Decision-support groundwater modelling is as much an art as it is a science. Much of the “art” is in decomposing the management problem that modelling must address. If this is done properly, then decision-support modelling has a much greater chance of being useful to decision-makers, while being acceptable to stakeholders.
Problem decomposition requires that those who build models understand not just the hydrogeological context in which groundwater management is required. Just as important is the information context. Any prediction that a model makes has a known component and an unknown component. The first is informed by site data, whereas the latter is not. Modelling must capture the first and express the second. This doesn’t just happen. It has to be planned.
Of course, planning is context-specific and subjective. Different people will do things in different ways. This doesn’t matter. What matters is that we all agree on the metrics that decision-support modelling must serve, and understand the trade-offs that are required in achieving these metrics.
This monograph (written by John Doherty and Catherine Moore) examines the metrics and discusses the trade-offs.
