SEBAL

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The Surface Energy Balance Algorithm for Land (SEBAL) uses the '''surface''' energy balance to estimate aspects of the hydrological cycle. SEBAL maps evapotranspiration, biomass growth, water deficit and soil moisture. Its main creator is Prof. Dr. W.G.M. Bastiaanssen [1]

Model background[edit]

The basis of SEBAL is the energy balance:[2] the energy driving the hydrological cycle is equal to the incoming energy minus:

  1. the energy going to heating of the soil and air, and
  2. the energy reflected back to space.

SEBAL quantifies the energy balance using satellite data as an input.[3] Land surface characteristics such as surface albedo, leaf area index, vegetation index and surface temperature are derived from satellite imagery. In addition to satellite images, the SEBAL model requires meteorological data, such as wind speed, humidity, solar radiation and air temperature. It uses meteorological data from the moment of the recording of the satellite data to solve the 'instantaneous' energy balance, and uses extrapolation to calculate daily evapotranspiration. Using a time series of satellite and meteorological data, periodic cumulative (e.g. weekly, monthly, yearly) evapotranspiration data can be calculated.[4]

The SEBAL model uses the energy balance, as opposed to in hydrology common water balance to solve for evapotranspiration.

Applications[edit]

The energy balance applies to all scales, ranging from global to river basin to region to farm and to field level. Satellite images come in a wide variety of spatial and temporal resolutions. Evapotranspiration and biomass production are key indicators for water management and irrigation performance.[5]

The combination of the energy balance with input from remote sensing data is applied by farmers,[6] irrigation districts,[7] catchment management agencies [8] and regional and national governments.[9]

References[edit]

  1. ^ "Precious Resources: Water and Landsat’s Thermal Band". NASA. Retrieved 2010-04-04. 
  2. ^ "FAO Irrigation and Drainage Paper No. 56. Crop Evapotranspiration (guidelines for computing crop water requirements)". Food and agricultural organization. 1998. Retrieved 2015-02-22. 
  3. ^ Irmak (Kilic), A., R.G. Allen, J. Kjaersgaard, J. Huntington, B. Kamble, R. Trezza, and I. Ratcliffe. 2012. Operational Remote Sensing of ET and Challenges. Chapter 21 in Evapotranspiration – Remote Sensing and Modeling (A. Irmak (Kilic), editor), Publisher: InTech. "Evapotranspiration - Remote Sensing and Modeling". Intech. Retrieved 2015-02-22. 
  4. ^ "A scientific description of SEBAL procedure". WaterWatch. Retrieved 2010-04-08. 
  5. ^ "SEBAL". WaterWatch. Retrieved 2010-04-08. 
  6. ^ "El uso de la teledetección para fortalecer el trabajo de los COTAS". State of Guanajuato Water Committee. 2008. Retrieved 2010-04-08. 
  7. ^ "Water Watchers". NASA. 2010-01-21. Retrieved 2010-04-08. 
  8. ^ "Estimating actual evapotranspiration through remote sensing techniques to improve agricultural water management: A case study in the transboundary Olifants catchment in the Limpopo basin, South Africa". UNESCO-IHE. Retrieved 2010-04-04. 
  9. ^ "Application of remote sensing in national water plans". Futurewater. February 2009. Retrieved 2010-04-04.