In viticulture, detailed spatial information about actual evapotranspiration (ETa) and vine water status within a vineyard may be of particular utility when applying site-specific, precision irrigation management. Over recent decades, extensive research has been carried out in the use of remote sensing energy balance models to estimate and monitor ETa at the field level. However, one of the major limitations remains the coarse spatial resolution in the thermal infrared (TIR) domain. In this context, the recent advent of the Sentinel missions of the European Space Agency (ESA) has greatly improved the possibility of monitoring crop parameters and estimating ETa at higher temporal and spatial resolutions. In order to bridge the gap between the coarse-resolution Sentinel-3 thermal and the fine-resolution Sentinel-2 shortwave data, sharpening techniques have been used to downscale the Sentinel-3 land surface temperature (LST) from 1 km to 20 m. However, the accurate estimates of high-resolution LST through sharpening techniques are still unclear, particularly when intended to be used for detecting crop water stress. The goal of this study was to assess the feasibility of the two-source energy balance model (TSEB) using sharpened LST images from Sentinel-2 and Sentinel-3 (TSEB-PTS2+3) to estimate the spatio-temporal variability of actual transpiration (T) and water stress in a vineyard. T and crop water stress index (CWSI) estimates were evaluated against a vine water consumption model and regressed with in situ stem water potential (Ystem). Two different TSEB approaches, using very high-resolution airborne thermal imagery, were also included in the analysis as benchmarks for TSEB-PTS2+3. One of them uses aggregated TIR data at the vine+inter-row level (TSEB-PTairb), while the other is based on a contextual method that directly, although separately, retrieves soil and canopy temperatures (TSEB-2T). The results obtained demonstrated that when comparing airborne Trad and sharpened S2+3 LST, the latter tend to be underestimated. This complicates the use of TSEB-PTS2+3 to detect crop water stress. TSEB-2T appeared to outperform all the other methods. This was shown by a higher R2 and slightly lower RMSD when compared with modelled T. In addition, regressions between T and CWSI-2T with Ystem also produced the highest R2.
One of the objectives of many studies conducted by breeding programs is to characterize and select rootstocks well-adapted to drought conditions. In recent years, field high-throughput phenotyping methods have been developed to characterize plant traits and to identify the most water use efficient varieties and rootstocks. However, none of these studies have been able to quantify the behavior of crop evapotranspiration in almond rootstocks under different water regimes. In this study, remote sensing phenotyping methods were used to assess the evapotranspiration of almond cv. “Marinada” grafted onto a rootstock collection. In particular, the two-source energy balance and Shuttleworth and Wallace models were used to, respectively, estimate the actual and potential evapotranspiration of almonds grafted onto 10 rootstock under three different irrigation treatments. For this purpose, three flights were conducted during the 2018 and 2019 growing seasons with an aircraft equipped with a thermal and multispectral camera. Stem water potential (Ψstem) was also measured concomitant to image acquisition. Biophysical traits of the vegetation were firstly assessed through photogrammetry techniques, spectral vegetation indices and the radiative transfer model PROSAIL. The estimates of canopy height, leaf area index and daily fraction of intercepted radiation had root mean square errors of 0.57 m, 0.24 m m–1 and 0.07%, respectively. Findings of this study showed significant differences between rootstocks in all of the evaluated parameters. Cadaman® and Garnem® had the highest canopy vigor traits, evapotranspiration, Ψstem and kernel yield. In contrast, Rootpac® 20 and Rootpac® R had the lowest values of the same parameters, suggesting that this was due to an incompatibility between plum-almond species or to a lower water absorption capability of the rooting system. Among the rootstocks with medium canopy vigor, Adesoto and IRTA 1 had a lower evapotranspiration than Rootpac® 40 and Ishtara®. Water productivity (WP) (kg kernel/mm water evapotranspired) tended to decrease with Ψstem, mainly in 2018. Cadaman® and Garnem® had the highest WP, followed by INRA GF-677, IRTA 1, IRTA 2, and Rootpac® 40. Despite the low Ψstem of Rootpac® R, the WP of this rootstock was also high.
