Estimation of Storm Hydrographs in a Small Forest Watershed Using a Distributed Hydrological Model

분포형 수문모형을 이용한 산림소유역의 홍수수문곡선의 추정

  • Lee, Sang-Ho (Department of Forest Sciences, Seoul National University, Research Institute for Agriculture and Life Sciences) ;
  • Woo, Bo-Myeong (Department of Forest Sciences, Seoul National University) ;
  • Im, Sang-Jun (Department of Forest Sciences, Seoul National University, Research Institute for Agriculture and Life Sciences)
  • 이상호 (서울대학교 산림과학부.농업생명과학연구원) ;
  • 우보명 (서울대학교 산림과학부) ;
  • 임상준 (서울대학교 산림과학부.농업생명과학연구원)
  • Published : 2008.03.31

Abstract

This study was conducted to simulate storm hydrographs on a small forested watershed using TOPMODEL, which is a distributed hydrological model. The Myeongseong watershed, which is 58.3 ha in size, was selected to monitor rainfall and runoff data. The Monte Carlo simulation was also used to calibrate parameters of TOPMODEL. Six rainfall-runoff pairs collected at the watershed in the year 1997 were used for parameter calibration, and eight rainfall-runoff pairs collected during the period of $1998\sim1999$ were used for validation effort. The errors of runoff volume ranged from -2.74% to 1.81%, and an average value of model efficiency in terms of runoff volume was 0.92 for the calibration period. The average value of observed peak discharge was $0.324m^3\;s^{-1}$ for six rainfall-runoff pairs, while the prediction value was $0.295m^3\;s^{-1}$. The simulation errors of peak discharge varied according to rainfall characteristics and antecedent condition, within ranges of -27.65% to -1.13%. The model efficiency for the validation period was 0.92. For the validation period, observed peak discharges have an average value of $0.087m^3\;s^{-1}$ and average value of simulated peak discharge was $0.090m^3\;s^{-1}$. Observed and simulated values of time to peak for the calibration period were 18.3 hrs and 11.0 hrs, respectively, and 16.6 hrs and 13.5 hrs, respectively, for the validation period.

본 연구의 목적은 분포형 수문모형인 TOPMODEL을 이용하여 산림유역의 홍수수문곡선을 추정하는 것이다. 이를 위하여 유역면적 58.3ha의 명성유역을 선정하였으며, 대상유역에 대하여 강우량과 유출량을 측정하였다. Monte Carlo기법을 이용하여 강우사상별로 최적의 매개 변수 조합을 구하고, 매개변수별 모의기간에 대한 평균값을 적용하여 매개변수를 결정하였다. 1997년에 측정된 6개의 강우-유출량 자료를 이용하여 매개변수 보정을 실시하였으며, $1998\sim1999$년에 측정된 8개의 강우-유출량 자료를 이용하여 모형의 검증을 실시하였다. 보정기간에 대한 유출량 추정 오차는 $-2.74\sim1.81%$의 범위를 보였으며, 모형 효율(E)은 평균 0.92이었다. 6개의 강우사상에 대하여 실측된 평균 첨두유량은 $0.324m^3\;s^{-1}$이었으며, 이에 대한 추정치는 $0.295m^3\;s^{-1}$로 모의되었다. 강우 사상별 첨두유량의 오차범위는 $-27.65\sim-1.13%$로 나타났으며, 이는 강우특성 및 선행강우조건에 영향을 받은 것으로 판단된다. 검증기간에 대하여 각 강우사상별 모형효율(E)의 평균값은 0.92로 나타났다. 첨두유량의 실측값은 평균적으로 $0.087m^3\;s^{-1}$이었으며, 추정된 첨두유량의 평균은 $0.090m^3\;s^{-1}$로 나타났다. 첨두시간은 보정기간에 대하여는 관측값과 모의값의 평균이 각각 18.3 hrs와 11.0 hrs이었으며, 검증기간에 대하여는 각각 16.6hrs와 13.5 hrs이었다.

