Skip to main content

Extreme water level analysis at three stations on the coast of the Northwestern Pacific Ocean

Abstract

In this study, the data from three long-term observation stations, Aburatsu, Xiamen, and Hong Kong, which are located on the northwest Pacific Ocean coast, were analyzed to estimate the 100-year annual maximum water levels. The performances of four common frequency analysis methods, namely the Gumbel, Weibull, GEV, and GPD distributions, were evaluated. It is found that the GEV model performs best among these four distribution models in Hong Kong and Aburatsu, whereas the Gumbel distribution is the best at the Xiamen station. It is also found that the GEV model generally performs better than the Gumbel model in regard to the mean high correlation coefficient and the mean minimum root-mean-square error. Moreover, in this study, the r-largest value model was used to study temporal trends in the 50-year annual maximum water levels on the northwest Pacific coast over the past fifty years using the observation data of Hong Kong, Xiamen, and Aburatsu. The results show that there are two temporal features in the 50-year return levels at all three stations, with the first being an overall increasing trend over the whole period and the other being an oscillatory trend over the period of observation. The relationships between the temporal trends and the Pacific Decadal Oscillation (PDO), sea level rise, and change of typhoons were also analyzed in this paper. It is found that when the PDO index is shifted to be 4 years in advance, a significantly negative correlation will occur between the PDO index and the 50-year return levels. However, sea level rise and changes of typhoons cause the overall increase over the entire period.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

References

  • Anderson PL, Meerschaert MM (1998) Modeling river flows with heavy tails. Water Resour Res 34:2271–2280. doi:10.1029/98WR01449

    Article  Google Scholar 

  • Bengtsson L, Hodges KI, Esch M, Keenlyside N, Kornblueh L, Luo JJ, Yamagata T (2007) How may tropical cyclones change in a warmer climate? Tellus Ser A Dyn Meteorol Oceanogr 59A:539–561. doi:10.1111/j.1600-0870.2007.00251.x

    Article  Google Scholar 

  • Brown J, Souza A, Wolf J (2010) Surge modelling in the Eastern Irish Sea: present and future storm impact. Ocean Dyn 60:227–236. doi:10.1007/s10236-009-0248-8

    Article  Google Scholar 

  • Butler A, Heffernan JE, Tawn JA, Flather RA, Horsburgh KJ (2007) Extreme value is of decadal variations in storm surge elevations. J Mar Syst 67:189–200. doi:10.1016/j.jmarsys.2006.10.006

    Article  Google Scholar 

  • Chen J (1997) The impact of sea level rise on China’s coastal areas and its disaster hazard evaluation. J Coast Res 13:925–930

    Google Scholar 

  • Chow VT, Maidment DR, Mays LW (1988) Applied Hydrology. McGraw-Hill, New York

    Google Scholar 

  • Coles SG (2001) An Introduction to statistical modelling of extreme values. Springer, London

    Book  Google Scholar 

  • Cunnane C (1978) Unbiased plotting positions—a review. J Hydrol 37:205–222. doi:10.1016/0022-1694(78)90017-3

    Article  Google Scholar 

  • Dasgupta S, Laplante B, Murray S, Wheeler D (2009) Climate change and the future impact of storm-surge disasters in developing countries. Center for Global Development 182

  • Davison AC, Ramesh NI (2000) Local likelihood smoothing sample extremes. J R Stat Soc Ser B 92:191–208

    Article  Google Scholar 

  • De Michele C, Salvadori G (2005) Some hydrological applications of small sample estimators of generalized Pareto and extreme value distributions. J Hydrol 301:37–53. doi:10.1016/j.jhydrol.2004.06.015

    Article  Google Scholar 

  • Dong JX, Zhang TY, Fu X, Wu W, Zhao LD, Wu SH, Yu FJ (2008) Calculation of the storm surges in the Shacheng Bay in Fujian Province in 100 years return periods. Mar Sci Bull 27:9–16, in Chinese, English abstract

    Google Scholar 

  • Eastoe EF, Tawn JA (2010) Statistical models for overdispersion in the frequency of peaks over threshold data for a flow series. Water Resour Res 46:W02510. doi:10.1029/2009WR007757

    Article  Google Scholar 

  • Elsner JB, Kossin JP, Jagger TH (2008) The increasing intensity of the strongest tropical cyclones. Nature 455:92–95. doi:10.1038/nature07234

