Forecasting Reference Evapotranspiration by ARIMA Approach

Yıl 2020, Cilt: 37 Sayı: 1, 17 - 22, 30.04.2020

Kadri Yürekli

https://doi.org/10.13002/jafag4680

Öz

The effort in the study is on forecasting reference evapotranspiration (ETo) by the SARIMA models. This was accomplished by using monthly ETo dataset obtained based on some parameters from meteorology station of Konya province. Stationary of the ETo dataset was fulfilled with differencing. Three SARIMA models that provides all conditions for the stationary data set were identified. The models have very close parsimony values depending on AIC and SBC criteria.

Anahtar Kelimeler

Reference Evapotranspiration, ARIMA approach, AIC, SBC

Referans Evapotrasprasyonun Tahmin Edilmesinde ARIMA Yaklaşımı

Öz

Çalışmadaki amaç SARIMA modellerle referans evapotranspırasyonun (ETo) tahmin edilmesi üzerinedir. Bu Konya meteoroloji istasyonunun bazı parametrelerine bağlı olarak elde edilen aylık ETo veri seti kullanılarak gerçekleştirilmiştir. ETo veri setinin durağanlığı fark alınarak sağlanmıştır. Durağan seri için bütün koşulları yerine getiren üç SARIMA modeli tanımlanmıştır. Bu modeller AIC ve SBC kriterlerine göre çok yakın tutumluluk (parsimony) değerlerine sahip olmuşlardır.

Anahtar Kelimeler

Referans Evapotranspirasyon, ARIMA Yaklaşımı, AIC, SBC

Kaynakça

• Akaike H. (1974). A look at the statistical model identification. IEEE Transactions on Automatic Control, AC-19(6): 716-723.
• Allen RG, Pereira LS, Raes D and Smith M (1998) .Crop Evapotranspiration (guidelines for computing crop water requirements). FAO Irrigation and Drainage Paper No. 56.
• Box GEP and Jenkins GM (1976). Time Series Analysis Forecasting and Control. 575p., Holden-Day: San Francisco.
• Chiew F and Sriwardena L (2005). Trend (trend/change detection software), User Guide. CRC for Catchement Hydrology, 23p., Australia.
• Dahmen ER and Hall MJ (1990). Screening of Hydrological Data: Tests for Stationarity and Relative Consistency. International Institute for Land Reclamation and Improvement, Publication 49, 58p., Wageningen, The Netherlands.
• Dwivedi DK and Shrivastava P K (2019). Time Series Modelling of Monthly Temperature and Reference Evapotranspiration for Navsari (Gujarat), India. Current Journal of Applied Science and Technology, 35:1-13.
• Ehlers JF (2002). Using the Fisher Transform. Stocks & Commodities, V(20:11): 40-42.
• Gautam R and Sinha AK (2016). Time series analysis of reference crop evapotranspiration for Bokaro District, Jharkhand, India. Journal of Water and Land Development, 30: 51-56.
• Hamdi MR, Bdour ANand Tarawneh ZS (2008). Developing Reference Crop Evapotranspiration Time Series Simulation Model Using Class a Pan: A Case Study for the Jordan Valley /Jordan. Jordan Journal of Earth and Environmental Sciences, 1: 33-44.
• Hipel KW, McLeod AI and Lennox WC. (1977). Advances in Box-Jenkins modeling: I. model construction. Water Resources Research 13(3): 567-575.
• Janacek G and Swift L. (1993). Time Series Forecasting, Simulation, Application. Ellis Horwood, 333p., New York.
• Jayalakshmi T and Santhakumaran A (2011). Statistical Normalization and Back Propagation for Classification. International Journal of Computer Theory and Engineering, 3(1): 1793-8201.
• Landeras G, Barredo AO and Lopez JJ (2009). Forecasting Weekly Evapotranspiration with ARIMA and Artificial Neural Network Models. Journal of Irrigation and Drainage Engineering, 135: 323-334.
• Ljung GM and Box GEP (1978). On a measure of lack of fit in time series models. Biometrika, 65(2): 297-303.
• Mossad A and Alazba AA (2016). Simulation of temporal variation for reference evapotranspiration under arid climate. Arabian Journal Geosciences, 9: 1-9.
• Patra SR (2018). Time Series Analysis of Reference Crop Evapotranspiration Using Machine Learning Techniques For Ganjam District, Odisha, India. Proceeding of the 2nd International Conference on Compute and Data Analysis, March 2018, DeKalb IL USA.
• Schwartz G (1978). Estimating the dimension of a model. The Annals Statistics, 6: 461-464.
• Sing S and Jaiswal CS (2006).Numerical Solution of 2D free surface to ditch drains in presence of transient recharge and depth-dependent ET in sloping aquifer. Water Resources Management, 20:779-793.
• Tao PC and Delleur JW (1976). Seasonal and Nonseasonal ARMA Models in Hydrology. Journal of The Hydraulics Division, HY10: 1541-1559,
• Tapur T (2008) Kazımkarabekir İlçesi’nde (Karaman) Tarım ve Hayvancılık. Selçuk Üniversitesi, Sosyal Bilimler Enstitüsü Dergisi, Sayı: 20: 603-620.
• Trajković S (1998). Comparıson of predıctıon models of reference crop evapotranspıratıon. The scientific journal Facta Universitatis, 1: 617-625.
• Yurekli K, Kurunc A and Ozturk F (2005). Application of Linear Stochastic Models to Monthly Flow Data of Kelkit Stream. Ecological Modeling, 183(1): 67-75.