Clustering Groundwater Level Time Series of the Exploited Almonte-Marismas Aquifer in Southwest Spain
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 mana...
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description | 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. |
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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.</description><identifier>ISSN: 2073-4441</identifier><identifier>EISSN: 2073-4441</identifier><identifier>DOI: 10.3390/w12041063</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Agriculture ; Algorithms ; Aquatic resources ; Aquifers ; Arid climates ; Climate change ; Climatic changes ; Clustering ; Fluid mechanics ; Geology ; Groundwater ; Groundwater levels ; Groundwater management ; Hydrogeology ; Hydrology ; Irrigation ; Management ; Piezometers ; Precipitation ; River basins ; Sea level ; Soil water ; Spain ; Spatial distribution ; Surface water ; Time series ; Tourism ; Water ; Water management ; Water resources ; Water resources management ; Water supply ; Water, Underground</subject><ispartof>Water (Basel), 2020-04, Vol.12 (4), p.1063</ispartof><rights>COPYRIGHT 2020 MDPI AG</rights><rights>2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c331t-c2bf6dbbb88cb22b530713795c2737d276555dd19118c4b6c037b5f8ac462e333</citedby><cites>FETCH-LOGICAL-c331t-c2bf6dbbb88cb22b530713795c2737d276555dd19118c4b6c037b5f8ac462e333</cites><orcidid>0000-0002-7600-7802 ; 0000-0001-9352-7618 ; 0000-0002-1593-1540 ; 0000-0001-9046-5837</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Naranjo-Fernández, Nuria</creatorcontrib><creatorcontrib>Guardiola-Albert, Carolina</creatorcontrib><creatorcontrib>Aguilera, Héctor</creatorcontrib><creatorcontrib>Serrano-Hidalgo, Carmen</creatorcontrib><creatorcontrib>Montero-González, Esperanza</creatorcontrib><title>Clustering Groundwater Level Time Series of the Exploited Almonte-Marismas Aquifer in Southwest Spain</title><title>Water (Basel)</title><description>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.</description><subject>Agriculture</subject><subject>Algorithms</subject><subject>Aquatic resources</subject><subject>Aquifers</subject><subject>Arid climates</subject><subject>Climate change</subject><subject>Climatic changes</subject><subject>Clustering</subject><subject>Fluid mechanics</subject><subject>Geology</subject><subject>Groundwater</subject><subject>Groundwater levels</subject><subject>Groundwater management</subject><subject>Hydrogeology</subject><subject>Hydrology</subject><subject>Irrigation</subject><subject>Management</subject><subject>Piezometers</subject><subject>Precipitation</subject><subject>River basins</subject><subject>Sea level</subject><subject>Soil water</subject><subject>Spain</subject><subject>Spatial distribution</subject><subject>Surface water</subject><subject>Time series</subject><subject>Tourism</subject><subject>Water</subject><subject>Water management</subject><subject>Water resources</subject><subject>Water resources management</subject><subject>Water supply</subject><subject>Water, Underground</subject><issn>2073-4441</issn><issn>2073-4441</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpNUMtOwzAQjBBIVKUH_sASJw4BP-PkWFWlIBVxaDlHtmO3rpI4tR0Kf49REWL3sK-ZHWmy7BbBB0Iq-HhCGFIEC3KRTTDkJKeUost__XU2C-EAU9CqLBmcZHrRjiFqb_sdWHk39s1JpBGs9YduwdZ2GmzSVQfgDIh7DZafQ-ts1A2Yt53ro85fhbehEwHMj6M1iWt7sHFj3J90iGAzCNvfZFdGtEHPfus0e39abhfP-fpt9bKYr3NFCIq5wtIUjZSyLJXEWDICOSK8YgpzwhvMC8ZY06AKoVJRWShIuGSmFIoWWBNCptnd-e_g3XFM8vXBjb5PkjXmnELGMWYJ9XBG7USra9sbF71QKRvdWeV6bWzaz3mFcMVKTBPh_kxQ3oXgtakHbzvhv2oE6x_n6z_nyTcZgXSj</recordid><startdate>20200401</startdate><enddate>20200401</enddate><creator>Naranjo-Fernández, Nuria</creator><creator>Guardiola-Albert, Carolina</creator><creator>Aguilera, Héctor</creator><creator>Serrano-Hidalgo, Carmen</creator><creator>Montero-González, Esperanza</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0002-7600-7802</orcidid><orcidid>https://orcid.org/0000-0001-9352-7618</orcidid><orcidid>https://orcid.org/0000-0002-1593-1540</orcidid><orcidid>https://orcid.org/0000-0001-9046-5837</orcidid></search><sort><creationdate>20200401</creationdate><title>Clustering