Inundation Hazard Assessment in a Chinese Lagoon Area under the Influence of Extreme Storm Surge
Abstract
:1. Introduction
2. Model, Data, and Validation
2.1. Storm Surge Inundation Model
2.2. Data Sources
2.3. The Calculation of the Typhoon Wind Field
2.4. Model Validation
3. Results
3.1. Typhoon Parameters for an Extreme Scenario
3.2. An Analysis of the Differences in the Numerical Simulations between the Two Lagoons
3.3. Inundation Hazard Assessment under Extreme Storm Surges
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Chen, J.L.; Wang, Z.Q.; Tam, C.Y.; Lau, N.C.; Lau, D.S.D.; Mok, H.Y. Impacts of climate change on tropical cyclones and induced storm surges in the Pearl River Delta region using pseudo-global-warming method. Sci. Rep. 2020, 10, 1965. [Google Scholar] [CrossRef]
- Zhang, Q.; Gu, X.H.; Shi, P.J.; Vijay, P. Impact of tropical cyclones on food risk in southeastern China: Spatial patterns, causes and implications. Glob. Planet. Chang. 2017, 150, 81–93. [Google Scholar] [CrossRef]
- Otto, P.; Mehta, A.; Liu, B. Mind the gap: Towards and beyond impact to enhance tropical cyclone risk communication. Trop. Cyclone Res. Rev. 2018, 7, 140–151. [Google Scholar] [CrossRef]
- Zhang, R.W.; Huangfu, J.L.; Hu, T. Dynamic mechanism for the evolution and rapid intensification of Typhoon Hato (2017). Atmos. Sci. Lett. 2019, 20, e930. [Google Scholar] [CrossRef]
- Choy, C.W.; Insurers, T.H.K.F.O.; Wu, M.C.; Lee, T.C. Assessment of the damages and direct economic loss in Hong Kong due to super typhoon Mangkhut in 2018. Trop. Cyclone Res. Rev. 2020, 9, 193–205. [Google Scholar] [CrossRef]
- Turan, C.K.; Kinfu, Y.P.; Samad, M.A.; Farhadzadeh, A.; Ng, K. Comparison of ADCIRC and SLOSH Model Simulations for Hurricanes Andrew and Irma near Miami, Florida. In World Environmental and Water Resources Congress 2018; American Society of Civil Engineers: Reston, VA, USA, 2018. [Google Scholar] [CrossRef]
- Condon, A.J.; Sheng, Y.P. Evaluation of coastal inundation hazard for present and future climates. Nat. Hazards 2011, 62, 345–373. [Google Scholar] [CrossRef]
- Makris, C.V.; Androulidakis, Y.; Baltikas, V.; Kontos, Y.N.; Krestenitis, Y. HiReSS: Storm surge simulation model for the operational forecasting of sea level elevation and currents in marine areas with harbor works. In Proceedings of the 1st International Conference Design And Management of Port, Coastal and Offshore Works (DMPCO), Thessaloniki, Greece, 24–27 May 2019. [Google Scholar]
- Vashist, K.; Singh, K. HEC-RAS 2D modeling for flood inundation mapping: A case study of the Krishna River Basin. Water Pract. Technol. 2023, 18, 831–844. [Google Scholar] [CrossRef]
- Ebersole, B.A.; Westerink, J.J.; Bunya, S.; Dietrich, J.C.; Cialone, M.A. Development of storm surge which led to flooding in St. Bernard Polder during Hurricane Katrina. Ocean Eng. 2010, 37, 91–103. [Google Scholar] [CrossRef]
- Yang, J.; Li, L.L.; Zhao, K.F.; Wang, P.T.; Wang, D.; Sou, I.M.; Yang, Z.T.; Hu, J.; Tang, X.C.; Mok, K.M.; et al. A comparative study of Typhoon Hato (2017) and Typhoon Mangkhut (2018)—Their impacts on coastal inundation in Macau. J. Geophys. Res. Ocean. 2019, 124, 9590–9619. [Google Scholar] [CrossRef]
- Lin, N.; Emanuel, K.A.; Smith, J.A.; Vanmarcke, E. Risk assessment of hurricane storm surge for New York City. J. Geophys. Res. 2010, 115, D18121. [Google Scholar] [CrossRef]
