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Advisor(s)
Abstract(s)
Reference evapotranspiration (ETo) is an important part of the water cycle, essential for cli-
mate studies, water resource management, and agricultural planning. However, accurate estimation
of ETo is challenging when meteorological data are insufficient or of low quality. Furthermore, in
climate change studies where large amounts of data need to be managed, it is important to minimize
the complexity of the ETo calculation. This study presents a comprehensive approach that integrates
data quality analysis with two calibration methods—annual and cluster-based—to improve ETo
estimates based solely on temperature data from a set of weather stations (WS). First, the quality and
integrity of meteorological data from several WS were analyzed to reduce uncertainty. Second, the
Hargreaves–Samani equation (HS) is site calibrated using two approaches: (a) annual calibration,
where the radiation coefficient (kRs) is adjusted using a data set covering the entire year; (b) cluster-
based calibration, where independent radiation coefficients are adjusted for clusters of years and
months. The methodology was evaluated for the Alentejo region in Southern Portugal, using data
from 1996 to 2023. When using the original HS equation with a kRs = 0.17 ◦C−0.5, ETo was estimated
with errors from 14.9% to 22.9% with bias ranging from −9.0% to 8.8%. The annual calibration
resulted in kRs values between 0.157 and 0.165 ◦C−0.5 with estimation errors between 13.3% and
20.6% and bias ranging from −1.5% to 1.0% across the different weather stations. Calibration based
on clusters of months and years produced unclear results. Dry season months showed better results
using cluster-based calibration, while wet season months performed poorly regardless of the calibra-
tion approach. The results highlight the importance of meteorological data quality and site-specific
calibration for refining temperature-based ETo estimation methods, and for the region studied, the
gains do not justify the increased complexity of the cluster-based approach.
Description
Keywords
temperature-based models radiation coefficient cluster analysis K-Means bias correction
Pedagogical Context
Citation
Ferreira, A.; Cameira, M.d.R.; Rolim, J. Methodology for Obtaining ETo Data for Climate Change Studies: Quality Analysis and Calibration of the Hargreaves–Samani Equation. Climate 2024, 12, 205. https://doi.org/10.3390/cli12120205
Publisher
MDPI