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 matching. This is possible due …
On 22 September 2020, Jeremy White and Mike Fienen from the USGS presented a GMDSI sponsored webinar on PEST++ V5. PEST++ V5 includes a wide range of tools for decision support modelling including global sensitivity analysis, data assimilation, uncertainty analysis, and management optimisation under uncertainty, with several new tools being actively developed to support increasingly …
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Led by the National Centre for Groundwater Research and Training (NCGRT) at Flinders University and in conjunction with the mining and groundwater industries, the Groundwater Modelling Decision-Support Initiative will enable better groundwater management through improved modelling, frameworks and practices.
Approaches to improve the value of models and to reduce total project costs. Presented by Ty Ferre, University of Arizona. Download on VIMEO
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. Presented by John Doherty Download on VIMEO
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 …
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. Presented by John Doherty Download on VIMEO
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 …
GMDSI is managed by the National Centre for Groundwater Research and Training (NCGRT) and administered by Flinders University.
