Modeling Surface Energy Fluxes over a Dehesa (Oak Savanna) Ecosystem Using a Thermal Based Two-Source Energy Balance Model (TSEB) I

Savannas are among the most variable, complex and extensive biomes on Earth, supporting livestock and rural livelihoods. These water-limited ecosystems are highly sensitive to changes in both climatic conditions, and land-use/management practices. The integration of Earth Observation (EO) data into process-based land models enables monitoring ecosystems status, improving its management and conservation. In this paper, the use of the Two-Source Energy Balance (TSEB) model for estimating surface energy fluxes is evaluated over a Mediterranean oak savanna (dehesa). A detailed analysis of TSEB formulation is conducted, evaluating how the vegetation architecture (multiple layers) affects the roughness parameters and wind profile, as well as the reliability of EO data to estimate the ecosystem parameters. The results suggest that the assumption of a constant oak leaf area index is acceptable for the purposes of the study and the use of spectral information to derive vegetation indices is sufficiently accurate, although green fraction index may not reflect phenological conditions during the dry period. Although the hypothesis for a separate wind speed extinction coefficient for each layer is partially addressed, the results show that taking a single oak coefficient is more precise than using bulk system coefficient. The accuracy of energy flux estimations, with an adjusted Priestley–Taylor coefficient (0.9) reflecting the conservative water-use tendencies of this semiarid vegetation and a roughness length formulation which integrates tree structure and the low fractional cover, is considered adequate for monitoring the ecosystem water use (RMSD ~40W m-2)

Uso de sensores remotos en el seguimiento de la vegetación de dehesa y su influencia en el balance hidrológico a escala de cuenca

