Assessment of a Remote Sensing Energy Balance Methodology (SEBAL) Using Different Interpolation Methods to Determine Evapotranspiration in a Citrus Orchard

Jiménez-Bello, M.A.; Castel, J.R.; Testi, Luca; Intrigliolo, Diego S.

doi:10.1109/jstars.2015.2418817

Cited by 15 publications

(11 citation statements)

References 54 publications

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“…It has since been validated several times, with the following reported errors: daily RMSE of 0.51 mm day −1 [67] and 0.38 mm day −1 [68], seasonal error of 4.3% [69] and mean deviation of 0.06 (daily) and 0.19 (16-daily) [70].…”

Section: Crop Water Productivity Modelmentioning

confidence: 99%

From Global Goals to Local Gains—A Framework for Crop Water Productivity

Blatchford

Karimi

Bastiaanssen

et al. 2018

IJGI

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Crop water productivity (CWP) has become a recognised indicator in assessing the state of Sustainable Development Goals (SDG) 6.4—to substantially increase water use efficiency. This indicator, while useful at a global scale, is not comprehensive at a local scale. To fill this gap, this research proposes a CWP framework, that takes advantage of the spatio-temporal availability of remote sensing, that identifies CWP goals and sub-indicators specific to the needs of the targeted domain. Three sub-indicators are considered; (i) a global water productivity score (GWPS), (ii) a local water productivity score (LWPS) and (iii) a land and water use productivity score (YWPS). The GWPS places local CWP in the global context and focuses on maximised CWP. The LWPS differentiates yield zones, normalising for potential product, and focuses on minimising water consumption. The YWPS focuses simultaneously on improving land and water productivity equally. The CWP framework was applied to potato in the West Bank, Palestine. Three management practices were compared under each sub-indicator. The case study showed that fields with high and low performance were different under each sub-indicator. The performance associated with different management practices was also different under each sub-indicator. For example, a winter rotation had a higher performance under the YWPS, the fall rotation had a higher performance under the LWPS and under the GWPS there was little difference. The results showed, that depending on the basin goal, not only do the sub-indicators required change, but also the management practices or approach required to reach those basin goals. This highlights the importance of providing a CWP framework with multiple sub-indicators, suitable to basin needs, to ensure that meeting the SDG 6.4 goal does not jeopardise local objectives.

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Section: Crop Water Productivity Modelmentioning

confidence: 99%

From Global Goals to Local Gains—A Framework for Crop Water Productivity

Blatchford

Karimi

Bastiaanssen

et al. 2018

IJGI

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“…The SEBAL model has been applied mainly in agricultural areas [17,35,[41][42][43][44][45][46][47], including to study flood mitigation in irrigation development or to investigate water availability and use [48,49]. Studies with SEBAL also concentrate on a specific land use type in some cases [50]. Some recent studies involve comparisons of various energy balance methods such as SEBAL, SEBS (Surface Energy Balance System), SSEB (Simplified Surface Energy Balance) and METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) [51][52][53].…”

Section: Introductionmentioning

confidence: 99%

Projecting Climate and Land Use Change Impacts on Actual Evapotranspiration for the Narmada River Basin in Central India in the Future

et al. 2018

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Assessment of actual evapotranspiration (ET) is essential as it controls the exchange of water and heat energy between the atmosphere and land surface. ET also influences the available water resources and assists in the crop water assessment in agricultural areas. This study involves the assessment of spatial distribution of seasonal and annual ET using Surface Energy Balance Algorithm for Land (SEBAL) and provides an estimation of future changes in ET due to land use and climate change for a portion of the Narmada river basin in Central India. Climate change effects on future ET are assessed using the ACCESS1-0 model of CMIP5. A Markov Chain model estimated future land use based on the probability of changes in the past. The ET analysis is carried out for the years 2009-2011. The results indicate variation in the seasonal ET with the changed land use. High ET is observed over forest areas and crop lands, but ET decreases over crop lands after harvest. The overall annual ET is high over water bodies and forest areas. ET is high in the premonsoon season over the water bodies and decreases in the winter. Future ET in the 2020s, 2030s, 2040s, and 2050s is shown with respect to land use and climate changes that project a gradual decrease due to the constant removal of the forest areas. The lowest ET is projected in 2050. Individual impact of land use change projects decreases in ET from 1990 to 2050, while climate change effect projects increases in ET in the future due to rises in temperature. However, the combined impacts of land use and climate changes indicate a decrease in ET in the future.

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“…These images are free from purposive errors, serving as a basis for the following discussions. Figure 3A shows that Ts has an amplitude ranging from 296 K to 312 K. Sites with lower temperatures are linked to those with higher evapotranspiration values, the reverse being true ( Figures 3A and 2B) since the more intense the evaporation phenomenon is, the higher the latent heat transfer and thus the surface cooling (Li et al, 2013;Jimenez-Bello et al, 2015). Engenharia Agrícola, Jaboticabal, v.39, special issue, p.23-32, sep. 2019…”

Section: Resultsmentioning

confidence: 99%

“…However, the estimation of evapotranspiration requires that the sensor on board the satellite can capture information emitted from the surface and relative to the electromagnetic spectrum of the thermal infrared (Bastiaanssen, 2000;Li et al, 2013;Jimenez-Bello et al, 2015). This spectrum is necessary to estimate the surface temperature, a parameter required in the calculation of evapotranspiration (Bastiaanssen, 2000;Teixeira, 2010;Santos et al, 2011;Li et al, 2013;Andrade et al, 2014;Teixeira et al, 2015;Coaguila et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Sensitivity of Evapotranspiration Estimated by Orbital Images Under Influence of Surface Temperature

et al. 2019

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Surface temperature (Ts) is a determining factor to obtain energy balance parameters, being relevant to understand the influence of this variable on the estimation of evapotranspiration. Thus, the objective of this study was to simulate errors in Ts estimation to verify the consequences of actual evapotranspiration (ETa) estimated by the SAFER (Simple Algorithm for Evapotranspiration Retrieving) model. For this, an image of the Landsat-8 satellite was used to induce errors from 0.2K to 10K in the variable Ts, allowing verifying the consequences in the ETa data. After the estimations of Ts and ETa, the quantitative consequences and dynamics of Ts impact on the ETa data were verified along the different land uses in the study area. The results showed that the precise estimation of Ts is essential to obtain ETa accurately. The image of ETa errors presented the highest relative errors on the surface with exposed soils and with high Ts values. However, the highest residuals of ETa images occurred on the surfaces with milder Ts and higher evapotranspiration rates (irrigated surfaces).

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Assessment of a Remote Sensing Energy Balance Methodology (SEBAL) Using Different Interpolation Methods to Determine Evapotranspiration in a Citrus Orchard

Cited by 15 publications

References 54 publications

From Global Goals to Local Gains—A Framework for Crop Water Productivity

From Global Goals to Local Gains—A Framework for Crop Water Productivity

Projecting Climate and Land Use Change Impacts on Actual Evapotranspiration for the Narmada River Basin in Central India in the Future

Sensitivity of Evapotranspiration Estimated by Orbital Images Under Influence of Surface Temperature

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