Sensitivity analysis of factors controlling earth fissures due to excessive groundwater pumping
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Open Access
- 6 May 2022
- journal article
- research article
- Published by Springer Nature in Stochastic Environmental Research and Risk Assessment
- Vol. 36 (11) , 3911-3928
Abstract
Aseisimic earth fissures are complex consequences of groundwater withdrawal and natural hydrogeologic conditions. This paper aims to improve the understanding of the mechanism of earth fissuring and investigate the relative importance of various factors to fissure activity, including bedrock geometry, piezometric depletion, compressibility and thickness of the exploited aquifer. For these purposes, a test case characterized by an impermeable and incompressible rock ridge in a subsiding basin is developed, where stress/displacement analyses and fissure state are predicted using an interface-finite element model. Three different methods for global sensitivity analysis are used to quantify the extent of the fissure opening to the aforementioned factors. The conventional sampling based Sobol’ sensitivity analysis is compared to two surrogate based methods, the general polynomial chaos expansion based Sobol’ analysis and a feature importance evaluation of a gradient boosting decision tree model. Numerical results indicate that earth fissure is forming in response to tensile stress accumulation above the ridge associated to pore-pressure depletion, inducing the fissure opening at land surface with further downward propagation. Sensitivity analysis highlights that the geometry of bedrock ridge is the most influential feature. Specifically, the fissure grows more when the ridge is steeper and closer to the land surface. Pore pressure depletion is a secondary feature and required to reach a certain threshold to activate the fissure. As for this specific application, the gradient boosting tree is the most suitable method for its better performance in capturing fissure characteristics.Keywords
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Funding Information
- European Food Safety Authority (PRIMA 1924)
- Innovative Research Group Project of the National Natural Science Foundation of China (41877180)
- Horizon 2020 (SNN 134368)
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