DOI QR코드

DOI QR Code

Drought analysis of Cheongmicheon watershed using meteorological, agricultural and hydrological drought indices

기상학적, 농업학적, 수문학적 가뭄지수를 이용한 청미천 유역의 가뭄 분석

  • Won, Kwang Jai (Dept. of Civil Engineering, Seoul National University of Science and Technology) ;
  • Chung, Eun-Sung (Dept. of Civil Engineering, Seoul National University of Science and Technology)
  • 원광재 (서울과학기술대학교 건설시스템디자인공학과) ;
  • 정은성 (서울과학기술대학교 건설시스템디자인공학과)
  • Received : 2016.02.11
  • Accepted : 2016.03.25
  • Published : 2016.06.30

Abstract

This study assessed drought of Cheongmicheon watershed from 1985 to 2015 according to duration. In order to quantify drought, we used meteorological and hydrological drought index. Standardized Precipitation Index(SPI) based on precipitation and Standardized Precipitation Evapotranspiration Index(SPEI) based on precipitation and evapotranspiration were applied as meteorological drought index. Palmer Drought Severity Index(PDSI) and Stream Drought Index(SDI) based on simulation of Soil and Water Assessment Tool(SWAT) model were applied as agricultural and hydrological drought index. As a result, in case average of extreme and averaged drought, 2014 and 2015 have the most vulnerable in all drought indices. Variation of drought showed different trend with regard to analysis of frequency. Also, the extreme and averaged drought have high correlation between drought indices excluding between PDSIs. However, each drought index showed different occurrence year and severity of drought Therefore, drought indices with various characteristics were used to analysis drought.

본 연구는 1985년부터 2015년까지 지속기간에 따른 청미천 유역의 가뭄을 분석하였다. 가뭄의 정량적 평가를 위해 기상학적 가뭄지수와 수문학적 가뭄지수를 사용하였다. 기상학적 가뭄지수로는 강수량을 변수로 하는 SPI(Standarized Precipitation Index)와 강수량과 증발산량을 변수로 하는 SPEI(Standarized Precipitation Evapotranspiration Index)를 사용하였다. SWAT 모형의 모의를 통해 도출된 결과를 바탕으로 농업학적 가뭄지수인 PDSI(Palmer Drought Severity Index)와 수문학적 가뭄지수인 SDI(Streamflow Drought Index)를 적용하였다. 산정 결과, 극한 및 평균 가뭄의 평균에서 2015년과 2014년이 가장 가뭄에 취약함이 확인되었다. 빈도분석에 따른 가뭄의 변동성은 서로 다른 형태를 보였다. 또한 상관분석에서 극한 가뭄 및 평균 가뭄은 PDSI를 제외한 SPI, SPEI, SDI 가뭄지수간에는 높은 상관관계가 확인되었다. 하지만 각 가뭄지수는 서로 다른 극한가뭄의 시기 및 강도를 보였다. 따라서 가뭄분석시 다양한 특성을 지닌 가뭄지수를 활용하는 것이 필요하다.

