Improvements to a MODIS global terrestrial evapotranspiration algorithm

Mu, Qiaozhen; Zhao, Maosheng; Running, Steven W.

doi:10.1016/j.rse.2011.02.019

Cited by 2,243 publications

(2,164 citation statements)

References 105 publications

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“…The five global ET products included a MODIS ET product (MOD16) (Mu et al, 2011), a merged ET synthesis product (MUE13) (Mueller et al, 2013), a normalized differential vegetation index (NDVI)-based ET product (ZHA10) , a product based on a machine-learning algorithm (i.e., model tree ensemble) (JUN11) (Jung et al, 2011), and a product based on water balance approach (ZEN14) (Zeng et al, 2014). Their brief information was summarized in Table 2.…”

Section: The Published Global Et Productsmentioning

confidence: 99%

“…In recent years, several studies have quantified the spatial patterns of AET at regional (e.g., Li et al, 2014;Liu et al, 2013a;Wang et al, 2013) and global scales (e.g., Mu et al, 2011;Yan et al, 2012;Yuan et al, 2010) using process-based or remote sensing models. Although the spatial patterns described by different models generally agreed well with each other for a given region (Mueller et al, 2011;Liu et al, 2013a), large obvious uncertainties in AET values still remain.…”

Section: Introductionmentioning

confidence: 99%

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Spatial variation in annual actual evapotranspiration of terrestrial ecosystems in China: Results from eddy covariance measurements

Zheng

Wang

et al. 2016

J. Geogr. Sci.

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Abstract:Understanding the spatial variation in annual actual evapotranspiration (AET) and its influencing factors is crucial for a better understanding of hydrological processes and water resources management. By synthesizing ecosystem-level observations of eddy-covariance flux sites in China (a total of 61 sites), we constructed the most complete AET dataset in China up to now. Based on this dataset, we quantified the statistic characteristics of AET and water budgets (defined as the ratio of AET to annual mean precipitation (MAP), AET/MAP) of terrestrial ecosystems in China. Results showed that AET differed significantly among both different vegetation types and climate types in China, with overall mean AET of 534.7±232.8 mm yr -1 . AET/MAP also differed significantly among different climate types, but there were no distinct differences in AET/MAP values across vegetation types, with mean AET/MAP of 0.82±0.28 for non-irrigated ecosystems. We further investigated how the main climatic factors and vegetation attributes control the spatial variation in AET. Our findings revealed that the spatial variation of AET in China was closely correlated with the geographical patterns of climate and vegetation, in which the effects of total annual net radiation (R n ), MAP and mean annual air temperature (MAT) were dominant. Thus, we proposed an empirical equation to describe the spatial patterns of AET in China, which could explain about 84% of the spatial variation in AET of terrestrial ecosystems in China. Based on the constructed dataset, we also evaluated the uncertainties of five published global evapotranspiration products in simulating 1392 Journal of Geographical Sciences site-specific AET in China. Results showed that large biases in site-specific AET values existed for all five global evapotranspiration products, which indicated that it is necessary to involve more observation data of China in their parameterization or validation, while our AET dataset would provide a data source for it.

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Section: The Published Global Et Productsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial variation in annual actual evapotranspiration of terrestrial ecosystems in China: Results from eddy covariance measurements

Zheng

Wang

et al. 2016

J. Geogr. Sci.

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“…The MOD16 (Mu et al, 2011) global evapotranspiration (ET) datasets (Fig. 3) are regular 1-km 2 land surface ET datasets for the global vegetated land areas at 8-day, monthly and annual intervals.…”

Section: Evaluation Datasets 241 Modis Evapotranspiration Datamentioning

confidence: 99%

“…For addressing these questions, simulations of three LSMs (Mosaic, Noah, and VIC) obtained from the North American Land Data Assimilation Systemphase 2 (NLDAS-2) were used for assessing recharge estimates across the western US. We used MODIS ET (Mu et al, 2011) and baseflow index (BFI) based recharge (Wolock, 2003a) for the whole western US for comparison and evaluation purpose. Simulated recharge from the LSMs was compared with published recharge estimates from 10 aquifers in the region (Northern Plains, Central High Plains, Southern High Plains, San Pedro, Death Valley, Salt Lake Valley, Central Valley, Columbia Plateau, Spokane Valley, and Williston, Fig.…”

