- Title
- Improved water resource management through remote sensing: methods to quantify irrigation water use
- Creator
- Bretreger, David
- Relation
- University of Newcastle Research Higher Degree Thesis
- Resource Type
- thesis
- Date
- 2023
- Description
- Research Doctorate - Doctor of Philosophy (PhD)
- Description
- With a growing global population, there is forecasted growth for the use of water by irrigated agriculture to keep up with food demands. In many remote and isolated locations there is insufficient infrastructure in place to adequately monitor irrigated agricultures water use and the associated environmental impacts of over extraction from water sources (both surface water and groundwater). Although models provide an opportunity to simulate these water fluxes, they are typically based on theoretical growth stages and conditions of crops as well as assumed management practices, which can misrepresent reality. Remote sensing has an opportunity to observe on the actual on-the-ground conditions, combining these with models, allowing improvements to be implemented in water accounting techniques and water management more generally. This thesis developed new methods of using analysis ready data from multi-spectral remote sensing satellites to observe irrigation water use across a range of spatial scales. The various input options are explored, ranging from differing meteorological evapotranspiration and precipitation products that are calculated with different input data or observations from a range of satellite sensor platforms (i.e. Landsat 5, 7 and 8 or Sentinel-2). Multiple remote sensing methodologies were used to calculate crop coefficients (Kc), based on the FAO56 methodology, meaning results are easily compared against tabulated coefficients derived for more conventional use. Methods explored ranged from simple linear NDVI-Kc relationships to more complex non-linear methods using a range of vegetation indices. Irrigation validation data was only available at a monthly time scale and hence simulated irrigation was also on a monthly scale. Subsequent studies in this thesis included soil water deficit modelling which returned better results due to the representation of soil processes and moisture storage potential. Implementing this relies on the availability of in-situ soil measurements or reliable digital soil maps that match the spatial scale being examined which may limits its application in some locations. Finally, the implications of these satellite techniques for quantifying irrigation were explored in the transboundary water sharing context of Australia’s Murray-Darling Basin. Here challenges in compliance and regulation were identified as well as the opportunities for new techniques such as the ones explored in this thesis, and many others, to be part of a comprehensive and transparent water accounting and compliance framework. This is particularly important in water scarce regions globally and in transboundary water management systems as these techniques may allow more transparent water accounting to be undertaken. When this thesis was started, there was very limited literature available on remote sensing methods used to quantify irrigation, although this field of research has expanded considerably since. The work contained in this thesis has contributed to the global field of research of irrigation quantification using remote sensing. The methods developed give a relatively high spatial resolution (10-30 m) of accurate monthly irrigation. There are many methods that have recently been developed, they each demonstrate individual situations that highlight their usefulness meaning in most scenarios there is a method suitable for use.
- Subject
- irrigation; remote sensing; water resources; hydrology; water management; Murray-Darling Basin; thesis by publication
- Identifier
- http://hdl.handle.net/1959.13/1471915
- Identifier
- uon:48743
- Rights
- Copyright 2023 David Bretreger
- Language
- eng
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT01 | Thesis | 23 MB | Adobe Acrobat PDF | View Details Download | ||
| View Details Download | ATTACHMENT02 | Abstract | 203 KB | Adobe Acrobat PDF | View Details Download |