Top-down seasonal streamflow model with spatiotemporal forest sapwood area

Abstract

Forest growth dynamics affect streamflow with changes in actual evapotranspiration (AET) during forest regeneration. Using a “top-down” model approach, we present a seasonal forest hydrology model that estimates streamflow in forested catchments containing sparse soil and climate data. Across a 1423 km2 remote study area, a rainfall interpolation procedure using available rainfall data and information on terrain was integrated into a new seasonal streamflow model, called ABCF, which uses catchment sapwood area (SA) as the emergent property that equilibrates with potential evapotranspiration (PET), and a soil storage threshold that reduces AET below PET when soil water is limiting. We produce seasonal estimates of streamflow with Nash Sutcliffe efficiencies of 0.85, 0.87, and 0.91 for three major catchments within the study area. A fundamental feature of the “top-down” model approach is the use of LiDAR data and forest inventory data to model forest structural properties that relate strongly with SA. Building on our previous work with this modelling framework, our representation of eco-hydrological properties of the forest has been refined with a more accurate procedure for estimating stand mean sapwood thickness, and hence SA, and a remotely sensed tree stocking density (N) of old-growth forests to correct the temporal evolution of N as a means to improve SA estimates. Regional consistency of model parameters shows that the “top-down” modelling framework may be used to estimate streamflow in ungauged catchments using a forest growth model. The seasonal model generalised for both water-limited and water-unlimited forest conditions has significant potential for application in water supply planning and drought security.