A Hybrid Surface Energy Balance Approach For The Estimation Of Evapotranspiration In Agricultural Areas

Abstract. Evapotranspiration (ET) may be used as an ecological indicator to address the ecosystem complexity. The accurate measurement of ET is of great significance for studying environmental sustainability, global climate changes, and biodiversity. Remote sensing technologies are capable of monitoring both energy and water fluxes on the surface of the Earth. With this advancement, existing models, such as SEBAL, S_SEBI and SEBS, enable us to estimate the regional ET with limited temporal and spatial coverage in the study areas. This paper extends the existing modeling efforts with the inclusion of new components for ET estimation at different temporal and spatial scales under heterogeneous terrain with varying elevations, slopes and aspects. Following a coupled remote sensing and surface energy balance approach, this study emphasizes the structure and function of the Surface Energy Balance with Topography Algorithm (SEBTA). With the aid of the elevation and landscape information, such as slope and aspect parameters derived from the digital elevation model (DEM), and the vegetation cover derived from satellite images, the SEBTA can account for the dynamic impacts of heterogeneous terrain and changing land cover with some varying kinetic parameters (i.e., roughness and zero-plane displacement). Besides, the dry and wet pixels can be recognized automatically and dynamically in image processing thereby making the SEBTA more sensitive to derive the sensible heat flux for ET estimation. To prove the application potential, the SEBTA was carried out to present the robust estimates of 24 h solar radiation over time, which leads to the smooth simulation of the ET over seasons in northern China where the regional climate and vegetation cover in different seasons compound the ET calculations. The SEBTA was validated by the measured data at the ground level. During validation, it shows that the consistency index reached 0.92 and the correlation coefficient was 0.87.

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Using a Surface Energy Balance Model (ReSET-Raster) to Estimate Seasonal Crop Water Use for Large Agricultural Areas: Case Study of the Palo Verde Irrigation District

Journal of Irrigation and Drainage Engineering ◽

10.1061/(asce)ir.1943-4774.0000716 ◽

2014 ◽

Vol 140 (10) ◽

pp. 05014006 ◽

Cited By ~ 6

Author(s):

Aymn Elhaddad ◽

Luis A. Garcia

Keyword(s):

Energy Balance ◽

Surface Energy ◽

Water Use ◽

Surface Energy Balance ◽

Irrigation District ◽

Balance Model ◽

Crop Water ◽

Crop Water Use ◽

Agricultural Areas

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Inter-comparison of energy balance and hydrological models for land surface energy fluxes estimation over a whole river catchment

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-11-5905-2014 ◽

2014 ◽

Vol 11 (6) ◽

pp. 5905-5951 ◽

Cited By ~ 1

Author(s):

R. Guzinski ◽

H. Nieto ◽

S. Stisen ◽

R. Fensholt

Keyword(s):

Energy Balance ◽

Surface Energy ◽

Water Balance ◽

Land Surface ◽

Hydrological Model ◽

Area Index ◽

Mike She ◽

River Catchment ◽

Balance Approach ◽

Energy Balance Approach

Abstract. Evapotranspiration is the main link between the natural water cycle and the land surface energy budget. Therefore water-balance and energy-balance approaches are two of the main methodologies for modelling of this process. The water-balance approach ensures that the amount of water coming into a system, mainly through precipitation, is balanced by the amount of water leaving the system through evapotranspiration, runoff and other processes. This modelling methodology is usually implemented as a complex, distributed hydrological model. The energy-balance approach ensures the conservation of energy at the land surface and is often used with remotely sensed observations of, for example, the land surface temperature (LST) and the state of the vegetation. In this study we compare the catchment scale output of two remote sensing models based on the Two-Source Energy Balance (TSEB) scheme, against a hydrological model, MIKE SHE, calibrated over the Skjern river catchment in western Denmark, the area covered by the Danish Hydrological Observatory (HOBE). The first TSEB model utilizes the time differential LST measurements provided by the night and day overpasses of the MODIS sensor aboard the Aqua satellite, while the second uses the dual-angle LST measurements made available by the AATSR sensor that used to fly on the Envisat satellite. All three models use the same ancillary data (meteorological measurements, land cover type and leaf area index, etc.) and produce output at similar spatial resolution (1 km for the TSEB models, 500 m for MIKE SHE). The comparison is performed on the spatial patterns of the fluxes present within the catchment area as well as on temporal patterns visible in 7 year long time series. The results aid the understanding of strengths and weaknesses of each modelling approach and explore the benefits to the hydrological modelling community of evapotranspiration maps derived with the energy-balance methodology.

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