<p>Predmet ovog istraživanja su direktne materijalne posledice realizacije prirodnih nepogoda (direktna materijalna šteta) i procena štete na teritoriji AP Vojvodine. U prvom delu istraživanja analizirana je prostorna distribucija prirodnih nepogoda karakterističnih za područje AP Vojvodine sa ciljem utvrđivanja izloženosti populacije rizicima od prirodnih nepogoda. U drugom delu istraživanja, primenom kvantitativnih metoda koje uključuju parametarske i neparametarske statističke metode i regresiono modeliranje utvrđen je optimalni analitički izraz procene štete nastale usled realizacije rizika od oluje kao prirodne nepogode za koju je ustanovljena povećana izloženost populacije AP Vojvodine.</p> / <p>The subject of this research is the direct material consequences of the realization of natural disasters (direct material damage) and the assessment of damage in the territory of Vojvodina. In the first part of the research, the spatial distribution of natural disasters characteristic for the region of Vojvodina was analyzed in order to determine the population&#39;s exposure to natural hazards. In the second part of the research, the optimal analytical expression of damage estimation was determined by applying quantitative methods including parametric and non-parametric statistical methods and regression modeling. The optimal analytical expression of damage estimation has been identified for the risk of a storm as a natural disaster which has created increased exposure of the population of Vojvodina.</p>

Thailand has been often affected by severe flood events over the past century. The 2011’s Thailand Flood Catastrophe was the costliest in country’s history, and it was ranked to be the second most damaging natural hazard in the world in terms of economic losses. The Chao Phraya River Basin was noted to be the most vulnerable area prone to flooding in Thailand. The dynamics of flood risk in the river basin have changed drastically over the past fifty years. In particular, flood exposure increased due to rapid urbanization and population growth. Since 2012, integrated flood risk management has been addressed to be the major framework of water-related disasters with the goal of losses and damage reductions. However, there is currently little research in Thailand on how to quantify flood risks and mitigate flood inundation damage on the relation between the occurrence of flood events and their consequential socio-economic implications. In this study, a tradition method in flood risk assessment is implemented by integrating 2D hydrodynamic modelling and the assessment of socio-economic impact of floods into the Chao Phraya River Basin. More specifically, the fully 2D version of the LISFLOOD-FP model code was used to model flood inundation processes. The output of the model was then used to map inundation depth and assess the levels of physical/environmental risk associated to flood hazards on multiple receptors/elements at risk. The European Flood Directive and the KULTURisk methodology were applied to quantify flood risks in monetary terms for residential, industrial, and agricultural sectors. The 2011 flood event was used for model calibration, while a hypothetical flood event with a return period of 100 years was simulated to identify the potential flood losses. Depth-damage functions comprising of JRC-ASIA, the Flemish, and JICA models were used to estimate potential damage for residential and industrial structures. The results showed that LISFLOOD-FP could satisfactorily reproduce the flood inundation extent obtained from satellite imagery in 2011. The model performance (Critical Success Index or F1) was of 56%, with a Bias of 112%. The latter meant the total inundated area was 12% larger than flood extent’s observation. Moreover, the model could simulate flood levels with overall Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) of 2.03 m a.s.l. and 1.78 m a.s.l., respectively. For the estimation of flood damage and losses, the Flemish model showed the strongest agreement with the reported flood damage in the residential sector, while JICA-ASIA model underestimated flood damage for industrial sector by just 1%. The KULTURisk methodology also well-estimated crop losses in the 2011 event which an overestimation about 21% from the reported value. Apart from that, fully 2D numerical method could not perfectly represent 1-in-100 year flood inundation due to non-consideration of important features such as the precise river channel topography, hydraulic infrastructures, and flood protection schemes in the river basin. Lack of such features results in an overestimation of flood damage and losses for 1-in-100 year flood comparing to the national flood hazard map and damage assessment which are simulated and estimated by JICA’s study. Such features can be better handled by using a coupled 1D/2D numerical method in order to simulate flood inundation extent more realistically and estimate flood losses. This could help the Thai government to better prepare a budget for flood risk prevention. In addition, even if the Flemish model indicates a good representation of relative flood damage to housing structures, the government should establish depth-damage curves specific for Thailand.

Cette thèse de doctorat porte sur l’analyse des dommages et sur l’évaluation des coûts induits sur les habitations par les submersions marines. L’étude se base sur les données d’assurance de deux évènements récents ayant touché la France et causé des submersions sur les côtes bretonnes et atlantiques : les tempêtes Johanna (mars 2008) et Xynthia (février 2010).Dans un premier temps, l’analyse des données d’expertise et d’indemnisation d’assurance, en lien avec celle des paramètres de l’aléa et des enjeux exposés, a eu pour but la meilleure compréhension des différents types de dommages, et l’explication des coûts observés. En parallèle, un travail de modélisation de l’aléa a été réalisé à une échelle régionale, afin de déterminer des indicateurs des forçages météo-marins, et à une échelle locale, afin de préciser les processus d’endommagement sur les sites étudiés pour les deux tempêtes. La caractérisation de la vulnérabilité et de la valeur des enjeux (coûts de construction) a été menée à l’aide de différents paramètres issus de bases de données nationales (INSEE et IGN) et de campagnes de terrain.Dans un second temps, les informations recueillies ont permis la construction de modèles empiriques de prédiction du coût des dommages aux habitations spécifiques à l’aléa submersion marine, outils aujourd’hui inexistants en France. Les différents types de modèles testés sont basés sur des approches statistiques univariées (fonctions d’endommagement) et multivariées. L’apport des données d’assurance à la réalisation de tels modèles est discuté, et des recommandations ainsi que des perspectives de recherche sont évoquées, afin de rendre ces modèles opérationnels et d’augmenter leur capacité de prédiction des coûts d’évènements catastrophiques futurs. / This PhD work aims at analysing damage and evaluating costs related to coastal flooding on residential buildings. The study is based on insurance data from two recent storm events, which caused coastal flooding in the Brittany and Atlantic regions in France: the storms Johanna (March 2008) and Xynthia (February 2010).At first, the analysis of insurance indemnities and loss adjustment data, in connection with hazard parameters, and exposed assets characteristics, allowed a better understanding of the different types of damage and costs observed. At the same time, hazard models were carried out at a regional level, in order to identify meteorological forcing indicators, and at a local level, in order to link damages to the associated physical flooding processes on the studied sites. The characterization of the asset’s vulnerability and values (construction costs) was conducted using different parameters from national databases (INSEE and IGN) and field survey.In a second step, empirical cost-assessment models were built on the basis of the data analysed, using univariate (damage functions) and multivariate statistical approaches. This study is the first attempt in France to elaborate models for the prediction of damage costs linked to coastal flooding on housing. The contribution of insurance data to the implementation of such models is discussed, and recommendations and research perspectives are expressed, in order to make the models operational and to increase their capacity to predict future catastrophic events costs.