The Mediterranean region is characterized by hot summers with long dry periods, a situation that may be exacerbated by the progressive global warming. In these water-limited environments where productivity of the ecosystems depends mainly on water availability, the reduction of freshwater resources can have severe consequences. An increase in aridity may lead to low productivity, land degradation and unwanted changes in land use. To reduce the vulnerability of Mediterranean landscapes it is important to improve our knowledge of the hydrological processes conditioning the water exchanges, with evapotranspiration (ET) being a key indicator of the state of ecosystems and playing a crucial role in the basin's water and energy balances. The goal of this dissertation is to improve our understanding of the evapotranspiration dynamics over Mediterranean heterogeneous and complex vegetation covers, with a focus on the dehesa ecosystem. The final aim is to contribute to the conservation of the water resources in these regions in the medium to long term, supporting the decision-making processes with quantitative, distributed, and high-quality information. To reach this goal, in this research the evaluation of remote sensing-based soil water balance (SWB) and surface energy balance (SEB) models was proposed to monitor the water consumption and water stress of typical Mediterranean vegetation at different spatial and temporal scales. In particular, the VI-ETo methodology (SWB) and the ALEXI/DisALEXI approach (SEB) have been adapted and applied. ET modeling using the VI-ETo scheme has been improved through the assessment of the vegetation layers' effective parameters. A data fusion algorithm was applied to the ET maps produced by the SEB model over the dehesa ecosystem, and we analyzed the opportunities that this high-resolution ET product in time and space can provide for water and vegetation resource management. The results have demonstrated the feasibility of both approaches (SWB and SEB models) to accurately monitor ET dynamics over the dehesa landscape, adequately reproducing the annual bimodal behavior and the response of the vegetation in periods of water deficit. The error obtained using the SWB approach (the VI-ETo method) was RMSE = 0.47 mm day-1 over the whole dehesa system (grass + trees) and over an open grassland. The monitoring of water stress for both systems with different canopy structure, using as a proxy the ET/ETo ratio, and the stress coefficient (Ks), was successful. Improvements on the specific spectral properties of oak trees and layer-specific parameters were included into the modeling. We also analyzed the influence of the spectral properties of oak trees and another typical Mediterranean tree canopy, the olive orchard, in the VI-ETo model. We found that the use of appropriate values of the parameter SAVImax (0.51 for oak trees and 0.57 for olive trees) had notable implications in the computation of ET and water stress, in contrast to using a generic value for Mediterranean crops (SAVImax= 0.75). The accuracy of this water balance-based approach was also evaluated over two heterogeneous Mediterranean basins, with a mosaic of holm oaks and grasslands, shrubs, coniferous plantations, and irrigated horticultural crops. The annual discharge flows of both watersheds, which were determined from the modeled ET data and using a simple surface water balance, were very similar to those obtained with the HBV hydrological model, and to the values measured at the outlet of one of the basins, corroborating the usefulness of the VI-ETo methodology on these vegetation types. On the other hand, the resulting ET series (30 m, daily) derived with the SEB approach (ALEXI/DisALEXI method) and the STARFM fusion algorithm provided an RMSE value of 0.67 mm day-1, which was considered an acceptable error for management purposes. This error was slightly lower compared to using simpler interpolation methods, probably due to the high temporal frequency and better spatial representation of the flux tower footprint of the fused time series. The analysis of ET patterns over small heterogeneous vegetated patches that form the dehesa structure revealed the importance of having fine resolution information at field scale to distinguish the water consumed by the different vegetation components, which influences the provision of many ecosystem services. For example, it was key for identifying phenology dates of grasslands, or understanding the hydrological functioning of riverside dense evergreen vegetation with high ET rates during the whole year, in contrast with the herbaceous areas. Accurately modeling these different behaviors of dehesa microclimates is useful to support farmers‘ management and provide recommendations tailored for each structural component and requirements.La región mediterránea se caracteriza por veranos calurosos con largos períodos sin precipitaciones, situación que puede agravarse con el progresivo calentamiento global. En estos ambientes donde la productividad de los ecosistemas depende principalmente de la disponibilidad de agua, la reducción de los recursos hídricos puede tener graves consecuencias. Un aumento de la aridez puede conducir a una baja productividad, degradación de la tierra y cambios no deseados en el uso del suelo. Para reducir la vulnerabilidad de las zonas mediterráneas es importante profundizar en el estudio de los procesos hidrológicos que condicionan los intercambios de agua, siendo la evapotranspiración (ET) un indicador clave del estado de los ecosistemas y jugando un papel crucial en los balances hídricos y energéticos de la cuenca. El objetivo de esta tesis es mejorar nuestro conocimiento sobre la dinámica de la evapotranspiración en cubiertas mediterráneas heterogéneas y complejas, con el foco en el ecosistema de dehesa. El objetivo final es contribuir a la conservación de los recursos hídricos de estas regiones en el medio-largo plazo, apoyando en los procesos de toma de decisiones con información cuantitativa, distribuida y de calidad. Para alcanzar este objetivo, en esta investigación se propuso evaluar modelos de balance de agua en el suelo (SWB) y balance de energía en superficie (SEB) basados en el uso de sensores remotos, para el seguimiento del consumo de agua y el estrés hídrico de la vegetación mediterránea a diferentes escalas espaciales y temporales. En particular, se ha adaptado y aplicado la metodología VI-ETo (SWB) y el enfoque ALEXI/DisALEXI (SEB). Se ha mejorado el modelado de ET utilizando el esquema VI-ETo mediante la evaluación de los parámetros efectivos de las capas de vegetación. Se aplicó un algoritmo de fusión de datos remotos a los mapas de ET generados por el modelo SEB sobre el ecosistema de dehesa, y estudiamos las oportunidades que este producto de ET con alta resolución espacial y temporal puede aportar en la gestión de los recursos hídricos y de los ecosistemas. Los resultados han demostrado la viabilidad de ambos enfoques (modelos SWB y SEB) para monitorear con precisión la dinámica de la ET sobre el ecosistema de dehesa, reproduciendo adecuadamente el comportamiento bimodal anual y la respuesta de la vegetación en períodos de déficit hídrico. El error obtenido usando el enfoque SWB (el método VI-ETo) fue RMSE = 0.47 mm día-1, tanto para el sistema dehesa (pasto + árboles) como para una zona de pastizal. El seguimiento del estrés hídrico para ambos sistemas con diferente estructura de vegetación, utilizando la relación ET/ETo y el coeficiente de estrés (Ks), fue satisfactorio. Se incluyeron en el modelado mejoras sobre las propiedades espectrales específicas de las encinas y los parámetros específicos de los diferentes estratos de vegetación. También analizamos la influencia de las propiedades espectrales de las encinas y otra cubierta mediterránea, el olivar, en el modelo VI-ETo. Encontramos que el uso de valores apropiados del parámetro SAVImax (0,51 para robles y 0,57 para olivos) tuvo un efecto significativo en la determinación del consumo de agua y estrés hídrico, en comparación con usar un valor genérico para cultivos mediterráneos (SAVImax = 0,75). La precisión de este enfoque basado en el balance hídrico también se evaluó en dos cuencas mediterráneas heterogéneas, con un mosaico de encinas y pastizales, arbustos, plantaciones de coníferas y cultivos hortícolas de regadío. Los caudales de descarga anual de ambas cuencas, determinados a partir de los datos de ET modelados y utilizando un balance hídrico superficial muy simple, fueron muy similares a los obtenidos con el modelo hidrológico HBV, y a los valores medidos en la salida de una de las cuencas, corroborando la utilidad de la metodología VI-ETo sobre estas formaciones vegetales. Por otra parte, la serie final de ET (30 m, diaria) derivada del enfoque SEB (método ALEXI/DisALEXI) y del algoritmo de fusión STARFM proporcionó un valor de RMSE de 0,67 mm día-1, considerado un error aceptable para fines de manejo. Este error fue ligeramente inferior a los obtenidos usando métodos de interpolación más simples, debido probablemente a la alta frecuencia temporal y una mejor representación espacial del footprint de la torre de medida de flujos en la serie temporal fusionada. El análisis de los patrones de la ET sobre pequeñas manchas de vegetación heterogéneas, que forman la estructura de la dehesa, reveló la importancia de tener información con alta resolución a escala de campo para distinguir el agua consumida por los diferentes componentes de la vegetación, que tienen influencia en el aprovisionamiento de muchos servicios ecosistémicos. Por ejemplo, fue clave para identificar ciertas fechas fenológicas de los pastizales, o entender el funcionamiento hidrológico de la vegetación densa de hoja perenne en zonas de ribera con altas tasas de ET durante todo el año, en comparación con zonas de especies herbáceas. Modelar con precisión estos comportamientos diferentes de los microclimas de la dehesa es útil para apoyar la gestión de los agricultores y ofrecer recomendaciones adaptadas a cada componente y necesidades estructurales

