Capturing within catchment variation in evapotranspiration from montane forests using LiDAR canopy profiles with measured and modelled fluxes of water

Patterns in forest structure and function are tightly coupled to variation in energy and soil water gradients and disturbance history across the landscape. In eucalypt forests of southern Australia, changes in forest structure may account for the majority of variation in the evapotranspiration (E_t) signal across a single forest type. In this study, the potential for using light detection and ranging (LiDAR)-derived canopy height profiles to predict key components of E_t; transpiration (E_sap), interception loss (E_i) and forest floor evapotranspiration (E_floor) was assessed in a mixed-species eucalypt forest in south-eastern Australia. Step-wise regression was used to select suitable LiDAR canopy height indices to predict stand structural attributes at all grid points within the catchment using field plot inventory data (r² = 0.76–0.88). Similar rates of sap velocity were observed among trees at different landscape positions and during all seasons, irrespective of tree size and stature, enabling scaling of stand-level E_sap. The revised Gash interception model was successfully used to model E_t across the catchment using stand-level variation in canopy cover (derived from LiDAR). Similarly, E_floor was quantified spatially using variation in leaf area index and a two-bucket numeric model to interpolate field measurements. Our results show that variation in forest structure arising from changes in elevation in these south-facing catchments is a major determinant of forest water use and shows a threefold change in annual E_t across the elevation gradient. The merging of detailed forest structural data and field-validated E_t fluxes offers promise in advancing our understanding and prediction of key ecohydrologic processes in forested catchments.