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Error Autocorrelation and Linear Regression for Temperature-Based Evapotranspiration Estimates Improvement

Authors

  • Patrick Valverde Medeiros,

    1. Respectively, Graduate student (Medeiros, Marcuzzo, Youlton) and Professor (Wendland), Department of Hydraulics and Sanitary Engineering, University of São Paulo, Av. Trabalhador Sancarlense 400, São Carlos-SP 13566-590, Brazil
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  • Francisco Fernando Noronha Marcuzzo,

    1. Respectively, Graduate student (Medeiros, Marcuzzo, Youlton) and Professor (Wendland), Department of Hydraulics and Sanitary Engineering, University of São Paulo, Av. Trabalhador Sancarlense 400, São Carlos-SP 13566-590, Brazil
    2. Senior Hydrologist, (Marcuzzo), CPRM – Geological Survey of Brazil, Brazil’s Mines and Energy Ministry, Goiânia-GO 74170-110, Brazil
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  • Cristián Youlton,

    1. Respectively, Graduate student (Medeiros, Marcuzzo, Youlton) and Professor (Wendland), Department of Hydraulics and Sanitary Engineering, University of São Paulo, Av. Trabalhador Sancarlense 400, São Carlos-SP 13566-590, Brazil
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  • Edson Wendland

    1. Respectively, Graduate student (Medeiros, Marcuzzo, Youlton) and Professor (Wendland), Department of Hydraulics and Sanitary Engineering, University of São Paulo, Av. Trabalhador Sancarlense 400, São Carlos-SP 13566-590, Brazil
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  • Paper No. JAWRA-10-0203-P of the Journal of the American Water Resources Association (JAWRA).Discussions are open until six months from print publication.

(E-Mail/Wendland: ew@sc.usp.br)

Abstract

Medeiros, Patrick Valverde, Francisco Fernando Noronha Marcuzzo, Cristián Youlton, and Edson Wendland, 2012. Error Autocorrelation and Linear Regression for Temperature-Based Evapotranspiration Estimates Improvement. Journal of the American Water Resources Association (JAWRA) 48(2): 297-305. DOI: 10.1111/j.1752-1688.2011.00614.x

Abstract:  Estimates of evapotranspiration on a local scale is important information for agricultural and hydrological practices. However, equations to estimate potential evapotranspiration based only on temperature data, which are simple to use, are usually less trustworthy than the Food and Agriculture Organization (FAO)-Penman-Monteith standard method. The present work describes two correction procedures for potential evapotranspiration estimates by temperature, making the results more reliable. Initially, the standard FAO-Penman-Monteith method was evaluated with a complete climatologic data set for the period between 2002 and 2006. Then temperature-based estimates by Camargo and Jensen-Haise methods have been adjusted by error autocorrelation evaluated in biweekly and monthly periods. In a second adjustment, simple linear regression was applied. The adjusted equations have been validated with climatic data available for the Year 2001. Both proposed methodologies showed good agreement with the standard method indicating that the methodology can be used for local potential evapotranspiration estimates.

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