| Literature DB >> 32355404 |
Héctor Nieto1, William P Kustas2, Alfonso Torres-Rúa3, Joseph G Alfieri2, Feng Gao2, Martha C Anderson2, W Alex White2, Lisheng Song4, María Del Mar Alsina5, John H Prueger6, Mac McKee7, Manal Elarab8, Lynn G McKee2.
Abstract
The thermal-based Two-Source Energy Balance (TSEB) model partitions the evapotranspiration (ET) and energy fluxes from vegetation and soil components providing the capability for estimating soil evaporation (E) and canopy transpiration (T). However, it is crucial for ET partitioning to retrieve reliable estimates of canopy and soil temperatures and net radiation, as the latter determines the available energy for water and heat exchange from soil and canopy sources. These two factors become especially relevant in row crops with wide spacing and strongly clumped vegetation such as vineyards and orchards. To better understand these effects, very high spatial resolution remote-sensing data from an unmanned aerial vehicle were collected over vineyards in California, as part of the Grape Remote sensing and Atmospheric Profile and Evapotranspiration eXperiment and used in four different TSEB approaches to estimate the component soil and canopy temperatures, and ET partitioning between soil and canopy. Two approaches rely on the use of composite T rad, and assume initially that the canopy transpires at the Priestley-Taylor potential rate. The other two algorithms are based on the contextual relationship between optical and thermal imagery partition T rad into soil and canopy component temperatures, which are then used to drive the TSEB without requiring a priori assumptions regarding initial canopy transpiration rate. The results showed that a simple contextual algorithm based on the inverse relationship of a vegetation index and T rad to derive soil and canopy temperatures yielded the closest agreement with flux tower measurements. The utility in very high-resolution remote-sensing data for estimating ET and E and T partitioning at the canopy level is also discussed.Entities:
Year: 2019 PMID: 32355404 PMCID: PMC7192002 DOI: 10.1007/s00271-018-0585-9
Source DB: PubMed Journal: Irrig Sci ISSN: 0342-7188 Impact factor: 2.940