A nonlinear dynamics approach to Bogoliubov excitations of Bose-Einstein condensates

We assume the macroscopic wave function of a Bose-Einstein condensate as a superposition of Gaussian wave packets, with time-dependent complex width parameters, insert it into the mean-field energy functional corresponding to the Gross-Pitaevskii equation (GPE) and apply the time-dependent variational principle. In this way the GPE is mapped onto a system of coupled equations of motion for the complex width parameters, which can be analyzed using the methods of nonlinear dynamics. We perform a stability analysis of the fixed points of the nonlinear system, and demonstrate that the eigenvalues of the Jacobian reproduce the low-lying quantum mechanical Bogoliubov excitation spectrum of a condensate in an axisymmetric trap.Comment: 7 pages, 3 figures, Proceedings of the "8th International Summer School/Conference Let's Face Chaos Through Nonlinear Dynamics", CAMTP, University of Maribor, Slovenia, 26 June - 10 July 201

Capturing regional differences in flood vulnerability improves flood loss estimation

Flood vulnerability is quantified by loss models which are developed using either empirical or synthetic approaches. In reality, processes influencing flood risk are stochastic and loss predictions bear significant uncertainty, especially due to differences in vulnerability across exposed objects and regions. However, many state-of-the-art flood loss models are deterministic, i.e., they do not account for data and model uncertainty. The Bayesian Data-Driven Synthetic (BDDS) model was one of the first approaches that used empirical data to reduce the prediction errors at object-level and enhance the reliability of synthetic flood loss models. However, the BDDS model does not account for regional differences in vulnerability which may result in over-/under-estimation of losses in some regions. In order to overcome this limitation, this study introduces a hierarchical parameterization of the BDDS model which enhances synthetic flood loss model predictions by quantifying regional differences in vulnerability. The hierarchical parameterization makes optimal use of the process information contained in the overall data set for the various regional applications, so that it is particularly suitable for cases in which only a small amount of empirical data is available. The implementation and performance of the hierarchical parametrization is demonstrated with the Multi-Colored Manual (MCM) loss functions and empirical damage dataset from the UK consisting of residential buildings from the regions Appleby, Carlisle, Kendal and Cockermouth that suffered losses during the 2015 flood event. The developed model improves prediction accuracy of flood loss compared to MCM by reducing the absolute error and bias by at least 23 and 90%, respectively. The model reliability in terms of hit rate (i.e., the probability that the observed value lies in the 90% high density interval of predictions) is 88% for residential buildings from the same regions used for calibration and 73% for residential buildings from new regions. The approach is of high practical relevance for all regions where only limited amounts of empirical flood loss data is available

Long-term development and effectiveness of private flood mitigation measures: An analysis for the German part of the river Rhine

Flood mitigation measures implemented by private households have become an important component of contemporary integrated flood risk management in Germany and many other countries. Despite the growing responsibility of private households to contribute to flood damage reduction by means of private flood mitigation measures, knowledge on the long-term development of such measures, which indicates changes in vulnerability over time, and their effectiveness, is still scarce. To gain further insights into the long-term development, current implementation level and effectiveness of private flood mitigation measures, empirical data from 752 flood-prone households along the German part of the Rhine are presented. It is found that four types of flood mitigation measures developed gradually over time among flood-prone households, with severe floods being important triggers for an accelerated implementation. At present, still a large share of respondents has not implemented a single flood mitigation measure, despite the high exposure of the surveyed households to floods. The records of household's flood damage to contents and structure during two consecutive flood events with similar hazard characteristics in 1993 and 1995 show that an improved preparedness of the population led to substantially reduced damage during the latter event. Regarding the efficiency of contemporary integrated flood risk management, it is concluded that additional policies are required in order to further increase the level of preparedness of the flood-prone population. This especially concerns households in areas that are less frequently affected by flood events

Influence of flood risk characteristics on flood insurance demand: A comparison between Germany and the Netherlands

The existence of sufficient demand for insurance coverage against infrequent losses is important for the adequate function of insurance markets for natural disaster risks. This study investigates how characteristics of flood risk influence household flood insurance demand based on household surveys undertaken in Germany and the Netherlands. Our analyses confirm the hypothesis that willingness to pay (WTP) for insurance against medium-probability medium-impact flood risk in Germany is higher than WTP for insurance against low-probability high-impact flood risk in the Netherlands. These differences in WTP can be related to differences in flood experience, individual risk perceptions, and the charity hazard. In both countries there is a need to stimulate flood insurance demand if a relevant role of private insurance in flood loss compensation is regarded as desirable, for example, by making flood insurance compulsory or by designing information campaigns

Flood loss reduction of private households due to building precautionary measures -- lessons learned from the Elbe flood in August 2002

Building houses in inundation areas is always a risk, since absolute flood protection is impossible. Where settlements already exist, flood damage must be kept as small as possible. Suitable means are precautionary measures such as elevated building configuration or flood adapted use. However, data about the effects of such measures are rare, and consequently, the efficiency of different precautionary measures is unclear. To improve the knowledge about efficient precautionary measures, approximately 1200 private households, which were affected by the 2002 flood at the river Elbe and its tributaries, were interviewed about the flood damage of their buildings and contents as well as about their precautionary measures. The affected households had little flood experience, i.e. only 15% had experienced a flood before. 59% of the households stated that they did not know, that they live in a flood prone area. Thus, people were not well prepared, e.g. just 11% had used and furnished their house in a flood adapted way and only 6% had a flood adapted building structure. Building precautionary measures are mainly effective in areas with frequent small floods. But also during the extreme flood event in 2002 building measures reduced the flood loss. From the six different building precautionary measures under study, flood adapted use and adapted interior fitting were the most effective ones. They reduced the damage ratio for buildings by 46% and 53%, respectively. The damage ratio for contents was reduced by 48% due to flood adapted use and by 53% due to flood adapted interior fitting. The 2002 flood motivated a relatively large number of people to implement private precautionary measures, but still much more could be done. Hence, to further reduce flood losses, people's motivation to invest in precaution should be improved. More information campaigns and financial incentives should be issued to encourage precautionary measures

