The Hydrogeological Landscape (HGL) Framework is a landscape-characterisation tool that is used to discern areas of similar physical, hydrogeological, hydrological, chemical and biological properties, referred to as HGL Units. The HGL Framework facilitates prioritisation of natural-resource management investment by identifying current and potential hazards in the landscape. Within prioritised regions, on-ground management actions are tailored for specific Management Areas within individual HGL Units. The HGL Unit boundaries are determined through expert interpretation of spatial and field based datasets, such as climate, landform, geology, regolith, soil, stream network, groundwater flow systems, water quality and vegetation assemblages. The resulting HGL Units are validated by an interdisciplinary team using field assessment and biophysical testing. The use of the HGL Framework for new applications creates opportunities for refinement of the existing methodology and products for end users. This paper uses an application in the Australian Capital Territory as a case study to illustrate two enhanced techniques for the landscape characterisation component of the HGL Framework: use of an unsupervised statistical learning algorithm, Self-Organising Maps (SOM), to further validate HGL Units; and landform modelling to assist in delineation of Management Areas. The combined use of SOM and landform modelling techniques provides statistical support to the existing expert and field-based techniques, ensuring greater rigour and confidence in determination of landscape patterns. This creates a more refined HGL Framework landscape-characterisation tool, facilitating more precise hazard assessment and strategic natural-resource management by end users.

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In Australia, salinity has the potential to affect up to 17million hectares of agricultural and pastoral land. For many degraded sites, biophysical hazards are often poorly understood and consequently poorly managed. Attempts to remediate areas affected by salinity have met with varying degrees of success. The New South Wales (NSW) Office of Environment and Heritage, NSW Department of Primary Industries, University of Canberra and Geoscience Australia have collaborated to develop a biophysical expert-based approach for the assessment and management of salinity within landscapes. The Hydrogeological Landscape (HGL) framework provides a structure for understanding how salinity manifests in the landscape, how differences in salinity are expressed across the landscape and how salinity may best be managed. The HGL framework merges the flow dynamics of the groundwater flow system with the landscape elements of the soil landscape or regolith landform approaches. This is the first approach to specifically address all three manifestations of salinity: land salinity, in-stream salt load and in-stream salt concentration. The HGL framework methodology recognises the interplay between surface and subsurface flow systems, as well as the capacity for water to interact with salt stores in the landscape, and identifies biophysical landscape characteristics (e.g. amount and type of vegetation cover, typical land use practice) that affect these interactions. The HGL framework is an expert system that integrates the spatial variability of landscape characteristics and salinity processes to produce a salinity hazard assessment for any given area.

There are limited datasets which cover the heavy clays found in the Murray floodplain area. To understand the processes associated with the water balance within the Koondrook–Perricoota Forest (KPF), detailed hydraulic and hydrodynamic modelling of the flood inundation patterns and overland flow in the KPF is required. Reliable and accurate soils information is critical for any credible hydrologic or hydrodynamic modelling results. Extensive fieldwork across the entire KPF and detailed laboratory testing of the collected samples was undertaken to produce soils information including: spatial distribution of soil types, soil stratigraphy along the surface and subsurface flowpaths, soil hydraulic properties, soil salinity, and soil organic matter. Soil sampling and soil profile descriptions were undertaken at 26 sites spread across the forest. Deep drilling was done at 12 sites to check the existence of ancestral streams and for salinity profiles; soil hydrology testing to estimate infiltration rates was undertaken at 10 sites. Rapid appraisal methods for soil infiltration were developed for the project. Results were compared to soil pedotransfer functions generated from laboratory results; soil indexes including the dispersibilty index and electrochemical stability index; and typical infiltration and permeability rates inferred from soil texture and structure. The results from this study and the archived soil physical and hydraulic datasets can be used for any detailed hydraulic or hydrodynamic modelling exercise in the Murray floodplain area with similar soil properties.

The New South Wales (NSW) Soil Knowledge Network (SKN) is a group of retired soil specialist volunteers, who strive to promote the importance of soils through knowledge and expertise. The Soil Knowledge Network is unique and represents a new direction in knowledge sharing using the passion of recently retired soil scientists to support new and early career soil scientists. The terms 'legacy science' and 'sharing legacy knowledge' are used here to describe SKN activities. This paper reflects on the progress of the SKN and assesses its positive impact on raising the awareness and understanding of soils using qualitative examples from workshops, a survey of soil team coaches at the 2018 National soil judging competition, and metrics from social media and online resources. SKN successes and learning experiences are discussed along with notions of trust, credibility and the importance of people in delivering positive outcomes.