대한토목학회논문집 (KSCE Journal of Civil and Environmental Engineering Research)

  • 제43권3호
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  • Pages.337-352
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  • 2023
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  • 1015-6348(pISSN)
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  • 2799-9629(eISSN)
대한토목학회 (Korean Society of Civil Engeneers)
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지역적 민감도 분석을 이용하여 계절성을 고려한 수문 모형 보정 기법 개발

A Development of Hydrological Model Calibration Technique Considering Seasonality via Regional Sensitivity Analysis

  • 이예린 (세종대학교 공과대학 건설환경공학과) ;
  • 유재웅 (세종대학교 공과대학 건설환경공학과) ;
  • 김경탁 (한국건설기술연구원 수자원하천연구본부) ;
  • 권현한 (세종대학교 공과대학 건설환경공학과)
  • 투고 : 2023.04.13
  • 심사 : 2023.05.09
  • 발행 : 2023.06.01
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초록

일반적으로 강우-유출모형의 매개변수 최적화는 가용 자료 전체를 대상으로 수행하여 고유의 매개변수 집합을 활용한다. 그러나, 계절에 따른 강수량의 편차가 큰 국내의 기후 특성과 더불어 기후변화로 인하여 계절성에 따른 편차 및 변동성이 증가할 것으로 전망되고 있어, 물 수요자들에 대한 안정적인 공급을 위한 장기간의 계획에서 계절성을 반영한 매개변수 추정은 효율적인 물배분에 중요한 요소라 할 수 있다. 본 연구에서는 기후특성에 따른 강우-유출모형의 변동성을 분석하기 위하여 소양강댐 유역을 대상으로 GR4J 강우-유출모형을 활용한 지역적 민감도 분석을 수행하였으며, 산출된 민감도 분석 결과와 기상자료를 결합하여 SOM을 활용해 군집화하였다. 이를 통해 계절 분리를 수행하고 각 계절의 특징을 분석하여 강우-유출모형의 보정 기법을 개발하였으며, 통계적 지표를 이용하여 성능을 평가하였다. 결과적으로 비교적 유량이 적은 Cold 기간의 모형 성능이 개선되는 것을 확인할 수 있었다. 이는 몬순기후 등 강수편차가 큰 지역을 대상으로 수문모형의 성능 및 예측도를 높일 수 있을 것으로 판단된다.

In general, Rainfall-Runoff model parameter set is optimized using the entire data to calculate unique parameter set. However, Korea has a large precipitation deviation according to the season, and it is expected to even worsen due to climate change. Therefore, the need for hydrological data considering seasonal characteristics. In this study, we conducted regional sensitivity analysis(RSA) using the conceptual Rainfall-Runoff model, GR4J aimed at the Soyanggang dam basin, and clustered combining the RSA results with hydrometeorological data using Self-Organizing map(SOM). In order to consider the climate characteristics in parameter estimation, the data was divided based on clustering, and a calibration approach of the Rainfall-Runoff model was developed by comparing the objective functions of the Global Optimization method. The performance of calibration was evaluated by statistical techniques. As a result, it was confirmed that the model performance during the Cold period(November~April) with a relatively low flow rate was improved. This is expected to improve the performance and predictability of the hydrological model for areas that have a large precipitation deviation such as Monsoon climate.

키워드

과제정보

본 결과물은 환경부의 재원으로 한국환경산업기술원의 물관리연구사업의 지원을 받아 연구되었습니다(21AWMP-B121100-06).

