This contribution deals with the spatial and temporal scales involved in the processes that control evapotranspiration (ET) and confront these with the merits and limitations of various observation and modelling techniques. We make a strong case for integrated approaches to further develop our understanding of evapotranspiration.

The most challenging, but at the same time most relevant conditions to accurately represent ET are found in semi-arid regions, specifically complex terrains with strong thermal contrasts between dry and wet (irrigated) areas. We will present three cases with different objectives in terms of processes that control ET and the methods used to study them. First is the LIAISE campaign, where we will focus on how to describe ET depending on the spatial scale considered ranging from regional to landscape to local scale. Second is the E-DATA campaign, where ET is controlled by a thermally driven and topographically enhanced regional flow that alters the turbulent mixing and the structure of the atmospheric boundary layer. Third deals with a machine learning approach to determine ET based on standard weather station data.

LIAISE took place during the summer of 2021 in the Pla d’Urgell region of the Ebro River Valley in Catalonia, Spain. The surface was homogeneous at the field scale (e.g. fields of alfalfa). However, the surface was heterogeneous at the regional scale (~10-100km) because of the spatial distribution of irrigated crops and dry natural vegetation. We examined the impact of the boundary layer on surface fluxes at two of the LIAISE sites: one in the irrigated, crop-covered area and one in the dry, naturally-vegetated area.  We use an atmospheric mixed-layer column model that is heavily constrained by the surface and boundary layer observations from the LIAISE experiment.

The E-DATA experiment took place during November 2018 and focussed on quantifying the processes that drive ET in a shallow lake surrounded by extremely dry conditions in a salt flat (Salar del Huasco) of the Chilean Atacama desert. We use the WRF model at 100-m resolution to represent the local processes as well as the heterogeneity and regional transport to understand the evaporation and ABL dynamics over the water.

The machine learning study explores whether a physics-informed machine learning  approach can be used to improve the estimated evapotranspiration for irrigated fields located in a desert environment, without arbitrary tuning after training  and only using readily available data (standard meteorological data and satellite derived vegetation indices). We focus on an irrigated pecan orchard in Northwest Mexico. Multi-year eddy-covariance ET estimates are used to train and validate the model.

How to cite: Hartogensis, O., Mangan, M. R., Aguirre Correa, F., Lobos Roco, F., Stoffer, R., and Vilà-Guerau de Arellano, J.: Measuring and Modelling Evapotranspiration over Complex Terrain, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7847, https://doi.org/10.5194/egusphere-egu23-7847, 2023.

Waterlogged and anoxic conditions facilitate the preservation of carbon-rich peat layers in tropical peatlands coexisting with peat swamp forests. Peatlands in Southeast Asia, which host one-third of the tropical peatland area, have high temperatures throughout the year and high soil moisture availability, which support high evapotranspiration rates. The majority of existing land cover in Southeast Asia peatland is a canopy-covered ecosystem. Therefore, these ecosystems are considered to support high transpiration rates. However, the understanding of transpiration rates and their governing factors for existing land cover in Southeast Asia peatlands remains poorly understood due to limited measurements.

Here, we quantified transpiration rates and explored governing factors in Acacia crassicarpa plantations (fast-growing species, harvested on a 4-5 year rotation) in the coastal peatland of Eastern Sumatra, Indonesia, between 2020 and 2022. Transpiration was quantified by measuring in situ sap flow rate using the HFD8-50 and SFM1 (ICT International, Australia) during the plantation age of 2 to 4 years. We measured the sapwood cross-sectional area using an increment borer (Haglöf, Sweden). In addition, we implemented a sampling strategy that considered tree size, azimuth, height, and radial factors, to account for the variability and upscaling from tree to stand level of transpiration.

