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개념적 강우유출 모형의 유량구간별 적합성 평가 및 앙상블 모델 구축
Evaluation of conceptual rainfall-runoff models for different flow regimes and development of ensemble model 원문보기

Journal of Korea Water Resources Association = 한국수자원학회논문집, v.54 no.2, 2021년, pp.105 - 119  

유재웅 (세종대학교 건설환경공학과) ,  박문형 (한국건설기술연구원) ,  김진국 (한국건설기술연구원) ,  권현한 (세종대학교 건설환경공학과)

초록
AI-Helper 아이콘AI-Helper

최근 우리나라의 계절적 강우변동폭이 점점 커져 홍수 및 가뭄의 발생빈도와 심도가 증가하고 있다. 특히, 도시화에 따른 토지이용변화, 산업구조변화 등은 수자원의 수요량 및 공급량 불균형으로 이어져 수자원 관리에서 제약조건으로 작용하고 있다. 유역 내의 물순환 평가에 있어서 물수지 모델 구축과 함께 정확한 강우-유출 분석은 매우 중요한 분석단계라 할 수 있다. 이러한 점에서 본 연구에서는 국내외 주요 연속강우-유출모형의 특성을 파악하고 소양강댐 유역에 대해서 적합성을 평가하였다. 미계측유역의 불확실성을 고려한 유량 시나리오를 제시하기 위하여 다수의 모형을 활용하는 앙상블 개념을 도입하였으며, 향후 미계측유역에 대한 적용을 위한 모형의 확장성을 고려하여 매개변수 개수 및 관측 유량에 대한 재현능력 특성 등을 종합적으로 평가하였다. 본 연구에서는 40개 이상의 국내외 연속강우-유출모형을 소양강댐에 적용하였으며, 통계적 지표를 이용하여 9개의 모형을 1차적으로 선정하였다. 선정된 모형을 대상으로 매개변수의 개수 및 저유량, 중간유량, 고유량으로 분리하여 재현성을 평가하고 최종적으로 앙상블모형을 제시하였으며, 단일 모형에 비해 개선된 관측유량 재현효과를 확인할 수 있었다.

Abstract AI-Helper 아이콘AI-Helper

An increase in the frequency and intensity of both floods and droughts has been recently observed due to an increase in climate variability. Especially, land-use change associated with industrial structure and urbanization has led to an imbalance between water supply and demand, acting as a constrai...

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표/그림 (12)

참고문헌 (55)

  1. Akaikei, H. (1973). "Information theory and an extension of maximum likelihood principle." 2nd International Symposium on Information Theory, Edited by Petrov, B.N., and Csaki, F., Akademiai Kiado, Budapest, Hungary, pp. 267-281. 

  2. Atkinson, S., Sivapalan, M., Woods, R., and Viney, N. (2003). "Dominant physical controls on hourly flow predictions and the role of spatial variability: Mahurangi catchment, New Zealand." Advances in Water Resources, Vol. 26, No. 3, pp. 219-235. 

  3. Atkinson, S., Woods, R., and Sivapalan, M. (2002). "Climate and landscape controls on water balance model complexity over changing timescales." Water Resources Research, Vol. 38, No. 12, pp. 50-1 - 50-17. 

  4. Bae, D.H., and Lee, B.J. (2011). "Development of continuous rainfallrunoff model for flood forecasting on the large-scale basin." Journal of Korea Water Resource Association, Vol. 44, No. 1, pp. 51-64. 

  5. Bai, Y., Wagener, T., and Reed, P. (2009). "A top-down framework for watershed model evaluation and selection under uncertainty." Environmental Modelling & Software, Vol. 24, No. 8, pp. 901-916. 

  6. Beven, K. (1997). "TOPMODEL: A critique." Hydrological processes, Vol. 11, No. 9, pp. 1069-1085. 

  7. 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. CA, U.S., pp. 12-64. 

  8. 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. 

  9. Chiew, F.H.S., Peel, M.C., and Western, A.W. (2002). "Application and testing of the simple rainfall-runoff model SIMHYD." Mathematical Models of Small Watershed Hydrology and Applications, Edited by Vijay, P.S. and Donald, K.F., Water Resources Publications, CO, U.S., pp. 335-367. 

  10. Crooks, S., and Naden, P. (2007). "CLASSIC: A semi-distributed rainfall-runoff modelling system." Hydrology and Earth System Sciences, Vol. 11, No. 1, pp. 516-531. 

  11. Daliakopoulos, I.N., and Tsanis, I.K. (2016). "Comparison of an artificial neural network and a conceptual rainfall-runoff model in the simulation of ephemeral streamflow." Hydrological Sciences Journal, Vol. 61, No. 15, pp. 2763-2774. 

  12. Duan, Q., Ajami, N. K., Gao, X., and Sorooshian, S. (2007). "Multi-model ensemble hydrologic prediction using Bayesian model averaging." Advances in Water Resources, Vol. 30, No. 5, pp. 1371-1386. 

  13. Eder, G., Sivapalan, M., and Nachtnebel, H. (2003). "Modelling water balances in an Alpine catchment through exploitation of emergent properties over changing time scales." Hydrological Processes, Vol. 17, No. 11, pp. 2125-2149. 

