Mapping Coastal Flood Risk in China

Abstract

Coastal flooding poses a significant threat to China’s coastal zones, driven by the combined effects of global climate change and rapid urbanization. However, owing to notable discrepancies in data accuracy, model construction, and parameter settings, the applicability of findings from existing regional studies is limited when extrapolated to broader macroscale risk assessments. Therefore, this study quantitatively assessed the risk of casualties and economic losses in China’s coastal areas under different return period scenarios using multi-source spatial data based on the LISFLOOD-FP hydraulic model with a fine 30-m spatial resolution. Extreme water levels corresponding to return periods of 20-, 50-, 100-, 200-, and 500-years estimated by historical observations from 65 tide-gauge stations were employed as boundary conditions to simulate the flood inundation. Taking inundation depth-damage curves into consideration, we subsequently quantified the spatial distribution of the population casualty rates and economic losses under different inundation scenarios. Our assessment results reveal pronounced spatial characteristics in coastal flood risk, with the most severe impacts concentrated in low-lying urban areas, such as the Bohai Rim regions, the Yangtze River Delta, and the Pearl River Delta. The results indicate that under the 500-year return period inundation scenario, the total flooded coastal area across 11 provinces reaches 20,983 km², with the number of casualties amounting to 176,000 and economic losses totaling CNY 303.8 billion yuan (about USD 42.2 billion). The high-resolution flood risk maps developed in this study provide spatial information and data support for national-scale coastal management, disaster risk reduction, and land-use planning in China’s coastal areas.

Keywords

China / Coastal flooding / High resolution / LISFLOOD-FP / Risk assessment

References

[1] Atmaja T, Fukushi K, Lee D-J. Leveraging coupled hydrodynamic with data-driven GeoAI models for advancing systemic compound flood risk evaluation in coastal urban areas. Archives of Computational Methods in Engineering, 2025, 33: 3243-3289.

[2] Aziz F, Wang X, Mahmood MQ, Awais M, Trenouth B. Coastal urban flood risk management: Challenges and opportunities−A systematic review. Journal of Hydrology, 2024, 645: Article 132271.

[3] Babati A-H, Isa Z, Abdussalam AF, Baba SU, Mustapha BB, Musa AS. Application of machine learning for coastal flooding. Discover Cities, 2025, 2(1): Article 80.

[4] Bates PD. Flood inundation prediction. Annual Review of Fluid Mechanics, 2022, 54: 287-315.

[5] Bates PD, De Roo APJ. A simple raster-based model for flood inundation simulation. Journal of Hydrology, 2000, 236(1–2): 54-77.

[6] Bates PD, Horritt MS, Fewtrell TJ. A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling. Journal of Hydrology, 2010, 387(1–2): 33-45.

[7] Becker M, Seeger K, Paszkowski A, Marcos M, Papa F, Almar R, Bates P, France-Lanord C, et al.. Coastal flooding in Asian megadeltas Recent advances persistent challenges and call for actions amidst local and global changes. Reviews of Geophysics., 2024, 62(4): Article e2024RG000846.

[8] Bian W, Fang J, Du S, Hu T. Evidence of increasing coastal flood risk along mainland China from 1985 to 2050: Perspectives on climate change and urban expansion. Ocean & Coastal Management, 2025, 270: Article 107918.

[9] Bian W, Fang J, Wang P, Sun Q, Fang J, Kong F, Hu T. Deep learning surrogate models for spatiotemporal prediction of coastal flooding inundations in Tianjin. China. Journal of Hydrology: Regional Studies, 2025, 60: Article 102593

[10] Boumis G, Moftakhari HR, Moradkhani H. Coevolution of extreme sea levels and sea-level rise under global warming. Earth’s Future., 2023, 11(7): Article e2023EF003649.

[11] Boyd, E. 2005. Toward an empirical measure of disaster vulnerability: Storm surges, New Orleans, and Hurricane Betsy. Poster presented at the 4th UCLA Conference on Public Health and Disasters, 1–4 May 2005, Los Angeles.

[12] Cai R, Xu W. Risk of socio-economic losses from floods in China’s coastal cities. China Population Resources and Environment, 2022, 32: 174-184. in Chinese.

[13] Caruso MF, Marani M. Extreme-coastal-water-level estimation and projection: A comparison of statistical methods. Natural Hazards and Earth System Sciences, 2022, 22(3): 1109-1128.

