01676naa a2200289 a 450000100080000000500110000800800410001902000180006002400470007810000260012524500960015126000090024730000160025652007570027265300290102965300200105865300310107870000180110970000200112770000190114770000210116670000200118770000220120770000220122970000210125177301140127221699192024-12-03       2024    bl uuuu     u00u1 u    #d  a97810035414007 ahttps://doi.org/10.1201/97810035414002DOI1 aTEIXEIRA, A. H. DE C.  aModeling and monitoring water Productivity by using geotechnologies.h[electronic resource]  c2024  ap. 381-419.  aThis 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 (rs), 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.  aBrazilian agroecosystems  aClimate changes  aClimatic systems worldwide1 aLEIVAS, J. F.1 aTAKEMURA, C. M.1 aPACHECO, E. P.1 aGARCON, E. A. M.1 aSOUSA, I. F. DE1 aALMEIDA, A. Q. DE1 aTHENKABAIL, P. S.1 aSANTOS, A. F. M.  tIn: THENKABAIL, P. S. (ed.). Remote sensing handbook. 2. ed. Boca Raton, FL: CRC Press, 2024.gv. 5. cap. 11.