Simplified Two-Source Energy Balance Research Articles

High-throughput physiological phenotyping of crop evapotranspiration at the plot scale

ContextPlatforms and instrumentation for Field High-Throughput Plant Phenotyping (FHTPP) are well developed to measure important traits for crop breeding and agronomic studies. However, the research has focused on morphological and spectral traits; and approaches to estimate major physiological processes such as evapotranspiration (ET) for small experimental plots are lacking. ObjectiveIn this study, we put forward a new analytical framework to estimate plot-scale ET by integrating frequent phenotyping data (multispectral and thermal infrared images, canopy reflectance, and LiDAR point clouds) from a FHTPP system (known as NU-Spidercam), the weather data, a simplified two-source energy balance model, and reference ET and crop coefficient calculation. MethodsThe new plot-scale ET method was tested on five field experiments involving maize and soybean crops over two growing seasons, with the different treatment levels of irrigation water. Estimated plot-scale ET was accumulated across the growing reason for each plot, and its association with grain yield was investigated with regression analysis. ResultsThe result showed that plot-scale accumulated ET captured the seasonal trend of plot water use and clearly differentiated the irrigation treatments. Strong linear correlations were observed between plot-scale ET and grain yield, with R2 values ranging from 0.35 to 0.93 (average R2 = 0.71). Plot-scale ET appeared to be a more steady and stronger predictor of grain yield across the seasons than several other morphological and spectral traits including crop height, green pixel fraction, canopy temperature depression, and red-edge normalized difference vegetation index. ConclusionHigh spatial and temporal resolution of the field phenotyping data, along with the new analytical framework reported, successfully estimated ET at small plot scale, which is difficult to achieve with other systems or methods. SignificancesOur work of estimating ET at the plot-scale can be adopt to other ground-based platforms and drones, thus empowers physiologists, breeders, and agronomists for high-throughput phenotyping of water-use related traits and drought response evaluation.

Estimación de la evapotranspiración de los cultivos a partir de vuelos de drones

In this work, a two-source decoupling model called "STSEB" (Simplified Two-Source Energy Balance) is applied, whose purpose, through local information on air temperature, meteorology, topography, as well as additional data in situ, is to calculate the crop evapotranspiration through multispectral and thermal images obtained from a drone.The foregoing, with the purpose of classifying the priority irrigation areas of a plot of almond trees and being able to compare the results with the current planning of water treatments obtained by means of precision agriculture instruments. At the end of the work, it was possible to determine that there is an accuracy of 75% between the irrigation treatment plan of the administrators of the plot and the one obtained through the application of remotesensing techniques.

Estimación de la evapotranspiración de los cultivos a partir de vuelos de drones

In this work, a two-source decoupling model called "STSEB" (Simplified Two-Source Energy Balance) is applied, whose purpose, through local information on air temperature, meteorology, topography, as well as additional data in situ, is to calculate the crop evapotranspiration through multispectral and thermal images obtained from a drone.The foregoing, with the purpose of classifying the priority irrigation areas of a plot of almond trees and being able to compare the results with the current planning of water treatments obtained by means of precision agriculture instruments. At the end of the work, it was possible to determine that there is an accuracy of 75% between the irrigation treatment plan of the administrators of the plot and the one obtained through the application of remotesensing techniques.

Is the Subsurface Drip the Most Sustainable Irrigation System for Almond Orchards in Water-Scarce Areas?

The expansion of irrigated almond orchards in arid and semi-arid areas with scarce water available raises key issues related to the sustainability of the water resources. A 3-year field experiment was conducted on a commercial young almond orchard located in the southeast of Spain to study the effect of two drip irrigation systems (surface, DI and subsurface, SDI) on almond crop growth and their physiological responses under fully-irrigated conditions. Crop evapotranspiration (ETc) and its components (crop transpiration, Tc and soil evaporation, Es) were monitored as well as the irrigation water and nitrogen productivities. To estimate ETc, a simplified two-source energy balance (STSEB) approach was used. Although a lower irrigation water amount was applied in SDI compared to DI (differences between 10% and 13.8%), the almond crop growth and physiological responses as well as the yield components and kernel yield showed no significant differences. The ETc estimates resulted in small differences for spring and fall periods (0.1–0.2 mm day−1) for both treatments, while differences were significant during higher ETo periods (May–August), being 1.0–1.3 mm day−1 higher for the DI treatment than for the SDI treatment. The irrigation water productivity (IWP) was significantly higher in the SDI treatment than in the DI treatment. However, no significant differences between the two treatments were observed for nitrogen productivity. It can be concluded that the SDI system is a suitable strategy for irrigating almond crops, reducing consumptive water use and increasing IWP.