Our results showed that the greatest source of variability to determine transpiration were the radial and tree size. On a diel and daily basis, tree transpiration was affected by vapour pressure deficit and solar radiation. Further, we did not observe a relationship between seasonal rainfall variations and transpiration. We found that stand-level transpiration in deeper groundwater level sites (around -80 cm below peat surface) was higher by 20% than those in shallower sites (around -40 cm below peat surface) due to the higher stand density and total sapwood area. Overall measured transpiration rates (0.8 – 1.0 mm d^-1) represent 20-24 % of evapotranspiration measured by eddy covariance. This study provides the first insights into the eco-hydrological characteristics of the Acacia crassicarpa plantation and improves the understanding of water balance from this globally important ecosystem.

How to cite: Suardiwerianto, Y., Kurnianto, S., Hidayat, M. F., Simamora, N., Harahap, Mhd. I. F., Fitriyah, N. A., Jabbar, A., Ghimire, C. P., and Deshmukh, C. S.: Transpiration of Acacia plantations in a managed tropical peatland Sumatra, Indonesia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14383, https://doi.org/10.5194/egusphere-egu23-14383, 2023.

In light of the ongoing global change in climatic conditions and a related trend to increases in extreme hydrological events, it is increasingly crucial to assess ecosystem resilience and - in agricultural systems - to ensure sustainable management and food security.  A comprehensive understanding of ecosystem water cycle budgets and spatio-temporal dynamics is indispensable. Evapotranspiration (ET) plays a pivotal role returning up to 90 % of ingoing precipitation back to the atmosphere. Here, we studied impacts of soil types and management on an agroecosystem's water budgets and agronomic water use efficiencies (WUE_agro). To do so, a plot experiment with winter rye (September 17, 2020 to June 30, 2021) was conducted at an eroded cropland which is located in the hilly and dry ground moraine landscape of the Uckermark region in NE Germany. Along the experimental plot (110 m x 16 m), a gantry crane mounted mobile and automated two chamber system (FluxCrane as part of the AgroFlux platform within the CarboZALF-D research site) was used for the first time to continuously measure water fluxes and determine evapotranspiration. Three soil types representing the soil erosion gradient related to the hummocky ground moraine landscape (extremely eroded: Calcaric Regosol, strongly eroded: Nudiargic Luvisol, non-eroded: Calcic Luvisol) and additional soil manipulation (topsoil removal and subsoil admixture) were investigated (randomized block design, 3 replicates per treatment). Five different gap-filling approaches were used and compared in light of their potential for reliable water budgets over the entire crop growth period as well as reproduce short-term (day-to-day, diurnal) water flux dynamics. The best calibration performance was achieved with approaches based on machine learning, such as support vector machine (SVM) and artificial neural networks (with Bayesian regularization; ANN_BR), while especially SVM yielded in most reliable predictions of measured ET during validation.

We found significant differences in dry biomass (DM) and minor in evapotranspiration between soil types, resulting in different water use efficiencies (WUE_agro). The Calcaric Regosol (extremely eroded) shows a maximum of around 37% lower evapotranspiration and a maximum of around 52% lower water use efficiency (WUE_agro) compared to the non-eroded Calcic Luvisol.  The key period contributing to ~ 70% of overall ET of the entire growth period was from April until June (harvest), however differences in the overall ET budget (ET_sum) between soil types and manipulation resulted predominantly from small differences between the treatments over the entire growth period.

How to cite: Dahlmann, A., Hoffmann, M., Verch, G., Schmidt, M., Sommer, M., Augustin, J., and Dubbert, M.: Evapotranspiration measurements on an eroded cropland using an automated and mobile chamber system: gap filling strategies and impact of soil type and topsoil modification, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12768, https://doi.org/10.5194/egusphere-egu23-12768, 2023.

