河西走廊潜在蒸散发时空格局变化与气象因素的关系

doi:10.12118/j.issn.1000－6060.2023.108

摘要/Abstract

摘要：

蒸散发过程影响因素众多，潜在蒸散发（ET₀）与气象变量交互作用复杂，亟需揭示ET₀变化对气象变量的响应机理。基于河西走廊及周边21个气象站点气象资料，采用定性定量分析方法，以河西走廊整体及3分区2个空间尺度，揭示ET₀时空变化规律，明确ET₀对各气象因素变化敏感性及贡献。结果表明：（1）河西走廊及分区ET₀均呈显著波动上升趋势（Z>1.98），线性变化率2.94 mm·a^-1，且黑河分区变化最明显。（2） ET₀由东南向西北递增变化，中东部石羊河分区（1003.78 mm）、黑河分区（1031.30 mm）较小，西部疏勒河分区（1171.89 mm）较大。（3）河西走廊ET₀对气象因素变化敏感性排序为相对湿度（RH）、日最高气温（T_max）、日照时数（n）、平均风速（u）、日降水量（P），ET₀对RH减少最敏感，对P变化最不敏感。（4） u增大是造成河西走廊ET₀增大的主要原因，其次是RH减少、T_max升高、n增加。（5）疏勒河分区、黑河分区、石羊河分区ET₀呈增加变化，贡献最大因素分别为T_max（5.13%）、u（8.22%）、T_max（5.97%），贡献最小因素为n。气候因素中的风速和气温变化是河西走廊地区ET₀变化不容忽视的重要影响因素，研究成果对合理规划农田灌溉用水和提高农业水资源利用效率意义重大。

关键词: 潜在蒸散发, 气象变量, 响应, 定量关系, 河西走廊

Abstract:

Several factors affect the evapotranspiration process. Potential evapotranspiration (ET₀) interacts with meteorological variables in a complex manner. Therefore, there is an urgent need to determine the response mechanism of ET₀ changes to meteorological variables. Based on meteorological data from 21 meteorological stations in the Hexi Corridor, Gansu Province, China and its surrounding areas, qualitative and quantitative methods were adopted to reveal the spatiotemporal variation of ET₀ and to clarify the sensitivity of ET₀ to changes in various meteorological factors and contributions by taking two spatial scales of the Hexi Corridor as a whole and three subdistricts. The results showed the following: (1) ET₀ in both the Hexi Corridor and the subdistrict showed a significant fluctuating upward trend (Z>1.98), with a linear change rate of 2.94 mm·a^-1, and the most obvious change was observed in the Heihe subdistrict. (2) ET₀ increased from the southeast to northwest. It was smaller in the Shiyang River subdistrict (1003.78 mm) and Heihe subdistrict (1031.30 mm) in the central and eastern parts of the Hexi Corridor, and larger in the Shule River subdistrict (1171.89 mm) in the western part of the Hexi Corridor. (3) The sensitivity of ET₀ to changes in meteorological factors in the Hexi Corridor was ranked as relative humidity (RH), daily maximum temperature (T_max), sunshine duration (n), average wind speed (u), and daily rainfall (P), with ET₀ being the most sensitive to decreases in RH and least sensitive to changes in P. (4) The increase in u was the main cause of the increase in ET₀ in the Hexi Corridor, followed by a decrease in RH, increase in T_max, and increase in n. (5) The ET₀ in the subdistricts of the Shule River, Heihe River, and Shiyang River showed an increasing change, with the factors that contributed the most being T_max (5.13%), u (8.22%), and T_max (5.97%), respectively, and the factor that contributed the least being n. Variations in wind speed and air temperature were important factors that influenced the ET₀ change in the Hexi Corridor. The research results are significant for the rational planning of irrigation water use and improvement of the utilization efficiency of agricultural water resources.

