Space-Based Measurement of River Runoff

levels, and fl ow variability from orbital sensors have the potential to directly measure the runoff component of the Earth’s hydrologic cycle [Birkett et al.,2002; Brakenridge et al., 1998; Sippel et al.,1994, 1998; Townsend, 2001]. A remote-sensing-based measurement strategy for rivers and streams is emerging: Surface water data can be collected, their accuracy evaluated, and the results disseminated without regard to political boundaries. The results can be used to address a wide variety of applications. In this article, the needs for such measurements, a river reach-based methodology for their collection, and some sample results are presented. Because the international observational capability is increasing, some future opportunities for improving this strategy are also described. Previous articles document the inadequacy of present observational data concerning surface water [Shiklomanov et al.,2002; Alsdorf et al., 2003]. The problem is twofold: (1) inadequate data collection within many land areas, and (2) poor data access. In regard to the latter, the Global Runoff Data Centre (2004; http://grdc.bafg.de/) states: “Currently, only a few national hydrological services distribute their data in accordance with World Meteorological Organization resolutions which call for free and unrestricted exchange.” Also, depending on a nation’s position within a river basin, there are strong disincentives for sharing data. For example, the operation of dams and reservoirs can confl ict with water supply needs downstream. Reservoir construction within international river basins such as the Mekong, the Euphrates, and the Brahmaputra unavoidably raises diffi cult political issues. These issues are common in many regions, and will continue to motivate against free access to river discharge and other surface water data. The scientifi c need for such information is, however, critical. Examples of research problems cited by the Data Centre include water balance studies, coupling of hydrological and meteorological models, fl ux of freshwater and pollutants into the oceans, and comparisons of runoff volume to water quality data. Global climate change, including that associated with greenhouse gases, affects the Earth’s water cycle [Milly et al., 2002; Palmer and Raisanen, 2002; Smith, 1993; Trenberth et al., 2003]. Documentation and eventual prediction of such effects in particular requires consistent, globally distributed data. It will be very diffi cult to better understand and quantify the global water cycle without improved measurements of the runoff component. Better data sharing can be only part of the solution, because of the large land areas where gaging station networks have been discontinued, or where they have never existed (Figure 1).