A Multi-Scales Surface Energy Balance System For Operational Actual Surface Evapotranspiration Monitoring

2006 ◽  
Author(s):  
J. Colin
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Actual Surface ◽  
Balance System ◽  
Multi Scales

scholarly journals Improving Meteorological Input for Surface Energy Balance System Utilizing Mesoscale Weather Research and Forecasting Model for Estimating Daily Actual Evapotranspiration

Water ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 9 ◽  
Author(s):  
Dakang Wang ◽  
Yulin Zhan ◽  
Tao Yu ◽  
Yan Liu ◽  
Xiaomei Jin ◽  
...  
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Interpolation Method ◽  
Meteorological Data ◽  
Meteorological Station ◽  
Weather Research And Forecasting ◽  
Balance System ◽  
Meteorological Input ◽  
Sebs Model

Using Surface Energy Balance System (SEBS) to estimate actual evapotranspiration (ET) on a regional scale generally uses gridded meteorological data by interpolating data from meteorological stations with mathematical interpolation. The heterogeneity of underlying surfaces cannot be effectively considered when interpolating meteorological station measurements to gridded data only by mathematical interpolation. This study aims to highlight the improvement of modeled meteorological data from the Weather Research and Forecasting (WRF) mesoscale numerical model which fully considers the heterogeneity of underlying surfaces over the data from mathematical interpolation method when providing accurate meteorological input for SEBS model. Meteorological data at 1 km resolution in the Hotan Oasis were simulated and then were put into SEBS model to estimate the daily actual ET. The accuracy of WRF simulation was evaluated through comparison with data collected at the meteorological station. Results found that the WRF-simulated wind speed, air temperature, relative humidity and surface pressure correlate well with the meteorological stations measurements (R2 are 0.628, 0.8242, 0.8089 and 0.8915, respectively). Comparison between ET calculated using the meteorological data simulated from the WRF (ETa-WRF) and meteorological data interpolated from measurements at met stations (ETa-STA) showed that ETa-WRF could better reflect the ET difference between different land cover, and capture the vegetation growing trend, especially in areas with sparse vegetation, where ETa-STA intends to overestimate. In addition, ETa-WRF has less noise in barren areas compared to ETa-STA. Our findings suggest that WRF can provide more reliable meteorological input for SEBS model than mathematical interpolation method.

scholarly journals The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes

2002 ◽  
Vol 6 (1) ◽  
pp. 85-100 ◽  
Author(s):  
Z. Su
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Heat Fluxes ◽  
Physical Parameters ◽  
Turbulent Heat ◽  
Evaporative Fraction ◽  
Balance System ◽  
Turbulent Heat Fluxes

Abstract. A Surface Energy Balance System (SEBS) is proposed for the estimation of atmospheric turbulent fluxes and evaporative fraction using satellite earth observation data, in combination with meteorological information at proper scales. SEBS consists of: a set of tools for the determination of the land surface physical parameters, such as albedo, emissivity, temperature, vegetation coverage etc., from spectral reflectance and radiance measurements; a model for the determination of the roughness length for heat transfer; and a new formulation for the determination of the evaporative fraction on the basis of energy balance at limiting cases. Four experimental data sets are used to assess the reliabilities of SEBS. Based on these case studies, SEBS has proven to be capable to estimate turbulent heat fluxes and evaporative fraction at various scales with acceptable accuracy. The uncertainties in the estimated heat fluxes are comparable to in-situ measurement uncertainties. Keywords: Surface energy balance, turbulent heat flux, evaporation, remote sensing

scholarly journals Regional evapotranspiration from an image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous US

2018 ◽  
Vol 22 (4) ◽  
pp. 2311-2341 ◽  
Author(s):  
Nishan Bhattarai ◽  
Kaniska Mallick ◽  
Nathaniel A. Brunsell ◽  
Ge Sun ◽  
Meha Jain
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Temperature ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Regional Scale ◽  
Absolute Error ◽  
Error Statistics ◽  
Aridity Gradient ◽  
Balance System

