The utility of using Volunteered Geographic Information (VGI) for evaluating pluvial flood models.

Pluvial floods are increasingly threatening urban environments worldwide due to human-induced climate change. High-resolution, state-of-the-art pluvial flood models are urgently needed to inform climate change adaptation and disaster risk reduction measures but are generally not empirically tested because of the rarity of local high-intensity precipitation events and the lack of monitoring capabilities. Volunteered Geographic Information (VGI) collected by professionals, non-professionals and citizens and made available on the internet can be used to monitor the dynamic extent of a pluvial flood during and after an extreme rain event but is sometimes considered to be unreliable. In this paper, we explore the general utility of VGI to evaluate the performance of pluvial flood models and gain new insights to improve these models. As background for our research, we use the capital city of Budapest, which recently suffered three heavy rainfall events in just five years (2015, 2017 and 2020). For each pluvial flood event, we collected photographic evidence from different online media sources and estimated the associated water depths at various locations in the city from the image context. These were compared with the results of a 2D pluvial flood model that has been shown to provide comparable results to other state-of-the-art inundation models and is easily transferred to other urban areas due to its reliance on open data sources. We introduce a general methodology for comparing VGI with model data by probing different spatial resolutions. Our findings highlight untapped potential and fundamental challenges in using VGI for model evaluation. It is proposed that VGI may become an essential tool and improve the confidence in model-based risk assessments for climate change adaptation and disaster risk reduction.

The challenge of unprecedented floods and droughts in risk management.

Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3.

Exposure and vulnerability estimation for modelling flood losses to commercial assets in Europe.

Commercial assets comprise buildings, machinery and equipment, which are susceptible to floods. Existing damage models and exposure estimation methods for this sector have limited transferability between flood events and therefore limited potential for pan-European applications. In this study we introduce two methodologies aiming at improving commercial flood damage modelling: (1) disaggregation of economic statistics to obtain detailed building-level estimates of replacement costs of commercial assets; (2) a Bayesian Network (BN) damage model based primarily on post-disaster company surveys carried out in Germany. The BN model is probabilistic and provides probability distributions of estimated losses, and as such quantitative uncertainty information. The BN shows good accuracy of predictions of building losses, though overestimates machinery/equipment loss. To test its suitability for pan-European flood modelling, the BN was applied to three case studies, comprising a coastal flood in France (2010) and fluvial floods in Saxony (2013) and Italy (2014). Overall difference between modelled and reported average loss per company was only 2-19% depending on the case study. Additionally, the BN model achieved better results than six alternative damage models in those case studies (except for one model in the Italian case study). Further, our exposure estimates mostly resulted in better predictions of the damage models compared to previously published pan-European exposure data, which tend to overestimate exposure. All in all, the methods allow easy modelling of commercial flood losses in the whole of Europe, since they are applicable even if only publicly-available datasets are obtainable. The methods achieve a higher accuracy than alternative approaches, and inherently provide confidence intervals, which is particularly valuable for decision making under high uncertainty.

Probabilistic, Multivariable Flood Loss Modeling on the Mesoscale with BT-FLEMO.

Flood loss modeling is an important component for risk analyses and decision support in flood risk management. Commonly, flood loss models describe complex damaging processes by simple, deterministic approaches like depth-damage functions and are associated with large uncertainty. To improve flood loss estimation and to provide quantitative information about the uncertainty associated with loss modeling, a probabilistic, multivariable Bagging decision Tree Flood Loss Estimation MOdel (BT-FLEMO) for residential buildings was developed. The application of BT-FLEMO provides a probability distribution of estimated losses to residential buildings per municipality. BT-FLEMO was applied and validated at the mesoscale in 19 municipalities that were affected during the 2002 flood by the River Mulde in Saxony, Germany. Validation was undertaken on the one hand via a comparison with six deterministic loss models, including both depth-damage functions and multivariable models. On the other hand, the results were compared with official loss data. BT-FLEMO outperforms deterministic, univariable, and multivariable models with regard to model accuracy, although the prediction uncertainty remains high. An important advantage of BT-FLEMO is the quantification of prediction uncertainty. The probability distribution of loss estimates by BT-FLEMO well represents the variation range of loss estimates of the other models in the case study.

A Review of Flood Loss Models as Basis for Harmonization and Benchmarking.

Risk-based approaches have been increasingly accepted and operationalized in flood risk management during recent decades. For instance, commercial flood risk models are used by the insurance industry to assess potential losses, establish the pricing of policies and determine reinsurance needs. Despite considerable progress in the development of loss estimation tools since the 1980s, loss estimates still reflect high uncertainties and disparities that often lead to questioning their quality. This requires an assessment of the validity and robustness of loss models as it affects prioritization and investment decision in flood risk management as well as regulatory requirements and business decisions in the insurance industry. Hence, more effort is needed to quantify uncertainties and undertake validations. Due to a lack of detailed and reliable flood loss data, first order validations are difficult to accomplish, so that model comparisons in terms of benchmarking are essential. It is checked if the models are informed by existing data and knowledge and if the assumptions made in the models are aligned with the existing knowledge. When this alignment is confirmed through validation or benchmarking exercises, the user gains confidence in the models. Before these benchmarking exercises are feasible, however, a cohesive survey of existing knowledge needs to be undertaken. With that aim, this work presents a review of flood loss-or flood vulnerability-relationships collected from the public domain and some professional sources. Our survey analyses 61 sources consisting of publications or software packages, of which 47 are reviewed in detail. This exercise results in probably the most complete review of flood loss models to date containing nearly a thousand vulnerability functions. These functions are highly heterogeneous and only about half of the loss models are found to be accompanied by explicit validation at the time of their proposal. This paper exemplarily presents an approach for a quantitative comparison of disparate models via the reduction to the joint input variables of all models. Harmonization of models for benchmarking and comparison requires profound insight into the model structures, mechanisms and underlying assumptions. Possibilities and challenges are discussed that exist in model harmonization and the application of the inventory in a benchmarking framework.

Perspectives for motorcycle stability control systems.

On a global scale, motorcyclists are typically over-represented in crash statistics. This trend is increasing as although total road crashes and fatalities have decreased over the last fifteen years, motorcycle crash volumes have not. This paper describes the potential of stability control systems to help save motorcyclists' lives. It summarizes safety research conducted and commissioned by the Federal Highway Research Institute (Bundesanstalt für Straßenwesen, BASt) during the last twenty-five years, with particular focus on the authors' own work in the last five years, and the state of the art in motorcycle control systems. The conclusion is that further investigation and improvement of these systems should be encouraged. Unfortunately, active stabilization of motorcycles is not presently possible and may not be possible in the future. Therefore, further development, evolution and optimization of Anti-Lock Brake Systems (ABSs) and Traction Control Systems (TCS) should be undertaken, and Anti-Lock Brake Systems (ABSs) should be mandatory on powered two-wheelers. These steps will make the powered two-wheeler a safer urban transportation system.