Assessing the Long-Term Hydrological Effects of Rapid Urbanization in Metropolitan Shanghai, China: The Finer the Landscape Classification, the More Accurate the Modeling?

Tao Tao, Du Wang, Ganping Huang, Liqing Lin, Chenhao Wu, Qixin Xu, Jun Zhao () and Guangren Qian
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Tao Tao: Department of Environmental Science and Engineering, Shanghai University, Shanghai 200444, China
Du Wang: Department of Environmental Science and Engineering, Shanghai University, Shanghai 200444, China
Ganping Huang: Department of Environmental Science and Engineering, Shanghai University, Shanghai 200444, China
Liqing Lin: Academy of Environmental Planning and Design Co., Ltd., Nanjing University, Nanjing 210008, China
Chenhao Wu: Shanghai Municipal Engineering Design Institute, Shanghai 200433, China
Qixin Xu: School of Environmental and Geographical Sciences, East China Normal University, Shanghai 200234, China
Jun Zhao: Department of Environmental Science and Engineering, Shanghai University, Shanghai 200444, China
Guangren Qian: Department of Environmental Science and Engineering, Shanghai University, Shanghai 200444, China

Sustainability, 2023, vol. 15, issue 8, 1-14

Abstract: Rapid urbanization often leads to increase in surface runoff; its modelling is always the focus in the field of land use effect. One of the methodological issues is how to classify the landscape (land use/land cover) in the model. In this study, the long-term hydrological impact assessment (L-THIA) model was used to simulate the change of annual surface runoff during the rapid urbanization in Shanghai since 1965. Two landscape scenarios, based upon land uses and pervious/impervious surfaces, were compared, and the CN values were adjusted to validate the applicability of the two landscape scenarios. The results showed that there was almost no difference between the results based on the two landscape scenarios, and it was suggested that the simplified landscape scenario based upon pervious/impervious surfaces can be workable and efficient, while the land use scenario may not be necessary for the modelling considering its scale of interpretation of remote sensing data. It was found that there was a clear linear relationship between the percentage of impervious surfaces and surface runoff. For every 1% increase in impervious surface, runoff increased by 0.94%. In addition, the effect of precipitation on the modelling was also discussed, which indicated that with the increase in impervious surface percentage, the response of runoff change in both dry year and dry season was more sensitive.

Keywords: land use; impervious surface; L-THIA; runoff; rapid urbanization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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