참고문헌

  1. Akaikei, H. (1973). "Information theory and an extension of maximum likelihood principle." Proc. 2nd Int. Symp. on Information Theory, pp. 267-281.
  2. ASCE Task Committee on Definition of Criteria for Evaluation of Watershed Models of the Watershed Management Committee, I. and Division, D. (1993). "Criteria for evaluation of watershed models." Journal of Irrigation and Drainage Engineering, Vol. 119, No. 3, pp. 429-442. https://doi.org/10.1061/(ASCE)0733-9437(1993)119:3(429)
  3. Bosman, P. AN. (2010). "The anticipated mean shift and cluster registration in mixture-based EDAs for multi-objective optimization." Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation, pp. 351-358.
  4. Boyack, B., Catton, I., Duffey, R., Katsma, K., Lellouche, G., Levy, S., Wilson, G. and Zuber, N. (1990). "Quantifying reactor safety margins part 1: an overview of the code scaling, applicability, and uncertainty evaluation methodology." Nuclear Engineering and Design, Vol. 119, No. 1, pp. 1-15. https://doi.org/10.1016/0029-5493(90)90071-5
  5. Burnash, R. J., Ferral, R. L. and McGuire, R. A. (1973). "A generalized streamflow simulation system: Conceptual modeling for digital computers." US Department of Commerce, National Weather Service. California, USA, pp. 12-64.
  6. Chiew, F. and McMahon, T. (1994). "Application of the daily rainfall-runoff model MODHYDROLOG to 28 Australian catchments." Journal of Hydrology, Vol. 153, No. 1-4, pp. 383-416. https://doi.org/10.1016/0022-1694(94)90200-3
  7. Duan, Q., Schaake, J., Andreassian, V., Franks, S., Goteti, G., Gupta, H., Gusev, Y., Habets, F., Hall, A. and Hay, L. (2006). "Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops." Journal of Hydrology, Vol. 320, Nos. 1-2, pp. 3-17. https://doi.org/10.1016/j.jhydrol.2005.07.031
  8. Duan, Q., Sorooshian, S. and Gupta, V. (1992). "Effective and efficient global optimization for conceptual rainfall-runoff models." Water Resources Research, Vol. 28, No. 4, pp. 1015-1031. https://doi.org/10.1029/91WR02985
  9. Ewen, J. (2011). "Hydrograph matching method for measuring model performance." Journal of Hydrology, Vol. 408, Nos. 1-2, pp. 178-187. https://doi.org/10.1016/j.jhydrol.2011.07.038
  10. Feng, X., Porporato, A. and Rodriguez-Iturbe, I. (2013). "Changes in rainfall seasonality in the tropics." Nature Climate Change, Vol. 3, No. 9, pp. 811-815. https://doi.org/10.1038/nclimate1907
  11. Fennessey, N. and Vogel, R. M. (1990). "Regional flow-duration curves for ungauged sites in Massachusetts." Journal of Water Resources Planning and Management, Vol. 116, No. 4, pp. 530-549. https://doi.org/10.1061/(ASCE)0733-9496(1990)116:4(530)
  12. Feyen, L., Vrugt, J. A., Nuallin, B. O., van der Knijff, J. and De Roo, A. (2007). "Parameter optimisation and uncertainty assessment for large-scale streamflow simulation with the LISFLOOD model." Journal of Hydrology, Vol. 332, No. 3-4, pp. 276-289. https://doi.org/10.1016/j.jhydrol.2006.07.004
  13. Glaeser, H. (2008). "GRS method for uncertainty and sensitivity evaluation of code results and applications." Science and Technology of Nuclear Installations, Vol. 2008.
  14. Gupta, H. V., Beven, K. J. and Wagener, T. (2006). "Model calibration and uncertainty estimation." Encyclopedia of Hydrological Sciences.
  15. Gupta, H. V., Kling, H., Yilmaz, K. K. and Martinez, G. F. (2009). "Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling." Journal of Hydrology, Vol. 377, Nos. 1-2, pp. 80-91. https://doi.org/10.1016/j.jhydrol.2009.08.003
  16. Hall, M. and Minns, A. (1999). "The classification of hydrologically homogeneous regions." Hydrological Sciences Journal, Vol. 44, No. 5, pp. 693-704. https://doi.org/10.1080/02626669909492268
  17. Hornberger, G. M. and Spear, R. C. (1981). "Approach to the preliminary analysis of environmental systems." Journal of Environmental Management, Vol. 12, No. 1, pp. 7-18 .
  18. Im, S. S., Yoo, D. G. and Kim, J. H. (2012). "Improvement of GR4J model applying soil moisture accounting process anc its application in Korea Basin." Journal of the Korean Society of Hazard Mitigation, Vol. 12, No. 3, pp. 255-262 (in Korean). https://doi.org/10.9798/KOSHAM.2012.12.3.255
