A Geoinformatics Approach for Spatial Water Accounting and Irrigation Demand Forecasting for a Gravity Irrigation System

Muhammad Kaleem Ullah

    Research output: ThesisDoctoral Thesis

    72 Downloads (Pure)

    Abstract

    Water scarcity is rapidly becoming a critical global issue, and water demand already exceeds area was mapped using Landsat 5 TM satellite images by applying a simplified hybrid classification approach mainly based on a supervised classification algorithm. The SEBAL model was used to map spatial daily ETa from 18 Landsat 5 TM satellite images covering various parts of the cropping season in summer 2008-09 and 2009-10. For 2008-09, the seasonal ETa values ranged from 20 mm to 1,705 mm, and for 2009-10 the seasonal ETa was 13 mm to 1,645 mm. Overall, it was found that the remote sensing based energy balance algorithm coupled with ground data can be an efficient and reliable method for estimation of evapotranspiration at different spatio-temporal scales. Water accounting and productivity analysis of three commonly used indicators shows wide variation across the 22 nodes as well as at the system level in the CIA. Results show that a large amount of water is lost through non-process depletion (80% of available water) rather than process depletion (20% of available water) in both seasons at the system level. Most of the non-process depletion is from native vegetation, dry grass, fallow fields and bare soil as a result of rainfall stored in the root zone.
    Original languageEnglish
    QualificationDoctor of Philosophy
    Awarding Institution
    • Charles Sturt University
    Supervisors/Advisors
    • Hafeez, Muhammad, Principal Supervisor
    Award date01 Jun 2011
    Place of PublicationAustralia
    Publisher
    Publication statusPublished - 2011

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