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A Numerical Stream Transport Modeling Approach Including Multiple Conceptualizations of Hyporheic Exchange and Spatial Variability to Assess Contaminant Removal
Understanding the mechanisms and controls on contaminant removal in streams is essential in managing human and ecosystem health. The hyporheic zone (HZ) plays a key role in the removal of contaminants from streams. Often, tracer tests are implemented in conjunction with measurements of compounds to...
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Published in: | Water resources research 2020-03, Vol.56 (3), p.n/a |
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creator | McCallum, James L. Höhne, Anja Schaper, Jonas L. Shanafield, Margaret Banks, Edward W. Posselt, Malte Batelaan, Okke Lewandowski, Jörg |
description | Understanding the mechanisms and controls on contaminant removal in streams is essential in managing human and ecosystem health. The hyporheic zone (HZ) plays a key role in the removal of contaminants from streams. Often, tracer tests are implemented in conjunction with measurements of compounds to assess the removal rates of contaminants in streams. The predicted removal rates largely rely on the estimated hyporheic residence time, and hence, the chosen conceptual model of hyporheic exchange flows (HEFs) will influence the predicted removal rate. Despite this, different HEF models are generally not considered when assessing contaminant removal rates. In this paper, we present a numerical modeling approach for interpreting tracer tests to determine contaminant removal rates that allows for multiple conceptual models of HEF to be considered. We demonstrate this method by interpreting data from a conservative tracer test in conjunction with grab samples of trace organic compounds using two commonly used models of HEF: one that assumes first‐order exchange between the stream and the HZ and one that considers a power law weighting of first‐order exchange coefficients. For the three degrading compounds measured, guanylurea, valsartan, and diclofenac, we observed that the power law model consistently predicted higher removal rates in the stream compared to the first‐order model. Variations were also observed between the removal rates estimated in the HZ. Our results highlight the importance of considering multiple conceptualizations of the HEF when assessing contaminant removal rates.
Key Points
We present a flexible numerical modelling approach for incorporating hyporheic zone conceptualizations into one‐dimensional stream transport models to determine better removal rate constants
The model allows for the full range of hyporheic residence times to be considered when determining contaminant removal
The choice of the hyporheic exchange model has an impact on the predicted removal of contaminants |
doi_str_mv | 10.1029/2019WR024987 |
format | article |
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Key Points
We present a flexible numerical modelling approach for incorporating hyporheic zone conceptualizations into one‐dimensional stream transport models to determine better removal rate constants
The model allows for the full range of hyporheic residence times to be considered when determining contaminant removal
The choice of the hyporheic exchange model has an impact on the predicted removal of contaminants</description><identifier>ISSN: 0043-1397</identifier><identifier>ISSN: 1944-7973</identifier><identifier>EISSN: 1944-7973</identifier><identifier>DOI: 10.1029/2019WR024987</identifier><language>eng</language><publisher>Washington: John Wiley & Sons, Inc</publisher><subject>Coefficients ; Contaminants ; Data interpretation ; Diclofenac ; Ecosystem management ; Exchange coefficients ; Exchanging ; Hyporheic zone ; Hyporheic zones ; Mathematical models ; Modelling ; numerical modeling ; Organic compounds ; Pollutant removal ; Pollution control ; Power law ; Removal ; Residence time ; Rivers ; Spatial variability ; Spatial variations ; Streams ; tracer testing ; Tracers</subject><ispartof>Water resources research, 2020-03, Vol.56 (3), p.n/a</ispartof><rights>2020. American Geophysical Union. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a4058-dd0ea08eef1a8b05e152651a95fe01cb3fa277e4ead4e34e1baee378fd39c5773</citedby><cites>FETCH-LOGICAL-a4058-dd0ea08eef1a8b05e152651a95fe01cb3fa277e4ead4e34e1baee378fd39c5773</cites><orcidid>0000-0002-5526-3743 ; 0000-0003-1710-1548 ; 0000-0002-9281-0566 ; 0000-0001-8979-8044 ; 0000-0001-5278-129X ; 0000-0001-5862-9803 ; 0000-0002-2431-7649 ; 0000-0003-1443-6385</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F2019WR024987$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2019WR024987$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,780,784,885,11514,27924,27925,46468,46892</link.rule.ids><backlink>$$Uhttps://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-182904$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><creatorcontrib>McCallum, James L.</creatorcontrib><creatorcontrib>Höhne, Anja</creatorcontrib><creatorcontrib>Schaper, Jonas L.</creatorcontrib><creatorcontrib>Shanafield, Margaret</creatorcontrib><creatorcontrib>Banks, Edward W.</creatorcontrib><creatorcontrib>Posselt, Malte</creatorcontrib><creatorcontrib>Batelaan, Okke</creatorcontrib><creatorcontrib>Lewandowski, Jörg</creatorcontrib><title>A Numerical Stream Transport Modeling Approach Including Multiple Conceptualizations of Hyporheic Exchange and Spatial Variability to Assess Contaminant Removal</title><title>Water resources research</title><description>Understanding the mechanisms and controls on contaminant removal in streams is essential in managing human and ecosystem health. The hyporheic zone (HZ) plays a key role in the removal of contaminants from streams. Often, tracer tests are implemented in conjunction with measurements of compounds to assess the removal rates of contaminants in streams. The predicted removal rates largely rely on the estimated hyporheic residence time, and hence, the chosen conceptual model of hyporheic exchange flows (HEFs) will influence the predicted removal rate. Despite this, different HEF models are generally not considered when assessing contaminant removal rates. In this paper, we present a numerical modeling approach for interpreting tracer tests to determine contaminant removal rates that allows for multiple conceptual models of HEF to be considered. We demonstrate this method by interpreting data from a conservative tracer test in conjunction with grab samples of trace organic compounds using two commonly used models of HEF: one that assumes first‐order exchange between the stream and the HZ and one that considers a power law weighting of first‐order exchange coefficients. For the three degrading compounds measured, guanylurea, valsartan, and diclofenac, we observed that the power law model consistently predicted higher removal rates in the stream compared to the first‐order model. Variations were also observed between the removal rates estimated in the HZ. Our results highlight the importance of considering multiple conceptualizations of the HEF when assessing contaminant removal rates.