Remote sensing of water use and water stress in the African savanna ecosystem at local scale – Development and validation of a monitoring tool

Savannas are among the most productive biomes of Africa, where they comprise half of its surface. They support wildlife, livestock, rangelands, crops, and livelihoods, playing an important socioeconomic role in rural areas. These water-limited ecosystems with seasonal water availability are highly sensitive to changes in both climate conditions, and in land-use/management practices. Although monitoring programs for African savanna water use have been established in certain areas, most of them are largely restricted to point based measurements or coarse scales, and are not fully capable to provide distributed timely information for planning purposes. In this study we develop a mechanism for monitoring the water used by African savanna from fine scale (meters) to watershed scale, integrating the effects of the water stress. Our hypothesis is that the Ecosystem Stress Index (ESI) is a valuable tool to downscale estimates of actual evapotranspiration at coarse scale, to high resolutions. To monitor savanna water fluxes in a semi-continuous way this study integrates two different ET-estimation approaches: KC-FAO56 model, integrating reflectance-based “crop” coefficients (SPOT 4 & 5 satellites), is used to derive unstressed savanna evapotranspiration (with high spatial resolution), and the two-source surface energy balance model -TSEB, integrating radiometric surface temperature (AATSR satellites) allows the determination of water stress across savannas (ESI, with low spatial resolution). The difference between estimated and observed surface fluxes derived from TSEB (RMSDLE = 53 Wm-2, RMSDH = 50 Wm-2, RMSDRn = 60 Wm-2, RMSDG = 21 Wm-2) were of the same magnitude as the uncertainties derived from the flux measurement system, being sufficiently accurate to be employed in a distributed way and on a more regular basis. The approach of ESI to downscale ET proved to be useful, and errors between estimated and observed daily ET (RMSD 0.6 mmday−1) were consistent with the results of other studies in savanna ecosystems. The modelling framework proposed provided an accurate representation of the natural landscape heterogeneity and local conditions, with the potential of providing information suitable from local to broader scales.info:eu-repo/semantics/publishedVersio

