Emulation of a process-based estuarine hydrodynamic model
Emulation modelling can be an effective alternative to traditional mechanistic approaches for complex environmental systems and, if carefully conceived, can offer significantly reduced run times and user expertise requirements. We present a case study of dynamic emulation for the domain of estuarine...
Gespeichert in:
Veröffentlicht in: | Hydrological sciences journal 2018-04, Vol.63 (5), p.783-802 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 802 |
---|---|
container_issue | 5 |
container_start_page | 783 |
container_title | Hydrological sciences journal |
container_volume | 63 |
creator | Chen, Limin Roy, Sujoy B. Hutton, Paul H. |
description | Emulation modelling can be an effective alternative to traditional mechanistic approaches for complex environmental systems and, if carefully conceived, can offer significantly reduced run times and user expertise requirements. We present a case study of dynamic emulation for the domain of estuarine water quality modelling, by reporting the development and evaluation of a one-dimensional hydrodynamic model emulator. The proposed "neuroemulator" retains the dynamic nature of the process-based model utilizing a set of artificial neural networks. The underlying hydrodynamic model is routinely used for analysis and management of the northern reach of the San Francisco Bay-Delta estuary, a large complex region of strategic importance for water supply and ecosystem services on the Pacific coast of California, USA. The reduced computational expense of the emulator affords opportunities for direct use, as well as embedded use within other modelling frameworks such as those developed for reservoir operations and socio-hydrology. |
doi_str_mv | 10.1080/02626667.2018.1447112 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2025890190</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2025890190</sourcerecordid><originalsourceid>FETCH-LOGICAL-c281t-694c32ac07aa7221aa75988a02166bdd420d5d5437bda31dbdb4dbd96ed52e2d3</originalsourceid><addsrcrecordid>eNo1kMtqwzAQRUVpoW7aTygYunY6M3rYWpaQPiDQTbsWsqVQB9tKJXuRv69N0s2dzeHO5TD2iLBGqOAZSJFSqlwTYLVGIUpEumIZoYSCCy6vWbYwxQLdsruUDgBcaMUzprf91NmxDUMe9rnNjzE0PqWitsm73KdxsrEdfP5zcjG402D7tsn74Hx3z272tkv-4XJX7Pt1-7V5L3afbx-bl13RUIVjobRoONkGSmtLIpxT6qqyQKhU7ZwgcNJJwcvaWY6udrWYQyvvJHlyfMWezr3ztN9pXmQOYYrD_NIQkKw0oIaZkmeqiSGl6PfmGNvexpNBMIsl82_JLJbMxRL_A7BaWcE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2025890190</pqid></control><display><type>article</type><title>Emulation of a process-based estuarine hydrodynamic model</title><source>Taylor & Francis:Master (3349 titles)</source><source>Alma/SFX Local Collection</source><creator>Chen, Limin ; Roy, Sujoy B. ; Hutton, Paul H.</creator><creatorcontrib>Chen, Limin ; Roy, Sujoy B. ; Hutton, Paul H.</creatorcontrib><description>Emulation modelling can be an effective alternative to traditional mechanistic approaches for complex environmental systems and, if carefully conceived, can offer significantly reduced run times and user expertise requirements. We present a case study of dynamic emulation for the domain of estuarine water quality modelling, by reporting the development and evaluation of a one-dimensional hydrodynamic model emulator. The proposed "neuroemulator" retains the dynamic nature of the process-based model utilizing a set of artificial neural networks. The underlying hydrodynamic model is routinely used for analysis and management of the northern reach of the San Francisco Bay-Delta estuary, a large complex region of strategic importance for water supply and ecosystem services on the Pacific coast of California, USA. The reduced computational expense of the emulator affords opportunities for direct use, as well as embedded use within other modelling frameworks such as those developed for reservoir operations and socio-hydrology.</description><identifier>ISSN: 0262-6667</identifier><identifier>EISSN: 2150-3435</identifier><identifier>DOI: 10.1080/02626667.2018.1447112</identifier><language>eng</language><publisher>Abingdon: Taylor & Francis Ltd</publisher><subject>Artificial neural networks ; Brackishwater environment ; Case studies ; Ecosystem services ; Estuaries ; Estuarine dynamics ; Estuarine environments ; Estuarine water ; Evaluation ; Hydrodynamic models ; Hydrodynamics ; Hydrology ; Modelling ; Neural networks ; System effectiveness ; Water quality ; Water supply</subject><ispartof>Hydrological sciences journal, 2018-04, Vol.63 (5), p.783-802</ispartof><rights>2018 IAHS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c281t-694c32ac07aa7221aa75988a02166bdd420d5d5437bda31dbdb4dbd96ed52e2d3</citedby><cites>FETCH-LOGICAL-c281t-694c32ac07aa7221aa75988a02166bdd420d5d5437bda31dbdb4dbd96ed52e2d3</cites><orcidid>0000-0003-2143-7124</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids></links><search><creatorcontrib>Chen, Limin</creatorcontrib><creatorcontrib>Roy, Sujoy B.</creatorcontrib><creatorcontrib>Hutton, Paul H.</creatorcontrib><title>Emulation of a process-based estuarine hydrodynamic model</title><title>Hydrological sciences journal</title><description>Emulation modelling can be an effective alternative to traditional mechanistic approaches for complex environmental systems and, if carefully conceived, can offer significantly reduced run times and user expertise requirements. We present a case study of dynamic emulation for the domain of estuarine water quality modelling, by reporting the development and evaluation of a one-dimensional hydrodynamic model emulator. The proposed "neuroemulator" retains the dynamic nature of the process-based model utilizing a set of artificial neural networks. The underlying hydrodynamic model is routinely used for analysis and management of the northern reach of the San Francisco Bay-Delta estuary, a large complex region of strategic importance for water supply and ecosystem services on the Pacific coast of California, USA. The reduced computational expense of the emulator affords opportunities for direct use, as well as embedded use within other modelling frameworks such as those developed for reservoir operations and socio-hydrology.