- Thomas, A.; Dietrich, J.C.; Loveland, M.; Samii, A.; Dawson, C.N. Improving coastal flooding predictions by switching meshes during a simulation. Ocean Model. 2021, 164, 101820. [Google Scholar] [CrossRef]
- Bunya, S.; Dietrich, J.C.; Westerink, J.J.; Ebersole, B.A.; Smith, J.M.; Atkinson, J.H.; Jensen, R.; Resio, D.T.; Luettich, R.A.; Dawson, C.; et al. A High-Resolution Coupled Riverine Flow, Tide, Wind, Wind Wave, and Storm Surge Model for Southern Louisiana and Mississippi. Part I: Model Development and Validation. Mon. Weather Rev. 2010, 138, 345–377. [Google Scholar] [CrossRef]
- Dietrich, J.C.; Bunya, S.; Westerink, J.J.; Ebersole, B.A.; Smith, J.M.; Atkinson, J.H.; Jensen, R.; Resio, D.T.; Luettich, R.A.; Dawson, C.; et al. A High-Resolution Coupled Riverine Flow, Tide, Wind, Wind Wave, and Storm Surge Model for Southern Louisiana and Mississippi. Part II: Synoptic Description and Analysis of Hurricanes Katrina and Rita. Mon. Weather Rev. 2010, 138, 378–404. [Google Scholar] [CrossRef]
- Hsiao, S.C.; Chen, H.; Chen, W.B.; Chang, C.H.; Lin, L.Y. Quantifying the contribution of nonlinear interactions to storm tide simulations during a super typhoon event. Ocean Eng. 2019, 194, 106661. [Google Scholar] [CrossRef]
- Lewis, M.J.; Palmer, T.; Hashemi, R.; Robins, P.; Saulter, A.; Brown, J.; Lewis, H.; Neill, S. Wave-tide interaction modulates nearshore wave height. Ocean Dyn. 2019, 69, 367–384. [Google Scholar] [CrossRef]
- Xie, L.A.; Liu, H.Q.; Peng, M.C. The effect of wave–current interactions on the storm surge and inundation in Charleston Harbor during Hurricane Hugo 1989. Ocean Model. 2008, 20, 252–269. [Google Scholar] [CrossRef]
- Suh, S.-W.; Lee, M.-H. Analysis of Typhoon-Induced Wave Overtopping Vulnerability Due to Sea Level Rise Using a Coastal–Seawall–Terrestrial Seamless Grid System. J. Mar. Sci. Eng. 2023, 11, 2114. [Google Scholar] [CrossRef]
- Silveira, F.; Lopes, C.L.; Pinheiro, J.P.; Pereira, H.; Dias, J.M. Coastal Floods Induced by Mean Sea Level Rise—Ecological and Socioeconomic Impacts on a Mesotidal Lagoon. J. Mar. Sci. Eng. 2021, 9, 1430. [Google Scholar] [CrossRef]
- Montgomery, J.M.; Bryan, K.R.; Mullarney, J.C.; Horstman, E.M. Attenuation of storm surges by coastal mangroves. Geophys. Res. Lett. 2019, 46, 2680–2689. [Google Scholar] [CrossRef]
- Lagomasino, D.; Fatoyinbo, T.; Castaeda-Moya, E.; Cook, B.D.; Montesano, P.M.; Neigh, C.S.R.; Corp, L.A.; Ott, L.E.; Chavez, S.; Morton, D.C. Storm surge and ponding explain mangrove dieback in southwest Florida following Hurricane Irma. Nat. Commun. 2021, 12, 4003. [Google Scholar] [CrossRef]
- Mel, R.A.; Coraci, E.; Morucci, S.; Crosato, F.; Cornello, M.; Casaioli, M.; Mariani, S.; Carniello, L.; Papa, A.; Bonometto, A.; et al. Insights on the Extreme Storm Surge Event of the 22 November 2022 in the Venice Lagoon. J. Mar. Sci. Eng. 2023, 11, 1750. [Google Scholar] [CrossRef]
- Guidance for Flood Risk Analysis and Mapping. Available online: https://www.fema.gov/sites/default/files/documents/fema_rm-coastal-flood-frequency-and-extreme-value-analysis-guidance-nov-2016.pdf (accessed on 2 July 2024).
- National Storm Surge Risk Maps—Version 3. Available online: https://www.nhc.noaa.gov/nationalsurge/ (accessed on 2 July 2024).
