环境及生态因子对黄土高原典型农田生态系统鲍恩比的影响研究

任雪塬; 张强; 岳平; 杨金虎; 王胜

doi:10.11676/qxxb2022.015

环境及生态因子对黄土高原典型农田生态系统鲍恩比的影响研究

doi: 10.11676/qxxb2022.015

任雪塬^{1, 2,},
张强^{1, 2, 3},
岳平^{1, 2, 3, ,},
杨金虎⁴,
王胜^{1, 3}

1.
中国气象局兰州干旱气象研究所，兰州，730020
2.
兰州大学大气科学学院，兰州，730000
3.
甘肃省干旱气候变化与减灾重点实验室/中国气象局干旱气候变化与减灾重点实验室，兰州，730020
4.
兰州区域气候中心，兰州，730020

基金项目: 国家自然科学基金项目（41630426、41975016、41705075、41875020）和甘肃省基础研究创新群体项目（20JR5RA121）

详细信息

作者简介:
任雪塬，主要从事陆气相互作用研究。E-mail：rxy_atsc@163.com

通讯作者:
岳平，主要从事陆气相互作用研究。E-mail： jqyueping@126.com

中图分类号: P404
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出版历程
- 收稿日期: 2021-03-01
- 录用日期: 2022-02-28
- 修回日期: 2021-11-22
- 网络出版日期: 2021-12-23

Impacts of environmental factors on Bowen ratio in typical farmland ecosystem in the Loess Plateau

REN Xueyuan^{1, 2
,},
ZHANG Qiang^{1, 2, 3},
YUE Ping^{1, 2, 3
, ,},
YANG Jinhu⁴,
WANG Sheng^{1, 3}

1.
Institute of Arid Meteorology，China Meteorological Administration，Lanzhou 730020，China
2.
College of Atmospheric Sciences，Lanzhou University，Lanzhou 730000，China
3.
Key Laboratory of Arid Climatic Change and Reducing Deserter of Gansu Province；Key Laboratory of Arid Climatic Change and Reducing Deserter，China Meteorological Administration，Lanzhou 730020，China
4.
Lanzhou Regional Climate Center，Lanzhou 730020，China

