We present a new algorithm for mapping evapotranspiration (ET) that requires only local weather-station data including the ground heat flux and high resolution airborne thermal imagery. This ET mapping algorithm (ETMA) is based on the surface energy budget and partitions the available energy between the latent and sensible heat fluxes. Two parameters Tlatent and Tsensible are defined as the surface temperatures at which all of the turbulent heat flux is accounted for by the latent and sensible heat fluxes, respectively. These points are used to develop linear relationships between surface temperature and ET at specified times. Maps of ET at two times during the day are then used to model and integrate the diurnal pattern of ET using the Penman–Montieth and Jarvis–Stewart models of ET and surface resistance. The resulting maps of daily integrated ET have 1-m spatial resolution that is rarely available, yet important to the fields of hydrology, ecology, forestry, and agriculture. Our results comparing ET values to porometry-based local measurements within the meadows suggest that the mapped ETday values are accurate to within 10% of the potential ET rate or within 0.7 mm absolute error; however, under different conditions the error may be larger. The purpose of developing this algorithm was to investigate the hydroecology of restored and degraded meadows in the Sierra Nevada of northern California, USA. The pond-and-plug method of riparian restoration aims to raise the water table and re-establish native mesic vegetation that has been replaced by sagebrush and dryland species due to land-use practices over the past 150 years. By comparing the ET regime of two restored and two degraded meadows, we show that daily ET in the restored meadows (5–6.5 mm/day) was approximately twice that of the degraded ones (1.5–4 mm/day). The detailed images of ET show local impacts of land-use change and re-vegetation efforts. D 2005 Elsevier Inc. All rights reserved.
Keywords: Evapotranspiration; Hydroecology; Riparian restoration; Pond-and-plug method; High-resolution; Thermal imagery; Meadow