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Water
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Data-Driven Approach Supporting Groundwater Resource Understanding, Protection and Management
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Special Issue "Data-Driven Approach Supporting Groundwater Resource Understanding, Protection and Management"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "New Sensors, New Technologies and Machine Learning in Water Sciences".

Deadline for manuscript submissions: 30 June 2023 | Viewed by 1660

Special Issue Editors

Dr. Marco Rotiroti
E-Mail Website
SciProfiles
Guest Editor
Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milano, Italy
Interests: hydrogeochemical modelling; trace elements; groundwater quality; groundwater/surface water interactions
Special Issues, Collections and Topics in MDPI journals
Dr. Chiara Zanotti
E-Mail Website
SciProfiles
Guest Editor
Department of Earth and Environmental Sciences, University of Milano-Bicocca, Piazza della Scienza 1, 20126 Milan, Italy
Interests: hydrogeology; groundwater; climate change effects on groundwater resources; water safety plans; groundwater natural contamination; natural background levels (NBL)
Dr. Diego Di Curzio
E-Mail Website
SciProfiles
Guest Editor
TU Delft, Delft University of Technology, Delft, The Netherlands
Interests: reactive transport modeling; groundwater contamination; hydro(bio)geochemical processes modeling; uncertainty quantification; geostatistics for hydrogeology and environmental sciences; time series analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Rahim Barzegar
E-Mail Website
SciProfiles
Guest Editor
Department of Bioresource Engineering, McGill University, Montreal, QC, Canada
Interests: hydro(geo)logy; machine/deep learning and data-driven modeling; hydrological forecasting; time series; water quality; groundwater vulnerability and contamination risk; groundwater resources management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Groundwater is a vital resource for human and ecosystem needs worldwide. In a scenario of climate change and increasing anthropogenic impacts on groundwater, understanding the main drivers affecting groundwater resource quality and availability is the main challenge in the scope of more sustainable groundwater management. In the last few decades, monitoring networks' expansion and persistence over time have led to increased data availability: environmental datasets are growing in size, complexity, and resolution. Extensive monitoring data require proper techniques and tools to be managed, elaborated, interpreted, and integrated on a spatial or temporal scale to obtain reliable results.  The scientific community is constantly working on understanding the best and most up-to-date techniques to investigate and exploit these valuable data. This Special Issue aims to expand the knowledge on data-driven applications on groundwater data. We welcome the submission of papers concerning data analysis and modelling of groundwater quality or quantity datasets; examples can be: a) Data mining, spatial, temporal, or multivariate analysis of groundwater quality data or b) time series analysis and forecasting of groundwater head and springs discharge. We also encourage new insights on overcoming the most widely known problems such as missing or non-detected data or sensors and analytical uncertainty management. The final goal of this Special Issue is collecting up-to-date applications of data-driven techniques in the scope of groundwater resource understanding, protection, and management.  

Dr. Marco Rotiroti
Dr. Chiara Zanotti
Dr. Diego Di Curzio
Dr. Rahim Barzegar
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • groundwater
  • data mining
  • multivariate analysis
  • time series analysis
  • machine learning
  • geostatistics
  • neural networks
  • groundwater forecasting
  • data management and preprocessing

Published Papers (2 papers)

