Natural Hazards

, Volume 73, Issue 3, pp 1663–1678 | Cite as

Evaluation of drought and flood risks in a multipurpose dam under climate change: a case study of Chungju Dam in Korea

  • Soojun Kim
  • Jaewon Kwak
  • Hui Seong Noh
  • Hung Soo Kim
Original Paper

Abstract

The purpose of this study was to evaluate the effects of climate change on the drought and flood risks of a multipurpose dam. To achieve this, A2 climate change scenarios of RegCM3 were collected about Chungju Dam in Korea. To analyze drought risks, weather data obtained by the statistical downscaling method were entered to produce runoff series by runoff modeling and water balance was analyzed based on water use scenarios to review changes in the storage volume under climate change. To analyze flood risks, changes in water levels of the dam in future flood seasons were reviewed based on the current dam operation method. The results of the review indicated that both the drought and the flood risks of the dam would increase in the future. The reason was considered to be the movement of the flood season’s runoff characteristics from July and August to August and September because of climate change. Therefore, for climate change adaptation planning, not only quantitative changes in hydrologic values but also changes in temporal characteristics should be considered and given importance.

Keywords

Climate change Drought Flood Water balance Reservoir operation method 

References

  1. Andersson L, Wilk J, Todd MC, Hughes DA, Earle A, Kniveton D, Layberry R, Savenije HG (2006) Impact of climate change and development scenarios on flow patterns in the Okavango River. J Hydrol 331:43–57CrossRefGoogle Scholar
  2. Anthes RA, Hsie EY, Kuo YH (1987) Description of the Penn State/NCAR Mesoscale Model Version 4 (MM4). NCAR Tech. rep. TN-282+STR, 66Google Scholar
  3. Clark CO (1945) Storage and the unit hydrograph. Trans Am Soc Civ Eng 110:1419–1446Google Scholar
  4. Cuo L, Lettenmaier DP, Alberti M, Richey JE (2009) Effects of a century of land cover and climate change on the hydrology of the Puget Sound basin. Hydrol Process 23(6):907–933CrossRefGoogle Scholar
  5. Dunn SM, Brown I, Sample J, Post H (2012) Relationships between climate, water resources, land use and diffuse pollution and the significance of uncertainty in climate change. J Hydrol 434–435:19–35CrossRefGoogle Scholar
  6. Emanuel KA (1991) A scheme for representing cumulus convection in large-scale models. J Atmos Sci 48:2313–2335CrossRefGoogle Scholar
  7. Franczyk J, Chang H (2009) The effects of climate change and urbanization on the runoff of the Rock Creek basin in the Portland metropolitan area, Oregon, USA. Hydrol Process 23(6):805–815CrossRefGoogle Scholar
  8. Garbrecht J, Martz LW (1993) Network and subwatershed parameters extracted from digital elevation models: the Bill’s Creek experience. Water Resour Bull 29(6):909–916CrossRefGoogle Scholar
  9. Giorgi F, Bi X, Qian Y (2003) Indirect vs. direct effects of anthropogenic sulfate on the climate of East Asia as simulated with a regional coupled climate-chemistry/aerosol model. Clim Change 58(3):345–376CrossRefGoogle Scholar
  10. Gosling SN, Taylor RG, Arnell NW, Todd MC (2011) A comparative analysis of projected impacts of climate change on river runoff from global and catchment-scale hydrological models. Hydrol Earth Syst Sci 15:279–294CrossRefGoogle Scholar
  11. Grell GA (1993) Prognostic evaluation of assumptions used by cumulus parameterizations. Mon Weather Rev 121(3):764–787CrossRefGoogle Scholar
  12. Grell GA, Dudhia J, Stauffer DR (1994) Description of the fifth generation Penn State/NCAR Mesoscale Model (MM5). NCAR Tech. rep. TN-398+STR, 121Google Scholar
  13. Holtslag AAM, De Bruin EIF, Pan HL (1990) A high resolution air mass transformation model for short-range weather forecasting. Mon Weather Rev 118:1561–1575CrossRefGoogle Scholar
  14. Hosking JRM (1985) Maximum-likelihood estimation of the parameter of the generalized extreme-value distribution. Appl Stat 34(3):301–310CrossRefGoogle Scholar
  15. IPCC (2000) Special Report on Emissions Scenarios (SRES)Google Scholar
  16. IPCC (2007) Climate change 2007, the fourth assessment report (AR4) of the intergovernmental panel on climate changeGoogle Scholar
  17. IPCC (2012) Managing the risks of extreme events and disasters to advance climate change adaptation (SREX)Google Scholar
  18. Jha M, Pan Z, Takle ES, Gu R (2003) The impacts of climate change on stream flow in the upper Mississippi river basin: a regional climate model perspective. J Geophys Res 109Google Scholar
  19. Jha M, Arnold JG, Gassman PW, Gu R (2004) Climate change sensitivity assessment on upper Mississippi river basin streamflows using SWAT, Working Paper 04-WP 353, Center for Agricultural and Rural Development, Iowa State UniversityGoogle Scholar
