The occurrence of groundwater drought is closely linked to the meteorological input but also to the surface and subsurface properties, which function as lagging filter for the input signal.

Knowledge about the potential occurrence of groundwater droughts is relevant for existing and future groundwater users, particularly in regions where climate change is expected to extend or increase the number of dry periods. This study proposes a method to quantify the groundwater memory as basis for characterising the intrinsic susceptibility of groundwater to drought.

The memory of groundwater was estimated using a sliding window autocorrelation function applied on 114 groundwater level time series. A Random Forest regressor then modelled the groundwater memory across Ireland, using national digital maps as input files.

The key variables explaining groundwater memory are: the relative and absolute surface topography and a thick overburden (>10 m). Accordingly, the lowest memory appears in elevated areas with overburden thicknesses of <10 m, and vice versa. Areas of low, moderate and high groundwater memory relate to high, moderate and low groundwater drought susceptibility. The uncertainty of the results is lowest in areas of low memory and highest in areas of high memory, presumably related to the distribution of the observations.

The results are considered relevant in the context of water resources planning across sectors (agriculture, industry, domestic), particularly in the context of climate change adaptation.

地下水干旱的发生与气象输入密切相关，也与地表和地下特性密切相关，这些特性对输入信号起到滞后滤波器的作用。

关于地下水干旱潜在发生的知识与现有和未来的地下水使用者相关，特别是在气候变化预计会延长或增加干旱期数量的地区。本研究提出了一种量化地下水记忆的方法，作为表征地下水对干旱内在敏感性的基础。

使用应用于 114 个地下水位时间序列的滑动窗口自相关函数估计地下水的记忆。然后，随机森林回归器使用国家数字地图作为输入文件对爱尔兰的地下水记忆进行建模。

解释地下水记忆的关键变量是：相对和绝对地表地形和厚覆盖层（>10 m）。因此，最低记忆出现在覆盖层厚度<10 m的高架区域，反之亦然。低、中、高地下水记忆区与高、中、低地下水干旱敏感性有关。结果的不确定性在记忆力低的区域最低，而在记忆力高的区域最高，可能与观察的分布有关。

这些结果被认为与跨部门（农业、工业、家庭）的水资源规划相关，特别是在适应气候变化的背景下。