scholarly journals Inter-comparison of four remote sensing based surface energy balance methods to retrieve surface evapotranspiration and water stress of irrigated fields in semi-arid climate

2013 ◽  
Vol 10 (1) ◽  
pp. 895-963 ◽  
Author(s):  
J. Chirouze ◽  
G. Boulet ◽  
L. Jarlan ◽  
R. Fieuzal ◽  
J. C. Rodriguez ◽  
...  
Keyword(s):  
Heat Flux ◽  
Water Stress ◽  
Energy Balance ◽  
Surface Energy ◽  
Surface Temperature ◽  
Latent Heat ◽  
Surface Energy Balance ◽  
Stress Levels ◽  
Single Pixel ◽  
Semi Arid

Abstract. Remotely sensed surface temperature can provide a good proxy for water stress level and is therefore particularly useful to estimate spatially distributed evapotranspiration. Instantaneous stress levels or instantaneous latent heat flux are deduced from the surface energy balance equation constrained by this equilibrium temperature. Pixel average surface temperature depends on two main factors: stress and vegetation fraction cover. Methods estimating stress vary according to the way they treat each factor. Two families of methods can be defined: the contextual methods, where stress levels are scaled on a given image between hot/dry and cool/wet pixels for a particular vegetation cover, and single-pixel methods which evaluate latent heat as the residual of the surface energy balance for one pixel independently from the others. Four models, two contextual (S-SEBI and a triangle method, inspired by Moran et al., 1994) and two single-pixel (TSEB, SEBS) are applied at seasonal scale over a four by four km irrigated agricultural area in semi-arid northern Mexico. Their performances, both at local and spatial standpoints, are compared relatively to energy balance data acquired at seven locations within the area, as well as a more complex soil-vegetation-atmosphere transfer model forced with true irrigation and rainfall data. Stress levels are not always well retrieved by most models, but S-SEBI as well as TSEB, although slightly biased, show good performances. Drop in model performances is observed when vegetation is senescent, mostly due to a poor partitioning both between turbulent fluxes and between the soil/plant components of the latent heat flux and the available energy. As expected, contextual methods perform well when extreme hydric and vegetation conditions are encountered in the same image (therefore, esp. in spring and early summer) while they tend to exaggerate the spread in water status in more homogeneous conditions (esp. in winter).

scholarly journals Intercomparison of four remote-sensing-based energy balance methods to retrieve surface evapotranspiration and water stress of irrigated fields in semi-arid climate

2014 ◽  
Vol 18 (3) ◽  
pp. 1165-1188 ◽  
Author(s):  
J. Chirouze ◽  
G. Boulet ◽  
L. Jarlan ◽  
R. Fieuzal ◽  
J. C. Rodriguez ◽  
...  
Keyword(s):  
Water Stress ◽  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
In Situ Data ◽  
Stress Levels ◽  
Single Pixel ◽  
Semi Arid ◽  
Svat Model

Abstract. Instantaneous evapotranspiration rates and surface water stress levels can be deduced from remotely sensed surface temperature data through the surface energy budget. Two families of methods can be defined: the contextual methods, where stress levels are scaled on a given image between hot/dry and cool/wet pixels for a particular vegetation cover, and single-pixel methods, which evaluate latent heat as the residual of the surface energy balance for one pixel independently from the others. Four models, two contextual (S-SEBI and a modified triangle method, named VIT) and two single-pixel (TSEB, SEBS) are applied over one growing season (December–May) for a 4 km × 4 km irrigated agricultural area in the semi-arid northern Mexico. Their performance, both at local and spatial standpoints, are compared relatively to energy balance data acquired at seven locations within the area, as well as an uncalibrated soil–vegetation–atmosphere transfer (SVAT) model forced with local in situ data including observed irrigation and rainfall amounts. Stress levels are not always well retrieved by most models, but S-SEBI as well as TSEB, although slightly biased, show good performance. The drop in model performance is observed for all models when vegetation is senescent, mostly due to a poor partitioning both between turbulent fluxes and between the soil/plant components of the latent heat flux and the available energy. As expected, contextual methods perform well when contrasted soil moisture and vegetation conditions are encountered in the same image (therefore, especially in spring and early summer) while they tend to exaggerate the spread in water status in more homogeneous conditions (especially in winter). Surface energy balance models run with available remotely sensed products prove to be nearly as accurate as the uncalibrated SVAT model forced with in situ data.

