Abstract: Ground subsidence, a slowly occurring and irreversible geological disaster, is an environmental geological problem which commonly occurs in the process of urbanization. In order to solve the problems of incomplete subsidence information obtained by the existing ground subsidence monitoring network and the lack of precision in monitoring urban ground subsidence, it needs to be optimized. In this paper, taking the ground subsidence monitoring network of Nanjing Yangtze River floodplain as an example, using the regionalized variable theory of geostatistics and the variational function theory, Kriging interpolation method is used to establish the variational function model for the ground subsidence monitoring network of the study area, and the standard deviation distribution characteristics of each monitoring network of the Yangtze River floodplain in Nanjing area are investigated for the optimization of the deployment. The results show that the ground subsidence monitoring networks in the study area has the problem of unreasonable distribution. After the optimization, 34 redundant and marginal monitoring wells are eliminated and 16 new monitoring wells are added; 49 redundant and marginal level points are exempted and 21 new level points are added; 18 groups of stratified settlement monitoring network are eliminated and 13 groups of stratified settlement monitoring points are added. The improved monitoring well network can maximize the acquisition of monitoring data while meeting the accuracy requirements, and efficiently optimizes the arrangement of the settlement monitoring network, with reasonable results.

Key words: land subsidence monitoring ')">

land subsidence monitoring , network')">network,  ')">geostatistics , theory')">theory,  ')">Kriging , interpolation')">interpolation,  ')">optimization , design')">design,  ')">geological , hazard')">hazard,  ')">variogram , model