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dc.contributor.advisorDennis B. McLaughlin.en_US
dc.contributor.authorSmith, Tizianaen_US
dc.contributor.otherTechnology and Policy Program.en_US
dc.coverage.spatiala-cc---en_US
dc.date.accessioned2016-09-13T19:07:43Z
dc.date.available2016-09-13T19:07:43Z
dc.date.copyright2016en_US
dc.date.issued2016en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/104166
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2016.en_US
dc.descriptionThesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, Institute for Data, Systems, and Society, Technology and Policy Program, 2016.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 95-99).en_US
dc.description.abstractCrop production has significantly altered the terrestrial environment by changing land use (Ramankutty et al., 2008) and by altering the water cycle through both co-opting rainfall and surface water withdrawals (Postel et al., 1996). As the world's population continues to grow and individual diets become more resource-intensive, the demand for food - and the land and water necessary to produce it - will continue to increase. Quantitative data about water availability, water use, and agricultural land use are needed to develop sustainable water and agricultural planning and policies. However, existing large-scale data are susceptible to errors and can be physically inconsistent. China is an example of a large area where food demand is expected to increase and a lack of data clouds the resource management dialogue. Some assert that China will have insufficient land and water resources to feed itself, posing a threat to global food security if they seek to increase food imports (Brown and Starke, 1995). Others believe resources are plentiful (Lomborg, 2001). Without quantitative data, it is difficult to discern if these concerns are realistic or overly dramatized. This thesis presents a quantitative approach to characterize hydrologic fluxes, crop water use, and agricultural land use and applies the methodology in China using data from around the year 2000. The approach uses the principles of water balance and of crop water requirements to assimilate existing data with a least-squares estimation technique, producing new estimates of water and land use variables that are physically consistent while minimizing differences from measured data. We argue that this technique for estimating water fluxes and agricultural land use can provide a useful basis for resource management and policy, both in China and around the world.en_US
dc.description.statementofresponsibilityby Tiziana Smith.en_US
dc.format.extent99 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectCivil and Environmental Engineering.en_US
dc.subjectInstitute for Data, Systems, and Society.en_US
dc.subjectEngineering Systems Division.en_US
dc.subjectTechnology and Policy Program.en_US
dc.titleEstimating hydrologic fluxes, crop water use, and agricultural land use in China from multiple data sourcesen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.description.degreeS.M. in Technology and Policyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineering
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Society
dc.contributor.departmentTechnology and Policy Program
dc.identifier.oclc957527110en_US


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