The WACMOS-ET project – Part 1: Tower-scale evaluation of four remote sensing-based evapotranspiration algorithms

Michel, Dominik; Jiménez, Carlos; Miralles, Diego G.; Jung, Martin; Hirschi, Martin; Ershadi, Ali; Martens, Brecht; McCabe, Matthew F.; Fisher, Joshua B.; Mu, Qiaozhen; Wood, Eric F.; Fernàndez–Prieto, Diego

doi:10.5194/hessd-12-10739-2015

Cited by 56 publications

(112 citation statements)

References 55 publications

(62 reference statements)

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“…The poor performance of the models during the wet season in Elandsberg could be related to the weather conditions, particularly since it was raining during these days (Figure 4). The low correlations that were recorded in our study, notably for Elandsberg wet season, are comparable to other studies that have been done in dry ecosystems [30,64]. Vinukollu et al [32] reported low correlations in grasslands and woody savannas with all the models they tested in their study.…”

Section: Discussionsupporting

confidence: 77%

An Intercomparison of Satellite-Based Daily Evapotranspiration Estimates under Different Eco-Climatic Regions in South Africa

et al. 2017

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Knowledge of evapotranspiration (ET) is essential for enhancing our understanding of the hydrological cycle, as well as for managing water resources, particularly in semi-arid regions. Remote sensing offers a comprehensive means of monitoring this phenomenon at different spatial and temporal intervals. Currently, several satellite methods exist and are used to assess ET at various spatial and temporal resolutions with various degrees of accuracy and precision. This research investigated the performance of three satellite-based ET algorithms and two global products, namely land surface temperature/vegetation index (TsVI), Penman-Monteith (PM), and the Meteosat Second Generation ET (MET) and the Global Land-surface Evaporation: the Amsterdam Methodology (GLEAM) global products, in two eco-regions of South Africa. Daily ET derived from the eddy covariance system from Skukuza, a sub-tropical, savanna biome, and large aperture boundary layer scintillometer system in Elandsberg, a Mediterranean, fynbos biome, during the dry and wet seasons, were used to evaluate the models. Low coefficients of determination (R 2 ) of between 0 and 0.45 were recorded on both sites, during both seasons. Although PM performed best during periods of high ET at both sites, results show it was outperformed by other models during low ET times. TsVI and MET were similarly accurate in the dry season in Skukuza, as GLEAM was the most accurate in Elandsberg during the wet season. The conclusion is that none of the models performed well, as shown by low R 2 and high errors in all the models. In essence, our results conclude that further investigation of the PM model is possible to improve its estimation of low ET measurements.

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Section: Discussionsupporting

confidence: 77%

An Intercomparison of Satellite-Based Daily Evapotranspiration Estimates under Different Eco-Climatic Regions in South Africa

et al. 2017

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“…This study is unique from previous work partly because this is the most sites that have been used in such a comparison study evaluating remote sensing ET products by comparison with flux towers, compared to studies that have used a number of towers in the 45-85 range [9,11,16]. The unique collection of 5089 months of data from towers from many different settings, land cover types, and climate regimes across the country may have contributed to our overall R 2 being lower than some previous studies, such as showing R 2 = 0.64 for SSEBop [9], R 2 = 0.80 for the Global Land Evaporation Amsterdam Model (GLEAM) ET product [11], or a skill score of 0.53 for MOD16 [12].…”

Section: Discussionmentioning

confidence: 99%

Combining Remote Sensing and Water-Balance Evapotranspiration Estimates for the Conterminous United States

