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dc.contributorAwan, Usmanen_US
dc.contributorCheema, Muhammad Jehanzeben_US
dc.contributorAhmad, Ishfaqen_US
dc.contributorAhmad, Matloben_US
dc.contributorAli, Sikandaren_US
dc.contributorShah, Syed Hamiden_US
dc.contributorBakhsh, Allahen_US
dc.contributorIqbal, Muhammaden_US
dc.creatorMohsin Waqas, Muhammaden_US
dc.date2019-07-01en_US
dc.date.accessioned2020-02-15T22:01:10Z
dc.date.available2020-02-15T22:01:10Z
dc.identifierhttps://mel.cgiar.org/dspace/limiteden_US
dc.identifier.citationMuhammad Mohsin Waqas, Usman Awan, Muhammad Jehanzeb Cheema, Ishfaq Ahmad, Matlob Ahmad, Sikandar Ali, Syed Hamid Shah, Allah Bakhsh, Muhammad Iqbal. (1/7/2019). Estimation of Canal Water Deficit Using Satellite Remote Sensing and GIS: A Case Study in Lower Chenab Canal System. Journal of the Indian Society of Remote Sensing, 47 (7), pp. 1153-1162.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/10735
dc.description.abstractThe timely precise information of land use land cover (LULC) in the canal command area can help in managing irrigation water according to the crop water requirement. A study was conducted to map the LULC of irrigated command area of three distributaries in the lower Chenab canal system, Pakistan, namely Mungi, Killianwala and Khurrianwala for the estimation of canal water deficit (CWD). Multispectral images of LANDSAT-7 were used for Rabi season of 2009–2010 and 2010–2011. Normalized difference vegetation index-based unsupervised classification was performed for the formation of LULC of the commands area. During the initial classification, totally nine clusters were created with maximum likelihood. These clusters were then merged into final four classes on the basis of field knowledge. Accuracy assessment was performed using error matrix; producer and user accuracies were estimated for each class with overall accuracy of 84% and 86% for the Rabi season 2009–2010 and 2010–2011, respectively. For the assessment of the irrigation water demand, potential evapotranspiration was estimated using the Penman–Monteith equation. Crop water requirement was estimated based on the 10-day Kc value of the mapped crop from the LULC. Irrigation water demand for cropped area was estimated from the LULC and crop evapotranspiration. Canal water deficit was estimated from the available canal water supply and irrigation water requirement in the Rabi season. During the Rabi seasons, average CWD was 64%, 72% and 32% (2009–2010) and 33%, 46% and 36% (2010–2011) for Khurrianwala, Killianwala and Mungi distributary, respectively.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherSpringer Verlag (Germany)en_US
dc.rightsCC-BY-NC-4.0en_US
dc.sourceJournal of the Indian Society of Remote Sensing;47,(2019) Pagination 1153,1162en_US
dc.subjectland use land coveren_US
dc.subjectirrigation water demanden_US
dc.subjectcanal water deficiten_US
dc.subjectremote sensing and gisen_US
dc.titleEstimation of Canal Water Deficit Using Satellite Remote Sensing and GIS: A Case Study in Lower Chenab Canal Systemen_US
dc.typeJournal Articleen_US
cg.creator.idAwan, Usman: 0000-0001-8663-5688en_US
cg.creator.ID-typeORCIDen_US
cg.subject.agrovoclandsaten_US
cg.contributor.centerKhawaja Fareed University of Engineering and Information Technology - KFUEITen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerUniversity of Agriculture, Faisalabad - UAFen_US
cg.contributor.centerGhazi University, Faculty of Agricultural Sciences - GU - FoASen_US
cg.contributor.funderInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.projectCommunication and Documentation Information Services (CODIS)en_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.date.embargo-end-dateTimelessen_US
cg.coverage.regionSouthern Asiaen_US
cg.coverage.countryINen_US
cg.contactmohsin.waqas@kfueit.edu.pken_US
cg.identifier.doihttps://dx.doi.org/10.1007/s12524-019-00977-9en_US
dc.identifier.statusTimeless limited accessen_US
mel.impact-factor0.869en_US


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