DOI QR코드

DOI QR Code

Resampling for Roughness Coefficient of Surface Runoff Model Using Mosaic Scheme

모자이크기법을 이용한 지표유출모형의 조도계수 리샘플링

  • Park, Sang-Sik (Department of Civil & Environmental Engineering, Dankook University) ;
  • Kang, Boo-Sik (Department of Civil & Environmental Engineering, Dankook University)
  • 박상식 (단국대학교 토목환경공학과) ;
  • 강부식 (단국대학교 토목환경공학과)
  • Received : 2010.10.21
  • Accepted : 2010.12.09
  • Published : 2011.01.31

Abstract

Physically-based resampling scheme for roughness coefficient of surface runoff considering the spatial landuse distribution was suggested for the purpose of effective operational application of recent grid-based distributed rainfall runoff model. Generally grid scale(mother scale) of hydrologic modeling can be greater than the scale (child scale) of original GIS thematic digital map when the objective basin is wide or topographically simple, so the modeler uses large grid scale. The resampled roughness coefficient was estimated and compared using 3 different schemes of Predominant, Composite and Mosaic approaches and total runoff volume and peak streamflow were computed through distributed rainfall-runoff model. For quantitative assessment of biases between computational simulation and observation, runoff responses for the roughness estimated using the 3 different schemes were evaluated using MAPE(Mean Areal Percentage Error), RMSE(Root-Mean Squared Error), and COE(Coefficient of Efficiency). As a result, in the case of 500m scale Mosaic resampling for the natural and urban basin, the distribution of surface runoff roughness coefficient shows biggest difference from that of original scale but surface runoff simulation shows smallest, especially in peakflow rather than total runoff volume.

Keywords

References

  1. 강부식, 김서영, 고익환, 2005, 레이다 강우를 이용한 격자기반의 저수지 홍수유입량 모의, 2005 학술발표회, 한국수자원학회, 183-188.
  2. 건설교통부, 2006, 도시홍수재해관리기술연구사업단 연구성과보고서, 별책 제2권, 도시홍수재해 해석기술.
  3. 건설교통부, 2007, 도시홍수 재해해석 기술.2, 건설기술혁신사업 제4차년도 중간보고서, 별책 제2권, 제1-5세세부과제, 56-102.
  4. 박완희, 2007, 강우-유출해석을 위한 분포형 모형의 적용성 향상에 관한 연구, 석사학위논문, 경기대학교.
  5. 박진혁, 강부식, 2006, 댐유역 홍수예측을 위한 GIS기반의 분포형 모형과 집중형 모형의 유출해석 비교, 한국지리정보 학회지, 9(3), 171-182.
  6. 서울특별시, 2007, 대학과 연계한 하천관리에 대한 연구용역(2단계2차)보고서.
  7. 정인균, 이미선, 박종윤, 김성준, 2008a, 격자기반 운동파강우유출모형 KIMSTORM의 개선(I)-이론 및 모형, 대한토목학회논문집, 28(6B), 697-707.
  8. 정인균, 이미선, 박종윤, 김성준, 2008b. 격자기반 운동파강우유출모형 KIMSTORM의 개선(II)-적용 및 분석, 대한토목학회논문집, 28(6B), 709-721.
  9. 진병화, 황수진, 1999. Vegetation Canopy의 접지층 환경에 대한 열적 영향, 한국환경과학회지, 8(2), 145-150.
  10. Koster, R. D., Suarez, M. J., 1992, A comparative analysis of two land surface heterogeneity representations, Journal of Climate, AMS, 5(12), Article, 1379-1390. https://doi.org/10.1175/1520-0442(1992)005<1379:ACAOTL>2.0.CO;2
  11. Lee, K. H., 2008, Integrating remotely sensed data using a simple vegetation parameter aggregation method applicable to a distributed rainfall-runoff model, ASCE J. of Hydrologic Engineering, 13(4), 236-241. https://doi.org/10.1061/(ASCE)1084-0699(2008)13:4(236)
  12. Nash, J., Sutcliffe, J., 1970, River flow forecasting through conceptual models. Part I - A discussion of principles, Journal of Hydrology, 10(3), 282-290. https://doi.org/10.1016/0022-1694(70)90255-6
  13. Vieux, B. E., 2004, Distributed hydrologic modeling using GIS, Second Edition, Kluwer Academic Publishers, Dordrecht, The Netherlands.
  14. Vieux, B. E., 2005, $Vflo^{TM}$ 3.0 Desktop User manual.
  15. Vieux, B. E., Kang, B., Park, J. H., 2009, Distributed hydrologic prediction: Sensitivity to accuracy of initial soil moisture conditions and radar rainfall input, ASCE J. of Hydrologic Engineering, 14(7), 671-689. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000039