西北干旱区灌溉绿洲农田生态系统冠层导度估算及其在蒸散计算中的应用

doi:10.11867/j.issn.1001-8166.2020.040

地球科学进展 ›› 2020, Vol. 35 ›› Issue (5): 523 -533. doi: 10.11867/j.issn.1001-8166.2020.040

郭飞 ^1, ²(

),吉喜斌 ¹(

),金博文 ¹,赵丽雯 ¹,焦丹丹 ³,赵文玥 ^1, ²,张靖琳 ^1, ²

^1.中国科学院西北生态环境资源研究院临泽内陆河流域研究站，中国科学院生态水文与流域科学重点实验室，甘肃兰州 730000
^2.中国科学院大学，北京 100049
^3.北京师范大学地理科学学部，地表过程与资源生态国家重点实验室，北京 100875

收稿日期:2019-12-31 修回日期:2020-04-14 出版日期:2020-05-10
通讯作者: 吉喜斌 E-mail:guofei18@lzb.ac.cn;xuanzhij@lzb.ac.cn
基金资助:
国家自然科学基金项目“干旱区绿洲—荒漠过渡带能水交换及其组分拆分研究”(41771041)

Quantification of Canopy Conductance of the Agroecosystem in an Irrigated Oasis in Arid Regions of Northwest China and Its Application in Evapotranspiration Estimation

Fei Guo ^1, ²( ),Xibin Ji ¹( ),Bowen Jin ¹,Liwen Zhao ¹,Dandan Jiao ³,Wenyu Zhao ^1, ²,Jinglin Zhang ^1, ²

^1.Linze Inland River Basin Research Station，Key Laboratory of Ecohydrology and Watershed Science，Northwest Institute of Eco-Environment and Resources，Chinese Academy of Sciences，Lanzhou 730000, China
^2.University of Chinese Academy of Sciences, Beijing 100049, China
^3.State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

Received:2019-12-31 Revised:2020-04-14 Online:2020-05-10 Published:2020-06-05
Contact: Xibin Ji E-mail:guofei18@lzb.ac.cn;xuanzhij@lzb.ac.cn
About author:Guo Fei (1996-), female, Shijiazhuang City, Hebei Province, Master student. Research areas include ecohydrology and micrometeorology. E-mail: guofei18@lzb.ac.cn
Supported by:
the National Natural Science Foundation of China "Study on energy-water exchange and its composition in oasis-desert transition zone in arid region"(41771041)

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冠层导度是植被与大气间碳、水、热交换的关键调控因子，可靠合理的冠层导度估计对于量化陆地表面蒸散的物质与能量交换具有重要意义。基于Jarvis模型原理，采用叶片气孔导度对环境因子响应的分时段函数和叶面积指数构建了适用于西北干旱区灌溉绿洲农田生态系统的冠层导度模型，并用Penman-Monteith方程结合环境因子观测数据和涡度相关数据的反推计算结果对模型进行了验证，结果表明冠层导度模型能够提供合理的预测；应用该模型进一步计算了在叶面积指数大于3时的蒸散，模拟值与实测值也具有很好的一致性；此外，叶片气孔导度向冠层导度的尺度提升需要考虑遮荫系数(shelter factor)，并拟合得到了其与叶面积指数的对应函数关系。这为干旱区土壤水分条件较好的农田生态系统提供了估算冠层导度和提高蒸散计算准确度的方法，对于理解植物与大气间物质和能量交换机制以及当地的水资源管理具有重要意义。

关键词: 叶片气孔导度, 冠层导度, Jarvis模型, 灌溉农田, 玉米

Canopy conductance (g_c) is a key regulating factor of carbon, water and heat exchange between vegetation and atmosphere. Reliable and reasonable g_c estimation is of great significance for quantifying evapotranspiration (ET) mass and energy exchange at terrestrial surface. Based on the Jarvis model, a canopy conductance model of agroecosystem in an irrigated oasis, located in arid regions of Northwestern China, was formulated by using the time-piecewise functions of the response of leaf stomatal conductance (g_s) to environmental factors and Leaf Area Index (LAI). The developed gc model was tested with the calculated results derived from the inversion of the Penman-Monteith (PM) equation, in combination with observations of environmental variables and ET measured by the Eddy Covariance (EC) method, suggesting that the developed g_c model can provide reasonable prediction. In order to further assess the performance of the developed gc model, we consequently calculated ET under the conditions that LAI was larger than three, indicating that the estimation was in good agreement with the observations from EC method. It should be noted that the scaling leaf stomatal conductance to canopy conductance needs to take into account shelter factor (f_s), and the corresponding function relation with LAI is obtained by fitting. These results from our present study will provide a useful approach to quantifying the g_c of agroecosystems under the well-watered conditions in arid climatic areas, and then can improve the performance of ET estimation, which have important implications for well understanding the controlling mechanisms of plant on energy exchange and ET, and even for local water resources management.

Key words: Leaf stomatal conductance, Canopy conductance, Jarvis model, Irrigated cropland, Maize.

