Prediction of Daily Reference Crop Water Requirement Based on Radial Basis Neural Network Model
This paper aimed to realize the accurate prediction of the daily reference crop water requirement of the water storage pit irrigation apple orchard based on the limited meteorological data.According to the data of daily temperature and humidity data of the water storage pit irrigation orchard at the Institute of Shanxi Academy of Agricultural Sciences,an ET0 prediction model based on radial basis neural network was built.The simulation results and the calculation results of the two commonly used ET0 calculation formulas of Hargreaves and Priestley-Taylor were compared with the standard values calculated by the FAO-PM formula.The results show that the simulation results of the radial basis neural network model are closer to the standard values calculated by the FAO-PM formula.The calculation results of the Hargreaves for-mula and the Priestley-Taylor formula are larger than that of the standard values,which should be corrected by coefficients in practical appli-cations.
water storage pit irrigationdaily reference crop water requirementradial basis neural networkHargreaves equationPriestley-Taylor equation
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