Enhancing Flood Risk Management: A Review on Numerical Modelling of Past Flood Events
Recent scientific literature has consistently highlighted a significant increase in both the frequency and intensity of flood events, primarily attributed to the effects of climate change. Projections suggest that this trend will likely intensify in the coming decades. In this context, enhancing our...
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Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-05-01
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Series: | Hydrology |
Subjects: | |
Online Access: | https://www.mdpi.com/2306-5338/12/6/133 |
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Summary: | Recent scientific literature has consistently highlighted a significant increase in both the frequency and intensity of flood events, primarily attributed to the effects of climate change. Projections suggest that this trend will likely intensify in the coming decades. In this context, enhancing our understanding of flooding dynamics becomes not only necessary but urgent. A critical component of this advancement lies in the numerical analysis of historical flood events, which provides valuable insights into flood behaviour across extended temporal and spatial scales. This approach enables two key outcomes: a significant improvement in conventional methods for estimating return periods and a reduction in the uncertainties associated with historical flood events by simulating multiple plausible scenarios to identify the most likely one. This paper presents a comprehensive review of the scientific literature focused on the numerical simulation and reconstruction of past flood events. Two main conclusions emerge from this review: First, the temporal scope of the studies is notably wide, covering events ranging from glacial periods to those occurring in the mid-20th century. Second, there exists a pronounced spatial imbalance in the geographical distribution of these studies, with certain regions significantly underrepresented. This review provides a valuable resource for researchers and practitioners working in flood risk assessment and hydrological modelling. By consolidating existing knowledge, it supports the development and refinement of decision-support tools aimed at improving mitigation strategies to reduce the impact of flooding on both populations and infrastructure. |
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ISSN: | 2306-5338 |