Long-Term water stress and drought assessment of Mediterranean oak savanna vegetation using thermal remote sensing

Drought is a devastating natural hazard that is difficult to define, detect and quantify. The increased availability of both meteorological and remotely sensed data provides an opportunity to develop new methods to identify drought conditions and characterize how drought changes over space and time. In this paper, we applied the surface energy balance model, SEBS (Surface Energy Balance System), for the period 2001 2018, to estimate evapotranspiration and other energy fluxes over the dehesa area of the Iberian Peninsula, with a monthly temporal resolution and 0.05° pixel size. A satisfactory agreement was found between the fluxes modeled and the measurements obtained for 3 years by two flux towers located over representative sites (RMSD = 21 W m-2 and R2 = 0.76, on average, for all energy fluxes and both sites). The estimations of the convective fluxes (LE and H) showed higher deviations, with RMSD = 26 W m-2 on average, than Rn and G, with RMSD = 15 W m-2. At both sites, annual evapotranspiration (ET) was very close to total precipitation, with the exception of a few wet years in which intense precipitation events that produced high runoff were observed. The analysis of the anomalies of the ratio of ET to reference ET (ETo) was used as an indicator of agricultural drought on monthly and annual scales. The hydrological years 2004/2005 and 2011/2012 stood out for their negative values. The first one was the most severe of the series, with the highest impact observed on vegetation coverage and grain production. On a monthly scale, this event was also the longest and most intense, with peak negative values in January February and April May 2005, explaining its great impact on cereal production (up to 45 % reduction). During the drier events, the changes in the grasslands and oak trees ground cover allowed for a separate analysis of the strategies adopted by the two strata to cope with water stress. These results indicate that the drought events characterized for the period did not cause any permanent damage to the vegetation of dehesa systems. The approach tested has proven useful for providing insight into the characteristics of drought events over this ecosystem and will be helpful to identify areas of interest for future studies at finer resolutions

Seasonal adaptation of the thermal‐based two‐source energy balance model for estimating evapotranspiration in a semiarid tree‐grass ecosystem

© 2020 by the authors.The thermal-based two-source energy balance (TSEB) model has accurately simulated energy fluxes in a wide range of landscapes with both remote and proximal sensing data. However, tree-grass ecosystems (TGE) have notably complex heterogeneous vegetation mixtures and dynamic phenological characteristics presenting clear challenges to earth observation and modeling methods. Particularly, the TSEB modeling structure assumes a single vegetation source, making it difficult to represent the multiple vegetation layers present in TGEs (i.e., trees and grasses) which have different phenological and structural characteristics. This study evaluates the implementation of TSEB in a TGE located in central Spain and proposes a new strategy to consider the spatial and temporal complexities observed. This was based on sensitivity analyses (SA) conducted on both primary remote sensing inputs (local SA) and model parameters (global SA). The model was subsequently modified considering phenological dynamics in semi-arid TGEs and assuming a dominant vegetation structure and cover (i.e., either grassland or broadleaved trees) for different seasons (TSEB-2S). The adaptation was compared against the default model and evaluated against eddy covariance (EC) flux measurements and lysimeters over the experimental site. TSEB-2S vastly improved over the default TSEB performance decreasing the mean bias and root-mean-square-deviation (RMSD) of latent heat (LE) from 40 and 82 W m−2 to −4 and 59 W m−2, respectively during 2015. TSEB-2S was further validated for two other EC towers and for different years (2015, 2016 and 2017) obtaining similar error statistics with RMSD of LE ranging between 57 and 63 W m−2. The results presented here demonstrate a relatively simple strategy to improve water and energy flux monitoring over a complex and vulnerable landscape, which are often poorly represented through remote sensing models.The research received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 721995. It was also funded by Ministerio de Economía y Competitividad through FLUXPEC CGL2012-34383 and SynerTGE CGL2015-G9095-R (MINECO/FEDER, UE) projects. The research infrastructure at the measurement site in Majadas de Tiétar was partly funded through the Alexander von Humboldt Foundation, ELEMENTAL (CGL 2017-83538-C3-3-R, MINECO-FEDER) and IMAGINA (PROMETEU 2019; Generalitat Valenciana).Peer reviewe

