Don´t be afraid to do simple things
The main goal of part A of this book is to develop a basic conceptual understanding for the key aspects of modern probabilistic seismic hazard analysis (PSHA). The epigraph, which I picked up from Robin Adams, one of the pioneers of observational seismology in the 20th century, has stuck to my memory ever since I attended one of his training courses for young seismologists more than 20 years ago. It can be considered as one of the mottos for the approach taken here, namely to first develop concepts for rather simple situations in which most aspects are easy to understand. Subsequently, these concepts can be extended to more realistic situations. It has been my experience that this transition from the “toy world” to the “real world” can at least partially done rather intuitively.
Modern seismic hazard analysis draws from a number of disciplines such as probability therory, earthquake seismology and earthquake engineering. The fact that the analysis of any type of natural hazard is concerned with situations which are characterized by large amounts of uncertainties and randomness makes uncertainty assessment a key element of hazard analysis. In the context of seismic hazard it is for example the spatial distribution of future earthquakes which is uncertain, as are their occurrence rates, their source properties, and their site specific shaking characteristics. As a consequence, modern probabilistic seismic hazard analysis (PSHA) is usually accompanied by a systematic uncertainty analysis, sometimes involving different experts or expert groups. Different experts might provide different estimates for the building blocks of a hazard model, which in themselves carry uncertainties. In other words, uncertainties are everywhere and they appear in different flavors. Uncertainties are called aleatory (from alea the latin word for dice) if they appear as an intrinsic and unseparable aspect of the process under study. They are referred to as epistemic (from the greek word επιστεμωσ related to knowledge) if they are caused simply from the lack of knowledge. Epistemic uncertainties can be reduced, at least in principle, by gathering more knowledge while aleatoric can not. This makes important differences for the way these can be treated in practice.
Some aspects of the process under consideration might also be more uncertain than others, independent on the type of uncertainty. This naturally leads to the need for the quantification of different degrees of uncertainties. A common way in which this is done is in terms of probabilities. As a consequence, before we even start to think about details of a seismic hazard model in terms of seismicity models, earthquake source properties, site effects, or how to calulate hazard curves, we have to make sure that we have a basic knowledge in probability theory. This will be covered in chapter 2.
Fundemental aspects of earthquake seismology and earthquake engineering are very briefly touched upon in chapters 3 and 4, respectively, but only to a degree which I consider necessary from a seismic hazard analysis perspective which is then covered in detail in chapter 5, which then concludes part A of this book.