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  • Inland sulfidic soils have recently formed throughout wetlands of the Murray River floodplain associated with increased salinity and river regulation (Lamontagne et al., 2006). Sulfides have the potential to cause widespread environmental degradation both within sulfidic soils and down stream depending on the amount of carbonate available to neutralise acidity (Dent, 1986). Sulfate reduction is facilitated by organic carbon decomposition, however, little is known about the sources of sedimentary organic carbon and carbonate or the process of sulfide accumulation within inland sulfidic wetlands. This investigation uses stable isotopes from organic carbon (13C and 15N), inorganic sulfur (34S) and carbonate (13C and 18O) to elucidate the sources and cycling of sulfur and carbon within sulfidic soils of the Loveday Disposal Basin.

  • How much easier it would be to map and quantify the key elements of the hydrological cycle if the Earth's surface was transparent! Unfortunately, this is not the case and it is this very inability to penetrate to sufficient depths to map and quantify groundwater components of the hydrological cycle that currently necessitates the integration of satellite- airborne- and ground observations. In Australia, important advances have been made in the last 3 years in quantifying key elements of the hydrological cycle. This has been achieved in part through the increased use of Landsat, MODIS, SPOT, hyperspectral, NOAA and LiDAR datasets to improve the mapping and quantification of surface water, evapotranspiration, soil moisture and recharge and discharge. However, significant limitations remain in using satellite-based platforms alone for quantifying catchment water balances, surface-groundwater interactions, groundwater resource estimation and managing groundwater dependent ecosystems. Increasingly, the need to map the key elements of the hydrological cycle to calibrate water balance models and for environmental management, is leading to the development of more holistic systems approaches, involving the integration of satellite-, airborne and ground-based techniques and measurements. One example is in the River Murray Corridor (RMC) in SE Australia, where previous attempts to assess the water needs for iconic floodplain wetland ecosystems, based largely on satellite-based measurements, did not adequately take into account sub-surface soil conditions and groundwater quality and processes. In floodplain environments such as the River Murray Floodplain, the factors that govern tree health are invariably complex, and include a wide range of biophysical and biogeochemical factors.

  • In many areas of the world, vegetation dynamics in semi-arid floodplain environments have been seriously impacted by increased river regulation and groundwater use. In this study, the condition of two of Australia's iconic riparian and floodplain vegetation elements, River Red Gums (Eucalyptus camaldulensis) and Black Box (E. largiflorens) are examined in relation to differing hydraulic regimes. With increases in regulation along Murray-Darling Basin rivers, flood volume, seasonality and frequency have changed which has in turn affected the condition and distribution of vegetation. Rather than undertaking a field based assessment of tree health in response to current water regimes, this paper documents a remote sensing study that assessed historic response of vegetation to a range of different climatic and hydraulic regimes at a floodplain scale. This methodology innovatively combined high-resolution vegetation structural mapping derived from LiDAR data (Canopy Digital Elevation Model and Foliage Projected Cover) with 23 years of Landsat time-series data. Statistical summaries of Normalised Difference Vegetation Index values were generated for each spatially continuous vegetation structural class (e.g. stand of closed forest) for each Landsat scene. Consequently long-term temporal change in vegetation condition was assessed against different water regimes (drought, local rainfall, river bank full, overbank flow, and lake filling). Results provide insight into vegetation response to different water sources and overall water availability. Additionally, some inferences can be made about lag times associated with vegetation response and the duration of the response once water availability has declined (e.g. after floodwaters recede). This methodology should enable water managers to better assess the adequacy of environmental flows.

