Evolutionary leap in large-scale flood risk assessment needed

Current approaches for assessing large-scale flood risks contravene the fundamental principles of the flood risk system functioning because they largely ignore basic interactions and feedbacks between atmosphere, catchments, river-floodplain systems and socio-economic processes. As a consequence, risk analyses are uncertain and might be biased. However, reliable risk estimates are required for prioritizing national investments in flood risk mitigation or for appraisal and management of insurance portfolios. We review several examples of process interactions and highlight their importance in shaping spatio-temporal risk patterns. We call for a fundamental redesign of the approaches used for large-scale flood risk assessment. They need to be capable to form a basis for large-scale flood risk management and insurance policies worldwide facing the challenge of increasing risks due to climate and global change. In particular, implementation of the European Flood Directive needs to be adjusted for the next round of flood risk mapping and development of flood risk management plans focussing on methods accounting for more process interactions in flood risk systems

Are flood damage models converging to “reality”? Lessons learnt from a blind test

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

A comparative analysis of flood damage models: lessons learnt and future challenges

The estimation of flood losses implies the use of vulnerability/exposure models for flood damage and risk assessment (Meyer et al. 2013; Zischg et al. 2018; Wagenaar et al. 2018; Molinari et al. 2019). According to Gerl et al. (2016), in central Europe there are 28 models with 652 functions to assess flood losses, whereas almost half of the functions refer to residential buildings. The main differences among damage models are: (i) spatial scale, (ii) metric (i.e. absolute or relative loss), (iii) exposure assessment (i.e. whole building or affected floors, market values or reconstruction-replacement costs), (iv) number of input variables, (v) calibration/validation with observed losses. These differences pose the issue of model transferability to other urban or environmental contexts. With a joint effort of eight research groups, the objective of this study is to test and compare damage models for residential buildings used or developed by each group, by applying them in a “blind exercise”, i.e. a common flood case study characterised by high availability of hazard and building data, with unknown information on observed losses in the implementation stage of the models. As the research groups use approaches representing many different types and characteristics of models (e.g. univariable – multivariable; absolute – relative; graduated – regression – machine learning), being calibrated based on empirical data stemming from different countries (Austria, France, Germany, Italy, Japan, Netherlands), with different landscapes, the blind exercise provides an extensive comparison of models and their transferability. The analysis of the differences in the ensemble of model outcomes aims at pointing out common patterns or divergent behaviours between model outcomes and with respect to observed losses

TYK2 is a key regulator of the surveillance of B lymphoid tumors

Aberrant activation of the JAK-STAT pathway has been implicated in tumor formation; for example, constitutive activation of JAK2 kinase or the enforced expression of STAT5 induces leukemia in mice. We show here that the Janus kinase TYK2 serves an opposite function. Mice deficient in TYK2 developed Abelson-induced B lymphoid leukemia/lymphoma as well as TEL-JAK2–induced T lymphoid leukemia with a higher incidence and shortened latency compared with WT controls. The cell-autonomous properties of Abelson murine leukemia virus–transformed (A-MuLV–transformed) TYK2(–/–) cells were unaltered, but the high susceptibility of TYK2(–/–) mice resulted from an impaired tumor surveillance, and accordingly, TYK2(–/–) A-MuLV–induced lymphomas were easily rejected after transplantation into WT hosts. The increased rate of leukemia/lymphoma formation was linked to a decreased in vitro cytotoxic capacity of TYK2(–/–) NK and NKT cells toward tumor-derived cells. RAG2/TYK2 double-knockout mice succumbed to A-MuLV–induced leukemia/lymphoma faster than RAG2(–/–)TYK2(+/–) mice. This defines NK cells as key players in tumor surveillance in Abelson-induced malignancies. Our observations provide compelling evidence that TYK2 is an important regulator of lymphoid tumor surveillance

A comparative analysis of flood damage models: lessons learnt and future challenges

Flood damage assessment is crucial to address the challenges of climate and socio-economic changes. Researchers and practitioners have developed several damage models to tackle local and regional situations. Particularly for direct damages to the residential sector, these models rely on numerous hypothesis (e.g. zero damage threshold) and parameters (e.g. recovery costs) assumed to fit specific local conditions and available data. Thus, transferability of damage models and reliability of observed losses have become key topics in the debate.This work aims at understanding the behaviour of different residential building damage models through their application to a case study in order to compare assumptions, estimated exposure values and losses. The research work is designed as a “blind” exercise where different research groups make a damage assessment starting from the same building dataset. Nine models are applied to estimate exposure and damage at the single-building scale. The results are compared in terms of exposure values, total damage and individual building damage. Although damage models differ in assumptions and parameters, the application highlights a good correlation among models in terms of exposure and relative damage, while correlation with monetary damage recorded in claims is low

Evolutionary leap in large-scale flood risk assessment needed

Current approaches for assessing large-scale flood risks contravene the fundamental principles of the flood risk system functioning because they largely ignore basic interactions and feedbacks between atmosphere, catchments, river-floodplain systems, and socioeconomic processes. As a consequence, risk analyses are uncertain and might be biased. However, reliable risk estimates are required for prioritizing national investments in flood risk mitigation or for appraisal and management of insurance portfolios. We review several examples of process interactions and highlight their importance in shaping spatiotemporal risk patterns. We call for a fundamental redesign of the approaches used for large-scale flood risk assessment. They need to be capable to form a basis for large-scale flood risk management and insurance policies worldwide facing the challenge of increasing risks due to climate and global change. In particular, implementation of the European Flood Directive needs to be adjusted for the next round of flood risk mapping and development of flood risk management plans focusing on methods accounting for more process interactions in flood risk systems

Are flood damage models converging to “reality”? Lessons learnt from a blind test

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. </jats:p