Monitoring Crop Evapotranspiration and Transpiration/Evaporation Partitioning in a Drip-Irrigated Young Almond Orchard Applying a Two-Source Surface Energy Balance Model

Encouraged by the necessity to better understand the water use in this woody crop, a study was carried out in a commercial drip-irrigated young almond orchard to quantify and monitor the crop evapotranspiration (ETc) and its partitioning into tree canopy transpiration (T) and soil evaporation (E), to list and analyze single and dual crop coefficients, and to extract relationships between them and the vegetation fractional cover (fc) and remote-sensing-derived vegetation indices (VIs). A Simplified Two-Source Energy Balance (STSEB) model was applied, and the results were compared to ground measurements from a flux tower. This study comprises three consecutive growing seasons from 2017 to 2019, corresponding to Years 2 to 4 after planting. Uncertainties lower than 50 W m−2 were obtained for all terms of the energy balance equation on an instantaneous scale, with average estimation errors of 0.06 mm h−1 and 0.6 mm d−1, for hourly and daily ETc, respectively. Water use for our young almond orchard resulted in average mid-season crop coefficient (Kc mid) values of 0.30, 0.33, and 0.45 for the 2017, 2018, and 2019 growing seasons, corresponding to fc mean values of 0.21, 0.35, and 0.39, respectively. Average daily evapotranspiration for the same periods resulted in 1.7, 2.1, and 3.2 mm d−1. The results entail the possibility of predicting the water use of any age almond orchards by monitoring its biophysical parameters.

Evapotranspiration of sorghum from the energy balance by METRIC and STSEB

ABSTRACT The estimate of the actual surface evapotranspiration (ET) contributes to quantifying the water needs of crops. An alternative to the use of lysimeter for an accurate estimation of water needs, which has proved to be of great value in recent years, is the use of remote sensing combined with models based on surface energy balance. There is wide variety of models that can be classified into two types: one-source models, such as the Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) algorithm, or two-source models, such as the Simplified Two-Source Energy Balance (STSEB). The objective of this study was to analyze how METRIC and STSEB can be used to estimate ET, in comparison with the lysimeter data, for the different stages of development of the sorghum crop in Apodi, RN, Brazil. The accuracy of both models in the daily ET estimation for the semi-arid conditions of the experiment, with RMSE values of 0.8 and of 0.7 mm d-1 through METRIC and STSEB, respectively, is considered acceptable for irrigation management purposes. The errors obtained with METRIC at an instantaneous scale were 60, 50, 130 and 5 W m-2 for Rn, LE, H and G, respectively, on the other hand, using STSEB these errors were of 40, 70, 120 and 21 W m-2 for Rn, LE, H and G, respectively. The METRIC and STSEB models are very similar when it comes to providing information on water needs of the sorghum.

Comparing evapotranspiration and yield performance of maize under sprinkler, superficial and subsurface drip irrigation in a semi-arid environment

In arid and semiarid environments, with shortage of water resources, maize production is competing for available water. This study analyzed the effect of different irrigation systems on maize yield, crop evapotranspiration and its components, i.e., canopy transpiration (T) and soil evaporation (E). A 2-year field experiment was conducted at the ITAP Research facilities located in Albacete (southeast Spain). Four treatments were assessed: surface drip irrigation with a spacing between drip lines of 1.5 m (SDI_1.5) and 0.75 m (SDI_0.75); subsurface drip irrigation (SubDI); solid set sprinkler irrigation (Sprink). In all treatments, irrigation was applied to refill the estimated potential water demand. Crop evapotranspiration (ETc) and E/T partitioning were estimated using a Simplified Two-Source Energy Balance (STSEB) approach. Although there was an important difference in the irrigation water applied between treatments, ranging from 743 and 722 for Sprink system to 534 and 495 for SubDI system in 2014 and 2015, respectively, yield was unaffected by the irrigation regime, resulting in an increase in the irrigation water productivity (IWP) by an average of 25% when irrigation was applied by the subsurface system. Maize ETc was affected by the irrigation system, with the SubDI achieving in 2015 a 39% reduction of seasonal ETc in comparison with the Sprink system. Similar reductions were obtained for separated E and T components with soil evaporation accounting in general for 15–20% of the total ETc. It is concluded that subsurface irrigation is a water savings strategy for irrigation of maize reducing the consumptive water use and increasing IWP. The final convenience for the widespread adoption of subsurface irrigation will depend on water availability and prices.

