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Probabilistic risk analysis in subsurface hydrology
Author(s) -
Tartakovsky Daniel M.
Publication year - 2007
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2007gl029245
Subject(s) - aquifer , probabilistic logic , uncertainty quantification , probabilistic risk assessment , environmental remediation , fault tree analysis , subsurface flow , parametric statistics , environmental science , uncertainty analysis , hydrology (agriculture) , geology , groundwater , computer science , contamination , geotechnical engineering , statistics , reliability engineering , mathematics , engineering , machine learning , ecology , biology
We present a general framework for probabilistic risk assessment (PRA) of subsurface contamination. PRA provides a natural venue for the rigorous quantification of structural (model) and parametric uncertainties inherent in predictions of subsurface flow and transport. A typical PRA starts by identifying relevant components of a subsurface system (e.g., a buried solid‐waste tank, an aquitard, a remediation effort) and proceeds by using uncertainty quantification techniques to estimate the probabilities of their failure. These probabilities are then combined by means of fault‐tree analyses to yield probabilistic estimates of the risk of system failure (e.g., aquifer contamination). Since PRA relies on subjective probabilities, it is ideally suited for assimilation of expert judgment and causal relationships.