阿克苏地区日蒸散量估算方法研究

Study on estimation method of daily evapotranspiration in Aksu Prefecture

采用阿克苏地区2006—2015年日蒸散量数据和气象数据,对几种不同的日蒸散量估算方法进行评估与修正。结果表明,修正后的彭曼公式在阿克苏地区的适用性、准确性有所提高,均方根误差值由11.78减小到8.80;BP神经网络比GRNN神经网络估算效果好,前者Nash-Sutcliffe系数为-0.09、RMSE值为3.27,后者Nash-Sutcliffe系数为-0.44、RMSE值为3.34。研究成果可为极端干旱区的棉花等作物节水种植提供参考。

Based on the daily evapotranspiration data and meteorological data of Aksu from 2006 to 2015,several different estimation methods of daily evap otranspiration were evaluated and modified.The applicability and accuracy of the modified Penman-Monteith(PM)formula in Aksu are improved,and the root mean square error is reduced from 11.78 to 8.80.The BP neural network(Back Propagation Neural Network)has better estimation effect than the GRNN(General Regression Neural Network).The former has a Nash-Sutcliffe coefficient of-0.09 and an RMSE value of 3.27,while the latter has a Nash-Sutcliffe coefficient of-0.44 and an RMSE value of 3.34.The research results can provide references for water-saving planting of cotton and other crops in extremely arid regions.