Next Article in Journal
Accuracy Verification of Airborne Large-Footprint Lidar based on Terrain Features
Next Article in Special Issue
Feasibility of Estimating Turbulent Heat Fluxes via Variational Assimilation of Reference-Level Air Temperature and Specific Humidity Observations
Previous Article in Journal
Using Training Samples Retrieved from a Topographic Map and Unsupervised Segmentation for the Classification of Airborne Laser Scanning Data
Previous Article in Special Issue
Responses of Water Use Efficiency to Drought in Southwest China
Open AccessArticle

A Bayesian Three-Cornered Hat (BTCH) Method: Improving the Terrestrial Evapotranspiration Estimation

State Key Laboratory of Earth Surface Processes and Resource Ecology, School of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
I. M. Systems Group at Environmental Modeling Center (EMC), National Centers for Environmental Prediction (NCEP), College Park, MD 20741, USA
Department of Civil and Environmental Engineering and Water Resources Research Center, University of Hawaii at Manoa, Honolulu, HI 96822, USA
National Hulunber Grassland Ecosystem Observation and Research Station, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(5), 878;
Received: 13 January 2020 / Revised: 23 February 2020 / Accepted: 6 March 2020 / Published: 9 March 2020
(This article belongs to the Special Issue Remote Sensing and Modeling of the Terrestrial Water Cycle)
In this study, a Bayesian-based three-cornered hat (BTCH) method is developed to improve the estimation of terrestrial evapotranspiration (ET) by integrating multisource ET products without using any a priori knowledge. Ten long-term (30 years) gridded ET datasets from statistical or empirical, remotely-sensed, and land surface models over contiguous United States (CONUS) are integrated by the BTCH and ensemble mean (EM) methods. ET observations from eddy covariance towers (ETEC) at AmeriFlux sites and ET values from the water balance method (ETWB) are used to evaluate the BTCH- and EM-integrated ET estimates. Results indicate that BTCH performs better than EM and all the individual parent products. Moreover, the trend of BTCH-integrated ET estimates, and their influential factors (e.g., air temperature, normalized differential vegetation index, and precipitation) from 1982 to 2011 are analyzed by the Mann–Kendall method. Finally, the 30-year (1982 to 2011) total water storage anomaly (TWSA) in the Mississippi River Basin (MRB) is retrieved based on the BTCH-integrated ET estimates. The TWSA retrievals in this study agree well with those from the Gravity Recovery and Climate Experiment (GRACE). View Full-Text
Keywords: evapotranspiration; Bayesian-based three-cornered hat method; total water storage anomaly evapotranspiration; Bayesian-based three-cornered hat method; total water storage anomaly
Show Figures

Graphical abstract

MDPI and ACS Style

He, X.; Xu, T.; Xia, Y.; Bateni, S.M.; Guo, Z.; Liu, S.; Mao, K.; Zhang, Y.; Feng, H.; Zhao, J. A Bayesian Three-Cornered Hat (BTCH) Method: Improving the Terrestrial Evapotranspiration Estimation. Remote Sens. 2020, 12, 878.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Search more from Scilit
Back to TopTop