Dynamic baselines for the detection of water quality impacts – the case of shale gas development,Environmental Science: Processes & Impacts

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Dynamic baselines for the detection of water quality impacts – the case of shale gas development
Environmental Science: Processes & Impacts ( IF 4.3 ) Pub Date : 2021-06-18 , DOI: 10.1039/d0em00440e
Fred Worrall ₁ , Richard J Davies , Alwyn Hart

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There is a need for the development of effective baselines against which the water quality impacts of new developments can be assessed. The specific conductance of flowback water from shale gas operations is typically many times the specific conductance of surface water and near-surface groundwater. This contrast in specific conductance means that specific conductance could be the ideal determinand for detecting water quality impacts from shale gas extraction. If specific conductance is to be used for detecting the impacts of shale gas operations, then a baseline of specific conductance in water bodies is required. Here, Bayesian hierarchical modelling of specific conductance was applied across English groundwater. The modelling used existing, spot-sampled data from the years 2000 to 2018 from 537 unique borehole locations. When the differences between boreholes was considered, then the approach was sufficiently sensitive to detect 1% mixing of fracking fluid in groundwater at a 95% confidence interval. The Bayesian hierarchical modelling maximises the return on public investment and provides a means by which future observations can be judged.

中文翻译：

检测水质影响的动态基线——以页岩气开发为例

需要制定有效的基线，以此评估新开发项目对水质的影响。页岩气作业回流水的电导率通常是地表水和近地表地下水的电导率的许多倍。比电导的这种对比意味着比电导可能是检测页岩气开采对水质影响的理想决定因素。如果要使用特定电导率来检测页岩气作业的影响，则需要水体中特定电导率的基线。在这里，特定电导率的贝叶斯分层建模应用于英国地下水。该建模使用了 2000 年至 2018 年间来自 537 个独特钻孔位置的现有现场采样数据。当考虑钻孔之间的差异时，该方法足够灵敏，可以以 95% 的置信区间检测地下水中 1% 的压裂液混合。贝叶斯分层建模最大限度地提高了公共投资的回报，并提供了一种可以判断未来观察结果的方法。

更新日期：2021-06-30

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