Keywords

References

  1. 김상현. 1997. 인공배수유역에서의 TOPMODEL의 적용. 한국수자원학회논문집 30(5): 539-548
  2. 김상현. 1998. 확장 TOPMODEL의 영역화 민감도 분석. 한국수자원학회논문집 31(6): 741-755
  3. 조홍제, 조인률, 김정식. 1997. TOPMODEL을 이용한 강우-유 출해석에 관한 연구. 한국수자원학회논문집 30(5): 515-526
  4. 조홍제, 조인률. 1998. 분포형 유출모형을 이용한 홍수유출해석. 한국수자원학회논문집 31(2): 199-208
  5. 정용호, 이헌호, 박재현, 최형태, 김경하, 윤호중. 2000. 영월댐 유역에서의 산림정비에 의한 홍수저감효과 분석. 영월댐 조사결과보고서 2: 홍수. 영월댐 공동조사단. p. 247-272
  6. 최형태. 2001. 분포형 수문모형 TOPMODEL을 이용한 산림 유역 강우-유출모형의 개발, 서울대학교 박사학위논문. 183 p.
  7. 한국수자원공사. 1993. 지리정보시스템을 이용한 수자원 관리 및 계획에 관한 연구. 한국수자원공사, 180 p.
  8. 谷誠. 1985. 山地溪流の流出特性を考慮した一次元鉛直不飽和浸透流の解析. 日林誌 67(11): 449-460
  9. 太田岳史. 1983. 一次元鉛直不飽和浸透流を用いた雨水流出特性の檢討(II)-初期水分條件を直接流出特性. 日林誌 65(12): 448-457
  10. 太田猛彦, 塚本良則, 城戶 毅. 1983a. 丘陵性自然斜面における雨水移動の實證的硏究(II)-斜面內地中流の實態. 日林誌 67(10): 383-390
  11. 太田岳史. 福島義宏, 鈴木雅一. 1983b. 一次元鉛直不飽和浸透流を用いた雨水流出特性の檢討. 日林誌 65(4): 125-134
  12. 太田岳史. 阿部 實. 1985. 一次元鉛直不飽和浸透流を用いた雨水流出特性の檢討(III)-斜面流出モデルの三期層斜面への適用結果. 日林誌 67(3): 99-102
  13. Ambroise, B., J. Freer and K.J. Beven. 1996a. Application of a generalized TOPMODEL to the small Rigelbach catchment, Vosges, France. Water Resources Research 32(7): 2147-2159 https://doi.org/10.1029/95WR03715
  14. Ambroise, B., J. Freer and K.J. Beven. 1996b. Toward a generalization of the TOPMODEL concepts: topographic indices of hydrological similarity. Water Resources Research 32(7): 2134-2145
  15. Beven, K.J. 1986. Runoff production and flood frequency in catchments of order n: an alternative approach. p. 107- 131. In: Gupta, V.K., I. Rodriguez-Iturbe, E.F. Wood, eds. Scale Problems in Hydrology. Boston: D. Reidel
  16. Beven, K.J. 1997. Topmodel: A critique. Hydrological Processes 11: 1069-1085 https://doi.org/10.1002/(SICI)1099-1085(199707)11:9<1069::AID-HYP545>3.0.CO;2-O
  17. Beven, K.J. and A.M. Binley. 1992. The furture of distributed models: model calibration and uncertainty prediction. Hydrological Processes 6: 279-293 https://doi.org/10.1002/hyp.3360060305
  18. Beven, K.J. and E.F. Wood. 1983. Catchment geomorphology and the dynamics of runoff contributing areas. Journal of Hydrology 65: 139-158 https://doi.org/10.1016/0022-1694(83)90214-7
  19. Beven, K.J. and M.J. Kirkby. 1979. A physically based variable contributing area model of basin hydrology. Hydrological Sciences Bulletin 24(1): 43-69 https://doi.org/10.1080/02626667909491834
  20. Beven, K.J., R. Lamb, P. Quinn, R. Romanowiez and J. Freer. 1995. TOPMODEL. p. 627-668. In: Singh, V.P. (eds.), Computer Models of Watershed Hydrology. Water Resources Publications. USA
  21. Chang, J.H., Y.K. Tung and J.C. Yang. 1994. Monte Carlo simulation for correlated variables with marginal distributions. Journal of Hydraulic Engineering 120(3): 313-331 https://doi.org/10.1061/(ASCE)0733-9429(1994)120:3(313)
  22. Domingo, F., G. Sánchez, M.J. Moro, A.J. Brenner and J. Puigdefábregas. 1998. Measurement and modelling of rainfall interception by three semi-arid canopies. Agricultural and Forest Meteorology 91: 275-292 https://doi.org/10.1016/S0168-1923(98)00068-9
  23. Fisher, J. and K.J. Beven. 1996. Modelling of streamflow at Slapton Wood using TOPMODEL within and uncertainty estimation framework. Field Studies 8: 577-584
  24. Fishman, G.S. 1996. Monte Carlo: concepts, algorithms, and applications, Springer Verlag, New York. 698 p.