Key words: potential evapotranspiration, meteorological variables, response, quantitative relation, Hexi Corridor

马亚丽, 牛最荣, 孙栋元. 河西走廊潜在蒸散发时空格局变化与气象因素的关系[J]. 干旱区地理, 2024, 47(2): 192-202.

MA Yali, NIU Zuirong, SUN Dongyuan. Relationship between changes in spatial and temporal patterns of potential evapotranspiration and meteorological factors in the Hexi Corridor[J]. Arid Land Geography, 2024, 47(2): 192-202.

图/表 9

图1

表1

图2

图3

表2

表3

表4

图4

表5

参考文献 32

[1]	王燕鑫, 李瑞平, 李夏子. 河套灌区不同土地类型生长季蒸散发量估算及其变化特征[J]. 干旱区研究, 2020, 37(2): 364-373.
	[ Wang Yanxin, Li Ruiping, Li Xiazi. Estimation and variability of evapotranspiration for different land types during the growing season in the Hetao Irrigation District[J]. Arid Zone Research, 2020, 37(2): 364-373. ]
[2]	阴晓伟, 吴一平, 赵文智, 等. 西北旱区潜在蒸散发的气候敏感性及其干旱特征研究[J]. 水文地质工程地质, 2021, 48(3): 20-30.
	[ Yin Xiaowei, Wu Yiping, Zhao Wenzhi, et al. Drought characteristics and sensitivity of potential evapotranspiration to climatic factors in the arid and semi-arid areas of northwest China[J]. Hydrogeology & Engineering Geology, 2021, 48(3): 20-30. ]
[3]	秦大河, 丁一汇, 王绍武, 等. 中国西部生态环境变化与对策建议[J]. 地球科学进展, 2002, 17(3): 314-319. doi: 10.11867/j.issn.1001-8166.2002.03.0314
	[ Qin Dahe, Ding Yihui, Wang Shaowu, et al. Ecological and environmental change in west China and its response strategy[J]. Advance in Earth Sciences, 2002, 17(3): 314-319. ]
[4]	施雅风, 沈永平, 李栋梁, 等. 中国西北气候由暖干向暖湿转型的特征和趋势探讨[J]. 第四纪研究, 2003, 23(2): 152-164.
	[ Shi Yafeng, Shen Yongping, Li Dongliang, et al. Discussion on the present climate change from warm-dry to warm-wet in northwest China[J]. Quaternary Sciences, 2003, 23(2): 152-164. ]
[5]	黄会平, 曹明明, 宋进喜, 等. 1957—2012年中国参考作物蒸散量时空变化及其影响因子分析[J]. 自然资源学报, 2015, 30(2): 315-326.
	[ Huang Huiping, Cao Mingming, Song Jinxi, et al. Temporal and spatial changes of potential evapotranspiration and its influencing factors in China from 1957 to 2012[J]. Journal of Natural Resources, 2015, 30(2): 315-326. ]
[6]	李霞, 刘廷玺, 段利民, 等. 科尔沁湿草甸参考作物蒸散发模拟分析[J]. 中国沙漠, 2020, 40(2): 134-143. doi: 10.7522/j.issn.1000-694X.2019.00077
	[ Li Xia, Liu Tingxi, Duan Limin, et al. Simulation of reference crop evapotranspiration and analysis of the factor effect in Horqin wet meadow[J]. Journal of Desert Research, 2020, 40(2): 134-143. ] doi: 10.7522/j.issn.1000-694X.2019.00077
[7]	郭雯雯, 黄生志, 赵静, 等. 渭河流域潜在蒸散发时空演变与驱动力量化分析[J]. 农业工程学报, 2021, 37(3): 81-89.
	[ Guo Wenwen, Huang Shengzhi, Zhao Jing, et al. Spatio-temporal dynamics and driving forces of potential evapotranspiration in the Wei River Basin[J]. Transactions of the Chinese Society of Agricultural Engineering, 2021, 37(3): 81-89. ]
[8]	郭小娇, 龚晓萍, 石建省, 等. 典型岩溶区潜在蒸散发变化及其影响因素[J]. 地质学报, 2019, 93(12): 3269-3281.