  • Identification of groundwater-dependent (terrestrial) vegetation, and assessment of the relative importance of different water sources to vegetation dynamics commonly involves detailed ecophysiological studies over a number of seasons or years. However, even when groundwater dependence can be quantified, results are often difficult to upscale beyond the plot scale. Consequently, quicker, more regional mapping approaches have been developed. These new approaches utilise advances in computation geoscience, and remote sensing and airborne geophysical technologies. This study, undertaken in the semi-arid Darling River Floodplain in N.S.W., Australia, combines Landsat Normalised Difference Vegetation Index (NDVI) time series data with hydrogeological, hydrogeochemical and hydrogeophysical data to assess the relative importance of hydrological processes and groundwater characteristics. The first stage in the study combined high-resolution vegetation structural mapping derived from LiDAR data (Canopy Digital Elevation Model and Foliage Projected Cover), with 23 years of Landsat time-series data. Statistical summaries of Normalised Difference Vegetation Index values were generated for each spatially continuous vegetation structural class for each Landsat scene (e.g. stand of closed forest). This has enabled long-term temporal changes in vegetation condition to be assessed against different water regimes (drought, local rainfall, river bank full, overbank flow, and lake filling), and groundwater dependent vegetation to be identified. The second stage involved integration with airborne electromagnetics (AEM), hydrogeology and hydrogeochemistry. This has shown that the deeper (>25m), semi-confined aquifer is only rarely important to vegetation dynamics, with the shallow unconfined aquifer and river lateral bank recharge zones being of greater importance.

  • Identification of groundwater-dependent (terrestrial) vegetation, and assessment of the relative importance of different water sources to vegetation dynamics commonly involves detailed ecophysiological studies over a number of seasons or years. However, even when groundwater dependence can be quantified, results are often difficult to upscale beyond the plot scale. Consequently, quicker, more regional mapping approaches have been developed. These new approaches utilise advances in computation geoscience, and remote sensing and airborne geophysical technologies. The Darling River Floodplain, western New South Wales, Australia, was selected as the case study area. This semi-arid landscape is subject to long periods of drought followed by extensive flooding. Despite the episodic availability of surface water resources, two native Eucalyptus species, E. camaldulensis (River Red Gum) and E. largiflorens (Black Box) continue to survive in these conditions. Both species have recognised adaptations, include the ability to utilise groundwater resources at depth. A remote sensing methodology was developed to identify those communities potentially dependent on groundwater resources during the recent millennium drought in Australia.

  • Fresh groundwater resources are a highly valuable commodity, particularly in semi-arid to arid landscapes where annual precipitation is low and surface water is scarce. Water security, often achieved through the development of groundwater resources, is a high priority for rural communities within these water-limited landscapes. However this is often at the expense of the environment when alterations to the groundwater system, often in conjunction with drought conditions, can detrimentally impact floodplain and riparian vegetation structure and function. Remote-sensing methods can be used to detect such changes in vegetation. In this study, a multi-temporal Landsat Normalised Difference Vegetation Index (NDVI) approach was used to detect changes in riparian and floodplain vegetation in the Lower-Darling floodplain, NSW, Australia. When integrated with surface and subsurface data, these changes provided insight into how surface water availability and subsurface geological and hydrogeological characteristics influenced vegetation distribution and behaviour at multiple scales. It was found that while the availability of water resources was the primary driver of changes in vegetation canopy dynamics, this availability was strongly influenced by both tectonic and hydrogeological processes. These findings were of particular importance when considering the suitability of groundwater development options and they have implications for future groundwater assessment studies.

  • Geoscience Australia (GA) was invited by Murray-Darling Basin Authority (MDBA) in 2010 to participate in an evaluation of the Intermap IFSAR (Interferometric Synthetic Aperture RADAR) data that was acquired as part of the Murray-Darling Basin Information Infrastructure Project Stage 1 (MDBIIP1) in 2009. This evaluation will feed into the business case for Stage 2 of the project. As part of the evaluation GA undertook the following: 1. A comparison of the IFSAR Digital Surface Model (DSM) and Digital Terrain Model (DTM) with a recent LiDAR acquisition, covering approximately 9000Km2 of the Lower Darling Region. It focused on assessment of the data over various land cover and terrain types and identified opportunities and issues with integrating IFSAR with LiDAR. 2. A comparison of the IFSAR Vegetation Canopy Surface (DSM minus DTM) with the Lower Darling LiDAR Canopy Elevation Model (CEM). 3. A comparison between currently mapped man-made and natural water bodies over the Murray-Darling Basin with the IFSAR derived products (water mask). 4. Application of the National Catchment Boundaries (NCBs) methodology to the IFSAR data and comparison with the delineated watersheds from PBS&J (Intermap's sub-contractor). This report outlines the findings of this evaluation based on the 4 items above MDBA requested.