    Article  Google Scholar 

  • Emanuel KA (1987) The dependence of hurricane intensity on climate. nature 326:483–485. doi:10.1038/326483a0

    Article  Google Scholar 

  • Esteban M, Webersik C, Shibayama T (2009) Effect of a global warming-induced increase in typhoon intensity on urban productivity in taiwan. Sustain Sci 4:151–163. doi:10.1007/s11625-009-0089-x

    Article  Google Scholar 

  • Fan J, Farmen M, Gijbels I (1998) Local maximum likelihood estimation and inference. J R Stat Soc Ser B (Stat Methodol) 60:591–608

    Article  Google Scholar 

  • FEMA (Federal Emergency Management Agency of the United States), (2005) Final draft guidelines for coastal flood hazard analysis and mapping for the Pacific Coast of the United States. FEMA Study Contractor, Northwest Hydraulic Consultants. (https://www.fema.gov/national-flood-insurance-program-flood-hazard-mapping/coastal-flood-hazard-mapping-requirements)

  • Haigh ID, Nicholls R, Wells N (2010) A comparison of the main methods for estimating probabilities of extreme still water levels. Coast Eng 57:839–849. doi:10.1016/j.coastaleng.2010.04.002

    Article  Google Scholar 

  • Hall P, Tajvidi N (2000) Nonparametric analysis of temporal trend when fitting parametric models to extreme-value data. Stat Sci, 153–167. doi: 10.1214/ss/1009212755

  • Hosking JRM, Wallis JR (1987) Parameter and quantile estimation for the generalized pareto distribution. Technometrics 29:339–349

    Article  Google Scholar 

  • Hou JM, Yu FJ, Yuan Ye FX (2011) Spatial and temporal distribution of red tropical storm surge disasters in China. Mar Sci Bull 30:535–539 (in Chinese with English abstract)

    Google Scholar 

  • Houghton JT, Ding Y, Griggs DJ, Noguer M, Van Der Linden PJX, Dai KM, Johnson CA (2001) Climate Change 2001: the scientific basis. Contribution of Working Group 1 to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press

  • Howard T, Lowe J, Horsburgh K (2010) Interpreting century-scale changes in North Sea storm surge climate derived from coupled model simulations. J Clim 23:6234–6247. doi:10.1175/2010JCLI3520.1

    Article  Google Scholar 

  • Huang W, Xu S, Nnaji S (2008) Evaluation of GEV model for frequency analysis of annual maximum water levels in the coast of United States. Ocean Eng 35:1132–1147. doi:10.1016/j.oceaneng.2008.04.010

    Article  Google Scholar 

  • IPCC (2007) Climate Change 2007: The physical science basis. Cambridge University Press, C. N. Y., ed.

  • IPCC (2013) Climate change 2014: The physical science basis. Cambridge University Press, C. N. Y., ed.

  • Irish JL, Resio DT, Ratcliff JJ (2008) The influence of storm size on hurricane surge. J Phys Oceanogr 38:2003–2013. doi:10.1175/2008JPO3727.1

    Article  Google Scholar 

  • Jia GD, Chen FJ, Peng P (2008) Sea surface temperature differences between the Western Equatorial Pacific and Northern South China Sea since the Pliocene and their paleoclimatic implications. Geophys Res Lett 35:L18609. doi:10.1029/2008GL034792

    Article  Google Scholar 

  • Katz RW, Parlange MB, Naveau P (2002) Statistics of extremes in hydrology. Adv Water Resour 25:1287–1304. doi:10.1016/S0309-1708(02)00056-8

    Article  Google Scholar 

  • Kottegoda N, Kottegoda NT (1997) Probability, statistics, and reliability for civil and environmental engineers. McGraw-Hill Companies

  • Leadbetter MR (1983) Extremes and local dependence in stationary sequences. Z Wahrsch Verw Gebiete 65:291–306

    Article  Google Scholar 

  • Letetrel C, Marcos M, Martín MB, Woppelmann G (2010) Sea level extremes in Marseille (NW Mediterranean) during 1885–2008. Cont Shelf Res 30:1267–1274. doi:10.1016/j.csr.2010.04.003

    Article  Google Scholar 

  • Li FL, Jiao ML, 2012 Decadal variability of SSTA in the South China Sea and its relationship with PDO. Marine Science Bulletin (In Chinese with English abstract) 31

