Monday, 8 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
Flood is a destructive phenomenon with meteorological and hydrological nature that causes casualties and financial losses every year. Therefore, simulation and prediction of severity and time of occurrence of this event can prevent these losses to a great extent. In order to achieve this goal, simulation of observed flooding in selected events is performed by optimization and calibration of the parameters of two hydrological models including Hydrological Model (HyMod) and a rainfall-runoff model named Asymmetric Laplace Unit Hydrograph (ALUH). More than 90 flood events, having different magnitude and duration; in the period 1991-2015 were selected in western boundary basin in Ilam, Iran (46º25′E,33º38′N). In order to identify return periods and the most likely time for occurrence of large-scale flood events, extreme values and harmonics analysis are performed on the time series of observed annual maximum precipitation and runoff. Calibration, verification and evaluation of performance of models according to Nash-Sutcliffe Efficiency (NSE) and root mean square (RMS) error of observations to standard deviation ratio indices are performed in 18 selected events. Then, the empirical relationships between characteristics of rainfall and runoff and sensitivity of ALUH model to each parameter are investigated. The results indicate that regional precipitation is mainly in form of rain and more than 200 mm/day rainfall and 2000 m3/s peak flow is possible with return period of 100 years. Overall, Harmonics of precipitations are in a 15 days advance compared to those of runoff and mostly reach to their peak in November, showing a high possibility of flood in it. The simulation results show that both models had good performance in calibration stage but ALUH model has good performance of in all conditions, including extremely positive to symmetric and unusual negative skewed event. Favorite results of study suggest applicability of ALUH for operational use on hydrograph simulation and prediction.
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