A hybrid method to predict flood vulnerability using MCDM methods and Pareto analysis in GIS framework

被引：0

作者：

Mishra, Priya ^{[1
]}

Prasad, Sanjeev Kr. ^{[1
]}

机构：

[1] School of Computer Science and Engineering, Galgotias University, Greater Noida

来源：

International Journal of Water | 2024年 / 16卷 / 04期

关键词：

AUC-ROC; flood hazard mapping; geographic information systems; Ghaghara basin; GIS; Google Earth engine; MCDM; multi-criteria decision making; Pareto analysis; Shuttle Radar Topography Mission; SRTM;

D O I：

10.1504/IJW.2024.146743

中图分类号：

学科分类号：

摘要：

The Rapti and Ghaghara rivers, most prone to flooding in northeastern Uttar Pradesh, India, have caused significant damage and loss of life. Due to flood damage, thorough and robust flood mitigation modelling methods are needed. Thus, this study uses multi-criteria decision making (MCDM) models (AHP, fuzzy-AHP, and Monte Carlo-AHP), geographic information systems (GIS), and remote sensing (RS) to create a regional flood susceptibility map. The study uses expert surveys and Pareto analysis to identify seven significant flood factors: drainage density, elevation, slope, land use/cover, average rainfall, topographic wetness index (TWI), and river proximity. Flood susceptibility maps are created using a weighted overlay approach and divided into five susceptibility zones. Fuzzy-AHP (FAHP) had the highest predictive accuracy, with AUC values of 0.92, 0.85 for Monte Carlo AHP (MC-AHP), and 0.75 for AHP. The flood susceptibility maps were verified using Uttar Pradesh official flood data from 2022, and 2023, bolstering their trustworthiness. Copyright © 2024 Inderscience Enterprises Ltd.

引用

页码：321 / 348

页数：27

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