Spatial hydrology aims at defining hydrosystem behavior more precisely, by means of a detailed characterization of the environment (using remote sensing images, DEM, maps, GPS). This analysis is based on large quantities of localized data from various sources and which are, to different degrees, of a fuzzy and heterogeneous character. The management of the data set as a whole gives rise to specific AI problems (fusion, updating, consistency). After clarification of these issues, we apply our conclusions by using a detailed example on a flood captured by aerial photographs: we transform information derived from the images into water levels, for any point of the flood zone. In addition to the collection of the source data (water levels, structuring of the plan, and definition of the topological relations), we present an algorithm built to generate consistent information, which is quite similar to a CSP approach. Results are applied to the 1993 flood of the Aisne River in France.