深圳岩溶空间发育规律统计分析

doi:10.16285/j.rsm.2021.2106

岩土力学 ›› 2022, Vol. 43 ›› Issue (7): 1899-1912.doi: 10.16285/j.rsm.2021.2106

深圳岩溶空间发育规律统计分析

刘动^{1, 2}，林沛元^{3, 4}，陈贤颖^{3, 4}，黄胜^{3, 4}，马保松^{3, 4}

1. 深圳市岩土综合勘察设计有限公司，广东深圳 518172；2. 深圳市龙岗地质勘查局，广东深圳 518172； 3. 南方海洋科学与工程广东省实验室（珠海），广东珠海 519080；4. 中山大学土木工程学院，广东广州 510275

收稿日期:2021-12-14 修回日期:2022-04-27 出版日期:2022-07-26 发布日期:2022-08-04
通讯作者: 林沛元，男，1986年生，博士，研究员，主要从事地下空间工程与海洋土木工程风险评估与智慧防控研究。E-mail: linpy23@mail.sysu.edu.cn E-mail:liudong04@126.com
作者简介:刘动，男，1986年生，博士，高级工程师，主要从事岩土工程勘察及设计方面的研究。
基金资助:
国家自然科学基金资助项目（No. 51979254）；国家自然科学基金青年基金资助项目（No. 52008408）；广东省基础与应用基础研究基金（No. 2021A1515012088）

Statistical analysis of karst spatial distribution in Shenzhen

LIU Dong^{1, 2}, LIN Pei-yuan^{3, 4}, CHEN Xian-ying^{3, 4}, HUANG Sheng^{3, 4}, MA Bao-song^{3, 4}

1. Shenzhen Comprehensive Geotechnical Engineering Investigation & Design Co.Ltd, Shenzhen, Guangdong 518172, China; 2. Shenzhen Longgang Geology Bureau, Shenzhen, Guangdong 518172, China; 3. Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519080, China; 4. School of Civil Engineering, Sun Yat-Sen University, Guangzhou, Guangdong 510275, China

Received:2021-12-14 Revised:2022-04-27 Online:2022-07-26 Published:2022-08-04
Supported by:
This work was supported by the National Natural Science Foundation of China (51979254), the National Natural Science Foundation for Young Scientists of China (52008408) and the Guangdong Basic and Applied Basic Research Foundation (2021A1515012088).

摘要/Abstract

摘要： 粤港澳大湾区建设是国家重大发展战略，而深圳市又是大湾区建设的核心引擎之一。深圳市岩溶地区行政区划上主要发育在龙岗区和坪山区，岩溶地质灾害给地下空间开发利用与城市安全构成极大挑战。通过收集深圳市岩溶勘察钻探数据，从地层岩性、基岩埋深与埋藏类型、地下水主要侵蚀指标、地下水埋深与年变化幅度、溶洞埋深、顶板厚度、洞高、充填情况、线溶率、见洞率、地表岩溶发育密度等方面对深圳市岩溶空间发育特征进行了统计分析。结果表明：深圳市岩溶主要为浅覆盖型，但溶洞空间特征变异性极大。从统计上讲，溶洞平均埋深约为20 m，平均洞高为2.5～4.0 m，以半充填为主，充填物主要为粉质黏土；平均线溶率约为15%，见洞率约为40%，地表岩溶发育密度超过300个/km²，综合上看，深圳场地岩溶发育等级超过90%为强发育。上述主要岩溶特征参数服从对数正态分布和Weibull分布。总体上，灰岩地层溶洞顶板厚度随着岩面埋深而呈现递减的趋势，而大理岩地层溶洞顶板厚度则与岩面埋深无关；已发育的溶洞高度与基岩面埋深、溶洞顶板厚度、地下水主要侵蚀指标及地下水埋深无关或弱正相关。研究成果为深圳市岩溶灾害风险评估提供了重要的先验信息。

关键词: 岩溶地质, 深圳市, 空间分布特征, 统计分析

Abstract: The construction of Guangdong-Hong Kong-Macao Greater Bay Area is a major national development strategy of China. Shenzhen is a core city in the Greater Bay area. The karst in Shenzhen typically is found in Longgang and Pingshan districts. It has brought great challenges and threats to the underground exploitation and ground construction safety for the city. In this paper, borehole data are first collected from karst geotechnical investigation projects in Shenzhen and from the relevant literature. Based on the data, the spatial features of the karst in Shenzhen are statistically characterized considering strata and rock type, rock stratum depth and burial type, main corrosive indices of the groundwater, depth of the karst caves, thickness of the cave ceiling, cave height, fillings, karst line ratio, karst borehole ratio, and ground karst growth density. Results showed that the karst in Shenzhen is typically buried shallowly, but largely varies as of the spatial features. Statistically, on average the karst cave is about 20 m in depth, 2.5 m to 4 m in height, and mainly half filled with silty clays. On average the karst is about 15% for line ratio, 40% for borehole ratio, and over 300 caves per km² for the ground karst growth density. Overall, over 90% of the sites are ranked as high in karst development. It is also found that the above karst parameters follow lognormal as well as Weibull distributions. The ceiling thickness tends to be smaller as the rock depth increases for limestone stratum, whereas these two factors are statistically uncorrelated at a significance level of 0.05 for marble stratum. The cave height appears to be statistically independent or positively weakly correlated to rock depth, ceiling thickness, underground corrosive indices, and groundwater table. The findings from this paper provide valuable priori information to risk assessment on karst hazards in Shenzhen.

Key words: karst geology, Shenzhen, spatial distribution characteristics, statistical analysis

中图分类号:

P 642

刘动, 林沛元, 陈贤颖, 黄胜, 马保松, . 深圳岩溶空间发育规律统计分析[J]. 岩土力学, 2022, 43(7): 1899-1912.

LIU Dong, LIN Pei-yuan, CHEN Xian-ying, HUANG Sheng, MA Bao-song, . Statistical analysis of karst spatial distribution in Shenzhen[J]. Rock and Soil Mechanics, 2022, 43(7): 1899-1912.

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深圳岩溶空间发育规律统计分析

Statistical analysis of karst spatial distribution in Shenzhen

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