A remote sensing-based three-source energy balance model to improve global estimations of evapotranspiration in semi-arid tree-grass ecosystems

It is well documented that energy balance and other remote sensing-based evapotranspiration (ET) models face greater uncertainty over water-limited tree-grass ecosystems (TGEs), representing nearly 1/6th of the global land surface. Their dual vegetation strata, the grass-dominated understory and tree-dominated overstory, make for distinct structural, physiological and phenological characteristics, which challenge models compared to more homogeneous and energy-limited ecosystems. Along with this, the contribution of grasses and trees to total transpiration (T), along with their different climatic drivers, is still largely unknown nor quantified in TGEs. This study proposes a thermal-based three-source energy balance (3SEB) model, accommodating an additional vegetation source within the well-known two-source energy balance (TSEB) model. The model was implemented at both tower and continental scales using eddy-covariance (EC) TGE sites, with variable tree canopy cover and rainfall (P) regimes and Meteosat Second Generation (MSG) images. 3SEB robustly simulated latent heat (LE) and related energy fluxes in all sites (Tower: LE RMSD ~60 W/m2; MSG: LE RMSD ~90 W/m2), improving over both TSEB and seasonally changing TSEB (TSEB-2S) models. In addition, 3SEB inherently partitions water fluxes between the tree, grass and soil sources. The modelled T correlated well with EC T estimates (r > .76), derived from a machine learning ET partitioning method. The T/ET was found positively related to both P and leaf area index, especially compared to the decomposed grass understory T/ET. However, trees and grasses had contrasting relations with respect to monthly P. These results demonstrate the importance in decomposing total ET into the different vegetation sources, as they have distinct climatic drivers, and hence, different relations to seasonal water availability. These promising results improved ET and energy flux estimations over complex TGEs, which may contribute to enhance global drought monitoring and understanding, and their responses to climate change feedbacks.The research received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie TRuStEE project (grant agreement No 721995). It was also funded by Ministerio de Economía y Competitividad through SynerTGE CGL2015-G9095-R funded by MCIN/ AEI /10.13039/501100011033/ FEDER ‘a way of making Europe’. The study also benefitted from the DIVERSPEC-TGA project, funded by the Ministerio de Ciencia e Innovación of Spain MCIN/ AEI /10.13039/501100011033. The infrastructure at ES-LM1 was partly funded through the Alexander von Humboldt Foundation, ELEMENTAL (CGL 2017-83538-C3-3-R, MINECO-FEDER) and IMAGINA (PROMETEU 2019; Generalitat Valenciana). Funding for the US-Ton AmeriFlux site was provided by the U.S. Department of Energy's Office of Science. This research was also supported by the NASA Ecostress project. We thank Siyan Ma for contributing to the collection and processing of US-Ton’s in situ data. USDA is an equal opportunity provider and employer.Peer reviewe

UAS-based high resolution mapping of evapotranspiration in a Mediterranean tree-grass ecosystem

Este artículo está sujeto a una licencia CC BY 4.0Understanding the impact of land use and land cover change on surface energy and water budgets is increasingly important in the context of climate change research. Eddy covariance (EC) methods are the gold standard for high temporal resolution measurements of water and energy fluxes, but cannot resolve spatial heterogeneity and are limited in scope to the tower footprint (few hundred meter range). Satellite remote sensing methods have excellent coverage, but lack spatial and temporal resolution. Long-range unmanned aerial systems (UAS) can complement these other methods with high spatial resolution over larger areas. Here we use UAS thermography and multispectral data as inputs to two variants of the Two Source Energy Balance Model to accurately map surface energy and water fluxes over a nutrient manipulation experiment in a managed semi-natural oak savanna from peak growing season to senescence. We use energy flux measurements from 6 EC stations to evaluate the performance of our method and achieve good accuracy (RMSD ≈ 60 W m− 2 for latent heat flux). We use the best performing latent heat estimates to produce very high-resolution evapotranspiration (ET) maps, and investigate the drivers of ET change over the transition to the senescence period. We find that nitrogen and nitrogen plus phosphorus treatments lead to significant increases in ET (P < 0.001) for both trees (4 and 6%, respectively) and grass (12 and 9%, respectively) compared to the control. These results highlight that the high sensitivity and spatial and temporal resolution of a UAS system allows the precise estimation of relative water and energy fluxes over heterogeneous vegetation cover.This research was supported by the DAAD/BMBF program Make Our Planet Great Again – German Research Initiative Project MONSOON (grant number 57429870).Peer reviewe