- Storm Inundation Modelling and Mapping. Available online: https://www.mlit.go.jp/river/shishin_guideline/kaigan/takashioshinsui_manual.pdf (accessed on 2 July 2024). (In Japanese).
- Westerink, J.J.; Luettich, R.A.; Blain, C.A.; Scheffner, N.W. ADCIRC: An advanced three-dimensional circulation model for shelves, coasts, and estuaries. report 2. user’s manual for adcirc-2ddi. J. Geol. 1994, 76, 721–723. [Google Scholar]
- Fu, C.; Liu, Q.; Gao, Y.; Cao, H.; Liang, S. Numerical Simulation of Storm Surge Inundation in Estuarine Area Considering Multiple Influencing Factors. Sustainability 2024, 16, 2274. [Google Scholar] [CrossRef]
- NAO.99b Tidal Prediction System. Available online: https://www.miz.nao.ac.jp/staffs/nao99/index_En.html (accessed on 6 May 2023).
- National Catalogue Service For Geographic Information of China. Available online: https://www.webmap.cn/main.do?method=index (accessed on 1 May 2023).
- CMA Tropical Cyclone Data Center for the Western North Pacific Basin. Available online: https://tcdata.typhoon.org.cn/zjljsjj.html (accessed on 6 May 2023).
- Lu, X.Q.; Yu, H.; Ying, M.; Zhao, B.; Zhang, S.; Lin, L.; Bai, L.; Wan, R. Western North Pacific tropical cyclone database created by the China Meteorological Administration. Adv. Atmos. Sci. 2021, 38, 690–699. [Google Scholar] [CrossRef]
- Integrated Water Level Dataset. Available online: https://mds.nmdis.org.cn/pages/dataViewDetail.html?dataSetId=35 (accessed on 6 May 2023).
- Holland, G.J. An Analytic Model of the Wind and Pressure Profiles in Hurricanes. Mon. Weather Rev. 1980, 108, 1212–1218. [Google Scholar] [CrossRef]
- Atkinson, G.D.; Holliday, C.R. Tropical cyclone minimum sea level pressure-maximum sustained wind relationship for western north pacific. Mon. Weather Rev. 1977, 105, 25. [Google Scholar] [CrossRef]
- Luo, J.M.; Jiang, Y.P.; Pang, L.; Feng, X.D. Numerical simulation of storm surge in the coast of Zhejiang based on parametric wind field model. Haiyang Xuebao 2022, 44, 20–34. (In Chinese) [Google Scholar] [CrossRef]
- Yu, F.J.; Dong, J.X.; Ye, L.; Hou, J.M.; Li, M.J.; Liu, S.C.; Wu, S.H.; Liu, Q.X.; Fu, X.; Fu, C.F.; et al. Collection of Storm Surge Disasters Historical Data in China 1949–2009; China Ocean Press: Beijing, China, 2015. (In Chinese) [Google Scholar]
- HY/T 0273-2019; Technical Guidelines for Risk Assessment and Zoning of Marine Disaster Part 1: Storm Surge. Standards Press of China: Beijing, China, 2019.
