Land subsidence due to groundwater pumping: hazard
probability assessment through the combination
of Bayesian model and fuzzy set theory
J. Li, L. Zhu, H. Gong, J. Zhou, X. Li
Capital Normal University, Beijing, China
G. Guo, R. Wang
Beijing Institute of Hydrogeology and Engineering Geology, Beijing, China
Z. Dai
College of Construction Engineering, Jilin University, Changchun, China
H. Wang
China Institute of Geo-Environment Monitoring, Beijing, China
C. Zoccarato, P. Teatini
Dept. of Civil, Environmental and Architectural Engineering,
University of Padova, Padova, Italy
Land subsidence is a geological process mainly caused by groundwater overdraft. Numerical modeling of land
subsidence is the main method used for its simulation and prediction. The elastic skeletal storage coefficient
(Ske), inelastic skeletal storage coefficient (Skv), and the related
specific values (Sske and Sskv Sske and Sskv) are fundamental
parameters to quantify land subsidence. In this paper, a novel approach integrating fast independent component
analysis (Fast-ICA) with variable preconsolidation head decomposition method is proposed to disentangle Sske
and Sskv at various depth and over time from piezometric and extensometer records. The proposed method is
applied to areas affected by severe land subsidence in the North China Plain (Tianzhu, Pinggezhuang and
Cangzhou stations). The elastic and inelastic parameters of the aquifer systems are quantified at different depths.
It is found that Sske and Sskv decrease with depth. The finer the sediment
grain size is, the smaller of the ratio Sske/Sskv. Moreover, Ske
remains almost unchanged over time, while Skv decreases as compaction and land subsidence increase.
