Boston University Libraries OpenBU
    JavaScript is disabled for your browser. Some features of this site may not work without it.
    View Item 
    •   OpenBU
    • Theses & Dissertations
    • Boston University Theses & Dissertations
    • View Item
    •   OpenBU
    • Theses & Dissertations
    • Boston University Theses & Dissertations
    • View Item

    Using satellite remote sensing and hydrologic modeling to improve understanding of crop management and agricultural water use at regional to global scales.

    Thumbnail
    Date Issued
    2013
    Author(s)
    Salmon, Jessica Meghan
    Share to FacebookShare to TwitterShare by Email
    Export Citation
    Download to BibTex
    Download to EndNote/RefMan (RIS)
    Metadata
    Show full item record
    Permanent Link
    https://hdl.handle.net/2144/11040
    Abstract
    Croplands are essential to human welfare. In the coming decades , croplands will experience substantial stress from climate change, population growth, changing diets, urban expansion, and increased demand for biofuels. Food security in many parts of the world therefore requires informed crop management and adaptation strategies. In this dissertation, I explore two key dimensions of crop management with significant potential to improve adaptation pathways: irrigation and crop calendars. Irrigation, which is widely used to boost crop yields, is a key strategy for adapting to changes in drought frequency and duration. However, irrigation competes with household, industrial, and environmental needs for freshwa t er r esources. Accurate information regarding irrigation patterns is therefore required to develop strategies that reduce unsustainable water use. To address this need, I fused information from remote sensing, climate datasets, and crop inventories to develop a new global database of rain-fed, irrigated, and paddy croplands. This database describes global agricultural water management with good realism and at higher spatial resolution than existing maps. Crop calendar management helps farmers to limit crop damage from heat and moisture stress. However, global crop calendar information currently lacks spatial and temporal detail. In the second part of my dissertation I used remote sensing to characterize global cropping patterns annually, from 2001-2010, at 0.08 degree spatial resolution. Comparison of this new dataset with existing sources of crop calendar data indicates that remote sensing is able to correct substantial deficiencies in available data sources. More importantly, the database provides previously unavailable information related to year-to-year variability in cropping patterns. Asia, home to roughly one half of the Earth's population, is expected to experience significant food insecurity in coming decades. In the final part of my dissertation, I used a water balance model in combination with the data sets described above to characterize the sensitivity of agricultural water use in Asia to crop management. Results indicate that water use in Asia depends strongly on both irrigation and crop management, and that previous studies underestimate agricultural water use in this region. These results support policy development focused on improving the resilience of agricultural systems in Asia.
    Description
    Thesis (Ph. D.)--Boston University
    Collections
    • Boston University Theses & Dissertations [6746]


    Boston University
    Contact Us | Send Feedback | Help
     

     

    Browse

    All of OpenBUCommunities & CollectionsIssue DateAuthorsTitlesSubjectsThis CollectionIssue DateAuthorsTitlesSubjects

    Deposit Materials

    LoginNon-BU Registration

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Boston University
    Contact Us | Send Feedback | Help