Sensitivity analysis on spatial models: a new approach

Sensitivity analysis involves determining the contribution of individual input factors to uncertainty in model predictions. The most commonly used approach when doing a sensitivity analysis on spatial models is using Monte Carlo simulation. There are a number of techniques for calculating sensitivity indices from the Monte Carlo simulations, some more effective or efficient than others. These techniques are summarised along with their limitations. A new technique for undertaking a spatial sensitivity analysis based on the Sobol' method is proposed and tested. This method is global, variance-based, and model-free. The technique is illustrated with two simple test models.