<p>The almond production has increased by doubling their hectares under irrigation treatments in Spain. In a context of water scarcity, the estimation of Evapotranspiration (ET) and its components, Transpiration (T) and Evaporation (E), are key variables to monitor and manage the water resources. High-resolution ET can be retrieved from surface energy flux modeling, such as a Two-Source Energy Balance (TSEB) model, using an Unmanned Aerial System (sUAS). sUAS equipped with Thermal and Multispectral cameras allows us to obtain the main parameters required in TSEB. Currently, there are no studies that evaluate the T obtained with TSEB Priestley Taylor (TSEB-PT) and TSEB-2T models in tree-scale almonds under different irrigation treatments (IR) and production systems (PS). In this context, we evaluated the T retrieved with TSEB-PT and TSEB-2T models using Sap Flows sensor in trees with three PS, Open Vase with Minimal Pruning (OVMP), Central Axis (CA) and Hedgerow (HGR), and three levels IR, Full Irrigation (FI), Mild Stressed (MS) and Stressed (SS). Five flights were conducted from March 2021 to July 2021 to analyze the almond growing season with an aircraft equipped with a thermal and multispectral camera. Leaf area index (LAI), stem water potential (&#936;<sub>stem</sub>) and Fractional Intercepted Photosynthetically Active Radiation (fIPAR) was also measured concomitant to image acquisition. PS presents significant differences in fractional canopy cover (F_C), tree height (H_C), LAI and Sap Flow transpiration (Tsf). The two TSEB models show a generalized overestimation with a BIAS of 0.99 and 1.22 for TSEB-2T and TSEB-PT respectively. TSEB-PT presented worse statistics and R2 decreases in the more intensive production system. HGR has equal or greater LAI but lower F_C, which would imply an overestimation of canopy temperature (T_C) by the PT method. This is in addition to the difficulty of setting the PT coefficient according to the context of the crop. The overestimation in both models could be associated with an error in Campbell (1998) Radiative Transfer Model used to estimate transmittance, which has an error of 0.14 RMSE and 0.12 BIAS compared with fIPAR. Our results suggest the use of TSEB-2T with high resolution images considering the current available technology that allows us to estimate T_C and T_S separately, especially in intensive or super-intensive almond crops. To improve the T estimation, it is recommended to use in situ PAR measurement to decrease the influence of LAI measurements on the models.</p>
A growing number of intensive irrigated production systems of the almond crop have been established in recent years. However, there is little information regarding the crop water requirements. Remote sensing-based models such as the two-source energy balance (TSEB) have proven to be reliable ways to accurately estimate actual crop evapotranspiration. However, few efforts have been made to validate the transpiration with sap flow measurements in woody row crops with different production systems and water status. In this study, the TSEB Priestley-Taylor (TSEB-PT) and contextual approach (TSEB-2T) models were assessed to estimate canopy transpiration. In addition, the effect of applying a basic clumping index for heterogeneous randomly placed clumped canopies and a rectangular hedgerow clumping index on the TSEB transpiration estimation was assessed. The TSEB inputs were obtained from high resolution multispectral and thermal imagery using an unmanned aerial vehicle. The leaf area index (LAI), stem water potential (Ψstem) and fractional intercepted photosynthetically active radiation (fIPAR) were also measured. Significant differences were observed in transpiration between production systems and irrigation treatments. The combined use of the TSEB-2T with the C&N-R transmittance model gave the best transpiration estimations for all production systems and irrigation treatments. The use of in situ PAR transmittance in the TSEB-2T model significantly improved the root mean squared error. Thus, the better agreement observed with the TSEB when using the C&N-R model and in situ PAR transmittance highlights the importance of improving radiative transfer models for shortwave canopy transmittance, especially in woody row crops.
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