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Parameter optimization of agricultural reservoir long-term runoff model based on historical data

실측자료기반 농업용 저수지 장기유출모형 매개변수 최적화

  • Hong, Junhyuk (Department of Civil System Engineering, Ajou University) ;
  • Choi, Youngje (Department of Civil System Engineering, Ajou University) ;
  • Yi, Jaeeung (Department of Civil System Engineering, Ajou University)
  • 홍준혁 (아주대학교 건설시스템공학과) ;
  • 최영제 (아주대학교 건설시스템공학과) ;
  • 이재응 (아주대학교 건설시스템공학과)
  • Received : 2020.12.14
  • Accepted : 2021.01.12
  • Published : 2021.02.28

Abstract

Due to climate change the sustainable water resources management of agricultural reservoirs, the largest number of reservoirs in Korea, has become important. However, the DIROM, rainfall-runoff model for calculating agricultural reservoir inflow, has used regression equation developed in the 1980s. This study has optimized the parameters of the DIROM using the genetic algorithm (GA) based on historical inflow data for some agricultural reservoirs that recently begun to observe inflow data. The result showed that the error between the historical inflow and simulated inflow using the optimal parameters was decreased by about 80% compared with the annual inflow with the existing parameters. The correlation coefficient and root mean square error with the historical inflow increased to 0.64 and decreased to 28.2 × 103 ㎥, respectively. As a result, if the DIROM uses the optimal parameters based on the historical inflow of agricultural reservoirs, it will be possible to calculate the long-term reservoir inflow with high accuracy. This study will contribute to future research using the historical inflow of agricultural reservoirs and improvement of the rainfall-runoff model parameters. Furthermore, the reliable long-term inflow data will support for sustainable reservoir management and agricultural water supply.

최근 기후변화로 인해 국내 저수지 중 가장 큰 개소수를 차지하고 있는 농업용 저수지의 안정적인 용수공급이 중요해지고 있다. 그러나 현재 사용하고 있는 농업용 저수지의 유입량 산정모형인 DIROM 모형은 매개변수 산정을 위해 1980년대에 개발된 회귀식을 현재까지 사용하고 있다. 우리나라의 강우 및 유출 특성이 변화함에 따라 본 연구에서는 최근 수문자료 관측을 시작한 일부 농업용 저수지를 대상으로 실측 수문자료 및 유전자 알고리즘을 이용하여 DIROM 모형의 매개변수를 최적화하고, 그 결과를 평가하고자 하였다. 그 결과 기존의 매개변수를 적용한 결과에 비하여 최적 매개변수를 적용하였을 때 실측 유입량과의 차이가 약 80% 감소하는 것으로 분석되었다. 또한 평균적으로 상관계수는 0.64로 증가하였고, 평균제곱근오차는 28.2 × 103 ㎥로 감소하였다. 최적 매개변수를 사용하여 장기유출모의를 하는 것이 실측 유입량에 좀 더 근접하게 모의 할 수 있음을 확인하였다. 본 연구 결과 장기적으로 관측된 실측 수문자료를 활용하게 된다면 좀 더 정확도 높은 유입량을 모의할 수 있으며, 미계측 농업용 저수지에서의 안정적인 용수공급 분석에 도움이 될 것이라 판단된다.

