What question did this study set out to answer?

This research aims to evaluate the accuracy of temperature and radiation-based models for estimating reference evapotranspiration (ETo) in the Cross River basin.

March 29, 2026Discover Environment0 citationsOpen Access

Evaluation of temperature and radiation based reference evapotranspiration methods over Cross River basin Nigeria

OEOluwadamilare Oluwasegun EludireFederal University of Technology OFOluwaseun Temitope FaloyeFederal University of Technology BTBadmus TayoUniversity of Calabar

Key Points

This research aims to evaluate the accuracy of temperature and radiation-based models for estimating reference evapotranspiration (ETo) in the Cross River basin.
Utilized climatic variables such as temperature, relative humidity, solar radiation, and wind speed.
Compared various temperature-based and radiation-based models against the Penman–Monteith (PM-ETo) reference.
Sourced meteorological data from 22 stations over 30 years (1987-2017).
Evaluated model performance using several statistical metrics including root-mean-square-error and Nash–Sutcliffe Efficiency.
Conducted sensitivity analysis on model responsiveness to climatic variables.
Radiation-based models outperformed temperature-based models in all evaluations.
Blaney-Morin-Nigeria and Copais excelled in dry season assessments, while Hargreaves–Samani and Abtew performed best during the rainy season.
Abtew and Hargreaves–Samani had the highest annual performance metrics.
An increasing trend in PM-ETo suggests impacts of global warming, with a slope of 0.0029 mm/day.

Abstract

The accurate estimation of reference evapotranspiration (ETo) on seasonal and annual scale is vital for determination of water requirement of crops and impact of climate change on irrigated agriculture. This study investigates the influence of climatic variables (temperature, relative-humidity, solar-radiation, and wind speed) on ETo and comparison of the performance evaluation of temperature and radiation-based models over Cross River basin on seasonal and annual basis. Estimation of ETo was done using temperature-based; Schendel, Samani, Trajkovic, Droogers Jensen-Haise, Stephens and Stewart, Oudin, Abtew, Irmak-1, Copais, Tabari & Talaee-4, and Hargreaves under humid-tropic condition, with Penman–Monteith (PM-ETo) as a reference. Remotely-sensed meteorological variables from 1987 to 2017 were sourced from the Climatic Research Unit (CRU) database, over 22 stations. These variables were used for estimating ETo. Models were evaluated with coefficient of determination, a root-mean-square-error, Willmott’s index of agreement, Percentage-Bias and Nash–Sutcliffe Efficiency. Sensitivity analysis (± 5%) revealed that PM-ETo was most sensitive to solar-radiation and temperature, compared to relative-humidity and wind speed. Blaney-Morin-Nigeria demonstrated seasonal estimation bias. Further analysis revealed that radiation-based models out-performed the temperature-based models across all categories. Blaney-Morin-Nigeria and Copais recorded the best performance in dry season, while Hargreaves–Samani and Abtew recorded the best performance in rainy season. Abtew and Hargreaves–Samani recorded the best performance on annual basis. An increasing trend (slope = 0.0029 mm/day) of PM-ETo further suggests global warming scenario. This demonstrates the ability of radiation-driven models for crop water requirement estimation in data-scarce regions.

问 AI

Bookmark

View Full Paper