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dc.creatorJat, Deepak Kumaren_US
dc.date.accessioned2016-02-01T21:30:05Z
dc.date.available2016-02-01T21:30:05Z
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/2UIYXIBBen_US
dc.identifier.citationDeepak Kumar Jat. (31/12/2015). M. Sc. thesis on improving water productivity in IGNP stage-I.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/3556
dc.description.abstractAn experiment entitled “Evaluation of water productivity for improved soil and water management at the scheme scale using CropSyst model” was carried out at village Menawali, Hanumangarh, Rajasthan, during kharif and rabi season of 2013-14. After calibration of the CropSyst model for kharif and rabi season crops (cotton, clusterbean,wheat, barley and mustard) in 2012-13. The calibrated model was validated during 2013-14 for the site conditions using the crop model parameter values calibrated as mentioned years with associated water management. Soil characteristics, initial conditions of available soil water, nitrogen and organic matter and daily weather data were model input data for CropSyst as observed in the experiment. Model evaluation and validation was conventionally made by comparing simulation outputs with observed and simulated data. The CropSyst model was validated using the field experiment data conducted in 2013-14 growing season. It was validated for aboveground biomass (AGB), grain yield, N-uptake and green area index (GAI) of each crops were collected from 15 farmers. Bt–cotton and clusterbean of kharif and wheat and Indian mustard in rabi were prominent crops; cotton–wheat, cotton–mustard, clusterbean–wheat and clusterbean–mustard were major cropping sequences of the study region. In kharif season, Bt-cotton gave higher economic and biomass yields than clusterbean and amongst rabi season crops, wheat produced higher economic and biomass yields than barley and mustard. The economic yield of cropping sequences were higher for cotton wheat (6390 kg ha-1) and lower for clusterbean–mustard (3548 kg ha-1) and cotton–mustard (4148 kg ha-1). Clusterbean-mustard cropping system recorded highest water productivity (20.2 kg ha-1 mm) followed by clusterbean-wheat (18.5 kg ha-1 mm). The clusterbean-mustard cropping sequence was most profitable ( 178 ha-1mm) and fetched highest net return followed by cotton-mustard ( 146 ha-1mm). The CropSyst model simulates and validates the biomass and grain yield reasonably well for cotton, clusterbean, wheat, mustard and barley. The model underestimated the biomass and grain yield of clusterbean, mustard and grain yield of wheat while overestimated cotton, barley and biomass yield of wheat. The results suggested that cotton based cropping system were more profitable and clusterbean based cropping system were more water productive than other cropping system. * Post Graduate Scholar, Department of Agronomy, College of Agriculture, Swami Keshwanand Rajasthan Agricultural University, Bikaner ** Professor, Agronomy, Swami Keshwanand Rajasthan Agricultural University, Bikaner.en_US
dc.formatZIPen_US
dc.languageenen_US
dc.rightsCC-BY-NC-4.0en_US
dc.subjectmodelingen_US
dc.titleM.Sc. thesis on improving water productivity in IGNP stage-Ien_US
dc.typeThesisen_US
dcterms.available2015-12-31en_US
cg.subject.agrovocagricultureen_US
cg.subject.agrovocwater productivityen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerSwami Keshwanand Rajasthan Agricultural University - SKRAUen_US
cg.contributor.crpCRP on Dryland Systems - DSen_US
cg.contributor.funderIndian Council of Agricultural Research - ICARen_US
cg.contributor.projectIndia 2010/11 Collaborative Program: Small Ruminants' Productivity and Integrating Crop-livestock System and Rangeland Managementen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.regionSouthern Asiaen_US
cg.coverage.countryINen_US
cg.coverage.start-date2014-01-01en_US
cg.coverage.end-date2015-12-31en_US
cg.contactjatdeepak62@yahoo.comen_US
dc.identifier.statusOpen accessen_US
mel.project.openhttps://mel.cgiar.org/projects/24en_US
mel.sub-typeManuscript-unpublisheden_US


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