Oral Presentation NCGRT/IAH Australasian Groundwater Conference 2019

Time series analytical modelling using HydroSight to investigate drivers of groundwater level fluctuation   (328)

Tim Armstrong 1 , Vahid Shapoori 1
  1. Australasian Groundwater and Environmental Consultants, Bowen Hills, QLD, Australia

Variations in groundwater levels are complicated by natural and anthropogenic drivers and processes. For instance, a decline in groundwater water level could be the combined result of, but not limited to, reduced recharge, evapotranspiration, and groundwater pumping. Effective groundwater management often requires identification and separation of these drivers and the prediction of the groundwater level under differing scenarios.

Numerical models are usually built for such groundwater level investigations. However, numerical modelling often involves significant labour cost and they require prior assumptions about the hydrogeology and the dominant drivers.

As an alternative to numerical techniques, the hydrograph time-series model (HydroSight) has been recently introduced for simulating the impacts of multiple drivers of groundwater level variations. HydroSight is simple to apply and requires fewer prior assumptions about the hydrogeology compared to numerical models.

HydroSight consists of a soil-moisture layer to account for non-linearity between rainfall and recharge, as well as different response functions to account for pumping from multiple wells and/or mine induced drawdown. In this study, HydroSight was applied to an area surrounding a mine in Australia. The results showed that HydroSight can separate the effects of pumping from the effects of climate on groundwater-head variation. The results also gave insight into the potential extent and magnitude of drawdown in a basalt aquifer surrounding a mine and helped to quantify the potential impact on a nearby landholder bore. We encourage others to apply HydroSight when numerical models are either not warranted or the prior assumptions about the hydrogeology are not well understood.