The Darcy Lecture series is sponsored by the Groundwater Foundation (part of NGWA). The Henry Darcy Distinguished Lecture Series in Groundwater Science fosters interest and excellence in groundwater science and technology It was established in 1986 and named in in honour of Henry Darcy of France for his 1856 investigations that established the physical basis upon which groundwater hydrogeology has been studied ever since. Each year, a panel of scientists and engineers invites an outstanding groundwater professional to share his or her work with their peers and students through this lecture series. The Darcy Lecture Series is most often presented at universities and professional associations throughout the world.
The 2019 Darcy Lecture Series in Groundwater Science
John Doherty’s 2019 Darcy Lecture is now available online:
On Thursday 14 March 2019, the New Zealand Chapter of the International Association of Hydrogeologists with the support of University of Auckland and Beca hosted the first Darcy Lecture presented by John Doherty, Ph.D from Watermark Numerical Computing.
Starting the problem and working backwards
John Doherty, Ph.D., is the author of PEST, a software package that is widely used for groundwater model calibration and uncertainty analysis. He has worked for more than 35 years in the water industry, first as an exploration geophysicist and then as a modeller. Doherty been employed by both government and industry, and has also worked at numerous universities where he undertook research and supervised postgraduate students. Currently he works for his own company, Watermark Numerical Computing, doing consulting, research, programming, and education, mainly on issues related to model deployment in support of environmental management and impact assessment.
Many groundwater models are commissioned and built under the premise that real world systems can be accurately simulated on a computer – especially if the simulator has been “calibrated” against historical behaviour of that system. This premise ignores the fact that natural processes are complex at every level, and that the properties of systems that host them are heterogeneous at every scale. Models are, in fact, defective simulators of natural processes. Furthermore, the information content of datasets against which they are calibrated is generally low.
The laws of uncertainty tell us that a model cannot tell us what will happen in the future. It can only tell us what will NOT happen in the future. The ability of a model to accomplish even this task is compromised by a myriad of imperfections that accompany all attempts to simulate natural systems, regardless of the superficial complexity with which a model is endowed. This does not preclude the use of groundwater models in decision-support. However it does require smarter use of models than that which prevails at the present time.
It is argued that, as an industry, we need to lift our game as far as decision-support modelling is concerned. We must learn to consider models as receptacles for environmental information rather than as simulators of environmental systems. At the same time, we must acknowledge the defective nature of models as simulators of natural processes, and refrain from deploying them in a way that assumes simulation integrity. We must foster the development of modelling strategies that encapsulate prediction-specific complexity supported by complexity-enabling simplicity. Lastly, modellers must be educated in the mathematics and practice of inversion, uncertainty analysis, data processing, management optimization, and other numerical methodologies so that they can design and implement modelling strategies that process environmental data in the service of optimal environmental management.
The lecture was a great success, with about 50 to 55 people attending the meeting.