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Optimal design for dispersion experiment
The dispersion coefficient ( D) is a very important parameter for the management of water quality and pollution control. Conventional sampling methods are based on tracer studies. Sampling periods and intervals are often subjective and left to the choice of the experimenter. Sometimes several observ...
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Published in: | Water research (Oxford) 2002-11, Vol.36 (18), p.4570-4582 |
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description | The dispersion coefficient (
D) is a very important parameter for the management of water quality and pollution control. Conventional sampling methods are based on tracer studies. Sampling periods and intervals are often subjective and left to the choice of the experimenter. Sometimes several observations are made to determine D. Yet, making several observations does not necessarily ensure accurate estimation of the parameters. Sampling of tracer concentrations at poor times will result in inaccurate estimates of D and the flow velocity (
u). Therefore, the main aim of the study in question was to investigate the optimal sampling times for conducting fixed position variable-time sampling for tracer concentration experiments. This objective was achieved by the minimization of the least square criterion and applying the method proposed by Box and Lucas. The relative efficiency of each experimental design is predicted before data collection and analysis and confidence regions plotted. Results, on optimal sampling times for experiments are presented and illustrated. The application of these findings will harmonize results and reduce cost and labour expended on dispersion experiments. |
doi_str_mv | 10.1016/S0043-1354(02)00170-7 |
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D) is a very important parameter for the management of water quality and pollution control. Conventional sampling methods are based on tracer studies. Sampling periods and intervals are often subjective and left to the choice of the experimenter. Sometimes several observations are made to determine D. Yet, making several observations does not necessarily ensure accurate estimation of the parameters. Sampling of tracer concentrations at poor times will result in inaccurate estimates of D and the flow velocity (
u). Therefore, the main aim of the study in question was to investigate the optimal sampling times for conducting fixed position variable-time sampling for tracer concentration experiments. This objective was achieved by the minimization of the least square criterion and applying the method proposed by Box and Lucas. The relative efficiency of each experimental design is predicted before data collection and analysis and confidence regions plotted. Results, on optimal sampling times for experiments are presented and illustrated. The application of these findings will harmonize results and reduce cost and labour expended on dispersion experiments.</description><identifier>ISSN: 0043-1354</identifier><identifier>EISSN: 1879-2448</identifier><identifier>DOI: 10.1016/S0043-1354(02)00170-7</identifier><identifier>PMID: 12418660</identifier><identifier>CODEN: WATRAG</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Applied sciences ; Continental surface waters ; Dispersion experiment ; Earth sciences ; Earth, ocean, space ; Engineering and environment geology. Geothermics ; Exact sciences and technology ; Forecasting ; Hydrology ; Hydrology. Hydrogeology ; Least square criterion ; Models, Theoretical ; Natural water pollution ; Optimal design ; Pollution ; Pollution, environment geology ; Research Design ; Water Movements ; Water Pollutants ; Water treatment and pollution</subject><ispartof>Water research (Oxford), 2002-11, Vol.36 (18), p.4570-4582</ispartof><rights>2002</rights><rights>2002 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c422t-ec9da08dabf84ac9b40f89f6fe14b2db1db1eeb9e9866ac8113f1295209fd9303</citedby><cites>FETCH-LOGICAL-c422t-ec9da08dabf84ac9b40f89f6fe14b2db1db1eeb9e9866ac8113f1295209fd9303</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=13930922$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/12418660$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Agunwamba, J.C.</creatorcontrib><title>Optimal design for dispersion experiment</title><title>Water research (Oxford)</title><addtitle>Water Res</addtitle><description>The dispersion coefficient (
D) is a very important parameter for the management of water quality and pollution control. Conventional sampling methods are based on tracer studies. Sampling periods and intervals are often subjective and left to the choice of the experimenter. Sometimes several observations are made to determine D. Yet, making several observations does not necessarily ensure accurate estimation of the parameters. Sampling of tracer concentrations at poor times will result in inaccurate estimates of D and the flow velocity (
