Effect of uncertainties in breach location and breach mechanisms on risk‐related classification of off‐stream reservoirs

Abstract Off‐stream reservoirs are artificial water storage structures that increase the flood risk of an area. In some places, related risk reduction plans are based on a risk classification of these structures, which follows local water resource management regulations. These classification methods typically follow deterministic qualitative guidelines that do not account for uncertainties. This study introduces a fourth‐step probabilistic approach that accounts for uncertainties related to simultaneous breach formation and breaking point location of off‐stream reservoirs, and proposes an alternative visualisation for their classification. The methodology is applied to a set of Spanish off‐stream reservoirs that are classified according to the Spanish normative. Results show that different breaking points and breach formations generate diverse classifications that can affect risk reduction plans. Additionally, we demonstrate that the proposed visualisation can be used for various purposes, including the case of the evolution of the categorisation in time, due to land use changes, which could be used by decision‐makers to understand which off‐stream reservoir requires a category update. These findings introduce a novel approach to managing uncertainties, which is crucial for developing resilient flood management strategies and contributes to the innovation discourse in flood risk management.

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Publication Details

Journal
Journal of Flood Risk Management
Published
2024-11-06
DOI
https://doi.org/10.1111/jfr3.13044
Citations
1
Primary Topic
Dam Engineering and Safety
Type
article
Field-Weighted Citation Impact
0.26
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article

Effect of uncertainties in breach location and breach mechanisms on risk‐related classification of off‐stream reservoirs

Nathalia Silva‐Cancino, Leonardo Alfonso
1 citations
Journal of Flood Risk Management
Dam Engineering and Safety
0.26
article

Effect of uncertainties in breach location and breach mechanisms on risk‐related classification of off‐stream reservoirs

Nathalia Silva‐Cancino, Leonardo Alfonso
article en
1 citations

Abstract

Abstract Off‐stream reservoirs are artificial water storage structures that increase the flood risk of an area. In some places, related risk reduction plans are based on a risk classification of these structures, which follows local water resource management regulations. These classification methods typically follow deterministic qualitative guidelines that do not account for uncertainties. This study introduces a fourth‐step probabilistic approach that accounts for uncertainties related to simultaneous breach formation and breaking point location of off‐stream reservoirs, and proposes an alternative visualisation for their classification. The methodology is applied to a set of Spanish off‐stream reservoirs that are classified according to the Spanish normative. Results show that different breaking points and breach formations generate diverse classifications that can affect risk reduction plans. Additionally, we demonstrate that the proposed visualisation can be used for various purposes, including the case of the evolution of the categorisation in time, due to land use changes, which could be used by decision‐makers to understand which off‐stream reservoir requires a category update. These findings introduce a novel approach to managing uncertainties, which is crucial for developing resilient flood management strategies and contributes to the innovation discourse in flood risk management.

Journal of Flood Risk ManagementVol. 18(1)
IHE Delft Institute for Water Education (NL), International Center for Numerical Methods in Engineering (ES), Universitat Politècnica de Catalunya (ES)
Openalex Percentile: Top 43%
Dam Engineering and Safety
0.26
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Effect of uncertainties in breach location and breach mechanisms on risk‐related classification of off‐stream reservoirs — Nathalia Silva‐Cancino, Leonardo Alfonso · Journal of Flood Risk Management (2024) | TGRS Research Map | TGRS