1998—2017年中国典型森林生态系统潜在蒸散的变化趋势及成因

doi:10.18402/resci.2020.05.10

资源科学 ›› 2020, Vol. 42 ›› Issue (5): 920-932.doi: 10.18402/resci.2020.05.10

1998—2017年中国典型森林生态系统潜在蒸散的变化趋势及成因

孙婉馨^1,^2,³, 张黎^1,^2,⁴(), 任小丽^1,², 何洪林^1,^2,⁴, 吕妍^1,^2,³, 牛忠恩^1,^2,³, 常清青^1,^2,³

1.中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室,北京 100101;
2.国家生态科学数据中心,北京 100101;
3.中国科学院大学,北京 100049;
4.中国科学院大学资源与环境学院,北京 100049

收稿日期:2019-10-07 修回日期:2020-03-07 出版日期:2020-05-25 发布日期:2020-07-25
通讯作者: 张黎
作者简介:孙婉馨,女,河北保定人,硕士生,研究方向为生态系统生态学。E-mail: sunwanxin95@126.com
基金资助:
国家重点研发计划项目(2016YFC0500204);国家自然科学基金项目(31971512);中国科学院科技服务网络计划项目(KFJ-SW-STS-167)

Trends and influencing factors of potential evapotranspiration in typical forest ecosystems of China during 1998-2017

SUN Wanxin^1,^2,³, ZHANG Li^1,^2,⁴(), REN Xiaoli^1,², HE Honglin^1,^2,⁴, Lü Yan^1,^2,³, NIU Zhongen^1,^2,³, CHANG Qingqing^1,^2,³

1. Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
2. National Ecosystem Science Data Center, Beijing 100101, China;
3. University of Chinese Academy of Sciences, Beijing 100049, China;
4. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

Received:2019-10-07 Revised:2020-03-07 Online:2020-05-25 Published:2020-07-25
Contact: Li ZHANG

摘要/Abstract

摘要：

潜在蒸散（PET）是计算实际蒸散、评价区域干湿状况和合理规划水资源的关键因子。本文基于1998—2017年中国生态系统研究网络（CERN）11个森林生态系统定位研究站的逐日气象数据,分别采用Penman-Monteith和Priestley-Taylor两种方法计算各森林生态系统的潜在蒸散（PET_PM和PET_PT）,分析近20年潜在蒸散年总量的变化趋势及成因,并量化了基于邻近国家气象站观测数据计算的PET_{_}_CMA偏差。两种方法均表明,近20年来7个森林生态系统的潜在蒸散呈下降趋势。风速是长白山温带针阔混交林和鹤山亚热带人工常绿阔叶林潜在蒸散变化的主导因子,而净辐射主导了其他9个森林的潜在蒸散变化。PET_{_}_CMA年总量较PET_PM偏高,主要是由于国家气象站下垫面的气温、风速和净辐射均高于森林定位研究站,而相对湿度偏低。北部和东部森林邻近气象站的风速和净辐射变化趋势偏高,导致PET_{_}_CMA变化趋势偏高,而其他森林邻近气象站PET_{_}_CMA变化趋势偏低主要源自相对湿度变化趋势偏高和净辐射变化趋势偏低。研究可为认识中国森林生态系统潜在蒸散的变化特征及其对气候变化的响应提供参考。

关键词: 潜在蒸散, 森林生态系统, 变化趋势, 气象因子, 中国生态系统研究网络, Penman-Monteith方法, Priestley-Taylor方法

Abstract:

Potential evapotranspiration (PET) is a key factor in calculating actual evapotrans-piration, evaluating regional dry and wet conditions, and water resources management. Using daily meteorological data at 11 typical forest sites of the Chinese Ecosystem Research Network (CERN) in the past 20 years, we estimated PET by both the Penman-Monteith equation and Priestley-Taylor equation, and analyzed the trend of PET and its climate attribution. The results of the two methods indicate that PET in seven typical forest ecosystems in China showed decreasing trends in the past 20 years. Wind speed dominated PET changes in the Changbai Mountain temperate coniferous and broadleaved mixed forest and the He Mountain subtropical artificial evergreen broadleaved forest, while net radiation dominated PET changes in other forests. We also quantified the difference between PET at each forest site (PET_PM) and that estimated by meteorological data from a nearby site of China Meteorological Administration (PET_{_}_CMA). On average, PET_{_}_CMA is higher than PET_PM, mainly because the meteorological stations are mostly with higher temperature, wind speed, and net radiation, and lower relative humidity than the CERN forest sites. For the forests in northern and eastern China, PET_{_}_CMA trends were higher than PET_PM, because the former have higher wind speed and net radiation trends. In contrast, PET_{_}_CMA trends were lower than PET_PM for other forests, which are mainly due to their higher trend of relative humidity and lower trend of net radiation. The research can provide a reference for understanding the characteristics of the potential evapotranspiration in China’s forest ecosystems and its response to climate change.

