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Chinese Journal of Applied Ecology ›› 2017, Vol. 28 ›› Issue (6): 1917-1924.doi: 10.13287/j.1001-9332.201706.016

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Parameters modification and evaluation of two evapotranspiration models based on Penman-Monteith model for summer maize

WANG Juan1, WANG Jian-lin2*, LIU Jia-bin3, JIANG Wen2, ZHAO Chang-xing2   

  1. 1College of Science and Information, Qingdao Agricultural University, Qingdao 266109, Shandong, China
    2College of Agronomy and Plant Protection, Qingdao Agricultural University, Qingdao 266109, Shandong, China
    3Modern Agricultural Demonstration Farm, Qingdao Agricultural University, Qingdao 266109, Shandong, China
  • Received:2016-11-11 Published:2017-06-18
  • Contact: *E-mail:wangjianlin@qau.edu.cn
  • Supported by:
    This work was supported by National Natural Science Foundation of China (31371574), the National Science & Technology Pillar Program of China (2011BAD09B01-2,2013BAD07B06) and the National Key Technology Research and Development Program of China (2016YFD0300306)

Abstract: 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.