地理研究 ›› 2014, Vol. 33 ›› Issue (1): 23-30.doi: 10.11821/dlyj201401003

• 气候变化 • 上一篇    下一篇

山体基面高度对青藏高原及其周边地区雪线空间分布的影响

韩芳1, 张百平2, 谭靖3, 周亮广4, 李伟涛4, 刘民士4   

  1. 1. 山东农业大学信息科学与工程学院, 泰安271018;
    2. 中国科学院地理科学与资源研究所, 北京100101;
    3. 北京东方泰坦科技股份有限公司, 北京100083;
    4. 滁州学院, 滁州239000
  • 收稿日期:2012-11-21 修回日期:2013-07-05 出版日期:2014-01-10 发布日期:2014-01-10
  • 通讯作者: 张百平(1965- ),男,研究员,博士生导师,研究领域为山地生态与GIS应用。E-mail:zhangbp@lreis.ac.cn E-mail:zhangbp@lreis.ac.cn
  • 作者简介:韩芳(1981- ),女,汉族,山东兖州人,理学博士,主要从事山地GIS与山地生态学研究。E-mail:hanfah@163.com
  • 基金资助:
    国家自然科学基金项目(41030528,40971064);安徽省自然科学基金项目(1208085QD78);北京市科技新星计划(Z131101000413086)

The effect of mountain basal elevation on the distribution of snowline with different mountain basal elevations in Tibetan Plateau and its surrounding areas

HAN Fang1, ZHANG Baiping2, TAN Jing3, ZHOU Liangguang4, LI Weitao4, LIU Minshi4   

  1. 1. College of Information Science and Engineering, Shandong Agricultural University, Tai'an 271018, Shandong, China;
    2. State Key Laboratory of Resource and Environment Information System, Institute of Geographic Sciencesand Natural Resources Research, CAS, Beijing 100101, China;
    3. Beijing Oriental TITAN Technology Co., Ltd, Beijing 100083, China;
    4. Geographic Information and Tourism College, Chuzhou University, Chuzhou 239000, Anhui, China
  • Received:2012-11-21 Revised:2013-07-05 Online:2014-01-10 Published:2014-01-10

摘要: 山体效应是地理地带性之外,在大尺度上影响垂直带分布的主要因素,山体基面高度则是山体效应的第一影响因子。青藏高原及其周边地区,雪线呈现出中心高、周围低,与山体基面高度相一致的环状分布模式。为分析山体基面高度对雪线分布的影响,本文共收集青藏高原及周边地区雪线数据142个,采用纬度、经度和基面高度为自变量的三元一次方程拟合研究区雪线分布,计算各自的标准回归系数和相对贡献率,再将基面高度划分成5个子集(0~1000 m、1001~2000 m、2001~3000 m、3001~4000 m和4001~5000 m),分析基面高度不同的山地对雪线的影响差异。结果表明:① 在青藏高原,纬度、经度和基面高度对雪线高度分布的相对贡献率分别为51.49%、16.31%和32.20%;② 随着基面高度的增高,各子集模型的决定系数虽有逐渐降低的趋势,但仍保持在较高的值域(R2=0.895~0.668),说明模型的有效性;③ 随基面高度的抬升,纬度和山体基面高度对雪线分布高度的相对贡献率分别表现出降低(92.6%~48.99%,R2=0.855)和增大(3.33%~31.76%,R2=0.582)的趋势,表明基面高度越高,其对雪线分布高度的影响越大。

关键词: 山体效应, 山体基面高度, 雪线, 空间分布, 相对贡献率, 青藏高原

Abstract: Mountain elevation effect (MEE) is a major factor responsible for the spatial pattern of mountain altitudinal belts. Mountain basal elevation (MBE) was thought to be the most important factor of MEE. And it almost can be regarded as MEE itself. In Tibetan Plateau and its surrounding areas, the contours of snowline present an approximation of rings, a large degree change from its basic distribution pattern with latitude. It was thought to have a close relationship with MEE and MBE. In order to quantitative analyze the Influence of MBE to snowline, we compiled 142 snowline descriptions from literatures covering the Tibetan Plateau and its surrounding areas. Snowline elevation was related to longitude, latitude and MBE, to construct a multivariate linear regression equation. And then, the standard regression coefficient and relative contribution of each influencing factors were counted out, so as to compare the influence of three factors. Afterwards, we divided all samples into 5 subsets according to their MBE (0-1000 m, 1001-2000 m, 2001-3000 m, 3001~ 4000 m, 4001-5000 m), for the purpose of analyzing the effect of MBE to the snowlines. The results turned out that, (1) to the whole research area, the relative contribution of latitude, longitude and MBE to snowline distribution reach to 30.60%, 26.53%, and 42.87%, respectively; (2) as the uplift of MBE and the reduction of research scale, the determination coefficient (R2) of each subset model diminishes and retains a high domain (0.668-0.895), which illustrates the significant and scientificity of the model clearly; (3) the relative contribution of latitude decreases linearly with the increase of MBE (92.6%-48.99%, R2=0.855), while the effect of MBE increases obviously with its uplift (3.33%-31.76%, R2=0.582), the higher the MBE, the more significant influence to snowline.

Key words: mass elevation effect, mountain basal elevation, snowline, spatial distribution, relative contribution, Tibetan Plateau