  20. Kiehl JT, Hack JJ, Bonan GB, Boville BA, Briegleb BP, Williamson DL, Rasch PJ (1996) Description of the NCAR community climate model (CCM3), technical report TN-420?STR. NCAR, Boulder, p 152Google Scholar
  21. Kim SJ (2011) Impact of climate change on water resources and ecological habitat in a river basin. Inha University, Doctoral DissertationGoogle Scholar
  22. Kim BS, Kim HS, Seoh BH, Kim NW (2007) Impact of climate change on water resources in Yongdam Dam Basin, Korea. Stoch Env Res Risk Assess 21(4):355–357CrossRefGoogle Scholar
  23. Kim SJ, Lim HJ, Park GA, Park MJ, Kwon HJ (2008) Assessment of future climate change impact on DAM inflow using SLURP hydrologic model and CA-Markov technique. Korean J Remote Sens 24(1):25–33Google Scholar
  24. Kim U, Jagath J, Kaluarachchi (2009) Climate change impacts on water resources in the Upper Blue Nile River Basin, Ethiopia. J Am Water Resour As 45(6):1361–1378CrossRefGoogle Scholar
  25. Kite GW (2007) Manual for the SLURP Hydrologic Model Version 12.7Google Scholar
  26. Kwak J, Kim DG, Lee JS, Kim HS (2012) Hydrological drought analysis using Copula Theory. KSCE J Civ Eng B 32(3B):161–168Google Scholar
  27. Kwon HH, Kim BS (2009) Development of statistical downscaling model using nonstationary Markov chain. J Korea Water Resour As 42(3):213–225Google Scholar
  28. Kyoung MS, Lee YW, Kim HS, Kim BS (2009) Assessment of climate change effect on temperature and drought in Seoul: based on the AR4 SRES A2 scenario. KSCE J Civ Eng B 30(2B):267–276Google Scholar
  29. Lee HL (2005) Revaluation of reservoir operation guideline for flood season considering flood control and conservational water use. Chungnam National University, Master thesisGoogle Scholar
  30. Martz LW, Garbrecht J (1999) Automated extraction of drainage network and watershed data from digital elevation models. Water Resour Bull 29(6):901–908CrossRefGoogle Scholar
  31. Ministry of Construction & Transportation, Korea (2006) Long-term comprehensive water resources plan (2006–2020)Google Scholar
  32. Mishra AK, Singh VP (2009) Analysis of drought severity-area-frequency curves using a general circulation model and scenario uncertainty. J Geophys Res 114: D06120. doi:10.1029/2008JD010986
  33. Mishra V, Keith AC, Shraddhanand S (2010) Assessment of drought due to historic climate variability and projected future climate change in the Midwestern United States. J Hydrometeorol 11(1):46–68CrossRefGoogle Scholar
  34. Mpelasoka F, Hennessy K, Jones R, Bates B (2007) Comparison of suitable drought indices for climate change impacts assessment over Australia: towards resource management. Int J Climatol 28(10):1283–1292CrossRefGoogle Scholar
  35. National Emergency Management Agency in Korea (2011) Environmental change prediction of natural disaster and design criteria of the measures for disaster prevention according to climate changeGoogle Scholar
  36. National Emergency Management Agency in Korea (2013) Establishment of national drought disaster information systemGoogle Scholar
  37. Pal JS, Small EE, Eltahir EAB (2000) Simulation of regional-scale water and energy budgets: representation of subgrid cloud and precipitation processes within RegCM. J Geophys Res 105:29579–29594CrossRefGoogle Scholar
  38. Pal JS, Giorgi F, Bi X, Elguindi N, Solomon F, Gao X, Francisco R, Zakey A, Winter J, Ashfaq M, Syed F, Bell JL, Diffanbaugh NS, Kamacharya J, Konare A, Martinez D, da Rocha RP, Sloan LC, Steiner A (2007) The ICTP RegCM3 and RegCNET: regional climate modeling for the developing world. Bull Am Meteorol Soc 88:1395–1409CrossRefGoogle Scholar
  39. Stewart IT, Cayan DR, Dettinger MD (2005) Changes towards earlier streamflow timing across Western North America. J Clim 18:1136–1155CrossRefGoogle Scholar
  40. UNISDR (the United Nations International Strategy for Disaster Reduction) (2008) Climate change and disaster risk reductionGoogle Scholar
  41. World Meteorological Organization (2009) Guidelines on analysis of extremes in a changing climate in support of informed decisions for adaptationGoogle Scholar
  42. Yates D (2005) WEAP21—A demand-, priority-, and preference-driven water planning model: part 1: model characteristics. Water Int 30:487–500CrossRefGoogle Scholar
  43. Yu RMS, Osborn T, Conway D (2012) European drought under climate change and an assessment of the uncertainties in projections. EGU General Assembly 2012, EGU, Vienna, Austria, p 563Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Soojun Kim
    • 1
  • Jaewon Kwak
    • 2
  • Hui Seong Noh
    • 2
  • Hung Soo Kim
    • 2
  1. 1.Columbia Water Center, Earth InstituteColumbia UniversityUpper ManhattanUSA
  2. 2.Department of Civil EngineeringInha UniversityIncheonSouth Korea

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