PhD Student Presentation by Robert Armstrong: Monday 28th March at 2:30pm

Centre for Hydrology PhD Student Robert Armstrong will present details of his work on ‘Spatial Variability of Actual Evaporation in a Prairie Landscape’ on Monday 28 March, 2011 at 2:30pm, 144 Kirk Hall.
The following abstract provides an overview of his work;
Actual evaporation has considerable spatial variability that is not captured by point scale estimates from meteorological station data. Physically-based point scale evaporation models were found to provide reasonable estimates of evaporation for temporal scales from several days to seasonal periods but provided poorer estimates for daily and sub-daily periods. Remote sensing was valuable for deriving key variables needed for distributing point scale models for direct estimates over a larger area. A method was developed for distributing net radiation at the field scale which can be used to obtain the spatial variability of evaporation estimates. There was no evidence that spatial covariance between surface variables driving the Granger feedback evaporation model influenced upscaled evaporation estimates which can be attributed to offsetting interactions between model parameters. The variability of point scales estimates obtained from long term hydrological simulations during drought and non-drought periods was further considered across the Canadian Prairie region. The structure of drought was dynamic and there was no consistent spatial pattern of actual evaporation. The variability of evaporation increased as the drought progressed and declined sharply with ensuing wetter conditions.
The results contribute to a better understanding of the effects of spatial associations of key factors on evaporation estimates in a Prairie landscape. The methodology developed for distributing net radiation from assimilated visible and thermal images could potentially be used in regional scale modelling applications for improving evaporation estimates using point scale estimation techniques. The modelling algorithms applied to derive point estimates of evaporation from surface reference data may be useful for operational purposes that require estimates of evaporation (e.g. agriculture, hydrology, ecology, etc.).