Evaluation of Landsat-Based METRIC Modeling to Provide High-Spatial Resolution Evapotranspiration Estimates for Amazonian Forests

Numata, Izaya; Khand, Kul; Kjaersgaard, Jeppe; Cochrane, Mark A.; Silva, Sonaira S.

doi:10.3390/rs9010046

Cited by 47 publications

(41 citation statements)

References 46 publications

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“…We must also consider that during the harvest season there may be spectral mixing of harvested areas and sugarcane crop within the MODIS pixel ( Figure S5 on the Supplementary Material). Moreover, for taller vegetation (as woody savanna), deviations in estimated albedo may occur in situations where the sun is not at its zenith, which causes the mixing of sunlit and shaded areas in the same pixel, particularly in the winter months, when the solar zenith angle is higher [59].…”

Section: Discussionmentioning

confidence: 99%

“…An adjustment factor of 1.05 is typically used to reflect the actual evaporation amount at this anchor point. For a hot pixel, a non-vegetated agricultural area is selected, and a bare soil evaporation model, such as that presented by Reference [22], can be used to establish the adjustment factor which accounts for the residual soil evaporation from antecedent rainfall [59].…”

Section: Metric Modelmentioning

confidence: 99%

“…A digital elevation model (DEM) was obtained from SRTM (Shuttle Radar Topography Mission) with spatial resolution of 90 m (resampled to MODIS spatial resolution using bilinear interpolation) and utilized to account for changes in surface temperature caused by elevation differences [58,59].…”

Section: Satellite Datamentioning

confidence: 99%

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Improved Albedo Estimates Implemented in the METRIC Model for Modeling Energy Balance Fluxes and Evapotranspiration over Agricultural and Natural Areas in the Brazilian Cerrado

et al. 2018

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Abstract:In this study we assessed METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model performance to estimate energy balance fluxes and evapotranspiration (ET) in two heterogeneous landscapes in the Brazilian Cerrado, including fluxes and ET in both agricultural and natural vegetation. The estimates were evaluated by comparing them to flux tower data collected over sugarcane (USR site), woody savanna (PDG site) and stricto-sensu savanna (RECOR site) areas. The selection of the study years (2005)(2006)(2007) for USR/PDG sites and 2011-2015 for RECOR site) was based on the availability of meteorological data (to be used as inputs in METRIC) and of flux tower data for energy balance fluxes and ET comparisons. The broadband albedo submodel was adjusted in order to improve Net Radiation estimates. For this adjustment, we applied at-surface solar radiation simulations obtained from the SMARTS2 model under different conditions of land elevation, precipitable water content and solar angles. We also tested the equivalence between the measured crop coefficient (Kc _ec ) and the reference evapotranspiration fraction (ETrF or F), seeking to extrapolate from instantaneous to daily values of actual evapotranspiration (ETa). Surface albedo was underestimated by 10% at the USR site (showing a better performance for full crop coverage), by 15% at the PDG site (following the woody savanna dynamics pattern through dry and wet seasons) and was overestimated by 21% at the RECOR site. METRIC was effective in simulating the spatial and temporal variability of energy balance fluxes and ET over agricultural and natural vegetation in the Brazilian Cerrado, with errors within those reported in the literature. Net radiation (Rn) presented consistent results (coefficient of determination (R 2 ) > 0.94) but it was overestimated by 8% and 9% in sugarcane and woody savanna, respectively. METRIC-derived ET estimates showed an agreement with ground data at USR and PDG sites (R 2 > 0.88, root mean square error (RMSE) up to 0.87 mm day −1 ), but at the RECOR site, ET was overestimated by 14% (R 2 = 0.96, mean absolute error (MAE) = 0.62 mm.day −1 and RMSE = 0.75 mm day −1 ). Surface energy balance fluxes and ET were marked by seasonality, with direct dependence on available energy, rainfall distribution, soil moisture and other parameters like albedo and NDVI.

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Section: Discussionmentioning

confidence: 99%

Section: Metric Modelmentioning

confidence: 99%

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Improved Albedo Estimates Implemented in the METRIC Model for Modeling Energy Balance Fluxes and Evapotranspiration over Agricultural and Natural Areas in the Brazilian Cerrado

et al. 2018

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“…This will automatically result in disagreement between STIC1.2 and observed ET. Nevertheless, the performance of STIC1.2 in forest ecosystems is encouraging, given the uncertainties associated with more complex SEB models that use MOST to parameterize the turbulent mixing in tall canopies (Finnigan et al, 2009;Garratt, 1978;Harman and Finnigan, 2007) that could induce substantial biases in estimated fluxes (Wagle et al, 2017;Numata et al, 2017;Bhattarai et 25 al., 2016) Performance intercomparison of STIC1.2 with SEBS and MOD16 indicated overall low statistical errors for STIC1.2, and better agreement than SEBS and MOD16 with observed ET values. The principal differences between STIC1.2 and SEBS (as evident from Fig.…”

Section: Discussionmentioning

confidence: 99%

Regional evapotranspiration from image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous United States

