The Impacts of Impervious Surface on Water Quality in the Urban Agglomerations of Middle and Lower Reaches of the Yangtze River Economic Belt From Remotely Sensed Data
The Urban Agglomerations of Middle and Lower Reaches of the Yangtze River Economic Belt (UAMLYREB) have experienced rapid and intense urbanization over the past decades with natural ecosystems being converted to impervious surfaces. Thus, impervious surfaces are recognized as critical parameters whe...
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9519539/ |
| _version_ | 1818682756383637504 |
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| author | Zhihui Li Lu Peng Feng Wu |
| author_facet | Zhihui Li Lu Peng Feng Wu |
| author_sort | Zhihui Li |
| collection | DOAJ |
| description | The Urban Agglomerations of Middle and Lower Reaches of the Yangtze River Economic Belt (UAMLYREB) have experienced rapid and intense urbanization over the past decades with natural ecosystems being converted to impervious surfaces. Thus, impervious surfaces are recognized as critical parameters when considering the effect of urbanization on water quality. While understanding how the threshold of impervious surfaces affects water quality has been a hot topic, there has been little quantitative analysis on how such thresholds change during rapid urbanization periods across large urban areas. To remedy this deficiency, this article made use of remotely-sensed impervious surface area data and <italic>in situ</italic> water quality monitoring observations for the period 2000 to 2018 to quantitively derive the temporal variation in the thresholds of the percentage of the impervious surface area (PISA) when inferring the relationship between PISA and a set of water quality indicators for a selection of watersheds within the UAMLYREB. We employed segmented regression model to derive the nonlinear relationship between PISA, the water quality indicators, and the PISA-related thresholds. Our results indicate that PISA may be considered a useful water quality indicator over watershed spatial scales. We also found that the threshold effects differed between water quality indicators (DO, COD<sub>Mn</sub>, NH<sub>3</sub>-N), where, except for NH<sub>3</sub>-N, the indicators showed a PISA threshold of 30.08 to 42.34%, with slight variations over the study period. These results imply that maintaining PISA to be around 30% in watershed areas may be sufficient to mitigate against water quality degradation during the urbanization process. |
| first_indexed | 2024-12-17T10:23:54Z |
| format | Article |
| id | doaj.art-71bf1abbf20a4e438bb27b5c5a869121 |
| institution | Directory Open Access Journal |
| issn | 2151-1535 |
| language | English |
| last_indexed | 2024-12-17T10:23:54Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj.art-71bf1abbf20a4e438bb27b5c5a8691212022-12-21T21:52:44ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing2151-15352021-01-01148398840610.1109/JSTARS.2021.31060389519539The Impacts of Impervious Surface on Water Quality in the Urban Agglomerations of Middle and Lower Reaches of the Yangtze River Economic Belt From Remotely Sensed DataZhihui Li0https://orcid.org/0000-0002-3051-6580Lu Peng1Feng Wu2https://orcid.org/0000-0003-4688-0157Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, ChinaKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, ChinaKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, ChinaThe Urban Agglomerations of Middle and Lower Reaches of the Yangtze River Economic Belt (UAMLYREB) have experienced rapid and intense urbanization over the past decades with natural ecosystems being converted to impervious surfaces. Thus, impervious surfaces are recognized as critical parameters when considering the effect of urbanization on water quality. While understanding how the threshold of impervious surfaces affects water quality has been a hot topic, there has been little quantitative analysis on how such thresholds change during rapid urbanization periods across large urban areas. To remedy this deficiency, this article made use of remotely-sensed impervious surface area data and <italic>in situ</italic> water quality monitoring observations for the period 2000 to 2018 to quantitively derive the temporal variation in the thresholds of the percentage of the impervious surface area (PISA) when inferring the relationship between PISA and a set of water quality indicators for a selection of watersheds within the UAMLYREB. We employed segmented regression model to derive the nonlinear relationship between PISA, the water quality indicators, and the PISA-related thresholds. Our results indicate that PISA may be considered a useful water quality indicator over watershed spatial scales. We also found that the threshold effects differed between water quality indicators (DO, COD<sub>Mn</sub>, NH<sub>3</sub>-N), where, except for NH<sub>3</sub>-N, the indicators showed a PISA threshold of 30.08 to 42.34%, with slight variations over the study period. These results imply that maintaining PISA to be around 30% in watershed areas may be sufficient to mitigate against water quality degradation during the urbanization process.https://ieeexplore.ieee.org/document/9519539/Impervious surfacerapid urbanizationremote sensingsegmented regressionthresholdwater quality |
| spellingShingle | Zhihui Li Lu Peng Feng Wu The Impacts of Impervious Surface on Water Quality in the Urban Agglomerations of Middle and Lower Reaches of the Yangtze River Economic Belt From Remotely Sensed Data IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Impervious surface rapid urbanization remote sensing segmented regression threshold water quality |
| title | The Impacts of Impervious Surface on Water Quality in the Urban Agglomerations of Middle and Lower Reaches of the Yangtze River Economic Belt From Remotely Sensed Data |
| title_full | The Impacts of Impervious Surface on Water Quality in the Urban Agglomerations of Middle and Lower Reaches of the Yangtze River Economic Belt From Remotely Sensed Data |
| title_fullStr | The Impacts of Impervious Surface on Water Quality in the Urban Agglomerations of Middle and Lower Reaches of the Yangtze River Economic Belt From Remotely Sensed Data |
| title_full_unstemmed | The Impacts of Impervious Surface on Water Quality in the Urban Agglomerations of Middle and Lower Reaches of the Yangtze River Economic Belt From Remotely Sensed Data |
| title_short | The Impacts of Impervious Surface on Water Quality in the Urban Agglomerations of Middle and Lower Reaches of the Yangtze River Economic Belt From Remotely Sensed Data |
| title_sort | impacts of impervious surface on water quality in the urban agglomerations of middle and lower reaches of the yangtze river economic belt from remotely sensed data |
| topic | Impervious surface rapid urbanization remote sensing segmented regression threshold water quality |
| url | https://ieeexplore.ieee.org/document/9519539/ |
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