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Analysis of non-point and point source pollution in China - Case study in Shima watershed in Guangdong Province

  • Huaiyang Fang
  • , Qingshui Lu*
  • , Zhiqiang Gao
  • , Runhe Shi
  • , Wei Gao
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

China economy has been rapidly increased since 1978. Rapid economic growth led to fast growth of fertilizer and pesticide consumption. A significant portion of fertilizers and pesticides entered the water and caused water quality degradation. At the same time, rapid economic growth also caused more and more point source pollution discharge into the water. Eutrophication has become a major threat to the water bodies. Worsening environment problems forced governments to take measures to control water pollution. We extracted land cover from Landsat TM images; calculated point source pollution with export coefficient method; then SWAT model was run to simulate non-point source pollution. We found that the annual TP loads from industry pollution into rivers are 115.0 t in the entire watershed. Average annual TP loads from each sub-basin ranged from 0 to 189.4 ton. Higher TP loads of each basin from livestock and human living mainly occurs in the areas where they are far from large towns or cities and the TP loads from industry are relatively low. Mean annual TP loads that delivered to the streams was 246.4 tons and the highest TP loads occurred in north part of this area, and the lowest TP loads is mainly distributed in middle part. Therefore, point source pollution has much high proportion in this area and governments should take measures to control point source pollution.

Original languageEnglish
Title of host publicationRemote Sensing and Modeling of Ecosystems for Sustainability X
PublisherSPIE
ISBN (Print)9780819497192
DOIs
StatePublished - 2013
Externally publishedYes
EventRemote Sensing and Modeling of Ecosystems for Sustainability X - San Diego, CA, United States
Duration: 26 Aug 201329 Aug 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8869
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceRemote Sensing and Modeling of Ecosystems for Sustainability X
Country/TerritoryUnited States
CitySan Diego, CA
Period26/08/1329/08/13

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 2 - Zero Hunger
    SDG 2 Zero Hunger
  2. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  3. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Dongjiang watershed
  • LUCC
  • non-point pollution
  • point pollution

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