| 1. |
- Karagiorgos, Konstantinos, et al.
(författare)
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Cloudburst catastrophe modelling : Case study – Jönköping municipality, Sweden
- 2021
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In Europe, flash floods are one of the most significant natural hazards, causing serious risk to life and destruction of buildings and infrastructure. The intense rain causing those floods has a few different names, however, with very similar meaning. The term chosen in this study, ‘cloudburst’, was introduced by Woolley (1946) as “…a torrential downpour of rain which by its spottiness and relatively high intensity suggests the bursting and discharge of the whole cloud at once”. While these events play an important role in the ongoing flood risk management discussion, they are under-represented among flood models.The main aim of this study is to demonstrate an approach by showing how methods and techniques can be integrated together to construct a catastrophe model for flash flooding of Jönköping municipality in Sweden. The model is developed in the framework of the ‘Oasis Loss Modelling Framework’ platform, jointly with end-users from the public sector and the insurance industry. Calibration and validation of the model were conducted by comparisons against three historical cloudburst events and corresponding insurance-claim data.The analysis has shown that it is possible to get acceptable results from a cloudburst catastrophe model using only rainfall data, and not surface-water level as driving variable. The approach presented opens up for such loss modelling in places where complex hydraulic modelling cannot be done because of lacking data or skill of responsible staff. The Swedish case study indicates that the framework presented can be considered as an important decision making tool, by establishing an area for collaboration between academia; insurance businesses; and local authorities, to reduce long-term disaster risk in Sweden.
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| 2. |
- Knös, Daniel, et al.
(författare)
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Cloudburst-disaster modelling : A new open-source catastrophe model
- 2022
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Ingår i: International Journal of Disaster Risk Reduction. - : Elsevier. - 2212-4209. ; 67
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Tidskriftsartikel (refereegranskat)abstract
- Cloudburst flash floods cause big casualties and economic losses. This study primarily investigated if a cloudburst catastrophe (cat) model could be constructed to meaningfully assess such a hazard, exposure and vulnerability in Swedish urban context. Rainfall intensity was used directly as hazard measure, bypassing hydraulic water-level modelling, to predict vulnerability. The Splash (Swedish pluvial modelling analysis and safety handling) cloudburst-disaster model was constructed using the Oasis Loss Modelling Framework, and was based on individual property values and building locations, property-level insurance-loss data, high-resolution geographical data, and rainfall data from a dense municipal gauge network in the city of Jönköping. One major cloudburst event was used to derive a vulnerability curve. The following two events were used for validation and supported the hypothesis that the vulnerability curve changed with time because of municipal flood-risk-reduction measures after the first event. A faulty rain gauge during the first event, replaced by a trustworthy private gauge, clarified the very high sensitivity to cloudburst input. Given the limited amount of loss data, our results were uncertain but they pointed towards possible ways to further this study with other loss data at other locations, possibly using more easily available aggregated loss data. We concluded that a cat model based only on rainfall intensity provided acceptable results, thus providing an opening for future, simplified cloudburst cat models applicable in most geographical contexts where reliable cloudburst data are available, especially in cities with limited topographic data and hydraulic-modelling capacity.
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| 3. |
- Reynolds, J. Eduardo, et al.
(författare)
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Flood prediction using parameters calibrated on limited discharge data and uncertain rainfall scenarios
- 2020
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Ingår i: Hydrological Sciences Journal. - : Taylor & Francis. - 0262-6667 .- 2150-3435. ; 65:9, s. 1512-1524
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Tidskriftsartikel (refereegranskat)abstract
- Discharge observations and reliable rainfall forecasts are essential for flood prediction but their availability and accuracy are often limited. However, even scarce data may still allow adequate flood forecasts to be made. Here, we explored how far using limited discharge calibration data and uncertain forcing data would affect the performance of a bucket-type hydrological model for simulating floods in a tropical basin. Three events above thresholds with a high and a low frequency of occurrence were used in calibration and 81 rainfall scenarios with different degrees of uncertainty were used as input to assess their effects on flood predictions. Relatively similar model performance was found when using calibrated parameters based on a few events above different thresholds. Flood predictions were sensitive to rainfall errors, but those related to volume had a larger impact. The results of this study indicate that a limited number of events can be useful for predicting floods given uncertain rainfall forecasts.
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