We applied the Maximum Entropy model to characterize multi-hazard scenarios in karst environments, focusing on flood-triggered sinkholes in Val d'Orléans, France. Karst terrains as multi-hazard forming areas, have received little attention in multi-hazard literature. Our study developed a multi-hazard susceptibility map to forecast the spatial distribution of these hazards. The findings improve understanding of hazard interactions and demonstrate the model's utility in multi-hazard analysis.

The Himalayan landscape is particularly susceptible to extreme events, which interfere with increasing populations and the expansion of settlements and infrastructure. This preface introduces and summarizes the nine papers that are part of the special issue, Estimating and predicting natural hazards and vulnerabilities in the Himalayan region.

The article provides a comparison of a standard (deterministic) risk assessment approach for roads exposed to a multi-hazard environment with a probabilistic risk analysis method to show the potential bias in the results. A probabilistic approach enables the quantification of epistemic uncertainty and uses probability distributions to characterize data uncertainty of the input variables, while a deterministic computation uses single values with discrete values without uncertainty representation.

Mitigation planning and economic loss assessment generally rely on flood damage prediction models. However, unavailability of empirical data has limited the use of such models in data-scarce areas. This paper combines the vulnerability indicator and damage grade approach to develop a conceptual framework for predicting building damage in data-scarce regions. The framework can be implemented using only expert knowledge and facilitates transferability of flood damage models in data-scarce areas.

Landslides are destructive events, threatening the integrity of land transport systems. This paper presents how road networks are vulnerable to landslides, with emphasis on the consequences for affected road users. Results show the merits of using agent-based traffic modelling to assess the impacts of road network interruptions on rural communities by providing insights into the characteristics of the population affected and the effects on its daily routine in terms of detour costs.