Monthly and fixed coefficient calibration of empirical reference evapotranspiration equations: A case study for a Mediterranean climate (Izmir Province)
JOURNAL OF HYDROLOGY AND HYDROMECHANICS, cilt.74, sa.2, ss.177-211, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 74 Sayı: 2
- Basım Tarihi: 2026
- Doi Numarası: 10.2478/johh-2026-0014
- Dergi Adı: JOURNAL OF HYDROLOGY AND HYDROMECHANICS
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, CAB Abstracts, Compendex, Environment Index, Geobase, Directory of Open Access Journals, Natural Science Collection (ProQuest), Earth, Atmospheric, & Aquatic Science Collection (ProQuest), Materials Science & Engineering Collection (ProQuest), Technology Collection (ProQuest)
- Sayfa Sayıları: ss.177-211
- Dokuz Eylül Üniversitesi Adresli: Evet
Özet
Accurate estimation of reference evapotranspiration (ET0) is essential for efficient irrigation and water resource management, particularly in water-scarce regions. Although the FAO56 Penman-Monteith (PM-FAO56) equation is widely accepted as the standard method, its application is often constrained by the requirement for comprehensive meteorological data. This study provides a regional evaluation and calibration of three widely used empirical ET0 models Hargreaves and Samani (temperature-based), Priestley and Taylor (radiation-based), and Mahringer (mass transfer-based) under Mediterranean climatic conditions in & Idot;zmir, T & uuml;rkiye. Daily meteorological data from 40 stations covering the period 2000-2020 were used. Model performance was assessed against PM-FAO56 using the coefficient of determination (R & sup2;), mean absolute error (MAE), root mean square error (RMSE), percentage error (PE), Nash-Sutcliffe efficiency (NSE) and mean bias error (MBE). Calibration was performed using least squares (LS) regression and a gradient-based optimization approach, with both fixed and monthly varying coefficients. Before calibration, the Priestley-Taylor model showed the best performance among the empirical equations (R & sup2; = 0.932, MAE = 0.68, RMSE = 0.92, PE = 7.32, NSE=0.796, MBE=- 0.65). After calibration, all models improved substantially, with the Mahringer equation achieving the highest accuracy when monthly coefficients were applied (R & sup2; = 0.995, MAE = 0.05, RMSE = 0.154, PE = 1.41, NSE=0.992, MBE=0.022). The LS and gradient-based optimization approaches produced nearly identical results. In addition, the reconstruction of missing sunshine duration (ADS) data using a regression-based approach enabled the inclusion of a more spatially representative dataset without introducing significant bias into the calibration results. The findings demonstrate that locally calibrated empirical equations, particularly when temporal variability is accounted for through monthly coefficients, can provide highly accurate ET0 estimates with relatively limited data requirements. This study provides practical monthly and fixed calibration coefficients for the & Idot;zmir region and supports the use of monthly calibrated empirical models for irrigation planning in Mediterranean environments.