DOI QR코드

DOI QR Code

미래 기후변화에 따른 농업용 저수지 용수공급의 불확실성

Uncertainty of Water Supply in Agricultural Reservoirs Considering the Climate Change

  • 남원호 ;
  • 홍은미 (서울대학교 농업생명과학연구원) ;
  • 최진용 (서울대학교 조경.지역시스템공학부, 농업생명과학연구원)
  • 투고 : 2013.08.08
  • 심사 : 2014.02.06
  • 발행 : 2014.03.31

초록

The impact and adaption on agricultural water resources considering climate change is significant for reservoirs. The change in rainfall patterns and hydrologic factors due to climate change increases the uncertainty of agricultural water supply and demand. The quantitative evaluation method of uncertainty based on agricultural water resource management under future climate conditions is a major concern. Therefore, it is necessary to improve the vulnerability management technique for agricultural water supply based on a probabilistic and stochastic risk evaluation theory. The objective of this study was to analyse the uncertainty of water resources under future climate change using probability distribution function of water supply in agricultural reservoir and demand in irrigation district. The uncertainty of future water resources in agricultural reservoirs was estimated using the time-specific analysis of histograms and probability distributions parameter, for example the location and the scale parameter. According to the uncertainty analysis, the future agricultural water supply and demand in reservoir tends to increase the uncertainty by the low consistency of the results. Thus, it is recommended to prepare a resonable decision making on water supply strategies in terms of using climate change scenarios that reflect different future development conditions.

