A Systematic Review of Flood Damage Assessment: Insight for the Data-Scarce Regions

Noor Suraya Romali (), Sumiliana Sulong and Akiyuki Kawasaki
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Noor Suraya Romali: Universiti Malaysia Pahang Al- Sultan Abdullah
Sumiliana Sulong: Universiti Malaysia Pahang Al- Sultan Abdullah
Akiyuki Kawasaki: The University of Tokyo

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2025, vol. 39, issue 10, No 1, 4707-4734

Abstract: Abstract Literature gaps on the methodologies employed in developing countries facing data scarcity remain unresolved despite the growing literature on flood damage assessment. As such, this study aims to review flood damage assessment methods, with a specific emphasis on their application in data-scarce regions. The novelty of this paper lies in identifying the encountered challenges and providing recommendations for future research on methods tailored to address these issues. A total of 129 peer-reviewed articles published from 2000 to March 2024 were systematically assessed. Approximately 67% of the studies were conducted in developed countries, with the remaining 33% performed in developing countries. Given that 80% of the articles were published from 2010, developing countries highlight an exponential rise in research contributions. Unit loss methods, damage curve, and multivariate models were found to be the most frequently-used assessment methods. The study identified a critical gap in existing flood damage estimation methods, specifically their limited applicability in data-scarce regions due to insufficient data. Developing countries could benefit from applying the multivariate model, which facilitates synthetic data generation by establishing relationships between flood damage and variables pertaining to flood resistance and impact. This approach allows for more robust flood damage assessments in developing countries, which is key to bridging the existing gap in data-scarce regions.

Keywords: Flood risk management; Flood damage assessment; Data scarcity; Multivariate model; Developing countries (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11269-025-04265-9

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