mojdeh mohammadi; Hossein Malekinezhad; Mohammad Taghi Dastorani
Abstract
Main problems in flood frequency analysis are limited number of gauging stations and recorded data, together with the inaccurate at-site estimations in the study area. These problems have caused increasing application of regional methods. Regional analysis seems to be a useful method for estimating peak ...
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Main problems in flood frequency analysis are limited number of gauging stations and recorded data, together with the inaccurate at-site estimations in the study area. These problems have caused increasing application of regional methods. Regional analysis seems to be a useful method for estimating peak flow at an area of no data or low-recorded length. Regional flood frequency analysis relies on physical and climatic characteristic of basins and applies statistical method to study flow records. The methods of regional analysis are numerous that the selection of each one of them in any study area depends on data length, climatic factors, data type and expected return periods. In this study, four techniques of regional analysis were used to evaluate the priority and importance to estimate the peak flow for different return periods. The Hybrid, Multiple regression, L-moments and Canonical Correlation Analysis are the four approaches applied for some watersheds of Isfahan–Sirjan and Yazd-Ardakan Basins. A number of 16 stations were selected and their data were analyzed to find out peak flow. The results of this analysis were compared to the Hybrid and Multiple regression approaches using RRMSE and MAE statistics. The results showed better performance of the CCA method rather than other methods in all return periods. After CCA, Multiple regression methods were selected to estimate the peak flow (Model 2, 3). Therefore, CCA method can be adopted as regional flood frequency method for the study area.
Jamal Mosaffaie; Davoud Akhzari; Saeed Rashvand; Javad Ataei
Abstract
One of the important parameters in the design of flood control structures is to determine flood peak discharge for various return periods. A primary issue of planners in the face with flood is lack of data or insufficient data. One of the most reliable strategies is generalizing the results from sites ...
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One of the important parameters in the design of flood control structures is to determine flood peak discharge for various return periods. A primary issue of planners in the face with flood is lack of data or insufficient data. One of the most reliable strategies is generalizing the results from sites with observed data to ungauged locations. The main goal of this study is regional flood frequency analysis using multiple regression method for Qazvin province of Iran. 8 out of 23 existing hydrometric station were removed because of the short-term statistics and construction of storage dam at upstream. The results of factor analysis showed that perimeter, equivalent diameter, time of concentration, length of main waterway and area were the main variables affecting flood magnitude. The remaining 15 stations were divided into two homogenous regions using cluster analysis. Homogeneity of these two regions was confirmed using homogeneity and heterogeneity tests of L-moments. Based on the best-fit criteria of Zdist, GNO distribution with the statistic of 0.29 has the best fit for the entire region but for one and two homogeneous regions, GLO and GPA distributions with the statistics equal to 0.09 & 1.56 have the best fit respectively. After calculating parameter values for selected distributions, discharges with different return periods were estimated for all stations. Then, regression relations were obtained between peak discharge and factors affecting flood peak for each return periods at two homogeneous regions. Peak discharges at ungauged locations can be estimated for different recurrence interval using these relationships.
