sebal

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Python code to run SEBAL method

View the Project on GitHub rafatieppo/sebal

SEBAL model by means GRASS and PYTHON

DOI

Motivation

Now days it is noticed several occurrences about water shortage in agriculture, decreasing yield crops and profits. The irrigation system is a resource to aid the farmers to manage the system production to achieve a reasonable yield. Among several variables for a irrigation management, there are two of them with a major importance, the crop coefficient (kc) and Reference crop evapotranspiration (ETo) (Gondim et al., 2005).

In the last decades the remote sensing techniques has been used to identify landscapes, soil classes, and water energy balance as well, providing conditions to analyze data in a regional scale. By means orbital sensors and algorithms to convert digital numbers to reflectance and radiation flux, remotesensing methods to predict the evapotranspiration is a important tool to handle the hydrological cycle (Bernardo et al., 2006).

The SEBAL (Surface Energy Balance Algorithm for Land) uses the surface energy balance to predict some hydrological features (evapotranspiration, water deficit, etc) and Its main creator is Professor Wim G. M. Bastiaanssen (Bastiaanssen et al., 1998). That method has been validated under several conditions for different locations ((Bastiaanssen, 2000),(Bastiaanssen et al., 2002), (Santos et al., 2010)).

There are several available algorithms to evapotranspiration prediction ((Wolff, 2016), (Cavalcante et al., 2016), (Hessels et al., 2017)). However is missing a specific code to run on python 3 and GRASS 74. Thus we aimed to implement SEBAL model for Landsat 8 iamges using the language Python version 3 (Rossum, 1995) and GRASS version 7.4 (Neteler et al., 2012).

How to run

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