4.7 Article

Impact of urbanization on nonstationarity of annual and seasonal precipitation extremes in China

期刊

JOURNAL OF HYDROLOGY
卷 575, 期 -, 页码 638-655

出版社

ELSEVIER
DOI: 10.1016/j.jhydrol.2019.05.070

关键词

Urbanization; Precipitation extremes; Long-term changes; Nonstationarity; GAMLSS; China

资金

  1. National Science Foundation for Distinguished Young Scholars of China [51425903]
  2. National Key R&D Program of China [2018YFA0605603]
  3. Strategic Priority Research Program Grant of the Chinese Academy of Sciences [XDA19070402]
  4. Fund for Creative Research Groups of National Natural Science Foundation of China [41621061]
  5. Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) [CUGCJ1702, CUG180614]

向作者/读者索取更多资源

Chinese cities have been experiencing unprecedented growth for over three decades and the resulting urbanization is having a remarkable impact on the hydrological cycle at the local and regional scale. This study therefore examined the influence of urbanization on nonstationarity of annual and seasonal precipitation extremes in China, using daily precipitation data from 1857 stations for 1961-2014, and NCAR/NCEP and ERA Interim reanalysis datasets. Results of trend, change point, and bootstrap analyses revealed that urban signatures on long-term changes (i.e. trends and magnitudes) of precipitation extremes were not prominently visible at the national scale. However, a nonstationary frequency analysis of precipitation extremes by a Generalized Additive Model for Location, Scale and Shape (GAMLSS) framework with a cluster of 66 models showed that urbanization caused nonstationarity in precipitation extremes at local and regional scales, such as North China. Further, significant nonstationarity tended to occur more in urbanizing areas than in rural and urbanized areas, suggesting that land use/land cover (LULC) transition (i.e. rural areas turning into urban areas) played an important role in introducing nonstationarity. Furthermore, analysis of large-scale circulation patterns, using k-mean clustering, showed that urban signatures on extremes were not prominent at the national scale but at the regional scale. Further studies are needed to enumerate physical mechanisms causing the impact of local environmental changes on precipitation extremes at different geographical locations over China.

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