Efficiency Evaluation of the VIKOR, L-THIA, and Artificial Neural Network (ANT) Models in Flood Zone Analysis (Case Study: Khorasan Razavi Province)

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Zanganeh Asadi Mohammad Ali; Amir Ahmadi Abolghasem; NAEMI TABAR MAHNAZ

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Journal Paper

Paper Information

Journal: IRANIAN JOURNAL OF ECOHYDROLOGY Year:2021 | Volume:8 | Issue:1 Page(s): 89-108

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Information Journal Paper

Title

Efficiency Evaluation of the VIKOR, L-THIA, and Artificial Neural Network (ANT) Models in Flood Zone Analysis (Case Study: Khorasan Razavi Province)

Author(s)

Zanganeh Asadi Mohammad Ali | Amir Ahmadi Abolghasem | NAEMI TABAR MAHNAZ | Issue Writer Certificate

Keywords

Flood

Basins

Gamma test

modeling

zoning

Abstract

Considering the natural conditions of Iran, not paying attention to floods can cause irreparable damages, among which Flood estimation and zoning of floodplain areas are very significant in controlling hazards, so zoning of climate change is necessary. The present study aims to investigate the risk of floods in selected Basins of Khorasan Razavi using the VIKOR, L-THIA, and ANT models. Then, fourteen variables affecting the occurrence of floods including climate, land use, altitude, drainage density, geomorphological units, lithology, run-off height, permeability, slope and direction, distance to rivers/waterways, precipitation, temperature, and soil were used. The results showed that among the mentioned variables, climate parameters, land use, slope, drainage density, distance to rivers/waterways, precipitation, soil, and geomorphological units have greater effects on the occurrence of floods according to statistical calculations. Quantitative and qualitative evaluation of the results using various statistics showed that the L-THIA model, with a γ, =0. 8, had the highest correlation with the primary layers and was more accurate and efficient than the two VIKOR and ANT models in Flood prediction.

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APA: Copy

Zanganeh Asadi, Mohammad Ali, Amir Ahmadi, Abolghasem, & NAEMI TABAR, MAHNAZ. (2021). Efficiency Evaluation of the VIKOR, L-THIA, and Artificial Neural Network (ANT) Models in Flood Zone Analysis (Case Study: Khorasan Razavi Province). IRANIAN JOURNAL OF ECOHYDROLOGY, 8(1 ), 89-108. SID. https://sid.ir/paper/1058850/en

Vancouver: Copy

Zanganeh Asadi Mohammad Ali, Amir Ahmadi Abolghasem, NAEMI TABAR MAHNAZ. Efficiency Evaluation of the VIKOR, L-THIA, and Artificial Neural Network (ANT) Models in Flood Zone Analysis (Case Study: Khorasan Razavi Province). IRANIAN JOURNAL OF ECOHYDROLOGY[Internet]. 2021;8(1 ):89-108. Available from: https://sid.ir/paper/1058850/en

IEEE: Copy

Mohammad Ali Zanganeh Asadi, Abolghasem Amir Ahmadi, and MAHNAZ NAEMI TABAR, “Efficiency Evaluation of the VIKOR, L-THIA, and Artificial Neural Network (ANT) Models in Flood Zone Analysis (Case Study: Khorasan Razavi Province),” IRANIAN JOURNAL OF ECOHYDROLOGY, vol. 8, no. 1 , pp. 89–108, 2021, [Online]. Available: https://sid.ir/paper/1058850/en

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