Disentangling ecosystem transpiration from evapotranspiration observations employing simplified vegetation-substrate energy balance model

2020 ◽  
Author(s):  
Kaniska Mallick ◽  
Dennis Baldocchi ◽  
Andrew Jarvis ◽  
Ivonne Trebs ◽  
Mauro Sulis ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Energy Balance ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Energy Balance Model ◽  
Arid Ecosystems ◽  
Balance Model ◽  
Area Index ◽  
Availability Constraints

<p>Evapotranspiration (E<sub>ET</sub>) observed by eddy covariance (EC) towers is composed of physical evaporation (E<sub>E</sub>) from wet surfaces and biological transpiration (E<sub>T</sub>), that involves soil moisture uptake by roots and water vapor transfer regulated through the canopy-stomatal conductance (g<sub>C</sub>) during photosynthesis. E<sub>T</sub> plays a dominant role in the global water cycle and represents 80% of the total terrestrial E<sub>ET</sub>. Understanding the magnitude and variability of E<sub>T</sub> are critical to assess the ecophysiological responses of vegetation to drought. While separating E<sub>T</sub> signals from lumped E<sub>ET</sub> observations and/or simulating E<sub>T</sub> by terrestrial systems models is insufficiently constrained owing to the large uncertainties in disentangling g<sub>C</sub> from the aggregated canopy-substrate conductance (g<sub>cS</sub>), evaluating ecosystem E<sub>T</sub> derived through partitioning E<sub>ET</sub> observations (or model simulation) is also challenging due to the absence of any ecosystem-scale measurements of this biotic flux and g<sub>C</sub>. To date, the main methods for partitioning EC-E<sub>ET</sub> observations are largely based on regressing E<sub>ET</sub> with gross photosynthesis (P<sub>g</sub>) and atmospheric vapor pressure deficit (D<sub>A</sub>) observations. However, such methods ignore the essential feedback of the surface energy balance (SEB) and canopy temperature (T<sub>C</sub>) on g<sub>C</sub> and E<sub>T</sub>.</p><p>This study demonstrates partitioning E<sub>ET</sub> observations into E<sub>T</sub> and E<sub>E</sub> [soil evaporation (E<sub>Es</sub>) and interception evaporation (E<sub>Ei</sub>)] through an ‘analytical solution’ of g<sub>C</sub>, T<sub>C</sub> and canopy vapor pressures by employing a Shuttleworth-Gurney vegetation-substrate energy balance model with minimal complexity. The model is called TRANSPIRE (Top-down partitioning evapotRANSPIRation modEl), which ingests remote sensing land surface temperature (LST) and leaf area index (L<sub>ai</sub>) information in conjunction with meteorological, sensible heat flux (H) and E<sub>ET</sub> observations from EC tower into the SEB equations for retrieving canopy and soil temperatures (T<sub>S</sub>, T<sub>C</sub>), g<sub>C</sub>, and E<sub>T</sub>.</p><p>E<sub>T</sub> estimates from TRANSPIRE were tested and evaluated with a remote sensing based E<sub>T</sub> estimate from an analytical model (STIC1.2), where lumped E<sub>ET</sub> was partitioned by employing a moisture availability constraints across an aridity gradient in the North Australian Tropical Transect (NATT) by using time-series of 8-day MODIS Terra LST and LAI products in conjunction with EC measurements from 2011 to 2018. Both methods captured the seasonal pattern of E<sub>T</sub>/E<sub>ET</sub> ratio in a very similar way. While E<sub>T</sub> accounted for 60±10% of the annual E<sub>ET</sub> in the tropical savanna, E<sub>T</sub> in the arid mulga contributed 75±12% of the annual E<sub>ET</sub>. Seasonal variation of E<sub>T</sub> was higher in the arid, semi-arid ecosystems (50 - 90%), as compared to the humid tropical ecosystem (10 - 50%). The TRANSPIRE model reasonably captured E<sub>T</sub> variations along with soil moisture and precipitation dynamics in both sparse and homogeneous vegetation and showed the potential of partitioning E<sub>ET</sub> observations for cross-site comparison with a variety of models.</p>

scholarly journals Evaluation of Multiple Methods for the Production of Continuous Evapotranspiration Estimates from TIR Remote Sensing

2021 ◽  
Vol 13 (6) ◽  
pp. 1086
Author(s):  
Emilie Delogu ◽  
Albert Olioso ◽  
Aubin Alliès ◽  
Jérôme Demarty ◽  
Gilles Boulet
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Energy Balance ◽  
Irrigation Management ◽  
Global Radiation ◽  
Energy Balance Model ◽  
Balance Model ◽  
Spatially Distributed ◽  
Soil Moisture Availability ◽  
Local Surface Temperature

