Thermal-based Two-Source Energy Balance Model Research Articles

Applications of a Thermal-Based Two-Source Energy Balance Model Coupling the Sun-Induced Chlorophyll Fluorescence Data

Quantifying and monitoring land surface evapotranspiration (ET) is an essential task for understanding the earth’s water, energy, and carbon cycles. ET, specifically plant transpiration ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> ), is closely linked to the photosynthesis, which is coupled through stomatal function. However, the mechanistic links between sun-induced chlorophyll fluorescence (SIF) information indicating canopy photosynthetic activity and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> are complex and difficult to derive empirically. An empirical SIF- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> relationship at ecosystem scale was developed and coupled to the two-source energy balance model (TSEB-SIF) to estimate the ET and its components, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> and soil evaporation, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$E$ </tex-math></inline-formula> . By comparing model predictions with observations from an irrigated cropland site located in a semiarid region, the TSEB-SIF model shows a slightly better performance to the TSEB model in estimating ET, especially under water deficit conditions. Moreover, the TSEB-SIF model more reliably partitioned the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> from ET, while the TSEB model tended to overestimate the contribution of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> to ET.

Evaluating different metrics from the thermal-based two-source energy balance model for monitoring grapevine water stress

Precision irrigation management requires operational monitoring of crop water status. However, there is still some controversy on how to account for crop water stress. To address this question, several physiological, several physiological metrics have been proposed, such as the leaf/stem water potentials, stomatal conductance, or sap flow. On the other hand, thermal remote sensing has been shown to be a promising tool for efficiently evaluating crop stress at adequate spatial and temporal scales, via the Crop Water Stress Index (CWSI), one of the most common indices used for assessing plant stress. CWSI relates the actual crop evapotranspiration ET (related to the canopy radiometric temperature) to the potential ET (or minimum crop temperature). However, remotely sensed surface temperature from satellite sensors includes a mixture of plant canopy and soil/substrate temperatures, while what is required for accurate crop stress detection is more related to canopy metrics, such as transpiration, as the latter one avoids the influence of soil/substrate in determining crop water status or stress. The Two-Source Energy Balance (TSEB) model is one of the most widely used and robust evapotranspiration model for remote sensing. It has the capability of partitioning ET into the crop transpiration and soil evaporation components, which is required for accurate crop water stress estimates. This study aims at evaluating different TSEB metrics related to its retrievals of actual ET, transpiration and stomatal conductance, to track crop water stress in a vineyard in California, part of the GRAPEX experiment. Four eddy covariance towers were deployed in a Variable Rate Irrigation system in a Merlot vineyard that was subject to different stress periods. In addition, root-zone soil moisture, stomatal conductance and leaf/stem water potential were collected as proxy for in situ crop water stress. Results showed that the most robust variable for tracking water stress was the TSEB derived leaf stomatal conductance, with the strongest correlation with both the measured root-zone soil moisture and stomatal conductance gas exchange measurements. In addition, these metrics showed a better ability in tracking stress when the observations are taken early after noon.

Applications of a thermal-based two-source energy balance model coupled to surface soil moisture

The two-source energy balance (TSEB) model using the land surface temperature (LST) as a key boundary has been used to estimate land surface evapotranspiration (ET) over various landcovers and environmental conditions. However, LST may not always provide an adequate boundary condition to simultaneously constrain the soil evaporation and plant transpiration especially under water limited conditions. A refinement to TSEB model by coupling surface soil moisture information to derive the soil and vegetation component temperatures and a new transpiration algorithm was developed (TSEB-SM). The TSEB-SM model was evaluated under a wide range of surface soil water content values and vegetation cover conditions and compared with the performance with the original TSEB model using only LST. While the results showed that the TSEB-SM model produced similar agreement in the fluxes and ET as the original TSEB for the cropland and grassland sites, TSEB-SM model performance was notably improved at the shrub-forest and desert steppe sites with a significant reduction in mean absolute percent difference in daily ET from nearly 65% to 25% and from approximately 50% to 40%, respectively. It also appears to be more reliable in partitioning ET into soil evaporation and plant transpiration when compared to the partitioning using the water use efficiency (uWUE) approach in combination with the eddy covariance measurements. With satellite data such as MODIS LST and leaf area index, and surface soil moisture retrievals from microwave satellite observations, the TSEB-SM model may potentially be a more reliable tool for monitoring regional ET partitioning under sparse canopy cover conditions.