Key words: potential evapotranspiration, forest ecosystems, trends, meteorological factors, Chinese Ecosystem Research Network (CERN), Penman-Monteith method, Priestley-Taylor method

孙婉馨, 张黎, 任小丽, 何洪林, 吕妍, 牛忠恩, 常清青. 1998—2017年中国典型森林生态系统潜在蒸散的变化趋势及成因[J]. 资源科学, 2020, 42(5): 920-932.

SUN Wanxin, ZHANG Li, REN Xiaoli, HE Honglin, Lü Yan, NIU Zhongen, CHANG Qingqing. Trends and influencing factors of potential evapotranspiration in typical forest ecosystems of China during 1998-2017[J]. Resources Science, 2020, 42(5): 920-932.

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森林生态系统名称	海拔/m	年均温/^oC	年降水/mm	优势种	土壤类型	参考文献
长白山温带针阔混交林（CBF）	801.00	3.62	727.93	蒙古栎、色木槭、红松、水曲柳	暗棕壤	文献[25]
北京暖温带落叶阔叶混交林（BJF）	1263.00	4.80	530.38	油松、华北落叶松、辽东栎	棕壤	文献[26]
茂县暖温带针阔混交林（MXF）	1826.00	9.30	825.20	云杉、红桦	棕壤	文献[27]
神农架亚热带常绿落叶阔叶混交林（SNF）	1750.00	10.64	1456.71	米心水青冈、锐齿槲栎、红桦	黄棕壤	文献[28]
贡嘎山亚高山暗针叶林（GGF）	3160.00	4.80	1860.50	峨眉冷杉、糙皮桦	暗棕壤	文献[29]
千烟洲亚热带人工常绿针叶林（QYF）	100.00	17.90	1489.00	湿地松、杉木、马尾松	红壤	文献[30]
会同亚热带次生常绿阔叶林（HTF）	700.00	16.47	1234.01	红栲、青冈、刨花楠	红壤、红黄壤	文献[31]
哀牢山亚热带湿性常绿阔叶林（ALF）	2488.00	11.68	1728.54	木果石栎、多花含笑	黄棕壤	文献[32]
鼎湖山亚热带季风常绿阔叶林（DHF）	290.00	22.25	1844.36	木荷、厚壳桂	赤红壤	文献[33]
鹤山亚热带人工常绿阔叶林（HSF）	80.00	21.98	1663.71	马占相思	赤红壤	文献[34]
西双版纳热带季雨林（BNF）	750.00	22.65	1396.70	番龙眼、千果榄仁	砖红壤	文献[35]

	春季		夏季		秋季		冬季
	PET_PM	PET_PT	PET_PM	PET_PT	PET_PM	PET_PT	PET_PM	PET_PT
CBF	-1.21	-0.60	-0.65	-0.76	0.06	0.90	-0.67**	-0.25**
BJF	-1.65	-2.70*	-5.74**	-7.51**	-3.71**	-4.28**	-0.79**	-0.61**
MXF	0.44	1.76	1.71	3.84	-0.47	0.42	0.62	0.84
SNF	0.03	0.46	2.15	3.25	-0.31	-0.05	1.49	2.09
GGF	0.03	0.06	-1.89*	-2.24*	-0.77	-1.03	-0.30	-0.45
QYF	0.01	-1.36	-1.92	-2.69	-2.28*	-3.60**	-0.04	-0.90
HTF	-0.76	-0.72	2.43	2.81	-0.16	-0.04	0.61	0.44
ALF	2.10	4.26*	0.29	0.88	1.97	3.09*	0.40	2.48*
DHF	-0.54	-0.74	0.17	-0.21	-0.65	-0.73	0.29	0.18
HSF	-2.35**	-2.33*	-1.63	-0.85	-1.06	0.42	-0.36	0.62
BNF	-2.87*	-3.57*	-3.21*	-4.10*	-2.27	-2.91	-1.34	-1.70