Continuous daily estimates of evapotranspiration (ET) spatially distributed at plot scale are required to monitor the water loss and manage crop irrigation needs. Remote sensing approaches in the thermal infrared (TIR) domain are relevant to assess actual ET and soil moisture status but due to lengthy return intervals and cloud cover, data acquisition is not continuous over time. This study aims to assess the performances of 6 commonly used as well as two new reference quantities including rainfall as an index of soil moisture availability to reconstruct seasonal ET from sparse estimates and as a function of the revisit frequency. In a first step, instantaneous in situ eddy-covariance flux tower data collected over multiple ecosystems and climatic areas were used as a proxy for perfect retrievals on satellite overpass dates. In a second step, instantaneous estimations at the time of satellite overpass were produced using the Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) energy balance model in order to evaluate the errors concurrent to the use of an energy balance model simulating the instantaneous IRT products from the local surface temperature. Significant variability in the performances from site to site was observed particularly for long revisit frequencies over 8 days, suggesting that the revisit frequency necessary to achieve accurate estimates of ET via temporal upscaling needs to be fewer than 8 days whatever the reference quantity used. For shorter return interval, small differences among the interpolation techniques and reference quantities were found. At the seasonal scale, very simple methods using reference quantities such as the global radiation or clear sky radiation appeared relevant and robust against long revisit frequencies. For infra-seasonal studies targeting stress detection and irrigation management, taking the amount of precipitation into account seemed necessary, especially to avoid the underestimation of ET over cloudy days during a long period without data acquisitions.

scholarly journals Response of the Energy Balance on the Margin of the Greenland Ice Sheet to Temperature Changes

1990 ◽  
Vol 36 (123) ◽  
pp. 217-221 ◽  
Author(s):  
Roger J. Braithwaite ◽  
Ole B. Olesen
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Air Temperature ◽  
Sensible Heat Flux ◽  
Ice Sheet ◽  
Temperature Response ◽  
Greenland Ice Sheet ◽  
Energy Balance Model ◽  
Balance Model ◽  
Sensible Heat

AbstractDaily ice ablation on two outlet glaciers from the Greenland ice sheet, Nordbogletscher (1979–83) and Qamanârssûp sermia (1980–86), is related to air temperature by a linear regression equation. Analysis of this ablation-temperature equation with the help of a simple energy-balance model shows that sensible-heat flux has the greatest temperature response and accounts for about one-half of the temperature response of ablation. Net radiation accounts for about one-quarter of the temperature response of ablation, and latent-heat flux and errors account for the remainder. The temperature response of sensible-heat flux at QQamanârssûp sermia is greater than at Nordbogletscher mainly due to higher average wind speeds. The association of high winds with high temperatures during Föhn events further increases sensible-heat flux. The energy-balance model shows that ablation from a snow surface is only about half that from an ice surface at the same air temperature.

Estimating evapotranspiration using remote sensing and the METRIC energy balance model: case study of Sidi Benour region (Morocco)

2021 ◽  
Author(s):  
Abdelmejid Rahimi ◽  
Abdelkrim Bouasria ◽  
Mohamed Bounif ◽  
Fatna Zaakour ◽  
Ikram El Mjiri
Keyword(s):  
Remote Sensing ◽  
Energy Balance ◽  
Energy Balance Model ◽  
Balance Model ◽  
Model Case

scholarly journals Evaluation of the Simple Urban Energy Balance Model Using Selected Data from 1-yr Flux Observations at Two Cities

2009 ◽  
Vol 48 (4) ◽  
pp. 693-715 ◽  
Author(s):  
Toru Kawai ◽  
Mohammad Kholid Ridwan ◽  
Manabu Kanda
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Sensible Heat Flux ◽  
Energy Balance Model ◽  
Balance Model ◽  
Wave Radiation ◽  
Urban Energy Balance ◽  
Two Cities ◽  
Urban Energy