Evaluation of soil resistance formulations for estimates of sensible heat flux in a desert vineyard

For irrigated vineyards, accurate estimates of the sensible heat flux from the soil surface (Hs) is essential for determining the contribution of soil evaporation (E) to evapotranspiration (ET) using thermal-based energy balance approaches. A key to an accurate estimate of Hs is a robust physically-based soil resistance formulation. Here we compare the performance of two soil resistance formulations: a conventional resistance model (rKN) derived from field and laboratory studies which has been extensively implemented in the thermal-based Two-Source Energy Balance (TSEB) model, and a recently developed physically-based soil resistance formulation (rHO) that explicitly accounts for near-surface interactions affecting scalar fluxes at the soil surface in the presence of bluff-body roughness elements. Estimates of Hs using the two resistance formulations were evaluated using in-situ observations from a drip-irrigated vineyard in the arid central Negev Highlands of Israel. The results indicate that the soil resistance model rHO outperforms the rKN formulation using standard model coefficients and provides robust estimates of Hs independent of model calibration or parameter tuning. This offers an opportunity to advance the utility of TSEB model when applied to sparsely vegetated areas where ground-based calibration data are not available for adjusting coefficients in the rKN formulation, and potentially improves its practical applications to heterogeneous landscapes by obviating its reliance on semi-empirical coefficients.

Estimation of surface energy fluxes in the Arctic tundra using the remote sensing thermal-based Two-Source Energy Balance model

Abstract. The Arctic has become generally a warmer place over the past decades leading to earlier snow melt, permafrost degradation and changing plant communities. Increases in precipitation and local evaporation in the Arctic, known as the acceleration components of the hydrologic cycle, coupled with land cover changes, have resulted in significant changes in the regional surface energy budget. Quantifying spatiotemporal trends in surface energy flux partitioning is key to forecasting ecological responses to changing climate conditions in the Arctic. An extensive local evaluation of the Two-Source Energy Balance model (TSEB) – a remote-sensing-based model using thermal infrared retrievals of land surface temperature – was performed using tower measurements collected over different tundra types in Alaska in all sky conditions over the full growing season from 2008 to 2012. Based on comparisons with flux tower observations, refinements in the original TSEB net radiation, soil heat flux and canopy transpiration parameterizations were identified for Arctic tundra. In particular, a revised method for estimating soil heat flux based on relationships with soil temperature was developed, resulting in significantly improved performance. These refinements result in mean turbulent flux errors generally less than 50 W m−2 at half-hourly time steps, similar to errors typically reported in surface energy balance modeling studies conducted in more temperate climatic regimes. The MODIS leaf area index (LAI) remote sensing product proved to be useful for estimating energy fluxes in Arctic tundra in the absence of field data on the local biomass amount. Model refinements found in this work at the local scale build toward a regional implementation of the TSEB model over Arctic tundra ecosystems, using thermal satellite remote sensing to assess response of surface fluxes to changing vegetation and climate conditions.

Applications of a thermal-based two-source energy balance model using Priestley-Taylor approach for surface temperature partitioning under advective conditions

In this study ground measured soil and vegetation component temperatures and composite temperature from a high spatial resolution thermal camera and a network of thermal-IR sensors collected in an irrigated maize field and in an irrigated cotton field are used to assess and refine the component temperature partitioning approach in the Two-Source Energy Balance (TSEB) model. A refinement to TSEB using a non-iterative approach based on the application of the Priestley-Taylor formulation for surface temperature partitioning and estimating soil evaporation from soil moisture observations under advective conditions (TSEB-A) was developed. This modified TSEB formulation improved the agreement between observed and modeled soil and vegetation temperatures. In addition, the TSEB-A model output of evapotranspiration (ET) and the components evaporation (E), transpiration (T) when compared to ground observations using the stable isotopic method and eddy covariance (EC) technique from the HiWATER experiment and with microlysimeters and a large monolithic weighing lysimeter from the BEAREX08 experiment showed good agreement. Difference between the modeled and measured ET measurements were less than 10% and 20% on a daytime basis for HiWATER and BEAREX08 data sets, respectively. The TSEB-A model was found to accurately reproduce the temporal dynamics of E, T and ET over a full growing season under the advective conditions existing for these irrigated crops located in arid/semi-arid climates. With satellite data this TSEB-A modeling framework could potentially be used as a tool for improving water use efficiency and conservation practices in water limited regions. However, TSEB-A requires soil moisture information which is not currently available routinely from satellite at the field scale.

