|SONG, L. - Beijing Normal University|
|Kustas, William - Bill|
|LIU, S. - Chinese Academy Of Sciences|
|NIETO, H. - Collaborator|
|XU, Z. - Beijing Normal University|
|LI, M. - University Of Electronic Science And Technology Of China|
|XU, T. - Beijing Normal University|
|AGAM, N. - Agricultural Research Organization Of Israel|
|Evett, Steven - Steve|
Submitted to: Journal of Hydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/20/2016
Publication Date: 7/10/2016
Citation: Song, L., Kustas, W.P., Liu, S., Colaizzi, P.D., Nieto, H., Xu, Z., Li, M., Xu, T., Agam, N., Tolk, J.A., Evett, S.R. 2016. Applications of a thermal-based two-source energy balance model using Priestley-Taylor approach for surface temperature partitioning under advective conditions. Journal of Hydrology. 540:574–587.
Interpretive Summary: Efficient use of water resources for agricultural production is becoming a major issue as demand for food and fiber continually increases with population growth while drought, particularly in arid and semiarid regions, is causing a major depletion in ground water and water reservoir resources since crops are largely irrigated. Remote sensing methods have been developed to quantify the water use or evapotranspiration (ET) using satellite observations, but these techniques are particularly challenging to apply in irrigated environments which typically have significant heat advection strongly affecting ET. Moreover, it is becoming more critical to estimate water used by plants (transpiration, T) for growth and productivity versus water evaporated from the soil (soil evaporation, E) which does not contribute to biomass production and crop yield. A remote sensing ET model called TSEB (two-source energy balance) which separates E and T contributions is modified to provide reliable E and T estimates over irrigated cotton in the U.S. and corn fields in China. The modified TSEB requires estimates of surface soil moisture which are currently not available at the field scale, but may be provided in the future by combining microwave and thermal-infrared remote sensing and modeling. Estimates of ET and T and E with the TSEB model will improve crop stress monitoring and yield predictions as well as assist in developing irrigation technologies that reduce soil evaporation, E, which does not contribute to crop production.
Technical Abstract: In this study ground measured soil and vegetation component temperatures and composite temperature from a high spatial resolution thermal camera and a network of thermal-IR sensors collected in an irrigated maize field and in an irrigated cotton field are used to assess and refine the component temperature partitioning approach in the Two-Source Energy Balance (TSEB) model. A refinement to TSEB using a non-iterative approach based on the application of the Priestley-Taylor formulation for surface temperature partitioning and estimating soil evaporation from soil moisture observations under advective conditions (TSEB-A) was developed. This modified TSEB formulation improved the agreement between observed and modeled soil and vegetation temperatures. In addition, the TSEB-A model output of evapotranspiration (ET) and the components evaporation (E), transpiration (T) when compared to ground observations using the stable isotopic method and eddy covariance (EC) technique from the HiWATER experiment and with microlysimeters and a large monolithic weighing lysimeter from the BEAREX08 experiment showed good agreement. Difference between the modeled and measured ET measurements were less than 10% and 20% on a daily basis for HiWATER and BEAREX08 data sets, respectively. The TSEB-A model was found to accurately reproduce the temporal dynamics of E, T and ET over a full growing season under the advective conditions existing for these irrigated crops located in arid/semi-arid climates. With satellite data this TSEB-A modeling framework could potentially be used as a tool for improving water use efficiency and conservation practices in water limited regions. However, TSEB-A requires soil moisture information which is not currently available routinely from satellite at the field scale.