  • Lin N, Emanuel KA, Smith JA, Vanmarcke E (2010) Risk assessment of hurricane storm surge for New York City. J Geophys Res-Atmos 115:D18121. doi:10.1029/2009JD013630

    Article  Google Scholar 

  • Lin C, Ho C, Zheng Q, Huang S, Kuo N (2011) Variability of sea surface temperature and warm pool area in the South China Sea and its relationship to the Western Pacific warm pool. J Oceanogr 67:719–724. doi:10.1007/s10872-011-0072-x

    Article  Google Scholar 

  • Lombard A, Cazenave A, Dominh K, Cabanes C, Nerem RS (2005) Thermosteric sea level rise for the past 50 years; comparison with tide gauges and inference on water mass contribution. Glob Planet Chang 48:303–312. doi:10.1016/j.gloplacha.2005.02.007

    Article  Google Scholar 

  • Mantua NJ, Hare SR, Zhang Y, Wallace JM, Francis RC (1997) A Pacific interdecadal climate oscillation with impacts on salmon production. Bull Am Meteorol Soc 78:1069–1079. doi:10.1175/1520-0477(1997)078<1069:APICOW>2.0.CO;2

    Article  Google Scholar 

  • Marcos M, Jordà G, Gomis D, Pérez B (2011) Changes in storm surges in Southern Europe from a regional model under climate change scenarios. Glob Planet Chang 77:116–128. doi:10.1016/j.gloplacha.2011.04.002

    Article  Google Scholar 

  • Mcinnes KL, Walsh KJE, Hubbert GD, Beer T (2003) Impact of sea-level rise and storm surges on a coastal community. Nat Hazards 30:187–207

    Article  Google Scholar 

  • Meehl GA, Hu A, Santer BD (2009) The mid-1970s climate shift in the pacific and the relative roles of forced versus inherent decadal variability. J Clim 22:780–792. doi:10.1175/2008JCLI2552.1

    Article  Google Scholar 

  • Méndez FJ, Menéndez M, Luceño A, Losada IJ (2007) Analyzing monthly extreme sea levels with a time-dependent GEV model. J Atmos Ocean Technol 24:894–911

    Article  Google Scholar 

  • Menéndez M, Woodworth PL (2010) Changes in extreme high water levels based on a quasi-global tide-gauge data set. J Geophys Res 115:C10011. doi:10.1029/2009JC005997

    Article  Google Scholar 

  • Menéndez M, Méndez FJ, Losada IJ, Graham NE (2008) Variability of extreme wave heights in the northeast Pacific Ocean based on buoy measurements. Geophys Res Lett 35:L22607. doi:10.1029/2008GL035394

    Article  Google Scholar 

  • Miller L, Douglas BC (2004) Mass and volume contributions to twentieth-century global sea level rise. Nature 428:406–409. doi:10.1038/nature02309

    Article  Google Scholar 

  • Mochizuki T, Ishii M, Kimoto M, Chikamoto Y, Watanabe M, Nozawa T, Sakamoto TT, Shiogama H, Awaji T, Sugiura N, Toyoda T, Yasunaka S, Tatebe H (2010) Pacific decadal oscillation hindcasts relevant to near-term climate prediction. Proc Natl Acad Sci 107:1833–1837. doi:10.1073/pnas.0906531107

    Article  Google Scholar 

  • Morris JT, Sundareshwar PV, Nietch CT, Kjerfve B, Cahoon DR (2002) Responses of coastal wetlands to rising sea level. Ecology 83:2869–2877

    Article  Google Scholar 

  • Nicholls RJ (2002) Analysis of global impacts of sea-level rise: a case study of flooding. Phys Chem Earth A B C 27:1455–1466. doi:10.1016/S1474-7065(02)00090-6

    Article  Google Scholar 

  • Nielsen P (2009) How storm size matters for surge height. Coast Eng 56:1002–1004. doi:10.1016/j.coastaleng.2009.02.006

    Article  Google Scholar 

  • Park J, Jung H, Kim R, Oh J (2001) Modelling summer extreme rainfall over the Korean peninsula using Wakeby distribution. Int J Climatol 21:1371–1384. doi:10.1002/joc.701

    Article  Google Scholar 

  • Pickands III J (1975) Statistical inference using extreme order statistics. Ann Stat 119–131

  • Rybczyk J, Cahoon D (2002) Estimating the potential for submergence for two wetlands in the Mississippi River Delta. Estuar Coasts 25:985–998

