中国沙漠 ›› 2016, Vol. 36 ›› Issue (2): 499-507.DOI: 10.7522/j.issn.1000-694X.2014.00206

• 天气与气候 • 上一篇    下一篇


王鹏涛1, 延军平1, 蒋冲2,3, 曹永旺1   

  1. 1. 陕西师范大学 旅游与环境学院, 陕西 西安 710119;<2r>2. 北京师范大学 全球变化与地球科学研究院/地表过程与资源生态国家重点实验室, 北京 100875;<2r>3. 西北农林科技大学 资源环境学院, 陕西 杨凌 712100
  • 收稿日期:2014-09-24 修回日期:2014-12-08 出版日期:2016-03-20 发布日期:2016-03-20
  • 作者简介:王鹏涛(1988-),男,陕西渭南人,博士研究生,主要研究环境变化与灾害防治。
  • 基金资助:

Spatial and Temporal Variations of Evapotranspiration and Its Influencing Factors in the Loess Plateau in Shaanxi-Gansu-Ningxia Region

Wang Pengtao1, Yan Junping1, Jiang Chong2,3, Cao Yongwang1   

  1. 1. College of Tourism and Environment, Shaanxi Normal University, Xian 710119, China;
    2. Academy of Disaster Reduction and Emergency Management/State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China;
    3. College of Resources and Environment, Northwest Agriculture and Forestry University, Yangling 712100, Shaanxi, China
  • Received:2014-09-24 Revised:2014-12-08 Online:2016-03-20 Published:2016-03-20

摘要: 分析陕甘宁黄土高原区地表蒸散变化特征及其影响因素,可以为区域水资源规划、生态环境改善提供依据。本文利用MOD16蒸散数据,统计分析了陕甘宁黄土高原区2000-2012年地表实际蒸散量的时空变化特征,并结合国家气象站点观测数据和基于像元的相关分析法探讨了其影响因素。结果表明:(1) 2000-2002年蒸散量迅速上升,在2003年达到最高值378.6 mm, 2003-2006年蒸散量呈下降趋势,2006年之后蒸散量呈现缓慢上升趋势。(2) 近13年来,陕甘宁黄土高原区多年平均蒸散量具有明显的空间差异,蒸散量自西北至东南递增,最南部的六盘山、子午岭、黄龙山地是3个主要的高值区;年蒸散量以夏季最多,其次是春季,秋季和冬季最少,且季节蒸散的分布与年蒸散的空间分布格局基本一致。(3) 陕甘宁黄土高原区蒸散量草地和耕地的贡献率最高,密灌丛、疏灌丛次之,常绿针叶林、森林草原贡献率则较小。(4) 陕甘宁黄土高原区动力因素对地表蒸散量影响以正相关为主,风速对该区影响较大;热力因素对地表蒸散量影响以负相关为主,其中气温与蒸散在空间上呈负相关的区域较大,日照时数与蒸散在空间上的负相关区域的面积次之;水分条件(降水量、相对湿度)对蒸散的影响也以正相关为主。

关键词: 黄土高原, 地表蒸散, 时空分布, 相关分析

Abstract: Evapotranspiration (ET) and its response to global change are one of the focuses of global change research and study on variations in evapotranspiration can provide credible data for regional water resources planning and ecological environment improvement. Based on MODIS-ET data, spatial-temporal variation patterns of evapotranspiration in the Loess Plateau in Shaanxi-Gansu-Ningxia Region during 2000-2012 were analyzed. Meanwhile, the influencing factors of the ET's variations in the Loess Plateau in Shaanxi-Gansu-Ningxia Region were analyzed by observation data of the meteorological stations and correlation coefficients calculation of ET to climate elements. The results showed that: (1) The average of ET in the Loess Plateau in Shaanxi-Gansu-Ningxia Region increased rapidly in 2000-2002 and peaked in 2003(378.6mm), and there was a downward trends in evapotranspiration in 2003-2006, after 2006 evapotranspiration showed a slow upward trend. (2)The spatial distribution pattern of annual ET was apparently various. ET increased gradually from the northwest to the southeast, and ET of southern forest regions, such as Liupanshan Mountain, Ziwuling Mountain and Huanglong Mountain were higher than that in other parts of the Loess Plateau in Shaanxi-Gansu-Ningxia Region. The maximum seasonal value of the ET lay in summer, then followed by spring, and the lest ET was in autumn and winter; the spatial distribution pattern of seasonal ET was basically the same as annual pattern. (3) Different land use/cover types had different contribution to the ET distribution in the Loess Plateau in Shaanxi-Gansu-Ningxia Region. The highest contribution rates were made by grasslands and croplands, closely followed by closed shrubland and open shrubland, while the evergreen needle leaf forest and woody savannas contributed less for ET distribution. (4) The influencing factors of ET were as the following: ET in main part was positively correlated with forceful factor, wind speed affected the ET significantly. The thermodynamical factor mainly negatively correlated with ET changes. The air temperature was negatively correlated with ET in most areas whereas sunshine hours in the less region with negative correspondence with ET than air temperature. Besides, it can be found that moisture condition like precipitation and relative humidityboth had strong positive effect on the ET.

Key words: Loess Plateau, evapotranspiration, spatial and temporal variations, correlation analysis