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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01d504rp368
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dc.contributor.advisorCaudill, Reggie-
dc.contributor.advisorvan Handel, Ramon-
dc.contributor.advisorPorporato, Amilcare-
dc.contributor.authorDong, Zhengyue Anna-
dc.date.accessioned2020-09-30T13:27:32Z-
dc.date.available2020-09-30T13:27:32Z-
dc.date.created2020-05-05-
dc.date.issued2020-09-30-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01d504rp368-
dc.description.abstractIn many regions of the world, irrigation is vital to food security and agricultural productivity. Prudent management of irrigation systems becomes paramount under a probable scenario of rising climatic variability and population growth, which would necessitate increased irrigation. This thesis seeks to extend a mathematical model for irrigation schemes, first introduced by Vico and Porporato, to include the influence of weather forecast data on irrigation schedules. We then propose a novel irrigation strategy which minimizes irrigation volume throughout the growing season using weather forecast information. This thesis employs a life-cycle assessment (LCA) methodology to evaluate the environmental impact of different irrigation strategies. Using LCA, we can include both the upstream and downstream environmental impacts of each irrigation strategy in our analysis. The profitability of each method is examined alongside its environmental impact. Ultimately, we observe that while profitability comes at a cost in terms of environmental impact, an irrigation strategy which incorporates four days of weather forecast data may optimally balance both interests.en_US
dc.format.mimetypeapplication/pdf-
dc.language.isoenen_US
dc.titleAn Environmental Analysis of Irrigation with Optimization and Weather Forecastsen_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2020en_US
pu.departmentOperations Research and Financial Engineeringen_US
pu.pdf.coverpageSeniorThesisCoverPage-
pu.contributor.authorid920082732-
pu.certificateEngineering and Management Systems Programen_US
pu.certificateCenter for Statistics and Machine Learning-
Appears in Collections:Operations Research and Financial Engineering, 2000-2020

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