Uncertainty and sensitivity analysis: tools for GIS-based model implementation

A novel procedure to analyse the uncertainty associated to the output of GI S-based models is presented. The procedure can handle models of any degree of complexity that accept any kind of input data. Two important aspects of spatial modelling are addressed: the propagation of uncertainty from model inputs and model parameters up to the model output (uncertainty analysis); and the assessment of the relative importance of the sources of uncertainty in the output uncertainty (sensitivity analysis). Two main applications ar e proposed. The procedure allows implementation of a GIS-based model whose output can reliably support the decision process with an optimized allocati on of resources for spatial data acquisition. This is possible in low cost strategy, based on numerical simulations on a small prototype of the GIS-ba sed model. Furthermore, the procedure provides an effective model building tool to choose, from a group of alternative models, the best one in terms o f cost-benefit analysis. A comprehensive case study is described. It concer ns the implementation of a new GIS-based hydrologic model, whose goal is pr oviding near real-time flood forecasting.