Suchergebnisse

"Several scholars across the globe identified the present lack of high quality damage data as the main constraint to efficient risk mitigation. The need for a systematic collection of damage data in the aftermath of flood events come into light, thus the aim being the creation of complete and reliable databases. Flood damage data collected in the aftermath of a disastrous event can support a variety of actions, which include: (i) the identification of priorities for intervention during emergencies, (ii) the creation of complete event scenarios on the basis of which understanding the fragilities of the flooded areas and tailoring risk mitigation strategies, (iii) the definition of victims compensation schemes, and (iv) the validation/definition of damage models to feed cost-benefit analysis of structural and non-structural mitigation actions (including insurance schemes). Volume highlights include: A good compilation of real world case studies elaborating on the survey experiences and best practices associated with flood damage data collection, storage and analysis, that can help strategize flood risk mitigation in an efficient manner; Valuable contributions covering different flooding phenomena such as riverine and mountain floods, different spatial level of analysis from local to global scales, and different stakeholders perspectives, e.g. public decision makers, researchers, private companies; and contributions from leading experts in the field, researchers and practitioners, including civil protection actors working at different spatial and administrative level, insurers and professionals working in the field of natural hazards mitigation. Flood Damage Survey and Assessment: New Insights from Research and Practice will be a valuable resource to all earth scientists, hydrologists, meteorologists, geologists, geographers, civil engineers, insurers and policy decision makers"--Publisher's website, November 8, 2017

"Several scholars across the globe identified the present lack of high quality damage data as the main constraint to efficient risk mitigation. The need for a systematic collection of damage data in the aftermath of flood events come into light, thus the aim being the creation of complete and reliable databases. Flood damage data collected in the aftermath of a disastrous event can support a variety of actions, which include: (i) the identification of priorities for intervention during emergencies, (ii) the creation of complete event scenarios on the basis of which understanding the fragilities of the flooded areas and tailoring risk mitigation strategies, (iii) the definition of victims compensation schemes, and (iv) the validation/definition of damage models to feed cost-benefit analysis of structural and non-structural mitigation actions (including insurance schemes). Volume highlights include: A good compilation of real world case studies elaborating on the survey experiences and best practices associated with flood damage data collection, storage and analysis, that can help strategize flood risk mitigation in an efficient manner; Valuable contributions covering different flooding phenomena such as riverine and mountain floods, different spatial level of analysis from local to global scales, and different stakeholders perspectives, e.g. public decision makers, researchers, private companies; and contributions from leading experts in the field, researchers and practitioners, including civil protection actors working at different spatial and administrative level, insurers and professionals working in the field of natural hazards mitigation. Flood Damage Survey and Assessment: New Insights from Research and Practice will be a valuable resource to all earth scientists, hydrologists, meteorologists, geologists, geographers, civil engineers, insurers and policy decision makers"--Publisher's website, November 8, 2017.

Abstract. INSYDE is a multivariable, synthetic model for flood damage assessment to
dwellings. The analysis and use of this model highlighted some weaknesses,
linked to its complexity, that can undermine its usability and correct
implementation. This study proposes a simplified version of INSYDE which
maintains its multivariable and synthetic nature but has simpler
mathematical formulations permitting easier use and a direct analysis of
the relation between damage and its explanatory variables.

Abstract. This paper presents AGRIDE-c, a conceptual model for the
assessment of flood damage to crops, in favour of more comprehensive flood
damage assessments. Available knowledge on damage mechanisms triggered by
inundation phenomena is systematised in a usable and consistent tool, with
the main strength represented by the integration of physical damage
assessment into the evaluation of its economic consequences on the income of
the farmers. This allows AGRIDE-c to be used to guide the flood damage
assessment process in different geographical and economic contexts, as
demonstrated by the example provided in this study for the Po Plain (north
of Italy). The development and implementation of the model highlighted that
a thorough understanding and modelling of mechanisms causing damage to crops is a
powerful tool to support more effective damage mitigation strategies, both
at public and at private (i.e. farmers) levels.

Abstract. Effective flood risk mitigation requires the impacts of flood events to be much better and more reliably known than is currently the case. Available post-flood damage assessments usually supply only a partial vision of the consequences of the floods as they typically respond to the specific needs of a particular stakeholder. Consequently, they generally focus (i) on particular items at risk, (ii) on a certain time window after the occurrence of the flood, (iii) on a specific scale of analysis or (iv) on the analysis of damage only, without an investigation of damage mechanisms and root causes. This paper responds to the necessity of a more integrated interpretation of flood events as the base to address the variety of needs arising after a disaster. In particular, a model is supplied to develop multipurpose complete event scenarios. The model organizes available information after the event according to five logical axes. This way post-flood damage assessments can be developed that (i) are multisectoral, (ii) consider physical as well as functional and systemic damage, (iii) address the spatial scales that are relevant for the event at stake depending on the type of damage that has to be analyzed, i.e., direct, functional and systemic, (iv) consider the temporal evolution of damage and finally (v) allow damage mechanisms and root causes to be understood. All the above features are key for the multi-usability of resulting flood scenarios. The model allows, on the one hand, the rationalization of efforts currently implemented in ex post damage assessments, also with the objective of better programming financial resources that will be needed for these types of events in the future. On the other hand, integrated interpretations of flood events are fundamental to adapting and optimizing flood mitigation strategies on the basis of thorough forensic investigation of each event, as corroborated by the implementation of the model in a case study.

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.