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草业学报 ›› 2017, Vol. 26 ›› Issue (10): 10-19.DOI: 10.11686/cyxb2017008

• 研究论文 • 上一篇    下一篇

2006-2013年三江源草地产草量的时空动态变化及其对降水的响应

张雅娴1, 2, 樊江文1, *, 曹巍1, 张海燕1, 2   

  1. 1.中国科学院地理科学与资源研究所,陆地表层格局与模拟重点实验室,北京100101;
    2.中国科学院大学,北京100049
  • 收稿日期:2017-01-09 出版日期:2017-10-20 发布日期:2017-10-20
  • 通讯作者: fanjw@igsnrr.ac.cn
  • 作者简介:张雅娴(1992-),女,辽宁东港人,博士。E-mail:zhangyx.15b@igsnrr.ac.cn
  • 基金资助:
    青海省科技支撑计划项目(2015-SF-A4-1)资助

Spatial and temporal dynamics of grassland yield and its response to precipitation in the Three River Headwater Region from 2006 to 2013

ZHANG Ya-Xian1, 2, FAN Jiang-Wen1, *, CAO Wei1, ZHANG Hai-Yan1, 2   

  1. 1.Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
    2.University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2017-01-09 Online:2017-10-20 Published:2017-10-20

摘要: 三江源地区是我国重要的江河发源地,分析该地区多年草地产草量的时空动态变化,探讨产草量与降水量的关系,对于在未来气候变化情景下合理管理草地、指导畜牧业发展具有重要意义。利用2006-2013年MODIS-NDVI数据和同期442个地面采样数据,对3个草地类型分别建立NDVI与实测产草量之间的经验关系模型,并用这些模型推算2006-2013年三江源草地产草量的分布;同时,从三江源不同类型草地产草量与年降水量、不同月份降水量及不同降水累积时期的关系入手,探讨三江源地区草地生产力如何响应降水格局的变化。结果表明,从整个三江源地区来看:(1)2006-2013年产草量呈现增加的趋势,不同草地类型产草量对年降水量变化的响应程度不同。(2)对产草量影响最重要的降水月份是前一年10月,其次是当年4和5月。(3)驱动产草量年际变化最重要的累积降水时期是前一年的10月到当年5月。(4)前一年秋季和当年春季的累积降水量对第二年产草量有着至关重要的影响。

Abstract: The Three River Headwater Region is one of the source areas of China’s major rivers. For better grassland management under future climate change scenarios and for the sustainable development of animal husbandry in this region, it is very important to understand the spatiotemporal dynamic changes of grassland yield and the relationship between grassland yield and local precipitation. In this study, we used MODIS-NDVI (Moderate Resolution Imaging Spectrometer-Normalized Difference Vegetation Index) data and 442 ground sampling data from 2006 to 2013 to construct empirical models for the correlation between NDVI and the yields of three types of grasslands. Then, we used these models to estimate the distribution of grassland yield in The Three River Headwater Region during 2006-2013. We also studied the response of grassland productivity to changes in precipitation patterns in the Three River Headwater Region based on the correlation between grassland yield and annual, monthly, and cumulative precipitation. The major conclusions were as follows: (1) Grassland yield showed an increasing trend during 2006-2013 in the Three River Headwater Region, and the yield of different grassland types showed different responses to annual precipitation. (2) The most important rainfall month for grassland yield was October of the previous year; rainfall in April and May of the current year also strongly contributed to grassland yield. (3) The cumulative precipitation from October (previous year) to May in the current year was the main cause of inter-annual variations in grassland yield. (4) The cumulative precipitation in autumn of the previous year and in spring of the current year was a key factor in current-year grassland output.