The reference evapotranspiration (ETo) is considered one of the primary variables for water resource management, irrigation practices, agricultural and hydro-meteorological studies, and modeling different hydrological processes. Therefore, an accurate prediction of ETo is essential. A large number of empirical methods have been developed by numerous scientists and specialists worldwide to estimate ETo from different climatic variables. The FAO56 Penman-Monteith (PM) is the most accepted and accurate model to estimate ETo in various environments and climatic conditions. However, the FAO56-PM method requires radiation, air temperature, air humidity, and wind speed data. In this study in Adana Plain, which has a Mediterranean climate for the summer growing season, using 22-year daily climatic data, the performance of the FAO56-PM method was evaluated with different combinations of climatic variables when climatic data were missing. Additionally, the performances of Hargreaves-Samani (HS) and HS (A&G) equations were assessed, and multiple linear regression models (MLR) were developed using different combinations of climatic variables. The FAO56-PM method could accurately estimate daily ETo when wind speed (U) and relative humidity (RH) data were unavailable, using the procedures suggested by FAO56 Paper (RMSEs were smaller than 0.4 mm d−1, and percent relative errors (REs) were smaller than 9%). Hargreaves-Samani (A&G) and HS equations could not estimate daily ETo accurately according to the statistical indices (RMSEs = 0.772-0.957 mm d−1; REs (%) = 18.2–22.6; R2 = 0.604–0.686, respectively). On the other hand, MLR models’ performance varied according to a combination of different climatic variables. According to t-stat and p values of independent variables for MLR models, solar radiation (Rs) and sunshine hours (n) variables had more effect on estimating ETo than other variables. Therefore, the models that used Rs and n data estimated daily ETo more accurately than the others. RMSE values of the models that used Rs were between 0.288 to 0.529 mm d−1; RE(%) values were between 6.2%–11.5% in the validation process. RMSE values of the models that used n were between 0.457 to 0.750 mm d−1; RE(%) values were between 9.9%–16.3% in the validation process. The models based only on air temperature had the worst performance (RMSE = 1.117 mm d−1; RE(%) = 24.2; R2 = 0.423).

Bu çalışma, 2010-2011 yıllarında Çukurova Üniversite'sinde, yağış koşullarından etkilenmemek amacıyla üstü kapalı bir alanda gerçekleştirilmiştir. Helvacı serisi tuzlu-sodyumlu toprakları, büyük tanklara yerleştirilerek; jips ihtiyacı (JI) ve JI+0.5JI (13 ve 20 kg.m-2) kadar jips, ilk 10 cm'ye ve tüm toprak profiline karıştırılarak uygulanmıştır. Yıkama yöntemi olarak damla ve aralıklı göllendirme sulama teknikleri kullanılmıştır. Çalışma, bölünen-bölünmüş bloklar deneme desenine göre düzenlenmiştir. Çalışmada, farklı jips miktarlarının, farklı uygulama biçimlerinin ve farklı sulama yöntemlerinin EC, pH, sodyum adsorbsiyon oranı (SAR) ve değişebilir sodyum yüzdesi (ESP) üzerine olan etkileri araştırılmıştır. Deneme sonuçlarına göre; tüm toprak profilinde ESP azalmasına, 20 kg.m-2 jipsin tüm toprak profiline karıştırılması ve göllendirme yöntemiyle yıkama yapılması diğer kombinasyonlara göre 0.95 güvenle istatistiki olarak daha önemli bulunmuştur.

Buharlaşma, su döngüsünün anahtar bileşenidir. Buharlaşma miktarının belirlenmesinin; su kaynaklarının yönetimi, su varlığının belirlenmesi, sulama programlaması ve çevresel modelleme çalışmalarında çok önemli bir yeri vardır. A sınıfı buharlaşma kapları açık su yüzeyi buharlaşmasını ölçmek, tarla-bahçe bitkilerinin sulama programlaması ve su yönetimi için; bitki su tüketimlerini tahmin etmek amacıyla tüm dünyada yaygın olarak kullanılmaktadır. Pratik, teorik veya finansal nedenlerden dolayı kap buharlaşmasını ölçmek her zaman mümkün olmayabilir. Açık su yüzeyi buharlaşmasını meteorolojik verilerden kestirmek için pek çok model geliştirilmiştir.

Today, accurate irrigation approaches are of great importance due to climate change and a decrease in water resources. FAO methodology based on reference evapotranspiration (ET0) and crop coefficients (Kc) are commonly used worldwide to determine crop water requirements (ETc). Kc values of different plants for different areas can be taken from FAO-56 and FAO-24. However, crop coefficients must be determined or calibrated for every relevant region because the climate conditions in the field and surrounding conditions may not be similar to the standard conditions. For this purpose, what crop evapotranspiration and crop coefficients would be in the case of timely (first crop) and late sowing (second crop) of maize were investigated in this study in Adana where the Mediterranean climate characteristics are prevalent during 2012 and 2013 years. A weighing lysimeter was used to obtain ETc and Kc of maize. ET0 was calculated using the FAO-56 Penman-Monteith (PM56) method. The results showed that the duration of initial, development, mid-season, and end-season growth stages for first crop maize was 22, 26, 43, and 37 days totaling 128 days, and for second crop maize, it was 14, 24, 42, and 38 days totaling 118 days. The ETc value of the second crop maize was 14% higher than that value of the first crop maize. The mean Kc values were 0.74, 0.92, 1.63, and 0.42 at the initial, development, mid-season, and end-season growth stages for the first crop maize, whereas they were determined as 0.46, 0.89, 1.68, and 0.92, respectively for the second crop maize.

Reference evapotranspiration (ETo) is essential for irrigation practices and the management of water resources and plays a vital role in agricultural and hydro-meteorological studies. The FAO-56 Penman-Monteith (PM) equation, recommended as the sole standard method of calculating ETo by the Food and Agriculture Organization of the United Nations (FAO), is the most commonly used and accurate model to determine the ETo and evaluate ETo equations. However, it requires many meteorological variables, often restricting its applicability in regions with poor or missing meteorological observations. Many empirical and semi-empirical equations have been developed to predict the ET0 from numerous meteorological data. The FAO-24 Pan method is commonly used worldwide to estimate ETo because it is simple and requires only pan coefficients. However, pan coefficients (Kpan) should be determined accurately to estimate ET0 using the FAO-24 Pan method. As the accuracy and reliability of the Kpan models can be different from one location to another, they should be tested or calibrated for different climates and surrounding conditions. In this study, the performance of the eight Kpan models was evaluated using 22-year daily climate data for the summer growing season in Adana, which has a Mediterranean climate in Turkey. The results showed that the mean seasonal pan coefficients estimated by all Kpan models differed significantly at a 1% significance level from those observed by FAO-56 PM according to the two-tail z test. In the study, ETo values estimated by Kpan models were compared against those obtained by the FAO-56 PM equation. The seasonal and monthly performance of Kpan models was varied, and the Wahed & Snyder model presented the best performance for ETo estimates at the seasonal scale. (RMSE = 0.550 mm d−1; MAE = 0.425 mm d−1; MBE = −0.378 mm d−1; RE = 0.134). In addition, it showed a good performance in estimating ETo on a monthly scale. The Orang model showed the lowest performance in estimating ETo among all models, with a very high relative error on the seasonal scale. (RMSE = 1.867 mm d−1; MAE = 1.806 mm d−1; MBE = −1.806 mm d−1; RE = 0.455). In addition, it showed the poorest performance on a monthly scale. Hence, the Wahed & Snyder model can be considered to estimate ETo under Adana region conditions after doing the necessary calibration.