Evapotranspiration (ET) is an important part of surface hydrological cycle and energy exchange process. Under the background of frequent drought and water resource shortage, it is of great significance to study the seasonal and interannual variations in ET and energy budget of farmland ecosystem in arid regions. This will help to reveal the process of crop ET and water consumption in farmland ecosystems and its response to drought conditions and environmental factors. Based on continuous eddy-covariance observation data, this study analyzed the seasonal and interannual variations in ET and energy budget of one maize farmland ecosystem in the semi-arid region of Chinese Loess Plateau and its response to environmental changes during 2019-2020. Results showed that ET and meteorological factors presented obvious seasonal and interannual changes during the study period. The annual total ET was 339.3 mm/yr and 386.5 mm/yr during the drought year 2019 and the normal year 2020, respectively. It was 16.4% and 30.4% lower than the annual total precipitation (P) in the same period. The ET/P ratio for two years was 0.84 and 0.70, respectively. While the latent heat flux and sensible heat flux showed obvious seasonal and interannual variation trends, it also reflected that the latent heat flux dominated the net radiation energy budget in the growing season and the sensible heat flux is the main consumption component of the net radiation energy budget in the non-growing season. During 2020, due to better moisture conditions, the Bowen ratio was smaller and sensible heat exchange was more moderate, making the air more stable. The volatility of albedo in 2020 was significantly greater than that in 2019, which was closely related to the frequent precipitation in the normal year. The results of the path analysis model showed that soil water content (SWC) had stronger impacts on the ET variation during the drought year (2019) at the scales of entire year, growing season and non-growing season. Meanwhile, leaf area index (LAI) had more significant impacts on the ET variation during the hydrologically normal year (2020) when the water supply was much more sufficient. We also found that there was a strong coupling relationship between the atmosphere and vegetation during the study period (decoupling factor Ω varied between 0 and 0.5), indicating that the ecosystem ET is mainly controlled by canopy conductance(g_s) and vapor pressure deficit (VPD). Moreover, g_s decreased with the increase of VPD, and VPD played a stronger role in controlling g_s during 2020 which was with better water supply condition.

How to cite: Zheng, H. and Sun, Y.: Seasonal and interannual variations in evapotranspiration and energy budget over a rainfed maize field in the Chinese Loess Plateau, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12065, https://doi.org/10.5194/egusphere-egu23-12065, 2023.

Actual evapotranspiration (ETa) is difficult to measure and limited long-term information is available about ETa. With eddy covariance systems ETa can be measured at the field scale, but the method is associated with energy balance closure issues. For measuring ETa, weighing lysimeters are considered to be the most accurate and reliable method. However, weighing lysimeters have some disadvantages like elevated costs of installation and maintenance, and a small footprint (e.g., about 1 m²). A main question is therefore whether the precise ETa-measurements by lysimeters are representative for a larger area like a field, a meso-scale catchment, or even a larger region. Our hypothesis was that a lysimeter provides information about ETa that represents a larger area than its underlying measurement area. To this end, we examined here the daily ETa measurements from lysimeter at four study sites across Germany (separation distances 10 - 500 km) for the years 2015 to 2020. The Pearson correlations of the standardized anomalies (SA) of daily ETa between different lysimeters were calculated and compared with SA of daily ETa obtained from the corresponding eddy covariance tower. The correlations were further analyzed and related to spatial correlations of SA of environmental controls like precipitation, potential evapotranspiration (ET₀), and soil moisture. We found that SA of daily ETa shows high spatial correlations (>0.5) for considerable separation distances between sites of up to 50km, with similar correlations for lysimeters and eddy covariance systems. ET₀ is the dominant factor for the spatial correlation of ETa, as SA of ET₀ shows stronger spatial correlations than SA of ETa.

How to cite: Lu, X., Groh, J., Pütz, T., Vereecken, H., and Hendricks Franssen, H.-J.: Analysis of Scale-dependent Spatial Correlations of Actual Evapotranspiration Measured by Lysimeters, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11808, https://doi.org/10.5194/egusphere-egu23-11808, 2023.

