کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5751906 | 1619708 | 2017 | 14 صفحه PDF | دانلود رایگان |

- Water quality investigation by trained citizen scientists was integrated with land cover data.
- Water quality dynamics of the Huangpu River was characterized.
- Up-catchment conditions not land cover use dominated Huangpu River dynamics in high urbanized area of Shanghai City.
- FWW activities can assist in the design of efficient environmental strategies.
In recent years, the massive land use changes and urbanization of Shanghai City have coincided with a growing eutrophication and an overall degradation of Huangpu River, with related risks to the city's drinking water supply and economic development. However, there is only limited information to evaluate the spatial and temporal changes to the Huangpu River and its many tributaries. In the present study, 400 citizen scientists were trained to monitor water quality and environmental conditions on a monthly basis over three years in the lower (high urbanized) Huangpu River catchment. Their data were integrated with high resolution land cover data using GIS techniques to characterize water quality dynamics of the Huangpu River system with respect to main environmental drivers. Environmental driver analysis indicated that up-catchment conditions dominate river dynamics while typical urban impacts (first flush, impermeable land coverâ¦) have only limited influence. According to these results, the city's investments to improve wastewater treatment and mitigate lower river impacts need to be extended throughout the catchment to reduce nutrient concentrations that are near or above thresholds for rivers and streams. The positive impact of in-stream vegetation pointed to the possibilities that local scale ecological remediation activities to reduce runoff could be viable approaches to improve river conditions throughout the catchment.
RDA results of the land use and water quality indicators in Huangpu River using different dataset.134
Journal: Science of The Total Environment - Volumes 584â585, 15 April 2017, Pages 651-664