</description><subject>Artificial neural networks</subject><subject>Brackishwater environment</subject><subject>Case studies</subject><subject>Ecosystem services</subject><subject>Estuaries</subject><subject>Estuarine dynamics</subject><subject>Estuarine environments</subject><subject>Estuarine water</subject><subject>Evaluation</subject><subject>Hydrodynamic models</subject><subject>Hydrodynamics</subject><subject>Hydrology</subject><subject>Modelling</subject><subject>Neural networks</subject><subject>System effectiveness</subject><subject>Water quality</subject><subject>Water supply</subject><issn>0262-6667</issn><issn>2150-3435</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNo1kMtqwzAQRUVpoW7aTygYunY6M3rYWpaQPiDQTbsWsqVQB9tKJXuRv69N0s2dzeHO5TD2iLBGqOAZSJFSqlwTYLVGIUpEumIZoYSCCy6vWbYwxQLdsruUDgBcaMUzprf91NmxDUMe9rnNjzE0PqWitsm73KdxsrEdfP5zcjG402D7tsn74Hx3z272tkv-4XJX7Pt1-7V5L3afbx-bl13RUIVjobRoONkGSmtLIpxT6qqyQKhU7ZwgcNJJwcvaWY6udrWYQyvvJHlyfMWezr3ztN9pXmQOYYrD_NIQkKw0oIaZkmeqiSGl6PfmGNvexpNBMIsl82_JLJbMxRL_A7BaWcE</recordid><startdate>20180404</startdate><enddate>20180404</enddate><creator>Chen, Limin</creator><creator>Roy, Sujoy B.</creator><creator>Hutton, Paul H.</creator><general>Taylor & Francis Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7ST</scope><scope>7TG</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0003-2143-7124</orcidid></search><sort><creationdate>20180404</creationdate><title>Emulation of a process-based estuarine hydrodynamic model</title><author>Chen, Limin ; Roy, Sujoy B. ; Hutton, Paul H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c281t-694c32ac07aa7221aa75988a02166bdd420d5d5437bda31dbdb4dbd96ed52e2d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Artificial neural networks</topic><topic>Brackishwater environment</topic><topic>Case studies</topic><topic>Ecosystem services</topic><topic>Estuaries</topic><topic>Estuarine dynamics</topic><topic>Estuarine environments</topic><topic>Estuarine water</topic><topic>Evaluation</topic><topic>Hydrodynamic models</topic><topic>Hydrodynamics</topic><topic>Hydrology</topic><topic>Modelling</topic><topic>Neural networks</topic><topic>System effectiveness</topic><topic>Water quality</topic><topic>Water supply</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Limin</creatorcontrib><creatorcontrib>Roy, Sujoy B.</creatorcontrib><creatorcontrib>Hutton, Paul H.</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><jtitle>Hydrological sciences journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Limin</au><au>Roy, Sujoy B.</au><au>Hutton, Paul H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Emulation of a process-based estuarine hydrodynamic model</atitle><jtitle>Hydrological sciences journal</jtitle><date>2018-04-04</date><risdate>2018</risdate><volume>63</volume><issue>5</issue><spage>783</spage><epage>802</epage><pages>783-802</pages><issn>0262-6667</issn><eissn>2150-3435</eissn><abstract>Emulation modelling can be an effective alternative to traditional mechanistic approaches for complex environmental systems and, if carefully conceived, can offer significantly reduced run times and user expertise requirements. We present a case study of dynamic emulation for the domain of estuarine water quality modelling, by reporting the development and evaluation of a one-dimensional hydrodynamic model emulator. The proposed "neuroemulator" retains the dynamic nature of the process-based model utilizing a set of artificial neural networks. The underlying hydrodynamic model is routinely used for analysis and management of the northern reach of the San Francisco Bay-Delta estuary, a large complex region of strategic importance for water supply and ecosystem services on the Pacific coast of California, USA. The reduced computational expense of the emulator affords opportunities for direct use, as well as embedded use within other modelling frameworks such as those developed for reservoir operations and socio-hydrology.</abstract><cop>Abingdon</cop><pub>Taylor & Francis Ltd</pub><doi>10.1080/02626667.2018.1447112</doi><tpages>20</tpages><orcidid>https://orcid.org/0000-0003-2143-7124</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0262-6667 |
ispartof | Hydrological sciences journal, 2018-04, Vol.63 (5), p.783-802 |
issn | 0262-6667 2150-3435 |
language | eng |
recordid | cdi_proquest_journals_2025890190 |
source | Taylor & Francis:Master (3349 titles); Alma/SFX Local Collection |
subjects | Artificial neural networks Brackishwater environment Case studies Ecosystem services Estuaries Estuarine dynamics Estuarine environments Estuarine water Evaluation Hydrodynamic models Hydrodynamics Hydrology Modelling Neural networks System effectiveness Water quality Water supply |
title | Emulation of a process-based estuarine hydrodynamic model |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-11T13%3A06%3A38IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Emulation%20of%20a%20process-based%20estuarine%20hydrodynamic%20model&rft.jtitle=Hydrological%20sciences%20journal&rft.au=Chen,%20Limin&rft.date=2018-04-04&rft.volume=63&rft.issue=5&rft.spage=783&rft.epage=802&rft.pages=783-802&rft.issn=0262-6667&rft.eissn=2150-3435&rft_id=info:doi/10.1080/02626667.2018.1447112&rft_dat=%3Cproquest_cross%3E2025890190%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2025890190&rft_id=info:pmid/&rfr_iscdi=true |