Groundwater Videos

Basic Geostatistics - Part 1

Presented By: John Doherty

This is the first of a two-part series.

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Basic Geostatistics – Part 2

Presented By: John Doherty

In this continuation of the first video of this series, links between geostatistics and history matching of groundwater models are explored.

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Who cares? What will it cost?

Presented By: Ty Ferre, University of Arizona

Approaches to improve the value of models and to reduce total project costs.

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What is PEST?

Presented By: John Doherty

This video provides an overview of PEST and the three families of utility software that accompany it. It also provides a brief discussion of the demands of decision-support environmental modelling, for this is the context in which PEST must operate.

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Getting the Most out of PEST - Part 1

Presented By: John Doherty

This is the first video of a two-part series whose intention is to provide PEST users with some information on how to use PEST, and some of its supporting software, to best effect. This video covers the PEST control file, the difference between singular value decomposition and SVD-assist, and easy ways to add Tikhonov regularization to a PEST control file.

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Getting the Most out of PEST - Part 2

Presented By: John Doherty

This second video of a two-part series covers calculation of finite-difference derivatives, defences against model output numerical granularity, some aspects of observation weighting, termination criteria, Marquardt lambda settings, and the use of some important PEST support utilities.

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Pilot Points

Presented By: John Doherty

Pilot points are often employed as a parameterization device for groundwater models. This is because they can provide a sound basis for highly-parameterized inversion while restricting parameters to a number which is low enough to allow filling of a Jacobian matrix using finite difference derivatives. The video discusses options for their emplacement, and how Tikhonov regularization is best applied in the estimation of pilot point parameters. An example is provided that illustrates how nonuniqueness of the groundwater model calibration process may render important geological structures invisible to that process.

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Problems with Manual Regularisation

Presented By: John Doherty

This video extends the discussion of the preceding video while laying the foundation for ensuing videos. It explains how calibration based on manual regularization, whether performed automatically by software such as PEST or done manually by a modeller, may fail to find a parameter field that is of minimized error variance. It also shows that calibration achieved through manual regularization does not provide a good foundation for post-calibration uncertainty analysis. This is because the relationships between estimated and true hydraulic properties cannot be resolved when regularization is undertaken manually. The “cost of uniqueness” cannot, therefore, be assessed.

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Vectors and Statistics

Presented By: John Doherty

This video provides a short refresher on some aspects of matrix and vector algebra that we all learned at school but have since forgotten. It then does the same for a few basic statistical concepts. It is useful to watch this video before watching some of the other videos in this series.

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Well-Posed Inversion

Presented By: John Doherty

This video shows how parameters can be estimated when model calibration constitutes a well-posed inverse problem. However, in groundwater modelling, well-posedness does not occur unless preceded by manual regularization. This is not recommended practice, for reasons discussed in the video. Nevertheless, the discussion is good preparation for other videos which focus on solution of ill-posed inverse problems. Of particular interest is the discussion on how to extend linear theory to calibration of nonlinear models.

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Singular Value Decomposition

Presented By: John Doherty

Singular value decomposition (SVD) is explained. Also explained is the important role that SVD can play in solving an ill-posed inverse problem, and the insights that it can provide into what calibration of a groundwater model can and cannot achieve. Important concepts such as the null space are also discussed. An explanation is provided of how over-fitting to a calibration dataset can occur, and why this is a bad thing.

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Tikhonov Regularization

Presented By: John Doherty

The importance of Tikhonov regularization in the solution of an ill-posed inverse problem in general, and in the calibration of a groundwater model in particular, is explained. Also explained is its ability to achieve a solution to an inverse problem that is of minimized error variance through the role that it bestows on expert knowledge and site characterization in achieving that solution.

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What is calibration?

Presented By: John Doherty

This short video discusses what it means to calibrate a groundwater (or other) model. Calibration implies uniqueness. The quest for uniqueness is not a quest for truth. The uniqueness of a solution of an ill-posed inverse problem requires regularization. If properly applied, regularization yields a solution to that problem which is of minimized error variance. However, the potential for error in a calibrated parameter field, and in model predictions made by a calibrated model, can still be high.

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Cumulative impacts on streamflow from potential groundwater extraction under MDB Plan

Presented By: Dr Glen Walker

Presented by Dr Glen Walker, Grounded in Water on Thursday 27th June 2019

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Archived Videos