  25. Franchini, M., J. Wending, C. Obled and E. Todini. 1996. Physical interpretation and sensitivity analysis of the TOPMODEL. Journal of Hydrology 175: 293-338 https://doi.org/10.1016/S0022-1694(96)80015-1
  26. Gardner, R.H., D.D. Huff, R.V. O'Neill, J.B. Mankin, J. Garney and J. Jones. 1980. Application of error analysis to a marsh hydrology model. Water Resources Research 16(4): 659-664 https://doi.org/10.1029/WR016i004p00659
  27. Holko, I. and A. Lepisto. 1997. Modelling the hydrological behaviour of a mountain catchment using TOPMODEL. Journal of Hydrology 196: 361-377 https://doi.org/10.1016/S0022-1694(96)03237-4
  28. Iorgulescu, I. and J.P. Jordan. 1994. Validation of TOPMODEL in a small Swiss catchment. Journal of Hydrology 159: 255-273 https://doi.org/10.1016/0022-1694(94)90260-7
  29. Krajewski, W.F., V. Lakshmi, K.P. Georgakakos and S.C. Jain. 1991. A Monte Carlo study of rainfall sampling effect on a distributed catchment model. Water Resources Research 27(1): 119-128 https://doi.org/10.1029/90WR01977
  30. Nash, J.E. and J.V. Sutcliffe. 1970. River flow forecasting through conceptual models. I. A discussion for principles. Journal of Hydrology 10: 282-290 https://doi.org/10.1016/0022-1694(70)90255-6
  31. Ostendorf, B. 1996. The influence of hydrological processes on spatial and temporal pattern of $CO_2$ soil efflux from an arctic tundra environment. Arctic and Alpine Research 28: 316-325
  32. Ostendorf, B., P.F. Quinn, K.J. Beven and J.D. Tenhunen. 1996. Hydrological controls on ecosystem gas exchange in an Arctic landscape. p. 369-386. In: Reynolds, J.R. and J.D. Tenhunen (eds.), Landscape Function and Disturbance in Arctic Tundra. Springer-Verlag, Berlin
  33. Pinol, J., K.J. Beven and J. Freer. 1997. Modelling the hydrological response of Mediterranean catchments, Prades, Catalonia. The use of distributed models as aids to hypothesis testing. Hydrological Processes 11: 1287-1306 https://doi.org/10.1002/(SICI)1099-1085(199707)11:9<1287::AID-HYP561>3.0.CO;2-W
  34. Quinn, P.F. and K.J. Beven. 1993. Spatial and temporal predictions of soil moisture dynamics, runoff variable source areas and evapotranspiration for Plynlimon, mid- Wales. Hydrological Processes 7: 425-448 https://doi.org/10.1002/hyp.3360070407
  35. Refsgaard, J.C. and B. Storm. 1995. MIKE SHE. pp. 809- 846. In: Singh, V.P. (eds.), Computer Models of Watershed Hydrology. Water Resources Publications. USA
  36. Singh, V.P. 1995. Computer models of watershed hydrology. Water Resources Publications. USA. 1144 p.
  37. Takasao, T. and K. Takara. 1998. Evaluation of rainfallrunoff models from the stochastic viewpoint. Journal of Hydrology 102: 381-406 https://doi.org/10.1016/0022-1694(88)90108-4
  38. Troch, P.A., M. Mancini, C. Paniconi and E.F. Wood. 1993. Evaluation of a distributed catchment scale water balance model. Water Resources Research 29: 1805-1817 https://doi.org/10.1029/93WR00398
  39. Wolock, D.M. and G.J. McCabe. 1995. Comparison of single and multiple flow direction algorithms for computing topographic parameters in TOPMODEL. Water Resources Research 31: 1315-1324 https://doi.org/10.1029/95WR00471
  40. Young, R.A., C.A. Onstand, D.D. Bosch and W.P. Anderson. 1989. AGNPS. A non-point source pollution model for evaluating agricultural watersheds. Journal of Soil Water Conservation 44(2): 168-173