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Article
Assessing Groundwater Evolution with a Combined Approach of Hydrogeochemical Modelling and Data Analysis: Application to the Rhodope Coastal Aquifer (NE Greece)
by
Evangelos Tziritis
,
Ekaterini Sachsamanoglou
and
Vassilis Aschonitis
Water 2023, 15(2), 230; https://doi.org/10.3390/w15020230 - 05 Jan 2023
Viewed by 396
Abstract
Assessing the hydrogeochemical evolution of groundwater is a challenging task, which is further exacerbated when considering the multiple geogenic and anthropogenic impacts that affect its quality and the hydraulic interactions between different aquifer bodies. This study combined hydrogeochemical modelling and data analysis to [...] Read more.
Assessing the hydrogeochemical evolution of groundwater is a challenging task, which is further exacerbated when considering the multiple geogenic and anthropogenic impacts that affect its quality and the hydraulic interactions between different aquifer bodies. This study combined hydrogeochemical modelling and data analysis to assess this complex hydrogeological regime. Before modelling, the groundwater samples were clustered using a multivariate statistical method (hierarchical cluster analysis (HCA)). Then, the Geochemist Workbench (GWB) software was applied to model the hydrogeochemical groundwater evolution, including the dominant ion exchange process, and to explain the changes in groundwater chemistry towards its flow. The input data consisted of five key parameters from seventy-seven sampling points collected in two periods (accounting for the start and the end of the irrigation period). A data analytical approach based on the optimal mixing ratios between the interacting groundwater systems and recharge inputs was also performed as part of the methodological approach. It revealed a progressively temporal-dependent behaviour of the aquifer system during the irrigation period, resulting in seasonal changes in the hydrodynamic conditions and depletion of the upper aquifer layers. Specifically, the aquifer system was confirmed to undergo cation exchange as the dominant geochemical process that increases calcium concentrations. The complex hydrogeological regime was further evaluated by assessing the mixing ratios of the different aquifer layers. Hence, the aquifer system (bulk samples) was mixed with the irrigation water by 71% and 97% and with the lateral recharge by 76% and 29% for the beginning and at the end of the irrigation period, respectively. Overall, the joint assessments were confirmed by the hydrogeochemical status of the end-members and the modelling approach and explained the sequential changes in groundwater chemistry due to the dominant ion-exchange process and the mixing of different water bodies. The proposed methodological approach proved that it could be used as an exploratory and preliminary method for capturing the temporal dynamics in complex groundwater systems and supporting groundwater resource management. Full article
(This article belongs to the Special Issue Data-Driven Approach Supporting Groundwater Resource Understanding, Protection and Management)
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Article
Multivariate Time Series Clustering of Groundwater Quality Data to Develop Data-Driven Monitoring Strategies in a Historically Contaminated Urban Area
by
Chiara Zanotti
,
Marco Rotiroti
,
Agnese Redaelli
,
Mariachiara Caschetto
,
Letizia Fumagalli
,
Camilla Stano
,
Davide Sartirana
and
Tullia Bonomi
Water 2023, 15(1), 148; https://doi.org/10.3390/w15010148 - 30 Dec 2022
Viewed by 504
Abstract
As groundwater quality monitoring networks have been expanded over the last decades, significant time series are now available. Therefore, a scientific effort is needed to explore innovative techniques for groundwater quality time series exploitation. In this work, time series exploratory analysis and time [...] Read more.
As groundwater quality monitoring networks have been expanded over the last decades, significant time series are now available. Therefore, a scientific effort is needed to explore innovative techniques for groundwater quality time series exploitation. In this work, time series exploratory analysis and time series cluster analysis are applied to groundwater contamination data with the aim of developing data-driven monitoring strategies. The study area is an urban area characterized by several superimposing historical contamination sources and a complex hydrogeological setting. A multivariate time series cluster analysis was performed on PCE and TCE concentrations data over a 10 years time span. The time series clustering was performed based on the Dynamic Time Warping method. The results of the clustering identified 3 clusters associated with diffuse background contamination and 7 clusters associated with local hotspots, characterized by specific time profiles. Similarly, a univariate time series cluster analysis was applied to Cr(VI) data, identifying 3 background clusters and 7 hotspots, including 4 singletons. The clustering outputs provided the basis for the implementation of data-driven monitoring strategies and early warning systems. For the clusters associated with diffuse background contaminations and those with constant trends, trigger levels were calculated with the 95° percentile, constituting future threshold values for early warnings. For the clusters with pluriannual trends, either oscillatory or monotonous, specific monitoring strategies were proposed based on trends’ directions. Results show that the spatio-temporal overview of the data variability obtained from the time series cluster analysis helped to extract relevant information from the data while neglecting measurements noise and uncertainty, supporting the implementation of a more efficient groundwater quality monitoring. Full article
(This article belongs to the Special Issue Data-Driven Approach Supporting Groundwater Resource Understanding, Protection and Management)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Geostatistically-based water budget estimation in Periadriatic river basins

Authors: Di Curzio D., Di Giovanni A., Rusi S., Pantanella D., Picchi C.
Affiliation: University "G. d'Annunzio" of Chieti-Pescara, Chieti, Italy

Title: Comparison of three imputation methods for groundwater level time series
Authors: Mara Meggiorin, Giulia Passadore, Andrea Sottani and Andrea Rinaldo
Affiliation: Federal Polytechnic School of Lausanne

Title: Wavelet analysis on groundwater, surface water levels and water temperature in Doñana National Park (Southwestern Spain)
Authors: Jennifer Treviño; Miguel Rodríguez-Rodríguez; María José Montes-Vega; Héctor Aguilera-Alonso; Ana Fernández-Ayuso; Nuria Naranjo-Fernández
Affiliation: Center Hydrogeology of University of Málaga, Complutense University of Madrid
Abstract: The Doñana National Park (DNP) is a protected area with water resources drastically diminishing due to unsustainable extraction of water for agricultural irrigation and human consumption of a nearby coastal city. In this study, we explore the potential of wavelet time series analysis applied to groundwater and surface water of temporary coastal ponds in the DNP. Wavelet time series analysis was used to measure the frequency of changes in water levels and water temperature, both of which are crucial to our understanding of complex hydrodynamic patterns. Results show that the temporary ponds are still connected to the sand dune aquifer, regardless their hydrological affection due to groundwater withdrawal.

Title: Impact of seawater intrusion and climate change on groundwater quality in coastal aquifers of the Essaouira basin, southwestern Morocco, using hydrogeochemistry and isotopic signatures.
Authors: Otman El Mountassir (1*), Mohammed Bahir (1)
Affiliation: 1High Energy and Astrophysics Laboratory, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakech, Morocco.

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