Abstract. Over the last 25 years, flash floods in the South of France have killed almost 250 people. The protection of prone populations is a priority for the French government. It is also a goal of the 2007 European flood directive. However, no accurate database exists gathering the fatalities due to floods in France. Fatalities are supposed to be rare and hazardous, mainly due to individual behaviour. A Ph. D. work has initiated the building of a database gathering a detailed analysis of the circumstances of death and the profiles of the deceased DJH JHQGHU« 7KH VWXG\ DUHD FRYHUV the French Mediterranean departments prone to flash floods over the period 1988-2015. This presentation details the main features of the sample, 244 fatalities collected through newspapers completed with field surveys near police services and municipalities. The sample is broken down between huge events that account for two thirds of the IDWDOLWLHV DQG ³VPDOO´ HYHQWV 4 % of the fatalities). Deaths at home account for 35 % of the total number of fatalities, mainly during huge events. 30 % of fatalities are related to vehicles. The last part of the work explains the relations between fatalities and prevention and how better knowledge of flood-related deaths can help to improve flood prevention. The given example shows the relationship between flood forecasting and fatalities. Half of the deaths took place in a small watershed (< 150 km 2 ). It emphasizes the need for the dissemination of a complementary system of flash flood forecast based on forecasted rainfall depth and adapted to small watersheds.
Abstract. Occurring at small temporal and spatial scales, flash floods (FF) can cause severe economic damages and human losses. To better anticipate such events and mitigate their impacts, the French Ministry in charge of Ecology has decided to set up a national FF warning system over the French territory. This automated system will be run by the SCHAPI, the French national service in charge of flood forecasting, providing warnings for fast-responding ungauged catchments (area ranging from ~10 tR a NPð ,W ZLOO WKHUHIRUH EH FRPSOHPHQWDU\ WR WKH 6&+$3, ¶V QDWLRQDO ³YLJLODQFH´ V\VWHP ZKLFK FRQFHUQV RQO\ JDXJHG FDWFKPHQWV 7KH )) ZDUQLQJ V\VWHP WR EH LPSOHPHQWHG in 2017 will be based on a discharge-threshold flood warning method called AIGA (Javelle et al. 2014). This method has been experimented in real time in the south of France in the RHYTMME project (http://rhytmme.irstea.fr). It consists in comparing discharges generated by a simple conceptual hourly hydrologic model run at a 1-km² resolution to reference flood quantiles of different (e.g., 2-, 10-and 50-year) return periods. Therefore the system characterizes in real time the severity of ongoing events by the range of the return period estimated by AIGA at any point along the river network. The hydrologic model ingests operational rainfall radar-gauge products from Météo-France and takes into account the baseflow and the initial soil humidity conditions to better estimate the basin response to rainfall inputs. To meet the requirements of the future FF warning system, the AIGA method has been extended to the whole French territory (except Corsica and overseas French territories). The calibration, regionalization and validation procedures of the hydrologic model were carried out using data for ~700 hydrometric stations from the 2002-2015 period. Performance of the warning system was evaluated with various contingency criteria (e.g., probability of detection and success rate). Furthermore, specific flood events were analysed in more details, by comparing warnings issued for exceeding different critical flood quantiles and their associated timing with field observations. The performance results show that the proposed FF warning system is useful, especially for ungauged sites. The analysis also points out the need to account for the uncertainties in the precipitation inputs and the hydrological modelling, as well as include precipitation forecasts to improve the effective warning lead time.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.