- Kopp, R.E.; Kemp, A.C.; Bittermann, K.; Horton, B.P.; Donnelly, J.P.; Gehrels, W.R.; Hay, C.C.; Mitrovica, J.X.; Morrow, E.D.; Rahmstorf, S. Temperature-driven global sea-level variability in the Common Era. Proc. Natl. Acad. Sci. USA 2016, 113, 1434–1441. [Google Scholar] [CrossRef]
- Parker, A. Sea level trends at locations of the United States with more than 100 years of recording. Nat. Hazards 2013, 65, 1011–1021. [Google Scholar] [CrossRef]
- Kazuyoshi, O.; Jun, Y.; Hiromasa, Y.; Ryo, M.; Shoji, K.; Akira, N. Tropical cyclone climatology in a global-warming climate as simulated in a 20 km-mesh global atmospheric model: Frequency and wind intensity analyses. J. Meteorol. Soc. Jpn. Ser. II 2006, 84, 259–276. [Google Scholar] [CrossRef]
- Ying, M.; Knutson, T.R.; Kamahori, H.; Lee, T.C. Impacts of climate change on tropical cyclones in the western North Pacific basin. Part II: Late twenty-first century projections. Trop. Cyclone Res. Rev. 2012, 1, 231–241. [Google Scholar] [CrossRef]
- Shan, K.Y.; Lin, Y.L.; Chu, P.S.; Yu, X.P.; Song, F.F. Seasonal advance of intense tropical cyclones in a warming climate. Nature 2023, 623, 83–89. [Google Scholar] [CrossRef] [PubMed]
- Garner, A.J.; Mann, M.E.; Emanuel, K.A.; Kopp, R.E.; Lin, N.; Alley, R.B.; Horton, B.P.; Deconto, R.M.; Donnelly, J.P.; Pollard, D. Impact of climate change on New York City’s coastal flood hazard: Increasing flood heights from the preindustrial to 2300 CE. Proc. Natl. Acad. Sci. USA 2017, 114, 11861–11866. [Google Scholar] [CrossRef] [PubMed]
- Fu, X.; Liang, S.D.; Guo, H.L.; Li, M.J.; Ye, L. Characteristic analysis of tropical storm surges affecting the coastal area of China in the past 40 years. Mar. Forecast. 2023, 40, 1–11. (In Chinese) [Google Scholar] [CrossRef]
- Fu, X.; Hou, J.M.; Liu, Q.X.; Li, M.J.; Liang, S.D. Evaluation of surge hazard based on a storm surge hazard indicator along the mainland coast of China. Nat. Hazards 2023, 116, 3481–3493. [Google Scholar] [CrossRef]
- Madsen, H.; Jakobsen, F. Cyclone induced storm surge and flood forecasting in the northern Bay of Bengal. Coast. Eng. 2004, 51, 277–296. [Google Scholar] [CrossRef]
- Gayathri, R.; Bhaskaran, P.K.; Sen, D. Numerical Study on Storm Surge and Associated Coastal Inundation for 2009 AILA Cyclone in the Head Bay of Bengal. Aquat. Procedia 2015, 4, 404–411. [Google Scholar] [CrossRef]
- Ferguson, S.; Provan, M.; Murphy, E.; Bérubé, D.; Desrosiers, M.; Robichaud, A.; Kim, J. Assessing Numerical Model Skill at Simulating Coastal Flooding Using Field Observations of Deposited Debris and Photographic Evidence. Water 2022, 14, 589. [Google Scholar] [CrossRef]
- 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, 103. [Google Scholar] [CrossRef]
- He, P.D.; Zuo, J.C.; Gu, Y.B.; Zhang, B.; Kang, X.; Zhang, H. Inundation risk assessment of storm surge along Putuo cosatal areas. Trans. Oceanol. Limnol. 2015, 1, 1–8. (In Chinese) [Google Scholar]
- Cyriac, R.; Dietrich, J.C.; Fleming, J.G.; Blanton, B.O.; Kaiser, C.; Dawson, C.N.; Luettich, R.A. Variability in Coastal Flooding predictions due to forecast errors during Hurricane Arthur. Coast. Eng. 2018, 137, 59–78. [Google Scholar] [CrossRef]
- Hashimoto, N.; Yokota, M.; Yamashiro, M.; Kinashi, Y.; Kodama, M. Numerical Simulations of Storm-Surge Inundation Along Innermost Coast of Ariake Sea Based on Past Violent Typhoons. J. Disaster Res. 2016, 11, 1221–1227. [Google Scholar] [CrossRef]
