Mine de-watering is the removal of unwanted groundwater from a mine to allow rock and mineral extraction from beneath the water table. In some circumstances, this can affect the health of groundwater-dependent vegetation (GDV) in the vicinity, which relies on a stable water-table for water requirements. Monitoring the potential impact of mining operations on GDV is an important compliance requirement for mining companies.
However, the distribution of GDV species, and the selection of monitoring sites, requires comprehensive knowledge and extensive time to set up. Narrowing the search space to accurately determine the distribution of GDV species is the first step towards establishing a time saving, cost efficient, and comprehensive monitoring program to monitor and manage de-watering activities. However, to date there is no standard tool to simplify this process.
De-watering of mine pits contributes to groundwater depletion potentially placing proximal groundwater-dependent vegetation at risk of water stress. While earth observation data has been trialed to monitor the effects of de-watering on vegetation health, a lack of ground truthing has limited its uptake. This project will develop a validated remote sensing method for detecting declining heath symptoms (e.g. reduced greenness/leaf moisture) of deep-rooted vegetation species caused by a lowering water table.
The project will leverage the Digital Earth Australia platform (DEA) reviewing the applicability of temporal Landsat Imagery and review higher resolution temporal Sentinel imagery data where possible. A spatial multi-criteria evaluation (SMCE) model will be used to integrate a temporal series of remotely-sensed vegetation indices to estimate vegetation health on a scale of 0-1. A decade's worth of regulatory environmental surveys reporting on the vegetation system impact, including floristic surveys and vegetation health monitoring, will be used to calibrate and validate the outputs. Results will be presented through accessible open source tools providing an efficient method for monitoring and reporting.
Over 6 months
GA: $125,000, 0.1FTE, analysis-ready data
