| 引用本文: | 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,2021,(6):28-35. |
| 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,2021,(6):28-35. |
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| 摘要: |
| 【目的】更精确地估算怀来地区夏玉米蒸散量（ET）。【方法】利用怀来站点2013年的气象数据与涡度相关数据，分别采用最小二乘法与蚁群算法优化冠层阻力Jarvis模型（JA模型）和耦合表层阻力模型（CO模型）中的经验参数，使用BP神经网络模型分析冠层阻力（rc）对各气象因子的敏感程度。再利用2014年的气象数据计算ET，并以涡度相关系统实测的ET为标准验证参数优化的结果。【结果】①rc对各影响因子敏感程度从大到小顺序为：Rn>LAI>θ>T>VPD。②使用蚁群算法优化的CO模型拟合rc结果最好（R2=0.89，RMSE=410.90 s/m，d=0.88）。③使用蚁群算法优化后的CO模型模拟ET精度最高（R2=0.72，RMSE=1.07 mm，d=0.75）。【结论】Rn和LAI是影响夏玉米rc的主要因素，使用蚁群算法优化CO模型中的参数，可以获得精度最高的rc拟合结果和ET估计值，可为夏玉米精量用水提供理论依据。 |
| 关键词: 蒸散量；模型；冠层阻力；敏感度；参数优化 |
| DOI：10.13522/j.cnki.ggps.2020450 |
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| Optimizing the Canopy Resistance Models to Calculate Evapotranspiration from Summer Maize Fields |
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LIN Xinbei, ZHOU Gang, ZHENG Zetao, ZHAO Lu, LIANG Chuan
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1.College of Water Resource and Hydropower, Sichuan University, Chengdu 610065, China; 2. Provincial Key Laboratory of Water-Saving Agriculture in Hill Areas of Southern China, Chengdu 610066, China
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| Abstract: |
| 【Objective】Canopy resistance (rc) is an important parameter to calculate evapotranspiration (ET) from natural and planted fields, and its value varies between plants. Different models have been proposed to calculate rc and the objective of this paper is to propose a method to optimize these models.【Method】We took summer maize as the model plant, and the optimized canopy resistance model was used to estimate the evapotranspiration from the maize field using both meteorological data and eddy covariance data measured from a weather station at Huailai in China. Data and results measured and calculated in 2013 were used to calibrate the coefficients in the Jarvis (JA) model and the coupled surface resistance model (CO), using the ant colony optimization (ACO) and least square method (LSM) respectively; the backpropagation neural network model was used to analyze the sensitivity of rc to different factors. The ET calculated by the optimized model was tested against the ET measured from fields using an eddy covariance system in 2014.【Result】The meteorological factors to which rc was sensitive were ranked in the order radiation >leave area index>humidity >temperature > wind speed. The CO model optimized by the ACO gave the best calibrated rc model with R2=0.89, RMSE=410.90 s/m and d=0.88, and the ET estimated by it was also most accurate with R2=0.72, RMSE=1.07 mm and d=0.75.【Conclusion】Radiation and leave area index are the factors affecting rc the most. The CO model optimized by ACO was most accurate for calibrating the rc model and calculating ET of the maize field. |
| Key words: evapotranspiration; canopy resistance model; maize field; sensitivity; parameter optimization |
