Abstract: Aims Changing climate and land use patterns make it increasingly important that the hydrology of catchments and ecosystems can be reliably characterized. The aim of this paper is to identify the biophysical factors that determine the rates of water vapor loss from different types of vegetation, and to seek, from an array of currently available satellite-borne sensors, those that might be used to initialize and drive landscape-level hydrologic models.
Important findings Spatial variation in the mean heights, crowd widths, and leaf area indices (LAI) of plant communities are important structural variables that affect the hydrology of landscapes. Canopy stomatal conductance (G) imposes physiological limitation on transpiration by vegetation. The maximum value of G (G max) is closely linked to canopy photosynthetic capacity, which can be estimated via remote sensing of foliar chlorophyll or nitrogen contents. G can be modeled as a nonlinear multipliable function of: (i) leaf–air vapor pressure deficit, (ii) water potential gradient between soil and leaves, (iii) photosynthetically active radiation absorbed by the canopy, (iv) plant nutrition, (v) temperature and (vi) the CO₂ concentration of the air. Periodic surveys with Light Detection and Ranging (LiDAR) and interferometric RADAR, along with high-resolution spectral coverage in the visible, near-infrared, and thermal infrared bands, provide, along with meteorological data gathered from weather satellites, the kind of information required to model seasonal and interannual variation in transpiration and evaporation from landscapes with diverse and dynamic vegetation.

Key words: canopy stomatal conductance, plant water relations, process-based models, remote sensing