Remote Sensing Of Land Surface Energy Balance: Effects Of Scale And Landscape Structure

Author(s):  
F.G. Hall ◽  
D.E. Strebel ◽  
P.J. Sellers ◽  
K.F. Huemmrich ◽  
S.J. Goetz
2021 ◽  
Vol 58 (03) ◽  
pp. 274-285
Author(s):  
H. V. Parmar ◽  
N. K. Gontia

Remote sensing based various land surface and bio-physical variables like Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), surface albedo, transmittance and surface emissivity are useful for the estimation of spatio-temporal variations in evapotranspiration (ET) using Surface Energy Balance Algorithm for Land (SEBAL) method. These variables were estimated under the present study for Ozat-II canal command in Junagadh district, Gujarat, India, using Landsat-7 and Landsat-8 images of summer season of years 2014 and 2015. The derived parameters were used in SEBAL to estimate the Actual Evapotranspiration (AET) of groundnut and sesame crops. The lower values NDVI observed during initial (March) and end (May) stages of crop growth indicated low vegetation cover during these periods. With full canopy coverage of the crops, higher value of NDVI (0.90) was observed during the mid-crop growth stage. The remote sensing-based LST was lower for agricultural areas and the area near banks of the canal and Ozat River, while higher surface temperatures were observed for rural settlements, road and areas with exposed dry soil. The maximum surface temperatures in the cropland were observed as 311.0 K during March 25, 2014 and 315.8 K during May 31, 2015. The AET of summer groundnut increased from 3.75 to 7.38 mm.day-1, and then decreased to 3.99 mm.day-1 towards the end stage of crop growth. The daily AET of summer sesame ranged from 1.06 to 7.72 mm.day-1 over different crop growth stages. The seasonal AET of groundnut and sesame worked out to 358.19 mm and 346.31 mm, respectively. The estimated AET would be helpful to schedule irrigation in the large canal command.


2018 ◽  
Vol 34 (3) ◽  
pp. 555-566 ◽  
Author(s):  
Gabriel B Senay

Abstract.Remote sensing-based evapotranspiration (ET) can be derived using various methods, from soil moisture accounting to vegetation-index based approaches to simple and complex surface energy balance techniques. Due to the complexity of fully representing and parameterizing ET sub-processes, different models tend to diverge in their estimations. However, most models appear to provide reasonable estimations that can meet user requirements for seasonal water use estimation and drought monitoring. One such model is the Operational Simplified Surface Energy Balance (SSEBop). This study presents a formulation of the SSEBop model using the psychrometric principle for vapor pressure/relative humidity measurements where the “dry-bulb” and “wet-bulb” equivalent readings can be obtained from satellite-based land surface temperature estimates. The difference in temperature between the dry (desired location) and wet limit (reference value) is directly correlated to the soil-vegetation composite moisture status (surface humidity) and thus producing a fractional value (0-1) to scale the reference ET. The reference ET is independently calculated using available weather data through the standardized Penman-Monteith equation. Satellite Psychrometric Approach (SPA) explains the SSEBop model more effectively than the energy balance principle because SSEBop does not solve all terms of the surface energy balance such as sensible and ground-heat fluxes. The SPA explanation demonstrates the psychrometric constant for the air can be readily adapted to a comparable constant for the surface, thus allowing the creation of a “surface” psychrometric constant that is unique to a location and day-of-year. This new surface psychrometric constant simplifies the calculation and explanation of satellite-based ET for several applications in agriculture and hydrology. The SPA formulation of SSEBop was found to be an enhancement of the ET equation formulated in 1977 by pioneering researchers. With only two key parameters, improved model results can be obtained using a one-time calibration for any bias correction. The model can be set up quickly for routine monitoring and assessment of ET at landscape scales and beyond. Keywords: Dry-bulb, ET fraction, ET modeling, Remote sensing, Satellite psychrometry, Wet-bulb.


Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2369
Author(s):  
Jing Lu ◽  
Li Jia ◽  
Chaolei Zheng ◽  
Ronglin Tang ◽  
Yazhen Jiang

The diurnal cycle of evapotranspiration (ET) is significant in studying the dynamics of land–atmosphere interactions. The diurnal ET cycle can be considered as an indicator of dry/wet surface conditions. However, the accuracy of current models in estimating the diurnal ET cycle is generally low. This study developed an improved scheme to estimate the diurnal cycle of ET by solving the surface energy balance equation combined with simplified parameterization, with daily ET as the constraint. Meteosat Second Generation (MSG) land surface temperature, and longwave and shortwave radiation products were the primary inputs. Daily ET was from the remote sensing-based ETMonitor model. The estimated instantaneous (30 min) ET from the improved scheme outperformed the official MSG instantaneous ET product when compared with in situ half-hourly measurements at 35 flux sites from the FLUXNET2015 dataset, and was also comparable with European Center for Medium-Range Weather Forecasts (ECMWF) ERA5 ET data, with an R2 of 0.617 and root mean square error (RMSE) of 65.8 W/m2 for the improved scheme. Results were largely improved compared with those without daily ET as the constraint. The improved method was stable for the estimation of ET’s diurnal cycle at the similar atmospheric conditions and the accuracy was comparative at different land cover surfaces. Errors in the input variables and the simplification of surface heat flux parameterization affected surface energy balance closure, which can lead to instability of the solution of constants in the simplified parameterization and further to the uncertainty of ET’s diurnal cycle estimation. Measurement errors, different source areas in measured variables, and inconsistent spatial representativeness between remote sensing and site measurements also impacted the evaluation.


