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Coal Seam Gas (CSG) development within the Surat Basin of Queensland, Australia, is expanding, with petroleum leases already approved for tenements covering over 24,000 km2. Many thousands of kilometres of access tracks will be developed to allow transport of vehicles to each of the CSG wells (Figure 1). Studies from agricultural watersheds across the globe have shown that rural roads provide a disproportionate contribution toward sediment loads into water ways. With CSG development, the intensity of roadways in agricultural land will increase significantly and there is a risk that erosion losses will increase likewise. We have evaluated the use of surface water flow models derived from fine-scale digital elevation models for identifying areas where CSG infrastructure has altered surface hydrology and areas of erosion risk. Aerial digital photogrammetry with a ground sample distance of 20 cm was used to create elevation models for a 1200 km2 focal region currently undergoing CSG development. Baseline digital terrain models were processed using a multi-direction flow-path prediction model. The ground elevation model (GEM) was evaluated using survey data at three different sites (a road cross section, a gravel pad, a road crossing a gully) obtained using a hand held Real-time Kinematic Global Navigation Satellite System (RTK GNSS). The water flow model was assessed using manual recording of visible water paths observed in open agricultural field conditions and within native forests where a significant canopy cover could influence predictions of soil surface elevation. Comparison of the GEM with ground surface elevation measurements showed good agreement with many of the predictions showing an error of less than 5 cm. This accuracy is approaching that of the RTK GNSS system (±2 cm) used in the ground surveys. A subset of predictions showed higher levels of error. Investigation found these to predominantly include points where sudden changes in elevation occurred, which suggests error introduced by smoothing algorithms used in creating the GEM. Comparison of predicted water flow paths against those mapped directly indicates that the model is able to accurately identify the location of many water flow paths across roadways. The model was effective in locating the major water flow paths under forest conditions, even when some of the soil surface may be obscured by foliage. Exploration, interpretation and discussion of the datasets with agricultural landholders and CSG staff developed interest in portraying the information as water flow maps such as those presented here.

High resolution spatial modelling approaches for monitoring surface water and erosion impacts of coal seam gas infrastructure