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.

In many areas of the world, vegetation dynamics in semi-arid floodplain environments have been seriously impacted by increased river regulation and groundwater use. With increases in regulation along many rivers in the Murray-Darling Basin, flood volume, seasonality and frequency have changed which has in turn affected the condition and distribution of vegetation. Floodplain vegetation can be degraded from both too much and too little water due to regulation. Over-regulation and increased use of groundwater in these landscapes can exacerbate the effects related to natural climate variability. Prolonged flooding of woody plants has been found to induce a number of physiological disturbances such as early stomatal closure and inhibition of photosynthesis. However, drought conditions can also result in leaf biomass reduction and sapwood area decline. Depending on the species, different inundation and drought tolerances are observed. Identification of groundwater-dependent terrestrial vegetation, and assessment of the relative importance of different water sources to vegetation dynamics, typically requires detailed ecophysiological studies over a number of seasons or years as shown in Chowilla, New South Wales [] and Swan Coastal Plain, Western Australia []. However, even when groundwater dependence can be quantified, results are often difficult to upscale beyond the plot scale. Quicker, more regional approaches to mapping groundwater-dependent vegetation have consequently evolved with technological advancements in remote sensing techniques. Such an approach was used in this study. LiDAR canopy digital elevation model (CDEM) and foliage projected cover (FPC) data were combined with Landsat imagery in order to characterise the spatial and temporal behaviour of woody vegetation in the Lower Darling Floodplain, New South Wales. The multi-temporal dynamics of the woody vegetation were then compared to the estimated availability of different water sources in order to better understand water requirements.

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.

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.

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).

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.

This compilation data release is a selection of remotely sensed imagery used in the Exploring for the Future (EFTF) East Kimberley Groundwater Project. Datasets include: • Mosaic 5 m digital elevation model (DEM) with shaded relief • Normalised Difference Vegetation Index (NDVI) percentiles • Tasselled Cap exceedance summaries • Normalised Difference Moisture Index (NDMI) • Normalised Difference Wetness Index (NDWI) The 5m spatial resolution digital elevation model with associated shaded relief image were derived from the East Kimberley 2017 LiDAR survey (Geoscience Australia, 2019b). The Normalised Difference Vegetation Index (NDVI) percentiles include 20th, 50th, and 80th for dry seasons (April to October) 1987 to 2018 and were derived from the Landsat 5,7 and 8 data stored in Digital Earth Australia (see Geoscience Australia, 2019a). Tasselled Cap Exceedance Summary include brightness, greenness and wetness as a composite image and were also derived from the Landsat data. These surface reflectance products can be used to highlight vegetation characteristics such as wetness and greenness, and land cover. The Normalised Difference Moisture Index (NDMI) and Normalised Difference Water Index (NDWI) were derived from the Sentinel-2 satellite imagery. These datasets have been classified and visually enhanced to detect vegetation moisture stress or water-logging and show distribution of moisture. For example, positive NDWI values indicate waterlogged areas while waterbodies typically correspond with values greater than 0.2. Waterlogged areas also correspond to NDMI values of 0.2 to 0.4. Geoscience Australia, 2019a. Earth Observation Archive. Geoscience Australia, Canberra. http://dx.doi.org/10.4225/25/57D9DCA3910CD Geoscience Australia, 2019b. Kimberley East - LiDAR data. Geoscience Australia, Canberra. C7FDA017-80B2-4F98-8147-4D3E4DF595A2 https://pid.geoscience.gov.au/dataset/ga/129985

Two vegetation maps (sold separately) - Natural Vegetation (1788) and Post-European Vegetation (1988) reconstruct Australia`s vegetation in the 1780s and the mid-1980s. Areas over 30 000 hectares are shown, plus small areas of significant vegetation such as rainforest. Attribute information includes: growth form of tallest and lower stratum, foliage cover of tallest stratum and dominant floristic types. Data was captured from 1:5 million source material. These maps are also available as free vector GIS data. Product Specifications Coverage: Australia Currency: Compiled mid-1980s Coordinates: Geographical Datum: AGD66 Projection: Simple Conic on two standard parallels 18S and 36S Medium: Printed map (flat and folded); Data - Free online and CD-ROM (fee applies) Forward Program: Under review

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.

Identification of groundwater-dependent terrestrial vegetation, and assessment of the relative importance of different water sources to vegetation dynamics, typically requires 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. Quicker, more regional approaches to mapping groundwater-dependent vegetation have consequently evolved with technological advancements in remote sensing techniques. These approaches however often fail to incorporate sub-surface hydrogeological processes in their interpretation of groundwater dependence. This study, undertaken in the semi-arid Darling River Floodplain in NSW, Australia, innovatively 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. Central to the approach is the use of airborne electromagnetics which provides a 3-dimensional context to otherwise point-based borehole data. This approach has resulted in an improved understanding of vegetation dynamics including the spatial distribution of vegetation utilising groundwater, timing and duration of groundwater use, and response to different hydrologic regimes (e.g. rainfall, lateral bank recharge, and overbank flooding). In particular, the study has established that the deeper (>25m), semi-confined aquifer is only rarely important to vegetation dynamics, with the shallow unconfined aquifer and river flush zones being of greater importance. These findings are being used to assess the suitability of proposed groundwater-development schemes in the study area, and have implications for riparian vegetation management more broadly.