scholarly journals Evaluation of the SPARSE Dual-Source Model for Predicting Water Stress and Evapotranspiration from Thermal Infrared Data over Multiple Crops and Climates

2018 ◽  
Vol 10 (11) ◽  
pp. 1806 ◽  
Author(s):  
Emilie Delogu ◽  
Gilles Boulet ◽  
Albert Olioso ◽  
Sébastien Garrigues ◽  
Aurore Brut ◽  
...  
Keyword(s):  
Heat Flux ◽  
Water Stress ◽  
Energy Balance ◽  
Surface Energy ◽  
Surface Temperature ◽  
Surface Energy Balance ◽  
Source Model ◽  
Vegetation Stress ◽  
Stress Levels ◽  
Dual Source

Using surface temperature as a signature of the surface energy balance is a way to quantify the spatial distribution of evapotranspiration and water stress. In this work, we used the new dual-source model named Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) based on the Two Sources Energy Balance (TSEB) model rationale which solves the surface energy balance equations for the soil and the canopy. SPARSE can be used (i) to retrieve soil and vegetation stress levels from known surface temperature and (ii) to predict transpiration, soil evaporation, and surface temperature for given stress levels. The main innovative feature of SPARSE is that it allows to bound each retrieved individual flux component (evaporation and transpiration) by its corresponding potential level deduced from running the model in prescribed potential conditions, i.e., a maximum limit if the surface water availability is not limiting. The main objective of the paper is to assess the SPARSE model predictions of water stress and evapotranspiration components for its two proposed versions (the “patch” and “layer” resistances network) over 20 in situ data sets encompassing distinct vegetation and climate. Over a large range of leaf area index values and for contrasting vegetation stress levels, SPARSE showed good retrieval performances of evapotranspiration and sensible heat fluxes. For cereals, the layer version provided better latent heat flux estimates than the patch version while both models showed similar performances for sparse crops and forest ecosystems. The bounded layer version of SPARSE provided the best estimates of latent heat flux over different sites and climates. Broad tendencies of observed and retrieved stress intensities were well reproduced with a reasonable difference obtained for most of the points located within a confidence interval of 0.2. The synchronous dynamics of observed and retrieved estimates underlined that the SPARSE retrieved water stress estimates from Thermal Infra-Red data were relevant tools for stress detection.

scholarly journals The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models

2021 ◽  
Author(s):  
Ivonne Trebs ◽  
Kaniska Mallick ◽  
Nishan Bhattarai ◽  
Mauro Sulis ◽  
James Cleverly ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Surface Temperature ◽  
Surface Energy Balance ◽  
Aerodynamic Resistance ◽  
Atmospheric Stability ◽  
Semi Arid

<p>‘Aerodynamic resistance’ (hereafter r<sub>a</sub>) is a preeminent variable in the modelling of evapotranspiration (ET), and its accurate quantification plays a critical role in determining the performance and consistency of thermal remote sensing-based surface energy balance (SEB) models for estimating ET at local to regional scales. Atmospheric stability links r<sub>a</sub> with land surface temperature (LST) and the representation of their interactions in the SEB models determines the accuracy of ET estimates.</p><p>The present study investigates the influence of r<sub>a</sub> and its relation to LST uncertainties on the performance of three structurally different SEB models by combining nine OzFlux eddy covariance datasets from 2011 to 2019 from sites of different aridity in Australia with MODIS Terra and Aqua LST and leaf area index (LAI) products. Simulations of the latent heat flux (LE, energy equivalent of ET in W/m<sup>2</sup>) from the SPARSE (Soil Plant Atmosphere and Remote Sensing Evapotranspiration), SEBS (Surface Energy Balance System) and STIC (Surface Temperature Initiated Closure) models forced with MODIS LST, LAI, and in-situ meteorological datasets were evaluated using observed flux data across water-limited (semi-arid and arid) and radiation-limited (mesic) ecosystems.</p><p>Our results revealed that the three models tend to overestimate instantaneous LE in the water-limited shrubland, woodland and grassland ecosystems by up to 60% on average, which was caused by an underestimation of the sensible heat flux (H). LE overestimation was associated with discrepancies in r<sub>a</sub> retrievals under conditions of high atmospheric instability, during which errors in LST (expressed as the difference between MODIS LST and in-situ LST) apparently played a minor role. On the other hand, a positive bias in LST coincides with low r<sub>a</sub> and causes slight underestimation of LE at the water-limited sites. The impact of r<sub>a</sub> on the LE residual error was found to be of the same magnitude as the influence of errors in LST in the semi-arid ecosystems as indicated by variable importance in projection (VIP) coefficients from partial least squares regression above unity. In contrast, our results for mesic forest ecosystems indicated minor dependency on r<sub>a</sub> for modelling LE (VIP<0.4), which was due to a higher roughness length and lower LST resulting in dominance of mechanically generated turbulence, thereby diminishing the importance of atmospheric stability in the determination of r<sub>a</sub>.</p>

scholarly journals Analysing surface energy balance closure and partitioning over a semi-arid savanna FLUXNET site in Skukuza, Kruger National Park, South Africa

