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Open AccessArticle

Clustering Groundwater Level Time Series of the Exploited Almonte-Marismas Aquifer in Southwest Spain

1
Facultad de Ciencias Geológicas, Universidad Complutense de Madrid, Calle José Antonio Novais 12, 28040 Madrid, Spain
2
Instituto Geológico y Minero de España, Calle Ríos Rosas 23, 28003 Madrid, Spain
*
Author to whom correspondence should be addressed.
Water 2020, 12(4), 1063; https://doi.org/10.3390/w12041063
Received: 3 March 2020 / Revised: 3 April 2020 / Accepted: 4 April 2020 / Published: 8 April 2020
(This article belongs to the Section Hydrology and Hydrogeology)
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. View Full-Text
Keywords: groundwater level hydrographs; k-means clustering; time series clustering; water resource management groundwater level hydrographs; k-means clustering; time series clustering; water resource management
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MDPI and ACS Style

Naranjo-Fernández, N.; Guardiola-Albert, C.; Aguilera, H.; Serrano-Hidalgo, C.; Montero-González, E. Clustering Groundwater Level Time Series of the Exploited Almonte-Marismas Aquifer in Southwest Spain. Water 2020, 12, 1063.

AMA Style

Naranjo-Fernández N, Guardiola-Albert C, Aguilera H, Serrano-Hidalgo C, Montero-González E. Clustering Groundwater Level Time Series of the Exploited Almonte-Marismas Aquifer in Southwest Spain. Water. 2020; 12(4):1063.

Chicago/Turabian Style

Naranjo-Fernández, Nuria; Guardiola-Albert, Carolina; Aguilera, Héctor; Serrano-Hidalgo, Carmen; Montero-González, Esperanza. 2020. "Clustering Groundwater Level Time Series of the Exploited Almonte-Marismas Aquifer in Southwest Spain" Water 12, no. 4: 1063.

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