While eddy covariance (EC) is a standard for measuring total ecosystem evaporation (evapotranspiration, ET), upscaling from the tower to the regional and global scales is still marred with uncertainties. Here, we explore this scale translation via the FLUXCOM-X framework, which links data from EC measurements and remote sensing to machine learning techniques to produce models for generating globally gridded products. In particular, we explore potential sources of uncertainty inherent to this pipeline and how these influence the resulting gridded products: training data quality including site-selection and coverage of in-situ data, and modelling distinct water flux components (i.e., transpiration (T) and abiotic evaporation) individually compared to total evapotranspiration.

Overall, changes in the FLUXCOM-X framework compared to previous versions (Jung et al. 2019) results in tangible improvements to the spatial and temporal patterns of the global evapotranspiration products. Furthermore, the predictions of a corresponding transpiration product provide an empirical estimate of plant controlled water fluxes. The resulting global T/ET ratios are consistent with current estimates from isotopic analyses, but with the advantage of high spatio-temporal coverage. Lessons learned from this analysis provide a more targeted line of inquiry into potential avenues for further improvements in global evapotranspiration modeling.

Jung, M., Koirala, S., Weber, U. et al. The FLUXCOM ensemble of global land-atmosphere energy fluxes. Sci Data 6, 74 (2019). https://doi.org/10.1038/s41597-019-0076-8

How to cite: Nelson, J. A., Walther, S., Kraft, B., Zhang, W., Duveiller, G., Gans, F., Weber, U., Hamdi, Z. M., and Jung, M.: From site-scale land-atmsophere water fluxes to globally gridded products: Advances with the FLUXCOM-X framework, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14103, https://doi.org/10.5194/egusphere-egu23-14103, 2023.

Accurate measurements of actual evapotranspiration (ETa) play an important role in understanding land surface processes and agricultural management. Two of the most commonly used and established methods for quantifying ETa are eddy covariance (EC) and weighable lysimeters measurements. Previous studies on hourly or daily basis indicated sometimes large differences between the ETa of the two methods (Δ_ly-EC). It is still unclear which factors influence these differences. Here, we examine and compare half-hourly ETa measurements from EC (ET_EC) and weighable lysimeters (ET_ly) at four different sites. The four sites span a climatic gradient from humid conditions at a pre-alpine (Fendt, DE) and a mid-mountain grassland (Rollesbroich, DE) to semi-arid conditions at two sites with a natural grass and shrub (Els Plans, ES) and a tree-grass ecosystem (Majadas de Tiétar, ES). We used a boosted regression tree method to identify environmental drivers of Δ_ly-EC during day and night at the half-hourly resolution.

Our results revealed that substantial differences were found with a mean annual Δ_ly-EC of 117 mm, and Δ_ly-EC displayed obvious spatiotemporal variabilities across the sites. Energy balance non-closure of EC was found to be the most important factor contributing to the large annual Δ_ly-EC, especially at Majadas de Tiétar site. With the distinct climatic gradient, Δ_ly-EC was negatively correlated with mean annual wind speed and vapor pressure deficit when they reached a specific level. Monthly ET_EC and ET_ly agreed well with Δ_ly-EC peaking in summer at the sites in Germany, while Δ_ly-EC peaked earlier due to the different climate in Spain. Differences in grass height caused by field management and EC footprint also affected Δ_ly-EC, especially at daily timescales for the pre-alpine and the mid-mountain grassland ecosystem. The relative impacts of different environmental variables to half-hourly ET_EC and ET_ly were almost the same with soil water content (SWC) being more important for nighttime ET_ly. Meanwhile, we found that the dominant controlling factors of daytime Δ_ly-EC changed with climatic conditions, but nighttime Δ_ly-EC were mainly regulated by SWC. These findings provide a critical evaluation for the roles of climatic and land surface conditions on turbulent flux dynamics from different measurements, which has important implications for ecosystem water and energy balance.

