Estimating Crop Water Use of Cotton in the Texas High Plains
The growth and yield of cotton (Gossypium hirsutum L.) in the semiarid Texas High Plains is driven by the amount of water available to the crop through rainfall and irrigation. Various methods have been developed for quantifying the crop water use (CWU) of agricultural crops. In this study, we descr...
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| Veröffentlicht in: | Agronomy journal 2010-11, Vol.102 (6), p.1641-1651 |
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| description | The growth and yield of cotton (Gossypium hirsutum L.) in the semiarid Texas High Plains is driven by the amount of water available to the crop through rainfall and irrigation. Various methods have been developed for quantifying the crop water use (CWU) of agricultural crops. In this study, we described a method for estimating CWU that uses a modified version of the Penman–Monteith Equation. In this method, CWU is equal to the transpiration of a well-watered crop with complete ground cover (determined from ambient environmental conditions) multiplied by the amount of plant canopy present (quantified by crop ground cover) and a parameter (Fs ) related to the effects of stomatal closure. For irrigated and dryland cotton that are acclimated to their respective environments, Fs ≈ 1. This suggests that control of canopy leaf area is a primary mechanism for acclimating to the surrounding environment. When Fs < 1, the plant is not acclimated with its environment and must rely on stomatal closure to conserve available water in the root zone. The method was developed using surface energy balance data and remotely sensed crop ground cover for three fields near Lubbock, TX. This method could be used in irrigation scheduling where irrigation is used to replace the daily CWU of a crop. This approach might be superior to the standard crop coefficient approach because it could use remotely sensed crop ground cover as a “spectral crop coefficient” that would make the resulting estimates of CWU specific to individual fields. |
| doi_str_mv | 10.2134/agronj2010.0076 |
| format | Article |
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Various methods have been developed for quantifying the crop water use (CWU) of agricultural crops. In this study, we described a method for estimating CWU that uses a modified version of the Penman–Monteith Equation. In this method, CWU is equal to the transpiration of a well-watered crop with complete ground cover (determined from ambient environmental conditions) multiplied by the amount of plant canopy present (quantified by crop ground cover) and a parameter (Fs ) related to the effects of stomatal closure. For irrigated and dryland cotton that are acclimated to their respective environments, Fs ≈ 1. This suggests that control of canopy leaf area is a primary mechanism for acclimating to the surrounding environment. When Fs < 1, the plant is not acclimated with its environment and must rely on stomatal closure to conserve available water in the root zone. The method was developed using surface energy balance data and remotely sensed crop ground cover for three fields near Lubbock, TX. This method could be used in irrigation scheduling where irrigation is used to replace the daily CWU of a crop. This approach might be superior to the standard crop coefficient approach because it could use remotely sensed crop ground cover as a “spectral crop coefficient” that would make the resulting estimates of CWU specific to individual fields.</description><identifier>ISSN: 0002-1962</identifier><identifier>ISSN: 1435-0645</identifier><identifier>EISSN: 1435-0645</identifier><identifier>DOI: 10.2134/agronj2010.0076</identifier><identifier>CODEN: AGJOAT</identifier><language>eng</language><publisher>Madison: American Society of Agronomy</publisher><subject>acclimation ; Agronomy. Soil science and plant productions ; Biological and medical sciences ; canopy ; cotton ; crop coefficient ; crop yield ; dryland farming ; energy balance ; equations ; estimation ; Fundamental and applied biological sciences. Psychology ; Gossypium hirsutum ; irrigated farming ; irrigation rates ; irrigation scheduling ; mathematical models ; Penman-Monteith Equation ; plant-water relations ; rain ; remote sensing ; rhizosphere ; semiarid zones ; stomatal conductance ; stomatal movement ; transpiration ; vegetation cover ; Water use ; water use efficiency</subject><ispartof>Agronomy journal, 2010-11, Vol.102 (6), p.1641-1651</ispartof><rights>2010 The Authors.