The field of remote sensing continues to develop rapidly, making synoptic data sources regarding landscape characteristics more accessible for modelling applications ( Engman and Gurney 1991; Dozier 1992; Stewart and Finch 1993; Engman, this issue). In addition to topography, the spatial distribution of factors such as meteorological conditions, vegetation, soil characteristics, and land use are of significant interest in hydrological modelling, as they strongly influence soil moisture content and runoff contributions ( Moore et al. 1991; Rango 1992a; Wigmosta et al. 1994). Spatial variation in landscape attributes can be analyzed and mapped from digital imagery, yielding input data for models. For example, Goodrich et al. (1994) examine the use of remotely sensed soil wetness for modelling runoff in a semi-arid environment.
Offering significant advances in our ability to quantify precipitation, the first Next Generation Weather Radar (NEXRAD) Weather Surveillance Radars--88 Doppler (WSR-88) have been deployed after many years of development. Well over one hundred WSR-88 sites will be installed across the nation by 1996, providing near real-time, high resolution precipitation data, including (but not limited to) the reflectivity data from which precipitation volume and intensity are computed over space and time. With data collected from initial sites already being investigated and used as a tool for model input, NEXRAD promises to become an invaluable data source for hydrological modellers as the network expands and data become widely available. ( Klazura et al. 1992; Klazura and Imy 1993).
Collection of snow precipitation data also has been improved. The Soil Conservation Service (SCS) continues to monitor and collect real-time data detailing snowpack properties, which are transmitted automatically from a network of approximately 500 snowpack telemetry (SNOTEL) sites located in remote mountainous areas of the western United States. Such ``point'' measurements are augmented now with satellite remote sensing to determine the spatial and temporal distribution of snow properties. The National Operational Hydrologic Remote Sensing Center of the National Weather Service (NWS) continued to develop its line of products in the past four years ( NWS 1992). Real-time snow water equivalent (SWE) data for river basins in more than twenty-five states are available. Comparison of airborne gamma radiation measurements over bare ground with those over snow covered ground allow computation of SWE. Areal extent of snow cover is mapped for more than 4000 river basins nation wide using satellite data from the Advanced Very High Resolution Radiometer (AVHRR) and Geostationary Operational Environmental Satellite (GOES). The images are classified into categories of snow free, snow covered, or cloud covered areas; a GIS is then used to overlay the categories onto the terrain and digitally map the extent of snow cover in various elevation zones of each river basin. Both water equivalent and areal extent of snow cover data are mapped, and are available in near real time over electronic mail networks. ( NWS 1992). These data have become a primary source of information for modelling of snow covered basins (e.g., Rango 1992b).
Satellite imagery also has proved to be a fundamental data source
for successful mapping and classification of land-use
applications. Accurate classification of vegetative land cover can be
made using synoptic imagery of the landscape (e.g., Baker et
al. 1991; Bolstad and Lillesand 1992; Duchon et al. 1992;
Kite and Kouwen 1992). In recent years it has become commonplace
to use data obtained from the Landsat Thematic Mapper (TM),
Multispectral Scanner (MSS), or Syst
me Probatoire
d'Observation de la Terre (SPOT), along with coincident aerial photos
and terrain data, for these purposes.
Remote sensing of many additional hydrological parameters is still in the investigative stages. Ongoing research seeks to improve spatial and temporal data resolution for precipitation, soil moisture ( Shih and Jordan 1992; Paloscia et al. 1993), snow water equivalent ( Chang et al. 1991; Hosang and Dettwiler 1991; Blyth 1993), extent and depth of snow cover ( Srivastav and Singh 1991; Chang and Foster 1992; Blyth 1993) and reflectance derived surface albedo ( Duguay and LeDrew 1991; Winther 1992). Undoubtedly, progress in improving remote sensing techniques in the future will lead to products that will be very useful for catchment modelling. See Rango (1992a, 1993) and Engman (this issue) for further discussion.