Key Points
We present a flexible numerical modelling approach for incorporating hyporheic zone conceptualizations into one‐dimensional stream transport models to determine better removal rate constants
The model allows for the full range of hyporheic residence times to be considered when determining contaminant removal
The choice of the hyporheic exchange model has an impact on the predicted removal of contaminants</description><subject>Coefficients</subject><subject>Contaminants</subject><subject>Data interpretation</subject><subject>Diclofenac</subject><subject>Ecosystem management</subject><subject>Exchange coefficients</subject><subject>Exchanging</subject><subject>Hyporheic zone</subject><subject>Hyporheic zones</subject><subject>Mathematical models</subject><subject>Modelling</subject><subject>numerical modeling</subject><subject>Organic compounds</subject><subject>Pollutant removal</subject><subject>Pollution control</subject><subject>Power law</subject><subject>Removal</subject><subject>Residence time</subject><subject>Rivers</subject><subject>Spatial variability</subject><subject>Spatial variations</subject><subject>Streams</subject><subject>tracer testing</subject><subject>Tracers</subject><issn>0043-1397</issn><issn>1944-7973</issn><issn>1944-7973</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kcFu1DAQhi0EEsvCjQewxJUFO3bWzjFaWlqpBWlb2qM1SSa7rhw72A5leRoelawWASdOI40-fTP6f0Jec_aOs6J6XzBe3W9ZISutnpAFr6RcqUqJp2TBmBQrLir1nLxI6YExLsu1WpCfNf00DRhtC47e5Igw0NsIPo0hZnodOnTW72g9jjFAu6eXvnVTd1xdTy7b0SHdBN_imCdw9gdkG3yioacXh9mwR9vSs-_tHvwOKfiO3owzMp-6g2ihsc7mA82B1ilhSkdVhsF68JlucQjfwL0kz3pwCV_9nkvy5fzsdnOxuvr88XJTX61AslKvuo4hMI3Yc9ANK5GXxbrkUJU9Mt42oodCKZQInUQhkTeAKJTuO1G1pVJiSd6evOkRx6kxY7QDxIMJYM0He1ebEHcmTYbropqzXJI3J3zO5euEKZuHMEU_f2gKoTVjSuj1X2kbQ0oR-z9azsyxMvNvZTMuTvijdXj4L2vut5ttIaXW4hcR8Jxe</recordid><startdate>202003</startdate><enddate>202003</enddate><creator>McCallum, James L.</creator><creator>Höhne, Anja</creator><creator>Schaper, Jonas L.</creator><creator>Shanafield, Margaret</creator><creator>Banks, Edward W.</creator><creator>Posselt, Malte</creator><creator>Batelaan, Okke</creator><creator>Lewandowski, Jörg</creator><general>John Wiley & Sons, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7QL</scope><scope>7T7</scope><scope>7TG</scope><scope>7U9</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H94</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>M7N</scope><scope>P64</scope><scope>ADTPV</scope><scope>AOWAS</scope><scope>DG7</scope><orcidid>https://orcid.org/0000-0002-5526-3743</orcidid><orcidid>https://orcid.org/0000-0003-1710-1548</orcidid><orcidid>https://orcid.org/0000-0002-9281-0566</orcidid><orcidid>https://orcid.org/0000-0001-8979-8044</orcidid><orcidid>https://orcid.org/0000-0001-5278-129X</orcidid><orcidid>https://orcid.org/0000-0001-5862-9803</orcidid><orcidid>https://orcid.org/0000-0002-2431-7649</orcidid><orcidid>https://orcid.org/0000-0003-1443-6385</orcidid></search><sort><creationdate>202003</creationdate><title>A Numerical Stream Transport Modeling Approach Including Multiple Conceptualizations of Hyporheic Exchange and Spatial Variability to Assess Contaminant Removal</title><author>McCallum, James L. ; Höhne, Anja ; Schaper, Jonas L. ; Shanafield, Margaret ; Banks, Edward W. ; Posselt, Malte ; Batelaan, Okke ; Lewandowski, Jörg</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a4058-dd0ea08eef1a8b05e152651a95fe01cb3fa277e4ead4e34e1baee378fd39c5773</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Coefficients</topic><topic>Contaminants</topic><topic>Data interpretation</topic><topic>Diclofenac</topic><topic>Ecosystem management</topic><topic>Exchange coefficients</topic><topic>Exchanging</topic><topic>Hyporheic zone</topic><topic>Hyporheic zones</topic><topic>Mathematical models</topic><topic>Modelling</topic><topic>numerical modeling</topic><topic>Organic compounds</topic><topic>Pollutant removal</topic><topic>Pollution control</topic><topic>Power law</topic><topic>Removal</topic><topic>Residence time</topic><topic>Rivers</topic><topic>Spatial variability</topic><topic>Spatial variations</topic><topic>Streams</topic><topic>tracer testing</topic><topic>Tracers</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>McCallum, James L.</creatorcontrib><creatorcontrib>Höhne, Anja</creatorcontrib><creatorcontrib>Schaper, Jonas L.