Bhattarai¹,

Mallick²,

Brunsell³

et al. 2017

Preprint

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Abstract. Recent studies have highlighted the need for improved characterizations of aerodynamic conductance and temperature (gA and T0) in thermal remote sensing-based surface energy balance (SEB) models to reduce uncertainties in regional-scale evapotranspiration (ET) mapping. By integrating radiometric surface temperature (TR) into the Penman-15Monteith (PM) equation and finding analytical solutions of gA and T0, this need was recently addressed by the Surface Temperature Initiated Closure (STIC) model. However, previous implementations of STIC were confined to the ecosystemscale using flux tower observations of infrared temperature. This study demonstrates the first regional-scale implementation of the most recent version of the STIC model (STIC1.2) that physically integrates Moderate Resolution Imaging Spectroradiometer (MODIS)-derived TR and ancillary land surface variables in conjunction with NLDAS (North American 20Land Data Assimilation System) atmospheric variables into a combined structure of the PM and Shuttleworth-Wallace framework for estimating ET at 1 km × 1 km spatial resolution. Evaluation of STIC1.2 at thirteen core AmeriFlux sites covering a broad spectrum of climates and biomes across an aridity gradient in the conterminous US suggests that STIC1.2 can provide spatially explicit ET maps with reliable accuracies from dry to wet extremes. When observed ET from one wet, one dry, and one normal precipitation year from all sites were combined, STIC1.2 explained 66 % of the variability in observed 8-day 25 cumulative ET with a root mean square error (RMSE) of 7.4 mm/8-day, mean absolute error (MAE) of 5 mm/8-day, and percent bias (PBIAS) of -4 %. These error statistics show higher accuracies than a widely-used SEB-based Surface Energy Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-535 Manuscript under review for journal Hydrol. Earth Syst. Sci. Discussion started: 11 September 2017 c Author(s) 2017. CC BY 4.0 License. 2Balance System (SEBS) and PM-based MOD16 ET, which were found to overestimate (PBIAS = 28 %) and underestimate ET (PBIAS = -26 %), respectively. The performance of STIC1.2 was better in forest and grassland ecosystems as compared to cropland (20 % underestimation) and woody savanna (40 % overestimation). Model inter-comparison suggested that ET differences between the models are robustly correlated with gA and associated roughness length estimation uncertainties which are intrinsically connected to TR uncertainties, vapour pressure deficit (DA), and vegetation cover. A consistent performance 5 of STIC1.2 in a broad range of hydrological and biome categories as well as the capacity to capture spatio-temporal ET signatures across an aridity gradient points to its potential for near real time ET mapping from regional to continental scales.

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“…METRIC is a Landsat imagery-based processing model designed to produce high resolution (30 m) ET maps for focused regions less than a few hundred kilometers across [10] and has been widely used over multiple land use types [11,[31][32][33][34]. Unlike other RSEB models, METRIC has the advantage of incorporating reference ET from measured weather data for determining the ET conditions at the cold and hot pixel calibration points and for extrapolation of instantaneous to 24-h ET to account for regional advection effects with expected higher accuracy [10].…”

Section: Metric Evapotranspirationmentioning

confidence: 99%

Estimating Impacts of Agricultural Subsurface Drainage on Evapotranspiration Using the Landsat Imagery-Based METRIC Model

et al. 2017

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Agricultural subsurface drainage changes the field hydrology and potentially the amount of water available to the crop by altering the flow path and the rate and timing of water removal. Evapotranspiration (ET) is normally among the largest components of the field water budget, and the changes in ET from the introduction of subsurface drainage are likely to have a greater influence on the overall water yield (surface runoff plus subsurface drainage) from subsurface drained (TD) fields compared to fields without subsurface drainage (UD). To test this hypothesis, we examined the impact of subsurface drainage on ET at two sites located in the Upper Midwest (North Dakota-Site 1 and South Dakota-Site 2) using the Landsat imagery-based METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model. Site 1 was planted with corn (Zea mays L.) and soybean (Glycine max L.) during the 2009 and 2010 growing seasons, respectively. Site 2 was planted with corn for the 2013 growing season. During the corn growing seasons (2009 and 2013), differences between the total ET from TD and UD fields were less than 5 mm. For the soybean year (2010), ET from the UD field was 10% (53 mm) greater than that from the TD field. During the peak ET period from June to September for all study years, ET differences from TD and UD fields were within 15 mm (<3%). Overall, differences between daily ET from TD and UD fields were not statistically significant (p > 0.05) and showed no consistent relationship.

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Evaluation of Landsat-Based METRIC Modeling to Provide High-Spatial Resolution Evapotranspiration Estimates for Amazonian Forests

Cited by 47 publications

References 46 publications

Improved Albedo Estimates Implemented in the METRIC Model for Modeling Energy Balance Fluxes and Evapotranspiration over Agricultural and Natural Areas in the Brazilian Cerrado

Improved Albedo Estimates Implemented in the METRIC Model for Modeling Energy Balance Fluxes and Evapotranspiration over Agricultural and Natural Areas in the Brazilian Cerrado

Regional evapotranspiration from image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous United States

Estimating Impacts of Agricultural Subsurface Drainage on Evapotranspiration Using the Landsat Imagery-Based METRIC Model

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