Journal of Korean Society of Coastal and Ocean Engineers (한국해안·해양공학회논문집)

Korean Society of Coastal and Ocean Engineers (한국해안·해양공학회)
권호 표지
DOI QR코드

DOI QR Code

A Study on Trend Analysis in Sea Level Data Through MK Test and Quantile Regression Analysis

MK 검정 및 분위회귀분석을 통한 해수면 자료의 경향성 평가에 관한 연구

  • Uranchimeg, Sumiya (Department of Civil Engineering, Chonbuk National University) ;
  • Kim, Yong-Tak (Department of Civil Engineering, Chonbuk National University) ;
  • Kwon, Hyun-Han (Department of Civil Engineering, Chonbuk National University) ;
  • Hwang, Kyu-Nam (Department of Civil Engineering, Chonbuk National University)
  • Received : 2015.03.09
  • Accepted : 2015.04.04
  • Published : 2015.04.30
Download PDF
⟨ Previous Next ⟩

Abstract

Population and urban development along the coast is growing in South Korea, and particularly sea level rise is likely to increase the vulnerability of coastal areas. This study aims to investigate the sea level rise through Mann-Kendall(MK) test, ordinary linear regression(OR) and quantile regression analysis(QRA) with sea level data at the 20 tide stations along the coast of Korean Peninsula. First, statistically significant long-term trends were analysed using a non-parametric MK test and the test indicated statistically significant trends for 18 and 10 stations at the 5% significance level in the annual mean value of sea level and the annual maximum value of sea level, respectively. The QRA method showed better performance in terms of characterizing the degree of trend. QRA showed that an average annual rise in mean sea level is about 1-6 mm/year, and an average rise in maximum sea level is about 1-20 mm. It was found that upward convergent and upward divergent were a representative change given the nine-category distributional changes. We expect that in future work we will address nonstationarities with respect to sea level that were identified above, and develop a nonstationary frequency analysis with climate change scenarios.

우리나라의 연안은 도시개발, 인구증가가 지속적으로 나타나고 있으며, 이러한 점에서 해수면 상승으로 인한 연안재해 취약성이 가중될 것으로 전망되고 있다. 본 연구에서는 우리나라 연안의 20개 지역의 조위자료를 바탕으로 Mann-Kendall(MK) 검정, 선형회귀분석(OR), 분위회귀분석(QRA) 등을 이용하여 해수면상승에 대한 분석을 수행하였다. MK 검정결과 연평균조위의 경우 18개 지점에서 경향성이 통계적으로 유의한 것으로 분석되었으며, 연최대치의 경우에도 10개 지점에서 경향성이 통계적으로 유의(p < 0.05)한 것으로 평가되었다. QRA 방법을 이용하여 해수면의 경향성을 분위별로 평가한 결과 기존 회귀분석 방법에 비해 다각적인 경향성 검토가 가능하였다. QRA분석 결과 연평균해수면은 매년 1-6 mm의 범위에서 상승하고 있으며, 연최대해수면의 경우 1-20 mm의 범위에서 증가경향이 나타나고 있음을 확인할 수 있었다. 우리나라의 해수면상승의 경우 대부분 상향수렴 및 상향발산의 형태를 가지는 경향성을 나타내고 있었다. 향후 연구로서 이러한 경향성을 기반으로 연최대해수면 자료에 대한 비정상성빈도해석 절차의 개발 및 적용이 필요할 것으로 판단된다.

