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Information Journal Paper

Title

AN INNOVATIVE METHOD FOR REGIONAL FLOOD MAGNITUDE PREDICTION IN RIVER NETWORKS

Pages

  79-88

Abstract

 Determining of the probable maximum flood magnitude at certain frequency is a major undertaking in flood control programs and hydraulic structure design. This is a difficult problem when and where accurate and long term data are not available. Regional analysis is a robust method to estimate flood magnitude in such circumstances, using existing local data and considering effective parameters. In this work, we have developed a model using regional analysis and extended it through the river network in a GIS-based environment. Regional analysis was performed with MULTIPLE REGRESSIONS and spatial extensions for the Karkheh, Karoun and Dez basins. Frequency analysis was performed for annual maximum discharges. Then, by getting from the hydrologic variables obtained in the previous step, their archival cluster analysis performed to identity the similar regions, and the best model for each region was developed by multiple regression. This was achieved by developing an improved MATLAB program, which is capable of mapping the regional analysis equations for the flooding river networks, using computational and stochastical operators for effective parameter determination on flood discharge.

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    APA: Copy

    SAGHAFIYAN, B., BAGHERI, M., & GHERMEZ CHESHMEH, B.. (2015). AN INNOVATIVE METHOD FOR REGIONAL FLOOD MAGNITUDE PREDICTION IN RIVER NETWORKS. WATER ENGINEERING, 8(24), 79-88. SID. https://sid.ir/paper/169351/en

    Vancouver: Copy

    SAGHAFIYAN B., BAGHERI M., GHERMEZ CHESHMEH B.. AN INNOVATIVE METHOD FOR REGIONAL FLOOD MAGNITUDE PREDICTION IN RIVER NETWORKS. WATER ENGINEERING[Internet]. 2015;8(24):79-88. Available from: https://sid.ir/paper/169351/en

    IEEE: Copy

    B. SAGHAFIYAN, M. BAGHERI, and B. GHERMEZ CHESHMEH, “AN INNOVATIVE METHOD FOR REGIONAL FLOOD MAGNITUDE PREDICTION IN RIVER NETWORKS,” WATER ENGINEERING, vol. 8, no. 24, pp. 79–88, 2015, [Online]. Available: https://sid.ir/paper/169351/en

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