  19. Jung, I., Bae, D. and Lee, B. (2013). "Possible change in Korean streamflow seasonality based on multi-model climate projections." Hydrological Processes, Vol. 27, No. 7, pp. 1033-1045. https://doi.org/10.1002/hyp.9215
  20. Kim, H. and Lee, S. (2014). "Assessment of a seasonal calibration technique using multiple objectives in rainfall-runoff analysis." Hydrological Processes, Vol. 28, No. 4, pp. 2159-2173. https://doi.org/10.1002/hyp.9785
  21. Kim, J.-P. and Kim, G.-S. (2011). "The impact of climate change on the trends of precipitation effectiveness ratio and runoff data in South Korea." Journal of Korea Water Resources Association, Vol. 44, No. 8, pp. 683-694 (in Korean). https://doi.org/10.3741/JKWRA.2011.44.8.683
  22. Kim, J. S. and Choi, C. U. (2013). "Impact of changes in climate and land use/land cover change under climate change scenario on streamflow in the basin." Journal of Korean Society for Geospatial Information Science, Vol. 21, No. 2, pp. 105-114 (in Korean). https://doi.org/10.7319/kogsis.2013.21.2.107
  23. Kim, K. B. and Han, D. (2017). "Exploration of sub-annual calibration schemes of hydrological models." Hydrology Research, Vol. 48, No. 4, pp. 1014-1031. https://doi.org/10.2166/nh.2016.296
  24. Kling, H., Fuchs, M. and Paulin, M. (2012). "Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios." Journal of Hydrology, Vol. 424, pp. 264-277. https://doi.org/10.1016/j.jhydrol.2012.01.011
  25. Korea Meteorological Administration (KMA) (2022). Rainy season white book 2022 (in Korean).
  26. Legates, D. R. and McCabe Jr, G. J. (1999). "Evaluating the use of "goodness-of-fit" measures in hydrologic and hydroclimatic model validation." Water Resources Research, Vol. 35, No. 1, pp. 233-241. https://doi.org/10.1029/1998WR900018
  27. Lence, B. J. and Takyi, A. (1992). "Data requirements for seasonal discharge programs: an application of a regionalized sensitivity analysis." Water Resources Research, Vol. 28, No. 7, pp. 1781-1789. https://doi.org/10.1029/92WR00763
  28. Levesque, E., Anctil, F., Van Griensven, A. and Beauchamp, N. (2008). "Evaluation of streamflow simulation by SWAT model for two small watersheds under snowmelt and rainfall." Hydrological Sciences Journal, Vol. 53, No. 5, pp. 961-976. https://doi.org/10.1623/hysj.53.5.961
  29. Lin, G.-F. and Chen, L.-H. (2006). "Identification of homogeneous regions for regional frequency analysis using the self-organizing map." Journal of Hydrology, Vol. 324, Nos. 1-4, pp. 1-9. https://doi.org/10.1016/j.jhydrol.2005.09.009
  30. Liong, S. Y., Lim, W. H., Kojiri, T. and Hori, T. (2000). "Advance flood forecasting for flood stricken Bangladesh with a fuzzy reasoning method." Hydrological Processes, Vol. 14, No. 3, pp. 431-448. https://doi.org/10.1002/(SICI)1099-1085(20000228)14:3<431::AID-HYP947>3.0.CO;2-0
  31. Mara, T. A. and Tarantola, S. (2008). "Application of global sensitivity analysis of model output to building thermal simulations." Building Simulation, Vol. 1, No. 4, pp. 290-302. https://doi.org/10.1007/s12273-008-8129-5
  32. Moore, R. (1985). "The probability-distributed principle and runoff production at point and basin scales." Hydrological Sciences Journal, Vol. 30, No. 2, pp. 273-297. https://doi.org/10.1080/02626668509490989
  33. Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D. and Veith, T. L. (2007). "Model evaluation guidelines for systematic quantification of accuracy in watershed simulations." Transactions of the ASABE, Vol. 50, No. 3, pp. 885-900. https://doi.org/10.13031/2013.23153
  34. Moriasi, D. N., Gitau, M. W., Pai, N. and Daggupati, P. (2015). "Hydrologic and water quality models: Performance measures and evaluation criteria." Transactions of the ASABE, Vol. 58, No. 6, pp. 1763-1785. https://doi.org/10.13031/trans.58.10715
  35. Murtagh, F. and Hernandez-Pajares, M. (1995). "The Kohonen self-organizing map method: an assessment." Journal of Classification, Vol. 12, No. 2, pp. 165-190. https://doi.org/10.1007/BF03040854