A promising new approach to estimate drought indices for fire danger assessment using remotely sensed data

One of the crucial input variables in fire danger rating systems is the water content of the soil, as well as of the living and dead fuels. This study concentrates on the Keetch-Byram Drought Index (KBDI) and the Drought Code (DC), which are both used to estimate the soil moisture deficit (SMD) and are inherent parts of well-established fire danger rating systems.These indices assume a simple water balance equation where effective rainfall is the only input and evapotranspiration is the only loss term, retrieved from empirical equations. We propose a method to increase spatial resolution of estimated SMD from KBDI and DC by replacing the empirical estimation of evapotranspiration with the actual evapotranspiration (ETa) estimated by the remote-sensing based Simplified Two-Source Energy Balance model (STSEB). For the days with no satellite observations, the basal crop coefficient (Kcb) and the adjusted crop coefficient (Kc,adj) approach for water stress conditions were applied to obtain continuous daily estimates for fire danger rating. A new approach was suggested to find a threshold dividing areas into fire-prone and fire-safe, regardless of the status of the drought indices.Both drought indices (KBDI and DC) benefited from the estimated ETa of the existing STSEB model obtaining SMD maps with higher spatial resolution (compared to conventional methods and products using interpolation techniques). Areas with higher proneness to drought and therefore to occurrence to fire were identified in the north-central part of Portugal, where e.g. on 16 July 2015, in the case of KBDI 47% of a specific area was classified as fire-prone and about 67% of the fires occurred within the identified area of this year.This new approach generated information on the water status of the soil at a spatial resolution of 500 m, which can be useful for forest management to identify endangered areas, as the danger of fire increases with increasing drought conditions.

Lysimeter assessment of the Simplified Two-Source Energy Balance model and eddy covariance system to estimate vineyard evapotranspiration

Estimation of crop water needs plays a key role in the water resource management in arid and semi-arid regions. Actual evapotranspiration (ETa) becomes the key term in both water and energy balances at this point. In this work we focus on vineyard due to the significance of this crop for La Mancha region, Spain, with the greatest concentration of vineyards in the world. Eddy-covariance (EC) technique has been traditionally used for ground observations of ETa. One of the aims of this work is to assess the feasibility of an EC system under the challenging conditions of a small drip-irrigated vineyard in a semi-arid environment.Two-source energy balance modelling allows for ETa estimation, as well as soil evaporation (E) and canopy transpiration (T) partitioning, using radiometric temperatures as a basis. A Simplified version of this Two-Source Energy Balance approach (STSEB) has been previously tested in a variety of crops and environments. The second goal of this paper is to explore now the performance of the STSEB model in a vineyard structure.Two experiments were carried out during the growing season of 2014 and 2015 in a ˜4 ha row-crop drip-irrigated Tempranillo vineyard, in a semi-arid location in Castilla-La Mancha, Spain. As a novelty in this work, a 9-m2 monolithic large weighting lysimeter was available. An eddy-covariance flux tower was deployed together with net radiation and soil heat flux instrumentation. The residual technique was selected to force the closure after an analysis of the energy imbalance based on the comparison EC-Lysimeter. Good agreement between adjusted EC measurements and lysimeter data (RMSE of ±0.09 mm h−1 and ±0.5 mm d−1 at hourly and daily scales, respectively) supports the validity of eddy-covariance technique to monitor turbulent fluxes and accurate ETa in vineyards.A set of 5 thermal-infrared radiometers were assembled to guaranty an appropriate thermal characterization of the vineyard structure required in the STSEB approach. Surface energy fluxes were modeled every hour with average estimation errors lower than ±30 W m−2 for net radiation and soil heat flux, and around ±50 W m−2 for sensible and latent heat fluxes, with systematic deviations lower than 25 W m−2 in all fluxes. Comparison with lysimeter data showed an average underestimation of 0.04 mm d-1 with a RMSE value of ±0.6 mm d-1 in modeled daily ETa. In terms of accumulated ETa for the full experiments, an underestimation of 12% in 2014 and an overestimation of 7% in 2015 were observed. These results reinforce the feasibility of the STSEB approach to monitor hourly, daily and accumulated ETa in row-crops such as vineyards. Although no ground measurements were available to assess the partitioning, separated E–T values were obtained for the full campaigns, showing a significant ratio E/ETa of 0.35−0.40 for soil evaporation.