Keywords

References

  1. Ahn, J.H. (2013). Development of regression equations for the parameter estimation of TANK model based on basin slope, Master thesis, Seoul National University.
  2. Ahn, J.H., Song, J.H., Kang, M.S., Song, I.H., Jun, S.M., and Park, J.H. (2015). "Regression equations for estimating the TANK model parameters." Journal of the Korean Society of Agricultural Engineers, Vol. 57, No. 4, pp. 121-133. https://doi.org/10.5389/KSAE.2015.57.4.121
  3. Choi, H.J. (2015). A study on changes in the design flood of irrigation reservoir, Master thesis, Ajou University.
  4. DeJong, K. (1975). An analysis of the behavior of a class of genetic adaptive systems. Ph. D. dissertation, University of Michigan, Ann Arbor, MI, U.S.
  5. Goldberg, D.E. (1989). Genetic algorithms in search, optimization and machine learning. Addison-Wesley Publishing Co., MA, U.S.
  6. Ho, T.P., Nguyen., X.T., Hidetaka, C., and Kenji, O. (2018). "A hydrological Tank model assessing historical runoff variation in the Hieu River basin." Asian Journal of water, Environment and Pollution, Vol. 15, No. 1, pp. 75-86. https://doi.org/10.3233/AJW-180008
  7. Holland, J.H. (1975). Adaptation in natural and artificial systems. MIT Press, Chambrige, MA, U.S.
  8. Jang, J.H. (2002). A study on the estimation of streamflows using a distributed Rainfall-Runoff mdel, Master thesis, Inha University.
  9. Jang, J.S. (2003). "Introduction of hydrologic models and parameters." journal of Korean National Committee on Irrigation and Drainage, Vol. 10, No. 1, pp. 95-102.
  10. Kang, M.G., Lee, J.H., and Park, K.W. (2013). "Parameter regionalization of a Tank model for simulating runoffs from ungauged watersheds." Journal of the Korean Water Resources Association, Vol. 46, No. 5, pp. 519-530. https://doi.org/10.3741/JKWRA.2013.46.5.519
  11. Kim, C., and Kim, S.G. (2004). "Parameter optimization of TANK model using geographic data." Journal of the Korean Society of Civil Engineers B, Vol. 24, No. 6B, pp. 553-560.
  12. Kim, C.G., and Kim, N.W. (2012). "Comparison of natural flow estimates for the Han River basin using TANK and SWAT models." Journal of Korea Water Resources Association, Vol. 45, No. 3, pp. 301-316. https://doi.org/10.3741/JKWRA.2012.45.3.301
  13. Kim, H.Y., and Park, S.W. (1988). "Simulating daily inflow and release rates for irrigation reservoirs (1)-modeling inflow rates by a linear reservoir model-." Journal of the Korean Society of Agricultural Engineers, Vol. 30, No. 1, pp. 50-62.
  14. Kim, K.U., Song, J.H., Ahn, J.H., Park, J.H., Jun, S.M., Song, I.H., and Kang, M.S. (2014). "Evaluation of the Tank model optimized parameter for watershed modeling." Journal of the Korean Society of Agricultural Engineers, Vol. 56, No. 4, pp. 9-19. https://doi.org/10.5389/KSAE.2014.56.4.009
  15. Kim, Y.K., Yoo, J.A., and Chung, E.S. (2012). "Water management vulnerability assessment considering climate change in Korea." Journal of Climate Change Research, Vol. 3, No. 1, pp. 1-12. https://doi.org/10.3724/SP.J.1248.2012.00001
  16. Korea Meteorological Administration (KMA) (2020). Korea climate change Assessment Report 2020.
  17. Korea Rural Community Corporation (KRC) (2016). Development of a integrated assessment of system for impact of climate change on agricultural water.
  18. Lee, K.S., and Kim, S.U. (2001). "Automatic calibration of SSARR model with genetic algorithm." Journal of the Korean Society of Civil Engineers B, Vol. 21, No. 3B, pp. 171-183.
  19. Lee. T.H. (2012). The study of water supply reliability considering the management for restricted water level of agricultural reservoirs during flood period, Master thesis, Kookmin University.
  20. Ministry of Agriculture, Food and Rural Affairs (MAFRA) (2015). Development of a rural water resources assessment tool.
  21. Ministry of Agriculture, Food and Rural Affairs (MAFRA) (2019). Standard for Agricultural fill dam design.
  22. Ministry of Environment (MOE) (2013). A study on the improvement measures for survey on lake environmental.
  23. Ministry of Land, Transport and Maritime Affairs (MOLTMA) (2011). A long-term comprehensive plan of water resources (2011-2020).
  24. Roh, K.B., Lee, H.M., Park, S.C., and Lee, K.S. (2000). "The river flows forecasting using genetic algorithm." Proceeding of 2000 Korean Society of Civil Engineers Convention, Vol. 2000, No. 3, pp. 533-536.
  25. Song, J.H. (2017). Hydrologic analysis system with multi-objective optimization for agricultural watersheds, PhD dissertation, Seoul National University.
  26. Sugawara, M. (1961). "On the analysis of runoff structure about several Japanese rivers." Japanese Journal of Geophysics, Vol. 2, No. 4, pp. 1-76. https://doi.org/10.1016/S0074-6142(08)60649-X
  27. Sugawara, M. (1972). A method for runoff analysis. Kyoritsu Shuppan Co., Ltd., Tokyo, Japan (in Japanese).
  28. Yang, S.C. (2006). Analysis and prediction of inflow for long-term water management of agricultural dams, Master thesis, Hanbat University.
  29. Yokoo, Y., Kazama, S., Sawamoto, M., and Nishimura, H. (2001). "Regionalization of lumped water balance model parameters based on multiple regression." Journal of Hydrology, Vol. 246, pp. 209-222. https://doi.org/10.1016/S0022-1694(01)00372-9