  14. Edijatno, N., and Michel, C. (1989). "Un modele pluie-debit journalier a trois parametres." La Houille Blanche, Vol. 2, pp. 113-121. 

  15. Edijatno, N., De Oliveira Nascimento, N., Yang, X., Makhlouf, Z., and Michel, C. (1999). "GR3J: A daily watershed model with three free parameters." Hydrological Sciences Journal, Vol. 44, No. 2, pp. 263-277. 

  16. Farmer, D., Sivapalan, M., and Jothityangkoon, C. (2003). "Climate, soil, and vegetation controls upon the variability of water balance in temperate and semiarid landscapes: Downward approach to water balance analysis." Water Resources Research, Vol. 39, No. 2, pp. 1-1-1-21. 

  17. Fenicia, F., Savenije, H.H., Matgen, P., and Pfister, L. (2008). "Understanding catchment behavior through stepwise model concept improvement." Water Resources Research, Vol. 44, No. 1, pp. 1-13. 

  18. Fukushima, Y. (1988). "A model of river flow forecasting for a small forested mountain catchment." Hydrological Processes, Vol. 2, No. 2, pp. 167-185. 

  19. Garcia, F., Folton, N., and Oudin, L. (2017). "Which objective function to calibrate rainfall-runoff models for low-flow index simulations?" Hydrological Sciences Journal, Vol. 62, No. 7, pp. 1149-1166. 

  20. Jakeman, A., Littlewood, I., and Whitehead, P. (1990). "Computation of the instantaneous unit hydrograph and identifiable component flows with application to two small upland catchments." Journal of Hydrology, Vol. 117, No. 1-4, pp. 275-300. 

  21. Jothityangkoon, C., Sivapalan, M., and Farmer, D. (2001). "Process controls of water balance variability in a large semi-arid catchment: Downward approach to hydrological model development." Journal of Hydrology, Vol. 254, No. 1-4, pp. 174-198. 

  22. Kalin, L., Isik, S., Schoonover, J.E., and Lockaby, B.G. (2010). "Predicting water quality in unmonitored watersheds using artificial neural networks." Journal of Environmental Quality, Vol. 39, No. 4, pp. 1429-1440. 

  23. Khazaei, M.R., Zahabiyoun, B., and Saghafian, B. (2012). "Assessment of climate change impact on floods using weather generator and continuous rainfall­runoff model." International Journal of Climatology, Vol. 32, No. 13, pp. 1997-2006. 

  24. Kim, T.-J., So, B.-J., Ryou, M.-S., and Kwon, H.-H. (2016). "Development of dam inflow simulation techniqe coupled with rainfall simulation and rainfall-runoff model." Journal of Korea Water Resource Association, Vol. 49, No. 4, pp. 315-325. 

  25. Kwon, H.-H., Moon, Y.-I., Kim, B.-S., and Yoon, S.-Y. (2008). "Parameter optimization and uncertainty analysis of the NWS-PC rainfall-runoff model coupled with Bayesian Markov Chain Monte Carlo Inference Scheme." Journal of The Korean Society of Civil Engineers, KSCE, Vol. 28, No. 4, pp. 383-392. 

  26. Lee, M.J., Kang, N.R., Kim, J.S., and Kim, H.S. (2018). "Estimation of optimal runoff hydrograph using radar rainfall ensemble and blending technique of rainfall-runoff models." Journal of Korea Water Resources Association, Vol. 51, No. 3, pp. 221-233. 

  27. Liang, X., Lettenmaier, D.P., Wood, E.F., and Burges, S.J. (1994). "A simple hydrologically based model of land surface water and energy fluxes for general circulation models." Journal of Geophysical Research: Atmospheres, Vol. 99, No. D7, pp. 14415-14428. 

  28. Lindstrom, G., Johansson, B., Persson, M., Gardelin, M., and Bergstrom, S. (1997). "Development and test of the distributed HBV-96 hydrological model." Journal of hydrology, Vol. 201, No. 1-4, pp. 272-288. 

  29. Lyne, V., and Hollick, M. (1979). "Stochastic time-variable rainfall-runoff modelling." Institute of Engineers Australia National Conference, Institute of Engineers Australia Barton, Australia, pp. 89-93. 

  30. Markstrom, S.L., Regan, R.S., Hay, L.E., Viger, R.J., Webb, R.M., Payn, R.A., and LaFontaine, J.H. (2015). PRMS-IV, the precipitation-runoff modeling system, version 4, Branch of Regional Research U.S. Geological Survey, Reston, VA, U.S., pp. 1-158. 

  31. Mlynski, D., Petroselli, A., and Walega, A. (2018). "Flood frequency analysis by an event-based rainfall-runoff model in selected catchments of southern Poland." Soil and Water Research, Vol. 13, No. 3, pp. 170-176. 

  32. Montanari, A., and Brath, A. (2004). "A stochastic approach for assessing the uncertainty of rainfall­runoff simulations." Water Resources Research, Vol. 40, No. 1, pp. 1-11. 

  33. 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. 