- Rey, W.; Mendoza, E.T.; Salles, P.; Zhang, K.; Teng, Y.C.; Trejo-Rangel, M.A.; Franklin, G.L. Hurricane flood risk assessment for the Yucatan and Campeche State coastal area. Nat. Hazards 2019, 96, 1041–1065. [Google Scholar] [CrossRef]
- Prince, H.C.; Nirmala, R.; Mahendra, R.S.; Murty, P.L.N. Storm Surge Hazard Assessment Along the East Coast of India Using Geospatial Techniques. Asian J. Water Environ. Pollut. 2020, 19, 51–57. [Google Scholar] [CrossRef]
- Yang, J.; Chen, M. Potential impacts of flood risk with rising sea level in Macau: Dynamic simulation from historical Typhoon Mangkhut (2018). Ocean Eng. 2022, 246, 110605. [Google Scholar] [CrossRef]
- Thomas, A.; Dietrich, J.C.; Dawson, C.N.; Luettich, R.A. Effects of Model Resolution and Coverage on Storm-Driven Coastal Flooding Predictions. J. Waterw. Port Coast. Ocean Eng. 2022, 148, 04021046. [Google Scholar] [CrossRef]
- Rajput, A.A.; Liu, C.; Liu, Z. Human-centric characterization of life activity flood exposure shifts focus from places to people. Nat. Cities 2024, 1, 264–274. [Google Scholar] [CrossRef]
- Mohammed, F.K.; Nobuo, M. Impacts of climate change and sea-level rise on cyclonic storm surge floods in Bangladesh. Glob. Environ. Chang. 2008, 18, 490–500. [Google Scholar] [CrossRef]
Model Parameter | Description | Value and Its Meaning |
---|---|---|
NOLIBF | Parameter of the type of bottom stress parameterization | 2 hybrid nonlinear bottom friction law is used |
NOLIFA | Parameter of the finite amplitude terms | 2 finite amplitude terms included in the model are run and the wetting and drying of elements are enabled |
NWS | Parameter of the wind velocity or stress, atmospheric pressure, and wave radiation stress | 8 hurricane parameters are calculated at every node using the Holland wind model |
τ0 | Generalized Wave Continuity Equation (GWCE) weighting factor in the model | −3 this parameter is calculated based on nodal attributes, and it is variable in space and time |
DT | Time step (in seconds) | 0.8 time interval for the iterative model calculation |
Data | Source | Description |
---|---|---|
Water depth | National Catalogue Service for Geographic Information of China [30] | The water data observed in 2021 have a spatial resolution of 50 m. |
Geographic information | National Catalogue Service for Geographic Information of China [30] | The DEM data and the land use data observed in 2021 have a spatial resolution of 10 m. |
Typhoon | China Meteorological Administration (CMA) [31,32] | The typhoon data are in six-hour intervals and include information on time, location, center pressure, and maximum wind speed. |
Tidal level | National Marine Data Center of China [33] | The tidal level data with hourly intervals from the Gangbei and Sanya tidal gauge stations in Hainan Province are used. |
Time (Year-Month-Day-Hour) | Position | Central Air Pressure (hPa) | Maximum Wind Speed (m/s) | Maximum Wind Speed Radius (km) | Description |
---|---|---|---|---|---|
1981070214 | 115.6° E, 14.4° N | 981 | 30 | 65 | Typhoon Kelly caused a maximum storm surge of over 1.0 m at three tidal gauge stations in Guangdong and Hainan Provinces, with the highest level at Gangbei tidal gauge station in Hainan, i.e., 1.62 m. The storm surge disaster information was not collected [37]. |
1981070220 | 114.5° E, 14.9° N | 980 | 30 | 65 | |