How to cite: Han, Q., Pütz, T., Vereecken, H., Wang, T., Graf, A., Mauder, M., Paulus, S., Lee, S.-C., El-Madany, T., Schneider, K., Price, J., Martínez-Villagrasa, D., Cuxart, J., and Groh, J.: Actual evapotranspiration differences between measurements of eddy covariance and lysimeters over grasslands, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8184, https://doi.org/10.5194/egusphere-egu23-8184, 2023.

Interception of a Norway spruce stand was analysed based on canopy water balance measurements E_mass and for Eddy Covariance (EC) related measurements. The study site is located in the Tharandt Forest (Germany) and the analysis covers a long period from 2008 to 2018. E_mass was calculated as residual between gross rainfall above and net rainfall below the canopy. EC related observations are based on the water equivalent either directly measured (uncorrected) by Eddy Covariance (ET_EC) or as residual in the Energy Balance equation (ET_EB). Additionally, evaporation of intercepted water was modelled with the Penman-Monteith equation, which was adapted for a gradually wetted canopy (E_Rutter) by the use of the Rutter model. The latter approach was used to integrate the time series of all methods over the duration of modelled interception events leading to different estimates of wet canopy evaporation.

The canopy water balance from 2008 to 2018 shows a mean annual gross precipitation of 936±173mm and a mean annual interception evaporation of 376±56mm (E_mass). The majority of rainfall events (81%) is characterized by a depth less than 5mm, which leads to a high fraction of annual precipitation being captured by the canopy surface (0.41). The application of the Rutter model yielded good results with a mean modelled annual interception E_Rutter of 361±47mm being very close to E_mass. Thus, the model served as a good standard to define interception events. The water equivalent of wet canopy evaporation as the residual of the energy balance ET_EB and from gas analyser measurements ET_EC are both systematically underestimating E_mass, to a higher extent for the winter than summer half-year. On a mean annual basis, ET_EB and ET_EC underestimate E_mass by 145mm and 288mm, respectively. Comparing the totals over the majority of interception events, ET_EB corresponds to only 72% and ET_EC to only 33% of canopy water balance based measurements.

One reason for this underestimation might be a scaling problem between the interception measurement site and the flux tower footprint, which could not be resolved by the application of a simple scaling factor. A more likely explanation is the underestimation of turbulent fluxes by the EC method. The data is most affected during raining conditions with the highest gap in winter. An annual analysis of the linear relation between the sum of turbulent fluxes and available energy shows the lowest slope (0.57±0.15) for measurements during rain, while the highest slopes occur under completely dry conditions (0.76±0.03). Wet canopy conditions without rainfall seem not to be as crucial for energy imbalance as rain, but affect the closure gap for the winter half-year.

Records of EC measurements are generally too low and the magnitude of supplied sensible heat and sustained latent heat flux rates during interception events remains unclear. We conclude that gap filling and correction of both turbulent fluxes should be done separately for rain (interception) and dry (transpiration) conditions in order to determine proper amounts of evapotranspiration with the eddy-covariance method.

How to cite: Fischer, S., Moderow, U., Queck, R., and Bernhofer, C.: Rainfall interception – a year-round crucial component of evapotranspiration and potential consequences for eddy-covariance measurements. Comparing long-term measurements of canopy water budget and eddy-covariance fluxes at a Norway spruce site, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14179, https://doi.org/10.5194/egusphere-egu23-14179, 2023.

