基于不同LSTM模型和Hargreaves模型估算鲁中地区参考作物蒸散量

Estimation of reference crop evapotranspiration in central Shandong by different LSTM models and Hargreaves models

为找出在仅使用温度这一气象参数条件下适用于区域参考作物蒸散量(ET0)估算的简化模型,本研究以鲁中地区为研究区域,基于6个气象站点1961-2019年的逐日气象数据,以长短期记忆神经网络(LSTM)模型和Hargreaves(HS)模型为基础,利用粒子群优化LSTM模型(PSO-LSTM)、遗传算法优化LSTM模型(GA-LSTM)、贝叶斯理论优化LSTM模型(BA-LSTM)和5种HS改进模型估算ET0,并将估算结果与Penman-Monteith(PM)模型的ET0进行对比。结果表明,相同参数输入条件下,LSTM模型精度普遍优于HS模型,4种LSTM模型具有较强的适用性,其中BA-LSTM模型对ET0日值的估算效果最优,其均方根差(RMSE)、平均绝对误差(MAE)、决定系数(R2)、效率系数(Ens)的中位线分别为0.378 mm/d、0.276 mm/d、0.904和0.902,其综合性指标指数(GPI)的中位线为1.837。同时,BA-LSTM模型在全区的相对误差(RE)仅为0.01%~1.75%。因此,在仅有温度这一气象参数时,推荐使用BA-LSTM模型估算鲁中地区ET0。

To find out a simplified model suitable for regional reference crop evapotranspiration(ET0) estimation using only temperature data, we took the central region of Shandong as the research area in this study, and used the daily meteorological data of six meteorological stations from 1961 to 2019. Based on long short-term memory neural network(LSTM) model and Hargreaves(HS) model, three optimization models including particle swarm optimization LSTM(PSO-LSTM) model, genetic algorithm optimization LSTM(GA-LSTM) model and Bayesian theory optimization LSTM(BA-LSTM) model and five improved HS models were used to estimate ET0. The calculation results were compared with the Penman-Monteith(PM) model. The results showed that under the same parameter input conditions, the accuracy of the LSTM model was generally better than that of the HS model, and the four LSTM models had strong applicability. The BA-LSTM model had the best estimation effect on the daily value of ET0. The medians of root mean square error(RMSE), mean absolute error(MAE), determination coefficient(R~2) and efficiency coefficient(Ens) were 0.378 mm/d, 0.276 mm/d, 0.904 and 0.902. The median of global performance index(GPI) was 1.837. The relative error(RE) of the BA-LSTM model in the whole area was only 0.01%-1.75%. Therefore, it is recommended to use BA-LSTM model to estimate ET0in central Shandong when only temperature data are available.