</rights><rights>2015 INIST-CNRS</rights><rights>Copyright American Society of Agronomy Nov 2010</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4516-83df20b746004705247887cc65ea4c311545d624d3aa21db4a2a22978cad50d03</citedby><cites>FETCH-LOGICAL-c4516-83df20b746004705247887cc65ea4c311545d624d3aa21db4a2a22978cad50d03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.2134%2Fagronj2010.0076$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.2134%2Fagronj2010.0076$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23437039$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Rajan, Nithya</creatorcontrib><creatorcontrib>Maas, Stephan J</creatorcontrib><creatorcontrib>Kathilankal, James C</creatorcontrib><title>Estimating Crop Water Use of Cotton in the Texas High Plains</title><title>Agronomy journal</title><description>The growth and yield of cotton (Gossypium hirsutum L.) in the semiarid Texas High Plains is driven by the amount of water available to the crop through rainfall and irrigation. Various methods have been developed for quantifying the crop water use (CWU) of agricultural crops. In this study, we described a method for estimating CWU that uses a modified version of the Penman–Monteith Equation. In this method, CWU is equal to the transpiration of a well-watered crop with complete ground cover (determined from ambient environmental conditions) multiplied by the amount of plant canopy present (quantified by crop ground cover) and a parameter (Fs ) related to the effects of stomatal closure. For irrigated and dryland cotton that are acclimated to their respective environments, Fs ≈ 1. This suggests that control of canopy leaf area is a primary mechanism for acclimating to the surrounding environment. When Fs < 1, the plant is not acclimated with its environment and must rely on stomatal closure to conserve available water in the root zone. The method was developed using surface energy balance data and remotely sensed crop ground cover for three fields near Lubbock, TX. This method could be used in irrigation scheduling where irrigation is used to replace the daily CWU of a crop. This approach might be superior to the standard crop coefficient approach because it could use remotely sensed crop ground cover as a “spectral crop coefficient” that would make the resulting estimates of CWU specific to individual fields.</description><subject>acclimation</subject><subject>Agronomy. Soil science and plant productions</subject><subject>Biological and medical sciences</subject><subject>canopy</subject><subject>cotton</subject><subject>crop coefficient</subject><subject>crop yield</subject><subject>dryland farming</subject><subject>energy balance</subject><subject>equations</subject><subject>estimation</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Gossypium hirsutum</subject><subject>irrigated farming</subject><subject>irrigation rates</subject><subject>irrigation scheduling</subject><subject>mathematical models</subject><subject>Penman-Monteith Equation</subject><subject>plant-water relations</subject><subject>rain</subject><subject>remote sensing</subject><subject>rhizosphere</subject><subject>semiarid zones</subject><subject>stomatal conductance</subject><subject>stomatal movement</subject><subject>transpiration</subject><subject>vegetation cover</subject><subject>Water use</subject><subject>water use efficiency</subject><issn>0002-1962</issn><issn>1435-0645</issn><issn>1435-0645</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqFkEFrGzEQhUVJoE7Sc48VhdDTJiNptNqFQjEmcRJCU9qYHsVEq3XWbFautKbNv4-MTQu59DTMzDfvDY-x9wLOpFB4TssYhpWE3AOY8g2bCFS6gBL1AZsAgCxEXcq37CilFYAQNYoJ-3yRxu6Jxm5Y8lkMa_6TRh_5InkeWj4L4xgG3g18fPT83v-hxK-65SP_1lM3pBN22FKf_Lt9PWaLy4v72VVxeze_nk1vC4dalEWlmlbCg8ESAA1oiaaqjHOl9oROCaFRN6XERhFJ0TwgSZKyNpWjRkMD6ph92umuY_i18Wm0T11yvu9p8GGTbCWFUboCzOTHV-QqbOKQn7MVGJS1KnWGzneQiyGl6Fu7jjmD-GwF2G2W9l-Wdptlvjjdy1Jy1LeRBtelv2dSoTKg6sx92XG_u94__0_WTuc3cjr_fvf1ZjvbO33YKbQUtnx2WfzIWwWilghYqxdJJY3c</recordid><startdate>201011</startdate><enddate>201011</enddate><creator>Rajan, Nithya</creator><creator>Maas, Stephan J</creator><creator>Kathilankal, James C</creator><general>American Society of Agronomy</general><scope>FBQ</scope><scope>24P</scope><scope>WIN</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X2</scope><scope>7XB</scope><scope>88I</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M0K</scope><scope>M2O</scope><scope>M2P</scope><scope>M7S</scope><scope>MBDVC</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>S0X</scope><scope>7UA</scope><scope>C1K</scope></search><sort><creationdate>201011</creationdate><title>Estimating Crop Water Use of Cotton in the Texas High Plains</title><author>Rajan, Nithya ; Maas, Stephan J ; Kathilankal, James