ABSTRACT
Remote sensing has many applications in hydrology but is particularly attractive as a source of data for hydrological models. Modelling work has progressed from a period characterised as being data sparse and computationally constrained to one that is data rich and computationally powerful (DeCoursey, 1988; Melone et al., 1998; Storck et al., 1998; Jakeman et al., 1999). Many hydrological models have been produced but selecting a model and obtaining appropriate data to use in it can, however, be difficult (Melone et al., 1998). Initially, and to some extent as a function of past data availability and computing facilities, emphasis was placed on lumped models. Although valuable, lumped models are spatially constrained. Remote sensing has the potential to provide complete data coverage of large areas. As a consequence, remote sensing may be used to parameterise spatially distributed models (Harvey & Solomon, 1984). These distributed models offer the potential to refine our understanding of important hydrological issues, particularly those for which the spatial dimension is important (Dunn et al., 1998; Frankenberger et al., 1999).
