The dynamic variations of evapotranspiration (ET) and weather data during summer maize growing season in 2013-2015 were monitored with eddy covariance system, and the applicability of two operational models (FAO-PM model and KP-PM model) based on the Penman-Monteith model were analyzed. Firstly, the key parameters in the two models were calibrated with the measured data in 2013 and 2014; secondly, the daily ET in 2015 calculated by the FAO-PM model and KP-PM model was compared to the observed ET, respectively. Finally, the coefficients in the KP-PM model were further revised with the coefficients calculated according to the different growth stages, and the performance of the revised KP-PM model was also evaluated. These statistical parameters indicated that the calculated daily ET for 2015 by the FAO-PM model was closer to the observed ET than that by the KP-PM model. The daily ET calculated from the revised KP-PM model for daily ET was more accurate than that from the FAO-PM model. It was also found that the key parameters in the two models were correlated with weather conditions, so the calibration was necessary before using the models to predict the ET. The above results could provide some guidelines on predicting ET with the two models.
利用涡度相关系统和小气象系统对2013—2015年夏玉米生长季的蒸散量和气象数据进行实时观测,基于观测数据对以Penman-Monteith模型为基础的FAO-PM模型和KP-PM模型进行分析:首先利用2013和2014年数据对两个模型中的关键参数进行校正,其次利用两个模型对2015年夏玉米农田的日蒸散量进行计算,并与测量值对比,说明两个模型在夏玉米农田的适用性;最后采用分阶段法对KP-PM模型中的经验系数进行修正.结果表明: FAO-PM模型对2015年夏玉米农田日蒸散量的计算值更加接近测量值;利用分阶段法对KP-PM模型进行修正后,模型对日蒸散量的计算效果有了很大提高,且计算值比FAO-PM模型更接近测量值.模型中关键系数与气象条件之间有很大关系,因此利用模型进行蒸散预测时,必须先对模型进行参数校正.该研究可为其他研究人员利用模型估算蒸散量提供方法上的参考.
Keywords: Penman-Monteith model; eddy covariance method; evapotranspiration; meteorological parameters.