[14] Chan FKS, Lu X, Li J, Lai Y, Luo M, Chen YD, Wang D, Li N, et al.. Compound flood effects, challenges and solutions: Lessons toward climate-resilient Chinese coastal cities. Ocean & Coastal Management, 2024, 249: Article 107015.

[15] Chen, Q. 2023. Spatially explicit assessment of coastal flood risks in Chinese mainland based on hydrological modelling and geospatial big data. PhD dissertation. Hangzhou: Zhejiang University.

[16] Chen B, He J, He Z, Li L, Chen Q, Li F, Cao Z, Yang X. Potential impacts of storm surge-induced flooding based on refined exposure estimation: A case study. Geomatics, Natural Hazards and Risk, 2023, 14(1): Article 2232080.

[17] Chen B, He Z, Li L, Chen Q, He J, Li F, Chu D, Cao Z, Yang X. Comprehensive economic losses assessment of storm surge disasters using open data: A case study of Zhoushan, China. Journal of Water and Climate Change, 2024, 15(8): 3647-3665.

[18] Chen Y, Xu C, Ge Y, Zhang X, Zhou YN. A 100m gridded population dataset of China’s seventh census using ensemble learning and big geospatial data. Earth System Science Data, 2024, 16(8): 3705-3718.

[19] Coles S, Bawa J, Trenner L, Dorazio P. An introduction to statistical modeling of extreme values, 2001. London, Springer.

[20] Cui Q, Xie W, Liu Y. Effects of sea level rise on economic development and regional disparity in China. Journal of Cleaner Production, 2018, 176: 1245-1253.

[21] Fang J, Lincke D, Brown S, Nicholls RJ, Wolff C, Merkens J-L, Hinkel J, Vafeidis AT, et al.. Coastal flood risks in China through the 21st century –An application of DIVA. Science of the Total Environment, 2020, 704: Article 135311.

[22] Fang J, Sun S, Shi P, Wang JA. Assessment and mapping of potential storm surge impacts on global population and economy. International Journal of Disaster Risk Science, 2014, 5(4): 323-331.

[23] Fang J, Wahl T, Zhang Q, Muis S, Hu P, Fang J, Du S, Dou T, Shi P. Extreme sea levels along coastal China: Uncertainties and implications. Stochastic Environmental Research and Risk Assessment, 2021, 35(2): 405-418.

[24] Gao C, Wang L, Chen C, Luo G, Sun Y. Population and economic risk exposure in coastal region of China under sea level rise. Acta Geographica Sinica, 2019, 74: 1590-1604. (in Chinese).

[25] Gori A, Lin N, Xi D. Tropical cyclone compound flood hazard assessment: From investigating drivers to quantifying extreme water levels. Earth’s Future, 2020, 8(12): Article e2020EF001660.

[26] Green J, Haigh I, Quinn N, Neal J, Wahl T, Wood M, Eilander D, de Ruiter M, et al.. Review article: A comprehensive review of compound flooding literature with a focus on coastal and estuarine regions2024EGUsphere,

[27] Haces-Garcia F, Ross N, Glennie CL, Rifai HS, Hoskere V, Ekhtari N. Rapid 2D hydrodynamic flood modeling using deep learning surrogates. Journal of Hydrology, 2025, 651: Article 132561.

[28] Hague BS, Jones DA, Jakob D, McGregor S, Reef R. Australian coastal flooding trends and forcing factors. Earth’s Future, 2022, 10(2): Article e2021EF002483.

[29] Hallegatte S, Green C, Nicholls RJ, Corfee-Morlot J. Future flood losses in major coastal cities. Nature Climate Change, 2013, 3(9): 802-806.

[30] Jafarzadegan K, Moradkhani H, Pappenberger F, Moftakhari H, Bates P, Abbaszadeh P, Marsooli R, Ferreira C, et al.. Recent advances and new frontiers in riverine and coastal flood modeling. Reviews of Geophysics, 2023, 61(2): Article e2022RG000788.

[31] Jin H, Yuan J, Kulp S, Wang H, Li D, Wang G. Substantial reduction in population exposure to sea level changes along the Chinese mainland coast through emission mitigation. Environmental Research Letters, 2024, 19(11): Article 114044.

[32] Kirezci E, Young IR, Ranasinghe R, Muis S, Nicholls RJ, Lincke D, Hinkel J. Projections of global-scale extreme sea levels and resulting episodic coastal flooding over the 21st Century. Scientific Reports, 2020, 10(1): Article 11629.

