scholarly journals Implementing tools to meet the Floods Directive requirements: a “procedure” to collect, store and manage damage data in the aftermath of flood events

2014 ◽  
Author(s):  
D. Molinari ◽  
M. Mazuran ◽  
C. Arias ◽  
G. Minucci ◽  
F. Atun ◽  
...  
Keyword(s):  
Flood Events ◽  
Damage Data ◽  
Floods Directive

Estimation of flood loss functions by activity sectors in the Pamplona metropolitan area in Spain by using insurance flood direct damage data

2020 ◽  
Author(s):  
Luis Mediero ◽  
Enrique Soriano ◽  
David Santillán ◽  
Luis Cueto-Felgueroso ◽  
Luis Garrote
Keyword(s):  
Metropolitan Area ◽  
Hydrodynamic Model ◽  
Loss Functions ◽  
Regional Government ◽  
Flow Depth ◽  
Flood Events ◽  
The Real ◽  
Direct Damage ◽  
Damage Data ◽  
Water Depths

<p>Flood risk assessment studies require information about direct damages that depend on several variables, such as water depth, water velocity, flood duration, activity sector and type of building, among others. However, loss functions are usually simplified through flow depth-direct damage curves. Direct flood damages driven by a given flood event can be estimated directly from such loss functions by using either known or estimated water depths.</p><p>In his study, flow depth-direct damage curves are estimated for a set of activity sectors in the Pamplona metropolitan area located in the northern part of Spain, within the activities of the EIT Climate-KIC SAFERPLACES project. A dataset containing all flood direct damages in the Pamplona metropolitan area in the period 1996-2018 were supplied by the Spanish ‘Consorcio de Compensación de Seguros’ (CSC), benefiting from the fact that CSC is the insurance company that covers all damages produced by natural hazards in Spain. Flood direct damages are classified by activity sectors and postal codes. In addition, observed streamflow data at a set of gauging sites in the Ulzama and Arga rivers were supplied by both the Ebro River Basin Authority and the Regional Government of Navarre. A set of seven flood events with both streamflow and direct damage data available were selected. Flood hydrographs in the Arga River at Pamplona were obtained with a temporal resolution of 15 minutes. The Regional Government of Navarre supplied the real flood extensions for a set of flood events. With such real flood extensions, the two-dimensional hydrodynamic IBER model was calibrated. Flood extensions and water depths with a spatial resolution of 1 m were estimated with the calibrated hydrodynamic model for the seven flood events. Combining the dataset of direct damages with standard flow depth-direct damage curves and with water depths simulated by the hydrodynamic model, flood depth-damage curves were estimated by municipalities and postal codes. Such curves were obtained for activity sectors, considering residential, commercial and industrial assets.</p><p><strong>Acknowledgments</strong></p><p>This study was supported by the project SAFERPLACES funded by the EIT Climate-KIC. The authors also acknowledge the ‘Consorcio de Compensación de Seguros’ for providing the flood direct damage dataset and the Regional Government of Navarre for providing the real flood extensions for given flood events.</p>

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

2018 ◽  
Author(s):  
Clotilde Saint-Martin ◽  
Pierre Javelle ◽  
Freddy Vinet
Keyword(s):  
New Media ◽  
Personal Information ◽  
Flood Damage ◽  
Online Media ◽  
Flood Events ◽  
Multiple Sources ◽  
Partial Data ◽  
Damage Data ◽  
Reproducible Method ◽  
The Impact

Abstract. The present paper introduces a new database for collection of flood-related damage and assessment at the local scale. 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. Even if partial data were available, data sharing within the research community is very limited and closely supervised to ensure the protection of individuals' personal information. In comparison, the growth of social and online media has provided access to broad information at the local and global scales. Therefore, the DamaGIS database offers an innovative bottom-up approach to gather and identify damage data from multiple sources, including new media. This paper also presents an easily reproducible method to assess the severity of flood damage. The DamaGIS database is available at doi:10.5281/zenodo.1186623.

scholarly journals Adaptability and transferability of flood loss functions in residential areas

2013 ◽  
Vol 13 (11) ◽  
pp. 3063-3081 ◽  
Author(s):  
H. Cammerer ◽  
A. H. Thieken ◽  
J. Lammel
Keyword(s):  
Flood Risk ◽  
Loss Functions ◽  
Flood Events ◽  
Residential Areas ◽  
Damage Functions ◽  
Residential Sector ◽  
Geographical Regions ◽  
Flood Loss ◽  
Loss Data ◽  
Damage Data

Abstract. Flood loss modeling is an important component within flood risk assessments. Traditionally, stage-damage functions are used for the estimation of direct monetary damage to buildings. Although it is known that such functions are governed by large uncertainties, they are commonly applied – even in different geographical regions – without further validation, mainly due to the lack of real damage data. Until now, little research has been done to investigate the applicability and transferability of such damage models to other regions. In this study, the last severe flood event in the Austrian Lech Valley in 2005 was simulated to test the performance of various damage functions from different geographical regions in Central Europe for the residential sector. In addition to common stage-damage curves, new functions were derived from empirical flood loss data collected in the aftermath of recent flood events in neighboring Germany. Furthermore, a multi-parameter flood loss model for the residential sector was adapted to the study area and also evaluated with official damage data. The analysis reveals that flood loss functions derived from related and more similar regions perform considerably better than those from more heterogeneous data sets of different regions and flood events. While former loss functions estimate the observed damage well, the latter overestimate the reported loss clearly. To illustrate the effect of model choice on the resulting uncertainty of damage estimates, the current flood risk for residential areas was calculated. In the case of extreme events like the 300 yr flood, for example, the range of losses to residential buildings between the highest and the lowest estimates amounts to a factor of 18, in contrast to properly validated models with a factor of 2.3. Even if the risk analysis is only performed for residential areas, our results reveal evidently that a carefree model transfer in other geographical regions might be critical. Therefore, we conclude that loss models should at least be selected or derived from related regions with similar flood and building characteristics, as far as no model validation is possible. To further increase the general reliability of flood loss assessment in the future, more loss data and more comprehensive loss data for model development and validation are needed.

