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当前位置: 首页 > 文章 > 基于Penman-Monteith模型的两个蒸散模型在夏玉米农田的参数修正及性能评价 应用生态学报 2017 (6) 1917-1924
Position: Home > Articles > Parameters modification and evaluation of two evapotranspiration models based on Penman-Monteith model for summer maize Chinese Journal of Applied Ecology 2017 (6) 1917-1924

基于Penman-Monteith模型的两个蒸散模型在夏玉米农田的参数修正及性能评价

作  者：
王娟;王建林;刘家斌;姜雯;赵长星
单  位：
青岛农业大学理学与信息科学学院;青岛农业大学现代农业科技示范园;青岛农业大学农学与植物保护学院
关键词：
蒸散量;涡度相关法;Penman-Monteith模型;气象因素
摘  要：
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:FAOPM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.
译  名：
Parameters modification and evaluation of two evapotranspiration models based on Penman-Monteith model for summer maize
作  者：
WANG Juan;WANG Jian-lin;LIU Jia-bin;JIANG Wen;ZHAO Chang-xing;College of Science and Information,Qingdao Agricultural University;College of Agronomy and Plant Protection,Qingdao Agricultural University;Modern Agricultural Demonstration Farm,Qingdao Agricultural University;
关键词：
evapotranspiration;;eddy covariance method;;Penman-Monteith model;;meteorological parameters
摘  要：
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 PenmanMonteith 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.

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