In this study, an empirical method proposed by Caselles et al. (1992a) is utilized to determine the potential evapotranspiration (ETP) on a regional scale. This method uses the global solar radiation data retrieved by the global radiation model GL1.0, which in turn utilizes data from the visible channel of the GOES-8 satellite. This method is applied to the northeast region of Brazil, using daily and monthly climatological data as the ground truth information to estimate the ETP and the estimated daily ETP data for September, 1997. The methodology involved three steps: 1) to perform a spatial regionalization of the ETP using the method of Ward, which is available in the Statistical Package for the Social Sciences (SPSS); 2) to obtain the correlation between the ETP as estimated by the methods of Jensen & Haise (1963) - MJH, Caselles (1992a) - MCA, and the Penman's combined method (1948) - MCP; 3) to test the sensibility of the empirical formulations proposed and to assess the estimates using the satellite-based global solar radiation provided by the GL1.0 model. The spatial regionalization shows two distinct regions in the Northeastern Brazil. The MCA yielded better results than the MJH. The ETP estimates using satellite data were satisfactory, showing a maximum error of 20% when compared with the ground truth data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.