1981070302 | 113.9° E, 15.7° N | 975 | 35 | 60 | |
1981070308 | 112.8° E, 16.8° N | 964 | 45 | 45 | |
1981070314 | 111.4° E, 17.3° N | 962 | 45 | 45 | |
1981070320 | 110.7° E, 17.7° N | 965 | 45 | 45 | |
1981070402 | 109.7° E, 18.3° N | 965 | 45 | 45 | |
1981070408 | 108.5° E, 18.7° N | 980 | 35 | 55 | |
1981070414 | 107.6° E, 19.0° N | 985 | 30 | 60 | |
1981070420 | 106.8° E, 19.2° N | 985 | 30 | 60 | |
1981070502 | 105.6° E, 19.3° N | 985 | 30 | 60 | |
1981070508 | 105.0° E, 19.3° N | 994 | 20 | 70 | |
1981070514 | 103.5° E, 19.3° N | 995 | 15 | 80 |
Time (Year-Month-Day-Hour) | Position | Central Air Pressure (hPa) | Maximum Wind Speed (m/s) | Maximum Wind Speed Radius (km) | Description |
---|---|---|---|---|---|
1996082002 | 121.5° E, 17.6° N | 990 | 23 | 85 | Affected by Typhoon Niki, the storm surge at the Gangbei tidal gauge station in Hainan was the highest, reaching 1.57 m, with the highest recorded tidal level exceeding the warning level. According to statistics, 200 hectares of seawater aquaculture facilities were damaged in the Lingshui area, with 948 tons of farmed fish lost, four fishing boats sunk or run aground, and one person deceased [37]. |
1996082008 | 119.9° E, 17.6° N | 985 | 25 | 85 | |
1996082014 | 118.3° E, 17.3° N | 985 | 25 | 75 | |
1996082020 | 116.8° E, 17.1° N | 985 | 25 | 75 | |
1996082102 | 115.7° E, 17.1° N | 980 | 30 | 75 | |
1996082108 | 114.2° E, 17.3° N | 980 | 30 | 75 | |
1996082114 | 112.7° E, 17.5° N | 975 | 33 | 75 | |
1996082120 | 111.5° E, 17.8° N | 975 | 33 | 70 | |
1996082202 | 110.4° E, 18.2° N | 970 | 35 | 70 | |
1996082208 | 109.4° E, 18.5° N | 975 | 30 | 70 | |
1996082214 | 108.0° E, 18.9° N | 975 | 30 | 70 | |
1996082220 | 106.9° E, 19.5° N | 980 | 30 | 85 | |
1996082302 | 105.4° E, 20.0° N | 985 | 25 | 85 |
Typhoon Number (Year-No.) | Name | Central Air Pressure (hPa) | Maximum Wind Speed (m/s) | Maximum Wind Speed Radius (km) | Direction of Movement |
---|---|---|---|---|---|
1952 No. 10 | Lois | 960 | 40 | 20 | W |
1954 No. 01 | Elsie | 960 | 35 | 15 | NNW |
1956 No. 09 | Vera | 975 | 35 | 30 | WNW |
1956 No. 07 | Charlotte | 960 | 45 | 13 | WNW |
1962 No. 19 | Carla | 975 | 35 | 25 | WNW |
1964 No. 26 | Clara | 965 | 40 | 18 | WNW |
1968 No. 08 | Rose | 970 | 35 | 15 | WNW |
1971 No. 30 | Elaine | 965 | 40 | 16 | WNW |
1973 No. 14 | Marge | 938 | 60 | 25 | WNW |
1973 No. 18 | Ruth | 973 | 35 | 18 | NW |
1981 No. 05 | Kelly | 965 | 45 | 20 | WNW |
1982 No. 23 | Nancy | 965 | 45 | 20 | WNW |
1985 No. 21 | Dot | 970 | 40 | 28 | WNW |
1987 No. 10 | Cary | 970 | 35 | 25 | NW |
1989 No. 05 | Dot | 960 | 40 | 15 | WNW |
1989 No. 26 | Elsie | 975 | 30 | 25 | WNW |
1991 No. 06 | Zeke | 960 | 45 | 15 | WNW |
1992 No. 04 | Chuck | 965 | 40 | 18 | NW |
1996 No. 12 | Niki | 970 | 35 | 18 | WNW |
2000 No. 16 | Wukong | 970 | 35 | 15 | W |
2005 No. 18 | Damrey | 930 | 55 | 18 | W |
2010 No. 02 | Conson | 970 | 35 | 16 | NW |
2012 No. 23 | Son-tinh | 950 | 45 | 18 | NW |
2013 No. 30 | Haiyan | 960 | 40 | 30 | NNW |
2016 No. 21 | Sarika | 960 | 45 | 18 | WNW |
Average | 963.2 | 40.4 | 19.8 |
Typhoon Track | P1 (m) | P2 (m) | Typhoon Track | P1 (m) | P2 (m) | Typhoon Track | P1 (m) | P2 (m) | Typhoon Track | P1 (m) | P2 (m) |
---|---|---|---|---|---|---|---|---|---|---|---|
W, +20 km | 0.51 | 0.66 | WNW, +20 km | 0.58 | 0.73 | NW, +20 km | 0.56 | 0.70 | NNW, +20 km | 0.54 | 0.68 |
