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A method for investigating the potential impacts of climate-change scenarios on annual minimum groundwater levels

机译:一种调查气候变化情景对年度最低地下水位的潜在影响的方法

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摘要

Previous approaches to assessing the impact of climate-change scenarios on groundwater levels and groundwater droughts have focused on modelling specific recharge processes or phenomena. However, statistical methods, based on correlations between historic groundwater level and rainfall time-series, provide an alternative and robust approach to predicting minimum groundwater levels and droughts. For the purposes of this study, groundwater droughts are defined in terms of the return period of a given groundwater level. A multiple linear regression model (regression of monthly rainfall totals for a given period against values of minimum annual groundwater levels for the same period), when used with synthetic rainfall data based on climate-change scenarios, enables changes in future annual groundwater-level minima to be modelled. The method is illustrated at three sites on the Chalk, Permo-Triassic sandstone and Jurassic limestone aquifers.
机译:先前评估气候变化情景对地下水位和地下水干旱影响的方法主要集中在模拟特定的补给过程或现象。但是,基于历史地下水位与降雨时间序列之间的相关性的统计方法为预测最低地下水位和干旱提供了一种替代性且可靠的方法。为了本研究的目的,根据给定地下水位的恢复期来定义地下水干旱。多元线性回归模型(给定期间的月降雨量总量与同期的最低年度地下水水平值的回归)与基于气候变化情景的合成降雨数据一起使用时,可以实现未来年度地下水最低水平的变化进行建模。该方法在白垩,Permo-Triassic砂岩和侏罗系石灰岩含水层的三个位置进行了说明。

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