This study aimed to estimate the risk of low-income people whose suffer livelihood problems and housing damage due to present and future flooding, which will be affected by climate change. Data about problems in livelihood and housing damage affected by various flooding characteristics of households were collected in three low-income settlements in Chiang Mai which experience different flood types: flash floods, drainage floods and river floods. The data about livelihood problems and housing damage was developed using mathematical models by using ordinal logistic regression methodology. The five variables included house style, flood depth, duration, flow velocity, and frequency. These variables were used in the models which estimated housing damage and living problems probability during the floods. Then the future flood scenarios of the household were put into the models. It was found that living problems and housing damage were different among the households even though they were in the same community. This difference was due to the variations in housing style and the flood characteristics of each household. These models could be used to estimate future living problems and housing damage of other low-income settlements. The results could be analyzed and used to design low-income housing that is more resilient to flooding.
Nachawit Tikul, Maejo University, Thailand
Sirichai Hongwitthayakon, Maejo University, Thailand
Pansuk Pakdee, Maejo University, Thailand
Stream: Social Sustainability and Sustainable Living
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