Relative sea-level rise and inundation risks in the Bohai Rim: Dominant role of vertical land motion
• Quantify VLM’s contributions to RSLR and coastal inundation risk in the Bohai Rim. • Develop a dynamic flood model to enhance flood risk assessment. • Analyze VLM drivers and uncertainties to refine coastal flood risk evaluation. Coastal regions worldwide are increasingly threatened by Relative Sea Level Rise (RSLR), which results from the combined effects of Sea Level Rise (SLR) and Vertical Land Motion (VLM). Satellite Interferometric Synthetic Aperture Radar (InSAR) can measure millimeter-scale VLM. However, the spatiotemporal variability of VLM remains poorly quantified in RSLR estimation and projection and flood inundation assessment. This study constructed an RSLR dataset for the Bohai Rim by integrating high-resolution InSAR-derived VLM with SLR. We develop a dynamic flood inundation model by incorporating hydrological connectivity and flow path attenuation factors to improve flood risk assessment. The results show significant spatial variability of VLM and concentration on muddy and sandy coastlines. VLM dominates the spatial patterns and magnitude of RSLR. The maximum inundation extent and depth reach 17,756 km 2 and 5.4 m, respectively, under the RSLR-SSP5-8.5 scenario by 2100, which threatens 10.4 million residents. The uncertainties in inundation projection can be reduced by considering the drivers and nonlinear evolution of VLM. The flood protection infrastructures can reduce inundation largely. Our findings highlight the crucial importance of incorporating VLM into coastal risk assessments and provide insights for RSLR adaptation strategies.
Authors
- Jie Dong (ORCID: https://orcid.org/0000-0001-8916-3292)
- Shangjing Lai (ORCID: https://orcid.org/0000-0002-8358-5520)
- Jingchun Wu
- Li Zhang (ORCID: https://orcid.org/0000-0002-3684-4729)
- Qianye Lan (ORCID: https://orcid.org/0009-0007-5588-8755)
- Zhiqiang Gong
- Jinxin Lin
Institutions
- Ministry of Natural Resources (CN)
- China Geological Survey (CN)
- Wuhan University (CN)
- SGIDI Engineering Consulting (China) (CN)
- State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN)
- Lac Courte Oreilles Ojibwe University (US)
Publication Details
- Journal
- International Journal of Applied Earth Observation and Geoinformation
- Published
- 2026-01-21
- DOI
- https://doi.org/10.1016/j.jag.2026.105115
- Primary Topic
- Flood Risk Assessment and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00