C</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4516-83df20b746004705247887cc65ea4c311545d624d3aa21db4a2a22978cad50d03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>acclimation</topic><topic>Agronomy. Soil science and plant productions</topic><topic>Biological and medical sciences</topic><topic>canopy</topic><topic>cotton</topic><topic>crop coefficient</topic><topic>crop yield</topic><topic>dryland farming</topic><topic>energy balance</topic><topic>equations</topic><topic>estimation</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Gossypium hirsutum</topic><topic>irrigated farming</topic><topic>irrigation rates</topic><topic>irrigation scheduling</topic><topic>mathematical models</topic><topic>Penman-Monteith Equation</topic><topic>plant-water relations</topic><topic>rain</topic><topic>remote sensing</topic><topic>rhizosphere</topic><topic>semiarid zones</topic><topic>stomatal conductance</topic><topic>stomatal movement</topic><topic>transpiration</topic><topic>vegetation cover</topic><topic>Water use</topic><topic>water use efficiency</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rajan, Nithya</creatorcontrib><creatorcontrib>Maas, Stephan J</creatorcontrib><creatorcontrib>Kathilankal, James C</creatorcontrib><collection>AGRIS</collection><collection>Wiley Open Access</collection><collection>Wiley-Blackwell Open Access Backfiles</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>eLibrary</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Agriculture Science Database</collection><collection>ProQuest research library</collection><collection>Science Database (ProQuest)</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>Environmental Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering collection</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>SIRS Editorial</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><jtitle>Agronomy journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rajan, Nithya</au><au>Maas, Stephan J</au><au>Kathilankal, James C</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimating Crop Water Use of Cotton in the Texas High Plains</atitle><jtitle>Agronomy journal</jtitle><date>2010-11</date><risdate>2010</risdate><volume>102</volume><issue>6</issue><spage>1641</spage><epage>1651</epage><pages>1641-1651</pages><issn>0002-1962</issn><issn>1435-0645</issn><eissn>1435-0645</eissn><coden>AGJOAT</coden><abstract>The growth and yield of cotton (Gossypium hirsutum L.) in the semiarid Texas High Plains is driven by the amount of water available to the crop through rainfall and irrigation. Various methods have been developed for quantifying the crop water use (CWU) of agricultural crops. In this study, we described a method for estimating CWU that uses a modified version of the Penman–Monteith Equation. In this method, CWU is equal to the transpiration of a well-watered crop with complete ground cover (determined from ambient environmental conditions) multiplied by the amount of plant canopy present (quantified by crop ground cover) and a parameter (Fs ) related to the effects of stomatal closure. For irrigated and dryland cotton that are acclimated to their respective environments, Fs ≈ 1. This suggests that control of canopy leaf area is a primary mechanism for acclimating to the surrounding environment. When Fs < 1, the plant is not acclimated with its environment and must rely on stomatal closure to conserve available water in the root zone. The method was developed using surface energy balance data and remotely sensed crop ground cover for three fields near Lubbock, TX. This method could be used in irrigation scheduling where irrigation is used to replace the daily CWU of a crop. This approach might be superior to the standard crop coefficient approach because it could use remotely sensed crop ground cover as a “spectral crop coefficient” that would make the resulting estimates of CWU specific to individual fields.</abstract><cop>Madison</cop><pub>American Society of Agronomy</pub><doi>10.2134/agronj2010.0076</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | acclimation Agronomy. Soil science and plant productions Biological and medical sciences canopy cotton crop coefficient crop yield dryland farming energy balance equations estimation Fundamental and applied biological sciences. Psychology Gossypium hirsutum irrigated farming irrigation rates irrigation scheduling mathematical models Penman-Monteith Equation plant-water relations rain remote sensing rhizosphere semiarid zones stomatal conductance stomatal movement transpiration vegetation cover Water use water use efficiency |
| title | Estimating Crop Water Use of Cotton in the Texas High Plains |
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