[33] Kopp RE, Garner GG, Hermans THJ, Jha S, Kumar P, Reedy A, Slangen ABA, Turilli M, et al.. The Framework for Assessing Changes To Sea-level (FACTS) v1.0: A platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change. Geoscientific Model Development, 2023, 16(24): 7461-7489.

[34] Le Gal M, Fernández-Montblanc T, Duo E, Montes Perez J, Cabrita P, Souto Ceccon P, Gastal V, Ciavola P, Armaroli C. A new European coastal flood database for low-medium intensity events. Natural Hazards and Earth System Sciences, 2023, 23(11): 3585-3602.

[35] Lee W, Sun AY, Scanlon BR, Dawson C. Hindcasting compound pluvial, fluvial and coastal flooding during Hurricane Harvey (2017) using Delft3D-FM. Natural Hazards, 2024, 120(1): 851-880.

[36] Leijnse T, van Ormondt M, Nederhoff K, van Dongeren A. Modeling compound flooding in coastal systems using a computationally efficient reduced-physics solver: Including fluvial, pluvial, tidal, wind- and wave-driven processes. Coastal Engineering, 2021, 163: Article 103796.

[37] Li C, Wang F, Yang P, Wang F-C, Hu Y-Z, Zhao Y-L, Tian L-Z, Zhao R-B. Mangrove wetlands distribution status identification, changing trend analyzation and carbon storage assessment of China. China Geology, 2024, 7(1): 1-11.

[38] Liu S, Shi X, Liu Q, Tan J, Sun Y, Liu Q, Guo H. Warning water level determination and its spatial distribution in coastal areas of China. Natural Hazards and Earth System Sciences, 2023, 23(1): 127-138.

[39] Makris C, Mallios Z, Androulidakis Y, Krestenitis Y. CoastFLOOD: A high-resolution model for the simulation of coastal inundation due to storm surges. Hydrology, 2023, 10(5): Article 103.

[40] Ministry of Natural Resources of China. Technical directives for risk assessment and zoning of marine disaster – Part 1: Storm surge: HY/T 0273–2019, 2019. Beijing, National Standards Press of China

[41] Muis S, Verlaan M, Winsemius HC, Aerts JC, Ward PJ. A global reanalysis of storm surges and extreme sea levels. Nature Communications, 2016, 7(1): Article 11969.

[42] Neal J, Schumann G, Fewtrell T, Budimir M, Bates P, Mason D. Evaluating a new LISFLOOD-FP formulation with data from the summer 2007 floods in Tewkesbury. UK. Journal of Flood Risk Management, 2011, 4(2): 88-95

[43] Nicholls RJ, Cazenave A. Sea-level rise and its impact on coastal zones. Science, 2010, 328(5985): 1517-1520.

[44] Ohenhen LO, Shirzaei M, Ojha C, Sherpa SF, Nicholls RJ. Disappearing cities on US coasts. Nature, 2024, 627(8002): 108-115.

[45] Pandey S, Rao A, Haldar R. Modeling of coastal inundation in response to a tropical cyclone using a coupled hydraulic HEC-RAS and ADCIRC model. Journal of Geophysical Research: Oceans, 2021, 126(7): Article e2020JC01681010

[46] Rajib A, Liu Z, Merwade V, Tavakoly AA, Follum ML. Towards a large-scale locally relevant flood inundation modeling framework using SWAT and LISFLOOD-FP. Journal of Hydrology, 2020, 581: Article 124406.

[47] Sanders BF, Wing OEJ, Bates PD. Flooding is not like filling a bath. Earth’s Future, 2024, 12(12): Article e2024EF005164.

[48] Sharifian MK, Kesserwani G, Chowdhury AA, Neal J, Bates P. LISFLOOD-FP 8.1: New GPU-accelerated solvers for faster fluvial/pluvial flood simulations. Geoscientific Model Development, 2023, 16(9): 2391-2413.

[49] Shi X, Chen B, Liang Y, Zhang B, Ye T. Inundation simulation of different return periods of storm surge based on a numerical model and observational data. Stochastic Environmental Research and Risk Assessment, 2021, 35(10): 2093-2103.

[50] Shi X, Lv Y, Dong D, Jia N, Ge J, Yin J. Quantitative assessment of building risks and loss ratios caused by storm surge disasters: A case study of Xiamen. China. Applied Ocean Research, 2024, 145: Article 103934.

[51] Shi X, Yu P, Guo Z, Sun Z, Chen F, Wu X, Cheng W, Zeng J. Simulation of storm surge inundation under different typhoon intensity scenarios: Case study of Pingyang County, China. Natural Hazards and Earth System Sciences, 2020, 20(10): 2777-2790.

