Believe it or not? The challenge of validating large scale probabilistic risk models

Sayers, Paul; Lamb, Robert A.; Panzeri, M.; Bowman, Hayley; Horritt, M. S.; Penning‐Rowsell, Edmund C.

doi:10.1051/e3sconf/20160711004

Cited by 9 publications

(19 citation statements)

References 22 publications

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“…In recent years, advances have been also made in how to approach the comparison of probabilistic outputs from defence 5 performance analysis, focusing on probabilistic risk models (Sayers et al, 2016).…”

Section: Defence Failure Modelsmentioning

confidence: 99%

“…As explained by Sayers et al (2016) a top-down or a bottom-up approach can be used. The top-down approach is often the first obvious step.…”

Section: Integration Of Risk Componentsmentioning

confidence: 99%

“…With his paper he provoked not only discussion but also further investigation into the usability of outcomes, uncertainties and validation questions. Next, Sayers et al (2016) explained the aim and usability of the risk outcomes in the UK. He made 20 clear that risk outcomes on national scale can be confident even if local values of national scale analyses are wrong as it is expected that local errors counteract each other in such a way that the national estimate is sufficiently reliable.…”

Section: Integration Of Risk Componentsmentioning

confidence: 99%

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Review Article: Validation of flood risk models: current practice and innovations

Molinari

Bruijn

Castillo

et al. 2017

Preprint

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Abstract.Although often neglected, model validation is a key topic in flood risk analysis, as flood risk estimates are characterised by significant levels of uncertainty. In this paper, we discuss the state of art of flood risk models validation, as concluded from the discussion among more than 50 experts at two main scientific events. The events aimed at identifying policy and research recommendations towards promoting more common practice of validation, and an improvement of flood 15 risk models reliability. We pay specific attention to the different components of the risk modelling chain (i.e. flood hazard, defence failure and flood damage analysis) as well as to their role into risk estimates, to highlight specificities and commonalities with respect to implemented techniques and research needs. The main conclusions from this review can be summarised as the need of higher quality data to perform validation and of benchmark solutions to be followed in different contexts, along with a greater involvement of end-users in the debate on flood risk models validation. 20

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Section: Defence Failure Modelsmentioning

confidence: 99%

“…As explained by Sayers et al (2016) a top-down or a bottom-up approach can be used. The top-down approach is often the first obvious step.…”

Section: Integration Of Risk Componentsmentioning

confidence: 99%

Section: Integration Of Risk Componentsmentioning

confidence: 99%

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Review Article: Validation of flood risk models: current practice and innovations

Molinari

Bruijn

Castillo

et al. 2017

Preprint

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“…A state-of-the-art review of study-related approaches, analysis techniques, results, uncertainties and validation processes of the results associated with each of these four work scales is collected in Reference [5]. Regarding this last point, the validation and calibration of the results involved fundamental elements that will require further study in the future (regardless of the work scale in the analysis), since they condition the usefulness of these studies for end users [6].…”

Section: Introductionmentioning

confidence: 99%

On the Influence of the Main Floor Layout of Buildings in Economic Flood Risk Assessment: Results from Central Spain

Garrote

Bernal

2020

Water

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Multiple studies have been carried out on the correct estimation of the damages (direct tangible losses) associated with floods. However, the complex analysis and the multitude of variables conditioning the damage estimation, as well as the uncertainty in their estimation, make it difficult, even today, to reach one single, complete solution to this problem. In no case has the influence that the topographic relationship between the main floor of a residential building and the surrounding land have in the estimation of flood economic damage been analysed. To carry out this analysis, up to a total of 28 magnitude–damage functions (with different characteristics and application scales) were selected on which the effect of over-elevation and under-elevation of the main floor of the houses was simulated (at intervals of 20 cm, between −0.6 and +1 metre). According to each of the two trends, an overestimation or underestimation of flood damage was observed. This pattern was conditioned by the specific characteristics of each magnitude–damage function, meaning that the percentage of damage became asymptotic from a certain flow depth value. In a real scenario, the consideration of this variable (as opposed to its non-consideration) causes an average variation in the damage estimation around 30%. Based on these results, the analysed variable can be considered as (1) another main source of uncertainty in the correct estimation of flood damage, and (2) an essential variable to take into account in a flood damage analysis for the correct estimation of loss.