Assessment of the indirect impact of wildfire (severity) on actual evapotranspiration in eucalyptus forest based on the surface energy balance estimated from remote-sensing techniques

ABSTRACTWildfires have a strong impact on the environment, changing its structure, soil properties, and microclimate and subsequently its water cycle with implications on the surface energy fluxes. Persisting droughts and catastrophic forest fires initiated this case study of pure eucalyptus stands in north-central Portugal. Although many studies have investigated changes in actual evapotranspiration (ETa), surface energy flux patterns, and the related physical parameters, only a few concentrated on the fire-driven changes in pure eucalyptus stands in the Mediterranean climate. This study aims to understand the consequences of wildfires on the water cycle, namely the ETa, and the surface energy heat fluxes by applying a simplified two-source energy balance model in combination with medium-resolution imagery (Landsat 8). A total of 21 different burnt locations were evaluated, which burned between 2011 and 2013. Estimated surface energy fluxes and daily ETa were compared to nearby control sites (unburnt) during satellite overpass for the time after the fire (2013–2015). The fire scars were classified into their burn severity, using the differenced Normalized Burn Ratio. The absolute difference of ETa ( ETa) between unburnt and burnt locations was used to identify fire-driven changes in magnitude and its evolution over time. Our results show that for the unburnt stands, the contributions to the total latent heat flux were around 80% from the canopy and 20% from the soil, while for the burnt site the contributions were around 30% (canopy) and 70% (soil) shortly after the fire. Inter-annually, the difference in ETa increased during the rainy season, which was related to the epicormic shooting, the fast regrowth rate of foliage, and the abundance of water. Generally, smaller differences in ETa were related to the severity classification and stand properties (i.e. tree species and soil characteristics). Two to three years after the fire events, ETa became non-significant for all severity classes, leading to an impact on the total water cycle smaller in comparison to other post-fire studies.

Estimation and partitioning of actual daily evapotranspiration at an intensive olive grove using the STSEB model based on remote sensing

This study is based on the application of an existing simplified two-source energy balance (STSEB) model, using medium-resolution satellite imagery (Landsat) to estimate instantaneous (at the satellite overpass time) and daily actual crop evapotranspiration (ETa) over an intensive olive grove. Daily values were obtained by the use of the evaporative fraction method and corrected for latent heat, available energy, and evaporative fraction biases (beta-factor correction). Model estimates were compared to ground-based measurements. Heat flux densities (eddy covariance method) were recorded, and five Landsat images at approximately monthly intervals were used, covering our study site in 2011. Comparison with ground measurements showed a maximum difference of −0.6 mm day−1 before, and 0.2 mm day−1 after beta-factor correction for the main plot.The experimental site consisted of a main plot exposed to deficit irrigation, and two small subplots where—during a limited period of time (six weeks)—one was temporarily not irrigated, and the other well-irrigated for reference. One Landsat image was available for this limited period of time.Additionally, the STSEB algorithm was tested for partitioning evapotranspiration into its evaporation and transpiration components. Evaporation estimated from the STSEB model was compared with evaporation estimated from a model adjusted from local lysimeter measurements. Transpiration data obtained from calibrated sap flow measurements were, after local calibration, also compared to model estimates. Model results agreed with the measured data, showing) under- and overestimation for transpiration and evaporation, respectively.

Estimating high resolution evapotranspiration from disaggregated thermal images

Accurate evapotranspiration (ET) estimations based on surface energy balance from remote sensing require information in the thermal infrared (TIR) domain, normally provided with an insufficient spatial resolution. In order to estimate ET in heterogeneous agricultural areas, we inspect in this paper the use of disaggregation techniques applied to two different sensors, such as MODIS (daily revisit cycle and 1km spatial resolution in the TIR domain) and Spot 5 (5days revisit cycle and 10m spatial resolution in the VNIR bands but no TIR band). Spot 5 images were used as a proxy for upcoming Sentinel-2. The Simplified Two-Source Energy Balance (STSEB) model was used for the estimation of ET. Since no Sentinel-2 images were available yet, images from the Spot 5 Take 5 experiment were used for testing this approach. Results assessment was conducted at two different levels: field scale (using ground data), and scene scale (using Landsat 7-ETM+ images as a reference). Validation of both disaggregated land surface temperature (LST) and derived surface energy fluxes was performed. Mean absolute deviations of ~2°C in disaggregated LST were observed at both field and scene scales. At field scale, relative errors of 22% and 19% were obtained for ET at instantaneous and daily scales, respectively. At scene scale, the four components of the surface energy balance equation were obtained with relative errors of 3, 14, 11 and 8% for net radiation, evapotranspiration, sensible heat flux and soil heat flux, respectively, compared to Landsat. The results obtained were compared to the use of the MODIS LST at its original resolution (1km), which was used also to obtain the surface energy fluxes. As the surface heterogeneity increases the errors in both MODIS LST and ET become more and more significant, compared to the use of the disaggregated images. Although reference images at 10m spatial resolution were not available at this stage for a more robust comparison, this paper shows the potential of the use of disaggregated LST to estimate ET at 10m spatial resolution, which is especially attractive in highly heterogeneous areas.

