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Estimation of evaporation from saline water
Evaporation, as the main source of water loss from closed lakes, makes a significant contribution to the water balance equation of the lake and can lead to changes in the chemical composition thereof. The objective of the study was to develop an equation for estimation of evaporation from the water...
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Published in: | Environmental monitoring and assessment 2020-11, Vol.192 (11), p.694-694, Article 694 |
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description | Evaporation, as the main source of water loss from closed lakes, makes a significant contribution to the water balance equation of the lake and can lead to changes in the chemical composition thereof. The objective of the study was to develop an equation for estimation of evaporation from the water surface with different depths and concentrations. To that end, 48 barrels were used to model evaporation at 6 different depths and 8 different concentrations of salinity. The experiments have been conducted in the same meteorological condition for all the barrels near the Urmia Lake. Data were collected in March 1, 2019, to Aug 31, 2019. Different equations fitted to data for each concentrations of salinity separately with different depths, and the equations with the least errors were selected. A model was then developed for the estimation of evaporation, considering the effect of salinity and depth, and the results were compared with daily measurements. The results were evaluated using the root mean square error (RMSE), correlation coefficient (CC), and Nash-Sutcliffe efficiency coefficient (NS). The results indicated that evaporation (Horizontal row) from water surface with high concentrations of salinity to low concentrations of salinity in different depths had an incremental trend. However, it can be seen in the vertical row that evaporation increased from low depth to high depth, and then decreased at a certain depth (120 cm) while the maximum evaporation rate belonged to 90-cm barrels for each concentration of salinity (in the vertical and horizontal row). At the end, the comparison of evaporation computed from the model and measured data showed that the model estimated evaporation at different depths and concentrations of salinity satisfactorily. |
doi_str_mv | 10.1007/s10661-020-08634-2 |
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The objective of the study was to develop an equation for estimation of evaporation from the water surface with different depths and concentrations. To that end, 48 barrels were used to model evaporation at 6 different depths and 8 different concentrations of salinity. The experiments have been conducted in the same meteorological condition for all the barrels near the Urmia Lake. Data were collected in March 1, 2019, to Aug 31, 2019. Different equations fitted to data for each concentrations of salinity separately with different depths, and the equations with the least errors were selected. A model was then developed for the estimation of evaporation, considering the effect of salinity and depth, and the results were compared with daily measurements. The results were evaluated using the root mean square error (RMSE), correlation coefficient (CC), and Nash-Sutcliffe efficiency coefficient (NS). The results indicated that evaporation (Horizontal row) from water surface with high concentrations of salinity to low concentrations of salinity in different depths had an incremental trend. However, it can be seen in the vertical row that evaporation increased from low depth to high depth, and then decreased at a certain depth (120 cm) while the maximum evaporation rate belonged to 90-cm barrels for each concentration of salinity (in the vertical and horizontal row). At the end, the comparison of evaporation computed from the model and measured data showed that the model estimated evaporation at different depths and concentrations of salinity satisfactorily.</description><identifier>ISSN: 0167-6369</identifier><identifier>EISSN: 1573-2959</identifier><identifier>DOI: 10.1007/s10661-020-08634-2</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Atmospheric Protection/Air Quality Control/Air Pollution ; Barrels ; Chemical composition ; Closed lakes ; Correlation coefficient ; Correlation coefficients ; Depth ; Earth and Environmental Science ; Ecology ; Ecotoxicology ; Environment ; Environmental Management ; Environmental monitoring ; Environmental science ; Evaporation ; Evaporation rate ; Lakes ; Low concentrations ; Mathematical models ; Meteorological conditions ; Monitoring/Environmental Analysis ; Root-mean-square errors ; Saline water ; Salinity ; Salinity effects ; Water balance ; Water loss</subject><ispartof>Environmental monitoring and assessment, 2020-11, Vol.192 (11), p.694-694, Article 694</ispartof><rights>Springer Nature Switzerland AG 2020</rights><rights>Springer Nature Switzerland AG 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c352t-2c38d52b0556145cd76c10e5cbb5fc26a1588f53a485953e6f2b846d67c2d5513</citedby><cites>FETCH-LOGICAL-c352t-2c38d52b0556145cd76c10e5cbb5fc26a1588f53a485953e6f2b846d67c2d5513</cites><orcidid>0000-0002-8596-2051</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2473344488/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2473344488?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,11688,27924,27925,36060,36061,44363,74895</link.rule.ids></links><search><creatorcontrib>Biazar, Seyed Mostafa</creatorcontrib><creatorcontrib>Fard, Ahmad Fakheri</creatorcontrib><creatorcontrib>Singh, Vijay P.