Accuracy Assessment of Chow's Regression and Stochastic Methods for Estimating Instantaneous Peak Discharge (Case Study: Central Alborz Region)

Salajegheh Ali, Khosravi Mohammad, Mahdavi Mohammad


In this research, accuracy of chow’s regression and stochastic methods was analyzed for estimating instantaneous peak discharge in central Alborz region, Iran. Instantaneous peak discharges data in this region were incomplete, so we were used daily peak flood data for completing Instantaneous peak discharges using regression method. Finally 23 gauge stations with 20 years common data selected for analysis. Used 7 important frequency distributions including, Normal, two parameters Log Normal, three parameters Log Normal, Two parameters Gama, Pearson type three, Log Pearson type three and Gumbel. Then the best distribution was chosen to estimating instantaneous peak discharges for 2, 5, 10, 15, 20, 25, 30, 50 and 100 years return periods. Instantaneous Peak discharges for above return periods were estimated using chow’s regression and Stochastic methods, and were compared with the best fitted distributions results using probabilities indices such as MSE and MBE. Our results showed that chow’s regression method is better than stochastic method for estimating instantaneous peak discharge in central Alborz region.

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