Performance evaluation of a water level sensor under various turbidity levels in lowland crop production systems
The practice of alternate wetting and drying (AWD), a water-saving technology in lowland crop production systems, can be greatly facilitated using wireless water level sensors. However, these sensors generally work under clear water conditions. The sensitivity of these sensors to turbidity is import...
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creator | Pereira, G S Ramirez, R C Agulto, E S Ella, V B |
description | The practice of alternate wetting and drying (AWD), a water-saving technology in lowland crop production systems, can be greatly facilitated using wireless water level sensors. However, these sensors generally work under clear water conditions. The sensitivity of these sensors to turbidity is important for accurate water level measurement and appropriate irrigation scheduling. This study evaluated the performance of a high-end water level sensor of the submersible pressure transducer type under various turbidity levels. The performance tests were performed in the laboratory using water samples collected from a typical lowland rice production system under various levels of turbidity replicated three times with clear water as control. The readings of the sensors were compared with manual readings for each turbidity level in all replications. Results showed that the measured water level depth generally increases with increasing turbidity for each voltage level. The linear regression or calibration equation developed for each turbidity level proved to be adequate as evidenced by a relatively low RMSE of less than 1 mV. Results of ANOVA suggest that turbidity significantly affects the accuracy of the water level sensor (
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p <.001
). A unified calibration equation (R
2
=0.9985 and RMSE=1.971 mV) was developed to account for the effect of turbidity up to 4300 FAU on the water level measurements. Results of this study can be used to improve the accuracy of water level monitoring in irrigated lowland crop production systems employing alternate wetting and drying technology to further increase irrigation efficiencies and augment water savings particularly during the dry season or under water-scarce conditions for a more sustainable crop production.</description><identifier>ISSN: 1755-1307</identifier><identifier>EISSN: 1755-1315</identifier><identifier>DOI: 10.1088/1755-1315/1038/1/012033</identifier><language>eng</language><publisher>Bristol: IOP Publishing</publisher><subject>Calibration ; Crop production ; Crop production systems ; Crops ; Dry season ; Drying ; Irrigation ; Irrigation efficiency ; Irrigation scheduling ; Irrigation systems ; Irrigation water ; Performance evaluation ; Performance tests ; Sensors ; Sustainable agriculture ; Technology ; Turbidity ; Variance analysis ; Water analysis ; Water conservation ; Water depth ; Water levels ; Water sampling ; Wetting</subject><ispartof>IOP conference series. Earth and environmental science, 2022-06, Vol.1038 (1), p.12033</ispartof><rights>Published under licence by IOP Publishing Ltd</rights><rights>Published under licence by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2733-b88f52b409b20d84a047923ecae09981bd54aa4780ff216c6ce77db5260805603</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.1088/1755-1315/1038/1/012033/pdf$$EPDF$$P50$$Giop$$Hfree_for_read</linktopdf><link.rule.ids>314,776,780,27903,27904,38847,38869,53819,53846</link.rule.ids></links><search><creatorcontrib>Pereira, G S</creatorcontrib><creatorcontrib>Ramirez, R C</creatorcontrib><creatorcontrib>Agulto, E S</creatorcontrib><creatorcontrib>Ella, V B</creatorcontrib><title>Performance evaluation of a water level sensor under various turbidity levels in lowland crop production systems</title><title>IOP conference series. Earth and environmental science</title><addtitle>IOP Conf. Ser.: Earth Environ. Sci</addtitle><description>The practice of alternate wetting and drying (AWD), a water-saving technology in lowland crop production systems, can be greatly facilitated using wireless water level sensors. However, these sensors generally work under clear water conditions. The sensitivity of these sensors to turbidity is important for accurate water level measurement and appropriate irrigation scheduling. This study evaluated the performance of a high-end water level sensor of the submersible pressure transducer type under various turbidity levels. The performance tests were performed in the laboratory using water samples collected from a typical lowland rice production system under various levels of turbidity replicated three times with clear water as control. The readings of the sensors were compared with manual readings for each turbidity level in all replications. Results showed that the measured water level depth generally increases with increasing turbidity for each voltage level. The linear regression or calibration equation developed for each turbidity level proved to be adequate as evidenced by a relatively low RMSE of less than 1 mV. Results of ANOVA suggest that turbidity significantly affects the accuracy of the water level sensor (
p <.001
). A unified calibration equation (R
2
