Alternative Title
NCKRI Symposium 2: Proceedings of the Thirteenth Multidisciplinary Conference on Sinkholes and the Engineering and Environmental Impacts of Karst
Files
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Publication Date
May 2013
Abstract
The aim of this paper is to describe improvements in the accuracy of forecasting karst collapse by summarizing the methods and analyzing their advantages and disadvantages. The forecasting methods were classified as geophysical surveys, monitoring of triggering factors, and strain measurements using optical fibers. Geophysical surveys can directly identify soil cavities, but the precision and depth of exploration are limited by equipment parameters and geological conditions. For example, ground penetrating radar can discover a soil cavity when the overburden layer is less than 15 m thick, and frequent scanning can determine changes in the soil cavity and predict sinkhole collapse when combined with a balance arch model. Monitoring of triggering factors is widely used to forecast karst collapse when the opening is caused by pumping, as the dynamic groundwater conditions can be acquired in real-time. However, the prediction criteria can be very difficult to obtain. In this paper we recommend a method based on the relationship between the times when anomalous monitoring data appear and the time a sinkhole opens. Using optical fibers to forecast karst collapse is the most advanced technology currently available in China. The location and time of sinkhole opening can be forecast by this method in theory, but some key issues have yet to be resolved. These issues include the strain correlation between the optical fiber and the soil, the effect of temperature on the optical fiber strain and the method of laying optical fibers in the soil. Finally, some proposals are suggested in the hope that they will generate public discussion, reducing the damage caused by karst collapse. -- Authors Open Access - Permission by Publisher See Extended description for more information.
Type
Conference Proceeding
Publisher
University of South Florida
Identifier
K26-04816
Recommended Citation
Meng, Yan; Dai, Jianling; and Jia, Long, "Typical methods for forecasting karst collapse in China NCKRI Symposium 2: Proceedings of the Thirteenth Multidisciplinary Conference on Sinkholes and the Engineering and Environmental Impacts of Karst" (2013). KIP Talks and Conferences. 138.
https://digitalcommons.usf.edu/kip_talks/138
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