| Cite this article: | 林馨贝,周岗,郑泽涛,等.不同冠层阻力模型在夏玉米蒸散发计算中的优化应用[J].灌溉排水学报,0,():-. |
| Lin Xinbei,Zhou Gang,Zheng Zetao,et al.不同冠层阻力模型在夏玉米蒸散发计算中的优化应用[J].灌溉排水学报,0,():-. |
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| Optimization of Different Canopy Resistance Models in Estimating Evapotranspiration of Summer Maize |
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Lin Xinbei, Zhou Gang, Zheng Zetao, Zhao LU, Liang Chuan
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College of Water Resource and Hydropower, Sichuan University
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| Abstract: |
| 【Objective】To better estimate evapotranspiration (ET) of summer maize, the present study collected meteorological data and eddy covariance data from Huailai station. 【Method】By utilizing ant colony optimization (ACO) and least square method (LSM), data during 2013 were used for calibration of coefficients in Jarvis (JA) model and coupled surface resistance model (CO). In addition, Back Propagation Neuron Network was applied to analyze sensitivity of canopy resistance (rc) to different affecting factor respectively. Data during 2014 were used for validation of evapotranspiration computed by optimized models, which using ET measured by eddy covariance system as a benchmark. 【Result】The results show that (1) Sensitivity of rc to different affecting factor come by the order of Rn>LAI>θ>T>VPD. (2) CO model optimized by ACO have the best result in rc model calibration, with R2=0.89, RMSE=410.90 s·m-1, d=0.88. (3) CO model optimized by ACO gives the best result in ET estimation with R2=0.72, RMSE=1.07 mm, d=0.75.【Conclusion】Rn and LAI are the main factors affecting rc. CO model optimized by ACO can give the most accurate results both in rc model calibration and ET estimation, which provides basis for precision irrigating of summer maize in Huailai. |
| Key words: evapotranspiration; model; canopy resistance |
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