Section: Introductionmentioning

confidence: 99%

Comparing potential recharge estimates from three Land Surface Models across the western US

Niraula

Meixner

Ajami

et al. 2017

Journal of Hydrology

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a b s t r a c tGroundwater is a major source of water in the western US. However, there are limited recharge estimates in this region due to the complexity of recharge processes and the challenge of direct observations. Land surface Models (LSMs) could be a valuable tool for estimating current recharge and projecting changes due to future climate change. In this study, simulations of three LSMs (Noah, Mosaic and VIC) obtained from the North American Land Data Assimilation System (NLDAS-2) are used to estimate potential recharge in the western US. Modeled recharge was compared with published recharge estimates for several aquifers in the region. Annual recharge to precipitation ratios across the study basins varied from 0.01% to 15% for Mosaic, 3.2% to 42% for Noah, and 6.7% to 31.8% for VIC simulations. Mosaic consistently underestimates recharge across all basins. Noah captures recharge reasonably well in wetter basins, but overestimates it in drier basins. VIC slightly overestimates recharge in drier basins and slightly underestimates it for wetter basins. While the average annual recharge values vary among the models, the models were consistent in identifying high and low recharge areas in the region. Models agree in seasonality of recharge occurring dominantly during the spring across the region. Overall, our results highlight that LSMs have the potential to capture the spatial and temporal patterns as well as seasonality of recharge at large scales. Therefore, LSMs (specifically VIC and Noah) can be used as a tool for estimating future recharge in data limited regions.

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“…Other groups of ET algorithms are based on the vegetation index and its derivatives such as published by Nemani and Running (1989), Guerschman et al (2009), K. Zhang et al (2010, Mu et al (2011), andMiralles et al (2011). ETLook is a new ET model that directly computes the surface energy balance using surface soil moisture estimations for the top soil (to feed soil evaporation) and subsoil moisture for the root zone (to feed vegetation transpiration).…”

Section: Evapotranspirationmentioning

confidence: 99%

Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data

Karimi

Bastiaanssen

2015

Hydrol. Earth Syst. Sci.

124

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Abstract. The scarcity of water encourages scientists to develop new analytical tools to enhance water resource management. Water accounting and distributed hydrological models are examples of such tools. Water accounting needs accurate input data for adequate descriptions of water distribution and water depletion in river basins. Ground-based observatories are decreasing, and not generally accessible. Remote sensing data is a suitable alternative to measure the required input variables. This paper reviews the reliability of remote sensing algorithms to accurately determine the spatial distribution of actual evapotranspiration, rainfall and land use. For our validation we used only those papers that covered study periods of seasonal to annual cycles because the accumulated water balance is the primary concern. Review papers covering shorter periods only (days, weeks) were not included in our review. Our review shows that by using remote sensing, the absolute values of evapotranspiration can be estimated with an overall accuracy of 95 % (SD 5 %) and rainfall with an overall absolute accuracy of 82 % (SD 15 %). Land use can be identified with an overall accuracy of 85 % (SD 7 %). Hence, more scientific work is needed to improve the spatial mapping of rainfall and land use using multiple space-borne sensors. While not always perfect at all spatial and temporal scales, seasonally accumulated actual evapotranspiration maps can be used with confidence in water accounting and hydrological modeling.

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Improvements to a MODIS global terrestrial evapotranspiration algorithm

Cited by 2,243 publications

References 105 publications

Spatial variation in annual actual evapotranspiration of terrestrial ecosystems in China: Results from eddy covariance measurements

Spatial variation in annual actual evapotranspiration of terrestrial ecosystems in China: Results from eddy covariance measurements

Comparing potential recharge estimates from three Land Surface Models across the western US

Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data

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