	[ Guo Xiaojiao, Gong Xiaoping, Shi Jiansheng, et al. The temporal variations of potential evapotranspiration and influence factors for a typical karst area[J]. Acta Ecologica Sinica, 2019, 93(12): 3269-3281. ]
[9]	刘昌明, 孙睿. 水循环的生态学方面: 土壤-植被-大气系统水分能量平衡研究进展[J]. 水科学进展, 1999, 10(3): 251-259.
	[ Liu Changming, Sun Rui. Ecological aspects of water cycle: Advances in soil-vegetation-atmosphere of energy and water fluxes[J]. Advances in Water Science, 1999, 10(3): 251-259. ]
[10]	Wen J, Wang X H, Guo M H, et al. Impact of climate change on reference crop evapotranspiration in Chuxiong City, Yunnan Province[J]. Procedia Earth and Planetary Science, 2012, 5: 113-119. doi: 10.1016/j.proeps.2012.01.019
[11]	Allen R G, Pereira L S, Raes D, et al. Crop evapotranspiration-guidelines for computing crop water requirements-FAO irrigation and drainage paper 56[M]. Rome, Italy: FAO-Food and Agriculture Organization of the United Nations, 1998.
[12]	祝昌汉. 再论总辐射的气候学计算方法(二)[J]. 南京气象学院学报, 1982(2): 196-206.
	[ Zhu Changhan. A further discussion on the climatological calculation method of total radiation (Ⅱ)[J]. Journal of Nanjing Institute of Meteorology, 1982(2): 196-206. ]
[13]	Hamed K H, Rao A R. A modified Mann-Kendall trend test for autocorrelated data[J]. Journal of Hydrology, 1998, 204(1-4): 182-196. doi: 10.1016/S0022-1694(97)00125-X
[14]	Sung J H, Chung E S, Kim Y, et al. Meteorological hazard assessment based on trends and abrupt changes in rainfall characteristics on the Korean Peninsula[J]. Theoretical and Applied Climatology, 2017, 127(1-2): 305-326. doi: 10.1007/s00704-015-1581-0
[15]	高惠璇. 应用多元统计分析[M]. 北京: 北京大学出版社, 2005.
	[ Gao Huixuan. Application of multivariate statistical analysis[M]. Beijing: Peking University Press, 2005. ]
[16]	屈家安, 曹杰. 主成分分析与聚类分析在青岛夏季气温变化研究中的应用[J]. 大气科学学报, 2014, 37(4): 517-520.
	[ Qu Jia’an, Cao Jie. Application of principal component analysis and cluster analysis in a study on the change of summer temperature in Qingdao[J]. Transactions of Atmospheric Sciences, 2014, 37(4): 517-520. ]
[17]	何亮. 主成分分析在SPSS中的应用[J]. 山西农业大学学报(社会科学版), 2007, 6(5): 20-22.
	[ He Liang. Principal components analysis in SPSS[J]. Journal of Shanxi Agricultural University (Social Science Edition), 2007, 6(5): 20-22. ]
[18]	Pearson K. Notes on the history of correlation[J]. Biometrika, 1920, 13(1): 25-45. doi: 10.1093/biomet/13.1.25
[19]	Spearman C. General intelligence, objectively determined and measured[J]. The American Journal of Psychology, 1904, 15(2): 201-292. doi: 10.2307/1412107
[20]	Kendall M. A new measure of rank correlation[J]. Biometrika, 1938, 30(1): 81-93. doi: 10.1093/biomet/30.1-2.81
[21]	杜家菊, 陈志伟. 使用SPSS线性回归实现通径分析的方法[J]. 生物学通报, 2010, 45(2): 4-6.
	[ Du Jiaju, Chen Zhiwei. Path analysis using SPSS linear regression[J]. Bulletin of Biology, 2010, 45(2): 4-6. ]
[22]	敬艳辉, 邢留伟. 通径分析及其应用[J]. 统计教育, 2006(2): 24-26.
