• Title/Summary/Keyword: gaged rainfall events

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The Developmet and Application of GIS-Based Geomorpho-Hydrological Watershed Model (G2WMS) (GIS기반 지형수문유역모의 모형의 개발 및 적용 연구)

  • Kim, Hong-Tae;Shin, Hyun-Suk
    • Journal of the Korean Society of Hazard Mitigation
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    • v.9 no.1
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    • pp.123-133
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    • 2009
  • In this study, we developed the GIS-based Geomorpho-hydrological Watershed Modeling System($G^{2}WMS$) which could consider both nonlilear rainfall-runoff relationship based on Geomorpho-Climatic Unit Hydrograph(GCUH) as well as watershed system inducing river routing. The developed new model was calibrated at the gaged rainfall events at natural watersheds and previewed to apply at the ungaged mountain basins, such as Sulma basin for small mountain basin and Andong-Dam basin for large scale basin, compared single with partitioned basin in the observed unit hydrographs and rainfall-discharge events. Finally, at the large scale Andong dam basin, we concluded that partitioned basin cases which including th nonlinear GCUH and river routing methods were superior to single basins which including the traditional methods in rainfall-discharge simulation at the mountain basins.

A Rainfall Forecasting Model for the Ungaged Point of Meteorological Data (기상 자료 미계측 지점의 강우 예보 모형)

  • Lee, Jae Hyoung;Jeon, Ir Kweon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.14 no.2
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    • pp.307-316
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    • 1994
  • The rainfall forecasting model of the short term is improved at the point where meterological data is not gaged. In this study, the adopted model is based on the assumptions for simulation model of rainfall process, meteorological homogeneousness, prediction and estimation of meteorological data. A Kalman Filter technique is used for rainfall forecasting. In the existing models, the equation of the model is non-linear type with regard to rainfall rate, because hydrometer size distribution (HSD) depends on rainfall intensity. The equation is linearized about rainfall rate as HSD is formulated by the function of the water storage in the cloud. And meteorological input variables are predicted by emprical model. It is applied to the storm events over Taech'ong Dam area. The results show that root mean square error between the forecasted and the observed rainfall intensity is varing from 0.3 to 1.01 mm/hr. It is suggested that the assumptions of this study be reasonable and our model is useful for the short term rainfall forecasting at the ungaged point of the meteorological data.

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Development of Runoff Hydrograph Model for the Derivation of Optimal Design Flood of Agricultural Hydraulic Structures(1) (농업수리구조물의 적정설계홍수량 유도를 위한 유출수문곡선모형의 개발(I))

  • 이순혁;박명근;맹승진
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.37 no.3_4
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    • pp.34-47
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    • 1995
  • It is experienced fact as a regular annual event that the structure to he designed on unreasonable flood for the agricultural structures including reservoirs have been brought not only loss of lives, but also enormous property damage. For the solution of this problem at issue, this study was conducted to develop an optimal runoff hydrograph model by comparison of the peak flows and time to peak between observed and simulated flows derived by linear time-invariant and linear time-variant models under the condition of having a short duration of heavy rainfall with uniform rainfall intensity at nine small watersheds which are within the range of 55.9 to 140.7 square kilometers in area in Han, Geum, Nagdong and Yeongsan Rivers. The results obtained through this study can be summarized as follows. 1. Storage constants and Gamma function arguments were calculated within the range of 1.2 to 6.42 and of 1.28 to 8.05 respectively by the moment method as the parameters for the analysis of runoff hydrograph based on linear time-invariant model. 2. Parameters for both linear time-invariant and linear time-variant models were calibrated with nine gaged watershed data, using a trial and error method. The resulting parameters including Gamma function argument, N and storage constant, K for linear time-invariant model were related statistically to watershed characteristic variables such as area, slope, length of main stream and the centroid length of the basin. 3. Average relative errors of the simulated peak discharge of calibrated runoff hydrographs by using linear time-variant and linear time-invariant models were shown to be 0.75 and 5.42 percent respectively to the peak of observed runoff hydrographs. Correlation coefficients for the statistical analysis in the same condition were shown to be 0.999 and 0.978 with a high significance respectively. Therefore, it can be concluded that the accuracy of a linear time-variant model is approaching more closely to the observed runoff hydrograph than that of a linear time-invariant model in the applied watersheds. 4. Average relative errors of the time to peak of calibrated runoff hydrographs by using linear time-variant and linear time-invariant models were shown to be 16.44 and 19.89 percent respectively to the time to peak of observed runoff hydrographs. Correlation coefficients in the same condition were also shown to be 0.999 and 0.886 with a high significance respectively. 5. It can be seen that the shape of simulated hydrograph based on a linear time- variant model is getting closer to the observed runoff hydrograph than that of a linear time-invariant model in the applied watersheds. 6. Two different models were verified with different rainfall-runoff events from data for the calibration by relative error and correlation analysis. Consequently, it can be generally concluded that verification results for the peak discharge and time to peak of simulated runoff hydrographs were in good agreement with those of calibrated runoff hydrographs.

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