• Current Research on Agriculture and Life Sciences
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• v.16
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• pp.37-44
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• 1998

The estimation of PMP (Probable Maximum Precipitation) and the analysis of characteristics of PMF (Probable Maximum Flood) according to the types of time distribution of rainfall and variations of base flow for the determination of design flood of major hydraulic structures in the watershed area of Wi stream were analysed. The PMP was estimated by the hydro-meteorological method suggested by the guideline of the World Meteorological Organization(WMO). The Blocking method was cited to transpose from PMP to PMS (Probable Maximum Storm) with time distribution. The unit hydrograph, applied for the estimation of PMF was derived by Clark's method. The summaryzed results : (1) The 72 hrs duration PMP in the area is 477.3mm which is 80mm less than the PMP map in Korea and 134 mm lager than the maximum precipitation of 342.9mm in Taegu, near the Wi stream watershed. (2) According to the types of time distribution and variations of base flow, the ranges of PMF for advanced type, central type and delayed type are 3,145.3~3,348.3cms, 3,774.6~3,977.7cms and 3,814.6~4,017.3cms, respectively. Those mean that peak discharge of advanced type is 600cms less than the central type and delayed type. (3) Delayed type among three types by Blocking method has been estimated the largest PMF of 4,017.3cms, and the advanced type has been estimated the smallest PMF of 3,145.3cms. The mean value of the peak PMF of 3,653.6cms may probably be resonable PMF in the Wi stream watershed. The mean PMF could probably be 1.7 times lager than the result of Gajiyama's equation. It is equivalent to the flood of return period 1,000 to 10,000 yrs.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.887-901
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• 2022

Estimation of the parameters for individual rainfall-rainfall events can lead to a different set of parameters for each event which result in lack of parameter identifiability. Moreover, it becomes even more ambiguous to determine a representative set of parameters for the watershed due to enhanced variability exceeding the range of model parameters. To reduce the variability of estimated parameters, this study proposed a parameter optimization framework with the simultaneous use of multiple rainfall-runoff events based on NSE as an objective function. It was found that the proposed optimization framework could effectively estimate the representative set of parameters pertained to their physical range over the entire watershed. It is found that the difference in NSE value of optimization when it performed individual and multiple rainfall events, is 0.08. Furthermore, In terms of estimating the observed floods, the representative parameters showed a more improved (or similar) performance compared to the results obtained from the single-event optimization process on an NSE basis.