地理学报 ›› 2021, Vol. 76 ›› Issue (11): 2697-2709.doi: 10.11821/dlxb202111008

• 气候变化与地表过程 • 上一篇    下一篇

地形对黄土高原滑坡的影响

胡胜1,2,3(), 邱海军1,2,3(), 王宁练1,2,3, 崔一飞4, 曹明明1, 王家鼎3,5, 王新刚3,5   

  1. 1.西北大学城市与环境学院,西安 710127
    2.陕西省地表系统与环境承载力重点实验室,西安 710127
    3.西北大学地表系统与灾害研究院,西安 710127
    4.清华大学水沙科学与水利水电工程国家重点实验室,北京 100084
    5.西北大学地质学系大陆动力学国家重点实验室,西安 710069
  • 收稿日期:2020-06-22 修回日期:2021-04-27 出版日期:2021-11-25 发布日期:2022-01-25
  • 通讯作者: 邱海军(1983-), 男, 陕西神木人, 博士, 教授, 主要从事山地灾害研究。E-mail: haijunqiu@nwu.edu.cn
  • 作者简介:胡胜(1988-), 男, 湖北枣阳人, 博士后, 中国地理学会会员(S110014073M), 主要从事黄土地质灾害研究。E-mail: shenghu@nwu.edu.cn
  • 基金资助:
    国家自然科学基金项目(42001006);国家自然科学基金项目(41771539);中国博士后科学基金(2019M663792);西北大学科研启动基金(360051900075)

The influence of terrain on loess landslides in Loess Plateau

HU Sheng1,2,3(), QIU Haijun1,2,3(), WANG Ninglian1,2,3, CUI Yifei4, CAO Mingming1, WANG Jiading3,5, WANG Xingang3,5   

  1. 1. College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China
    2. Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi'an 710127, China
    3. Institute of Earth Surface System and Hazards, Northwest University, Xi'an 710127, China
    4. State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
    5. State Key Laboratory of Continental Dynamics, Department of Geology, Northwest University, Xi'an 710069, China
  • Received:2020-06-22 Revised:2021-04-27 Published:2021-11-25 Online:2022-01-25
  • Supported by:
    National Natural Science Foundation of China(42001006);National Natural Science Foundation of China(41771539);China Postdoctoral Science Foundation(2019M663792);Scientific Research Foundation of Northwest University(360051900075)

摘要:

高分辨率地形与影像数据的缺乏已成为研究地表现象、特征与过程的重要瓶颈。低成本无人机设备和摄影测量技术的发展,打开了地学领域获取高分辨率数据的大门,大大提高了地质灾害野外调查与灾害编目的精度与效率。本文通过无人机野外调查和遥感室内目视解译,构建了一个包含307个黄土滑坡属性的数据库。在此基础上,通过数字地形分析和数理统计等方法,总结归纳了黄土滑坡样本数据的分布规律,探讨了地形对黄土滑坡分布的影响,阐述了地形相对高差对最长滑动距离、滑坡周长、滑坡面积的影响,提出了基于传统经验公式拟合的滑坡规模快速预测公式。结果表明:① 滑坡规模—频率分布具有明显的规律性,不同最大长度、最大宽度和周长的黄土滑坡数量分布均呈现正偏态分布,而不同面积的滑坡数量分布则服从幂函数分布;② 地形对黄土滑坡发育控制作用明显,不同地形高差、平均坡度、坡形的斜坡单元滑坡发育数量差异较大;③ 地形相对高差与滑坡的最长滑距、周长和面积的拟合曲线很好地符合幂律分布规律,但不同地形区的拟合效果有所差异,黄土丘陵区拟合效果最好,黄土高原全区次之,黄土台塬区最差;④ 本文建立的黄土滑坡规模快速预测模型,为黄土滑坡灾害调查提供了经验公式支撑。

关键词: 高分辨率, 地形, 黄土滑坡, 黄土高原

Abstract:

The lack of high-resolution terrain and image data has become a major bottleneck for geoscientists to study surface phenomena, features and processes. In recent years, the development of low-cost UAV equipment and photogrammetric technology makes it possible to obtain high-resolution data in the field of geoscience, which has greatly improved the accuracy and efficiency of geological disaster field survey and disaster cataloging. In this study, a database including 307 loess landslides was constructed through field investigation of UAV and remote sensing image interpretation. On this basis, through digital terrain analysis (DTA) and mathematical statistics, we summarize the distribution rule of loess landslides sample data, discuss the influence of terrain on the distribution of loess landslides is discussed, describe the influence of the relative height difference of terrain on the longest sliding distance, landslide perimeter, and landslide area, and propose formulas for quickly estimating landslide scale based on traditional empirical formula fitting. The results show that: (1) There are obvious regularities in the scale-frequency distribution of landslides. The frequency of loess landslides with different maximum lengths, maximum widths and perimeters shows a positive skew distribution, while the frequency distribution of landslides with different areas presents a power function pattern. (2) Terrain plays a significant role in controlling the development of loess landslides. The quantity of landslides on slope units with different height differences, average slopes, slope forms varies greatly. (3) The fitting curves of the relative height difference and the longest slipping distance, or landslide's perimeter, or landslide's area follow the power law distribution well. However, the fitting effects of different terrain areas are different. The loess hilly area has the best fitting effect, followed by the whole Loess Plateau, and the loess tableland area is the worst. (4) The rapid prediction models of loess landslide scale established in this study provide empirical formula support for landslide investigation.

Key words: high resolution, terrain, loess landslides, Loess Plateau