Multiple sources of uncertainties in satellite retrieval of terrestrial actual evapotranspiration

被引:27
作者
Cao, Mingzhu [1 ,2 ]
Wang, Weiguang [1 ,2 ,3 ]
Xing, Wanqiu [1 ]
Wei, Jia [1 ]
Chen, Xintao [1 ]
Li, Jinxing [4 ]
Shao, Quanxi [5 ]
机构
[1] Hohai Univ, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing 210098, Peoples R China
[2] Hohai Univ, Key Lab Water Big Data Technol, Minist Water Resources, Nanjing 210098, Peoples R China
[3] Hohai Univ, Joint Int Res Lab Global Change & Water Cycle, Nanjing 210098, Peoples R China
[4] Zhejiang Inst Hydraul & Estuary, Water Resources & Water Environm Inst, Hangzhou 310020, Peoples R China
[5] CSIRO Data 61, Australian Resources Res Ctr, 26 Dick Perry Ave, Kensington, WA 6151, Australia
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Evapotranspiration; Remote sensing; Uncertainty; Penman-Monteith; Priestly-Taylor; Eddy covariance; PRIESTLEY-TAYLOR EQUATION; ENERGY-BALANCE CLOSURE; PENMAN-MONTEITH MODEL; LATENT-HEAT FLUX; SURFACE-TEMPERATURE; EVAPORATIVE FRACTION; SENSITIVITY-ANALYSIS; ARIDITY GRADIENT; SOIL-MOISTURE; WATER-BALANCE;
D O I
10.1016/j.jhydrol.2021.126642
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Since evapotranspiration (ET) is the intrinsic link between global energy and water cycle, remote sensing-based models have been developed for regional and global scale ET on heterogeneous land surface over the past four decades. In view of the significantly different physical mechanisms and mathematical expressions among remote sensing ET models as well as data availability and quality control process among the model input products, it is necessary to investigate the uncertainties of the multiple sources in actual ET estimation. Here, three remote sensing ET models, including the PT-DTsR model, the PM-mod model and the PML model, were simultaneously driven by three meteorological reanalysis products, resulting in nine calculation schemes to analyze the combined effect of the models and the input datasets. The Sobol' sensitivity method was also adopted for identifying the influential model parameters and in turn understanding the model process. The results indicated that estimates from nine calculation schemes showed great differences in the magnitude and temporal variation, explaining 20-50% of ET variability over all sites. Additionally, schemes compared with both uncorrected and corrected energy balance observations, as well as schemes using meteorological variables from three reanalysis products and Eddy Covariance tower observations, verified that the uncertainties in latent heat flux data observations caused by the energy budget mis-closure problem and spatial scale mismatch have propagated into the ET estimation. Our study is a beneficial reference for the uncertainties in remote sensing-based methods, and thus can provide guidance for the future development of ET models.
引用
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页数:16
相关论文
共 106 条
[1]   Water, Energy, and Carbon with Artificial Neural Networks (WECANN): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence [J].
Alemohammad, Seyed Hamed ;
Fang, Bin ;
Konings, Alexandra G. ;
Aires, Filipe ;
Green, Julia K. ;
Kolassa, Jana ;
Miralles, Diego ;
Prigent, Catherine ;
Gentine, Pierre .
BIOGEOSCIENCES, 2017, 14 (18) :4101-4124
[2]   A recommendation on standardized surface resistance for hourly calculation of reference ETO by the FAO56 Penman-Monteith method [J].
Allen, RG ;
Pruitt, WO ;
Wright, JL ;
Howell, TA ;
Ventura, F ;
Snyder, R ;
Itenfisu, D ;
Steduto, P ;
Berengena, J ;
Yrisarry, JB ;
Smith, M ;
Pereira, LS ;
Raes, D ;
Perrier, A ;
Alves, I ;
Walter, I ;
Elliott, R .
AGRICULTURAL WATER MANAGEMENT, 2006, 81 (1-2) :1-22
[3]   A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales [J].
Anderson, M. C. ;
Norman, J. M. ;
Kustas, W. P. ;
Houborg, R. ;
Starks, P. J. ;
Agam, N. .
REMOTE SENSING OF ENVIRONMENT, 2008, 112 (12) :4227-4241
[4]   Upscaling and downscaling - A regional view of the soil-plant-atmosphere continuum [J].
Anderson, MC ;
Kustas, WP ;
Norman, JM .
AGRONOMY JOURNAL, 2003, 95 (06) :1408-1423
[5]  
[Anonymous], 2007, ENERGY BALANCE BOWEN
[6]   Isolating the roles of different forcing agents in global stratospheric temperature changes using model integrations with incrementally added single forcings [J].
Aquila, V. ;
Swartz, W. H. ;
Waugh, D. W. ;
Colarco, P. R. ;
Pawson, S. ;
Polvani, L. M. ;
Stolarski, R. S. .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2016, 121 (13) :8067-8082
[7]   Using precipitation, vertical root distribution, and satellite-retrieved vegetation information to parameterize water stress in a Penman-Monteith approach to evapotranspiration modeling under Mediterranean climate [J].
Bai, Yun ;
Zhang, Jiahua ;
Zhang, Sha ;
Koju, Upama Ashish ;
Yao, Fengmei ;
Igbawua, Tertsea .
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 2017, 9 (01) :168-192
[8]  
Baldocchi D, 2001, B AM METEOROL SOC, V82, P2415, DOI 10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO
[9]  
2
[10]   Monitoring the moisture balance of a boreal aspen forest using a deep groundwater piezometer [J].
Barr, AG ;
van der Kamp, G ;
Schmidt, R ;
Black, TA .
AGRICULTURAL AND FOREST METEOROLOGY, 2000, 102 (01) :13-24