    Article  Google Scholar 

  • Sobey RJ (2005) Extreme low and high water levels. Coast Eng 52:63–77. doi:10.1016/j.coastaleng.2004.09.003

    Article  Google Scholar 

  • Tawn JA (1988) An extreme-value theory model for dependent observations. J Hydrol 101:227–250. doi:10.1016/0022-1694(88)90037-6

    Article  Google Scholar 

  • Tian B, Zhang L, Wang X, Zhou Y, Zhang W (2010) Forecasting the effects of sea-level rise at Chongming Dongtan Nature Reserve in the Yangtze Delta Shanghai, China. Ecol Eng 36:1383–1388. doi:10.1016/j.ecoleng.2010.06.016

    Article  Google Scholar 

  • Tibshirani RJ, Hastie TJ (1987) Local likelihood estimation. J Am Stat Assoc 559–567

  • Tsimplis MN, Blackman D (1997) Extreme sea-level distribution and return periods in the Aegean and Ionian Seas. Estuar Coast Shelf Sci 44:79–89. doi:10.1006/ecss.1996.0126

    Article  Google Scholar 

  • Van G.P, Neykov NM (1998) Regional frequency analysis of extreme water levels along the dutch coast using L-moments: a preliminary study, Stochastic models of hydrological processes and their applications to problems of environmental preservation 14–20

  • Viessman WJ, Lewis GL (1996) Introduction to Hydrology. Harper Collins College Publishers, New York

    Google Scholar 

  • Wakelin SL, Woodworth PL, Flather RA, Williams JA (2003) Sea-level dependence on the NAO over the NW European Continental Shelf. Geophys Res Lett 30:1403. doi:10.1029/2003GL017041

    Article  Google Scholar 

  • Walton TL (2000) Distributions for storm surge extremes. Ocean Eng 27:1279–1293. doi:10.1016/S0029-8018(99)00052-9

    Article  Google Scholar 

  • Webster PJ, Holland GJ, Curry JA, Chang HR (2005) Changes in tropical cyclone number, duration, and intensity in a warming environment. Science 309:1844–1846. doi:10.1126/science.1116448

    Article  Google Scholar 

  • Wu L, Wang B (2008) What has changed the proportion of intense hurricanes in the last 30 years? J Clim 21:1432–1439. doi:10.1175/2007JCLI1715.1

    Article  Google Scholar 

  • Yan Y, Qi Y, Zhou W (2012) Variability of tropical cyclone occurrence date in the South China Sea and its relationship with SST warming. Dyn Atmos Oceans 6:45–59. doi:10.1016/j.dynatmoce.2012.05.001

    Article  Google Scholar 

  • Zhang H, Sheng J (2015) Examination of extreme sea levels due to storm surges and tides over the northwest Pacific Ocean. Cont Shelf Res 93:81–97. doi:10.1016/j.csr.2014.12.001

    Article  Google Scholar 

  • Zhang WZ, Hu JY, Shang SP, Chen MN, She WM (2004) On the characteristics of storm surges along Fujian coast. Mar Sci Bull 23(3):12–19, in Chinese, English abstract

    Google Scholar 

  • Zhang Q, Xu C, Chen YD, Liu C (2009) Extreme value analysis of annual maximum water levels in the Pearl River Delta China. Front Earth Sci China 3:154–163

    Article  Google Scholar 

  • Zhang WZ, Shi FY, Hong HS, Shang SP, Kirby JT (2010) Tide-surge interaction intensified by the Taiwan Strait, J Geophys Res Oceans, C06012. doi: 10.1029/2009JC005762

  • Zhou J, Yan X (2008) Frequency analysis on annual maximum water level in Huangpu River. In Conference of Association of Professional Committee of China Maritime 482–488

Download references

Acknowledgments

This work is supported by Public Science and Technology Research Funds Projects of Ocean (201305020–4) and NSFC-Shandong Joint Fund for Marine Science Research Centers (grant no. U1406401). We acknowledge the comments of two anonymous reviewers and appreciate the suggestions of the associate editor.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wensheng Jiang.

Additional information

Responsible Editor: Bruno Castelle

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Feng, J., Jiang, W. Extreme water level analysis at three stations on the coast of the Northwestern Pacific Ocean. Ocean Dynamics 65, 1383–1397 (2015). https://doi.org/10.1007/s10236-015-0881-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10236-015-0881-3

Keywords