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A study on flooding scenario simulation of future extreme precipitation in Shanghai

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Abstract

In the context of climate warming and urbanization, predictions and inundation simulations for future extreme precipitation have become highly active research topics. In this paper, using daily precipitation recorded at 10 meteorological stations in Shanghai for the period 1961–2010, the daily precipitation of each station during the period 2011–2099 was simulated by the statistical downscaling model (SDSM). And we examined the varying tendencies of future precipitation by the Mann- Kendall test. Further, the Soil Conservation Service (SCS) model and Pearson-III distribution curve were used to simulate the waterlogging duration and depth of future extreme precipitation in different scenarios with 3-, 5-, 10-, 20-, 50-, and 100-year return periods. The results show that: 1) Precipitation in Shanghai before the 2050s shows a trend of increasing and decreasing alternations, followed by a trend of decreasing and a marked decrease in about the 2070s. 2) In the 21st century, the waterlogging duration with return periods of 3, 5, and 10 years in Shanghai is predicted to last for less than 30 minutes, while the return periods of 20, 50, and 100 years last for less than 45 minutes. From the spatial distribution, the waterlogging duration to the east and south of the Huangpu River is predicted to be shorter than that of the west and north. 3) With the increase of the return periods, the depth of waterlogging is predicted to increase. The deepest inundated areas are Jinshan to the south-west of Shanghai, the east side of the Huangpu River, and Chongming Island.

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Acknowledgements

The work was supported by the National Natural Science Foundation of China (Grant Nos. 41371493 and 41071324), and the Innovation Program of the Shanghai Municipal Education Commission (13YZ061).

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Correspondence to Zhan’e Yin.

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Wang, X., Yin, Z., Wang, X. et al. A study on flooding scenario simulation of future extreme precipitation in Shanghai. Front. Earth Sci. 12, 834–845 (2018). https://doi.org/10.1007/s11707-018-0730-z

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