Conceptual Model of Arsenic Mobility in the Shallow Alluvial Aquifers Near Venice (Italy) Elucidated Through Machine Learning and Geochemical Modeling. Issue 9 (3rd September 2020)
- Record Type:
- Journal Article
- Title:
- Conceptual Model of Arsenic Mobility in the Shallow Alluvial Aquifers Near Venice (Italy) Elucidated Through Machine Learning and Geochemical Modeling. Issue 9 (3rd September 2020)
- Main Title:
- Conceptual Model of Arsenic Mobility in the Shallow Alluvial Aquifers Near Venice (Italy) Elucidated Through Machine Learning and Geochemical Modeling
- Authors:
- Dalla Libera, Nico
Pedretti, Daniele
Tateo, Fabio
Mason, Leonardo
Piccinini, Leonardo
Fabbri, Paolo - Abstract:
- Abstract: This work proposed a novel method to elucidate the controls of As mobility in complex aquifers based on an unsupervised machine learning algorithm, Self‐Organizing Map (SOM), and process‐based geochemical modeling. The approach is tested in the shallow aquifers of the Venetian Alluvial Plain (VAP) near Venice, Italy, where As concentrations seasonally and locally exceed recommended drinking water limits. SOM was fed using information from two geochemical surveys on eight VAP boreholes, and continuous reading of hourly groundwater head levels and weekly geochemical analyses from three VAP boreholes between mid‐October 2017 and end of January 2018. The SOM analysis is consistent with redox‐controlled dissolution‐precipitation hydrous ferric oxides (HFOs) as a key control of As mobility in the aquifer. Dissolved As is positively correlated to Fe and N H 4 + and negatively to the oxidizing‐reducing potential (ORP). Negative correlation between As and groundwater head levels suggests a redox control by rainfall‐driven recharge, which adds oxidants to the aquifer while progressively attenuating As. This mechanism is tested using process‐based geochemical modeling, which simulates different transport modalities of oxidants entering the aquifer. Starting from reducing aquifer conditions, the model reproduces correctly the observed ORP and the trends in As and Fe, when the function describing the occurrence of oxidizing events scales according to the temporal occurrence ofAbstract: This work proposed a novel method to elucidate the controls of As mobility in complex aquifers based on an unsupervised machine learning algorithm, Self‐Organizing Map (SOM), and process‐based geochemical modeling. The approach is tested in the shallow aquifers of the Venetian Alluvial Plain (VAP) near Venice, Italy, where As concentrations seasonally and locally exceed recommended drinking water limits. SOM was fed using information from two geochemical surveys on eight VAP boreholes, and continuous reading of hourly groundwater head levels and weekly geochemical analyses from three VAP boreholes between mid‐October 2017 and end of January 2018. The SOM analysis is consistent with redox‐controlled dissolution‐precipitation hydrous ferric oxides (HFOs) as a key control of As mobility in the aquifer. Dissolved As is positively correlated to Fe and N H 4 + and negatively to the oxidizing‐reducing potential (ORP). Negative correlation between As and groundwater head levels suggests a redox control by rainfall‐driven recharge, which adds oxidants to the aquifer while progressively attenuating As. This mechanism is tested using process‐based geochemical modeling, which simulates different transport modalities of oxidants entering the aquifer. Starting from reducing aquifer conditions, the model reproduces correctly the observed ORP and the trends in As and Fe, when the function describing the occurrence of oxidizing events scales according to the temporal occurrence of rainfall events. Heterogeneity can strongly control the local‐scale effectiveness of recharge as a natural As attenuating factor, requiring a different model analysis to be properly assessed and to be developed in a follow‐up study. Key Points: SOM and PHREEQC find site‐specific conceptual model of As mobility based on time series of aquifer dissolved compounds and head levels Redox‐controlled As mobility was corroborated by positive correlation of As with Fe, N H 4 +, and TOC and negatively to ORP and groundwater heads Redox‐controlled As mobility was controlled by rainfall‐driven aquifer recharge; the process was corroborated by PHREEQC modeling … (more)
- Is Part Of:
- Water resources research. Volume 56:Issue 9(2020)
- Journal:
- Water resources research
- Issue:
- Volume 56:Issue 9(2020)
- Issue Display:
- Volume 56, Issue 9 (2020)
- Year:
- 2020
- Volume:
- 56
- Issue:
- 9
- Issue Sort Value:
- 2020-0056-0009-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2020-09-03
- Subjects:
- arsenic mobility -- Self‐Organized Maps -- PHREEQC -- redox changes -- subsurface heterogeneity -- Venetian Alluvial Plain
Hydrology -- Periodicals
333.91 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1944-7973 ↗
http://www.agu.org/pubs/current/wr/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1029/2019WR026234 ↗
- Languages:
- English
- ISSNs:
- 0043-1397
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9275.150000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25919.xml