Clarifying urban flood response characteristics and improving interpretable flood prediction with sparse data considering the coupling effect of rainfall and drainage pipeline siltation

Author:

Liu Guangxin,Fang Hongyuan,Di Danyang,Du Xueming,Zhang Shuliang,Xiao Lizhong,Zhang Jinping,Zhang Zhaoyang

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference40 articles.

1. A novel machine learning tool for current and future flood susceptibility mapping by integrating remote sensing and geographic information systems;Amiri;J. Hydrol.,2024

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3. Climate vulnerability and economic determinants: linkages and risk reduction in Sagar Island, India; a geospatial approach;Bera;Quat. Sci. Adv.,2021

4. Application of PCSWMM for assessing the impacts of urbanization and climate changes on the efficiency of stormwater drainage systems in managing urban flooding in Robe town, Ethiopia;Bibi;J. Hydrol.-Reg. Stud.,2023

5. Rediscovering South Africa: flood disaster risk management through ecosystem-based adaptation;Busayo;Environ. Sustain. Indic.,2022

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