This paper presents a broad overview, characterization, and visualization of the interaction relationships between 21 natural hazards, drawn from six hazard groups (geophysical, hydrological, shallow Earth, atmospheric, biophysical, and space hazards). A synthesis is presented of the identified interaction relationships between these hazards, using an accessible visual format particularly suited to end users. Interactions considered are primarily those where a primary hazard triggers or increases the probability of secondary hazards occurring. In this paper we do the following: (i) identify, through a wide-ranging review of grey- and peer-review literature, 90 interactions; (ii) subdivide the interactions into three levels, based on how well we can characterize secondary hazards, given information about the primary hazard; (iii) determine the spatial overlap and temporal likelihood of the triggering relationships occurring; and (iv) examine the relationship between primary and secondary hazard intensities for each identified hazard interaction and group these into five possible categories. In this study we have synthesized, using accessible visualization techniques, large amounts of information drawn from many scientific disciplines. We outline the importance of constraining hazard interactions and reinforce the importance of a holistic (or multihazard) approach to natural hazard assessment. This approach allows those undertaking research into single hazards to place their work within the context of other hazards. It also communicates important aspects of hazard interactions, facilitating an effective analysis by those working on reducing and managing disaster risk within both the policy and practitioner communities.

Despite the many complexities concerning their initiation and propagation, forest fires exhibit power-law frequency-area statistics over many orders of magnitude. A simple forest fire model, which is an example of self-organized criticality, exhibits similar behavior. One practical implication of this result is that the frequency-area distribution of small and medium fires can be used to quantify the risk of large fires, as is routinely done for earthquakes.