Framework for assessing the floodplain inundation susceptibility in the lower Yellow River using long-term high-temporal resolution remote sensing images
Study region: The lower Yellow River (LYR) in China. Study Focus: The LYR floodplain system faces significant inundation risks, threatening riverside communities and infrastructure. This study develops a floodplain inundation susceptibility assessment framework using long-term high-temporal resolution remote sensing images (913 scenes), proposing the Floodplain Inundation Susceptibility Index (FISI) as indicator to guide inundation risk management. New hydrological insights for the region: The FISI values exhibit notable variations among different sub-reaches along both riverbanks, with R1-R2 showing higher values compared to other sub-reaches. The mean FISI values in the upper sections of LYR (R1-R2) are determined to be 0.24 for both riverbanks, whereas the mean value is 0.07 in downstream sub-reaches. The floodplain inundation susceptibility in LYR dominantly comes from the frequent channel migration. The operation of Xiaolangdi Dam has reduced the floodplain inundation susceptibility, with the mean FISI values in river sections R1 and R2 decreased from 0.260 and 0.229–0.169 and 0.167, respectively. The assessment suggests that additional river management measures are necessary to confine the channel located upstream of Gaocun station on the LYR. The proposed assessment framework is expected to offer guidance for identifying priority zones for protective interventions within the floodplains of the LYR and analogous river systems globally.
Authors
- Chiyuan Miao (ORCID: https://orcid.org/0000-0001-6413-7020)
- Dongxian Kong (ORCID: https://orcid.org/0000-0002-2912-6526)
- Jinquan Xu
- Mo Liu (ORCID: https://orcid.org/0000-0001-5990-6585)
Publication Details
- Journal
- Journal of Hydrology Regional Studies
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1016/j.ejrh.2025.102559
- Primary Topic
- Flood Risk Assessment and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Shandong Province