Multi-scale spatial sensitivity analysis of a model for economic appraisal of flood risk management policies

We demonstrate the use of sensitivity analysis to rank sources of uncertainty in models for economic appraisal of flood risk management policies, taking into account spatial scale issues. A methodology of multi-scale variance-based global sensitivity analysis is developed, and illustrated on the NOE model on the Orb River, France. The variability of the amount of expected annual flood avoided damages, and the associated sensitivity indices, are estimated over different spatial supports, ranging from small cells to the entire floodplain. Both uncertainty maps and sensitivity maps are produced to identify the key input variables in the NOE model at different spatial scales. Our results show that on small spatial supports, variance of the output indicator is mainly due to the water depth maps and the assets map (spatially distributed model inputs), while on large spatial supports, it is mainly due to the flood frequencies and depthedamage curves (non spatial inputs). © 2014 Elsevier Ltd. All rights reserved. Software availability Name of software: NOE Description: The NOE model computes expected annual flood damages at the scale of individual flood-exposed assets, from a given situation, i.e. from a land use map, a set of water depth maps, and a set of depthedamage curves. It also computes expected annual avoided damages at the same scale, when comparing one situation with another. Developers: N. Saint-Geours, T. Langer, F. Grelot and J.-S. Bailly Source language: Python (arcpy library) and R Software required: ArcGIS Availability: Contact the developers