Groundwater resources are regularly the principal water supply in semiarid and arid climate areas. However, groundwater levels (GWL) in semiarid aquifers are suffering a general decrease because of anthropic exploitation of aquifers and the repercussions of climate change. Effective groundwater management strategies require a deep characterization of GWL fluctuations, in order to identify individual behaviors and triggering factors. In September 2019, the Guadalquivir River Basin Authority (CHG) declared that there was over-exploitation in three of the five groundwater bodies of the Almonte-Marismas aquifer, Southwest Spain. For that reason, it is critical to understand GWL dynamics in this aquifer before the new Spanish Water Resources Management Plans (2021–2027) are developed. The application of GWL series clustering in hydrogeology has grown over the past few years, as it is an extraordinary tool that promptly provides a GWL classification; each group can be related to different responses of a complex aquifer under any external change. In this work, GWL time series from 160 piezometers were analyzed for the period 1975 to 2016 and, after data pre-processing, 24 piezometers were selected for clustering with k-means (static) and time series (dynamic) clustering techniques. Six and seven groups (k) were chosen to apply k-means. Six characterized types of hydrodynamic behaviors were obtained with time series clustering (TSC). Number of clusters were related to diverse affections of water exploitation depending on soil uses and hydrogeological spatial distribution parameters. TSC enabled us to distinguish local areas with high hydrodynamic disturbance and to highlight a quantitative drop of GWL during the studied period.

中文翻译：

---

西班牙西南部已开发的 Almonte-Marismas 含水层地下水位时间序列聚类

地下水资源通常是半干旱和干旱气候地区的主要供水。然而，由于人类对含水层的开采和气候变化的影响，半干旱含水层的地下水位 (GWL) 普遍下降。有效的地下水管理策略需要对 GWL 波动进行深入表征，以便识别个体行为和触发因素。2019 年 9 月，瓜达尔基维尔河流域管理局 (CHG) 宣布西班牙西南部阿尔蒙特-马里斯马斯含水层的五个地下水体中的三个存在过度开发。因此，在制定新的西班牙水资源管理计划（2021-2027）之前了解该含水层的 GWL 动态至关重要。GWL 系列聚类在水文地质学中的应用在过去几年中得到了发展，因为它是一种能够迅速提供 GWL 分类的非凡工具；每个组都可能与复杂含水层在任何外部变化下的不同反应有关。在这项工作中，分析了 1975 年至 2016 年期间 160 个压力计的 GWL 时间序列，并在数据预处理后选择了 24 个压力计，用于使用 k 均值（静态）和时间序列（动态）聚类技术进行聚类。选择六组和七组 (k) 来应用 k 均值。通过时间序列聚类 (TSC) 获得了六种特征类型的水动力行为。根据土壤用途和水文地质空间分布参数，聚类的数量与水资源开发的不同影响有关。