2020 ◽  
Author(s):  
Wenyu Wu

<p>Evapotranspiration(ET) is a critical component of the land surface energy balance system and hydrologic processes. Analysis of spatiotemporal variations and influencing factors of ET is of great importance to evaluate the growing environment for crops and to effectively use water resources, a critical base for production in research region. The traditional methods are based on point measurement, while the remote sensing provides extensive surface information. The development of remote sensing has promoted the study of regional ET.SEBAL model is based on Surface Energy Balance Algorithm for Land and its physical meaning is clear. This model was developed to show the spatial variability of surface evapotranspiration. SEBAL model was capable of being applied to large regional areas in conjunction with Moderate-resolution Imaging Spectroradiometer (MODIS) data products.According to the shortcomings of the traditional method of calculating ET, based on SEBAL model, the daily regional evapotranspiration of Anhui Province was estimated with 1km spatial resolution by using MODIS products and a few of meteorological data(temperature, wind speed) collected in meteorological stations distributed over the study area.Because of lacking observed data from the lysimeter, the results of P-M were compared with the estimation results based on SEBAL model in this research.The comparison of the evapotranspiration estimated with MODIS products and field observation showed that the former results were lower than the latter results on the whole, and demonstrated that there existed certain trend in correlation between the two results, the average relative error was different at different land surface.The ET computation method based on Remote Sensing proves that this model has strong practicality in Anhui, and it will show great potential in this field with more optimizing the model parameters.</p>


2005 ◽  
Vol 2 (1) ◽  
pp. 209-227 ◽  
Author(s):  
X. Jin ◽  
L. Wan ◽  
Z. Su

Abstract. Taiyuan basin is enclosed by hills and mountains, located in the middle of Shanxi province, standing between longitudes 111°40'–113°00'E and latitude 37°00'–38&deg00'N. With various types and wide distribution, the mineral resources are very abundant in this basin area. However, there is a great shortage of water resources. Due to continual fall of groundwater level caused by excessive extraction of ground water, some severe environmental problems are induced in this area, such as ground subsidence, etc. The goal of this paper is to estimate the spatial distribution of actual evaporation over the basin by using remote sensing data. The Surface Energy Balance System (SEBS) has been developed (Su, 2001, 2002). Using visible and infrared satellite remote sensing data, SEBS is based on land surface energy balance theory combined with the in-situ meteorological data or the product of atmospheric numerical model to estimate land surface turbulent flux and the relative evaporation at different scales. SEBS was served as the core methodology of this paper and was used for evaporation estimation. On the basis of hydro-geological data and NOAA satellite data, the SEBS was used in this paper for the estimation of actual evaporation of Taiyuan basin. The spatial distribution of the evaporative fraction and daily evaporation over the basin area was shown. On the other hand, the difference of land surface parameters and evaporation for various target types in the basin area was discussed.


2020 ◽  
Author(s):  
Joao Martins ◽  
Isabel Trigo ◽  
Mafalda Silva ◽  
Rita Cunha ◽  
Frederico Johannsen ◽  
...  

<p>The EUMETSAT Land Surface Analysis Satellite Application Facility (LSA-SAF) now offers a wide range of satellite-derived products for land surface monitoring. The catalogue comprises variables quantifying different terms of the surface energy balance (land surface temperature – LST - and emissivity, downwelling radiative fluxes and turbulent fluxes), as well as several vegetation-related indicators, such as the Leaf Area Index, Fraction of Vegetation Cover, Evapotranspiration, Net Primary Production and Fire Radiative Power. The availability of these datasets, especially taking into account that the time series now span nearly two decades,  already allows many interesting applications, overviewed in this presentation.</p><p>Comparisons of remote sensing data for land surfaces with corresponding model data have already been useful: the standard L2 (clear sky) LST has been used to diagnose a systematic cold bias of ERA5 skin temperature over the Iberian Peninsula. Offline simulations using H-TESSEL revealed that the bias could be alleviated using a more realistic representation of vegetation than what is currently used in ERA5. A recently developed product by LSA SAF allows LST retrievals for all-weather conditions, using a surface energy balance model to provide estimates under cloudy pixels. This product is compared to ERA5-Land skin temperature, showing that despite the increased level of detail of the latter (with respect to ERA5), it is still not representing the former correctly. ERA5 Land skin temperature shows large biases (of more than 10 K) and phase errors (with the satellite LST warming up prior to ERA-Land during the morning and cooling down earlier in the late afternoon). Comparisons of the different terms of the surface energy balance from ERA5-Land and LSA SAF are currently in progress to identify causes of the biases.</p><p>Another interesting application of LSA SAF products is the study of vegetation recovery over wild fire scars. Five wild fire events over Portugal were analyzed in terms of the long term anomalies introduced by the fire in 3 variables: LST, Albedo and Fraction of Vegetation Cover (all provided by LSA SAF). Results suggest that albedo returns to close-to-normal conditions in less than a year, while LST anomalies last much longer.  </p><p>Finally, trends in the land-ocean thermal contrast were evaluated over Western Iberia and Northwest Africa (due to its importance in generating coastal mesoscale circulations). The study used long time series from 1) satellite – LST from CM-SAF and SST from GHRSST; 2) ERA5 global reanalysis and 3) UERRA regional reanalysis. The results strongly depend on the used dataset and sub-region, with UERRA showing a sharp decrease of the thermal contrast over Iberia, while ERA5 shows a positive trend.</p><p>These results emphasize the need to improve the representation of surface processes in numerical models, particularly over land surfaces. This presentation shows that datasets such as the ones provided by the LSA SAF are key to such improvements.</p>


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