Comparison of hybrid regression and multivariate regression in the regional flood frequency analysis: A case study in Khorasan Razavi province

Seyed Hashem Hosseini, Mohammad Reza Khaleghi*,, and Hasan Jami, Sajjad Baygi, (2018) Comparison of hybrid regression and multivariate regression in the regional flood frequency analysis: A case study in Khorasan Razavi province. Environmental Health Engineering and Management Journal.

[img] Text
6=Khaleghi.pdf - Published Version

Download (743kB)


Background: Magnitude, rate and frequency of the stochastic and unexpected events are of great significance and importance in hydrology. Nowadays, for economic planning of the projects, the use of analytical methods of unexpected events in hydrology is unavoidable. The aim of this study was to compare hybrid regression and multivariate regression to estimate flood peak discharge in the province of Khorasan Razavi and in the selected water measured stations. Methods: For this purpose, 19 hydrometric stations were selected and analyzed. In the first step, the rate of peak discharge was estimated with different return periods and by selecting the best regional distribution (lognormal distribution type ΠΙ). In the next step, independent and important variables including area, mean annual rainfall, the average height of the watershed and its slope were determined using functional analysis and using SPSS software version 22. Then, two hydrologically homogeneous regions were determined by homogeneity test using cluster analysis, and accordingly, two models were presented for the whole area and also for homogeneous areas. To compare and evaluate the accuracy and efficiency of the estimated models, the rates of discharges were estimated and compared with observational rates using three control watersheds. To compare models, it was used from the average absolute values of the relative error index. Results: It was revealed that the hybrid method was more accurate than the multivariate regression method in the return period of 50 years and provides better results of flood discharges for the area. Homogenous areas had a higher coefficient of determination (R2) and lower relative standard error (RSE) compared to the whole area. It was also revealed that with increase of return period, the rates of R2 decreased but the rates of relative standard error increased. Conclusion: The accuracy of multivariate regression and hybrid methods was the same in the 25-year return period. In the present study, the importance and necessity of homogenous areas compared with the model of the whole area are completely evident. Keywords: Floods, Regression analysis, Khorasan Razavi province, Statistical distributions, Hybrid regression

Item Type: Article
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Depositing User: ehemj ehemj ehemj
Date Deposited: 25 Jul 2018 05:31
Last Modified: 25 Jul 2018 05:31

Actions (login required)

View Item View Item