中图分类号:

P935.1

图1 气孔导度(a)和光合有效辐射(b)、饱和水汽压差(c)、大气温度(d)的平均日变化

Fig.1 Mean diurnal variations of stomatal conductance (g_s) (a), Photosynthetically Active Radiation (PAR) (b), Vapor Pressure Deficit (VPD) (c) and air temperature (T) (d)

图2 叶片气孔导度对光合有效辐射(a)、饱和水汽压差(b)和大气温度(c)的迟滞响应

Fig.2 Hysteresis loops between stomatal conductance and environmental variables (Photosynthetically Active Radiation (PAR) (a), Vapor Pressure Deficit (VPD) (b), air temperature (T) (c)

表1 各响应函数表达式及决定系数

Table 1 Fitting functions and its coefficient of determination

环境变量	响应函数	7:00-11:00		11:00-17:00		17:00-21:00
环境变量	响应函数	参数取值	决定系数	参数取值	决定系数	参数取值	决定系数
PAR	$f 1 P A R = a 1 + a 2 P A R$ ^{[ 36 ]}	a₁=0.051 a₂=9.810×10^-5	0.682	a₁=0.083 a₂=5.230×10^-5	0.191	a₁=0.045 a₂=0.0002	0.351
	$f 2 P A R = a 1 e x p (a 2 P A R)$ ^{[ 37 ]}	a₁=0.066 a₂=0.001	0.691	a₁=0.090 a₂=0.0004	0.194	a₁=0.050 a₂=0.002	0.359
	$f 3 P A R = (a 1 + a 2 P A R / a 3) (1 + P A R / a 3)$ ^{[ 38 ]}	a₁=0.067 a₂=-0.103 a₃=-3 158.5	0.692	a₁=0.094 a₂=-0.025 a₃=-3 972.2	0.195	a₁=0.050 a₂=-0.079 a₃=-1 356.6	0.359
VPD	$f 1 V P D = b 1 + b 2 V P D$ ^{[ 8 ]}	b₁=-0.008 b₂=0.057	0.292	b₁=0.348 b₂=-0.053	0.531	b₁=0.018 b₂=0.017	0.106
	$f 2 V P D = b 1 e x p (b 2 V P D)$ ^{[ 39 ]}	b₁=0.051 b₂=0.386	0.270	b₁=0.662 b₂=-0.399	0.542	b₁=0.036 b₂=0.208	0.092
	$f 3 V P D = b 1 (b 2 + V P D)$ ^{[ 21 ]}	b₁=-0.395 b₂=-5.445	0.251	b₁=0.372 b₂=-1.176	0.530	b₁=-0.389 b₂=-8.765	0.081
T	$f T = ? c 1 + c 2 T$ ^{[ 40 ]}	c₁=-0.177 c₂=0.011	0.352	c₁=0.448 c₂=-0.009	0.372	c₁=-0.052 c₂=0.004	0.063
T	$f T = c 1 + c 2 T + c 3 T 2$ ^{[ 40 ]}	c₁=-0.984 c₂=0.070 c₃=-0.001	0.373	c₁=-1.046 c₂=0.078 c₃=-0.001	0.404	c₁=0.111 c₂=-0.007 c₃=0.0002	0.064

表1 各响应函数表达式及决定系数

Table 1 Fitting functions and its coefficient of determination

环境变量	响应函数	7:00-11:00		11:00-17:00		17:00-21:00
环境变量	响应函数	参数取值	决定系数	参数取值	决定系数	参数取值	决定系数
PAR	$f 1 P A R = a 1 + a 2 P A R$ ^{[ 36 ]}	a₁=0.051 a₂=9.810×10^-5	0.682	a₁=0.083 a₂=5.230×10^-5	0.191	a₁=0.045 a₂=0.0002	0.351
	$f 2 P A R = a 1 e x p (a 2 P A R)$ ^{[ 37 ]}	a₁=0.066 a₂=0.001	0.691	a₁=0.090 a₂=0.0004	0.194	a₁=0.050 a₂=0.002	0.359
	$f 3 P A R = (a 1 + a 2 P A R / a 3) (1 + P A R / a 3)$ ^{[ 38 ]}	a₁=0.067 a₂=-0.103 a₃=-3 158.5	0.692	a₁=0.094 a₂=-0.025 a₃=-3 972.2	0.195	a₁=0.050 a₂=-0.079 a₃=-1 356.6	0.359
VPD	$f 1 V P D = b 1 + b 2 V P D$ ^{[ 8 ]}	b₁=-0.008 b₂=0.057	0.292	b₁=0.348 b₂=-0.053	0.531	b₁=0.018 b₂=0.017	0.106
	$f 2 V P D = b 1 e x p (b 2 V P D)$ ^{[ 39 ]}	b₁=0.051 b₂=0.386	0.270	b₁=0.662 b₂=-0.399	0.542	b₁=0.036 b₂=0.208	0.092
	$f 3 V P D = b 1 (b 2 + V P D)$ ^{[ 21 ]}	b₁=-0.395 b₂=-5.445	0.251	b₁=0.372 b₂=-1.176	0.530	b₁=-0.389 b₂=-8.765	0.081
T	$f T = ? c 1 + c 2 T$ ^{[ 40 ]}	c₁=-0.177 c₂=0.011	0.352	c₁=0.448 c₂=-0.009	0.372	c₁=-0.052 c₂=0.004	0.063
T	$f T = c 1 + c 2 T + c 3 T 2$ ^{[ 40 ]}	c₁=-0.984 c₂=0.070 c₃=-0.001	0.373	c₁=-1.046 c₂=0.078 c₃=-0.001	0.404	c₁=0.111 c₂=-0.007 c₃=0.0002	0.064

