Modeling and Monitoring Water Productivity by Using Geotechnologies
A. H. de C. Teixeira, Janice Freitas Leivas, Celina Maki Takemura, Edson Patto Pacheco, E. A. M. Garçon, Inajá Francisco de Sousa, André Quintão de Almeida, Prasad S. Thenkabail, Ana Flávia Maria Santos · 2024
This chapter highlights the combination of the newest version of the SAFER algorithm and the Monteith RUE model, with applications in agroecosystems inside some Brazilian biomes. This is done to demonstrate that remote sensing measurements, together with weather data, can be used for water productivity assessments on different spatial and temporal scales, to support the rational water resources management. A third model for the surface resistance to water fluxes (r s ), SUREAL (Surface Resistance Algorithm), is used to classify the vegetation into irrigated crops and natural ecosystems ( Teixeira, 2010 ; Teixeira et al., 2013 ) to retrieve the incremental values of ET and BIO, resulted from the replacement of natural vegetation by irrigated crops. Following the introduction, the study regions, data set, and the steps for modeling are described. Water productivity assessments are done by using remote sensing parameters at different spatial and temporal resolutions, involving natural vegetation and agricultural crops, under both irrigation and rainfed conditions, for distinct agroecosystems inside the Brazilian biomes. The successful applications carried out in Brazil may encourage replications of the methods in other countries through simple calibrations of the modeling equations.