	[ Jing Yanhui, Xing Liuwei. Path analysis and its application[J]. Statistical Education, 2006(2): 24-26. ]
[23]	刘昌明, 张丹. 中国地表潜在蒸散发敏感性的时空变化特征分析[J]. 地理学报, 2011, 66(5): 579-588.
	[ Liu Changming, Zhang Dan. Temporal and spatial change analysis of the sensitivity of potential evapotranspiration to meteorological influencing factors in China[J]. Acta Geographica Sinica, 2011, 66(5): 579-588. ] doi: 10.11821/xb201105001
[24]	Beven K. A sensitivity analysis of the Penman-Monteith actual evapotranspiration estimates[J]. Journal of Hydrology, 1979, 44(3): 169-190. doi: 10.1016/0022-1694(79)90130-6
[25]	杨林山, 李常斌, 王帅兵, 等. 洮河流域潜在蒸散发的气候敏感性分析[J]. 农业工程学报, 2014, 30(11): 102-109.
	[ Yang Linshan, Li Changbin, Wang Shuaibing, et al. Sensitive analysis of potential evapotranspiration to key climatic factors in Taohe River Basin[J]. Transactions of the Chinese Society of Agricultural Engineering, 2014, 30(11): 102-109. ]
[26]	Yin Y H, Wu S H, Chen G, et al. Attribution analyses of potential evapotranspiration changes in China since the 1960s[J]. Theoretical and Applied Climatology, 2010, 101(1/2): 19-28. doi: 10.1007/s00704-009-0197-7
[27]	胡晓萌, 张鑫, 雒舒琪, 等. 甘肃省不同气候区1961—2020年蒸散发时空变化及其影响因子[J]. 节水灌溉, 2022(11): 73-78. doi: 10.12396/jsgg.2022104
	[ Hu Xiaomeng, Zhang Xin, Luo Shuqi, et al. Temporal and spatial changes of potential evapotranspiration and its influencing factors in different climatic regions of Gansu Province from 1961 to 2020[J]. Water Saving Irrigation, 2022(11): 73-78. ] doi: 10.12396/jsgg.2022104
[28]	张彩霞, 花婷, 郎丽丽. 河西地区潜在蒸散发量变化及其敏感性分析[J]. 水土保持研究, 2016, 23(4): 357-362.
	[ Zhang Caixia, Hua Ting, Lang Lili. Analysis of potential evapotranspiration and its sensitivity in Hexi region[J]. Research of Soil and Water Conversation, 2016, 23(4): 357-362. ]
[29]	卓玛兰草. 甘肃省1960—2009年不同气候区潜在蒸散量敏感性分析研究[D]. 兰州: 西北师范大学, 2012.
	[ Zhuo Malancao. Sensitivity of the potential evapotranspiration to different climatic regions from 1960 to 2009 in Gansu Province[D]. Lanzhou: Northwest Normal University, 2012. ]
[30]	张春玲. 基于S-W模型的河西地区潜在蒸散发对气候和植被的敏感性研究[D]. 兰州: 西北师范大学, 2014.
	[ Zhang Chunling. Sensitivity of the potential evapotranspiration to climate and vegetation in Hexi Area based on S-W model[D]. Lanzhou: Northwest Normal University, 2014. ]
[31]	杨一飞, 杨鹏年, 汪昌树, 等. 新疆焉耆盆地农田耗水有效性评价[J]. 干旱区地理, 2023, 46(5): 730-741.
	[ Yang Yifei, Yang Pengnian, Wang Changshu, et al. Effectiveness evaluation of water consumption in agricultural land of Yanqi Basin, Xinjiang[J]. Arid Land Geography, 2023, 46(5): 730-741. ]
[32]	潘子豪, 杨胜天, 娄和震, 等. 缺测站干旱流域生态输水遥感监测与农业节水效益分析[J]. 干旱区地理, 2022, 45(3): 774-785.
	[ Pan Zihao, Yang Shengtian, Lou Hezhen, et al. Remote sensing monitoring of ecological water conveyance and benefits evaluation of agricultural water-saving in arid basin without observation station[J]. Arid Land Geography, 2022, 45(3): 774-785. ]

