The paper uses the Cann River as a case study to move beyond retrospective geomorphic interpretation into the practical question of how rich datasets can be used to guide management. 30 years of evidence has been assembled to establish a geomorphic story; this paper asks what to do with that understanding.
We developed an integrated monitoring plan and framework combining remote sensing products, field observations and environmental data. From this, we defined a targeted monitoring program to selectively supplement the existing data tracking waterway trajectory and progressively improving accuracy of numerical and conceptual models that guide management. By improving such models, a digital twin of the Cann River is developed, so that differing management scenarios can be tested and optimised.
The central issue is what combination of analysis, modelling and field monitoring (including LiDAR and geomorphometric products) is needed to predict change, test management options and identify future data collection, rather than just describing results.
Flood recovery funding and community concern often concentrate attention on visible erosion and immediate intervention, but these do not always align with geomorphic trajectory or what is realistically achievable. The paper argues that management needs to be framed by an agreed understanding of river behaviour, likely trajectory and feasible intervention windows.
We describe a framework for using increasingly detailed datasets to support prediction, design and monitoring focusing on collecting what is needed, at the right resolution and over the right timeframe, to support practical river management.