Most hydrologists are aware of and perhaps intrigued by remote sensing, but very few are actual users of the data and almost none have the necessary technical background to easily use remote sensing. There are a number of reasons for this, but perhaps the most important reason is that remote sensing data are 'different' from the data that we have collected experimentally or used to run or calibrate our models. They are different because they do not duplicate what we measure on the ground from point measurements. In other words, remote sensing data are spatial and in many instances some of the detail that we are accustomed to working with in experimental hydrology is obliterated with remote sensing. In other instances they are different because they do not duplicate the variables that we measure on the ground. The only really successful applications of remote sensing to hydrology have involved models, such as the Soil Conservation Service (SCS) curve number, that use land use data. This is because there has been a one-to-one substitution for land use determined from photos or field surveys by remote sensing determined land use. There has been essentially no use of the soil surface layer's dielectric constant, which can be measured with a microwave instrument, in hydrology even though there is a very strong relationship between the dielectric constant and soil moisture.
The following three papers have been selected to give readers a broad spectrum of possible remote sensing applications to hydrology. The first paper, 'Snow hydrology processes and remote sensing' by A1 Rango not only covers the current state of development in snow hydrology, but also discusses what we can expect in the future. Other than land use, snow hydrology has been the most successful area of hydrology to use remote sensing. The second paper, 'Measuring large scale surface soil moisture using passive microwave remote sensing' by Tom Jackson introduces the reader to the nature of remote sensing that takes it beyond a photograph. That is, the microwave region of the spectrum allows us to penetrate clouds and vegetation to sample a layer of soil and determine the value of a state variable, soil moisture. The third paper, by McKim et al., illustrates how remote sensing data can be used with other emerging technologies such as object-oriented programming and geographical information systems to model hydrology and water resources.
These three papers illustrate the breadth and depth that is possible from remote sensing. Although these papers have perhaps emphasized the operational aspects of hydrology rather than the inquiry of the processes, this is, to a great degree, because more complete work has been done in the applications area. However, this does not mean that there is no place for remote sensing in the study of hydrological processes. To the contrary, I believe that remote sensing may be the key to unlocking some of the more difficult questions facing hydrologists. The questions of scale and the relationships among point measurements may only be successfully attacked with remote sensing. The temporal nature of satellite data and the spatial characteristics of remote sensing data offer to hydrologists a perspective of hydrological processes that is unfamiliar at best. However, to make maximum use of remote sensing we need to modify or redesign our models to reflect this new capability and the ability to measure new variables, such as soil moisture and snow water content. This, plus the expectation of new, higher resolution sensors and ways to handle the data make remote sensing a potentially valuable new tool for the investigation of hydrological processes.