A consistent approach for probabilistic residential flood loss modeling in Europe

In view of globally increasing flood losses, a significantly improved and more efficient flood risk management and adaptation policy are needed. One prerequisite is reliable risk assessments on the continental scale. Flood loss modeling and risk assessments for Europe are until now based on regional approaches using deterministic depth‐damage functions. Uncertainties associated with the risk estimation are hardly known. To reduce these shortcomings, we present a novel, consistent approach for probabilistic flood loss modeling for Europe, based on the upscaling of the Bayesian Network Flood Loss Estimation MOdel for the private sector, BN‐FLEMOps. The model is applied on the mesoscale in the whole of Europe and can be adapted to regional situations. BN‐FLEMOps is validated in three case studies in Italy, Austria, and Germany. The officially reported loss figures of the past flood events are within the 95% quantile range of the probabilistic loss estimation, for all three case studies. In the Italian, Austrian, and German case studies, the median loss estimate shows an overestimation by 28% (2.1 million euro) and 305% (5.8 million euro) and an underestimation by 43% (104 million euro), respectively. In two of the three case studies, the performance of the model improved, when updated with empirical damage data from the area of interest. This approach represents a step forward in European wide flood risk modeling, since it delivers consistent flood loss estimates and inherently provides uncertainty information. Further validation and tests with respect to adapting the model to different European regions are recommended

Development and assessment of uni- and multivariable flood loss models for Emilia-Romagna (Italy)

Flood loss models are one important source of uncertainty in flood risk assessments. Many countries experience sparseness or absence of comprehensive high-quality flood loss data, which is often rooted in a lack of protocols and reference procedures for compiling loss datasets after flood events. Such data are an important reference for developing and validating flood loss models. We consider the Secchia River flood event of January 2014, when a sudden levee breach caused the inundation of nearly 52km2 in northern Italy. After this event local authorities collected a comprehensive flood loss dataset of affected private households including building footprints and structures and damages to buildings and contents. The dataset was enriched with further information compiled by us, including economic building values, maximum water depths, velocities and flood durations for each building. By analyzing this dataset we tackle the problem of flood damage estimation in Emilia-Romagna (Italy) by identifying empirical uni- and multivariable loss models for residential buildings and contents. The accuracy of the proposed models is compared with that of several flood damage models reported in the literature, providing additional insights into the transferability of the models among different contexts. Our results show that (1) even simple univariable damage models based on local data are significantly more accurate than literature models derived for different contexts; (2) multivariable models that consider several explanatory variables outperform univariable models, which use only water depth. However, multivariable models can only be effectively developed and applied if sufficient and detailed information is available

Flood loss models and risk analysis for private households in can Tho City, Vietnam

Vietnam has a long history and experience with floods. Flood risk is expected to increase further due to climatic, land use and other global changes. Can Tho City, the cultural and economic center of the Mekong delta in Vietnam, is at high risk of flooding. To improve flood risk analyses for Vietnam, this study presents novel multi-variable flood loss models for residential buildings and contents and demonstrates their application in a flood risk assessment for the inner city of Can Tho. Cross-validation reveals that decision tree based loss models using the three input variables water depth, flood duration and floor space of building are more appropriate for estimating building and contents loss in comparison with depth-damage functions. The flood risk assessment reveals a median expected annual flood damage to private households of US$3340 thousand for the inner city of Can Tho. This is approximately 2.5%of the total annual income of households in the study area. For damage reduction improved flood risk management is required for the Mekong Delta, based on reliable damage and risk analyses

Needed: a systems approach to improve flood risk mitigation through private precautionary measures

Private precautionary measures play an increasingly important role in flood risk management. The degree to which private precautionary measures mitigate flood risk depends mainly on the type of measure (and how effective it is) and how frequently and successfully it is implemented. These aspects are influenced by a complex interaction of physical and socio-economic processes, which makes the assessment and the prediction of the mitigation of flood risk via private precautionary measures a challenge. This paper provides an overview of factors and processes that influence the implementation and effectiveness of private precaution in mitigating flood risk, underpinning it with highlights from international examples. We recommend private precautionary measures for further use to improve flood risk mitigation, but stress that they need to be considered and implemented through a holistic systems approach to maximize their effectiveness

Is flow velocity a significant parameter in flood damage modelling?

Flow velocity is generally presumed to influence flood damage. However, this influence is hardly quantified and virtually no damage models take it into account. Therefore, the influences of flow velocity, water depth and combinations of these two impact parameters on various types of flood damage were investigated in five communities affected by the Elbe catchment flood in Germany in 2002. 2-D hydraulic models with high to medium spatial resolutions were used to calculate the impact parameters at the sites in which damage occurred. A significant influence of flow velocity on structural damage, particularly on roads, could be shown in contrast to a minor influence on monetary losses and business interruption. Forecasts of structural damage to road infrastructure should be based on flow velocity alone. The energy head is suggested as a suitable flood impact parameter for reliable forecasting of structural damage to residential buildings above a critical impact level of 2 m of energy head or water depth. However, general consideration of flow velocity in flood damage modelling, particularly for estimating monetary loss, cannot be recommended