A probabilistic tool for multi-hazard risk analysis using a bow-tie approach: application to environmental risk assessments for geo-resource development projects

Abstract

In this paper, we present a methodology and a computational tool for performing environmental risk assessments for geo-resource development projects. The main scope is to implement a quantitative model for performing highly specialised multi-hazard risk assessments in which risk pathway scenarios are structured using a bow-tie approach, which implies the integrated analysis of fault trees and event trees. Such a model needs to be defined in the interface between a natural/built/social environment and a geo-resource development activity perturbing it. The methodology presented in this paper is suitable for performing dynamic environmental risk assessments using state-of-the-art knowledge and is characterised by: (1) the bow-tie structure coupled with a wide range of probabilistic models flexible enough to consider different typologies of phenomena; (2) the Bayesian implementation for data assimilation; (3) the handling and propagation of modelling uncertainties; and (4) the possibility of integrating data derived form integrated assessment modelling. Beyond the stochastic models usually considered for reliability analyses, we discuss the integration of physical reliability models particularly relevant for considering the effects of external hazards and/or the interactions between industrial activities and the response of the environment in which such activities are performed. The performance of the proposed methodology is illustrated using a case study focused on the assessment of groundwater pollution scenarios associated with the management of flowback fluids after hydraulically fracturing a geologic formation. The results of the multi-hazard risk assessment are summarised using a risk matrix in which the quantitative assessments (likelihood and consequences) of the different risk pathway scenarios considered in the analysis can be compared. Finally, we introduce an open-access, web-based, service called MERGER, which constitutes a functional tool able to quantitatively evaluate risk scenarios using a bow-tie approach.