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“…Approaches, analysis techniques, results, uncertainties, and processes used for validation of the results associated with each of these four working scales are included in de Moel et al [2]. The processes used to validate results are key points that will require a greater effort in the future (regardless of the scale of work of the analysis), since they also determine the utility for end users [3]. Thus, de Moel et al [2] raise the need to focus efforts on obtaining post-disaster information (with as much detail as possible) as a fundamental tool to improve the calibration, the validation, and the representativeness of flood risk models.When the study area is large (macro-scale analysis and above), one of the main problems we face in validation and calibration of the results is the lack of post-event information uniformly distributed throughout the territory.…”

mentioning

confidence: 99%

Can the Quality of the Potential Flood Risk Maps be Evaluated? A Case Study of the Social Risks of Floods in Central Spain

Garrote

Gutiérrez-Pérez

Díez‐Herrero

2019

Water

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Calibration and validation of flood risk maps at a national or a supra-national level remains a problematic aspect due to the limited information available to carry out these tasks. However, this validation is essential to define the representativeness of the results and for end users to gain confidence in them. In recent years, the use of information derived from social networks is becoming generalized in the field of natural risks as a means of validating results. However, the use of data from social networks also has its drawbacks, such as the biases associated with age and gender and their spatial distribution. The use of information associated with phone calls to Emergency Services (112) can resolve these deficiencies, although other problems are still latent. For example, a bias does exist in the relationship between the size of the population and the number of calls to the Emergency Services. This last aspect determines that global regression models have not been effective in simulating the behavior of related variables (calls to Emergency Services-Potential Flood Risk). Faced with this situation, the use of local regression models (such as locally estimated scatterplot smoothing (LOESS)) showed satisfactory results in the calibration of potential flood risk levels in the Autonomous Community of Castilla-La Mancha (Spain). This provides a new methodological path to the calibration studies of flood risk cartographies at national and supra-national levels. The results obtained through LOESS local regression models allowed us to establish the correct relationship between categorized potential risk levels and the inferred potential risk. They also permitted us to define the cases in which said levels differed ostensibly and where potential risk due to floods assigned to those municipalities led to a lower level of confidence. Therefore, based on the number of calls to the Emergency Service, we can categorize those municipalities that should be the subject of a more detailed study and those whose classification should be revised in future updates. territory conditions the flood risk analysis approach [2]; each scale of work requires the use of different methods of analysis, and the results must satisfy different uses. Depending on the spatial extent of the analysis, de Moel et al. [2] propose four scales (supra-national, macro-scale or national, meso-scale or regional, and micro-scale or local). This does not mean they are isolated, because some of the analysis methodologies are valid for different scales (in many cases by using grouping techniques or by simplifying calculation processes). Approaches, analysis techniques, results, uncertainties, and processes used for validation of the results associated with each of these four working scales are included in de Moel et al. [2]. The processes used to validate results are key points that will require a greater effort in the future (regardless of the scale of work of the analysis), since they also determine the utility for end users [3]. Thus, de Moel et al. [2] r...

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Believe it or not? The challenge of validating large scale probabilistic risk models

Cited by 9 publications

References 22 publications

Review Article: Validation of flood risk models: current practice and innovations

Review Article: Validation of flood risk models: current practice and innovations

On the Influence of the Main Floor Layout of Buildings in Economic Flood Risk Assessment: Results from Central Spain

Can the Quality of the Potential Flood Risk Maps be Evaluated? A Case Study of the Social Risks of Floods in Central Spain

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