Can the use of sUAS combined with satellite data effectively improve calibration of distributed hydrologic models? Previous work has focused on developing techniques to control variables such as evapotranspiration using satellite remote sensing. The critical component is the equilibrium surface temperature which is normally calibrated using thermal remote sensing data from MODIS (MODerate resolution Imaging Spectroradiometer) or AATSR (Advanced Along-Track Scanning Radiometer) which have a 1 km ground sample distance. This study seeks to improve thermal calibration techniques using much finer-resolution thermal measurements derived from a sUAS. The use of a sUAS will allow for the collection of high resolution imagery (< 1 cm – 1 m or more depending upon research goals) of landscape components, repeatedly and during desired time frames. Thermal data from a sUAS will provide much greater spatial and temporal resolution than satellite-based measurements, and will be obtained at a relatively low cost. This study seeks to determine the added benefit of improved spatial and temporal resolution of observations, evaluated through the existing model calibration framework of a sub-daily, sub-kilometer hydrologic model with complex terrain and vegetation, typical of many mountain headwaters systems experiencing change in the West.