  • The Integrated Vegetation Cover (2003), hereafter referred to as the IVC03 dataset represents vegetation cover across Australia and was compiled by integrating a number of recent vegetation-related datasets.This dataset was developed to assess and report on the type and extent of native, non-native and non-vegetated cover types across the whole landscape. This dataset has been used to describe vegetation types found in each National Action Plan and Natural Heritage Trust regions across Australia. Data are stored as a raster of 100m resolution and are projected in Albers conic equal-area coordinates.Version 1 incorporates a selection of the latest available vegetation data as at July 2003.Vegetation cover in the IVC03 dataset is described using a 12-class attribute schema that was developed to meet vegetation-related information needs of the Commonwealth Government natural resource management arena.The IVC03 dataset has 12 attribute classes:1Native forests and woodlands 2Native shrublands and heathlands 3Native grasslands and minimally modified pastures4Horticultural trees and shrubs5Perennial crops6Annual crops and highly modified pastures7Plantation (hardwood)8Plantation (softwood/mixed)9Bare10Ephemeral and Permanent Water Features11Built-up99Unknown/not reportable. Five datasets were used as inputs to create the IVC03 dataset.A national ruleset was developed to assign orders of precedence to each attribute value from each input dataset.The ruleset was used to integrate the inputs into a single vegetation cover dataset. The five input datasets were:-Agricultural Land Cover Change (ALCC95);-Forests of Australia 2003 (FOA03);-1996/97 Land Use of Australia, Version 2 (LUA97);-Land Use Mapping at the Catchment Scale (LUMCS03); and-National Vegetation Information System 2000 (NVIS00).

  • The Sustainable Management of Coastal Groundwater Resources Project was co-funded by the Raising National Water Standards Program, which supports the implementation of the National Water Initiative Program. The project was led by GHD Hassall, in consultation with Kempsey Shire Council, Geoscience Australia, NSW Department of Environment, Climate Change and Water, and Ecoseal Developments Pty. Ltd. The project aimed to improve the management of groundwater in coastal dune aquifers, undertaking a case study of the Hat Head National Park region on the Mid North Coast of New South Wales. Due to increasing pressures on groundwater resources from expanding urbanisation and tourism in this region, the sustainable management of the existing groundwater resources is of vital importance. There are many potential risks associated with extraction of groundwater resources including acidification of soils, seawater intrusion and increased salinity levels, and detrimental impacts on groundwater dependent ecosystems (GDEs). This final report documents all of the work undertaken by Geoscience Australia relating to Groundwater Dependent Ecosystems, or more specifically groundwater dependent terrestrial vegetation. Groundwater dependent ecosystems (GDEs) are naturally occurring ecosystems that require access to groundwater to meet all or some of their water requirements so as to maintain their communities of plants and animals, ecological processes and ecosystems services. Often the natural water regime of GDEs will comprise one or more of groundwater, surface water and soil moisture.

  • National vegetation cover derived from: - Values 1, 7, and 8 from the 2007 forests dataset (BRS) - Values 2 and 3 from the NVIS 3.1 dataset (ERIN) - Values 1-6 and 9-11 from the catchment scale land use dataset (as at April 2009, BRS) - Any remaining no data areas filled from the Integrated Vegetation 2008 dataset (BRS) The datasets were resampled to 100 metre grids and projected to Albers equal area if required. The integrated vegetation grid was derived using a conditional statement weighing each input grid in the order listed above. Bureau of Rural Sciences, Canberra are custodians of the dataset.