Groundwater modelling simulates groundwater flow processes underground. Developing useful numerical models requires a range of skills including an understanding of computer code, geology, geographic information systems, databases, statistics and mathematics. We have a team of six hydrogeologists and engineers with these unique skills, who work as a team, constructing numerical models to assist our clients with groundwater management challenges. Our modelling group each brings their own specialities to the team such as uncertainty analysis, calibration techniques, and solute transport modelling.
Conceptual Model Design
The key to developing a robust numerical groundwater model is good foundations. The foundation of a computer model is the understanding of the natural system it is designed to replicate. This is known as a conceptual model, which describes how the groundwater system works. It is based on available data and is an idealised and simplified representation of the natural system. Data sources for conceptual models, including:
climatic records including rainfall, evaporation and streamflow;
geological and topographical maps;
information from drill holes & bores;
geological models developed by resource companies, researchers and governments; and
government databases for geology, hydrogeology, ecology and hydrology.
We analyse this information to develop a conceptual model of the groundwater regime. In some cases we use software to create three dimensional visual models of the groundwater system to assist with communicating our findings to a range of stakeholders.
A complex model does not necessarily provide better results or predictions than a simple model. We often first develop simple analytical models to represent groundwater flow processes and assess the impacts of major projects on water resources.
Analytical models can be developed relatively quickly and inexpensively and can be used to assess groundwater issues at a high level. If risks and uncertainty are low then it may not be necessary to develop more complex numerical models.
Our team regularly develop numerical models that represent groundwater flow processes in either two, or three dimensions. We use two-dimensional models to assess seepage through artificial embankments, tailings dams and water impoundments.
Complex groundwater systems often require sophisticated methods to analyse potential impacts, for which we develop three dimensional models.
At AGE we specialise in the use of the MODFLOW code, and its many variants, MODHMS, MODFLOW SURFACT and MODFLOW-USG. MODFLOW is the most transparent and numerically efficient modelling code available. The latest iteration, MODFLOW-USG, combines the efficiencies of finite element mesh design with the numerical stability of control volume finite difference flow equations. We favour the use of Voronoi mesh design and layer pinching that MODFLOW-USG offers to optimise model run times, allowing us to speed up the modelling process.
At AGE we are also proficient in the use of SEEP/W (two-dimensional model) and FEFLOW (finite element three dimensional model) and where necessary can apply this software to meet our clients needs.
How groundwater interacts with surface water is often an important process that needs representing within numerical models. We replicate these interactions using recharge, evapotranspiration and stream flow routing packages using inputs from analytical calculations and other models such as AWBM and SWAT.
Our goal when developing numerical models is to ensure they replicate key underground processes as closely as possible. Numerical models have buyantibioticsonline many parameters that represent the groundwater system, and finding the optimal combination of these parameters can be a challenge.
At AGE we use automated optimisation software such as PEST to improve the calibration of our models. We also have our own high performance computing cluster that speeds up the calibration process allowing many models to run simultaneously. We also employ advanced optimisation techniques including Advanced Spatial Parameterisation and Shuffle Complex Evolution methods when required to ensure each model is well calibrated and suitable for use.
Numerical models are powerful tools for examining changes in underground water systems. However, they are always based on assumptions that simplify complex processes and systems, and therefore predictions from models have inherent uncertainty.
In recent years we have invested heavily in improving our capability to assess the level of uncertainty in the predictions from our numerical models. From this effort we have a growing and advanced capability, supported by a team that includes post-doctoral specialists in numerical uncertainty modelling.
We undertake ‘Monte Carlo’ style analysis that can provide upper and lower bounds on model predictions. This is important for our clients decision making process and can indicate if the level of uncertainty is a risk and whether it requires further work to be reduced. Consequently it can also assess where uncertainty has no material impact on the model predictions.
These types of analyses are made possible through the use of AGEs high performance computing cluster, which is capable of running thousands of model permutations in a matter of hours.
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