W, +10 km | 0.59 | 0.77 | WNW, +10 km | 0.64 | 0.84 | NW, +10 km | 0.62 | 0.82 | NNW, +10 km | 0.59 | 0.81 |
W, +0 km | 0.63 | 0.83 | WNW, +0 km | 0.66 | 0.89 | NW, +0 km | 0.65 | 0.88 | NNW, +0 km | 0.62 | 0.86 |
W, −10 km | 0.66 | 0.88 | WNW, −10 km | 0.68 | 0.93 | NW, −10 km | 0.67 | 0.92 | NNW, −10 km | 0.64 | 0.88 |
W, −20 km | 0.67 | 0.91 | WNW, −20 km | 0.70 | 0.95 | NW, −20 km | 0.69 | 0.93 | NNW, −20 km | 0.68 | 0.90 |
W, −30 km | 0.66 | 0.88 | WNW, −30 km | 0.69 | 0.93 | NW, −30 km | 0.69 | 0.89 | NNW, −30 km | 0.67 | 0.87 |
W, −40 km | 0.65 | 0.83 | WNW, −40 km | 0.68 | 0.91 | NW, −40 km | 0.67 | 0.87 | NNW, −40 km | 0.67 | 0.85 |
W, −50 km | 0.63 | 0.81 | WNW, −50 km | 0.66 | 0.89 | NW, −50 km | 0.65 | 0.84 | NNW, −50 km | 0.64 | 0.83 |
Time (Hour) | Position | Central Air Pressure (hPa) | Maximum Wind Speed (m/s) | Maximum Wind Speed Radius (km) | Speed (km/h) | Direction of Movement |
---|---|---|---|---|---|---|
0 | 117.6° E, 16.3° N | 910 | 66 | 27 | 20 | WNW |
6 | 116.5° E, 16.6° N | 910 | 66 | 27 | 20 | WNW |
12 | 115.4° E, 16.8° N | 910 | 66 | 27 | 20 | WNW |
18 | 114.3° E, 17.1° N | 910 | 66 | 27 | 20 | WNW |
24 | 113.3° E, 17.4° N | 910 | 66 | 27 | 20 | WNW |
30 | 112.2° E, 17.7° N | 910 | 66 | 27 | 20 | WNW |
36 | 111.1° E, 18.0° N | 910 | 66 | 27 | 20 | WNW |
42 | 110.0° E, 18.2° N | 910 (landfall) | 66 | 27 | 20 | WNW |
48 | 108.9° E, 18.5° N | 950 | 48 | 41 | 20 | WNW |
Inundation Hazard Level | Inundation Depth (m) | Influence |
---|---|---|
Low (level 4) | <0.5 | the movement of vehicles and residents could be affected |
Moderate (level 3) | 0.5–1.2 | the safety of vehicles and children could be threatened |
High (level 2) | 1.2–3.0 | the vehicles and first floors of buildings could be inundated, posing a serious hazard to residents |
Extremely high (level 1) | >3.0 | the life and property of residents could be greatly threatened |
Land Type | Inundation Area (km2) | Proportion | ||||
---|---|---|---|---|---|---|
>3.0 m | 1.2–3.0 m | 0.5–1.2 m | <0.5 m | Total | ||
Coastal wetland | 0 | 2.5049 | 2.1623 | 0.3016 | 4.9688 | 33.54% |
Farmland | 0 | 0.5951 | 0.5848 | 0.2034 | 1.3832 | 9.34% |
Forest | 0 | 1.1665 | 0.7424 | 0.3029 | 2.2117 | 14.93% |
Hydrographic net | 0 | 2.2046 | 2.1548 | 0.7812 | 5.1406 | 34.70% |
Low shrub | 0 | 0.0252 | 0.0490 | 0.0656 | 0.1397 | 0.95% |
Residential area | 0 | 0.3404 | 0.5162 | 0.1118 | 0.9684 | 6.54% |
Total | 0 | 6.8366 | 6.2094 | 1.7664 | 14.8124 | 100% |
Proportion | 0% | 46.15% | 41.92% | 11.93% | 100% |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Fu, C.; Li, T.; Cheng, K.; Gao, Y. Inundation Hazard Assessment in a Chinese Lagoon Area under the Influence of Extreme Storm Surge. Water 2024, 16, 1967. https://doi.org/10.3390/w16141967
Fu C, Li T, Cheng K, Gao Y. Inundation Hazard Assessment in a Chinese Lagoon Area under the Influence of Extreme Storm Surge. Water. 2024; 16(14):1967. https://doi.org/10.3390/w16141967
Chicago/Turabian StyleFu, Cifu, Tao Li, Kaikai Cheng, and Yi Gao. 2024. "Inundation Hazard Assessment in a Chinese Lagoon Area under the Influence of Extreme Storm Surge" Water 16, no. 14: 1967. https://doi.org/10.3390/w16141967
APA StyleFu, C., Li, T., Cheng, K., & Gao, Y. (2024). Inundation Hazard Assessment in a Chinese Lagoon Area under the Influence of Extreme Storm Surge. Water, 16(14), 1967. https://doi.org/10.3390/w16141967