SAR imagery to estimate roughness parameters when modelling runoff risk

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Abstract
The influence of the roughness of agricultural soil on runoff and erosion is a proven fact. Synthetic aperture radar (SAR) sensors should enable discrimination between plots with different cropping patterns. A study of Mediterranean vineyards in southern France was made, with the aim of obtaining a better understanding of the potential for using radar satellite data from ERS-1 when estimating roughness parameters. Roughness measurements enabled modelling of the backscattering coefficient (sigma0) of known surfaces, using the electromagnetic Integral Equation Model (IEM). The good correlation between ERS-1 and IEM data indicated the feasibility of extracting roughness parameters by means of remote sensing methods. Seven ERS-1 images were examined, corresponding to different stages in the development of vegetation and roughness. Two images were finally selected as they offered the possibility of discriminating between two factors: (1) the orientation of mechanical labour, which can be related toa periodic and stable roughness over time, and (2) cropping practices, corresponding to a random roughness pattern that changes with season. Both roughness parameters derived from SAR satellite data contribute additional data to runoff models a preferred runoff direction as defined by furrow direction, as well as the intensity of this runoff under the influence of random roughness. A rule for the behaviour of sigma0 in terms of furrow orientation is presented.

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