表2 白天各时段模型表达式及决定系数

Table 2 Fitting functions of stomatal conductance and its coefficient of determination for different periods of daytime

不同时段	模型表达式	2010年决定系数	2011年决定系数
7:00-11:00	$g c = g m a x a 1 + a 2 P A R / a 3 1 + P A R / a 3 (b 1 + b 2 V P D) (c 1 + c 2 T + c 3 T 2)$	0.805	0.806
11:00-17:00	$g c = g m a x a 1 + a 2 P A R / a 3 1 + P A R / a 3 b 1 e x p (b 2 V P D) (c 1 + c 2 T + c 3 T 2)$	0.704	0.789
17:00-21:00	$g c = g m a x a 1 + a 2 P A R / a 3 1 + P A R / a 3 (b 1 + b 2 V P D) (c 1 + c 2 T + c 3 T 2)$	0.654	0.618
全天	$g c = g m a x a 1 + a 2 P A R / a 3 1 + P A R / a 3 b 1 e x p (b 2 V P D) (c 1 + c 2 T + c 3 T 2)$	0.706	0.730

表2 白天各时段模型表达式及决定系数

Table 2 Fitting functions of stomatal conductance and its coefficient of determination for different periods of daytime

不同时段	模型表达式	2010年决定系数	2011年决定系数
7:00-11:00	$g c = g m a x a 1 + a 2 P A R / a 3 1 + P A R / a 3 (b 1 + b 2 V P D) (c 1 + c 2 T + c 3 T 2)$	0.805	0.806
11:00-17:00	$g c = g m a x a 1 + a 2 P A R / a 3 1 + P A R / a 3 b 1 e x p (b 2 V P D) (c 1 + c 2 T + c 3 T 2)$	0.704	0.789
17:00-21:00	$g c = g m a x a 1 + a 2 P A R / a 3 1 + P A R / a 3 (b 1 + b 2 V P D) (c 1 + c 2 T + c 3 T 2)$	0.654	0.618
全天	$g c = g m a x a 1 + a 2 P A R / a 3 1 + P A R / a 3 b 1 e x p (b 2 V P D) (c 1 + c 2 T + c 3 T 2)$	0.706	0.730

图3 气孔导度模拟值与实测值比较
分时段模型：(a)2010年拟合，(b)2011年验证；未分时段模型：(c)2010年拟合，(d)2011年验证

Fig.3 Comparison between simulated and measured values of stomatal conductance
Time-piecewise model： (a) Fitting in 2010， (b) Validation in 2011; Unsegmented model： (c) Fitting in 2010，(d) Validation in 2011

表3 模型拟合结果统计分析

Table 3 Statistical analyses between measured and estimated values

数据组	R²	RMSE	MAE	d
分时段气孔导度模型/[mol/(m²·s)]	0.837	0.019	0.015	0.801
全天气孔导度模型/[mol/(m²·s)]	0.706	0.033	0.022	0.687
冠层导度模型/(mm/s)(晴天)	0.665	1.956	1.605	0.644
冠层导度模型/(mm/s)(阴天和多云天)	0.606	1.499	1.192	0.603
蒸腾模型/(mm/h)(晴天)	0.782	0.048	0.038	0.765
蒸腾模型/(mm/h)(阴天和多云天)	0.756	0.024	0.018	0.749

表3 模型拟合结果统计分析

Table 3 Statistical analyses between measured and estimated values

数据组	R²	RMSE	MAE	d
分时段气孔导度模型/[mol/(m²·s)]	0.837	0.019	0.015	0.801
全天气孔导度模型/[mol/(m²·s)]	0.706	0.033	0.022	0.687
冠层导度模型/(mm/s)(晴天)	0.665	1.956	1.605	0.644
冠层导度模型/(mm/s)(阴天和多云天)	0.606	1.499	1.192	0.603
蒸腾模型/(mm/h)(晴天)	0.782	0.048	0.038	0.765
蒸腾模型/(mm/h)(阴天和多云天)	0.756	0.024	0.018	0.749

图4 冠层导度模拟值与实测值日变化
（a）晴天；（b）阴天和多云天

Fig.4 Diurnal variation of simulated and measured canopy conductance
(a） Sunny days; （b） Cloudy days

图5 半小时蒸散模拟值与实测值日变化
（a）晴天；（b）阴天和多云天

Fig.5 Diurnal variation of simulated and measured evapotranspiration for 30 min
(a） Sunny days; （b） Cloudy days

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