키워드

참고문헌

  1. Bae, D. H., I. W. Jung, B. J. Lee, and M. H. Lee, 2011. Future Korean water resources projection considering uncertainty of GCMs and hydrological models. Journal of the Korean Water Resources Association 44(5): 389-406 (in Korean). https://doi.org/10.3741/JKWRA.2011.44.5.389
  2. Chung, S. O., 2009. Prediction of paddy irrigation demand in Nakdong river basin using regional climate model outputs. Journal of the Korean Society of Agricultural Engineers 51(4): 7-13 (in Korean).
  3. Doorenbos, J., and W. O. Pruitt, 1977. Guidelines for Predicting Crop Water Requirements. FAO Irrigation and Drainage Paper 24, FAO, Rome.
  4. Giorgi, F., and L. O. Mearns, 2002. Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the "Reliability Ensemble Averaging (REA) method". Journal of Climate 15(10): 1141-1158. https://doi.org/10.1175/1520-0442(2002)015<1141:COAURA>2.0.CO;2
  5. Goodess, C. M., 2013. How is the frequency, location and severity of extreme events likely to change up to 2060?. Environmental Science and Policy 27: 4-15. https://doi.org/10.1016/j.envsci.2012.04.001
  6. Griffiths, G. M., L. E. Chambers, M. R. Haylock, M. J. Manton, N. Nicholls, H. J. Baek, Y. Choi, P. M. Della-Marta, A. Gosai, N. Iga, R. Lata, V. Laurent, L. Maitrepierre, H. Nakamigawa, N. Ouprasitwong, D. Solofa, L. Tahani, D. T. Thuy, L. Tibig, B. Trewin, K. Vediapan, and P. Zhai, 2005. Change in mean temperature as a predictor of extreme temperature change in the Asiapacific region. International Journal of Climatology 25: 1301-1330. https://doi.org/10.1002/joc.1194
  7. Hwang, S., Y. G. Her, and S. Chang, 2013. Uncertainty in regional climate change impact assessment using bias-correction technique for future climate scenarios. Journal of the Korean Society of Agricultural Engineers 55(4): 95-106 (in Korean). https://doi.org/10.5389/KSAE.2013.55.4.095
  8. Jee, Y. K., J. H. Lee, and S. D. Kim, 2012. Climate change impacts on agricultural water in Nakdong-river watershed. Journal of the Korean Society of Agricultural Engineers 54(3): 149-157 (in Korean). https://doi.org/10.5389/KSAE.2012.54.3.149
  9. Kang, D. S., T. W. Kim, and J. H. Ahn, 2013. Water resources infrastructure: sustainability and resilience. Journal of Korean Society of Hazard Mitigation 13(1): 309-315 (in Korean). https://doi.org/10.9798/KOSHAM.2013.13.1.309
  10. Kim, B. S., J. K. Lee, H. S. Kim, and J. W. Lee, 2011. Non-stationary frequency analysis with climate variability using conditional generalized extreme value distribution. Journal of Wetlands Research 13(3): 499-514 (in Korean).
  11. Kim, D. Y., S. H. Lee, Y. J. Hong, E. J. Lee, and S. J. Im, 2010. The determination of probability distributions of annual, seasonal and monthly precipitation in Korea. Korean Journal of Agricultural and Forest Meteorology 12(2): 83-94 (in Korean). https://doi.org/10.5532/KJAFM.2010.12.2.083
  12. Kim, G. S. and G. C. Lee, 2012. Application of a nonstationary frequency analysis method for estimating probable precipitation in Korea. Journal of the Korean Society of Agricultural Engineers 54(5): 141-153 (in Korean).
  13. Klein Tank, A. M. G., and G. P. Konnen, 2003. Trends in indices of daily temperature and precipitation extremes in Europe, 1946-99. Journal of Climate 16: 3665-3680. https://doi.org/10.1175/1520-0442(2003)016<3665:TIIODT>2.0.CO;2
  14. Kwon, H. J., and C. E. Lee, 2010. Safety analysis of storm sewer using probability of failure and multiple failure mode. Journal of the Korean Water Resources Association 43(11): 967-976 (in Korean). https://doi.org/10.3741/JKWRA.2010.43.11.967
  15. Lee, J. K., and Y. O. Kim, 2012. Selecting climate change scenarios reflecting uncertainties. Atmosphere. Korean Meteorological Society 22(2): 149-161 (in Korean).
  16. Lee, K. H., J. K. Lee, S. J. Kim, and H. S. Kim, 2011. Uncertainty analysis of flood demage estimation using Bootstrap method and SIR algorithm. Journal of Wetlands Research 13(1): 53-66 (in Korean).
  17. Lee, S. H., K. H. Song, S. J. Maeng, K. S. Ryoo, D. J. Kim, and H. K. Jee, 1999. Comparative analysis of flood frequency by L-moment in Weibull-3 and GEV distributions. Journal of the Korean Society of Agricultural Engineers 41(4): 25-36 (in Korean).
  18. Maeng, S. J., J. H. Hwang, and Q. Shi, 2009a. Estimation of reservoir inflow using frequency analysis. Journal of the Korean Society of Agricultural Engineers 51(3): 53-62 (in Korean).
