With help from colleagues, GMDSI have documented the construction and deployment of a number of models that have been developed to address complex, real-world issues.
GMDSI worked examples differ from GMDSI tutorials. Generally, model input datasets, and programs that were used to write these datasets, are not provided. Instead, our intention was to discuss a real-world problem, and to then demonstrate how numerical simulation was used to harvest problem-pertinent information from local data, and to make predictions on which decisions could rest. Generally, these predictions were accompanied by assessments of their uncertainties. Decision-makers were therefore fully acquainted with information limitations, and hence with decision-affecting risks.
Data processing and uncertainty quantification methodologies that are demonstrated in many of these worked examples are novel. In fact, the contents of two of them were later published in academic journals. Most of the simulator-partner software that was used in worked example development is available through the PEST, PEST++ and PyEMU suites.
Click on a worked example to find out more about it, and to download the worked example report.
Construction of a decision support groundwater model requires that parameters be adjustable, stochastic and representative of geological conditions. This can be difficult to achieve in complex hydrogeological environments where controls on hydraulic properties are both geological and structural in origin.This worked example report demonstrates use of the PLPROC parameter preprocessor
Locating sources of groundwater contamination is an inverse problem on steroids. It is, in fact, two inverse problems. Source locations must be back-calculated from field measurements. The hydraulic properties of aquifer material through which groundwater flows, and contaminants are transported, must also be inferred from these same measurements. Another spice
Management of coastal aquifers is unforgiving. If too much fresh water is extracted, salt water takes its place. Depending on the location, measurements of historical system behaviour may be scarce or plentiful. However assimilation of these data using a numerical model that attempts to simulate salt water intrusion is nearly
For this worked example, we rebuild an old USGS model. The focus of the original model was protection of water supply wells that serve a small town in New Hampshire. Those who built the original model did a good job – given the technology that was available at the time.
Simultaneous fitting of drawdowns induced by pumping at multiple sites in an area of complex geology revealed important patterns of connected permeability Over a six month period in July 2014, BHP conducted six pumping tests of between 5 and 11 days duration near the site of its OB31 pit in
Any groundwater model is riddled with imperfections. Do these compromise its decision-support utility? Linear analysis can answer this question.
Our first worked example report describes design and development of a predictive model built to examine water supply security of a small town in South Eastern Queensland. It shows how even with a relatively small observation dataset, sufficient information about hydraulic parameters, their distribution and uncertainty can be extracted during history
GMDSI is managed by the National Centre for Groundwater Research and Training (NCGRT) and administered by Flinders University.