[52] Shi X, Zhang Y, Liu S, Yang L, Yu L, Zhang Y, Jia N, Tian Z. Mapping storm surge risk at county level in coastal areas of China. Journal of Marine Science and Engineering, 2025, 13(3): Article 427.

[53] Souto-Ceccon PE, Montes J, Duo E, Ciavola P, Fernández-Montblanc T, Armaroli C. A European database of resources on coastal storm impacts. Earth System Science Data, 2025, 17(3): 1041-1054.

[54] Uhe P, Lucas C, Hawker L, Brine M, Wilkinson H, Cooper A, Saoulis AA, Savage J, Sampson C. FathomDEM: An improved global terrain map using a hybrid vision transformer model. Environmental Research Letters, 2025, 20(3): Article 034002.

[55] Vousdoukas MI, Mentaschi L, Voukouvalas E, Bianchi A, Dottori F, Feyen L. Climatic and socioeconomic controls of future coastal flood risk in Europe. Nature Climate Change, 2018, 8(9): 776-780.

[56] Vousdoukas MI, Voukouvalas E, Mentaschi L, Dottori F, Giardino A, Bouziotas D, Bianchi A, Salamon P, Feyen L. Developments in large-scale coastal flood hazard mapping. Natural Hazards and Earth System Sciences, 2016, 16(8): 1841-1853.

[57] Wang F, Liu X-Z, Li Y, Yu H, Wen M-Z, Hu Y-Z. Risk assessment of coastal flooding disaster by storm surge based on elevation-area method and hydrodynamic models: Taking Bohai Bay as an example. China Geology, 2024, 7(3): 494-504.

[58] Ward PJ, Jongman B, Weiland FS, Bouwman A, Beek RV, Bierkens MFP, Ligtvoet W, Winsemius HC. Assessing flood risk at the global scale: Model setup, results, and sensitivity. Environmental Research Letters, 2013, 8(4): Article 044019.

[59] Werner MGF, Hunter NM, Bates PD. Identifiability of distributed floodplain roughness values in flood extent estimation. Journal of Hydrology, 2005, 314(1): 139-157.

[60] Wing OEJ, Bates PD, Quinn ND, Savage JTS, Uhe PF, Cooper A, Collings TP, Addor N, et al.. A 30 m global flood inundation model for any climate scenario. Water Resources Research, 2024, 60(8): Article e2023WR036460.

[61] Xu H, Hou X, Li D, Wang X, Fan C, Du P, Song B. Spatial assessment of coastal flood risk due to sea level rise in China’s coastal zone through the 21st century. Frontiers in Marine Science, 2022, 9: Article 945901.

[62] Xu H, Hou X, Li D, Zheng X, Fan C. Projections of coastal flooding under different RCP scenarios over the 21st century: A case study of China’s coastal zone. Estuarine, Coastal and Shelf Science, 2022, 279: Article 108155.

[63] Yang J, Huang X. The 30m annual land cover dataset and its dynamics in China from 1990 to 2019. Earth System Science Data, 2021, 13(8): 3907-3925.

[64] Yang J, Liu K, Wang M, Zhao G, Wu W, Yue Q. A convolutional neural network-weighted cellular automaton model for the fast prediction of urban pluvial flooding processes. International Journal of Disaster Risk Science, 2024, 15(5): 754-768.

[65] Yang F, Wu J, Zhang Y, Zhu S, Liu G, Chen G, Wu S, Fan Z. Improved method for identifying Manning’s roughness coefficients in plain looped river network area. Engineering Applications of Computational Fluid Mechanics, 2021, 15(1): 94-110.

[66] Yin J, Lin N, Yang Y, Pringle WJ, Tan J, Westerink JJ, Yu D. Hazard assessment for typhoon-induced coastal flooding and inundation in Shanghai. China. Journal of Geophysical Research: Oceans., 2021, 126: Article e2021JC017319

[67] Yin J, Yin ZE, Yu D, Xu SY. Vulnerability analysis for storm induced flood: A case study of Huangpu River Basin. Scientia Geographica Sinica, 2012, 32(9): 1155-1160. (in Chinese).

[68] Zhou Z, Yang S, Hu F, Chen B, Shi X, Liu X. Tropical cyclone storm surge-based flood risk assessment under combined scenarios of high tides and sea-level rise: A case study of Hainan Island. China. Earth’s Future, 2024, 12(8): Article e2023EF004236.

RIGHTS & PERMISSIONS

The Author(s)