What is the key difference between a probability-based risk assessment and a deterministic risk assessment?

The key difference between a probability-based risk assessment and a deterministic risk assessment lies in how they treat uncertainty in the input parameters. A deterministic risk assessment uses single, fixed values for each input parameter to calculate a single, fixed outcome. It essentially assumes that all input parameters are known with certainty. A probability-based risk assessment, on the other hand, explicitly considers the uncertainty in the input parameters by assigning probability distributions to each parameter. These probability distributions represent the range of possible values for each parameter and the likelihood of each value occurring. The probability-based risk assessment then uses simulation techniques, such as Monte Carlo simulation, to generate a large number of possible outcomes based on the probability distributions of the input parameters. This results in a probability distribution of possible outcomes, rather than a single, fixed outcome. This allows decision-makers to assess the range of possible outcomes and the likelihood of each outcome occurring. For example, in a slope stability analysis, a deterministic risk assessment might use a single value for the shear strength of the soil. A probability-based risk assessment, on the other hand, might use a probability distribution to represent the uncertainty in the shear strength, based on the results of laboratory tests or expert judgment. The probability-based risk assessment would then generate a distribution of possible factors of safety, allowing decision-makers to assess the probability of slope failure. Probability-based risk assessments provide a more comprehensive and realistic assessment of risk than deterministic risk assessments, but they also require more data and computational resources.