2019
DOI: 10.4314/mejs.v11i1.6
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Flood Hazard and Flood Risk Vulnerability Mapping Using Geo-Spatial and MCDA around Adigrat, Tigray Region, Northern Ethiopia

Abstract: In Ethiopia, urban floods incidents are becoming a serious problem in recent years. They are mainly associated with poorly designed urban drainage system and land use planning. Combined to it, lack of early warning system and organized flood disaster mitigation measures at national and local level further increases the gravity of the problem. Adigrat is one of the north Ethiopian towns which is frequently attacked by these floods. To understand and address the issue, a study was conducted around Adigrat town w… Show more

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Cited by 39 publications
(36 citation statements)
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“…Slope (SP) was another significant factor associated with the house collapse rate, with a determinant power of 0.17, and exerted a notable effect on the house collapse rate that was comparable to the results of some previous studies (Smyth and Royle 2000;Fernandez and Lutz 2010). Nigusse and Adhanom (2019) reported that, in areas with flat slopes and lower elevations, more people and buildings are the most vulnerable to flooding. Smyth and Royle (2000) demonstrated that slope has an important effect on house damage.…”
Section: Spatial Clusterssupporting
confidence: 84%
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“…Slope (SP) was another significant factor associated with the house collapse rate, with a determinant power of 0.17, and exerted a notable effect on the house collapse rate that was comparable to the results of some previous studies (Smyth and Royle 2000;Fernandez and Lutz 2010). Nigusse and Adhanom (2019) reported that, in areas with flat slopes and lower elevations, more people and buildings are the most vulnerable to flooding. Smyth and Royle (2000) demonstrated that slope has an important effect on house damage.…”
Section: Spatial Clusterssupporting
confidence: 84%
“…Based on a comprehensive consideration of the hazard, the environment, the vulnerability of the affected communities, the disaster prevention and reduction capacity (Shi et al 2020), the results of previous studies (Gong and Hu 2015;Hu et al 2018;Nigusse and Adhanom 2019;Yuan et al 2020), and the availability of data, the 2018 house structures for each county of the study area that is the ratio of steel-concrete houses (RS), the ratio of brick-concrete houses (RC), and the ratio of brick-wood houses (RB) were taken as the explanatory variables. The variables of the socioeconomic factors for each county included the population density (PD), per capita GDP (PG), the ratio of urban to rural population (UR), high school penetration rate (HS), per capita housing area (PA), and the proportion of the tertiary industry (PT).…”
Section: Potential Driving Factors Of House Collapse and Proxiesmentioning
confidence: 99%
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