Implications of Soil and Canopy Temperature Uncertainty in the Estimation of Surface Energy Fluxes Using TSEB2T and High-Resolution Imagery in Commercial Vineyards

Estimation of surface energy fluxes using thermal remote sensing–based energy balance models (e.g., TSEB2T) involves the use of local micrometeorological input data of air temperature, wind speed, and incoming solar radiation, as well as vegetation cover and accurate land surface temperature (LST). The physically based Two-source Energy Balance with a Dual Temperature (TSEB2T) model separates soil and canopy temperature (Ts and Tc) to estimate surface energy fluxes including Rn, H, LE, and G. The estimation of Ts and Tc components for the TSEB2T model relies on the linear relationship between the composite land surface temperature and a vegetation index, namely NDVI. While canopy and soil temperatures are controlling variables in the TSEB2T model, they are influenced by the NDVI threshold values, where the uncertainties in their estimation can degrade the accuracy of surface energy flux estimation. Therefore, in this research effort, the effect of uncertainty in Ts and Tc estimation on surface energy fluxes will be examined by applying a Monte Carlo simulation on NDVI thresholds used to define canopy and soil temperatures. The spatial information used is available from multispectral imagery acquired by the AggieAir sUAS Program at Utah State University over vineyards near Lodi, California as part of the ARS-USDA Agricultural Research Service’s Grape Remote Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) project. The results indicate that LE is slightly sensitive to the uncertainty of NDVIs and NDVIc. The observed relative error of LE corresponding to NDVIs uncertainty was between -1% and 2%, while for NDVIc uncertainty, the relative error was between -2.2% and 1.2%. However, when the combined NDVIs and NDVIc uncertainties were used simultaneously, the domain of the observed relative error corresponding to the absolute values of |ΔLE| was between 0% and 4%

Can we use satellite-based soil-moisture products at high resolution to investigate land-use differences and land-atmosphere interactions? a case study in the savanna

The use of soil moisture (SM) measurements from satellites has grown in recent years, fostering the development of new products at high resolution. This opens the possibility of using them for certain applications that were normally carried out using in situ data. We investigated this hypothesis through two main analyses using two high-resolution satellite-based soil moisture (SBSM) products that combined microwave with thermal and optical data: (1) The Disaggregation based on Physical And Theoretical scale Change (DISPATCH) and, (2) The Soil Moisture Ocean Salinity-Barcelona Expert Center (SMOS-BEC Level 4). We used these products to analyse the SM differences among pixels with contrasting vegetation. This was done through the comparison of the SM measurements from satellites and the measurements simulated with a simple antecedent precipitation index (API) model, which did not account for the surface characteristics. Subsequently, the deviation of the SM from satellite with respect to the API model (bias) was analysed and compared for contrasting land use categories. We hypothesised that the differences in the biases of the varied categories could provide information regarding the water retention capacity associated with each type of vegetation. From the satellite measurements, we determined how the SM depended on the tree cover, i.e., the denser the tree cover, the higher the SM. However, in winter periods with light rain events, the tree canopy could dampen the moistening of the soil through interception and conducted higher SM in the open areas. This evolution of the SM differences that depended on the characteristics of each season was observed both from satellite and from in situ measurements taken beneath a tree and in grass on the savanna landscape. The agreement between both types of measurements highlighted the potential of the SBSM products to investigate the SM of each type of vegetation. We found that the results were clearer for DISPATCH, whose data was not smoothed spatially as it was in SMOS-BEC. We also tested whether the relationships between SM and evapotranspiration could be investigated using satellite data. The answer to this question was also positive but required removing the unrealistic high-frequency SM oscillations from the satellite data using a low pass filter. This improved the performance scores of the products and the agreement with the results from the in situ data. These results demonstrated the possibility of using SM data from satellites to substitute ground measurements for the study of land–atmosphere interactions, which encourages efforts to improve the quality and resolution of these measurements