  34. Moore, R., and Bell, V. (2001). Comparison of rainfall-runoff models for flood forecasting. Part 1: Literature review of models, Environment Agency, Almondsbury, Bristol, UK, pp. 1-94. 

  35. Moussa, R., and Chahinian, N. (2009). "Comparison of different multiobjective calibration criteria using a conceptual rainfall-runoff model of flood events." Hydrology and Earth System Sciences, Vol. 13, No. 4, pp. 519-535. 

  36. Nielsen, S.A., and Hansen, E. (1973). "Numerical simulation of the rainfall-runoff process on a daily basis." Hydrology Research, Vol. 4, No. 3, pp. 171-190. 

  37. O'connell, P., Nash, J., and Farrell, J. (1970). "River flow forecasting through conceptual models part II-The Brosna catchment at Ferbane." Journal of Hydrology, Vol. 10, No. 4, pp. 317-329. 

  38. 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. 

  39. Porter, J., and McMahon, T.A. (1976). The Monash model: user manual for daily program HYDROLOG. Department of Civil Engineering, Monash University, Victoria, Austraila, pp. 41. 

  40. Santos, L., Thirel, G., and Perrin, C. (2018). "Continuous state-space representation of a bucket-type rainfall-runoff model: A case study with the GR4 model using state-space GR4 (version 1.0)." Geoscientific Model Development, Vol. 11, No. 4, pp. 1591-1605. 

  41. Savenije, H.H. (2010). "HESS Opinions "Topography driven conceptual modelling (FLEX-Topo)."" Hydrology and Earth System Sciences, Vol. 14, No. 12, pp. 2681-2692. 

  42. Schaefli, B., Hingray, B., Niggli, M., and Musy, A. (2005). "A conceptual glacio-hydrological model for high mountainous catchments." Hydrology and Earth System Sciences, Vol. 9, pp. 95-109. 

  43. Schaefli, B., Nicotina, L., Imfeld, C., Da Ronco, P., Bertuzzo, E., and Rinaldo, A. (2014). "SEHR-ECHO v1.0: A spatially explicit hydrologic response model for ecohydrologic applications." Geoscientific Model Development, Vol. 7, No. 6, pp. 2733-2746. 

  44. Schwarz, G. (1978). "Estimating the dimension of a model." The Annals of Statistics, Vol. 6, No. 2, pp. 461-464. 

  45. Sitterson, J., Knightes, C., Parmar, R., Wolfe, K., Muche, M., and Avant, B. (2018). An overview of rainfall-runoff model types, US Environmental Protection Agency, Washington D.C., U.S., pp. 1-29. 

  46. Sivapalan, M., Ruprecht, J.K., and Viney, N.R. (1996). "Water and salt balance modelling to predict the effects of land­use changes in forested catchments. 1. Small catchment water balance model." Hydrological Processes, Vol. 10, No. 3, pp. 393-411. 

  47. Smakhtin, V., Sami, K., and Hughes, D. (1998). "Evaluating the performance of a deterministic daily rainfall-runoff model in a low-flow context." Hydrological Processes, Vol. 12, No. 5, pp. 797-812. 

  48. Son, K., and Sivapalan, M. (2007). "Improving model structure and reducing parameter uncertainty in conceptual water balance models through the use of auxiliary data." Water Resources Research, Vol. 43, No. 1, pp. 1-18. 

  49. Spiegelhalter, D.J., Best, N.G., Carlin, B.P., and Van Der Linde, A. (2002). "Bayesian measures of model complexity and fit." Journal of the Royal Statistical Society: Series b (Statistical Methodology), Vol. 64, No. 4, pp. 583-639. 

  50. Sugawara, M. (1979). "Automatic calibration of the tank model/L'etalonnage automatique d'un modele a cisterne." Hydrological Sciences Journal, Vol. 24, No. 3, pp. 375-388. 

  51. Tajiki, M., Schoups, G., Hendricks Franssen, H., Najafinejad, A., and Bahremand, A. (2020). "Recursive Bayesian estimation of conceptual rainfall­runoff model errors in real­time prediction of streamflow." Water Resources Research, Vol. 56, No. 2, pp. 1-25. 

  52. Wagener, T., Lees, M.J., and Wheater, H.S. (2002). "A toolkit for the development and application of parsimonious hydrological models." Mathematical Models of Large Watershed Hydrology, Vol. 2, pp. 87-136. 

  53. Ye, S., Yaeger, M., Coopersmith, E., Cheng, L., and Sivapalan, M. (2012). "Exploring the physical controls of regional patterns of flow duration curves-Part 2: Role of seasonality, the regime curve, and associated process controls." Hydrology and Earth System Sciences, Vol. 16, No. 11, pp. 4447-4465. 

  54. Ye, W., Bates, B., Viney, N., Sivapalan, M., and Jakeman, A. (1997). "Performance of conceptual rainfall-runoff models in lowyielding ephemeral catchments." Water Resources Research, Vol. 33, No. 1, pp. 153-166. 

  55. Zhao, R. (1992). "The Xinanjiang model applied in China." Journal of hydrology, Vol. 135, No. 1-4, pp. 371-381. 

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