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Stream temperature dynamics: Measurements and modeling
A numerical model based on a finite difference solution of the unsteady heat advection‐dispersion equation is formulated to predict water temperatures in streams at time increments of 1 hour. An energy balance accounts for the effects of air temperature, solar radiation, relative humidity, cloud cov...
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Published in: | Water resources research 1993-07, Vol.29 (7), p.2299-2312 |
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container_title | Water resources research |
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creator | Sinokrot, Bashar A. Stefan, Heinz G. |
description | A numerical model based on a finite difference solution of the unsteady heat advection‐dispersion equation is formulated to predict water temperatures in streams at time increments of 1 hour. An energy balance accounts for the effects of air temperature, solar radiation, relative humidity, cloud cover, and wind speed on the net rate of heat exchange through the water surface, and heat conduction between water and streambed. Continuous stream temperature recordings in shallow streams show strong dynamic behavior including diurnal variations of several degrees Celsius which are lost in the standard daily records. These measured water temperatures are used to calibrate the model for the optimum percentages of Sun shading and wind sheltering. Stream exposure to solar radiation is shown to vary from 30 to 100% and wind exposure from 10 to 30% depending on the character of the stream. Values are related to stream width and season because of variable leaf cover of trees on stream banks. After calibration, accuracies of hourly and daily water temperature predictions over periods of several weeks are of the order of 0.2° to 1°C. Solar (shortwave) radiation is shown to be the most important component of the heat flux across the stream water surface, but none of the other components, i.e., long‐wave radiation, evaporation, and convection to the atmosphere, are negligible. Conductive heat exchange between the streambed and the water is a significant heat balance component in shallow streams. |
doi_str_mv | 10.1029/93WR00540 |
format | article |
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An energy balance accounts for the effects of air temperature, solar radiation, relative humidity, cloud cover, and wind speed on the net rate of heat exchange through the water surface, and heat conduction between water and streambed. Continuous stream temperature recordings in shallow streams show strong dynamic behavior including diurnal variations of several degrees Celsius which are lost in the standard daily records. These measured water temperatures are used to calibrate the model for the optimum percentages of Sun shading and wind sheltering. Stream exposure to solar radiation is shown to vary from 30 to 100% and wind exposure from 10 to 30% depending on the character of the stream. Values are related to stream width and season because of variable leaf cover of trees on stream banks. After calibration, accuracies of hourly and daily water temperature predictions over periods of several weeks are of the order of 0.2° to 1°C. Solar (shortwave) radiation is shown to be the most important component of the heat flux across the stream water surface, but none of the other components, i.e., long‐wave radiation, evaporation, and convection to the atmosphere, are negligible. Conductive heat exchange between the streambed and the water is a significant heat balance component in shallow streams.</description><identifier>ISSN: 0043-1397</identifier><identifier>EISSN: 1944-7973</identifier><identifier>DOI: 10.1029/93WR00540</identifier><language>eng</language><publisher>United States: Blackwell Publishing Ltd</publisher><subject>540340 - Environment, Aquatic- Thermal Effluents Monitoring & Transport- (1990-) ; 990200 - Mathematics & Computers ; DYNAMICS ; ENERGY BALANCE ; ENVIRONMENTAL SCIENCES ; FORECASTING ; GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE ; MATHEMATICAL MODELS ; MECHANICS ; STREAMS ; SURFACE WATERS ; TEMPERATURE DISTRIBUTION</subject><ispartof>Water resources research, 1993-07, Vol.29 (7), p.2299-2312</ispartof><rights>Copyright 1993 by the American Geophysical Union.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a4835-95ff4e650947996ce2c453196545ba91039fc13722ed5fdb36d8111460a105da3</citedby><cites>FETCH-LOGICAL-a4835-95ff4e650947996ce2c453196545ba91039fc13722ed5fdb36d8111460a105da3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F93WR00540$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F93WR00540$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,780,784,885,1416,27924,27925,46049,46473</link.rule.ids><backlink>$$Uhttps://www.osti.gov/biblio/5414590$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Sinokrot, Bashar A.</creatorcontrib><creatorcontrib>Stefan, Heinz G.</creatorcontrib><title>Stream temperature dynamics: Measurements and modeling</title><title>Water resources research</title><addtitle>Water Resour. Res</addtitle><description>A numerical model based on a finite difference solution of the unsteady heat advection‐dispersion equation is formulated to predict water temperatures in streams at time increments of 1 hour. An energy balance accounts for the effects of air temperature, solar radiation, relative humidity, cloud cover, and wind speed on the net rate of heat exchange through the water surface, and heat conduction between water and streambed. Continuous stream temperature recordings in shallow streams show strong dynamic behavior including diurnal variations of several degrees Celsius which are lost in the standard daily records. These measured water temperatures are used to calibrate the model for the optimum percentages of Sun shading and wind sheltering. Stream exposure to solar radiation is shown to vary from 30 to 100% and wind exposure from 10 to 30% depending on the character of the stream. Values are related to stream width and season because of variable leaf cover of trees on stream banks. After calibration, accuracies of hourly and daily water temperature predictions over periods of several weeks are of the order of 0.2° to 1°C. Solar (shortwave) radiation is shown to be the most important component of the heat flux across the stream water surface, but none of the other components, i.e., long‐wave radiation, evaporation, and convection to the atmosphere, are negligible. Conductive heat exchange between the streambed and the water is a significant heat balance component in shallow streams.