Bayes Nets (BN), or Bayesian Belief Networks (BBN), are directed acyclic graphs which can be used to model multiple strands of uncertain evidence. The talk will describe a number of applications in Earth Sciences where the speaker has used BNs, mainly in the contexts of quick and cheerful hazard and risk assessments: evaluating indirect observations hinting at incipient magmatic eruptions in Montserrat and at Bardarbunga, Iceland; appraising alternative hypotheses of the cause(s) of seismic unrest and deformation at Santorini; estimating contributions of ice sheet melting to sea level rise; evaluating evidence for a supposed major active seismogenic fault close to a Japanese nuclear facility; attribution of induced seismicity in Oklahoma to individual waste disposal wells; lahar forecasting and alerts; resilience of radwaste geological barriers to climate change; retrospective analysis of the 1976 Guadeloupe volcanic crisis. These examples range from the simplest, very basic nets (by WPA) to all-singing all-dancing frameworks of great complexity and sophisticated analytical capability (due to TH). En passant, the talk should encourage the notion that - in the inevitable presence of uncertainties - BNs are a natural rational basis for combining empirical observations and expert judgements. Some available BN/BBN packages for constructing and enumerating such nets will be mentioned.
Willy Aspinall, with extensive contributions from Thea Hincks and others
School of Earth Sciences, Bristol