| Ganjiang river is the largest river in jiangxi province.Its watershed has the characteristics of subtropical humid climate,which nourishes 83,500 square kilometers of land along the river and supports nearly 20 million people.The agricultural planting structure in the basin is mainly rice,and the agricultural water accounts for a large proportion of the total water consumption in the region.Crop reference crop water demand is an important basis for agricultural departments to understand the law of crop water demand and formulate agricultural irrigation system.Paper to select 12 stations in Ganjiang river basin in jiangxi province in 1961 ~ 2016,on the basis of the historical meteorological data by 6 different formula respectively to calculate the Ganjiang river basin the daily reference crop water requirement of more than50 years,and analyzed the characteristics of regional distribution,various meteorological factors in 6 kinds of formulas is studied to research the influence of the reference of more than 50 years in the area of crop water requirement,on this basis,established the neural network calculation model reference crop water requirement,choose different parameters for the numerical simulation of the reference crop water requirement,more accurate results were obtained.The main research content and main work of the paper are as follows:According to the geographical distribution characteristics of each meteorological station in the river basin,the Ganjiang River basin is divided into three research areas: the upper,middle and lower reaches.Based on the penman montes formula recommended by fao,the daily reference crop water demand of 12 meteorological stations in the study area for more than 50 years was calculated and the regional distribution characteristics were analyzed.FAO-24 Penman formula,Hargreaves formula,Irmak formula,Makkink formula and Priestley-Tayor formula were used to calculate the daily crop water demand of 12 meteorological stations in ganjiang river basin for more than 50 years,and the results were analyzed and compared with those of Penman-Montieth formula.Finally,it was found that the Hargreaves formula,Priestley-Tayor formula and the Penman-Montieth formula were the closest to each other.However,Makkink formula,Irmak formula and FAO-24 Penman formula are different from Penman formula.The ET0 obtained by FAO-24 Penman formula was higher than that obtained by the other five formulas,followed by Priestley-Tayor formula,Hargreaves formula,Penman-Montieth formula,Irmak formula,and Makkink formula.The influence parameters of related meteorological factors on the water demand of reference crops in the six formulas in Ganjiang river basin were calculated,and the parameters were analyzed and compared.Using neural network theory,respectively by a single meteorological factor,two meteorological factors,three meteorological factors,4 meteorological factors as the input samples,the BP neural network model was established,the reference crop water requirement is simulated,finally it is concluded that as the input samples to a single meteorological factors,including radiation on crop water requirement of fitting effect is good,high precision,the vapor pressure of the fitting effect of crop water requirement,the precision is not high,and the fitting effect of temperature on crop water requirement is poorer,the precision is low;With two meteorological factors as input samples,the fitting effect of temperature radiation on crop water demand is general and the precision is not high.With three meteorological factors as input samples,the fitting effect of temperature radiation water vapor pressure on crop water demand is better and the precision is higher.With four meteorological factors as the input samples,the temperature radiation vapor pressure has a very good fitting effect on the crop water demand with high accuracy.With the increase of meteorological factors,the accuracy of the simulation of reference crop water demand is higher,indicating that it is feasible to use neural network to calculate the reference crop water demand. |
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