</description><subject>540340 - Environment, Aquatic- Thermal Effluents Monitoring & Transport- (1990-)</subject><subject>990200 - Mathematics & Computers</subject><subject>DYNAMICS</subject><subject>ENERGY BALANCE</subject><subject>ENVIRONMENTAL SCIENCES</subject><subject>FORECASTING</subject><subject>GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE</subject><subject>MATHEMATICAL MODELS</subject><subject>MECHANICS</subject><subject>STREAMS</subject><subject>SURFACE WATERS</subject><subject>TEMPERATURE DISTRIBUTION</subject><issn>0043-1397</issn><issn>1944-7973</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1993</creationdate><recordtype>article</recordtype><recordid>eNqN0E1LHEEQBuBGEnBjPPgPBg-Ch9Hqqf6Y9iaLX7AmsFH22LQ9NTo6H2t3L8n--4yMeBM8FRTPW1AvYwccTjgU5tTgagkgBeywGTdC5Npo_MZmAAJzjkbvsh8xPgNwIZWeMfUnBXJdlqhbU3BpEyirtr3rGh_Psltycdx01KeYub7KuqGitukff7LvtWsj7b_PPXZ_eXE3v84Xv69u5ueL3IkSZW5kXQtSEozQxihPhRcSuVFSyAdnOKCpPUddFFTJunpAVZWcc6HAcZCVwz12ON0dYmps9E0i_-SHviefrBTjEwZGdDShdRheNxST7ZroqW1dT8MmWl5KQFBfgKhKbbAc4fEEfRhiDFTbdWg6F7aWg33r2X70PNrTyf5tWtp-Du1qOV8qjnJM5FOiiYn-fSRceLFKo5Z29evK6mK-QK0KK_E_hvKKIQ</recordid><startdate>199307</startdate><enddate>199307</enddate><creator>Sinokrot, Bashar A.</creator><creator>Stefan, Heinz G.</creator><general>Blackwell Publishing Ltd</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7TG</scope><scope>KL.</scope><scope>OTOTI</scope></search><sort><creationdate>199307</creationdate><title>Stream temperature dynamics: Measurements and modeling</title><author>Sinokrot, Bashar A. ; Stefan, Heinz G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a4835-95ff4e650947996ce2c453196545ba91039fc13722ed5fdb36d8111460a105da3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1993</creationdate><topic>540340 - Environment, Aquatic- Thermal Effluents Monitoring & Transport- (1990-)</topic><topic>990200 - Mathematics & Computers</topic><topic>DYNAMICS</topic><topic>ENERGY BALANCE</topic><topic>ENVIRONMENTAL SCIENCES</topic><topic>FORECASTING</topic><topic>GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE</topic><topic>MATHEMATICAL MODELS</topic><topic>MECHANICS</topic><topic>STREAMS</topic><topic>SURFACE WATERS</topic><topic>TEMPERATURE DISTRIBUTION</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sinokrot, Bashar A.</creatorcontrib><creatorcontrib>Stefan, Heinz G.</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>OSTI.GOV</collection><jtitle>Water resources research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sinokrot, Bashar A.</au><au>Stefan, Heinz G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Stream temperature dynamics: Measurements and modeling</atitle><jtitle>Water resources research</jtitle><addtitle>Water Resour. Res</addtitle><date>1993-07</date><risdate>1993</risdate><volume>29</volume><issue>7</issue><spage>2299</spage><epage>2312</epage><pages>2299-2312</pages><issn>0043-1397</issn><eissn>1944-7973</eissn><abstract>A numerical model based on a finite difference solution of the unsteady heat advection‐dispersion equation is formulated to predict water temperatures in streams at time increments of 1 hour. An energy balance accounts for the effects of air temperature, solar radiation, relative humidity, cloud cover, and wind speed on the net rate of heat exchange through the water surface, and heat conduction between water and streambed. Continuous stream temperature recordings in shallow streams show strong dynamic behavior including diurnal variations of several degrees Celsius which are lost in the standard daily records. These measured water temperatures are used to calibrate the model for the optimum percentages of Sun shading and wind sheltering. Stream exposure to solar radiation is shown to vary from 30 to 100% and wind exposure from 10 to 30% depending on the character of the stream. Values are related to stream width and season because of variable leaf cover of trees on stream banks. After calibration, accuracies of hourly and daily water temperature predictions over periods of several weeks are of the order of 0.2° to 1°C. Solar (shortwave) radiation is shown to be the most important component of the heat flux across the stream water surface, but none of the other components, i.e., long‐wave radiation, evaporation, and convection to the atmosphere, are negligible. Conductive heat exchange between the streambed and the water is a significant heat balance component in shallow streams.</abstract><cop>United States</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/93WR00540</doi><tpages>14</tpages></addata></record> |
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subjects | 540340 - Environment, Aquatic- Thermal Effluents Monitoring & Transport- (1990-) 990200 - Mathematics & Computers DYNAMICS ENERGY BALANCE ENVIRONMENTAL SCIENCES FORECASTING GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE MATHEMATICAL MODELS MECHANICS STREAMS SURFACE WATERS TEMPERATURE DISTRIBUTION |
title | Stream temperature dynamics: Measurements and modeling |
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