Ability of Box-Jenkins Models to Estimate of Reference Potential Evapotranspiration (A Case Study: Mehrabad Synoptic Station, Tehran, Iran)

Abstract

The evapotranspiration rate has a vital role in agricultural water management. In this paper, ability of Box-Jenkins models in forecasting the reference potential evapotranspiration is estimated. For this purpose meteorological data of Mehrabad synoptic station in Tehran was selected. Using this data and according to eight famous evapotranspiration equations amounts of evapotranspiration were forecasted by Box-Jenkins models. Equations of reference potential evapotranspiration that used in this study include: FAO Penman Monteith (FPM), FAO Blaney Criddle (FBC), Turc, FAO Radiation Macking (FRM), Priestley Taylor (PT), Hargreaves Samani (HS), Thornthwaite (TW), and Corrected Jensen Haise (CJH). A box-Jenkins model has found a widespread application in many practical sciences. In addition, evapotranspiration forecasting is done by some methods such as remote sensing, genetic algorithm, and artificial neural networks. On the other hand, application of both Box-Jenkins models simultaneously in order to compare their ability in forecast of evapotranspiration has not been carried out in previous researches. Therefore, this paper attempts to forecast the evapotranspiration and meteorological data by using Box-Jenkins models while increasing the number of parameters in order to increase the forecast accuracy to five parameters and comparing them. By comparing root mean square error of the models, it was determined that Box-Jenkins models are appropriate approaches to evapotranspiration forecasting.