Global estimates of evapotranspiration for climate studies using multi-sensor remote sensing data: Evaluation of three process-based approaches

Vinukollu, R. K.; Wood, Eric F.; Ferguson, Craig R.; Fisher, Joshua B.

doi:10.1016/j.rse.2010.11.006

Cited by 406 publications

(328 citation statements)

References 126 publications

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“…By contrast, the SEBAL model estimated ET is only 4% higher than ET from eddy covariance. Although the overestimation of ET by 3T model is higher than that of SEBAL model, it in no way suggests that SEBAL outperforms 3T owing to the fact that eddy covariance generally underestimates ET by 10-30% (Twine et al, 2000;Vinukollu et al, 2011).…”

Section: General Reliability Of the 3t Modelmentioning

confidence: 85%

Comparison of ET estimations by the three-temperature model, SEBAL model and eddy covariance observations

Zhou

Yang

et al. 2014

Journal of Hydrology

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Keywords:3T model SEBAL model Eddy covariance Evapotranspiration Taklamakan desert oasis s u m m a r yThe three-temperature (3T) model is a simple model which estimates plant transpiration from only temperature data. In-situ field experimental results have shown that 3T is a reliable evapotranspiration (ET) estimation model. Despite encouraging results from recent efforts extending the 3T model to remote sensing applications, literature shows limited comparisons of the 3T model with other remote sensing driven ET models. This research used ET obtained from eddy covariance to evaluate the 3T model and in turn compared the model-simulated ET with that of the more traditional SEBAL (Surface Energy Balance Algorithm for Land) model. A field experiment was conducted in the cotton fields of Taklamakan desert oasis in Xinjiang, Northwest China. Radiation and surface temperature were obtained from hyperspectral and thermal infrared images for clear days in 2013. The images covered the time period of 0900-1800 h at four different phenological stages of cotton. Meteorological data were automatically recorded in a station located at the center of the cotton field. Results showed that the 3T model accurately captured daily and seasonal variations in ET. As low dry soil surface temperatures induced significant errors in the 3T model, it was unsuitable for estimating ET in the early morning and late afternoon periods. The modelsimulated ET was relatively more accurate for squaring, bolling and boll-opening stages than for seedling stage of cotton during when ET was generally low. Wind speed was apparently not a limiting factor of ET in the 3T model. This was attributed to the fact that surface temperature, a vital input of the model, indirectly accounted for the effect of wind speed on ET. Although the 3T model slightly overestimated ET compared with SEBAL and eddy covariance, it was generally reliable for estimating daytime ET during 0900-1600 h.

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Section: General Reliability Of the 3t Modelmentioning

confidence: 85%

Comparison of ET estimations by the three-temperature model, SEBAL model and eddy covariance observations

Zhou

Yang

et al. 2014

Journal of Hydrology

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“…Recent advancements in satellite-based sensors offer great potential to monitor SM over large scales for continental water resources assessment, particularly in areas where ground observation networks are sparse (Mohanty et al, 2017). Conventionally, satellite observations have been used in global water balance studies to provide information on the water cycle components, such as precipitation, evapotranspiration, soil moisture, water storage and runoff (Running et al, 2004;Kiehl and Trenberth, 10 1997;Vinukollu et al, 2011;Trenberth et al, 2007). However, sparse data coverage in satellite observations limits their ability to provide spatially and temporally consistent time series of water balance estimates.…”

Section: Introductionmentioning

confidence: 99%

“…CC BY 4.0 License. these important advancements, the current spatial resolution of these global scale studies is too coarse to provide locally relevant information (Wood et al, 2011, Bierkens et al, 2015. For example, predicting water cycle processes for scientific and applied assessment of the terrestrial water cycle requires a high-resolution modeling framework on the order of 10 0 km.…”

Section: Introductionmentioning

confidence: 99%

Improving soil moisture and runoff simulations over Europe using a high-resolution data-assimilation modeling framework

Naz

Kurtz

Montzka

et al. 2018

Preprint

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Abstract. Accurate and reliable hydrologic simulations are important for many applications such as water resources management, future water availability projections and predictions of extreme events. However, the accuracy of water balance estimates is limited by the lack of observations at large scales and the uncertainties of model simulations due to errors in model structure and inputs (e.g. hydrologic parameters and atmospheric forcings). In this study, we assimilated 15 ESA CCI soil moisture (SM) information to improve the estimation of continental-scale soil moisture and runoff. The seasons when cross-validated with independent CCI-SM observations. On average, the mean bias in soil moisture was reduced from 0.1 mm 3 /mm 3 in open-loop simulations to 0.004 mm 3 /mm 3 with SM assimilation. The assimilation experiment also shows overall improvements in runoff, particularly during peak runoff. The results demonstrate the potential of assimilating satellite soil moisture observations to improve high-resolution soil moisture and runoff simulations at the continental scale, which is useful for water resources assessment and monitoring. 25

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“…This approach leads to large and 15 usually unquantifiable uncertainties. As a result, gridded LSM evaluation products show considerable differences (Ershadi et al, 2014;Jiménez et al, 2011;McCabe et al, 2016 ;Michel et al, 2016;Vinukollu et al, 2011). If an accurate description of these uncertainties was available, then it might be possible to evaluate gridded LSM simulations in certain circumstances, but until now very few studies quantify LSM uncertainties at regional or global scales (Badgley et al, 2015;Loew et al, 2016;Zhang et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Derived Optimal Linear Combination Evapotranspiration (DOLCE): a global gridded synthesis ET estimate

Abramowitz¹,

Hobeichi²

2017

Preprint

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Abstract. Accurate global gridded estimates of evapotranspiration (ET) are key to understanding water and energy budgets, as well as being required for model evaluation. Several gridded ET products have already been developed which differ in their data requirements, the approaches used to derive them and their estimates, yet it is not clear which provides the most 10 reliable estimates. This paper presents a new global ET dataset and associated uncertainty with monthly temporal resolution for 2000-2009. Six existing gridded ET products are combined using a weighting approach trained by observational datasets from 159 FLUXNET sites. The weighting method is based on a technique that provides an analytically optimal linear combination of ET products compared to site data, and accounts for both the performance differences and error covariance between the participating ET products. We examine the performance of the weighting approach in several in-sample and out-15 of-sample tests that confirm that point-based estimates of flux towers provide information at the grid scale of these products.We also provide evidence that the weighted product performs better than its six constituent ET product members in three common metrics. Uncertainty in the ET estimate is derived by rescaling the spread of participating ET products so that their spread reflects the ability of the weighted mean estimate to match flux tower data. While issues in observational data and any common biases in participating ET datasets are limitations to the success of this approach, future datasets can easily be 20 incorporated and enhance the derived product.

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Global estimates of evapotranspiration for climate studies using multi-sensor remote sensing data: Evaluation of three process-based approaches

Cited by 406 publications

References 126 publications

Comparison of ET estimations by the three-temperature model, SEBAL model and eddy covariance observations

Comparison of ET estimations by the three-temperature model, SEBAL model and eddy covariance observations

Improving soil moisture and runoff simulations over Europe using a high-resolution data-assimilation modeling framework

Derived Optimal Linear Combination Evapotranspiration (DOLCE): a global gridded synthesis ET estimate

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