Abstract
Optical remote sensing data collected during the Monsoon '90 experiment in the Walnut Gulch Experimental Watershed in southern Arizona were used to estimate basin-scale surface temperature, net radiation (R n) and soil heat flux (G). These were combined with several atmospheric boundary-layer (ABL) models to allow computation of basin-scale surface fluxes of sensible (H) and latent heat (LE). The calculated fluxes were compared to averages from a network of surface flux stations. One ABL model calculatedH using a bulk similarity approach for wind and temperature with remotely sensed surface temperature as the lower boundary condition. With basin-scale estimates ofR n andG, LE was solved as a residual. The other ABL model applied atmospheric profiles from a series of soundings in the conservation equations of temperature and humidity in the mixed layer to computeH andLE directly. By combining theseH values withR n andG, calculation ofLE by residual also was performed. The ABL-derivedH values differed from the averages from the surface network by roughly 20 and 30% for the bulk similarity and conservation approaches, respectively. ForLE, these same differences were around 10 and 70%. The disparity was reduced to nearly 30% for the conservation approach whenLE was solved as a residual. Days with significant spatial variation in surface soil moisture and/or cloud cover were associated with most of the disagreement between the ABL-derived and surface-based values. This was particularly true for conservation estimates ofLE. The bulk similarity method appeared less sensitive non-ideal environmental conditions. This may in part be due to the use of remotely sensed information, which provided a lower boundary value of surface temperature and estimates ofR n andG over the study area, thereby allowing for residual calculations ofLE. Such information clearly has utility for assessing the surface energy and water balance at basin scale.
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Kustas, W.P., Hipps, L.E. & Humes, K.S. Calculation of basin-scale surface fluxes by combining remotely sensed data and atmospheric properties in a semiarid landscape. Boundary-Layer Meteorol 73, 105–124 (1995). https://doi.org/10.1007/BF00708932
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DOI: https://doi.org/10.1007/BF00708932