Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.1016/j.agrformet.2016.03.019 |
Parameter estimation for a simple two-source evapotranspiration model using Bayesian inference and its application to remotely sensed estimations of latent heat flux at the regional scale | |
Song, Yi1; Jin, Long2; Zhu, Gaofeng3; Ma, Mingguo4 | |
通讯作者 | Song, Yi |
来源期刊 | AGRICULTURAL AND FOREST METEOROLOGY |
ISSN | 0168-1923 |
EISSN | 1873-2240 |
出版年 | 2016 |
卷号 | 230页码:20-32 |
英文摘要 | A simple two-source evapotranspiration (ET) model was applied to the Yingke and Daman irrigation districts of the Zhangye Oasis, which is located in the middle reaches of the Heihe River, China. The ET model was composed of two parts, including an evaporation (E) sub-model and a transpiration (T) sub-model. A separated parameter estimation scheme was conducted using Bayesian inference. First, an empirical multiplier was estimated for an E sub-model using observations that were collected after crop harvests. The empirical multiplier was then assigned to the most-likely value in the simple two-source ET model. Second, a global sensitivity analysis was performed to identify the key parameters that were responsible for most of the variability in the lambda ET results within the T sub-model. To avoid equifinality or over-parameterization, Bayesian inference was applied to estimate the key parameters that induced the most variability in the first set. A second set of Bayesian inference was then performed by fixing the most-likely values of these parameters, and the other parameters were defined one-by-one as Bayesian parameters. These parameters were estimated for seven sites. The coefficient of determination for the modeled lambda ET and the observed values exceeded 0.9. Next, a cluster analysis was conducted using the canopy height, leaf area index (LAI) and soil moisture content to classify the fields with the highest similarities and then to distribute the same parameter values to similar fields. Finally, lambda ET Was estimated using the most-likely values of the parameters at the regional scale. The root-mean-square error of the remotely sensed estimates was less than 20W m(-2), the mean absolute percent error did not exceed 4%, and the correlation coefficient was greater than 0.97. The validation was conducted for both the modeled lambda ET at the point scale and for the remotely sensed lambda ET at the satellite pixel scale. The results demonstrate that the separated parameter estimation scheme using Bayesian inference yields reasonable parameter values; using cluster analysis, the most-likely values of the parameters can be effectively applied to estimate remotely sensed lambda ET. (C) 2016 Elsevier B.V. All rights reserved. |
英文关键词 | ET Bayesian inference of parameters Regional scale |
类型 | Article |
语种 | 英语 |
国家 | Peoples R China |
收录类别 | SCI-E |
WOS记录号 | WOS:000389731800003 |
WOS关键词 | SONIC ANEMOMETER ; EDDY-COVARIANCE ; FOREST MODELS ; WATER ; BALANCE ; TEMPERATURE ; UNCERTAINTY ; CALIBRATION ; GRASSLAND ; ALGORITHM |
WOS类目 | Agronomy ; Forestry ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Agriculture ; Forestry ; Meteorology & Atmospheric Sciences |
来源机构 | 兰州大学 ; 中国科学院地球环境研究所 |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/191079 |
作者单位 | 1.Chinese Acad Sci, Inst Earth Environm, State Key Lab Loess & Quaternary Geol, 97 Yanxiang Rd, Xian 710061, Shaanxi Provinc, Peoples R China; 2.CCCC First Highway Consultants Co LTD, Key Lab Highway Construct Maintenance Technol Per, Minist Transport, Xian 710065, Peoples R China; 3.Lanzhou Univ, Ministry Educ, Key Lab Western Chinas Environm Syst, Lanzhou 730000, Peoples R China; 4.Southwest Univ, Sch Geog Sci, Chongqing 400715, Peoples R China |
推荐引用方式 GB/T 7714 | Song, Yi,Jin, Long,Zhu, Gaofeng,et al. Parameter estimation for a simple two-source evapotranspiration model using Bayesian inference and its application to remotely sensed estimations of latent heat flux at the regional scale[J]. 兰州大学, 中国科学院地球环境研究所,2016,230:20-32. |
APA | Song, Yi,Jin, Long,Zhu, Gaofeng,&Ma, Mingguo.(2016).Parameter estimation for a simple two-source evapotranspiration model using Bayesian inference and its application to remotely sensed estimations of latent heat flux at the regional scale.AGRICULTURAL AND FOREST METEOROLOGY,230,20-32. |
MLA | Song, Yi,et al."Parameter estimation for a simple two-source evapotranspiration model using Bayesian inference and its application to remotely sensed estimations of latent heat flux at the regional scale".AGRICULTURAL AND FOREST METEOROLOGY 230(2016):20-32. |
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