Spatial variability of actual evaporation in a prairie landscape
Armstrong, Robert Norman
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Land surface evaporation has considerable spatial variability that is not reflected in meteorological station data alone. Knowing the spatial variability of evaporation is important for describing drought, managing agricultural land, and is valuable for improving the parameterization of hydrological models and land surface schemes over large areas. General difficulties arise for obtaining reliable, spatially distributed evaporation estimates as a result of uncertainty in estimation techniques, scale issues and complexities regarding land surface and atmospheric interactions, and the spatial and temporal variability of key factors governing the evaporation process. Estimating evaporation is further complicated when soil moisture becomes a critical limitation, particularly during drought. An examination of the spatial variability of evaporation and its association with governing factors was conducted in Prairie landscapes using three modelling techniques. First, eddy covariance measurements and reference meteorological data were obtained at two Prairie locations to assess the accuracy of physically-based models for calculating point estimates of actual evaporation under non-limited soil moisture conditions and during drought. Second, estimates of actual evaporation were distributed at the field scale in order to examine the impacts of driving factors and their spatial associations on upscaled evaporation estimates. This required the assimilation of high resolution visible and thermal images which were used to derive estimates of surface albedo and surface emitted longwave radiation. These were combined along with surface reference observations to develop an index of the mid-day radiation in order to distribute a known value of mean daily net radiation over the field. Third, archived historical climate data were used as input for a continuous hydrological simulation to examine spatial and temporal variations in evaporation across the Prairie region of Western Canada during a drought and non-drought period. Results of this research showed that the spatial variability of evaporation could be derived at the field scale by integrating remote sensing and surface reference climate data with a physically-based evaporation model. Surface temperature and soil moisture, and net radiation were found to be highly variable spatially at field scales whilst meteorological conditions tended to be less variable spatially but showed strong temporal variability. At the field scale it was found that the variability in albedo and surface temperature were both important for characterizing differences in surface state conditions. Their combined influence was reflected in the resulting pattern of net radiation that governed the distribution of actual evaporation estimates obtained with the Granger and Gray evaporation model. It was found that an areal estimate of evaporation obtained from the means of driving factors was similar to the areal average obtained from the distributed estimates. This was attributed to the offsetting interactions among the driving factors which effectively reduced the variability of the model estimates. In general, the physically-based models examined were found to provide reasonable estimates of actual evaporation when driven by observations at point-scales over multi-day and seasonal periods. This included periods when soil moisture was not a strong limitation and also under drought conditions. Variations in the spatial pattern of actual evaporation provided a useful indicator of drought across the Prairie region of Western Canada. 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 actual evaporation and for characterizing drought.
DegreeDoctor of Philosophy (Ph.D.)
SupervisorPomeroy, John; Martz, Lawrence
CommitteeSi, Bing; de Boer, Dirk; Amiro, Brian; Guo, Xulin; Granger, Raoul
Copyright DateJune 2011