Geological processes in 3D

Checking the scaling of a Google Earth image before draping the image on a 2D grid of digital elevation data viewed in the earthVision 3D viewer.

This research was first established during the ARC/NWC funded National Centre for Groundwater Research and Training (NCGRT) from 2009-2014, and is now a CWI Flagship Project.

The Connected Waters Initiative (CWI) is investigating how disparate earth science data relating to the hydrogeology of catchments can be integrated into improved frameworks for catchment water balance modelling. These 3D geological models will also lead to better scientific understanding of the processes surrounding coupled surface and ground water interactions. Improved quantification of uncertainty within these models can benefit resource management.

Data can be obtained from many sources including satellite, land and airborne geophysical surveys, geological field mapping and borehole logging. Due to variations in the scale of data collection (including the density of the samples and the volume of the samples), original survey objects and measurement errors, these data sets rarely combine cleanly in 3D space to give a unique interpretation of the hydrogeology.

Subprogram 1A: Linking Geological and Hydrogeological Processes

Regional hydrogeologic data such as hydraulic head and conductivity data are typically of low density. Building conceptual 3D geological models of aquifers therefore requires interpolation of data and the combination of hard data (data collected from bores) with soft data (geophysical surveys). This is best achieved with computer based interactive 3D geological models where multiple data sets can be stored, accessed and visualised. A particular problem encountered in building these models is that, while the current interpolation algorithms for estimating values at non sampled locations honour the geostatistical properties of the data (Renard, 2007), if naively applied, they can lead to serious misinterpretation of the hydrogeology (palaeo river channels running up hill, for example). This research will focus on how to blend geostatistical methods with geological rules.

Research Contributors from UNSW:

  • Chief Investigators - Professor Ian Acworth and Associate Professor Bryce Kelly
  • Post Doctoral Research Fellow

Research goals of this project include:

  • exploring approaches for blending geological rules with geostatistical estimation and uncertainty quantification methods,
  • development of gridding methods that generate realistic erosion surfaces and meandering rivers from sparse data,
  • examining how to best populate lithological and hydrogeological variables between boreholes, to give realistic geological distributions,
  • investigating the impact of aquifer dimension uncertainty on water balance models,
  • determining new approaches to scaling of hydrogeological data, and
  • researching methods of data integration that will constrain the uncertainty in hydrological variables for improved regional water balance models.

Understanding the 3D distribution of aquifer sediment types and their associated hydraulic properties is critical when coupling water chemistry and ecological processes to the movement of water movement through a catchment. 3D modelling will yield improved insights on recharge pathways, groundwater contributions to river baseflow, the impact of irrigation extraction, water quality characterisation and the possibility of examining climatic variability and change on groundwater availability.

Advances in 3D geological modelling software and numerical methods have improved available methods for estimation of physical and chemical properties in space at non-sampled locations,and better quantification of uncertainty in these estimates. These methods can be applied to modelling of a variety of data, including rainfall estimation at non-sampled locations; modelling hydraulic conductivity distribution throughout an aquifer; combining bore data with geophysical survey data; and estimation of aquifer contaminant levels.

Maules Creek 3D Geological Model

Dr. Beatrice Giambastiani (Postdoc Researcher)
A/Professor Bryce Kelly (Supervisor)

Maules Creek has been selected as a demonstration site for a collaboratively funded project by the National Water Commission and the Cotton Catchment Communities CRC to demonstrate the value of 3D geological modelling for improving coupled surface and ground water management.

The Maules Creek catchment is located with the Namoi Catchment Management Area. This region is world renowned for its agricultural production (both dryland and irrigation) and for its coal resources.

A significant aspect of the project is to determine how to best collate the available hydrogeological data, and establish an order of tasks as a template for future projects. The construction of the geological and hydrogeologic flow models requires the use of a combination of software packages including MS Access, ArcGIS and earthVision, FEFLOW and RMA.

The 3D geological models are being constructed from NSW government groundwater monitoring bore data, Geoscience Australia DEM data, and ground survey and water quality information being collected by Professor Ian Acworth, Dr. Martin Andersen, Andrew McCallum, Hamish Studholme and Anna Greve. Further details on the Maules Creek project were presented in Australian Landcare Magazine (March 2008).

Mapping Flood Recharge Zones in the Lower Namoi

Cynthia The (Honours Student)
A/Professor Bryce Kelly (Supervisor)

Flood recharge to aquifers is a significant contribution to the total recharge. However, flood events are relatively rare and the climatic conditions proceeding a flood influence how much water runs off, how much water infiltrates, and how much water migrates downwards to recharge the aquifers. The CWI team are investigating the response of the piezometric surface to historical flood events in the Lower Namoi, and how the changes in head correlate to the climatic conditions preceding the floods and the volume of flood waters. Also being investigated is the relationship between recharge zones indicated by the groundwater head and other groundwater properties like pH, temperature and electrical conductivity.

The work has been sponsored by the Cotton Catchment Communities CRC and is part of a Summer Project and Honours thesis.

Geostatistical Methods for Contaminated Sites

Geostatistical methods provide us with numerical tools to answer important questions about remediating contaminated sites. Questions that can be answered using geostatistical methods include:

  • What is the optimal number of samples required to balance the objectives of minimising sample costs, while reducing the uncertainty in our characterisation of the site and the subsequent risks?
  • What area of soil or water needs to be remediated and what is the uncertainty in the area or volume that exceeds the contaminant threshold limit?
  • Where do I need to sample to reduce the uncertainty in quantifying the distribution of the contaminant?
  • How do you grid data with extreme values?

Methods to answer these questions are well established. The Connected Waters Initiative, as part of its teaching goals, is focused on expanding the base of consultants that apply geostatistical methods for answering the above questions.

3D Geological Models for all Disciplines of the Earth Sciences

Although the focus of the CWI team is on 3D regional hydrogeological models, the methods are appropriate to most areas of the earth sciences where 3D visualisation and characterisation leads to improved understanding of processes, and better communication of complex 3D spatial information to managers and communities. Examples where enhanced knowledge of physical processes and communication of the scientific data benefit from 3D geological models include:

  • 3D mapping groundwater contamination plumes;
  • Modelling of karst terrains in all their spatial complexity;
  • Mapping hydrocarbon traps in petroleum reservoirs;
  • Calculation of coal resources;
  • Defining traps for CO2 storage;
  • 3D ore reserve models;
  • Modelling the distribution of ocean currents.

The possibilities of 3D data analysis are unlimited, so if you have 3D earth science data presentation and analysis problems contact us about collaborative research projects.

Further information: A/Prof Bryce Kelly.

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