  19. Maeng, S. J., B. J. Kim, and H. S. Kim, 2009b. Estimation of design floods using 3 and 4 parameter kappa distributions. Journal of the Korean Society of Agricultural Engineers 51(4): 49-55 (in Korean). https://doi.org/10.5389/KSAE.2009.51.4.049
  20. Maurer, E. P., 2007. Uncertainty in hydrologic impacts of climate change in the Sierra Nevada, California, under two emissions scenarios. Climatic Change 82: 309-325. https://doi.org/10.1007/s10584-006-9180-9
  21. Mays, L. W., and Y. K. Tung, 1992. Hydrosystems engineering and management. McGraw-Hill, New York.
  22. Nam, W. H., T. G. Kim, J. Y. Choi, and J. J. Lee, 2012a. Vulnerability assessment of water supply in agricultural reservoir utilizing probability distribution and reliability analysis methods. Journal of the Korean Society of Agricultural Engineers 54(2): 37-46 (in Korean).
  23. Nam, W. H., T. G. Kim, J. Y. Choi, and J. J. Lee, 2012b. Estimating vulnerable duration for irrigation with agricultural water supply and demand during residual periods. Journal of the Korean Society of Agricultural Engineers 54(5): 123-128 (in Korean). https://doi.org/10.5389/KSAE.2012.54.5.123
  24. Nam, W. H., T. G. Kim, J. Y. Choi, and H. J. Kim, 2012c. Evaluation of irrigation vulnerability characteristic curves in agricultural reservoir. Journal of the Korean Society of Agricultural Engineers 54(6): 39-44 (in Korean).
  25. Nam, W. H., 2013. Sustainability and operations evaluation of agricultural reservoirs based on probability theory. Ph.D. diss., Seoul National University.
  26. Nam, W. H., J. Y. Choi, M. W. Jang, and E. M. Hong, 2013. Agricultural drought risk assessment using reservoir drought index. Journal of the Korean Society of Agricultural Engineers 55(3): 41-49 (in Korean). https://doi.org/10.5389/KSAE.2013.55.3.041
  27. New, M., A. Lopez, S. Dessai, and R. Wilby, 2007. Challenges in using probabilistic climate change information for impact assessments: an example from the water sector. Philosophical Transactions of The Royal Society 365: 2117-2131. https://doi.org/10.1098/rsta.2007.2080
  28. Noh, J. K., 2000. Simulation of daily reservoir inflow using objective function based on storage error. Journal of the Korean Society of Agricultural Engineers 42(4): 76-86 (in Korean).
  29. Oh, T. S., and, Y. I. Moon, 2009. Evaluation of probability precipitation using climatic indices in Korea. Journal of the Korean Water Resources Association 42(9): 681-690 (in Korean). https://doi.org/10.3741/JKWRA.2009.42.9.681
  30. Park, S. S., 2009. Probabilistic risk evaluation method for human-induced disaster by risk curve analysis. Journal of Korean Society of Hazard Mitigation 9(6): 57-68 (in Korean).
  31. Raisanen, J., 2007. How reliable are climate models. Tellus 52A: 2-29.
  32. Shim, M. P., 2003. Economic analysis of water resources. Magazine of Korea Water Resources Association 36(3): 74-85 (in Korean).
  33. Sung, J. H., H. S. Kang, S. H. Park, C. H. Cho, D. H. Bae, and Y. O. Kim, 2012. Projection of extreme precipitation at the end of 21st century over South Korea based Representative Concentration Pathways (RCP). Atmosphere. Korean Meteorological Society 22(2): 221-231 (in Korean).
  34. Tramblay, Y., W. Badi, F. Driouech, S. E. Adlouni, L. Neppel, and E. Servat, 2012. Climate change impacts on extreme precipitation in Morocco. Global and Planetary Change 82-83: 104-114. https://doi.org/10.1016/j.gloplacha.2011.12.002
  35. Wood, A. W., L. R. Leung, V. Sridhar, and D. P. Lettenmarier, 2004. Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Climatic Change 62: 189-216. https://doi.org/10.1023/B:CLIM.0000013685.99609.9e
  36. Yoon, P. Y., T. W. Kim, J. S. Yang, and S. O. Lee, 2012. Estimating quantiles of extreme rainfall using a mixed Gumbel distribution model. Journal of the Korean Water Resources Association 45(3): 263-274 (in Korean). https://doi.org/10.3741/JKWRA.2012.45.3.263

피인용 문헌

  1. Projection of Consumptive Use and Irrigation Water for Major Upland Crops using Soil Moisture Model under Climate Change vol.56, pp.5, 2014, https://doi.org/10.5389/KSAE.2014.56.5.077
  2. Projection of Future Water Supply Sustainability in Agricultural Reservoirs under RCP Climate Change Scenarios vol.56, pp.4, 2014, https://doi.org/10.5389/KSAE.2014.56.4.059
  3. Water Quality Improvement Plans of Daeho Reservoir based on the Analysis of Watershed Characteristics and Water Quality Modelling vol.40, pp.7, 2018, https://doi.org/10.4491/KSEE.2018.40.7.267