With the successful launch of the first Earth Resources Technology Satellite (ERTS-1 or Landsat-1) on 23 July 1972, scientists and engineers gained a valuable new source of space-based observations for studying hydrologic systems and processes. Previously hampered by a lack of detailed spatial information, hydrologists were suddenly able to make detailed improved assessments of water-resource conditions. As the broad-scale utility of remotely sensed data became increasingly apparent, considerable effort was expended to extract more detailed information from the original imaging products. Moreover, hydrologic models were extensively revised or re-invented to make even more efficient use of this new form of information. Such work has continued to expand as the number of satellite and airborne platforms has multiplied and as their spatial resolution, global coverage, and orbital frequency have increased. Aided by a concurrent growth in the ability and sophistication of computer and software technology, it has now become possible for a multitude of downstream users to evaluate rapidly and quantify large numbers of watershed physical characteristics and state variables. Table I provides a sample listing of the broad range of satellite data and their specific characteristics that are currently being used, or have the potential, to determine various hydrologic variables. Such advances have also produced significant economic advantages. For example, Kite and Pietroniro (1996) note that benefit/cost ratios ranging from 75 : 1 to 100 : 1 can be easily realized by using remotely sensed data in hydrology and water resources management (e.g. Castruccio et al., 1980;Rango, 1980;Carroll, 1985). Major sources of savings result from more effective flood prevention and improved planning of irrigation and hydroelectric schemes (construction and operation).
In most cases, remote sensing data are used to assess the hydrological state of a basin or region by estimating various hydrologic-state variables (in the liquid, solid or gas phase) and/or hydrologically significant physiographic variables that can influence hydrologic processes or responses. Three broad classes are commonly used to describe the ways in which remote sensing is used in hydrology (Salomonson, 1983). The first is the simple delineation of readily identifiable, broad surface features, such as snow-cover, surface water or sediment plumes. The second use involves more detailed interpretation and classification of the remotely sensed data to derive more subtle features, such as specific geologic features or various land-cover types. The use of digital data to estimate hydrological state variables (e.g. soil moisture) forms the third class. This is normally achieved by establishing an initial correlation between measured conditions for a specific parameter and the pertinent remotely sensed data.
Over the years, research and applications of remote sensing within hydrology have embraced a variety of topics, ranging from the evaluation of the extent and condition of basic near-surface water features-such as snow, ice and soil moisture-to the mapping of extreme flood events, poorly definable wetlands or lake