2017 ◽  
Vol 21 (7) ◽  
pp. 3401-3415 ◽  
Author(s):  
Nobuhle P. Majozi ◽  
Chris M. Mannaerts ◽  
Abel Ramoelo ◽  
Renaud Mathieu ◽  
Alecia Nickless ◽  
...  
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Latent Heat ◽  
Surface Energy Balance ◽  
Sensible Heat Flux ◽  
Dry Season ◽  
Energy Balance Closure ◽  
Net Radiation ◽  
Wet Season

Abstract. Flux towers provide essential terrestrial climate, water, and radiation budget information needed for environmental monitoring and evaluation of climate change impacts on ecosystems and society in general. They are also intended for calibration and validation of satellite-based Earth observation and monitoring efforts, such as assessment of evapotranspiration from land and vegetation surfaces using surface energy balance approaches. In this paper, 15 years of Skukuza eddy covariance data, i.e. from 2000 to 2014, were analysed for surface energy balance closure (EBC) and partitioning. The surface energy balance closure was evaluated using the ordinary least squares regression (OLS) of turbulent energy fluxes (sensible (H) and latent heat (LE)) against available energy (net radiation (Rn) less soil heat (G)), and the energy balance ratio (EBR). Partitioning of the surface energy during the wet and dry seasons was also investigated, as well as how it is affected by atmospheric vapour pressure deficit (VPD), and net radiation. After filtering years with low-quality data (2004–2008), our results show an overall mean EBR of 0.93. Seasonal variations of EBR also showed the wet season with 1.17 and spring (1.02) being closest to unity, with the dry season (0.70) having the highest imbalance. Nocturnal surface energy closure was very low at 0.26, and this was linked to low friction velocity during night-time, with results showing an increase in closure with increase in friction velocity. The energy partition analysis showed that sensible heat flux is the dominant portion of net radiation, especially between March and October, followed by latent heat flux, and lastly the soil heat flux, and during the wet season where latent heat flux dominated sensible heat flux. An increase in net radiation was characterized by an increase in both LE and H, with LE showing a higher rate of increase than H in the wet season, and the reverse happening during the dry season. An increase in VPD is correlated with a decrease in LE and increase in H during the wet season, and an increase in both fluxes during the dry season.

scholarly journals Application of the Priestley–Taylor Approach in a Two-Source Surface Energy Balance Model

2010 ◽  
Vol 11 (1) ◽  
pp. 185-198 ◽  
Author(s):  
Nurit Agam ◽  
William P. Kustas ◽  
Martha C. Anderson ◽  
John M. Norman ◽  
Paul D. Colaizzi ◽  
...  
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Vapor Pressure ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Vapor Pressure Deficit ◽  
Surface Energy Balance ◽  
Area Index ◽  
Wide Range

Abstract The Priestley–Taylor (PT) approximation for computing evapotranspiration was initially developed for conditions of a horizontally uniform saturated surface sufficiently extended to obviate any significant advection of energy. Nevertheless, the PT approach has been effectively implemented within the framework of a thermal-based two-source model (TSM) of the surface energy balance, yielding reasonable latent heat flux estimates over a range in vegetative cover and climate conditions. In the TSM, however, the PT approach is applied only to the canopy component of the latent heat flux, which may behave more conservatively than the bulk (soil + canopy) system. The objective of this research is to investigate the response of the canopy and bulk PT parameters to varying leaf area index (LAI) and vapor pressure deficit (VPD) in both natural and agricultural vegetated systems, to better understand the utility and limitations of this approximation within the context of the TSM. Micrometeorological flux measurements collected at multiple sites under a wide range of atmospheric conditions were used to implement an optimization scheme, assessing the value of the PT parameter for best performance of the TSM. Overall, the findings suggest that within the context of the TSM, the optimal canopy PT coefficient for agricultural crops appears to have a fairly conservative value of ∼1.2 except when under very high vapor pressure deficit (VPD) conditions, when its value increases. For natural vegetation (primarily grasslands), the optimal canopy PT coefficient assumed lower values on average (∼0.9) and dropped even further at high values of VPD. This analysis provides some insight as to why the PT approach, initially developed for regional estimates of potential evapotranspiration, can be used successfully in the TSM scheme to yield reliable heat flux estimates over a variety of land cover types.