Keywords

References

  1. Cho, K.W., Maeng, J.H. (2007). Some Thoughts on Direction to Cope with the Sea level Rise in Korea. Journal of the Korean Society for Marine Environmental Engineering, 10(4), 227-234.
  2. Fangfang, ZHAO. Zongxue, X.U. and Junxiong, HUANG. (2007). Long-Term Trend and Abrupt Change for Major Climate Variables in the Upper Yellow River Basin. ACTA METEOROLOGICA SINICA, 21, 204-214.
  3. Hao, L. and Naiman, D.Q. (2007). Quantile regression. Sage Publications. Inc. CA. USA.
  4. Hirsch, R.M. and Slack, J.R. (1984). A Nonparametric Trend Test for Seasonal Data With Serial Dependence. WATER RESOURCES RESEARCH, 20(6), 727-732. https://doi.org/10.1029/WR020i006p00727
  5. IPCC, (2013): Summary for Policymakers. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
  6. Jang, H.B., Hong, K.H. (1991). Impact of Sea Level Rise and Coastal Area. Research Notes, 6(2), 407.
  7. KENDALL, M. (1975). Multivariate analysis. Charles Griffin. Londres, 0-85264-234-2
  8. Kendall, M. and Gibbons, J.D. (1990). Rank correlation methods. E.Arnold. London., 260.
  9. Khaled, H.H. and Rao, A.R. (1998). A modified Mann-Kendall trend test for autocorrelated data. Journal of Hydrology, 204, 182-196. https://doi.org/10.1016/S0022-1694(97)00125-X
  10. Kim, G.S. (2006). Review of Statistical Methods for Hydrologic - Meteorological Data Analysis. 2006 Subcommittee Research Task Report, 373-398.
  11. Kim, M.S. (2013). A study on legal issues from sea level rise which will have an effect on maritime delimitation and legal status of islands. KOREA MARITIME INSTITUTE. Ocean Policy Research., 28(2), 1-40.
  12. Koenker, R. (2005). Quantile regression. Cambridge Univ Pr. New York.
  13. Lee, D.W., Bu, Y.S. (2011). Analysis on Effect Construction Facilities Depending on a Scenario of Sea Level Rise around Jeju Coastal Area. Korean Society of Civil Engineers, 31(3), 267-274.
  14. Lee, S.Y., Choi, J.M. (2011). Analysis for Economic Cost of Sea Level Rise - Case Study: Haeundae Gu, Busan -. Journal of Korean Geographical Society, 46(5), 597-607.
  15. Mann, H.B. (1945). Nonparametric Tests Against Trend. Econometrica, 13(3), 245-259 . https://doi.org/10.2307/1907187
  16. Nicholls, R.J. Wong, P.P. Burkett, V. Woodroffe, C.D. and Hay, J. (2008). Climate change and coastal vulnerability assessment: scenarios for integrated assessment. Sustain Sci, 3:89-102, DOI 10.1007/s11625-008-0050-4.
  17. Oh, J.S., Jang, D.W., Kim, H.S., Seo, B.H. (2005). A study on Trend Analysis of Time Series Data. Korean Society of Civil Engineers, 1408-1411.
  18. Park, Y.K. (2012). The Problem of Rising Sea Levels and Ocean Jurisdiction Range. Chonbuk Law Review., 37 December 2012, pp. 49-70.
  19. So, B.J., Kwon, H.H., An, J.H. (2012). Trend Analysis of Extreme Precipitation Using Quantile Regression. Korea Water Resources Association, 45(8), 815-826. https://doi.org/10.3741/JKWRA.2012.45.8.815
  20. Titus, J.G., Hudgens, D.E., Trescott, D.L., Craghan, M., Nuckols, W.H., Hershner, C.H., Kassakian, J.M., Linn, C.J., Merritt, P.G., McCue, T.M., O'Connell, J.F., Tanski, J. and Wang, J. (2009). State and local governments plan for development of most land vulnerable to rising sea level along the US Atlantic coast. Environ. Res. Lett, 4 044008, 7. https://doi.org/10.1088/1748-9326/4/4/044008
  21. Yu, Y.S. Zou, S. and Whittemore, D. (1993). Non-parametric trend analysis of water quality data of rivers in Kansas. Journal of Hydrology, 150, 61-80, 0022-1694/93/$06.00. https://doi.org/10.1016/0022-1694(93)90156-4
  22. Yuk, G.H., Jung, J.H., An, Y.S. (2011). A Study on the Coastal Vulnerability Assessment Model to Sea Level Rise. Economy, Humanities and Social Green Growth Research Comprehensive Research Series, 11-02-65, Basic Research 2011-13.

Cited by

  1. Hierarchical Bayesian Model Based Nonstationary Frequency Analysis for Extreme Sea Level vol.28, pp.1, 2016, https://doi.org/10.9765/KSCOE.2016.28.1.34