GMDSI

GMDSI Update – Out Today! Two new videos are now available on YouTube, covering hydraulic property generation, alluvial channels, and the PLPROC parameter preprocessor. A new self-questionnaire is also available to guide decision-support groundwater modelling workflows. A big thank you to all attendees and UWA staff for making the decision-support modelling workshop and PEST course in Perth a success! For more information, check out the link below. https://lnkd.in/dD3ZNjQ4 #GMDSI #GroundwaterModelling #DecisionSupport #Training #Hydrology #WaterManagement

GMDSI Update out today! New Video - Nuts and bolts of using PEST/PEST++ GMDSI Workshop: Simulator Partner Technologies: When to use What, and Why – Perth spots still available on 18th Nov but PEST course sold out. GMDSI heads to IAH Conference Davos For more information read below - https://lnkd.in/ggzKvYT4

Parameter Estimation and Uncertainty Analysis Course When: 19-22 November Where: University of Western Australia, Crawley Campus Presenters: John Doherty, Jeremy White More information and to register - See below

Registrations are now open for the GMDSI Workshop: Simulator Partner Technologies: When to use What and Why. When: 18th November Where: Perth Want to know more: Check out the details below. Presenters: John Doherty, Jeremy White, Eduardo De Sousa, Catherine Moore

GMDSI Update out today. Inside this edition: New Monograph and Video One-Day Workshop in Perth Short course: Parameter Estimation and Uncertainty Analysis - Perth Check it out here: https://lnkd.in/gda7SeBx

Home Tutoring We are receiving an increasing number of requests for GMDSI home tutoring. If you would like help in thinking about how groundwater modelling can best serve your data-processing and/or decision-support needs, or in applying modern-day model-complementary technologies at your particular site, let us know and we can arrange a web meeting. Contact us at - gmdsi@groundwater.com.au

Check out the GMDSI update out today containing two new tutorials and videos on the GMDSI YouTube Channel. The new tutorials demonstrate workflows for model calibration using ensemble space inversion (ENSI), and linear parameter and predictive uncertainty analysis as adjuncts to ENSI-based model calibration. Software that implements these methodologies is available in version 18 of PEST_HP. Read more here: https://lnkd.in/gxzkDATj

GMDSI now has its very own YouTube Channel. Check out the content and subscribe here - https://lnkd.in/gJzjfrhs

GMDSI has just released a new tutorial - From site concepts to a 3D site model It continues the focus of a previous tutorial on bridging the gap between site conceptualisation on the one hand, and numerical modelling on the other hand. It turns its attention to the third dimension. The tutorial is a little experimental. However, the methodologies that it demonstrates have the potential to make parameterisation, history-matching and uncertainty analysis of three-dimensional models much easier than before. The three-dimensional modelling process begins with “conceptual points”. These comprise a three-dimensional “geological mudmap” of: ·        possible system hydraulic properties; ·        proclivity for the existence of hydraulic property heterogeneity; and ·        likely shapes and orientations of heterogeneity patterns in different parts of a study area. The tutorial shows how software available through the PEST and PEST++ suites can then be used to generate adjustable parameter fields from information that is associated with conceptual points using state-of-the-art methods that do not require an assumption of geostatistical stationarity. Hence they support spatial variability of heterogeneity patterns in ways that reflect knowledge of local geology. Topics that are covered by this tutorial include the following: ·        Conceptual points as a means of encapsulating the outcomes of site characterisation; ·        Generation of 3D, stochastic, non-stationary parameter fields that can paint semi-realistic pictures of subsurface hydraulic property heterogeneity; ·        Numerically cheap adjustment of these fields using PESTPP-IES and PEST_HP; Data space inversion as a stand-alone means of uncertainty analysis or as a complement to other methodologies. Download the tutorial here - https://lnkd.in/gqgZ9ZAZ