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ORIGINAL RESEARCH
Penman–Monteith Reference Evapotranspiration
Estimation Models, Using Latitude–Temperature
Data, in the State of Sinaloa, Mexico
1
Instituto Politécnico Nacional–Centro Interdisciplinario de Investigación para el Desarrollo Integral Regional
(CIIDIR-IPN–SINALOA)
2
Universidad Autónoma de Sinaloa–Facultad de Ingeniería Mochis (UAS–FIM)
Submission date: 2024-07-08
Final revision date: 2024-10-07
Acceptance date: 2024-10-28
Online publication date: 2024-12-30
Publication date: 2025-11-14
Corresponding author
Omar Llanes Cárdenas
Instituto Politécnico Nacional–Centro Interdisciplinario de Investigación para el Desarrollo Integral Regional (CIIDIR-IPN–SINALOA)
Instituto Politécnico Nacional–Centro Interdisciplinario de Investigación para el Desarrollo Integral Regional (CIIDIR-IPN–SINALOA)
Pol. J. Environ. Stud. 2025;34(6):8063-8076
KEYWORDS
reference evapotranspirationPenman–MonteithHargreavesintelligent irrigation“the breadbasket of Mexico”
TOPICS
ABSTRACT
The goal is to create regression models estimating the daily Penman–Monteith reference
evapotranspiration (PMR) using latitude–temperature for the state of Sinaloa. The reference
evapotranspiration was calculated (1979–2017) by the methods of Penman–Monteith using empirical
equations (PMC), Hargreaves (HAC), and PMR. Prior to calculating PMC, the incident solar radiation
(SR) was calculated. From the Acaponeta station (2005–2008, 2011–2013, and 2015–2017), all complete
observed variables were obtained: mean temperature, incident solar radiation (SRg), average relative
humidity, and average wind speed at a height of 10 m. The data from the eight weather stations were
provided by the National Meteorological Service and the National Water Commission. The daily
observed Penman–Monteith reference evapotranspiration (PMO) was calculated. For validation, three
simple linear regressions (SLR) were applied: SR vs SRg, PMC vs PMO, and PMR vs PMO hypothesis
tests were applied to each SLR: Pearson correlation (Pr) vs critical Pearson correlation (Pcr). All rP
were significantly different from zero (> |0.576|): SRg vs SR (Pr = 0.951), PMC vs PMO ( Pr = 0 .592),
and PMR vs PMO (Pr = 0.625). This study provides new models that can motivate and support intelligent
irrigation in “the breadbasket of Mexico.”
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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| eISSN: | 2083-5906 |
| ISSN: | 1230-1485 |
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