Determining water use of sorghum from two-source energy balance and radiometric temperatures

Abstract. Estimates of surface actual evapotranspiration (ET) can assist in predicting crop water requirements. An alternative to the traditional crop-coefficient methods are the energy balance models. The objective of this research was to show how surface temperature observations can be used, together with a two-source energy balance model, to determine crop water use throughout the different phenological stages of a crop grown. Radiometric temperatures were collected in a sorghum (Sorghum bicolor) field as part of an experimental campaign carried out in Barrax, Spain, during the 2010 summer growing season. Performance of the Simplified Two-Source Energy Balance (STSEB) model was evaluated by comparison of estimated ET with values measured on a weighing lysimeter. Errors of ±0.14 mm h−1 and ±1.0 mm d−1 were obtained at hourly and daily scales, respectively. Total accumulated crop water use during the campaign was underestimated by 5%. It is then shown that thermal radiometry can provide precise crop water necessities and is a promising tool for irrigation management.

Estimating energy balance fluxes above a boreal forest from radiometric temperature observations

The great areal extent of boreal forests confers these ecosystems potential to impact on the global surface-atmosphere energy exchange. A modelling approach, based on a simplified two-source energy balance model, was proposed to estimate energy balance fluxes above boreal forests using thermal infrared measurements. Half-hourly data from the Solar-Induced Fluorescence Experiment, carried out in a Finnish boreal forest, was used to evaluate the performance of the model. Energy balance closure, determined by linear regression, found all fluxes to underestimate available energy by 9% ( r 2 = 0.94). Significance in the energy balance of the heat storage in the air and in the soil terms was also analyzed. Canopy temperatures, measured by a CIMEL Electronique CE 312 radiometer, together with ancillary meteorological variables and vegetation characteristics, were used to run the model. Comparison with ground measurements showed errors lower than ±15 W m −2 for the retrieval of net radiation, soil heat flux and storage heat flux, and about ±50 W m −2 for the sensible and latent heat fluxes. A sensitivity analysis of the approach to typical operational uncertainties in the required inputs was conducted showing the necessity of accurate measurements of the target radiometric surface temperature.

Modelling surface energy fluxes over maize using a two-source patch model and radiometric soil and canopy temperature observations

Models estimating surface energy fluxes over partial canopy cover with thermal remote sensing must account for significant differences between the radiometric temperatures and turbulent exchange rates associated with the soil and canopy components of the thermal pixel scene. Recent progress in separating soil and canopy temperatures from dual angle composite radiometric temperature measurements has encouraged the development of two-source (soil and canopy) approaches to estimating surface energy fluxes given observations of component soil and canopy temperatures. A Simplified Two-Source Energy Balance (STSEB) model has been developed using a “patch” treatment of the surface flux sources, which does not allow interaction between the soil and vegetation canopy components. A simple algorithm to predict the net radiation partitioning between the soil and vegetation is introduced as part of the STSEB patch modelling scheme. The feasibility of the STSEB approach under a full range in fractional vegetation cover conditions is explored using data collected over a maize (corn) crop in Beltsville Maryland, USA during the 2004 summer growing season. Measurements of soil and canopy component temperatures as well as the effective composite temperature were collected over the course of the growing season from crop emergence to cob development. Comparison with tower flux measurements yielded root-mean-square-difference values between 15 and 50 W m − 2 for the retrieval of the net radiation, soil, sensible and latent heat fluxes. A detailed sensitivity analysis of the STSEB approach to typical uncertainties in the required inputs was also conducted indicating greatest model sensitivity to soil and canopy temperature uncertainties with relative errors reaching ∼ 30% in latent heat flux estimates. With algorithms proposed to infer component temperatures from bi-angular satellite observations, the STSEB model has the capability of being applied operationally.