不同参考温度取值对三温模型反演植被蒸腾精度的影响

doi:10.17521/cjpe.2021.0219

摘要/Abstract

摘要：

参考温度的参数化过程一直是三温模型反演蒸散发及其蒸发、蒸腾组分的关键和难点。该研究基于典型城市草坪的波文比与热红外观测数据, 对三温模型植被蒸腾子模型中涉及的输入变量进行敏感性分析和误差分析, 确定对三温模型反演植被蒸腾精度最为关键的变量, 而后量化和对比输入变量参数化方法对三温模型计算草坪蒸腾的影响, 由此确定最佳的参考温度取值。结果表明: 1)参考叶片温度选择为整个纸片温度的最大值时反演效果最好(R² = 0.91, 均方根误差(RMSE) = 0.078 mm·h^-1); 2)采用植被冠层温度的最大值为参考温度时, 直接假定了植被最高温度冠层蒸腾为0 (实际存在一定的蒸腾速率), 所以容易低估实际蒸腾量, 造成三温模型反演精度略低于取值参考叶片温度最大值的方法, 但反演效果仍然较好(R² = 0.87, RMSE = 0.080 mm·h^-1)。因此, 考虑到参考叶片设置的局限性, 如果在实际应用中无法或者没有实际测量参考叶片温度时, 使用植被最大温度为参考温度也可达到较好的反演效果。

关键词: 参考温度, 植被蒸腾, 三温模型, 植被温度, 参数化过程

Abstract:

Aims Parameterization of reference temperature has always been the key and difficult part in calculating evapotranspiration and its evaporation and transpiration components by using three-temperature model. In this paper, the best value of reference temperature was determined by quantifying and comparing the influence of different reference temperature values on the accuracy of transpiration estimation by three-temperature model.

Methods Based on the Bowen ratio and thermal infrared observation data of a typical urban lawn, sensitivity analysis and error analysis were carried out on the input variables involved in the sub-model of the three-temperature model to determine the most critical variables for the accuracy of transpiration estimation. Then the influence of input variables parameterization on the calculation of transpiration was quantified and compared to determine the best value of reference temperature.

Important findings When using the three-temperature model, the best estimation is to select the maximum temperature of the whole piece of paper as the reference leaf temperature (R² = 0.91, root mean square error (RMSE) = 0.078 mm·h^-1). When the maximum value of the vegetation canopy temperature was used as the reference temperature, it is directly assumed that the transpiration at the maximum temperature of the vegetation is zero (there is a certain transpiration rate in fact). Therefore, it is easy to underestimate the actual transpiration, resulting in that the estimation accuracy of the three-temperature model was slightly lower than the accuracy of using the maximum value of the reference leaf temperature, but the estimation effect is still good (R² = 0.87, RMSE = 0.080 mm·h^-1). Therefore, considering the limitations of the reference leaf settings, if the reference leaf temperature cannot be measured in practical applications, the maximum temperature of the vegetation canopy as the reference temperature can be used to achieve good estimate results.

Key words: reference temperature, vegetation transpiration, three-temperature model, vegetation temperature, parameterization process

熊博文, 李桐, 黄樱, 鄢春华, 邱国玉. 不同参考温度取值对三温模型反演植被蒸腾精度的影响. 植物生态学报, 2022, 46(4): 383-393. DOI: 10.17521/cjpe.2021.0219

XIONG Bo-Wen, LI Tong, HUANG Ying, YAN Chun-Hua, QIU Guo-Yu. Effects of different reference temperature values on the accuracy of vegetation transpiration estimation by three-temperature model. Chinese Journal of Plant Ecology, 2022, 46(4): 383-393. DOI: 10.17521/cjpe.2021.0219

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2021.0219

https://www.plant-ecology.com/CN/Y2022/V46/I4/383

图/表 12

图1 研究区概况。A, 北京大学深圳研究生院校园。B, 波文比系统。

Fig. 1 Study area. A, Peking University Shenzhen Graduate School campus. B, Bowen ratio system.

表1 波文比系统气象观测传感器信息

Table 1 Sensor information of meteorological measurements at the Bowen ratio system

气象要素 Meteorological factor	仪器型号 Instrument model	安装高度 Height (m)	测量精度 Measuring accuracy
气温和相对湿度 Air temperature and relative humidity	225-050YA, Novalynx, Grass Valley, USA	2.0, 1.5	±3%, ±0.6 ℃
风速与风向 Wind speed and direction	200-WS-02, Novalynx, Grass Valley, USA	2.0	±0.2 m∙s^-1, ±3°
太阳辐射 Solar radiation	PYP-PA, Apogee, Santa Monica, USA	2.0	10-40 μV·W^-1·m^-2
有效光合辐射 Photosynthetic active radiation	QSOA-S, Apogee, Santa Monica, USA	2.0	<3%
太阳净辐射 Net solar radiation	240-100, Novalynx, Grass Valley, USA	2.0	<4%
土壤热通量 Soil heat flux	HFP01, Hukseflux, Center Moriche, USA	-0.05, -0.02	50 μV·W^-1·m^-2

图2 草坪和参考叶片的可见光与热红外图像。A, 草坪可见光图像。B, 草坪热红外图像。C, 参考叶片可见光图像。D, 参考叶片热红外图像。

Fig. 2 Visible light and thermal infrared images of the lawn and the reference leaf. A, Visible images of the lawn. B, Thermal infrared images of the lawn. C, Visible images of the reference leaf. D, Thermal infrared images of the reference leaf.

