Flood Risk Perception and Its Attributes among Rural Households under Developing Country Conditions: The Case of Pakistan

• Published in: Water (Basel) Vol. 14; no. 6; p. 992
• Main Authors: Shah, Ashfaq Ahmad, Ajiang, Chen, Khan, Nasir Abbas, Alotaibi, Bader Alhafi, Tariq, Muhammad Atiq Ur Rehman
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.03.2022
• Subjects: Adaptation; Climate change; Community; Developing countries; Disaster management; Disaster victims; Disasters; Education; Emergency management; Emergency preparedness; Extreme weather; Family size; flood disaster; Flood forecasting; Flood management; Floods; Households; Khyber Pakhtunkhwa; LDCs; Natural disasters; Organizational aspects; Perception; Perceptions; Political ecology; preparedness; Risk assessment; Risk communication; Risk factors; Risk management; Risk perception; Rural areas; rural communities; Rural populations; Social factors; Society; socioeconomic and institutional factors; Socioeconomic factors; Socioeconomics; Pakistan
• ISSN: 2073-4441; 2073-4441
• DOI: 10.3390/w14060992

Managing and communicating flood risks necessitates a strong understanding of how people perceive risk. It has become critical to examine risk perception to implement effective disaster risk management (DRM) measures. Socioeconomic determinants have an impact on risk perception, which in turn affects future adaptive capacity and disaster preparedness. First and foremost, this research attempts to determine how Pakistani people in rural areas perceive flood risk, and second, to examine the factors that can influence rural residents’ perceptions of flood risk. The data for this study were collected through face-to-face interviews with 600 respondents (household heads) from Charsadda and Nowshera districts that were severely affected by the 2010 flood. A flood risk perception index was developed (using a risk matrix) using relevant attributes on a Likert scale and classified into two categories: high and low perceived risk. Furthermore, a binary regression model was used to examine the influence of socioeconomic and institutional factors on rural households’ risk perception. Flood risk was perceived by 67 percent of the total sampled participants in the study regions. The results of binary logistic regression demonstrate that flood risk perception is strongly linked to socioeconomic variables such as age, education, house ownership, family size, past flood experience, and distance from the nearest river source, as well as institutional factors such as access to credit and extreme weather forecast information. The findings of the current study additionally revealed that flood risk perception varied among household heads based on education (1–10 years perceived high flood risk (51.47%)), age (age greater than 40 years perceived high flood risk (52.83%)), and monthly income levels (lower monthly income group perceived high flood risk (73.02%)). The findings of this study shed light on rural households’ perception of flood risk and the factors that shape such perceptions. These findings can assist provincial and local disaster management authorities in better understanding flood risk and adopting local actions that could be used to respond to flood and other climate-related disasters.