Groundwater Level Time Series of the Exploited Almonte-Marismas Aquifer in Southwest Spain</title><author>Naranjo-Fernández, Nuria ; Guardiola-Albert, Carolina ; Aguilera, Héctor ; Serrano-Hidalgo, Carmen ; Montero-González, Esperanza</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c331t-c2bf6dbbb88cb22b530713795c2737d276555dd19118c4b6c037b5f8ac462e333</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Agriculture</topic><topic>Algorithms</topic><topic>Aquatic resources</topic><topic>Aquifers</topic><topic>Arid climates</topic><topic>Climate change</topic><topic>Climatic changes</topic><topic>Clustering</topic><topic>Fluid mechanics</topic><topic>Geology</topic><topic>Groundwater</topic><topic>Groundwater levels</topic><topic>Groundwater management</topic><topic>Hydrogeology</topic><topic>Hydrology</topic><topic>Irrigation</topic><topic>Management</topic><topic>Piezometers</topic><topic>Precipitation</topic><topic>River basins</topic><topic>Sea level</topic><topic>Soil water</topic><topic>Spain</topic><topic>Spatial distribution</topic><topic>Surface water</topic><topic>Time series</topic><topic>Tourism</topic><topic>Water</topic><topic>Water management</topic><topic>Water resources</topic><topic>Water resources management</topic><topic>Water supply</topic><topic>Water, Underground</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Naranjo-Fernández, Nuria</creatorcontrib><creatorcontrib>Guardiola-Albert, Carolina</creatorcontrib><creatorcontrib>Aguilera, Héctor</creatorcontrib><creatorcontrib>Serrano-Hidalgo, Carmen</creatorcontrib><creatorcontrib>Montero-González, Esperanza</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Water (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Naranjo-Fernández, Nuria</au><au>Guardiola-Albert, Carolina</au><au>Aguilera, Héctor</au><au>Serrano-Hidalgo, Carmen</au><au>Montero-González, Esperanza</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Clustering Groundwater Level Time Series of the Exploited Almonte-Marismas Aquifer in Southwest Spain</atitle><jtitle>Water (Basel)</jtitle><date>2020-04-01</date><risdate>2020</risdate><volume>12</volume><issue>4</issue><spage>1063</spage><pages>1063-</pages><issn>2073-4441</issn><eissn>2073-4441</eissn><abstract>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.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/w12041063</doi><orcidid>https://orcid.org/0000-0002-7600-7802</orcidid><orcidid>https://orcid.org/0000-0001-9352-7618</orcidid><orcidid>https://orcid.org/0000-0002-1593-1540</orcidid><orcidid>https://orcid.org/0000-0001-9046-5837</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Agriculture Algorithms Aquatic resources Aquifers Arid climates Climate change Climatic changes Clustering Fluid mechanics Geology Groundwater Groundwater levels Groundwater management Hydrogeology Hydrology Irrigation Management Piezometers Precipitation River basins Sea level Soil water Spain Spatial distribution Surface water Time series Tourism Water Water management Water resources Water resources management Water supply Water, Underground |
title | Clustering Groundwater Level Time Series of the Exploited Almonte-Marismas Aquifer in Southwest Spain |
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