Abstract The authors’ objective was to apply the Simple Urban Energy Balance Model for Mesoscale Simulation (SUMM) to cities. Data were selected from 1-yr flux observations conducted at three sites in two cities: one site in Kugahara, Japan (Ku), and two sites in Basel, Switzerland (U1 and U2). A simple vegetation scheme was implemented in SUMM to apply the model to vegetated cities, and the surface energy balance and radiative temperature TR were evaluated. SUMM generally reproduced seasonal and diurnal trends of surface energy balance and TR at Ku and U2, whereas relatively large errors were obtained for the daytime results of sensible heat flux QH and heat storage ΔQS at U1. Overall, daytime underestimations of QH and overestimations of ΔQS and TR were common. These errors were partly induced by the poor parameterization of the natural logarithm of the ratio of roughness length for momentum to heat (κB−1); that is, the observed κB−1 values at vegetated cities were smaller than the simulated values. The authors proposed a new equation for predicting this coefficient. This equation accounts for the existence of vegetation and improves the common errors described above. With the modified formula for κB−1, simulated net all-wave radiation and TR agreed well with observed values, regardless of site and season. However, at U1, simulated QH and ΔQS were still overestimated and underestimated, respectively, relative to observed values.

scholarly journals Response of the Energy Balance on the Margin of the Greenland Ice Sheet to Temperature Changes

1990 ◽  
Vol 36 (123) ◽  
pp. 217-221 ◽  
Author(s):  
Roger J. Braithwaite ◽  
Ole B. Olesen
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
Air Temperature ◽  
Sensible Heat Flux ◽  
Ice Sheet ◽  
Temperature Response ◽  
Greenland Ice Sheet ◽  
Energy Balance Model ◽  
Balance Model ◽  
Sensible Heat

AbstractDaily ice ablation on two outlet glaciers from the Greenland ice sheet, Nordbogletscher (1979–83) and Qamanârssûp sermia (1980–86), is related to air temperature by a linear regression equation. Analysis of this ablation-temperature equation with the help of a simple energy-balance model shows that sensible-heat flux has the greatest temperature response and accounts for about one-half of the temperature response of ablation. Net radiation accounts for about one-quarter of the temperature response of ablation, and latent-heat flux and errors account for the remainder. The temperature response of sensible-heat flux at QQamanârssûp sermia is greater than at Nordbogletscher mainly due to higher average wind speeds. The association of high winds with high temperatures during Föhn events further increases sensible-heat flux. The energy-balance model shows that ablation from a snow surface is only about half that from an ice surface at the same air temperature.

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

2017 ◽  
Vol 21 (3) ◽  
pp. 1339-1358 ◽  
Author(s):  
Jordi Cristóbal ◽  
Anupma Prakash ◽  
Martha C. Anderson ◽  
William P. Kustas ◽  
Eugénie S. Euskirchen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Arctic Tundra ◽  
Soil Heat Flux ◽  
Energy Balance Model ◽  
The Arctic ◽  
Balance Model ◽  
Climate Conditions

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

Intercomparison of Spatially Distributed Models for Predicting Surface Energy Flux Patterns during SMACEX

2005 ◽  
Vol 6 (6) ◽  
pp. 941-953 ◽  
Author(s):  
Wade T. Crow ◽  
Fuqin Li ◽  
William P. Kustas
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Energy Balance ◽  
Surface Energy ◽  
Surface Temperature ◽  
Energy Flux ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Energy Fluxes ◽  
Spatially Distributed

Abstract The treatment of aerodynamic surface temperature in soil–vegetation–atmosphere transfer (SVAT) models can be used to classify approaches into two broad categories. The first category contains models utilizing remote sensing (RS) observations of surface radiometric temperature to estimate aerodynamic surface temperature and solve the terrestrial energy balance. The second category contains combined water and energy balance (WEB) approaches that simultaneously solve for surface temperature and energy fluxes based on observations of incoming radiation, precipitation, and micrometeorological variables. To date, few studies have focused on cross comparing model predictions from each category. Land surface and remote sensing datasets collected during the 2002 Soil Moisture–Atmosphere Coupling Experiment (SMACEX) provide an opportunity to evaluate and intercompare spatially distributed surface energy balance models. Intercomparison results presented here focus on the ability of a WEB-SVAT approach [the TOPmodel-based Land–Atmosphere Transfer Scheme (TOPLATS)] and an RS-SVAT approach [the Two-Source Energy Balance (TSEB) model] to accurately predict patterns of turbulent energy fluxes observed during SMACEX. During the experiment, TOPLATS and TSEB latent heat flux predictions match flux tower observations with root-mean-square (rms) accuracies of 67 and 63 W m−2, respectively. TSEB predictions of sensible heat flux are significantly more accurate with an rms accuracy of 22 versus 46 W m−2 for TOPLATS. The intercomparison of flux predictions from each model suggests that modeling errors for each approach are sufficiently independent and that opportunities exist for improving the performance of both models via data assimilation and model calibration techniques that integrate RS- and WEB-SVAT energy flux predictions.

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