2017

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Evapotranspiration (ET) is a key component of the hydrologic cycle, accounting for~70% of precipitation in the conterminous U.S. (CONUS), but it has been a challenge to predict accurately across different spatio-temporal scales. The increasing availability of remotely sensed data has led to significant advances in the frequency and spatial resolution of ET estimates, derived from energy balance principles with variables such as temperature used to estimate surface latent heat flux. Although remote sensing methods excel at depicting spatial and temporal variability, estimation of ET independently of other water budget components can lead to inconsistency with other budget terms. Methods that rely on ground-based data better constrain long-term ET, but are unable to provide the same temporal resolution. Here we combine long-term ET estimates from a water-balance approach with the SSEBop (operational Simplified Surface Energy Balance) remote sensing-based ET product for 2000-2015. We test the new combined method, the original SSEBop product, and another remote sensing ET product (MOD16) against monthly measurements from 119 flux towers. The new product showed advantages especially in non-irrigated areas where the new method showed a coefficient of determination R 2 of 0.44, compared to 0.41 for SSEBop or 0.35 for MOD16. The resulting monthly data set will be a useful, unique contribution to ET estimation, due to its combination of remote sensing-based variability and ground-based long-term water balance constraints.Keywords: evapotranspiration; water resources; remote sensing; water balance; evaporation; transpiration Background and RationaleEvapotranspiration (ET) is the quantity of water that includes net water evaporation and plant transpiration. It plays a significant role in the hydrologic cycle, returning about 70% of precipitation across the conterminous United States (CONUS) to the atmosphere [1,2]. Because it is generally the second largest component of the water budget, following precipitation, researchers and water resource managers require accurate and reliable ET estimates to understand water availability and distribution for both short and long-term water resources management.The use of remote sensing-based methods of estimating ET has increased in recent years [3], and has proven useful in various applications such as agricultural water use monitoring and estimation [4], and hydrologic simulation [5]. These methods are particularly advantageous in their ability to produce estimates on timescales as short as weeks. The remote sensing approaches generally use surface energy balance arguments to partition the net incoming solar radiation energy into sensible heat flux, ground heat flux, and latent heat flux (energy equivalent of ET mass flux) [6][7][8][9][10]. Different algorithms applied to the same input remote sensing data sets can make predictions of the latent heat

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“…However, in studies estimating Ea, in which gc is adjusted so it reflects the actual rather than potential situation, the Penman-Monteith method has already been shown to perform worse than other, simpler methods, such as the Priestley and Taylor method (e.g. Michel et al, 2016;Ershadi et al, 2014). Its performance depends on the reliability of the wide range input data required, and 25 on the methods used to derive raH and gc (Seiller and Anctil, 2016;Singh and Xu, 1997;Dolman et al, 2014).…”

Section: Performance Of the Penman-monteith Methodsmentioning

confidence: 99%

“…For latent heat flux, we used the data corrected by energy balance closure (Michel et al, 2016). For Rn and the main fluxes (G, H, Ea), medium and poor gapfilled data were masked out according to the information provided by FLUXNET.…”

Section: Fluxnet2015 Databasementioning

confidence: 99%

Potential evaporation at eddy-covariance sites across the globe

Maes¹,

Gentine²,

Verhoest³

et al. 2018

Preprint

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Abstract. Potential evaporation (Ep) is a crucial variable for hydrological forecast and in drought monitoring systems. However, multiple interpretations of Ep exist, and these reflect a diverse range of methods to calculateEp. As such, a comparison of the performance of these methods against field observations in different global ecosystems is badly needed. In this study, we used eddy-covariance measurements from 107 sites of the FLUXNET2015 database, covering 11 different biomes, to parameterize and compare the main Ep methods and 10 uncover their relative performance. For each site, we extracted the days for which ecosystems are unstressed based on both an energy balance approach and on a soil water content approach. The evaporation measurements during these days were used as reference to validate the different methods to estimate Ep. Our results indicate that a simple radiation-driven method calibrated per biome consistently performed best, with a mean correlation of 0.93, an unbiased RMSE of 0.56 mm day -1, and a bias of -0.02 mm day -1 against in situ measurements of unstressed 15 evaporation. A Priestley and Taylor method, calibrated per biome, performed just slightly worse, yet substantially and consistently better than more complex Penman, Penman-Monteith-based or temperature-based approaches.We show that the poor performance of Penman-Monteith based approaches relates largely to the fact that the unstressed stomatal conductance was assumed constant. Further analysis showed that the biome-specific parameters required for the simple radiation-driven methods are relatively constant per biome. This makes this 20 simple radiation-driven method calibrated per biome a robust method that can be incorporated into models for improving our understanding of the impact of global warming on future global water use and demand, drought severity and ecosystem productivity.

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The WACMOS-ET project – Part 1: Tower-scale evaluation of four remote sensing-based evapotranspiration algorithms

Cited by 56 publications

References 55 publications

An Intercomparison of Satellite-Based Daily Evapotranspiration Estimates under Different Eco-Climatic Regions in South Africa

An Intercomparison of Satellite-Based Daily Evapotranspiration Estimates under Different Eco-Climatic Regions in South Africa

Combining Remote Sensing and Water-Balance Evapotranspiration Estimates for the Conterminous United States

Potential evaporation at eddy-covariance sites across the globe

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