图3 净辐射的日间变化。

Fig. 3 Diurnal variation of the net radiation.

图4 气温(Ta)和植被表面温度(Tc)的日间变化。

Fig. 4 Diurnal variation of the air temperature (Ta) and vegetation canopy temperature (Tc).

图5 各参数敏感性系数的日间变化。Rn, 净辐射; Rn,cp, 参考叶片净辐射; Ta, 气温; Tc, 植被表面温度; Tcp, 参考叶片温度。

Fig. 5 Diurnal variation of the sensitivity coefficients of each parameter. Rn, net radiation; Rn,cp, reference leaf net radiation; Ta, air temperature; Tc, vegetation canopy temperature; Tcp, reference leaf temperature.

图6 气温(Ta)、植被表面温度(Tc)和参考叶片温度(Tcp)对结果造成误差的日变化。

Fig. 6 Diurnal variation of the deviation caused by air temperature (Ta), vegetation canopy temperature (Tc) and reference leaf temperature (Tcp).

图7 波文比法与三温模型(3T)不同参考叶片温度取值计算草坪蒸腾速率结果对比。A, B, 2018年5月30日。C, D, 2018年11月7日。

Fig. 7 Comparison of lawn transpiration rate calculated by Bowen ratio method and three-temperature model (3T) with different reference leaf temperature value. A, B, May 30, 2018. C, D, November 7, 2018.

表2 不同参考叶片温度取值下的回归方程参数

Table 2 Regression equation parameters under different reference leaf temperature values

观测日期 Observation date	斜率 Slope					相关系数 Correlation coefficient					均方根误差 Root mean square error (mm·h^-1)
观测日期 Observation date	最大值 Max	前10% 平均值 First 10% mean	前20% 平均值 First 20% mean	前50% 平均值 First 50% mean	平均值 Mean	最大值 Max	前10% 平均值 First 10% mean	前20% 平均值 First 20% mean	前50% 平均值 First 50% mean	平均值 Mean	最大值 Max	前10% 平均值 First 10% mean	前20% 平均值 First 20% mean	前50% 平均值 First 50% mean	平均值 Mean
05-30	1.02	1.04	1.04	1.06	1.10	0.89	0.89	0.89	0.89	0.89	0.075	0.080	0.081	0.084	0.104
05-31	1.19	1.13	1.13	1.14	1.12	0.92	0.89	0.88	0.87	0.82	0.073	0.080	0.083	0.088	0.115
06-01	0.95	0.92	0.93	0.94	0.96	0.93	0.92	0.92	0.92	0.91	0.082	0.082	0.081	0.080	0.080
06-02	0.92	0.84	0.85	0.87	0.89	0.87	0.81	0.82	0.83	0.86	0.083	0.078	0.073	0.067	0.057
08-01	0.87	0.88	0.88	0.88	0.88	0.98	0.98	0.98	0.98	0.97	0.066	0.061	0.060	0.058	0.051
08-05	1.27	0.83	0.83	0.83	0.82	0.99	0.96	0.96	0.96	0.96	0.039	0.090	0.089	0.087	0.082
08-09	0.85	0.84	0.84	0.81	0.77	0.92	0.91	0.91	0.90	0.87	0.100	0.091	0.089	0.087	0.088
10-03	1.05	1.07	1.08	1.14	1.08	0.93	0.92	0.92	0.91	0.90	0.066	0.069	0.071	0.077	0.091
10-19	1.06	1.08	1.08	1.15	1.10	0.97	0.97	0.97	0.96	0.97	0.066	0.065	0.065	0.064	0.065
11-07	1.02	1.05	1.06	1.17	1.08	0.98	0.98	0.97	0.96	0.97	0.067	0.065	0.064	0.063	0.063

图8 观测期间波文比法与三温模型(3T)不同参考叶片温度取值计算草坪蒸腾速率结果对比。

Fig. 8 Comparison of lawn transpiration rate calculated by Bowen ratio method and three-temperature model (3T) with different reference leaf temperature values during the observation period.

表3 各取值方法的回归方程参数

Table 3 Regression equation parameters obtained by different reference leaf temperature approach

不同参考叶片温度取值 Different reference leaf temperature	相关系数 Correlation coefficient	斜率 Slope	截距 Intercept	均方根误差 Root mean square error (mm·h^-1)
最大值 Max	0.91	0.98	-0.03	0.078
前10%平均值 First 10% mean	0.90	0.98	-0.03	0.079
前20%平均值 First 20% mean	0.90	0.99	-0.02	0.078
前50%平均值 First 50% mean	0.89	1.00	-0.02	0.078
平均值 Mean	0.86	1.01	-0.01	0.083

图9 观测期间波文比法与三温模型(3T)观测冠层最高温度为参考温度时计算草坪蒸腾速率结果对比。

Fig. 9 Comparison of lawn transpiration rate calculated by Bowen ratio method and three-temperature model (3T) with the maximum temperature of the observed canopy as reference temperature during the observation period.

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