分区	多年平均值/mm	离散系数	最大值 /mm	最大值年份	最小值 /mm	最小值年份	线性变化率/mm·a^-1	变化趋势	统计量 Z值	显著性水平
河西走廊	1059.58	0.042	1152.16	2013	966.64	1993	2.943	↑	4.30	0.01
疏勒河分区	1196.82	0.039	1329.33	2018	1113.40	2003	1.975	↑	2.08	0.05
黑河分区	1013.48	0.059	1119.91	2017	904.49	1993	4.779	↑	5.38	0.01
石羊河分区	978.70	0.036	1054.01	2013	914.33	1992	2.331	↑	4.18	0.01

方法	成分	特征值	方差百分比/%	累积/%	T	T_max	T_min	e_a	n	P	RH	RH_min	u
主成分分析	1	4.019	44.658	44.658	0.989	0.994	0.959	0.842	-	-	-	-	-
	2	2.738	30.419	75.077	-	-	-	-	-0.637	0.720	0.882	0.871	-
	3	1.195	13.272	88.350	-	-	-	-	-	-	-	-	0.947
聚类分析		-	-	-	Ⅰ	Ⅰ	Ⅰ	Ⅰ	Ⅱ	Ⅲ	Ⅳ	Ⅳ	Ⅴ

气象因素		T	T_max	T_min	e_a	n	P	RH	RH_min	u
相关系数	Pearson	0.925	0.922	0.884	0.696	0.505	0.066	-0.400	-0.412	0.167
	Kendall	0.779	0.782	0.706	0.549	0.402	0.111	-0.307	-0.289	0.115
	Spearman	0.939	0.941	0.892	0.765	0.562	0.161	-0.443	-0.419	0.171
排序		2	1	3	4	5	9	6	7	8
选定指标			√			√	√	√		√

气象因素	通径系数	间接通径系数						相关系数
气象因素	通径系数	T_max	RH	n	u	P	Σ	相关系数
T_max	0.845	-	0.021	0.061	-0.005	0.000	0.077	0.922
RH	-0.084	-0.210	-	-0.072	-0.033	-0.001	-0.316	-0.400
n	0.140	0.370	0.043	-	-0.048	0.001	0.365	0.505
u	0.206	-0.019	0.014	-0.033	-	0.000	-0.039	0.167
P	-0.002	0.130	-0.037	-0.051	0.026	-	0.067	0.066

气象因素	河西走廊			疏勒河分区			黑河分区			石羊河分区
气象因素	敏感性系数	多年相对变化率/%	贡献率/%	敏感性系数	多年相对变化率/%	贡献率/%	敏感性系数	多年相对变化率/%	贡献率/%	敏感性系数	多年相对变化率/%	贡献率/%
T_max	0.617	6.14	3.79	0.519	9.88	5.13	0.631	10.61	6.70	0.544	10.97	5.97
RH	-1.082	-3.96	4.28	-0.867	1.49	-1.29	-1.003	-7.64	7.66	-0.901	-3.67	3.31
n	0.098	0.72	0.07	-0.158	0.20	-0.03	0.138	1.37	0.19	0.121	3.47	0.42
u	0.300	15.39	4.61	0.358	-10.50	-3.76	0.308	26.66	8.22	0.228	3.23	0.74
P	-0.124	42.96	-5.33	-0.099	40.51	-4.02	-0.113	30.75	-3.48	-0.118	13.31	-1.58