院报 ›› 2017, Vol. 34 ›› Issue (10): 57-63.DOI: 10.11988/ckyyb.20160660

• 工程安全与灾害防治 • 上一篇    下一篇

向家坝下游高边坡蓄水前后外观变形空间聚集性态对比分析

胡添翼1a,1b,2,许朴2,王成1a,1b   

  1. 1.河海大学 a.水文水资源与水利工程科学国家重点实验室; b.水资源高效利用与工程安全国家工程研究中心,南京 210098;
    2.上海市政工程设计研究总院 水利水运设计研究院,上海 200092
  • 收稿日期:2016-06-29 修回日期:2016-07-31 出版日期:2017-10-01 发布日期:2017-10-25
  • 作者简介:胡添翼(1991-),男,江苏南通人,助理工程师,硕士,研究方向为大坝安全监测,(电话)021-55009522(电子信箱)hutianyi@smedi.com。
  • 基金资助:
    国家自然科学基金重点项目(41323001, 51139001);高等学校博士学科点专项基金项目(20120094110005, 20120094130003, 20130094110010);江苏省杰出青年基金项目(BK20140039);水利部土石坝破坏机理与防控技术重点实验室基金项目(KY914002)

Comparative Analysis of Deformation Aggregation Behavior of High Slope in Downstream Xiangjiaba Dam

HU Tian-yi1,2,3, XU Pu3, WANG Cheng1,2   

  1. 1.State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China;
    2.National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing 210098, China;
    3.Water Conservancy & Water Transport Design Institute, Shanghai Municipal Engineering Design Institute, Shanghai 200092, China
  • Received:2016-06-29 Revised:2016-07-31 Online:2017-10-01 Published:2017-10-25

摘要: 水库蓄水会对周围工程与地质环境造成较大的影响,严重时甚至会引起岸体滑坡。基于空间计量学全局和局部空间自相关系数及其相关分析方法,以向家坝坝体下游坝后左岸人工高边坡为例,在传统研究只考虑二维坐标的情况下,进一步考虑不同测点的三维空间坐标,建立了考虑空间坐标的空间权重矩阵,计算了各个蓄水时段高边坡不同测点的外观变形数据的全局和局部空间自相关系数;对比了不同蓄水时段下游边坡外观变形的空间聚集性态,从而定位高边坡变形监测关键测点。研究结果表明:2种空间自相关系数可以有效探测变形数据的聚集程度,识别聚集区域;水库蓄水会在下游坡形成明显的空间聚集性变形,尤其是在蓄水初期变化最为剧烈,需要在该阶段加强观测。

关键词: 向家坝水库, 水库蓄水, 下游高边坡, 空间聚集性变形, 空间权重矩阵, 空间自相关系数

Abstract: Reservoir impoundment has a great impact on engineering and geological environment around the reservoir, and would even give rise to landslide. By adopting global and local spatial autocorrelation coefficients and their analysis method in spatial economics, we established the spatial weight matrix in consideration of 3-D spatial coordinates of measuring points for Xiangjiaba downstream high slope. Furthermore, we calculated the global and local spatial autocorrelation coefficients of deformation data during impoundment, and compared the aggregation behavior of high-slope deformation during different impoundment periods so as to determine key measurement points. The results showed that the global and local spatial autocorrelation coefficients could effectively detect the aggregation behavior of high-slope’s deformation. Apparent aggregative deformation in downstream slope would be induced during impoundment, in particular, the initial period of impoundment, which should be monitored in emphasis.

Key words: reservoir impoundment, downstream high-slope, visual deformation, spatial weight matrix, spatial autocorrelation coefficient

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