吉林大学学报(地球科学版) ›› 2025, Vol. 55 ›› Issue (3): 919-929.doi: 10.13278/j.cnki.jjuese.20240155

• 地质工程与环境工程 • 上一篇    下一篇

基于栅格信息量法的区域地面沉降风险评价:以河北省沧州市为例

刘波1, 李诗浓1, 李伟2, 王文鹏1, 鲁程鹏1, 束龙仓1   

  1. 1.河海大学水文水资源学院,南京210098
    2.南京水利科学研究院,南京210024

  • 出版日期:2025-05-26 发布日期:2025-06-06
  • 作者简介:刘波(1980-), 女, 副教授, 硕士生导师, 主要从事地下水系统模拟与资源管理方面的研究 , E-mail: liubohhu@hhu.edu.cn
  • 基金资助:
    国家重点研发计划项目(2024YFC3211600,2021YFC3200502);水利部重大科技项目(SKS-2022041)

Risk Assessment of Regional Land Subsidence Based on Raster Information Quantity Method: Case Study in Cangzhou City of Hebei Province

Liu Bo 1, Li Shinong1, Li Wei2, Wang Wenpeng1, Lu Chengpeng1, Shu Longcang1#br#

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  1. 1. College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
    2. Nanjing Hydraulic Research Institute, Nanjing 210024, China
  • Online:2025-05-26 Published:2025-06-06
  • Supported by:
    Supported by the National Key Research and Development Program of China (2024YFC3211600,2021YFC3200502) and the Major Science and Technology Program of Ministry of Water Resources (SKS-2022041)

摘要: 地面沉降风险诱发因素复杂、空间分布差异较大,为科学开展地面沉降风险评估工作,本研究提出栅格信息量法的地面沉降风险评价方法。首先通过计算各栅格化评价指标与地表形变量之间的信息量值,定量表征两者之间的关联程度;然后构建包含危险性、脆弱性和暴露度3个方面共11项指标的评价体系;再采用主客观综合赋权方法确定权重并计算风险值,通过受试者工作特征曲线进行的可靠性检验后进行风险评价;最后将上述方法应用于2022年河北省沧州市地面沉降风险评价。结果表明:相较于脆弱性评价指标,危险性和暴露度评价指标的栅格信息量值偏高。危险性评价指标中,年平均地面沉降速率为高风险指标,当年平均地面沉降速率为-127~-17 mm/a时,信息量值为1.538,对地面沉降风险的危险性最大;暴露度评价指标中,人口密度为高风险指标,当人口密度>5 430人/km2时,信息量值为1.923,对地面沉降风险的暴露度最高。沧州市1 km空间分辨率下地面沉降风险等级为高、较高、中、较低、低五个等级的区域面积占比分别为9.90%、24.91%、31.12%、23.05%、11.02%;高风险区主要集中在沧州市主城区、肃宁县、黄骅市等区域,中风险地区主要分布于沧州市西部区域。栅格信息量法对沧州市地面沉降风险评价的可靠性较好,准确度达到0.714。

关键词: 风险评价, 栅格信息量法, 地面沉降, 主客观组合赋权, 河北省沧州市

Abstract:  Land subsidence risk inducing factors are complex and spatial distribution varies greatly, in order to scientifically carry out land subsidence risk assessment, this paper proposes the raster information quantity method for the evaluation of land subsidence risk. Firstly, the information value between each rasterized evaluation index and surface variables is calculated to quantitatively characterize the strength of the association between the influencing factors and the risk of land subsidence; Then, an evaluation system with 11 indexes is constructed, including hazard, vulnerability, and exposure; Then, the subjective-objective comprehensive weighting method is used to determine the weights and calculate the risk value, and the risk evaluation is carried out through the reliability test of the working characteristic curve of the subjects; Finally, the above methods were applied to the risk evaluation of land subsidence in Cangzhou City, Hebei Province, in 2022. The results show that the raster informativeness values of the hazard and exposure evaluation indicators are high compared to the vulnerability evaluation indicators. Among the hazard evaluation indicators, the annual average land subsidence rate is a high-risk indicator, and when the annual average land subsidence rate is -127--17 mm/a, the informativeness value is 1.538, which is the most hazardous for the risk of land subsidence; Among the exposure evaluation indicators, the population density is a high-risk indicator, and when the population density is >5 430 people/km2, the informativeness value is 1.923, which is the most hazardous for the risk of land subsidence. At 1 km spatial resolution, the area proportions of land subsidence risk levels in Cangzhou City are distributed as follows: 9.90% high risk, 24.91% relatively high risk, 31.12% medium risk, 23.05% relatively low risk, and 11.02% low risk; The high-risk areas were mainly concentrated in the main urban area of Cangzhou City, Suning County, Huanghua City and other areas, and the medium-risk areas were mainly distributed in the western area of Cangzhou City; The reliability of the raster information quantity method to evaluate the risk of land subsidence in Cangzhou City is good, and the accuracy reaches 0.714.


Key words: risk assessment, raster information quantity method, land subsidence, subjective-objective combination assignment, Cangzhou City, Hebei Province

中图分类号: 

  • P694
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