Representation of the hydrological interaction between the land surface and the atmosphere requires considerable improvement, particularly for predicting evapotranspiration feedbacks for use in models of the general circulation (GCMs) of the atmosphere. The predictive model developed here attempts to use a water balance approach that extracts information from the masses of catchment-scale time series data available on precipitation, energy-related variables and stream discharge. It begins with a few simple assumptions in order to seek some synthesis of the climate and landscape controls on evapotranspiration and soil moisture feedbacks, and catchment water yields. The model adopts the hydrograph identification approach used in the linear module of the rainfall-runoff model IHACRES but replaces
the previous statistically based non-linear evapotranspiration loss module by a catchment moisture deficit accounting scheme. One advantage of this more conceptual approach is that evapotranspiration can be output on the same time step at which precipitation and energy variables are available (such as from GCMs), and this time step can be shorter (e.g. half hourly) than the discharge time step (e.g. daily) used to calibrate the model parameters.
Figure 3: Catchment moisture deficit in the Scott Catchment.
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Last updated 31st January 2013