Infilling missing data of binary geophysical fields using scale invariant properties through an application to imperviousness in urban areas

Abstract : High resolution modelling is needed to improve the understanding and management of storm water in cities. It requires data, which is not always available. Hence the growing importance of handling missing data. Here, we use impervious areas in cities as case study. They are responsible for rapid runoff that can generate surface flooding. A methodology to handle such binary missing data relying on scale invariance properties is presented. It uses a previous study, which showed on ten peri-urban areas that imperviousness exhibits scale invariant features from meter to kilometre, to generate realistic scenarios for the missing impervious data. More precisely, fractal fields are commonly simulated thanks to a simple binary multiplicative cascade process (beta-model). Here we condition it to the available data. Numerical simulations are used to confirm theoretical expectations. It is then