scholarly journals Comparison of Latent Heat Flux Using Aerodynamic Methods and Using the Penman–Monteith Method with Satellite-Based Surface Energy Balance

2014 ◽  
Vol 6 (9) ◽  
pp. 8844-8877 ◽  
Author(s):  
Ramesh Dhungel ◽  
Richard Allen ◽  
Ricardo Trezza ◽  
Clarence Robison
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Surface Energy Balance

scholarly journals The surface energy balance of a polygonal tundra site in northern Siberia – Part 1: Spring to fall

2011 ◽  
Vol 5 (1) ◽  
pp. 151-171 ◽  
Author(s):  
M. Langer ◽  
S. Westermann ◽  
S. Muster ◽  
K. Piel ◽  
J. Boike
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Snow Cover ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Surface Energy Balance ◽  
Heat Fluxes ◽  
Net Radiation ◽  
Ground Heat Flux

Abstract. In this article, we present a study on the surface energy balance of a polygonal tundra landscape in northeast Siberia. The study was performed during half-year periods from April to September in each of 2007 and 2008. The surface energy balance is obtained from independent measurements of the net radiation, the turbulent heat fluxes, and the ground heat flux at several sites. Short-wave radiation is the dominant factor controlling the magnitude of all the other components of the surface energy balance during the entire observation period. About 50% of the available net radiation is consumed by the latent heat flux, while the sensible and the ground heat flux are each around 20 to 30%. The ground heat flux is mainly consumed by active layer thawing. About 60% of the energy storage in the ground is attributed to the phase change of soil water. The remainder is used for soil warming down to a depth of 15 m. In particular, the controlling factors for the surface energy partitioning are snow cover, cloud cover, and the temperature gradient in the soil. The thin snow cover melts within a few days, during which the equivalent of about 20% of the snow-water evaporates or sublimates. Surface temperature differences of the heterogeneous landscape indicate spatial variabilities of sensible and latent heat fluxes, which are verified by measurements. However, spatial differences in the partitioning between sensible and latent heat flux are only measured during conditions of high radiative forcing, which only occur occasionally.

scholarly journals Permafrost and surface energy balance of a polygonal tundra site in Northern Siberia – Part 2: Winter

2010 ◽  
Vol 4 (3) ◽  
pp. 1391-1431 ◽  
Author(s):  
M. Langer ◽  
S. Westermann ◽  
S. Muster ◽  
K. Piel ◽  
J. Boike
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Surface Energy Balance ◽  
Radiation Budget ◽  
Sensible Heat ◽  
Northern Siberia ◽  
Ground Heat Flux

Abstract. Permafrost is largely determined by the surface energy balance. Its vulnerability to degradation due to climate warming depends on complex soil-atmosphere interactions. This article is the second part of a comprehensive surface energy balance study at a polygonal tundra site in Northern Siberia. It comprises two consecutive winter periods from October 2007 to May 2008 and from October 2008 to January 2009. The surface energy balance is obtained by independent measurements of the radiation budget, the sensible heat flux and the ground heat flux, whereas the latent heat flux is inferred from measurements of the atmospheric turbulence characteristics and a model approach. The measurements reveal that the long-wave radiation is the dominant factor in the surface energy balance. The radiative losses are balanced to about 60% by the ground heat flux and almost 40% by the sensible heat fluxes, whereas the contribution of the latent heat flux is found to be relatively small. The main controlling factors of the surface energy budget are the snow cover, the cloudiness and the soil temperature gradient. Significant spatial differences in the surface energy balance are observed between the tundra soils and a small pond. The heat flux released from the subsurface heat storage is by a factor of two increased at the freezing pond during the entire winter period, whereas differences in the radiation budget are only observed at the end of winter. Inter-annual differences in the surface energy balance are related to differences in snow depth, which substantially affect the temperature evolution at the investigated pond. The obtained results demonstrate the importance of the ground heat flux for the soil-atmosphere energy exchange and reveal high spatial and temporal variabilities in the subsurface heat budget during winter.

Sign in / Sign up

Export Citation Format

Share Document