Dlpak Ahmed Hamaamin; Amjad Maleki; Arash Azari; Azzadeen Darwesh; Mohammed Ahmadi
Abstract
Flood is inherently an uncertain phenomenon and the certainty and credibility of flood forecasting and warning systems will cause errors regardless of the sources of uncertainty. Extreme rainfall events are one of the most important input data to rainfall-runoff models, which always have uncertainty. ...
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Flood is inherently an uncertain phenomenon and the certainty and credibility of flood forecasting and warning systems will cause errors regardless of the sources of uncertainty. Extreme rainfall events are one of the most important input data to rainfall-runoff models, which always have uncertainty. Considering this issue the uncertainty of the design flood hydrograph can be investigated for different return periods. In this research first to simulate the flood hydrograph the HEC-HMS model was calibrated and validated based on the hourly flood hydrographs recorded at the basin outlet. Historical data were collected on the 24-hour maximum rainfall of Gharesoo Basin stations with 30-year statistics and the affected basins were identified. Then in each station 30 series of 30 years of artificial data with a maximum 24-hour rainfall were produced. For each of these produced stochastic series the best statistical distribution was fitted and in each series extreme values with a return period of 25 50 100 and 1000 years were calculated. Finally in each return period by combining 30 different amounts of rainfall obtained from stochastic series, the uncertainty bandwidth of the flood hydrograph was obtained during this return period. The results indicated that the highest predicted peak discharge for different return periods was between 1.2 and 1.7 times the historically recorded discharge during that return period. Generally the maximum discharge of different return periods was between 1.5 and 3 times the minimum discharge.
