Earth observation remote sensing

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Sims, Neil; Anstee, Janet; Barron, Olga; Botha, Hannelie; Lehmann, Eric; Li, Lingtao; McVicar, Tim; Paget, Matt; Ticehurst, Catherine; Van Niel, Tom; Warren, Garth

Sims, Neil; Anstee, Janet; Barron, Olga; Botha, Hannelie; Lehmann, Eric; Li, Lingtao; McVicar, Tim; Paget, Matt; Ticehurst, Catherine; Van Niel, Tom; Warren, Garth


2018-07-31


Report


75


This report presents the outcomes of the Northern Australia Water Resources Assessment (the Assessment) Earth observation activity. The objectives of this activity are to develop, update and improve spatial data products for the Fitzroy, Darwin and Mitchell catchments, primarily for use in other activities in the Assessment. This activity used satellite remote sensing datasets to address four main mapping tasks: 1. The frequency and distribution of flood inundation. 2. The distribution and persistence of waterhole inundation. 3. Waterhole water quality, including suspended solids. 4. The extent and water use requirements of riparian vegetation. The flood inundation task produced maps of the distribution, frequency and duration of surface water between 1988 and December 2015. This work compares inundation maps from a range of sensors and sources to provide new information about the recent hydrological character of these catchments. These maps have broad utility including to validate hydrological models in the surface water modelling activity. The waterhole persistence task compares Landsat observations throughout the dry season to show the pattern of water retention. Water persistence influences the ecological character of waterholes, and can indicate their sensitivity to water resource development impacts. The waterhole water quality assessment uses a physics-based model to retrieve water quality parameters from selected waterholes. The persistence and water quality information may be used to aid the interpretation of waterhole groundwater connectivity in subsequent analyses. The riparian vegetation assessment identifies areas of persistent greenness in the landscape. A range of additional information about the climate and underlying geology (etc.) are then used to separate areas reliant on groundwater access from those drawing on soil water. This report presents a proof-of-concept for these analyses including detailed methods, descriptions of the datasets and, in some cases, their implications for improving the understanding of the catchments. The accuracy of these analyses is limited by a range of factors associated with the spatial resolution of the image data, landcover variability in the assessment areas, the scale of the features of interest and the timing of image capture. In particular, neither the Landsat nor Moderate Resolution Imaging Spectrometer (MODIS) sensors can visually penetrate cloud cover, which means that these analyses have primarily occurred during the dry season between May and October each year. Subsequent assessments should strive to make greater use of the Australian Geoscience Data Cube and to exploit recent developments in radar datasets which can see through clouds and may provide more information and the distribution of water resources in the wet season.


CSIRO


Australia


Northern Australia Water Resource Assessment; NAWRA


Environmental Management


Published Version (pdf) (3.65MB)

Published Version (pdf) (25.74MB)


https://doi.org/10.25919/5b86edb95a4de


This report has been placed on the CSIRO repository and may be made available to persons outside of CSIRO for non commercial purposes, in its entirety and without deletion of disclaimers and copyright information.


Funding Body NameProject/Grant ID
Australia. Department of Infrastructure, Regional Development and Cities


EP186706


Technical Report (Author)


English


978-1-4863-10


Sims, Neil; Anstee, Janet; Barron, Olga; Botha, Hannelie; Lehmann, Eric; Li, Lingtao; McVicar, Tim; Paget, Matt; Ticehurst, Catherine; Van Niel, Tom; Warren, Garth. Earth observation remote sensing. Australia: CSIRO; 2018. csiro:EP186706. https://doi.org/10.25919/5b86edb95a4de



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