Scaling of potential evapotranspiration with MODIS data reproduces flux observations and catchment water balance observations across Australia

Guerschman, Juan Pablo; Dijk, Albert I. J. M. van; Mattersdorf, Guillaume; Beringer, Jason; Hutley, Lindsay B.; Leuning, R.; Pipunic, Robert; Sherman, Bradford S.

doi:10.1016/j.jhydrol.2009.02.013

Cited by 238 publications

(177 citation statements)

References 51 publications

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“…6A, as determined by eddy covariance. Guerschman et al (2009), which includes three of the authors from Wood et al, report monthly ET from the same Wallaby Creek flux tower consistent with the monthly eddy covariance ET data shown in Wood et al Fig. 6A.…”

Section: Inconsistencies In the Wood Et Al Transpiration And Evapotrsupporting

confidence: 61%

See 1 more Smart Citation

Comment on Wood et al. 2008, 'Impacts of fire on forest age and runoff in mountain ash forests'

Benyon

Haydon

Vertessy

et al. 2010

Functional Plant Biol.

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Abstract. Wood et al. (2008; FPB 35) concluded their measurements of evapotranspiration (ET) in Eucalyptus regnans F.Muell. forest at Wallaby Creek, Victoria showed that ET differs only slightly between regrowth and oldgrowth, contrary to the findings of previous research. We assert that the conclusions of Wood et al. are invalid and argue that Wood et al. substantially overestimated annual transpiration and rainfall. Monthly whole-forest ET measured by Wood et al. using eddy covariance in a 296-year-old stand sum to~700 mm year -1 ; consistent with rainfall of 721 mm year -1 recorded nearby by the Bureau of Meteorology. However, the Wood et al. conclusions were based on 1077 mm annual transpiration at this site, which appears to be estimated from a few months of heat pulse velocity measurements. Transpiration alone cannot be 54% higher than whole-forest ET because the latter includes transpiration, rainfall interception and evaporation from the forest floor. We believe Wood et al. made errors in scaling heat pulse velocities to whole-stand annual transpiration. Their rainfall of 1175 mm year -1 averages 62% higher than at three Bureau of Meteorology and Melbourne Water sites nearby. The paper also contains inaccuracies in reporting of the literature and numerous other errors.

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Section: Inconsistencies In the Wood Et Al Transpiration And Evapotrsupporting

confidence: 61%

“…6A. Guerschman et al (2009) use these data to validate the wide applicability of a remote sensingbased ET model. Had the higher estimate of 1077 mm year -1 annual transpiration alone been used by Guerschman et al (2009), their model would have substantially underestimated ET at Wallaby Creek.…”

Section: Inconsistencies In the Wood Et Al Transpiration And Evapotrmentioning

confidence: 99%

Comment on Wood et al. 2008, 'Impacts of fire on forest age and runoff in mountain ash forests'

Benyon

Haydon

Vertessy

et al. 2010

Functional Plant Biol.

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“…The upper boundary is determined by latent heat flux equal to zero; the lower limit by potential evapotranspiration with a minimum bulk surface resistance. CMRSET (Commonwealth Scientific and Industrial Research Organisation (CSIRO), Canberra, Australia) [76] calculates actual ET from the Priestley and Taylor reference ET for water unlimited land surfaces [77] and a crop factor (K c ) based on an enhanced vegetation index (EVI). A global vegetation moisture index (GVMI) is used to account for non-optimal moisture conditions.…”

Section: Actual Evapotranspirationmentioning

confidence: 99%

Calibration of Spatially Distributed Hydrological Processes and Model Parameters in SWAT Using Remote Sensing Data and an Auto-Calibration Procedure: A Case Study in a Vietnamese River Basin

Bastiaanssen

Griensven

et al. 2018

Water

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Abstract:In this paper, evapotranspiration (ET) and leaf area index (LAI) were used to calibrate the SWAT model, whereas remotely sensed precipitation and other climatic parameters were used as forcing data for the 6300 km 2 Day Basin, a tributary of the Red River in Vietnam. The efficacy of the Sequential Uncertainty Fitting (SUFI-2) parameter sensitivity and optimization model was tested with area specific remote sensing input parameters for every Hydrological Response Units (HRU), rather than with measurements of river flow representing a large set of HRUs, i.e., a bulk calibration. Simulated monthly ET correlations with remote sensing estimates showed an R 2 = 0.71, Nash-Sutcliffe Efficiency NSE = 0.65, and Kling Gupta Efficiency KGE = 0.80 while monthly LAI showed correlations of R 2 = 0.59, NSE = 0.57 and KGE = 0.83 over a five-year validation period. Accumulated modelled ET over the 5-year calibration period amounted to 5713 mm compared to 6015 mm of remotely sensed ET, yielding a difference of 302 mm (5.3%). The monthly flow at two flow measurement stations were adequately estimated (R 2 = 0.78 and 0.55, NSE = 0.71 and 0.63, KGE = 0.59 and 0.75 for Phu Ly and Ninh Binh, respectively). This outcome demonstrates the capability of SWAT model to obtain spatial and accurate simulation of eco-hydrological processes, also when rivers are ungauged and the water withdrawal system is complex.

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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%

“…To be able to compare error levels from different studies only papers that report errors in terms of mean error were included in the review. Thus, some of the valuable papers on this topic that use RMSE (root mean square error) to describe errors without including mean error could not be included in the review (e.g., Batra et al, 2006;Cleugh et al, 2007;Guerschman et al, 2009;Venturini et al, 2008). The data sources consulted are summarized in Appendix A.…”

Section: Accuracy Of Spatial Evapotranspiration Datamentioning

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.

128

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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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Scaling of potential evapotranspiration with MODIS data reproduces flux observations and catchment water balance observations across Australia

Cited by 238 publications

References 51 publications

Comment on Wood et al. 2008, 'Impacts of fire on forest age and runoff in mountain ash forests'

Comment on Wood et al. 2008, 'Impacts of fire on forest age and runoff in mountain ash forests'

Calibration of Spatially Distributed Hydrological Processes and Model Parameters in SWAT Using Remote Sensing Data and an Auto-Calibration Procedure: A Case Study in a Vietnamese River Basin

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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