</creatorcontrib><creatorcontrib>Dinpashoh, Yagob</creatorcontrib><creatorcontrib>Majnooni-Heris, Abolfazl</creatorcontrib><title>Estimation of evaporation from saline water</title><title>Environmental monitoring and assessment</title><addtitle>Environ Monit Assess</addtitle><description>Evaporation, as the main source of water loss from closed lakes, makes a significant contribution to the water balance equation of the lake and can lead to changes in the chemical composition thereof. The objective of the study was to develop an equation for estimation of evaporation from the water surface with different depths and concentrations. To that end, 48 barrels were used to model evaporation at 6 different depths and 8 different concentrations of salinity. The experiments have been conducted in the same meteorological condition for all the barrels near the Urmia Lake. Data were collected in March 1, 2019, to Aug 31, 2019. Different equations fitted to data for each concentrations of salinity separately with different depths, and the equations with the least errors were selected. A model was then developed for the estimation of evaporation, considering the effect of salinity and depth, and the results were compared with daily measurements. The results were evaluated using the root mean square error (RMSE), correlation coefficient (CC), and Nash-Sutcliffe efficiency coefficient (NS). The results indicated that evaporation (Horizontal row) from water surface with high concentrations of salinity to low concentrations of salinity in different depths had an incremental trend. However, it can be seen in the vertical row that evaporation increased from low depth to high depth, and then decreased at a certain depth (120 cm) while the maximum evaporation rate belonged to 90-cm barrels for each concentration of salinity (in the vertical and horizontal row). At the end, the comparison of evaporation computed from the model and measured data showed that the model estimated evaporation at different depths and concentrations of salinity satisfactorily.</description><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Barrels</subject><subject>Chemical composition</subject><subject>Closed lakes</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Depth</subject><subject>Earth and Environmental Science</subject><subject>Ecology</subject><subject>Ecotoxicology</subject><subject>Environment</subject><subject>Environmental Management</subject><subject>Environmental monitoring</subject><subject>Environmental science</subject><subject>Evaporation</subject><subject>Evaporation rate</subject><subject>Lakes</subject><subject>Low concentrations</subject><subject>Mathematical models</subject><subject>Meteorological conditions</subject><subject>Monitoring/Environmental Analysis</subject><subject>Root-mean-square errors</subject><subject>Saline water</subject><subject>Salinity</subject><subject>Salinity effects</subject><subject>Water balance</subject><subject>Water loss</subject><issn>0167-6369</issn><issn>1573-2959</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>M0C</sourceid><recordid>eNp9kMtKBDEQRYMoOD5-wFWDG0GilUelk6UM4wMG3Og6pNNp6WGmMyY9in9vtAXBhaui4NxL1SHkjMEVA6ivMwOlGAUOFLQSkvI9MmNYC8oNmn0yA6ZqqoQyh-Qo5xUAmFqaGblc5LHfuLGPQxW7Kry5bUzT2qW4qbJb90Oo3t0Y0gk56Nw6h9OfeUyebxdP83u6fLx7mN8sqRfIR8q90C3yBhAVk-jbWnkGAX3TYOe5cgy17lA4qdGgCKrjjZaqVbXnLSITx-Ri6t2m-LoLebSbPvuwXrshxF22XEpjlGAKCnr-B13FXRrKdYWqhZBSal0oPlE-xZxT6Ow2lafTh2Vgv_zZyZ8t_uy3P8tLSEyhXODhJaTf6n9Sn9EacJQ</recordid><startdate>20201101</startdate><enddate>20201101</enddate><creator>Biazar, Seyed Mostafa</creator><creator>Fard, Ahmad Fakheri</creator><creator>Singh, Vijay P.</creator><creator>Dinpashoh, 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of evaporation from saline water</title><author>Biazar, Seyed Mostafa ; Fard, Ahmad Fakheri ; Singh, Vijay P. ; Dinpashoh, Yagob ; Majnooni-Heris, Abolfazl</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c352t-2c38d52b0556145cd76c10e5cbb5fc26a1588f53a485953e6f2b846d67c2d5513</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Atmospheric Protection/Air Quality Control/Air Pollution</topic><topic>Barrels</topic><topic>Chemical composition</topic><topic>Closed lakes</topic><topic>Correlation coefficient</topic><topic>Correlation coefficients</topic><topic>Depth</topic><topic>Earth and Environmental Science</topic><topic>Ecology</topic><topic>Ecotoxicology</topic><topic>Environment</topic><topic>Environmental Management</topic><topic>Environmental monitoring</topic><topic>Environmental science</topic><topic>Evaporation</topic><topic>Evaporation 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water</atitle><jtitle>Environmental monitoring and assessment</jtitle><stitle>Environ Monit Assess</stitle><date>2020-11-01</date><risdate>2020</risdate><volume>192</volume><issue>11</issue><spage>694</spage><epage>694</epage><pages>694-694</pages><artnum>694</artnum><issn>0167-6369</issn><eissn>1573-2959</eissn><abstract>Evaporation, as the main source of water loss from closed lakes, makes a significant contribution to the water balance equation of the lake and can lead to changes in the chemical composition thereof. The objective of the study was to develop an equation for estimation of evaporation from the water surface with different depths and concentrations. To that end, 48 barrels were used to model evaporation at 6 different depths and 8 different concentrations of salinity. The experiments have been conducted in the same meteorological condition for all the barrels near the Urmia Lake. Data were collected in March 1, 2019, to Aug 31, 2019. Different equations fitted to data for each concentrations of salinity separately with different depths, and the equations with the least errors were selected. A model was then developed for the estimation of evaporation, considering the effect of salinity and depth, and the results were compared with daily measurements. The results were evaluated using the root mean square error (RMSE), correlation coefficient (CC), and Nash-Sutcliffe efficiency coefficient (NS). The results indicated that evaporation (Horizontal row) from water surface with high concentrations of salinity to low concentrations of salinity in different depths had an incremental trend. However, it can be seen in the vertical row that evaporation increased from low depth to high depth, and then decreased at a certain depth (120 cm) while the maximum evaporation rate belonged to 90-cm barrels for each concentration of salinity (in the vertical and horizontal row). At the end, the comparison of evaporation computed from the model and measured data showed that the model estimated evaporation at different depths and concentrations of salinity satisfactorily.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s10661-020-08634-2</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-8596-2051</orcidid></addata></record> |
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subjects | Atmospheric Protection/Air Quality Control/Air Pollution Barrels Chemical composition Closed lakes Correlation coefficient Correlation coefficients Depth Earth and Environmental Science Ecology Ecotoxicology Environment Environmental Management Environmental monitoring Environmental science Evaporation Evaporation rate Lakes Low concentrations Mathematical models Meteorological conditions Monitoring/Environmental Analysis Root-mean-square errors Saline water Salinity Salinity effects Water balance Water loss |
title | Estimation of evaporation from saline water |
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