Keywords

References

  1. Banimahd, S.A., and Khalili, D. (2013) "Factors influencing Markov Chains Predictability characteristics, utilizing SPI, RDI, EDI and SPEI drought indices in different climatic zones." Water Resources Management, Vol. 27(11), pp. 3911-3928. https://doi.org/10.1007/s11269-013-0387-z
  2. Beven, K. (1989). "Changing ideas in hydrology-the case of physically-based models." Journal of. Hydrology, Vol. 105, pp. 157-172. https://doi.org/10.1016/0022-1694(89)90101-7
  3. Beven, K. (2002). "Towards an alternative blueprint for a physically based digitally simulated hydrologic response modelling system." Hydrological Processes, Vol. 16, pp. 189-206. https://doi.org/10.1002/hyp.343
  4. Du Pisani, C.G., Fouche, H.J., and Venter, J.C. (1998)."Assessing rangeland drought in South Africa." Agricultural Systems, Vol. 57, No. 3, pp. 367-380. https://doi.org/10.1016/S0308-521X(98)00024-9
  5. Heim, R.R. (2002). "A review of twentieth-centurydrought indices used in the United States." Bulletinof the American Meteorological Society, Vol. 83, No. 8, pp. 1149-1165. https://doi.org/10.1175/1520-0477(2002)083<1149:AROTDI>2.3.CO;2
  6. Hernandez, E.A., and Uddameri, V. (2013). "Standardized precipitation evaporation index (SPEI)-based drought assessment in semi-arid south Texas." Environmental Earth Sciences, pp. 1-11.
  7. Karamouz, M., Nazif, S., and Falahi, M. (2012). Hydrology and hydroclimatology: principles and applications.
  8. Keyantash, J., and Dracup, J. (2002). "The quantification of drought: an evaluation of drought indices." Bulletin of the American Meteorological Society, Vol. 83, No. 8, pp. 1167-1180. https://doi.org/10.1175/1520-0477(2002)083<1191:TQODAE>2.3.CO;2
  9. Lee, B.R., Sung, J.H., and Chung, E.S. (2015) "Comparison of meteorological drought and hydrological drought index." Journal of Korea Water Resources Association, Vol. 48, No. 1, pp. 69-78. https://doi.org/10.3741/JKWRA.2015.48.1.69
  10. McKee, T.B., Doeskin, N.J., and Kleist, J. (1993). Drought monitoring with multiple time scales." Proceeding of 9th Conference on Applied Climatology, American Meteorological Society, pp. 233-236.
  11. Morid, S., Smakhtin, V.U., and Moghadasi, M. (2006) "Comparsion of seven meteorological indices for drought monitoring in Iran. Int Journal or Climatol, Vol. 26, pp.971-985. https://doi.org/10.1002/joc.1264
  12. Nalbantis, I. (2008). "Evaluation of a hydrological drought index." European Water, Vol. 23, No. 24, pp. 67-77.
  13. Nalbantis, I, and Tsakiris, G. (2009). "Assessment of hydrological drought revisited." Water Resources Management, Vol. 23, pp. 881-897. https://doi.org/10.1007/s11269-008-9305-1
  14. Nash. J. E., and Sutcliffe, J. V. (1970). "River flow forecasting through conceptual models: Part I: A discussion of principles." Journal of Hydrology, 10(3), pp.283-290.
  15. Palmer, W, C. (1965). Meteorological drought, Research paper. No. 45, U.S. Weather Bureau.
  16. Smakhtin, V.U., and Hughes, D.A. (2007). "Automated estimation and analyses of meteorological drought characteristics from monthly rainfall data." Environment Modelling Software, Vol. 22, pp. 880-890. https://doi.org/10.1016/j.envsoft.2006.05.013
  17. Sorooshian, S., and Gupta, V. (1995). "Chapter 2: Model calibration." Computer Models of Watershed Hydrology, Singh VP, Publications, LLC, Highlands Ranch, CO, pp. 23-68.
  18. Sung, J.H., and Chung, E.S. (2014). "Development of streamflow drought severity-duration -frequency curves using the threshold level method." Hydrology and Earth System Sciences, Vol. 18, No. 9, pp. 3341-3351. https://doi.org/10.5194/hess-18-3341-2014
  19. Thornthwaite, C.W. (1948). "An approach toward a rational classification of climate." Geographical Review, Vol. 38, No. 1, pp. 55-94. https://doi.org/10.2307/210739
  20. Thornthwaite, C.W., and Mather, J.R. (1955). "The water balance." Publications in Climatology, Vol. 8, No. 1, pp. 1-104.
  21. Vicente-Serrano, S.M., Begueria, S., and Lopez-Moreno, J.I. (2010). "A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspira tion index." Journal of Climate, Vol. 23, No.7, pp. 1696-1718. https://doi.org/10.1175/2009JCLI2909.1
  22. Won, G.J., Chung, E.S., and Choi, S.U. (2015). "Parametric assessment of water use vulnerability variations using SWAT and Fuzzy TOPSIS coupled with entropy."Sustainability, Vol. 7, No. 9, 12052-12070. https://doi.org/10.3390/su70912052