scholarly journals The Value of Disaster Damage Data

Eos ◽  
2017 ◽  
Vol 98 ◽  
Author(s):  
Daniela Molinari ◽  
Scira Menoni ◽  
Francesco Ballio
Keyword(s):  
Flood Events ◽  
Damage Data ◽  
Systematic Collection

The editors of a new book describe the benefits of systematic collection, storage, analysis, and sharing of damage data after flood events.

Validation of methods for the assessment of physical vulnerability to dynamic flooding

2021 ◽  
Author(s):  
Maria Papathoma-Koehle ◽  
Lea Dosser ◽  
Florian Roesch ◽  
Matthias Schlögl ◽  
Marco Borga ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Natural Hazards ◽  
Vulnerability Index ◽  
Insurance Companies ◽  
Flood Events ◽  
Physical Vulnerability ◽  
Vulnerability Indicators ◽  
Damage Data ◽  
Using Data ◽  
Physical Vulnerability Index

<p>The importance of assessing the physical vulnerability of assets to natural hazards is indisputable. Recent extreme events have shown that the severity of natural hazards is strongly linked to the vulnerability of the population and the built environment. Physical vulnerability, in particular, is directly connected to monetary damages and interruptions that are in the centre of the interests of several stakeholders including governments, authorities, insurance companies, engineers, and homeowners. A plethora of different approaches is available in the literature, nevertheless, two categories of approaches are the most prominent: vulnerability curves and vulnerability indicators. In this study, both are put to the test by using data from two relatively recent dynamic flood events. In more detail, a physical vulnerability index (PVI) and a Beta model based on damage data from Italy and Austria are validated using recent damage data from an event in Dimaro Folgarida (Trento, Italy) in 2018 and an event in Schallerbach (Tirol, Austria) in 2015. The study does not just validate the methods but also investigates remaining uncertainties related to the assessment of the process intensity on buildings and the calculation of the building value by conducting a sensitivity analysis. </p>

An analysis of Italian damage data to economic activities

2021 ◽  
Author(s):  
Marta Galliani ◽  
Francesca Carisi ◽  
Alessio Domeneghetti ◽  
Giovanni Menduni ◽  
Daniela Molinari ◽  
...  
Keyword(s):  
Critical Role ◽  
Flood Damage ◽  
Flood Events ◽  
Economic Activities ◽  
Commercial Activities ◽  
Flood Impacts ◽  
Damage Modelling ◽  
Damage Data ◽  
Observed Damage

<p>The study of flood impacts on the different sectors that compose the built environment and the society is crucial to implement actions of prevention, mitigation, and cautious planning. In such a context, the sector of businesses assumes a critical role, both for its importance for the wellbeing of the society and because of the high losses it suffers in case of inundations. Nevertheless, flood damage modelling to businesses is still a challenging task: the large number of different commercial activities, their specific geographical and economic contexts and the few observed damage data are just some of the reasons for that. In Italy, for example, a shared methodology to assess damage to enterprises is not present; building knowledge about types and dimensions of impacts of flood events to economic activities is then even more impelling. This contribution presents the analysis of about a thousand observed damage records regarding industrial and commercial activities, collected by four research groups after different flood events in Italy: the inundation occurred in the town of Lodi (Lombardia Region) in 2002, the one in Sardegna Region in 2013, and the floods caused in the Emilia-Romagna Region by Secchia (2014) and Enza (2017) Rivers. Data retrieved from the local and regional authorities responsible for damage compensation present different levels of detail and aggregation, according to the case study investigated. In all cases, they refer to the direct damage only and, for each case study, they have been first organised according to the activity types (e.g. trade, manufacturing, construction, finance) and per affected components: i.e. structure, equipment and stock. Data analysis has been led by some questions, we identified as key to start developing knowledge for damage modelling:  are there similarities in the different case studies? Which are the more affected business sectors in case of flood? Which component suffers the highest damage among structure, equipment, and stock? Is there an empirical trend of damage with hazard parameters? Results were first compared with the socio-economic context of the affected area, to have a first confirmation of data quality and reliability; then, the analysis focused on searching information and relationships between damage and activity type, activity dimension and water level. Results support the identification of the more vulnerable elements within the business sector, orienting modellers’ and decision-makers’ choices.</p>

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

2018 ◽  
Vol 10 (2) ◽  
pp. 1019-1029 ◽  
Author(s):  
Clotilde Saint-Martin ◽  
Pierre Javelle ◽  
Freddy Vinet
Keyword(s):  
New Media ◽  
Flood Damage ◽  
Flood Events ◽  
Multiple Sources ◽  
The Past ◽  
Damage Data ◽  
Reproducible Method ◽  
Operating Instructions ◽  
The Impact ◽  
Assess Data Quality

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.

Types of large flood events (1985-2016)

2017 ◽  
Author(s):  
Chloé Meyer
Keyword(s):  
Original Data ◽  
Flood Events

The information presented highlights large flood events from 1985 to 2016 identified by the Dartmouth Flood Observatory. For more information, visit: floodobservatory.colorado.edu/Archives/index.html For mapping purposes, some types of flood events have been merged into one, under the "MAINCAUSEF" attribute. Please refer to the "MAINCAUSE" attribute for original data. Flood

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