Abstract. Recent studies have highlighted the need for improved characterizations of aerodynamic conductance and temperature (gA and T0) in thermal remote-sensing-based surface energy balance (SEB) models to reduce uncertainties in regional-scale evapotranspiration (ET) mapping. By integrating radiometric surface temperature (TR) into the Penman–Monteith (PM) equation and finding analytical solutions of gA and T0, this need was recently addressed by the Surface Temperature Initiated Closure (STIC) model. However, previous implementations of STIC were confined to the ecosystem-scale using flux tower observations of infrared temperature. This study demonstrates the first regional-scale implementation of the most recent version of the STIC model (STIC1.2) that integrates the Moderate Resolution Imaging Spectroradiometer (MODIS) derived TR and ancillary land surface variables in conjunction with NLDAS (North American Land Data Assimilation System) atmospheric variables into a combined structure of the PM and Shuttleworth–Wallace (SW) framework for estimating ET at 1 km × 1 km spatial resolution. Evaluation of STIC1.2 at 13 core AmeriFlux sites covering a broad spectrum of climates and biomes across an aridity gradient in the conterminous US suggests that STIC1.2 can provide spatially explicit ET maps with reliable accuracies from dry to wet extremes. When observed ET from one wet, one dry, and one normal precipitation year from all sites were combined, STIC1.2 explained 66 % of the variability in observed 8-day cumulative ET with a root mean square error (RMSE) of 7.4 mm/8-day, mean absolute error (MAE) of 5 mm/8-day, and percent bias (PBIAS) of −4 %. These error statistics showed relatively better accuracies than a widely used but previous version of the SEB-based Surface Energy Balance System (SEBS) model, which utilized a simple NDVI-based parameterization of surface roughness (zOM), and the PM-based MOD16 ET. SEBS was found to overestimate (PBIAS = 28 %) and MOD16 was found to underestimate ET (PBIAS = −26 %). The performance of STIC1.2 was better in forest and grassland ecosystems as compared to cropland (20 % underestimation) and woody savanna (40 % overestimation). Model inter-comparison suggested that ET differences between the models are robustly correlated with gA and associated roughness length estimation uncertainties which are intrinsically connected to TR uncertainties, vapor pressure deficit (DA), and vegetation cover. A consistent performance of STIC1.2 in a broad range of hydrological and biome categories, as well as the capacity to capture spatio-temporal ET signatures across an aridity gradient, points to the potential for this simplified analytical model for near-real-time ET mapping from regional to continental scales.

scholarly journals SURFACE ENERGY BALANCE SYSTEM (SEBS) AND SATELLITE DATA FOR MONITORING WATER CONSUMPTION OF IRRIGATED SUGARCANE

2016 ◽  
Vol 36 (6) ◽  
pp. 1176-1185 ◽  
Author(s):  
Elizabeth Ferreira ◽  
Christiaan M. Mannaerts ◽  
Antonio A. Dantas ◽  
Bernardus H. Maathuis
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Water Consumption ◽  
Satellite Data ◽  
Surface Energy Balance ◽  
Balance System

Estimation of evapotranspiration using surface energy balance system and satellite datasets

2021 ◽  
pp. 157-183
Author(s):  
Garima Shukla ◽  
Prasoon Tiwari ◽  
Vikas Dugesar ◽  
Prashant K. Srivastava
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Balance System

scholarly journals A Critical Evaluation on the Role of Aerodynamic and Canopy–Surface Conductance Parameterization in SEB and SVAT Models for Simulating Evapotranspiration: A Case Study in the Upper Biebrza National Park Wetland in Poland

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1753 ◽  
Author(s):  
Kaniska Mallick ◽  
Loise Wandera ◽  
Nishan Bhattarai ◽  
Renaud Hostache ◽  
Malgorzata Kleniewska ◽  
...  
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
National Park ◽  
Surface Energy Balance ◽  
Critical Evaluation ◽  
Surface Conductance ◽  
Eastern European ◽  
Balance System ◽  
North Eastern ◽  
The Impact

Evapotranspiration (ET) estimation through the surface energy balance (SEB) and soil-vegetation-atmosphere-transfer (SVAT) models are uncertain due to the empirical parameterizations of the aerodynamic and canopy-substrate conductances (gA and gS) for heat and water vapor transfers. This study critically assessed the impact of conductance parameterizations on ET simulation using three structurally different SEB and SVAT models for an ecologically important North-Eastern European wetland, Upper Biebrza National Park (UBNP) in two consecutive years 2015 and 2016. A pronounced ET underestimation (mean bias −0.48 to −0.68 mm day−1) in SEBS (Surface Energy Balance System) was associated with an overestimation of gA due to uncertain parameterization of momentum roughness length and bare soil’s excess resistance to heat transfer (kB−1) under low vegetation cover. The systematic ET overestimation (0.65–0.80 mm day−1) in SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes) was attributed to the overestimation of both the conductances. Conductance parameterizations in SEBS and SCOPE appeared to be very sensitive to the general ecohydrological conditions, with a tendency of overestimating gA (gS) under humid (arid) conditions. Low ET bias in the analytical STIC (Surface Temperature Initiated Closure) model as compared to SEBS/SCOPE indicated the critical need for calibration-free conductance parameterizations for improved ET estimation.

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