Reliable, high-resolution evaporation data are needed for large-scale agricultural and hydrological management applications. However, field observations are too sparse to monitor large regions continuously, and satellite-based datasets are often too coarse or restricted to specific regions. An example of such satellite-based datasets is the Global Land Evaporation Amsterdam Model (GLEAM)¹. GLEAM is a state-of-the-art, global evaporation product which has been widely applied over the past decade in climate studies. However, due to its coarse original resolution (0.25 degree), it has not been used in hydrological and agricultural applications until recently². Ongoing developments have culminated in a high-resolution (HR, i.e. ~1 km) GLEAM version covering the Mediterranean region, over the 2015–2021 period. The Mediterranean region is characterised by intense human activities, different hydroclimatic conditions ranging from temperate cold to tropical, and intense seasonal rainfall at irregular spatial distributions. As a result, the region is prone to droughts, floods and landslides, making it an ideal testbed for GLEAM-HR. Here, we present current activities and future plans regarding this new dataset. Prospective plans include the extension from the Mediterranean domain to the entire European and African continents, by adopting a series of developments that have so far been confined to the coarse-scale application of the model. These include modifications in the interception module³, the incorporation of groundwater effects⁴, and the use of deep learning for the estimation of transpirational stress⁵.

¹ Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453–469, https://doi.org/10.5194/hess-15-453-2011, 2011.
² Martens, B., De Jeu, R. A. M., Verhoest, N. E. C., Schuurmans, H., Kleijer, J., and Miralles, D. G.: Towards estimating land evaporation at field scales using GLEAM. Remote Sens., 10, 1720, https://doi.org/10.3390/rs10111720, 2018.
³ Zhong, F., Jiang, S., van Dijk, A. I. J. M., Ren, L., Schellekens, J., and Miralles, D. G.: Revisiting large-scale interception patterns constrained by a synthesis of global experimental data, Hydrol. Earth Syst. Sci., 26, 5647–5667, https://doi.org/10.5194/hess-26-5647-2022, 2022.
⁴ Hulsman, P., Keune, J., Koppa, A., Schellekens, J., and Miralles, D. G: Incorporating plant access to groundwater in existing global, satellite-based evaporation estimates, ESS Open Archive, https://doi.org/10.1002/essoar.10512478.1, in review, 2022.
⁵ Koppa, A., Rains, D., Hulsman, P., Poyatos, R., and Miralles, D. G.: A deep learning-based hybrid model of global terrestrial evaporation, Nat. Commun., 13, 1912, https://doi.org/10.1038/s41467-022-29543-7, 2022.

How to cite: Hulsman, P., Koppa, A., and Miralles, D.: GLEAM-HR: current state and future prospects, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12253, https://doi.org/10.5194/egusphere-egu23-12253, 2023.

Remote sensing data provide valuable information on the spatial distribution of land surface conditions and properties, such as soil moisture, soil and vegetation water status. However, the frequency and resolution of remotely sensed data vary depending on the satellite and sensor. The frequency of observation of thermal infrared that allows an estimation of evapotranspiration is carried out daily by the satellites AQUA and TERRA (res. 1km), every 2 days by Sentinel-3 (res. 1km), 8 days by LANDSAT-8 and 9 (res. 60m) and will be 3 times per period of 8 days by the satellite TRISHNA (res. 60m). In addition, there is no data on days with heavy cloud cover. In order to obtain a daily evaluation of ET, we propose to correct the trajectory of a surface model based on the water balance with the assimilation of ET data from remote sensing. The question is what are the advantages of assimilation compared to open-loop or interpolation of observation. We present our work on modelling evapotranspiration and irrigation at the field scale with the SAMIR (Satellite monitoring of irrigation) model. This is a crop water balance model forced by weather data, soil and crop parameters to simulate the daily components of the water balance. A particle filter method is implemented to assimilate evapotranspiration from remote sensing. This evaluation is performed on several types of crops (wheat, barley and olive), irrigated or not, and in a semi-arid Mediterranean context (Tunisia and Morocco). Compared to open loop simulations, data assimilation allows to quickly reduce the simulation uncertainty. On the other hand, the higher the revisit frequency, the more the simulation uncertainty depends on the observation uncertainty and the model uncertainty is reduced.

How to cite: Ollivier, C., Olivera-Guerra, L., Laluet, P., Rivalland, V., Simonneaux, V., Demarty, J., Merlin, O., and Boulet, G.: The contribution of remote sensing data assimilation to simulate daily evapotranspiration of irrigated and non-irrigated crops in semi-arid context, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15128, https://doi.org/10.5194/egusphere-egu23-15128, 2023.