=0.9985 and RMSE=1.971 mV) was developed to account for the effect of turbidity up to 4300 FAU on the water level measurements. Results of this study can be used to improve the accuracy of water level monitoring in irrigated lowland crop production systems employing alternate wetting and drying technology to further increase irrigation efficiencies and augment water savings particularly during the dry season or under water-scarce conditions for a more sustainable crop production.</description><subject>Calibration</subject><subject>Crop production</subject><subject>Crop production systems</subject><subject>Crops</subject><subject>Dry season</subject><subject>Drying</subject><subject>Irrigation</subject><subject>Irrigation efficiency</subject><subject>Irrigation scheduling</subject><subject>Irrigation systems</subject><subject>Irrigation water</subject><subject>Performance evaluation</subject><subject>Performance tests</subject><subject>Sensors</subject><subject>Sustainable agriculture</subject><subject>Technology</subject><subject>Turbidity</subject><subject>Variance analysis</subject><subject>Water analysis</subject><subject>Water conservation</subject><subject>Water depth</subject><subject>Water levels</subject><subject>Water sampling</subject><subject>Wetting</subject><issn>1755-1307</issn><issn>1755-1315</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>O3W</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqFkF9LwzAUxYMoOKefwYBPPtTdJG2TPsqYf2CgoD6HtEmgo2tq0m7s25taUQTBpyQ355x7-CF0SeCGgBALwrMsIYxkCwIsPhdAKDB2hGbfP8ffd-Cn6CyEDUDOU1bMUPdsvHV-q9rKYLNTzaD62rXYWazwXvXG48bsTIODaYPzeGh1HO2Ur90QcD_4stZ1f5hEAdctbty-Ua3GlXcd7rzTQ_WZGA6hN9twjk6saoK5-Drn6O1u9bp8SNZP94_L23VSUc5YUgphM1qmUJQUtEgVpLygzFTKQFEIUuosVSrlAqylJK_yynCuy4zmICDLgc3R1ZQbK7wPJvRy4wbfxpWS5jGq4EU6qvikim1D8MbKztdb5Q-SgBzxyhGcHCHKEa8kcsIbnWxy1q77if7fdf2Ha7V6-a2TnbbsA9u9ivM</recordid><startdate>20220601</startdate><enddate>20220601</enddate><creator>Pereira, G S</creator><creator>Ramirez, R C</creator><creator>Agulto, E S</creator><creator>Ella, V B</creator><general>IOP Publishing</general><scope>O3W</scope><scope>TSCCA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>PATMY</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope></search><sort><creationdate>20220601</creationdate><title>Performance evaluation of a water level sensor under various turbidity levels in lowland crop production systems</title><author>Pereira, G S ; 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Earth and environmental science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pereira, G S</au><au>Ramirez, R C</au><au>Agulto, E S</au><au>Ella, V B</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Performance evaluation of a water level sensor under various turbidity levels in lowland crop production systems</atitle><jtitle>IOP conference series. Earth and environmental science</jtitle><addtitle>IOP Conf. Ser.: Earth Environ. Sci</addtitle><date>2022-06-01</date><risdate>2022</risdate><volume>1038</volume><issue>1</issue><spage>12033</spage><pages>12033-</pages><issn>1755-1307</issn><eissn>1755-1315</eissn><abstract>The practice of alternate wetting and drying (AWD), a water-saving technology in lowland crop production systems, can be greatly facilitated using wireless water level sensors. However, these sensors generally work under clear water conditions. The sensitivity of these sensors to turbidity is important for accurate water level measurement and appropriate irrigation scheduling. This study evaluated the performance of a high-end water level sensor of the submersible pressure transducer type under various turbidity levels. The performance tests were performed in the laboratory using water samples collected from a typical lowland rice production system under various levels of turbidity replicated three times with clear water as control. The readings of the sensors were compared with manual readings for each turbidity level in all replications. Results showed that the measured water level depth generally increases with increasing turbidity for each voltage level. The linear regression or calibration equation developed for each turbidity level proved to be adequate as evidenced by a relatively low RMSE of less than 1 mV. Results of ANOVA suggest that turbidity significantly affects the accuracy of the water level sensor (
p <.001
). A unified calibration equation (R
2
=0.9985 and RMSE=1.971 mV) was developed to account for the effect of turbidity up to 4300 FAU on the water level measurements. Results of this study can be used to improve the accuracy of water level monitoring in irrigated lowland crop production systems employing alternate wetting and drying technology to further increase irrigation efficiencies and augment water savings particularly during the dry season or under water-scarce conditions for a more sustainable crop production.</abstract><cop>Bristol</cop><pub>IOP Publishing</pub><doi>10.1088/1755-1315/1038/1/012033</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Calibration Crop production Crop production systems Crops Dry season Drying Irrigation Irrigation efficiency Irrigation scheduling Irrigation systems Irrigation water Performance evaluation Performance tests Sensors Sustainable agriculture Technology Turbidity Variance analysis Water analysis Water conservation Water depth Water levels Water sampling Wetting |
title | Performance evaluation of a water level sensor under various turbidity levels in lowland crop production systems |
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