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SA/NT Tech night: Constraining regional-scale groundwater transport predictions using multiple geophysical techniques

Event Type

Event Date

Tuesday, July 27, 2021

Event Location

Event Address

Thomas Cooper Room, Coopers Alehouse, 316 Pulteney Street, Adelaide, 5000

Event Start

1745

Event End

1930

Event Details

Title: Constraining regional-scale groundwater transport predictions using multiple geophysical techniques

Presenter: Dr Michael Hatch

Location: Thomas Cooper Room, Coopers Alehouse, 316 Pulteney St, Adelaide

Date: Tuesday 27th July 2021

Time: 5:45 pm for a 6:15 pm start

Cost: Members and students free, non-members $10, includes finger food and drinks

 

I would like to invite you to our next technical event on Tuesday 27th July at 5:45 pm for a 6:15 pm start at the Thomas Cooper Room, Coopers Alehouse.

We have Dr Michael Hatch from the University of Adelaide speaking on 'Constraining regional-scale groundwater transport predictions using multiple geophysical techniques'.

 

Due to often spatially discontinuous and sparse datasets from traditional geohydrological techniques, it is becoming more common to incorporate geophysical data in groundwater models.  Not only are the geophysical data sets more continuous, but they can often be collected non-invasively. A disadvantage is that there may be no consistent/obvious link between the geophysical data and the geohydrological properties that the groundwater model is simulating. It is therefore necessary to derive coupling relationships between the geophysical data and the underlying hydrogeology. This is usually performed in a deterministic manner in which the uncertainty inherent in the geophysical data (as well as in the coupling) is rarely incorporated. In this study we collect a number of geophysical data sets, including audio-frequency magnetotellurics (AMT), time‑domain electromagnetics (TEM) and nuclear magnetic resonance (NMR). These geophysical techniques provide constraints on hydraulic conductivity, water table depth, hydrostratigraphy and porosity. By combining this information with scattered and sparse hydrological measurements, the geophysical data can be coupled with other data in a stochastic groundwater modelling framework. When using geophysical data to provide parameters in groundwater model inversion, it is critical to quantify and account for their uncertainty to avoid incorrectly biasing model outcomes. This study achieves this goal by using an ensemble-smoother modelling method incorporating PESTPP-IES. This approach is illustrated using geophysical and hydrological data from Kapunda, South Australia, to evaluate the potential impact of a simulated In-Situ Recovery (ISR) lixiviant injection test