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Globally, between 1950 and 2011 nearly 80,000 debris flow fatalities occurred in densely populated regions in mountainous terrain. Mitigation of these hazards includes the construction of check dams, which limit coarse sediment transport and in the European Alps number in the 100,000s. Check dam functionality depends on periodic, costly maintenance, but maintenance is not always possible and check dams often fail. As such, there is a need to quantify the long-term (10–100 years) geomorphic response of rivers to check dam failures. Here, for the first time, a landscape evolution model (CAESAR-Lisflood) driven by a weather generator is used to replicate check dam failures due to the lack of maintenance, check dam age, and flood occurrence. The model is applied to the Guerbe River, Switzerland, a pre-Alpine catchment containing 73 check dams that undergo simulated failure. Also presented is a novel method to calibrate CAESAR-Lisflood’s hydrological component on this ungauged catchment. Using 100-year scenarios of check dam failure, the model indicates that check dam failures can produce 8 m of channel erosion and a 322% increase in sediment yield. The model suggests that after check dam failure, channel erosion is the remobilization of deposits accumulated behind check dams, and, after a single check dam failure channel equilibrium occurs in five years, but after many check dam failures channel equilibrium may not occur until 15 years. Overall, these findings support the continued maintenance of check dams.

The knowledge about potential flood damage is a key issue for disaster risk reduction. However, the scarcity of empirical data has limited flood damage modeling in several regions. As a result, studies in data-scarce regions have mostly been restricted to either building exposure assessment or identification of vulnerability indicators without a further linkage to probable damage. As expert-based approaches do not require empirical damage data, they have a high potential for flood damage modeling in data-scarce regions. In this study, we carried out a comparative assessment between an expert-based and a data-driven approach. The expert-based approach systematically combines the vulnerability indicator method and synthetic what-if analysis based on the knowledge of regional experts. The data-driven approach integrates empirical flood damage data in the analysis applying a multivariate random forest model. Flood damage data, collected through interviews after two flood events in 2017 and 2019 at separate locations in Nigeria, were used to evaluate the performance of both methods based on developed damage grades. Results from both methods showed i) a predictive accuracy of 30% and 38% for the expert-based and data-driven approaches respectively, ii) that distance to channel, wall material, building condition, and building quality are significant regional damage drivers, and iii) comparable model performance can be achieved even with a reduced number of variables. Furthermore, the study demonstrated how experts are likely to underestimate damage at low water depths and how a difference in conformity to building standards can add to challenges in flood damage prediction.

Reducing risk that emerges from hazards of natural origin and societal vulnerability is a key challenge for the development of more resilient communities and the overall goal of sustainable development. The following chapter outlines a framework for multidimensional, holistic vulnerability assessment that is understood as part of risk evaluation and risk management in the context of Disaster Risk Management (DRM) and Climate Change Adaptation (CCA). As a heuristic, the framework is a thinking tool to guide systematic assessments of vulnerability and to provide a basis for comparative indicators and criteria development to assess key factors and various dimensions of vulnerability, particularly in regions in Europe, however, it can also be applied in other world regions. The framework has been developed within the context of the research project MOVE (Methods for the Improvement of Vulnerability Assessment in Europe; ) sponsored by the European Commission within the framework of the FP 7 program.