Suchergebnisse

Abstract. To limit the losses due to floods, public authorities can try to foster the adoption of private measures aimed at reducing the vulnerability of dwellings. However, the efficacy and cost-efficiency of such measures to reduce material losses are not well-known. In particular, the influence of building and flood characteristics on these variables has not been thoroughly studied. A better understanding of this topic would help identify the measures that are relevant to implement in specific contexts. To address this gap, we examined the effect of building and flood characteristics on the cost, efficacy, and cost-efficiency of three groups of measures taken for existing dwellings: one consists of elevating the dwelling, one of dry proofing it, and one of using construction materials that are resistant to water or cheap to repair or replace. We combined expert judgement and computer modelling to assess their cost, efficacy, and cost-efficiency for a wide range of flood depths and durations, building characteristics, and levels of exposure. We found that the value of the building components has a positive effect on the efficacy of dry proofing and elevating a dwelling. Both the efficacy and cost of these two groups of measures increase with the size of the dwelling. Moreover, according to our results, dry proofing and elevating a dwelling are unlikely to be cost-efficient for dwellings that are not exposed to floods with a return period lower than 100 and 30 years, respectively. Our findings also highlight that it is often less expensive to use the adapted than the original materials when rebuilding a damaged dwelling. Moreover, adapting the materials of an intact dwelling is unlikely to be cost-efficient for dwellings that are not exposed to floods with a return period lower than 20 years. Our results apply to France because the damage and the installation costs of the measures are specific to France and the geometry of the dwellings considered to perform our analyses is based on French dwellings.

Floods can be managed at the collective and individual level. Knowing the interaction between measures taken at both scales can help design more efficient flood risk management policies. Here, we combine the data collected during a survey of 331 inhabitants of flood-prone areas in the South of France and spatial databases to empirically examine the interaction between individual adaptation measures and three types of collective management tools: a national insurance scheme, dikes, and zoning instruments. In line with the levee effect hypothesis, we found that dike protection reduces the probability to have or take individual adaptation measures and that this effect could be mitigated by zoning instruments. Moreover, we found that the national insurance scheme does not crowd out individual adaptation.

Floods can be managed at the collective and individual level. Knowing the interaction between measures taken at both scales can help design more efficient flood risk management policies. Here, we combine the data collected during a survey of 331 inhabitants of flood-prone areas in the South of France and spatial databases to empirically examine the interaction between individual adaptation measures and three types of collective management tools: a national insurance scheme, dikes, and zoning instruments. In line with the levee effect hypothesis, we found that dike protection reduces the probability to have or take individual adaptation measures and that this effect could be mitigated by zoning instruments. Moreover, we found that the national insurance scheme does not crowd out individual adaptation.

Floods can be managed at the collective and individual level. Knowing the interaction between measures taken at both scales can help design more efficient flood risk management policies. Here, we combine the data collected during a survey of 331 inhabitants of flood-prone areas in the South of France and spatial databases to empirically examine the interaction between individual adaptation measures and three types of collective management tools: a national insurance scheme, dikes, and zoning instruments. In line with the levee effect hypothesis, we found that dike protection reduces the probability to have or take individual adaptation measures and that this effect could be mitigated by zoning instruments. Moreover, we found that the national insurance scheme does not crowd out individual adaptation.

Floods can be managed at the collective and individual level. Knowing the interaction between measures taken at both scales can help design more efficient flood risk management policies. Here, we combine the data collected during a survey of 331 inhabitants of flood-prone areas in the South of France and spatial databases to empirically examine the interaction between individual adaptation measures and three types of collective management tools: a national insurance scheme, dikes, and zoning instruments. In line with the levee effect hypothesis, we found that dike protection reduces the probability to have or take individual adaptation measures and that this effect could be mitigated by zoning instruments. Moreover, we found that the national insurance scheme does not crowd out individual adaptation.

Abstract. Flood damage assessment is crucial for evaluating flood management policies. In particular, properly assessing damage to agricultural assets is important because they are complex economic systems particularly exposed to floods. The modelling approaches used to assess flood damage are of several types and can be fed by damage data collected post-flood, from experiments or based on expert knowledge. The process-based models fed by expert knowledge are the subject of research and also widely used in an operational way. Although identified as potentially transferable, they are in reality often case-specific and difficult to reuse in time (updatability) and space (transferability). In this paper, we argue that process-based models, based on a rigorous modelling process, can be suitable for application in different contexts. We propose a methodological framework aimed at verifying the conditions necessary to develop these models in a spirit of capitalisation by relying on four axes which are (i) the explicitation of assumptions, (ii) the validation, (iii) the updatability, (iv) the transferability. The methodological framework is then applied to the model we have developed in France to produce national damage functions for the agricultural sector. We show in this paper that the proposed methodological framework facilitates an explicit description of the modelling assumptions and data used, which is necessary to consider for a reuse in time or for transfer to another geographical area. In this sense, this methodological framework constitutes a solid basis for considering the validation, transfer, comparison and capitalisation of data collected around models based on processes relying on expert knowledge. In conclusion, we identify research tracks to be implemented so as to pursue this improvement in a spirit of capitalisation and international cooperation.

Abstract. Effective flood risk management requires a realistic estimation of flood losses. However, available flood damage estimates are still characterized
by significant levels of uncertainty, questioning the capacity of flood damage models to depict real damages. With a joint effort of eight
international research groups, the objective of this study was to compare, in a blind-validation test, the performances of different models for the
assessment of the direct flood damage to the residential sector at the building level (i.e. microscale). The test consisted of a common flood case
study characterized by high availability of hazard and building data but with undisclosed information on observed losses in the implementation
stage of the models. The nine selected models were chosen in order to guarantee a good mastery of the models by the research teams, variety of the
modelling approaches, and heterogeneity of the original calibration context in relation to both hazard and vulnerability features. By avoiding
possible biases in model implementation, this blind comparison provided more objective insights on the transferability of the models and on the
reliability of their estimations, especially regarding the potentials of local and multivariable models. From another perspective, the exercise
allowed us to increase awareness of strengths and limits of flood damage modelling, which are summarized in the paper in the form of take-home messages
from a modeller's perspective.