This study is for design of the detention system distributed in a watershed by the Multi-Objective Genetic Algorithms(MOGAs). A new model is developed to determine optimal size and location of detention. The developed model has two primary interfaced components such as a rainfall runoff model to simulate water surface elevation(or flowrate) and MOGAs to get the optimal solution. The objective functions used in this model depend on the peak flow and storage of detention. With various constraints such as structural limitations, capacities of storage and operational targets. The developed model is applied at Gwanyang basin within Anyang watershed. The simulation results show the maximum outlet reduction is occurred at detention facilities located in upper reach of watershed in the peak discharge rates. It is also reviewed the simultaneous construction of an off-line detention and an on-line detention. The methodologies obtained from this study will be used to control the flood discharges and to reduce flood damage in urbanized watershed.

This paper examines the implications of lag structure for estimating the effects of monetary policy shocks in a VAR. A symmetric lag structure in which all variables have the same lag length and an asymmetric lag structure in which the lag length differs across variables but is the same for a particular variable in each equation of the model are examined. This is important in light of the fact that the true lag structure is generally not known. Four commonly used identification schemes are employed to identify monetary policy shocks. Monte Carlo simulations strongly indicate that the lag structure of a VAR model does matter when assessing the quantitative effects of monetary policy shocks. Given the inherent uncertainty about the true lag structure in practice, it is thus important that one compare the impulse response functions from both symmetric lag and asymmetric lag VARs in assessing the effects of monetary policy shocks.

The applicability of the developed distributed rainfall runoff model using a multi-directional flow allocation algorithm and a real-time updating algorithm was evaluated. The rainfall runoff processes were simulated for the events of the Andong dam basin and the Namgang dam basin using raingauge network data and weather radar rainfall data, respectively. Model parameters of the basins were estimated using previous storm event then those parameters were applied to a current storm event. The physical propriety of the multi-directional flow allocation algorithm for flow routing was validated by presenting the result of flow grouping for the Andong dam basin. Results demonstrated that the developed model has efficiency of simulation time with maintaining accuracy by applying the multi-directional flow allocation algorithm and it can obtain more accurate results by applying the real-time updating algorithm. In this study, we demonstrated the applicability of a distributed rainfall runoff model for the advanced basin-wide flood management.

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