摘要

摘要: 鲍恩比能够综合反映陆面气候状态的物理特性，是有效刻画生态系统水热分配的关键参数之一。本研究利用安装在定西和庆阳的涡动相关系统开展了黄土高原半干旱和半湿润农田生态系统能量分配特征观测试验，研究了生态环境因子对鲍恩比的影响机理，揭示了干、湿条件下生理生态因子对水热交换的响应规律。结果表明，处于半干旱区的定西年内感热通量是可利用能量的主要消耗项，即使在降水较为集中的季风期，其鲍恩比依旧在1附近波动。对于半湿润地区的庆阳而言，夏季潜热通量在能量分配中占主导地位（鲍恩比平均为0.71），其余三季感热在能量分配中起支配作用（鲍恩比为1.15—5.85）。从影响陆面水热交换的气象因子来看，鲍恩比随饱和水汽压差的增大而增大，随降水量和土壤湿度的增大而显著减小。干旱条件下，鲍恩比与半湿润区饱和水汽压差的相关更高（R²=0.44）；湿润条件下，则与半干旱区的饱和水汽压差相关更好（R²=0.38），且生长季半干旱区的鲍恩比为半湿润区的1.5倍。半湿润区干、湿条件下降水量与鲍恩比均显著相关，干旱条件下R²达到0.79；但半干旱区仅在干旱条件下降水量与鲍恩比存在显著的相关（R²=0.40）。土壤含水量在半湿润区与鲍恩比的相关更显著，且干旱条件下鲍恩比随土壤含水量的降低而增大的幅度更大。从影响生长季鲍恩比的生态因子来看，Priestley-Taylor系数与鲍恩比满足幂函数规律，在黄土高原农田生态系统具有显著的相关，半湿润区和半干旱区R²分别为0.62和0.72。另外，黄土高原农田生态系统鲍恩比随归一化植被指数的增大而减小，半湿润区二者关系更显著（R²=0.40），但半干旱区鲍恩比对归一化植被指数变化的响应更迅速。冠层气孔导度与鲍恩比呈负指数关系，半干旱区鲍恩比随冠层气孔导度的增大而减小的趋势比半湿润区更明显。该研究对揭示黄土高原典型农田生态系统陆面特征及改进陆面过程参数化关系具有重要参考意义。
- 黄土高原 /
- 农田生态系统 /
- 生理生态因子 /
- 鲍恩比
Abstract: The Bowen ratio can comprehensively reflect physical characteristics of land surface climate state and is one of the key parameters that describe water and heat distribution of the ecosystem. In this paper, the eddy correlation systems installed in Dingxi and Qingyang are used to carry out the observation experiment on energy distribution characteristics in semi-arid and semi-humid farmland ecosystem over the Loess Plateau. Meanwhile, the influence mechanism of eco-environmental factors on the Bowen ratio is studied. This study also reveals the response law of physiological and ecological factors to water and heat exchanges under dry and wet conditions. The results show that sensible heat flux in Dingxi, a semi-arid region, is the main consumption item of available energy. Even in the monsoon season when precipitation is relatively concentrated, its Bowen ratio still fluctuates around 1. For the situation in Qingyang, which is located in the semi-humid area, latent heat flux in summer plays a dominant role in energy distribution, and sensible heat fluxes dominates the energy distribution in the rest of the season (the Bowen ratio is between 1.15—5.85). From the perspective of meteorological factors that affect land surface water and heat exchanges, the Bowen ratio increases with increasing VPD (vapor pressure deficit), and decreases significantly with increasing precipitation and soil moisture. Under arid condition, the Bowen ratio has a higher correlation with VPD in semi-humid areas (R²=0.44) and a higher correlation with VPD in semi-arid areas (R²=0.38) under humid conditions. In addition, the Bowen ratio in the semi-arid region is 1.5 times higher than that in the semi-humid region during the growing season. In semi-humid areas, there is a significant correlation between precipitation and the Bowen ratio under both dry and wet conditions, and the determination coefficient even reaches 0.79 under drought condition. However, in semi-arid areas, the correlation is significant (R²=0.40) only in drought condition. The correlation between soil water content (SWC) and the Bowen ratio is more significant in semi-humid areas, and the Bowen ratio increases with decreasing SWC under drought condition. From the perspective of ecological factors that affect Bowen ratio in the growing season, the relationship between the Priestley-Taylor coefficient ($\alpha $) and the Bowen ratio satisfies the power function law. There is a high correlation in the farmland ecosystem over the Loess Plateau, and the determination coefficients for semi-humid and semi-arid areas are 0.62 and 0.72 respectively. The Bowen ratio decreases with increasing NDVI (Normalized Difference Vegetation Index), and this phenomenon is more obvious in the semi-humid zone (R²=0.40). However, the response of the Bowen ratio to NDVI in semi-arid area is faster than that in semi-humid area. There is a negative exponential relationship between the canopy stomatal conductance (G_s) and the Bowen ratio. The Bowen ratio has a declining trend with increasing G_s in semi-arid areas than in semi-humid areas. This study reveals the land surface characteristics in typical farmland ecosystem over the Loess Plateau and provides an important reference for improving the parameterization of land surface process.
- Loess Plateau /
- Farmland ecosystem /
- Physiological and ecological factors /
- Bowen ratio

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图 1 研究区地理位置（星号为定西和庆阳站）

Figure 1. Geographical location of the study area （stars denote Dingxi and Qingyang stations）

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图 2 定西（a）和庆阳（b）站生态环境因子的季节和年际变化

Figure 2. Seasonal and interannual variations of eco-environmental factors in Dingxi （a） and Qingyang （b） stations

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图 3 能量平衡残差频率分布概率密度曲线

Figure 3. Frequency distribution and probability density curve of energy balance residual

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图 4 定西和庆阳能量通量年平均日变化（a. 净辐射，b. 潜热通量，c. 感热通量，d. 土壤热通量）

Figure 4. Annual averages of diurnal variations of energy fluxes in Dingxi and Qingyang （a. R_n，b. LE，c. H，d. G）

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图 5 能量通量季节平均日变化曲线（a. 净辐射，b. 潜热通量，c. 感热通量，d. 土壤热通量；1—4分别表示春季、夏季、秋季和冬季）

Figure 5. Seasonal average diurnal variation curves of energy flux （a. R_n，b. LE，c. H，d. G；1—4 represents spring，summer，autumn and winter， respectively）

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图 6 定西（a）和庆阳（b）能量分量的季节变化

Figure 6. Seasonal variations of energy components in Dingxi （a） and Qingyang （b）