u). Therefore, the main aim of the study in question was to investigate the optimal sampling times for conducting fixed position variable-time sampling for tracer concentration experiments. This objective was achieved by the minimization of the least square criterion and applying the method proposed by Box and Lucas. The relative efficiency of each experimental design is predicted before data collection and analysis and confidence regions plotted. Results, on optimal sampling times for experiments are presented and illustrated. The application of these findings will harmonize results and reduce cost and labour expended on dispersion experiments.</description><subject>Applied sciences</subject><subject>Continental surface waters</subject><subject>Dispersion experiment</subject><subject>Earth sciences</subject><subject>Earth, ocean, space</subject><subject>Engineering and environment geology. Geothermics</subject><subject>Exact sciences and technology</subject><subject>Forecasting</subject><subject>Hydrology</subject><subject>Hydrology. Hydrogeology</subject><subject>Least square criterion</subject><subject>Models, Theoretical</subject><subject>Natural water pollution</subject><subject>Optimal design</subject><subject>Pollution</subject><subject>Pollution, environment geology</subject><subject>Research Design</subject><subject>Water Movements</subject><subject>Water Pollutants</subject><subject>Water treatment and pollution</subject><issn>0043-1354</issn><issn>1879-2448</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2002</creationdate><recordtype>article</recordtype><recordid>eNqFkE1LxDAQhoMo7rr6E5RelPVQnaTpR04ii1-wsAf1HNJkIpFuW5Ou6L83-4EehcDk8MzMOw8hpxSuKNDi-hmAZynNcj4FdglAS0jLPTKmVSlSxnm1T8a_yIgchfAOAIxl4pCMKOO0KgoYk-miH9xSNYnB4N7axHY-MS706IPr2gS_4s8tsR2OyYFVTcCTXZ2Q1_u7l9ljOl88PM1u56nmjA0pamEUVEbVtuJKi5qDrYQtLFJeM1PT-BBrgSLuV7qiNLOUiZyBsEZkkE3IxXZu77uPFYZBLl3Q2DSqxW4VJC0oz7OKRzDfgtp3IXi0so9Jlf-WFORakdwokuv7JTC5USTL2He2W7Cql2j-unZOInC-A1TQqrFetdqFPy6LMUUUOSE3Ww6jjk-HXgbtsNVonEc9SNO5f6L8AAT7gi8</recordid><startdate>20021101</startdate><enddate>20021101</enddate><creator>Agunwamba, J.C.</creator><general>Elsevier Ltd</general><general>Elsevier Science</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7TV</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H97</scope><scope>L.G</scope></search><sort><creationdate>20021101</creationdate><title>Optimal design for dispersion experiment</title><author>Agunwamba, J.C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c422t-ec9da08dabf84ac9b40f89f6fe14b2db1db1eeb9e9866ac8113f1295209fd9303</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2002</creationdate><topic>Applied sciences</topic><topic>Continental surface waters</topic><topic>Dispersion experiment</topic><topic>Earth sciences</topic><topic>Earth, ocean, space</topic><topic>Engineering and environment geology. Geothermics</topic><topic>Exact sciences and technology</topic><topic>Forecasting</topic><topic>Hydrology</topic><topic>Hydrology. Hydrogeology</topic><topic>Least square criterion</topic><topic>Models, Theoretical</topic><topic>Natural water pollution</topic><topic>Optimal design</topic><topic>Pollution</topic><topic>Pollution, environment geology</topic><topic>Research Design</topic><topic>Water Movements</topic><topic>Water Pollutants</topic><topic>Water treatment and pollution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Agunwamba, J.C.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Pollution 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) 3: Aquatic Pollution & Environmental Quality</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Water research (Oxford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Agunwamba, J.C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimal design for dispersion experiment</atitle><jtitle>Water research (Oxford)</jtitle><addtitle>Water Res</addtitle><date>2002-11-01</date><risdate>2002</risdate><volume>36</volume><issue>18</issue><spage>4570</spage><epage>4582</epage><pages>4570-4582</pages><issn>0043-1354</issn><eissn>1879-2448</eissn><coden>WATRAG</coden><abstract>The dispersion coefficient (
D) is a very important parameter for the management of water quality and pollution control. Conventional sampling methods are based on tracer studies. Sampling periods and intervals are often subjective and left to the choice of the experimenter. Sometimes several observations are made to determine D. Yet, making several observations does not necessarily ensure accurate estimation of the parameters. Sampling of tracer concentrations at poor times will result in inaccurate estimates of D and the flow velocity (
u). Therefore, the main aim of the study in question was to investigate the optimal sampling times for conducting fixed position variable-time sampling for tracer concentration experiments. This objective was achieved by the minimization of the least square criterion and applying the method proposed by Box and Lucas. The relative efficiency of each experimental design is predicted before data collection and analysis and confidence regions plotted. Results, on optimal sampling times for experiments are presented and illustrated. The application of these findings will harmonize results and reduce cost and labour expended on dispersion experiments.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><pmid>12418660</pmid><doi>10.1016/S0043-1354(02)00170-7</doi><tpages>13</tpages></addata></record> |
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subjects | Applied sciences Continental surface waters Dispersion experiment Earth sciences Earth, ocean, space Engineering and environment geology. Geothermics Exact sciences and technology Forecasting Hydrology Hydrology. Hydrogeology Least square criterion Models, Theoretical Natural water pollution Optimal design Pollution Pollution, environment geology Research Design Water Movements Water Pollutants Water treatment and pollution |
title | Optimal design for dispersion experiment |
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