</creatorcontrib><creatorcontrib>Shanafield, Margaret</creatorcontrib><creatorcontrib>Banks, Edward W.</creatorcontrib><creatorcontrib>Posselt, Malte</creatorcontrib><creatorcontrib>Batelaan, Okke</creatorcontrib><creatorcontrib>Lewandowski, Jörg</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>SwePub</collection><collection>SwePub Articles</collection><collection>SWEPUB Stockholms universitet</collection><jtitle>Water resources research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>McCallum, James L.</au><au>Höhne, Anja</au><au>Schaper, Jonas L.</au><au>Shanafield, Margaret</au><au>Banks, Edward W.</au><au>Posselt, Malte</au><au>Batelaan, Okke</au><au>Lewandowski, Jörg</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Numerical Stream Transport Modeling Approach Including Multiple Conceptualizations of Hyporheic Exchange and Spatial Variability to Assess Contaminant Removal</atitle><jtitle>Water resources research</jtitle><date>2020-03</date><risdate>2020</risdate><volume>56</volume><issue>3</issue><epage>n/a</epage><issn>0043-1397</issn><issn>1944-7973</issn><eissn>1944-7973</eissn><abstract>Understanding the mechanisms and controls on contaminant removal in streams is essential in managing human and ecosystem health. The hyporheic zone (HZ) plays a key role in the removal of contaminants from streams. Often, tracer tests are implemented in conjunction with measurements of compounds to assess the removal rates of contaminants in streams. The predicted removal rates largely rely on the estimated hyporheic residence time, and hence, the chosen conceptual model of hyporheic exchange flows (HEFs) will influence the predicted removal rate. Despite this, different HEF models are generally not considered when assessing contaminant removal rates. In this paper, we present a numerical modeling approach for interpreting tracer tests to determine contaminant removal rates that allows for multiple conceptual models of HEF to be considered. We demonstrate this method by interpreting data from a conservative tracer test in conjunction with grab samples of trace organic compounds using two commonly used models of HEF: one that assumes first‐order exchange between the stream and the HZ and one that considers a power law weighting of first‐order exchange coefficients. For the three degrading compounds measured, guanylurea, valsartan, and diclofenac, we observed that the power law model consistently predicted higher removal rates in the stream compared to the first‐order model. Variations were also observed between the removal rates estimated in the HZ. Our results highlight the importance of considering multiple conceptualizations of the HEF when assessing contaminant removal rates.
Key Points
We present a flexible numerical modelling approach for incorporating hyporheic zone conceptualizations into one‐dimensional stream transport models to determine better removal rate constants
The model allows for the full range of hyporheic residence times to be considered when determining contaminant removal
The choice of the hyporheic exchange model has an impact on the predicted removal of contaminants</abstract><cop>Washington</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1029/2019WR024987</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-5526-3743</orcidid><orcidid>https://orcid.org/0000-0003-1710-1548</orcidid><orcidid>https://orcid.org/0000-0002-9281-0566</orcidid><orcidid>https://orcid.org/0000-0001-8979-8044</orcidid><orcidid>https://orcid.org/0000-0001-5278-129X</orcidid><orcidid>https://orcid.org/0000-0001-5862-9803</orcidid><orcidid>https://orcid.org/0000-0002-2431-7649</orcidid><orcidid>https://orcid.org/0000-0003-1443-6385</orcidid><oa>free_for_read</oa></addata></record> |
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source | Wiley-Blackwell AGU Digital Library |
subjects | Coefficients Contaminants Data interpretation Diclofenac Ecosystem management Exchange coefficients Exchanging Hyporheic zone Hyporheic zones Mathematical models Modelling numerical modeling Organic compounds Pollutant removal Pollution control Power law Removal Residence time Rivers Spatial variability Spatial variations Streams tracer testing Tracers |
title | A Numerical Stream Transport Modeling Approach Including Multiple Conceptualizations of Hyporheic Exchange and Spatial Variability to Assess Contaminant Removal |
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