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图 7 生长季定西和庆阳感热、潜热通量的累积分数曲线（a）及箱线图（b）

Figure 7. Cumulative fraction curves （a） and box plots （b） of sensible and latent heat fluxes in Dingxi and Qingyang during the growing season

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图 8 定西（a）和庆阳（b）鲍恩比季节变化及（c）多年季节平均

Figure 8. Seasonal variation of Bowen ratio in Dingxi （a） and Qingyang（b） and multi-year seasonal average （c）

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图 11 定西（a）和庆阳（b）各影响因子的通径图（实线箭头和虚线箭头分别代表正、负相关）

Figure 11. Path diagram of the impact factors in Dingxi （a） and Qingyang （b）（solid arrows and dotted arrows indicate positive and negative correlations，respectively）

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图 12 月尺度上归一化表面阻抗与鲍恩比（a）和Priestley-Taylor系数（b）的关系（灰色点线代表为两站的总体拟合关系）

Figure 12. Relationships between normalized surface impedance （$R_{\rm s}^* $） and （a） Bowen ratio，（b） $ \alpha $ on monthly time scale （gray dotted line represents the overall trend of the above relationships）

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表 1 实验仪器型号及安装高度

Table 1. Experimental instrument type and installation height

仪器	型号	安装高度
仪器	型号	定西站	庆阳站
气体分析仪	Li-7500，Li-Cor	2.5 m	3 m
三维超声风速仪	CSAT-3，Campbell	2.5 m	3 m
温、湿度计	HMP45C-L，Vaisala	1、2、4、10、16 m	2、4、8、18 m
净辐射计	CNR4，Kipp & Zone	1.5 m	1.5 m
热流板	HFP01SC-L50，Hukseflux	2 cm	1、2.5 cm
土壤温度探头	STP01-L50，Hukseflux	0、5、10、20、30、40、50、80 cm	0、5、10、20、40、60、90 cm
水含量反射计	CS616-L，Campbell	10、20、40、50、80 cm	5、10、20、60、90 cm

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表 2 本研究中使用的数据集

Table 2. Details regarding the datasets used in this study

数据类型	数据来源	观测要素	资料时段	观测地点
陆面综合观测试验资料	农业气象试验站	湍流通量，近地层温、湿、风梯度，辐射，土壤温、湿梯度等	2016年8月—2019年5月 2011年7月—2019年6月 2011年7月—2012年7月	定西
陆面综合观测试验资料	农业气象试验站	湍流通量，近地层温、湿、风梯度，辐射，土壤温、湿梯度等	2013年5月—10月 2015年12月—2016年5月 2018年5月—2019年7月	庆阳
常规气象观测资料	中国气象数据网	地温、气温、气压、降水等	2011年7月—2019年6月 1980年1月—2010年12月	定西、西峰
卫星遥感观测资料	NASA	归一化植被指数	2011年7月—2019年6月（时间分辨率为16 d）	中国区域内（空间分辨率为250 m）