  36. Pappenberger, F., Beven, K., Horritt, M. and Blazkova, S. (2005). "Uncertainty in the calibration of effective roughness parameters in HEC-RAS using inundation and downstream level observations." Journal of Hydrology, Vol. 302, No. 1-4, pp. 46-69. https://doi.org/10.1016/j.jhydrol.2004.06.036
  37. Perrin, C., Michel, C. and Andreassian, V. (2003). "Improvement of a parsimonious model for streamflow simulation." Journal of Hydrology, Vol. 279, No. 1-4, pp. 275-289. https://doi.org/10.1016/S0022-1694(03)00225-7
  38. Pushpalatha, R., Perrin, C., Le Moine, N. and Andreassian, V. (2012). "A review of efficiency criteria suitable for evaluating low-flow simulations." Journal of Hydrology, Vol. 420-421, pp. 171-182. https://doi.org/10.1016/j.jhydrol.2011.11.055
  39. Quintero, F., Krajewski, W. F., Seo, B.-C. and Mantilla, R. (2020). "Improvement and evaluation of the Iowa Flood Center Hillslope Link Model (HLM) by calibration-free approach." Journal of Hydrology, Vol. 584, pp. 124686.
  40. Rousseeuw, P. J. (1987). "Silhouettes: a graphical aid to the interpretation and validation of cluster analysis." Journal of Computational and Applied Mathematics, Vol. 20, pp. 53-65. https://doi.org/10.1016/0377-0427(87)90125-7
  41. Saltelli, A., Tarantola, S., Campolongo, F. and Ratto, M. (2004). Sensitivity analysis in practice: a guide to assessing scientific models, John Wiley & Sons, Ltd., Chichester, England.
  42. Schwarz, G. (1978). "Estimating the dimension of a model." The Annals of Statistics, Vol. 6, No. 2, pp. 461-464. https://doi.org/10.1214/aos/1176344136
  43. Sieber, A. and Uhlenbrook, S. (2005). "Sensitivity analyses of a distributed catchment model to verify the model structure." Journal of Hydrology, Vol. 310, Nos. 1-4, pp. 216-235. https://doi.org/10.1016/j.jhydrol.2005.01.004
  44. Sugawara, M. (1979). "Automatic calibration of the tank model. (In French)" Hydrological Sciences Journal, Vol. 24, No. 3, pp. 375-388. https://doi.org/10.1080/02626667909491876
  45. Tiao, G. C. and Box, G. E. P. (1973). "Some comments on "Bayes" estimators." The American Statistician, Vol. 27, No. 1, pp. 12-14.
  46. Vrugt, J. A., Gupta, H. V., Bouten, W. and Sorooshian, S. (2003). "A shuffled complex evolution metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters." Water Resources Research, Vol. 39, No. 8.
  47. Wagener, T., Sivapalan, M., Troch, P. and Woods, R. (2007). "Catchment classification and hydrologic similarity." Geography Compass, Vol. 1, No. 4, pp. 901-931. https://doi.org/10.1111/j.1749-8198.2007.00039.x
  48. Wallis, G. B. (2007). "Uncertainties and probabilities in nuclear reactor regulation." Nuclear Engineering and Design, Vol. 237, No. 15-17, pp. 1586-1592. https://doi.org/10.1016/j.nucengdes.2006.12.013
  49. Xu, C.-Y. and Vandewiele, G. (1994). "Sensitivity of monthly rainfall-runoff models to input errors and data length." Hydrological Sciences Journal, Vol. 39, No. 2, pp. 157-176. https://doi.org/10.1080/02626669409492731
  50. Young, R. C., Biggs, J. T., Ziegler, V. E. and Meyer, D. A. (1978). "A rating scale for mania: reliability, validity and sensitivity." The British Journal of Psychiatry, Vol. 133, No. 5, pp. 429-435. https://doi.org/10.1192/bjp.133.5.429
  51. Yu, J.-U., Park, M.-H., Kim, J.-G. and Kwon, H.-H. (2021). "Evaluation of conceptual rainfall-runoff models for different flow regimes and development of ensemble model." Journal of Korea Water Resources Association, Vol. 54, No. 2, pp. 105-119 (in Korean).
  52. Zeng, Q., Chen, H., Xu, C.-Y., Jie, M.-X. and Hou, Y.-K. (2016). "Feasibility and uncertainty of using conceptual rainfall-runoff models in design flood estimation." Hydrology Research, Vol. 47, No. 4, pp. 701-717. https://doi.org/10.2166/nh.2015.069
  53. Zhang, R., Cuartas, L. A., de Castro Carvalho, L. V., Reis Deusdara Leal, K., Mendiondo, E. M., Abe, N., Birkinshaw, S., Samprogna Mohor, G., Seluchi, M. E. and Nobre, C. A. (2018). "Seasonbased rainfall-runoff modelling using the probability-distributed model (PDM) for large basins in southeastern Brazil." Hydrological Processes, Vol. 32, No. 14, pp. 2217-2230. https://doi.org/10.1002/hyp.13154