Remote sensing data play an important role in understanding the spatio-temporal variations in hydro-meteorological conditions at different spatial scales. In particular, one of the key processes of hydrological cycle for monitoring water loss from space is evapotranspiration (ET). In contrast to sparsely distributed in-situ measurements, development of two surface energy balance (TSEB) models forced by satellite observations has made a significant contribution to estimate ET with global coverage. In this regard, in the framework of ESA’s 4DMED-Hydrology project, we combine Copernicus data from Sentinel-2 (S2) Multispectral Instrument (MSI) and Sentinel-3 (S3) Land Surface Temperature Radiometer (SLSTR) with ERA5 climate reanalysis dataset derived within the period 2017-2021 for daily ET retrieval at high (100 m) spatial resolution. In this work, an open-source implementation of TSEB developed in the framework of the ESA’s Sen-ET project has been applied over wide areas represented by four Mediterranean basins in Italy, Spain, France, and Tunisia (Po, Ebro, Hérault and Medjerda). Considering large volume of satellite data and high computational requirements of the Sen-ET, all processes have been optimized to be run in the automatic manner by combining multiple steps into one processing workflow utilized in cloud computing platforms offered by EODC and ESA HPC of CloudFerro. First, due to incomplete time-series of S2 Level-2A, we pre-process Sentinel-2 data for further retrieval of 100-m reflectance and biophysical parameters needed for the ET estimation afterwards. Next, we downscale S3 land surface temperature (LST) product by exploiting relationships between 1-km Sentinel-3 and time-coincident 100-m S2 reflectances using decision trees (DT) algorithm. Apart from biophysical properties (e.g., leaf area index and fractional vegetation cover) and sharpened LST data, meteorological forcings and solar radiation from ERA5 have been generated for estimating instantaneous energy fluxes and daily evapotranspiration. Based on preliminary results over Po basin, DT algorithm allowed predicting 100-m LST with the average root mean square error (RMSE) of 3.2°C when compared to ground-derived skin temperature from two eddy covariance (EC) towers. Meanwhile, turbulent fluxes driven by downscaled LST resulted in RMSE equal to 52 Wm^-2 and 108 Wm^-2 for sensible and latent heat fluxes, respectively. Despite some limitations mainly related to the EC locations in complex mountain areas, ET estimates forced by satellite observations have potential for providing energy fluxes at wider scale.

Keywords: evapotranspiration, Sentinel-3, land surface temperature, Mediterranean region

How to cite: Bartkowiak, P., Castelli, M., Ventura, B., and Jacob, A.: Large scale two-source energy balance modelling of evapotranspiration over Mediterranean region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8428, https://doi.org/10.5194/egusphere-egu23-8428, 2023.

To bypass the thermal data requirement for actual evapotranspiration (ET_a) estimation in satellite remote sensing, two general approaches have been taken into practice based on previous efforts: (1) Multi-sensor data fusion for thermal sharpening and (2) the use of the process-based models such as the Penman-Monteith and Shuttleworth-Wallace equations augmented with satellite-based crop parameters. To address this issue, this study introduced an optical satellite data-based ET_a estimation model, OPTRAM-ET, based on the optical trapezoid model (OPTRAM) estimates of soil moisture. The new model has been applied to Sentinel-2 and Landsat-8 images over 16 eddy covariance flux towers in the United States and Germany. The flux towers were chosen in a way to cover different ranges of landcover types, e.g., agriculture, orchard, permanent wetlands, and foothill forests. In order to assess the model in comparison to a thermal-based conventional method, the land surface temperature (LST)-vegetation index (VI) model was utilized. The results of the proposed OPTRAM-ET model showed promising performance in all the studied regions. While agricultural sites showed higher correlation due to their wider range of ET_a values, error indicators were lower in foothill forests because soil moisture changes were smaller compared to irrigated and wet lands. In addition, the OPTRAM-ET model showed comparable performance to the conventional LST-VI model. The OPTRAM-ET model however does not need thermal data, and it benefits from higher spatial and temporal resolution data provided by ever-increasing drone- and satellite-based optical sensors to predict crop water status and demand. It is worth noting that the thermal sharpening step was excluded in this model which subsequently makes the model substantially less computationally demanding than a thermal-based model. Unlike the LST-VI model, which needs to be calibrated for each satellite image, a temporally-invariant region-specific calibration is possible in the OPTRAM-ET model. Importantly, the model requires further enhancement due to limitations caused by the simplified basic assumptions.