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表 3 能量通量和环境要素

Table 3. Energy fluxes and environmental factors

站点	时间		S_r^* （MJ/m²）	R_n （MJ/m²）	H （MJ/m²）	LE （MJ/m²）	G （MJ/m²）	β	T_a （℃）	VPD （kPa）	雨量（mm）	ET^* （mm）	α	NDVI
定西	全年	2016	8544.0	3415.4	1698.6	853.2	388.4	3.8	11.8	0.9	275.9	348.1	0.5	0.3
		2017	8420.8	3324.0	1690.6	1020.2	461.2	3.3	11.4	0.9	405.4	416.2	0.7	0.3
		2018	8590.9	3699.1	1353.8	1298.5	267.9	2.6	10.7	0.8	478.9	529.8	0.6	0.3
		2019	8340.7	3547.3	1587.4	1014.8	263.4	4.1	11.0	0.8	405.4	414.0	0.5	0.3
	生长季	2016	5871.3	2605.4	1176.0	724.0	350.9	2.5	18.5	1.2	262.7	295.4	0.6	0.4
		2017	5782.2	2548.8	1136.7	877.0	392.6	2.3	18.0	1.2	363.8	357.8	0.7	0.4
		2018	5900.5	3028.6	916.9	1165.6	281.8	1.2	18.7	1.0	421.0	475.6	0.7	0.4
		2019	5684.4	2735.0	1072.2	903.9	258.1	2.2	17.8	1.0	371.0	368.8	0.6	0.4
庆阳	全年	2011	5827.2	2984.9	1044.4	1501.5	168.8	2.0	11.6	0.7	614.5	612.6	0.7	0.4
		2012	5918.9	2753.0	792.5	1579.5	119.9	1.9	12.0	0.7	493.6	644.4	0.7	0.4
		2013	6084.0	2972.4	1050.2	1572.2	156.1	1.9	11.9	0.7	745.8	641.5	0.7	0.5
		2015	6212.7	3141.8	1111.1	1575.0	155.1	2.0	11.6	0.7	493.7	642.6	0.7	0.5
		2016	6015.2	3084.7	1165.0	1554.0	166.2	1.9	11.5	0.7	507.9	634.0	0.7	0.5
		2018	6238.9	2921.8	1123.0	1427.5	170.8	2.8	10.5	0.6	687.2	582.4	0.5	0.4
		2019	5914.0	2915.4	997.3	1316.0	140.9	3.7	11.0	0.7	545.4	536.9	0.6	0.4
	生长季	2011	4034.2	2246.9	668.7	1284.2	177.2	0.7	18.3	0.9	498.7	524.0	0.8	0.5
		2012	3946.8	2092.8	485.9	1342.7	147.7	0.8	19.7	1.0	448.7	547.8	0.9	0.5
		2013	4060.0	2234.4	619.2	1379.3	175.1	0.6	18.7	0.9	724.3	562.7	0.9	0.6
		2015	3962.7	2250.9	631.6	1335.1	175.1	0.7	18.2	0.9	446.8	544.7	0.8	0.6
		2016	3989.3	2200.7	667.9	1317.5	181.7	0.8	18.2	0.9	482.1	537.5	0.8	0.6
		2018	4272.1	2377.4	690.4	1248.7	188.8	0.9	17.5	0.8	637.1	509.5	0.6	0.5
		2019	4027.3	2219.4	648.5	1213.9	163.3	0.8	18.1	0.9	506.0	495.3	0.8	0.5
*：S_r为短波辐射，ET为蒸散量。

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表 4 试验站地表能量平衡特征

Table 4. Characteristics of energy balance in different regions

站点	白天				夜间				全天
	样本数	普通最小二乘法		能量平衡比	样本数	普通最小二乘法		能量平衡比	样本数	普通最小二乘法		能量平衡比
	样本数	k	R²	能量平衡比	样本数	k	R²	能量平衡比	样本数	k	R²	能量平衡比
定西	10516	0.65	0.68	0.89	11190	0.18	0.05	0.03	40350	0.76	0.81	0.68
庆阳	5149	0.71	0.71	0.81	7773	0.11	0.05	0.49	24064	0.73	0.85	0.60

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表 5 能量分量年平均日变化峰值和日均值

Table 5. Annual average daily variation peak and daily average value of energy components

站点	R_n （W/m²）		LE （W/m²）		H （W/m²）		G （W/m²）
站点	峰值	均值	峰值	均值	峰值	均值	峰值	均值
定西	334.10	67.29	64.14	20.95	120.29	28.98	157.88	6.08
庆阳	348.37	71.74	125.83	41.41	122.32	28.50	96.93	1.62

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表 6 能量通量季节平均日峰值和日均结果

Table 6. Seasonal averages of peak and daily average values of energy fluxes

能量分量（W/m²）		春季		夏季		秋季		冬季
能量分量（W/m²）		定西	庆阳	定西	庆阳	定西	庆阳	定西	庆阳
R_n	峰值	345.02	376.71	440.16	460.16	362.38	348.03	226.45	240.88
R_n	均值	67.73	77.14	109.87	119.84	78.76	75.02	25.34	26.20
LE	峰值	39.31	82.61	103.10	169.41	101.19	168.67	22.55	21.63
LE	均值	11.77	25.70	36.00	74.11	32.54	58.31	5.23	6.64
H	峰值	148.75	162.54	143.10	112.81	107.21	110.68	93.27	118.66
H	均值	34.85	34.02	41.31	30.49	28.59	25.33	17.93	21.93
G	峰值	173.24	109.18	214.49	125.82	124.15	97.69	136.16	56.19
G	均值	10.34	6.68	20.07	8.67	1.24	−2.29	−3.29	−6.94

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