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Interaction prediction between groundwater and quarry extension using discrete choice models and artificial neural networks

机译:基于离散选择模型和人工神经网络的地下水与采石场扩展相互作用预测

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摘要

Groundwater and rock are intensively exploited in the world. When a quarry is deepened the water table of the exploited geological formation might be reached. A dewatering system is therefore installed so that the quarry activities can continue, possibly impacting the nearby water catchments. In order to recommend an adequate feasibility study before deepening a quarry, we propose two interaction indices between extractive activity and groundwater resources based on hazard and vulnerability parameters used in the assessment of natural hazards. The levels of each index (low, medium, high, very high) correspond to the potential impact of the quarry on the regional hydrogeology. The first index is based on a discrete choice modelling methodology while the second is relying on an artificial neural network. It is shown that these two complementary approaches (the former being probabilistic while the latter fully deterministic) are able to predict accurately the level of interaction. Their use is finally illustrated by their application on the Boverie quarry and the Tridaine gallery located in Belgium. The indices determine the current interaction level as well as the one resulting from future quarry extensions. The results highlight the very high interaction level of the quarry with the gallery.
机译:全世界都在大量开采地下水和岩石。当采石场加深时,可能会达到被开采地质层的地下水位。因此,安装了脱水系统,以使采石场的活动能够继续进行,可能会影响附近的集水区。为了建议在加深采石场之前进行充分的可行性研究,我们基于用于自然灾害评估的灾害和脆弱性参数,提出了开采活动与地下水资源之间的两个相互作用指数。每个指标的水平(低,中,高,非常高)对应于采石场对区域水文地质的潜在影响。第一个索引基于离散选择建模方法,而第二个索引则依赖于人工神经网络。结果表明,这两种互补的方法(前者是概率方法,而后者是完全确定性方法)能够准确地预测相互作用的程度。最后通过在Boverie采石场和比利时Tridaine画廊中的应用说明了它们的使用。这些索引确定了当前的交互级别以及将来的采石场扩展所产生的交互级别。结果突出了采石场与画廊的极高交互水平。

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