	大气压	平均气温	相对湿度	风速	净辐射
CBF	-0.27	0.11	-0.04	0.10	0.60
BJF	-0.23	0.15	-0.03	0.15	0.62
MXF	-0.25	0.28	-0.82	0.07	0.72
SNF	-0.34	0.25	-0.37	0.02	0.85
GGF	-0.41	0.13	-0.02	-0.01	0.91
QYF	-0.25	0.36	-0.04	0.04	0.83
HTF	-0.18	0.38	-0.06	0.10	0.71
ALF	-0.24	0.33	-1.11	0.04	0.75
DHF	-0.14	0.43	-0.72	0.11	0.76
HSF	-0.14	0.44	-0.07	0.11	0.76
BNF	-0.26	0.34	-0.02	0.01	0.96
平均	-0.24	0.29	-0.30	0.07	0.77

	大气压/(kPa/a)		平均气温/(^oC/a)		相对湿度/(%/a)		风速/(m/s/a)		净辐射/(MJ/m²/a)
	CERN	CMA	CERN	CMA	CERN	CMA	CERN	CMA	CERN	CMA
CBF	-0.03**	0.01**	0.01	0.03	-0.07	0.00	-0.05**	0.00	-0.01	-0.02*
BJF	0.00	0.00	0.02	0.03	-0.13	-0.12	-0.02**	-0.04**	-0.14**	0.00
MXF	0.00	0.00	0.01	0.06	0.33*	0.50	-0.01	-0.06*	0.06	0.04
SNF	0.01*	-0.04	0.06	0.01	0.38*	0.43	0.01	0.03	0.05	0.04
GGF	0.00	0.00	0.04*	0.00	0.12	0.23	0.00	-0.01*	-0.04*	0.00
QYF	-0.01*	-0.01*	0.02	0.02	-0.37*	0.17	0.00	0.01	-0.07*	0.00
HTF	0.00	0.00	0.01	0.02	-0.12	-0.07	-0.01	-0.01	0.02	-0.01
ALF	0.00	0.01	0.03	0.05*	0.24	0.49	0.01	0.01*	0.09*	0.04
DHF	0.01*	-0.02**	0.02	-0.06**	-0.07	0.43*	-0.01*	0.03	-0.01	0.01
HSF	-0.01*	-0.02**	0.02	-0.03	0.12	0.13	-0.08**	0.00	-0.02	0.03**
BNF	0.00	0.00	0.04*	0.00	-0.05	0.02	-0.01**	0.04**	-0.09*	-0.01

	大气压	平均气温	相对湿度	风速	净辐射
CBF	0.03	0.22	0.48	-5.32	-0.71
BJF	0.00	0.40	0.74	-3.65	-9.41
MXF	-0.01	0.15	-3.65	-0.61	4.30
SNF	-0.02	0.80	-1.59	0.39	4.27
GGF	0.00	0.55	-0.29	-0.02	-3.14
QYF	0.02	0.25	2.78	0.25	-6.31
HTF	0.00	0.18	1.32	-0.79	1.37
ALF	0.00	0.67	-3.74	0.44	6.56
DHF	0.00	0.46	1.08	-1.23	-1.34
HSF	0.00	0.42	-2.00	-9.38	-1.72
BNF	0.00	0.60	0.17	-1.05	-9.92

1998—2017年中国典型森林生态系统潜在蒸散的变化趋势及成因

Trends and influencing factors of potential evapotranspiration in typical forest ecosystems of China during 1998-2017

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	年均值/(MJ/m²)			变化趋势/(MJ/m²/a)			拟合的辐射系数
	观测值	原始值	反推值	观测值	原始值	反推值	a_s	b_s	R²
CBF	13.42	12.46	13.62	-0.04	-0.02	-0.02	0.28	0.53	0.60
BJF	10.15	11.60	8.96	-0.16	-0.02	-0.02	0.15	0.52	0.49
MXF	12.04	12.70	11.92	-0.02	0.01	0.01	0.18	0.64	0.86
SNF	12.61	12.76	12.51	0.01	-0.02	-0.02	0.20	0.63	0.61
GGF	9.06	10.95	8.50	0.08	0.07	0.10	0.13	0.72	0.69
QYF	12.10	13.94	11.44	-0.03	-0.04	-0.04	0.14	0.59	0.76
HTF	10.79	11.51	10.51	-0.03	0.03	0.03	0.20	0.59	0.63
ALF	14.29	13.95	14.21	0.04	0.10	0.12	0.23	0.58	0.83
DHF	13.15	12.78	12.92	-0.02	0.04	0.05	0.23	0.59	0.66
HSF	12.54	11.32	12.32	-0.03	0.08	0.08	0.28	0.50	0.47
BNF	15.41	15.26	15.46	-0.01	0.01	0.01	0.26	0.49	0.68

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