A GIS-based Spatial Multi-criteria Approach for Flash Flood Risk Assessment in the Ngan Sau-Ngan Pho Mountainous River Basin, North Central of Vietnam

Abstract

Flash flood risks in the Ngan Sau-Ngan Pho mountainous river basin (north central of Vietnam) were examined based on GIS and a spatial multi-criteria approach. A set of indicators were firstly proposed for the assessment of hazard, exposure and vulnerability. Analytic hierarchy process (AHP) technique and Iyengar and Sudarshan's method were then applied for calculating weights of hazard and vulnerability indicators, respectively. Flash flood risks were assessed by means of the "risk triangle" approach and were finally validated using past flood records. It was found that flash flood hazard was mainly at medium and low levels, with a very high hazard area of 178.6 ha accounting for 0.1% of the total river basin. Exposure at high and very high levels was mainly detected in the economic center of the basin. The high and very high vulnerability areas accounting for 98.2% of the total area were mainly concentrated in mountainous areas. The largest area was low risk totaling 219,083.1 ha (accounting for 68.6% of the basin area), followed by 67,148.6 ha (very low risk: 21%), 27,181 ha (medium risk: 9%), 5,909.7 ha (high and very high risks: 1.8%). These results demonstrate the proposed set of indicators, GIS and spatial multi-criteria analysis allow for effective flash flood risk assessment in mountains.

Análise Multicriterial De Decisão Aplicada Às Áreas Suscetíveis a Inundação Na Bacia Do Córrego Do Lenheiro – São João Del-Rei, Minas Gerais

“…Os pressupostos metodológicos baseiam-se na aplicação de modelagem por meio da AMD em SIG e da AHP, tendo como referência as investigações de Gigović et al, (2009), Rimba et al (2017), Hoang;Tran;Nguyen (2020); Ogato et al, (2020), dentre outras.…”

“…A Tabela 1 indica matriz elaborada para a modelagem da Bacia do Córrego do Lenheiro. As variáveis foram atribuídas com referência na literatura científica (FLORENZANO, 2008;HOANG;TRAN;NGUYEN, 2020;RAHMATI;ZEINIVAND;BESHARAT, 2020;OGATO et al, 2020;MATERANO;BRITO, 2020), Planos de Contingência, Proteção e Defesa Civil (DEFESA CIVIL, 2013, dados primários coletados em campo sobre os locais de ocorrências de inundações e dados secundários coletados na Defesa Civil para o período de 2016 a 2020.…”

A cartografia de síntese e as estruturas verticais e horizontais da paisagem em ambientes urbanos suscetíveis à inundação

“…A modelagem ambiental dos padrões espaciais teve como fundamentação teórico-metodológica os princípios da Análise Hierárquica de Processos (AHP) proposta por Saaty (2005Saaty ( , 2006 e Gigović et al (2009); Rahmati et al (2015); Santos e Ventorini (2017ab, 2018; Hoang et al, (2020); Ogato et al, (2020), dentre outros que utilizam a Análise Multicritério de Decisão (AMD) e AHP em ambientes de SIG para aplicação de modelagens de áreas propícias às inundações e enchentes.…”

“…Para determinar as variáveis, tomou-se como referência: Florenzano (2008), Dias e Silva (2014), Ceconi (2018), Hoang et al (2020), Rahmati et al (2020), Ogato et al (2020) e Materano e Brito (2020). Estes pesquisadores estabelecem relações entre os elementos os geográficos -hipsometria, declividade, distância euclidiana entre os corpos hídricos e uso da terra -e as ocorrências de inundações.…”

A GIS-Based Comparative Analysis of Frequency Ratio and Statistical Index Models for Flood Susceptibility Mapping in the Upper Krishna Basin, India

“…The FSM includes environmental, geological, geomorphological, meteorological, topographical factors, and soil characteristics [28][29][30][31]. The Logistic Regression (LR), Frequency Ratio (FR), Weight of Evidence (WoE), Statistical Index (SI), Analytical Hierarchy Process (AHP), and Artificial Neural Network (ANN) models have been used by several researchers and government agencies to estimate flood susceptibility precisely [32][33][34][35][36][37][38][39]. Although numerous models have been used for flood susceptibility analysis (FSA), the results obtained by different models varied slightly from region to region.…”