The Severe Hazards Analysis and Verification Experiment

Ortega, Kiel L.; Smith, Travis; Manross, Kevin L.; Scharfenberg, Kevin A.; Witt, Arthur; Kolodziej, Angelyn G.; Gourley, Jonathan J.

doi:10.1175/2009bams2815.1

Cited by 111 publications

(66 citation statements)

References 5 publications

(3 reference statements)

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“…Although data of this sort are generally confidential, they may be accessible through partnerships with insurance companies. Other sources of information on flash flood impacts could also be used, such as the logs of emergency services, emergency calls, information shared on social networks (USDHS, 2012;Jongman et al, 2015;Tkachenko et al, 2017), or information gathered in the field after or during the event (Ortega et al, 2009;Ruin et al, 2014). This information is also affected by uncertainties and severe biases, especially in flash flood situations: absence of information due to local breakdowns of communication networks, reduction of social network activity, and partial filling of emergency logs in strongly affected areas during the turmoil of the event.…”

Section: Discussionmentioning

confidence: 99%

The challenge of forecasting impacts of flash floods: test of a simplified hydraulic approach and validation based on insurance claim data

Bihan¹,

Payrastre²,

Gaumé³

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. Up to now, flash flood monitoring and forecasting systems, based on rainfall radar measurements and distributed rainfall-runoff models, generally aimed at estimating flood magnitudes -typically discharges or return periods -at selected river cross sections. The approach presented here goes one step further by proposing an integrated forecasting chain for the direct assessment of flash flood possible impacts on inhabited areas (number of buildings at risk in the presented case studies). The proposed approach includes, in addition to a distributed rainfall-runoff model, an automatic hydraulic method suited for the computation of flood extent maps on a dense river network and over large territories. The resulting catalogue of flood extent maps is then combined with land use data to build a flood impact curve for each considered river reach, i.e. the number of inundated buildings versus discharge. These curves are finally used to compute estimated impacts based on forecasted discharges. The approach has been extensively tested in the regions of Alès and Draguignan, located in the south of France, where welldocumented major flash floods recently occurred. The article presents two types of validation results. First, the automatically computed flood extent maps and corresponding water levels are tested against rating curves at available river gauging stations as well as against local reference or observed flood extent maps. Second, a rich and comprehensive insurance claim database is used to evaluate the relevance of the estimated impacts for some recent major floods.

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Section: Discussionmentioning

confidence: 99%

The challenge of forecasting impacts of flash floods: test of a simplified hydraulic approach and validation based on insurance claim data

Bihan¹,

Payrastre²,

Gaumé³

et al. 2017

Hydrol. Earth Syst. Sci.

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show abstract

“…MESH was defined as the hail diameter larger than 75% of the hail observed from a given storm. Ortega et al (2009) noted a wide range of measured hail sizes within a certain MESH value. Given these issues, MESH is used here as a proxy for likely hailfall size and location, rather than confirmation of the actual size of hail reaching the surface.…”

Section: ) Maximum Estimated Size Of Hailmentioning

confidence: 92%

Evaluation of approaches to identifying hail damage to crop vegetation using satellite imagery

Bell¹,

Molthan²

2016

J. Operational Meteor.

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“…Unlike NOAA's Storm Events Database, which is foremost interested in weather events independent of loss, SHELDUS focuses on loss data. Between 2008 and 2010, an experiment was also conducted by one of NOAA's laboratories to collect specific data on flash floods called the Severe Hazards Analysis and Verification Experiment (SHAVE; Gourley et al, 2013;Calianno et al, 2013;Ortega et al, 2009).…”

Section: Damage Data Collectionmentioning

confidence: 99%

DamaGIS: a multisource geodatabase for collection of flood-related damage data

Saint-Martin

Javelle

Vinet

2018

Earth Syst. Sci. Data

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Abstract. Every year in France, recurring flood events result in several million euros of damage, and reducing the heavy consequences of floods has become a high priority. However, actions to reduce the impact of floods are often hindered by the lack of damage data on past flood events. The present paper introduces a new database for collection and assessment of flood-related damage. The DamaGIS database offers an innovative bottom-up approach to gather and identify damage data from multiple sources, including new media. The study area has been defined as the south of France considering the high frequency of floods over the past years. This paper presents the structure and contents of the database. It also presents operating instructions in order to keep collecting damage data within the database. This paper also describes an easily reproducible method to assess the severity of flood damage regardless of the location or date of occurrence. A first analysis of the damage contents is also provided in order to assess data quality and the relevance of the database. According to this analysis, despite its lack of comprehensiveness, the DamaGIS database presents many advantages. Indeed, DamaGIS provides a high accuracy of data as well as simplicity of use. It also has the additional benefit of being accessible in multiple formats and is open access. The DamaGIS database is available at https://doi.org/10.5281/zenodo.1241089.

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The Severe Hazards Analysis and Verification Experiment

Cited by 111 publications

References 5 publications

The challenge of forecasting impacts of flash floods: test of a simplified hydraulic approach and validation based on insurance claim data

The challenge of forecasting impacts of flash floods: test of a simplified hydraulic approach and validation based on insurance claim data

Evaluation of approaches to identifying hail damage to crop vegetation using satellite imagery

DamaGIS: a multisource geodatabase for collection of flood-related damage data

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