| 温室葡萄蒸散量时间尺度提升方法优选 |
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| 引用本文： | 裴冬杰,魏新光,崔宁博,姚名泽,白义奎,王铁良,郑思宇,付诗宁.温室葡萄蒸散量时间尺度提升方法优选[J].农业工程学报,2022,38(14):88-97. |
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| 作者姓名： | 裴冬杰 魏新光 崔宁博 姚名泽 白义奎 王铁良 郑思宇 付诗宁 |
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| 作者单位： | 1. 沈阳农业大学水利学院，沈阳 110866；;2. 四川大学水力学与山区河流开发保护国家重点实验室，成都 610065 |
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| 基金项目： | 国家自然科学基金优秀青年基金项目（51922072）；国家自然科学基金面上项目（51779161）；辽宁省自然科学基金项目（2021-MS-233）；辽宁省重点研发项目（2021JH2/10200022）；国家博士后资助项目（2019M661128） |
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| 摘 要： | 为探索在东北寒区温室种植环境下温室葡萄蒸散发（Evapotranspiration，ET）规律与不同时间尺度ET转化方法，该研究对温室葡萄蒸散过程及环境因子进行2 a的连续监测，利用3种尺度提升方法（蒸发比法、改进蒸发比法、作物系数法）对葡萄ET进行了瞬时到日以及日到全生育期的时间尺度提升。结果表明：利用蒸发比法、改进蒸发比法和作物系数法进行ET瞬时到日尺度提升的关键参数在08:00-16:00变化平稳，平均值分别为0.54、0.52和0.76，变异系数平均值分别为0.11、0.10和0.09。采用3种日尺度提升方法对葡萄ET进行瞬时到日尺度提升时，基于不同评价指标确定的最优模型和最佳尺度提升时间均不一致。进一步，利用综合评价指标确定了4个生育期的最佳模拟时刻，基于该时刻进行瞬时到日尺度提升模拟，模拟精度以蒸发比法最高，作物系数法最低，改进蒸发比法居中。2020和2021年蒸发比法模拟的R2分别达到0.92和0.89，相对均方根误差仅为20.23%和21.49%。利用不同生育期的日蒸腾进行生育期尺度ET提升，其中果实膨大期效果最好，基于3种方法利用该生育期日数据进行全生育期ET模拟，模拟精度仍然以蒸发比法最高，作物系数法最低，改进蒸发比法居中。蒸发比法在2020和2021年的ET模拟绝对误差仅为1.8和7.4 mm，相对误差仅为0.68%和2.73%。研究为东北地区温室葡萄的水分管理提供科学依据。
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| 关 键 词： | 蒸散发 蒸腾 温室 时间尺度提升 蒸发比 改进蒸发比 作物系数 |
| 收稿时间： | 2022/4/11 0:00:00 |
| 修稿时间： | 2022/6/25 0:00:00 |
Optimization of the time scale improvement method for grape evapotranspiration in greenhouses |
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| Pei Dongjie,Wei Xinguang,Cui Ningbo,Yao Mingze,Bai Yikui,Wang Tieliang,Zheng Siyu,Fu Shining.Optimization of the time scale improvement method for grape evapotranspiration in greenhouses[J].Transactions of the Chinese Society of Agricultural Engineering,2022,38(14):88-97. |
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| Authors: | Pei Dongjie Wei Xinguang Cui Ningbo Yao Mingze Bai Yikui Wang Tieliang Zheng Siyu Fu Shining |
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| Institution: | 1. College of Water Conservancy, Shenyang Agricultural University, Shenyang 110866, China;;2. State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610065, China |
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| Abstract: | Abstract: Grapes evapotranspiration (ET) and its transformation are of great significance at different time scales under a greenhouse planting environment in the cold region of Northeast China. In this study, the ET process and environmental factors of greenhouse grapes were monitored continuously for two years, in order to optimize the time-scale improvement models. Three models were also used to enhance the temporal scale of grapes from the instantaneous to the daily scale, and from the daily to the whole growth period ET. The results showed that the key parameters improved the evaporative fraction (EF''), evaporative fraction (EF), and crop coefficient. Among them, the EF'', EF, and crop coefficient were used to elevate the ET from the instantaneous to the daily scale. There was a decrease at first and then an increase throughout the day, where the stable was from 8:00 to 16:00. Specifically, the mean values of the study period were 0.54, 0.52, and 0.76, respectively, while the mean values of the coefficients of variation were 0.11, 0.10, and 0.09, respectively. The ET increased from the day to the growth period, where the average values of the three key parameters were 0.60, 0.61, and 1.37, respectively. There was also no outstanding change during the study period. The highest simulation accuracy was achieved in the three instantaneous scale models of ET improvement in the fruit expansion period, compared with the rest growth periods. The optimal models were determined by various evaluation indicators, including the Relative Root Mean Square Error (RRMSE), efficiency coefficient, determination coefficient (R2), and Mean Absolute Error (MAE). The optimal scale improvement time of the three models was mainly concentrated from 11:00 to 13:30. The optimum scaling time of greenhouse grape was determined by GPI comprehensive evaluation in the period of the shoot growth, flowering and fruit setting, fruit expansion and maturity. The optimum expansion time of EF'' was 11:30, 11:30, 11:30, and 12:30, respectively. The optimum expansion time of EF was 12:30, 11:30, 11:30, and 12:00, respectively, while that of crop coefficient was 12:30, 12:00, 12:30, and 12:30, respectively. Three models were used to improve the instantaneous to daily scale ET of greenhouse grapes using the determined optimal scale improvement time. All three models underestimated the daily ET, where the underestimation rate ranged from 19.68% to 30.05%. The simulation accuracy was highest for EF method and lowest for the crop coefficient method. Among them, the EF presented the highest accuracy, where the R2 values reached 0.92 and 0.89 in 2020 and 2021, respectively, whereas, the RRMSE was only 20.23%, and 21.49%, respectively. The ET scale increased from the day to the whole growth period, indicating the underestimation in the shoot growth period, the flowering, and the fruit setting period. There was an overestimation in the fruit expansion and maturity period. Consequently, the date of fruit expansion can be expected to simulate the increase of ET in the whole growth period of grapes. The simulation accuracy was highest for EF method and lowest for the crop coefficient method. Specifically, the EF model presented the highest simulation accuracy, where the simulation errors were only 1.8 and 7.4mm in 2020 and 2021, respectively, whereas the relative errors were only 0.68% and 2.73%, respectively. |
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| Keywords: | evapotranspiration transpiration greenhouse time scaling up evaporative fraction improved evaporative fraction crop coefficient |
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