize the spatial pollution characteristics and identifying potential polluted risky regions. The results indicated that the general water quality in the watershed has been exposed to various pollutants, in which TP, NO2-N and TN were the main pollutants and seriously exceeded the standard of Category III. The zones of TP, TN, DO, NO2-N and NH3-N pollution covered 99.07%, 62.22%, 59.72%, 37.34% and 13.82% of the watershed respectively, and they were from medium to serious polluted. 83.27% of the watershed in total was polluted by comprehensive pollutants. These conclusions may provide useful and effective information for watershed water pollution control and management.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Evaluation of polluted urban river water quality: a case study of the Xunsi River watershed, China
    Zhou, Wei
    Zhang, Yizhe
    Yin, Jun
    Zhou, Jianan
    Wu, Zhonghua
    [J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (45) : 68035 - 68050
  • [2] Evaluation of polluted urban river water quality: a case study of the Xunsi River watershed, China
    Wei Zhou
    Yizhe Zhang
    Jun Yin
    Jianan Zhou
    Zhonghua Wu
    [J]. Environmental Science and Pollution Research, 2022, 29 : 68035 - 68050
  • [3] Assessment of Water Quality and Identification of Pollution Risk Locations in Tiaoxi River (Taihu Watershed), China
    Vadde, Kiran Kumar
    Wang, Jianjun
    Cao, Long
    Yuan, Tianma
    McCarthy, Alan J.
    Sekar, Raju
    [J]. WATER, 2018, 10 (02):
  • [4] The combined use of GIS and water quality indices for environmental assessment of Ouislane River watershed, Morocco
    Alitane, Abdennabi
    Essahlaoui, Ali
    Yimer, Estifanos Addisu
    Essahlaoui, Narjisse
    Chawanda, Celray James
    El Yousfi, Yassine
    Van Griensven, Ann
    [J]. EURO-MEDITERRANEAN JOURNAL FOR ENVIRONMENTAL INTEGRATION, 2024,
  • [5] GIS-Based Watershed Unit Forest Landscape Visual Quality Assessment in Yangshuo Section of Lijiang River Basin, China
    Dong, Shulong
    Ma, Jiangming
    Mo, Yanhua
    Yang, Hao
    [J]. SUSTAINABILITY, 2022, 14 (22)
  • [6] The Over Polluted Water Quality Assessment of Weihe River Based on Kernel Density Estimation
    Zhang, Z. M.
    Wang, X. Y.
    Zhang, Y.
    Nan, Z.
    Shen, B. G.
    [J]. 18TH BIENNIAL ISEM CONFERENCE ON ECOLOGICAL MODELLING FOR GLOBAL CHANGE AND COUPLED HUMAN AND NATURAL SYSTEM, 2012, 13 : 1271 - 1282
  • [7] Water quality assessment for Kaikong River (Xinjiang, China) based on multivariate statistical analysis and comprehensive water quality identification index
    State Key Laboratory of Eco-Hydraulic Engineering in Shanxi, Xi’an University of Technology, Xi’an
    Shanxi, China
    [J]. Intl. J. Earth Sci. Eng., 2 (590-596):
  • [8] Water quality index and GIS-based technique for assessment of groundwater quality in Wanaparthy watershed, Telangana, India
    Suantak Paolalsiam Vaiphei
    Rama Mohan Kurakalva
    Dinesh Kumar Sahadevan
    [J]. Environmental Science and Pollution Research, 2020, 27 : 45041 - 45062
  • [9] Water quality index and GIS-based technique for assessment of groundwater quality in Wanaparthy watershed, Telangana, India
    Vaiphei, Suantak Paolalsiam
    Kurakalva, Rama Mohan
    Sahadevan, Dinesh Kumar
    [J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2020, 27 (36) : 45041 - 45062
  • [10] River Health Assessment Method Based on Water Quality Indices for the Dagujia River in China
    Yi, Xuejun
    Shi, Yuhao
    Jiang, Long
    Fu, Changlu
    Xing, Yuzhen
    Yu, Zhongjiang
    [J]. FRONTIERS IN PHYSICS, 2022, 10