How to cite: Mokhtari, A., Sadeghi, M., Afrasiabian, Y., and Yu, K.: A novel method for actual evapotranspiration from a soil moisture optical trapezoid model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9385, https://doi.org/10.5194/egusphere-egu23-9385, 2023.

Agriculture is the largest consumer of water worldwide, accounting for about 70% of the global freshwater      withdrawals. Thus, crop water use efficiency and impacts of water stress on crop water consumption are the key concerns for agricultural water management.

Present study investigates the variability of evapotranspiration (ET) and crop water use efficiency by integrating very high spatial resolution (1 – 4 m) thermal infrared (TIR) data from airborne measurements and visible to near infrared data from Planet satellite with a numerical water-energy balance model and a diagnostic surface energy balance model.     

The analysis is done for an intensive agriculture area in central Italy near the city of Modena, where several fruit trees fields are present along with fresh vegetables. An intensive airborne campaign was organized in the summer of 2022 for three consecutive days in July. A hyperspectral TIR camera (Telops Hyper-Cam LW) has been operated at a spectral resolution of 8 cm-1, resulting in 64 wavebands, and covering a wavelength range of 850 cm-1 to 1350 cm-1 (7,39 µm – 11,8 µm).  During the 3 days of flight acquisitions, three overpasses per day are planned: 9:00, 12:30 and 16:00 h, respectively and two areas were intensively      surveyed at both 4 and 1 m spatial resolution. Planet data at 3.7 m spatial resolution were used to derive different vegetation indices, such as vegetation fraction coverage, NDVI and leaf area index. During airborne overpasses ground data of spectral reflectance, vegetation variables, LST and soil water content (SM) were collected in different fields. In addition, two different pear trees fields were monitored with an eddy covariance station and soil moisture profile measurements, respectively.

To investigate the diurnal and spatial patterns of evapotranspiration, soil moisture variability and crop water use efficiency, we used two numerical models: the surface energy balance model STIC based on Penman-Monteith and Shuttleworth-Wallace (Mallick et al., 2018) and the water-energy balance model FEST-EWB which computes continuously in time and is distributed in space soil moisture and evapotranspiration fluxes solving for a land surface temperature that closes the energy–water balance equations (Corbari et al., 2011).

Differences and similarities in ET estimates have been analysed from the two models for different soil moisture conditions and crop types, considering crop water use efficiency and water stress, and have been compared to eddy covariance measurements for accuracy evaluation considering both instantaneous and daily data. The assimilation of instantaneous estimates of ET into the water-energy balance model allowed to directly derived soil moisture maps at high spatial resolution which have been found in agreement with ground SM measurements.

How to cite: Corbari, C., Paciolla, N., Hu, T., Ronellenfitsch, F. K., Schlerf, M., Bossung, C., Ceppi, A., Feki, M., Llorens, R., Skokovic Jovanovic, D., Al Bitar, A., Mallick, K., Sobrino, J., and Mancini, M.: Evapotranspiration and crop water use efficiency from airborne thermal infrared data at 1 to 4 m spatial resolution, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7291, https://doi.org/10.5194/egusphere-egu23-7291, 2023.