Utility of a Thermal-based Two-source Energy Balance Model for Estimating Surface Fluxes over Complex Landscapes

Many landscapes are comprised of a variety of vegetation types with different canopy structure, rooting depth physiological characteristics, including r sponse to environmental stressors, etc. Even in agricultural regions different management practices, including crop rotations, irrigation scheduling, planting density, seed varieties, and other factors result in complex patterns in vegetation growth stages, canopy cover, canopy architecture and cropping densities. This variability at the canopy, field and landscape scale, makes it very challenging for quantifying spatially-distributed surface fluxes. This paper describes a robust but relatively simple thermal-based energy balance model that parameterizes the key soil/substrate and vegetation exchange processes affecting the radiative balance and turbulent energy transport with the overlying atmosphere. The thermal-based model, called the Two-Source Energy Balance (TSEB) model solves for the soil/substrate and canopy temperatures that achieves a balance in the radiation and turbulent heat flux exchange with the lower atmosphere for the soil/substrate and vegetation elements. The TSEB scheme permits interaction between soil/substrate and canopy elements which are both coupled to the atmosphere via the canopy-air temperature; this canopy-air temperature is highly correlated to the aerodynamic surface temperature used in computing surface sensible heat flux. As a result, the TSEB modeling framework is applicable to a wide range of atmospheric and canopy cover conditions. An overview of recent applications of the TSEB modeling framework to a variety of agricultural landscapes is presented.

The impact of in-canopy wind profile formulations on heat flux estimation in an open orchard using the remote sensing-based two-source model

Abstract. For open orchard and vineyard canopies containing significant fractions of exposed soil (&gt;50%), typical of Mediterranean agricultural regions, the energy balance of the vegetation elements is strongly influenced by heat exchange with the bare soil/substrate. For these agricultural systems a "two-source" approach, where radiation and turbulent exchange between the soil and canopy elements are explicitly modelled, appears to be the only suitable methodology for reliably assessing energy fluxes. In strongly clumped canopies, the effective wind speed profile inside and below the canopy layer can strongly influence the partitioning of energy fluxes between the soil and vegetation components. To assess the impact of in-canopy wind profile on model flux estimates, an analysis of three different formulations is presented, including algorithms from Goudriaan (1977), Massman (1987) and Lalic et al. (2003). The in-canopy wind profile formulations are applied to the thermal-based two-source energy balance (TSEB) model developed by Norman et al. (1995) and modified by Kustas and Norman (1999). High resolution airborne remote sensing images, collected over an agricultural area located in the western part of Sicily (Italy) comprised primarily of vineyards, olive and citrus orchards, are used to derive all the input parameters needed to apply the TSEB. The images were acquired from June to October 2008 and include a relatively wide range of meteorological and soil moisture conditions. A preliminary sensitivity analysis of the three wind profile algorithms highlights the dependence of wind speed just above the soil/substrate to leaf area index and canopy height over the typical range of canopy properties encountered in these agricultural areas. It is found that differences among the models in wind just above the soil surface are most significant under sparse and medium fractional cover conditions (15–50%). The TSEB model heat flux estimates are compared with micro-meteorological measurements from a small aperture scintillometer and an eddy covariance tower collected over an olive orchard characterized by moderate fractional vegetation cover (≈35%) and relatively tall crop (≈3.5 m). TSEB fluxes for the 7 image acquisition dates generated using both the Massman and Goudriaan in-canopy wind profile formulations give close agreement with measured fluxes, while the Lalic et al. equations yield poor results. The Massman wind profile scheme slightly outperforms that of Goudriaan, but it requires an additional parameter accounting for the roughness sub-layer of the underlying vegetative surface. The analysis also suggests that within-canopy wind profile model discrepancies become important, in terms of impact on modelled sensible heat flux, only for sparse canopies with moderate vegetation coverage.