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dc.contributor.advisorDennis McLaughlin.en_US
dc.contributor.authorJain Figueroa, Anjuli.en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Civil and Environmental Engineering.en_US
dc.date.accessioned2019-07-22T19:33:37Z
dc.date.available2019-07-22T19:33:37Z
dc.date.copyright2019en_US
dc.date.issued2019en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/121881
dc.descriptionThesis: Ph. D., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2019en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 118-125).en_US
dc.description.abstractEstimates suggest that the world needs a 50% increase in food production to meet the demands of the 2050 global population (Tilman et. al. 2011). Cropland expansion is unlikely to be sufficient, and yield improvements that require more inputs may lead to more environmental damage. This work focuses on reallocating limited land and water resources to optimize cropping patterns. By combining optimization methods, surrogate modeling, global data sources, data assimilation, and hydrologic modeling, we identify opportunities for increasing food-crop production and cash-crop revenue, while maintaining sustainability constraints that limit cropland expansion and prevent groundwater depletion. We apply the framework in India's Krishna river basin and find that reallocating resources to meet or exceed current production can lead to 96% gain in net revenue as resources over an estimated current baseline. Resources in this case are moved to high-yielding cash crops. Imposing a self-sufficient southern diet which depends on rice reduces the gains to 77% while imposing a self-sufficient national diet with more emphasis on wheat eliminates all net revenue gains to the region. The approach described in this thesis, highlights the trade-offs between food production, cost and environmental impacts in achieving specified food-security objectives. This research contributes to the field in two ways: 1) it provides a novel method for combining remotely sensed data, surrogate models and optimization to understand agricultural trade-offs, and 2) it furthers the discussion on food and water security and sustainable resource management by demonstrating that resource reallocation with sustainability constraints provides revenue gains in certain situations.en_US
dc.description.statementofresponsibilityby Anjuli Jain Figueroa.en_US
dc.format.extent125 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectCivil and Environmental Engineering.en_US
dc.titleSustainable agricultural management : a systems approach for examining food security tradeoffsen_US
dc.typeThesisen_US
dc.description.degreePh. D.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineeringen_US
dc.identifier.oclc1102638593en_US
dc.description.collectionPh.D. Massachusetts Institute of Technology, Department of Civil and Environmental Engineeringen_US
dspace.imported2019-07-22T19:33:33Zen_US
mit.thesis.degreeDoctoralen_US
mit.thesis.departmentCivEngen_US


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