Actual daily evapotranspiration estimated from MERIS and AATSR data over the Chinese Loess Plateau

Liu, R.; Wen, Jun; Wang, X.; Wang, L.; Tian, Hui; Zhang, T. T.; Shi, Xiaomei; Zhang, Junhui; Lv, Sh. N.

doi:10.5194/hess-14-47-2010

Cited by 17 publications

(4 citation statements)

References 35 publications

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“…Regarding the FAO-56 method, the SAFER showed an absolute mean error (MAE) of 0.40 mm d -1 . The relative error in the estimation of ET SAFER using spectral images is greater when the vegetation cover is incomplete (LIU et al, 2010), as observed in the early stages of the crop cycle, up to 30 days after planting, when the SAFER algorithm method obtained smaller evapotranspiration values when compared to the standard method, reaching a maximum value of 0.99 mm d -1 .…”

Section: Discussionmentioning

confidence: 89%

Evapotranspiration for irrigated agriculture using orbital satellites

Althoff¹,

Alvino²,

Filgueiras³

et al. 2019

Biosci. J.

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Acknowledging the importance of evapotranspiration as a mediating factor for efficient irrigation management and water balance, the objective of study is to compare the Simple Algorithm for Evapotranspiration Retrieving (SAFER) to the standard method proposed by FAO-56 for real evapotranspiration, as well as prove its value as an implement in irrigation management for the Brazilian Savanna. Data used refers to 2015's harvest of seven center pivots, located in the municipality of São Desidério in western Bahia. For the SAFER algorithm, the images used were acquired by the Landsat-8 satellite during the entire maize crop cycle. The SAFER algorithm estimation demonstrates the spatial and temporal distribution of the evapotranspiration. A maximum evapotranspiration of 5.38 mm d-1 was observed during the crop's reproductive stage. In relation to the standard method, SAFER showed a mean absolute error of 0.40 mm. Thus, concluding that the algorithm can be used to estimate the actual evapotranspiration crop as an alternative to the standard method proposed by FAO-56 for water resources management.

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Section: Discussionmentioning

confidence: 89%

Evapotranspiration for irrigated agriculture using orbital satellites

Althoff¹,

Alvino²,

Filgueiras³

et al. 2019

Biosci. J.

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“…To validate the product, we compiled a data set from 11 flux stations in China with land cover types including bare soil, alpine meadow, cropland, orchard, grassland, and wetlands. The elevations of these stations range from 5 to 4800 m. The observational data set includes data from Maqu (MQ) (Chen et al, 2013b;Wang et al, 2013), Wenjiang (WJ) (Zhang et al, 2012), Bijie (BJ) (Ma et al, 2006), Miyun (MY) (S. M. , Daxing (DX) (S. M. , Guantao (GT) (Liu et al, 2011;S. M. Liu et al, 2013), Yucheng (YC) (Flerchinger et al, 2009), Dongtan (DT) (Zhao et al, 2009), SC (Semi-Arid Climate and Environment Observatory of Lanzhou University) (Huang et al, 2008;Wang et al, 2010;Guan et al, 2009), and Weishan (WS) stations (Lei and Yang, 2010a, b).…”

Section: Validation Datamentioning

confidence: 99%

Development of a 10 year (2001–2010) 0.1° dataset of land-surface energy balance for mainland China

Chen¹,

Su²,

Ma³

et al. 2014

Preprint

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Abstract. In the absence of high resolution estimates of the components of surface energy balance for China, we developed an algorithm based on the surface energy balance system (SEBS) to generate a dataset of land-surface energy and water fluxes on a monthly time scale from 2001 to 2010 at a 0.1° × 0.1° spatial resolution by using multi-satellite and meteorological forcing data. A remote-sensing-based method was developed to estimate canopy height, which was used to calculate roughness length and flux dynamics. The land-surface flux dataset was validated against "ground-truth" observations from 11 flux tower stations in China. The estimated fluxes correlate well with the stations' measurements for different vegetation types and climatic conditions (average bias = 15.3 W m−2, RMSE = 26.4 W m−2). The quality of the data product was also assessed against the GLDAS dataset. The results show that our method is efficient for producing a high-resolution dataset of surface energy flux for the Chinese landmass from satellite data. The validation results demonstrate that more accurate downward long-wave radiation datasets are needed to be able to accurately estimate turbulent fluxes and evapotranspiration when using the surface energy balance model. Trend analysis of land-surface radiation and energy exchange fluxes revealed that the Tibetan Plateau has undergone relatively stronger climatic change than other parts of China during the last 10 years. The capability of the dataset to provide spatial and temporal information on water-cycle and land–atmosphere interactions for the Chinese landmass is examined. The product is free to download for studies of the water cycle and environmental change in China.

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“…Tropical deforestation, for example, results in the land experiencing a reduction in evapotranspiration (ET) -this reduction in cooling potential increases the surface temperature. Indeed, LST can be exploited to estimate ET by directly constraining the sensible heat flux from the land surface, with latent heat determined as a residual to the overall energy balance [9,10] -with the latter study being an example of utilisation of LST from AATSR. Another specific example of the exploitation of LST from AATSR includes the assimilation of LST into the UK's most important land surface scheme, thus enabling an improved representation of key surface to atmosphere fluxes of heat and moisture [11,12].…”

Section: Exploitation Of Lst Datamentioning

confidence: 99%