Remote Sensing and Hydrodynamic Modelling for Flood-Driven Soil Erosion in Northern Queensland

This PhD project develops an integrated remote sensing and modelling framework to assess flood-driven soil erosion and land degradation in Northern Queensland rangelands. Flood events in this region significantly reshape landscapes through gully erosion, sediment redistribution, and vegetation loss, posing risks to soil fertility, ecosystem resilience, and sustainable land management.
The research combines multi-sensor remote sensing data with advanced hydrodynamic modelling to monitor, quantify, and predict erosion processes. A key component involves generating high-resolution Digital Elevation Models (DEMs) by integrating multiple data sources, including Copernicus, TanDEM-X, ASTER, SRTM, ALOS, ICESat-2, UAV photogrammetry, and LiDAR. These datasets are used to produce a refined terrain baseline for hydrological and geomorphic analysis.

Time-series analysis using SAR (InSAR), optical satellite imagery (e.g., Sentinel-2 and Landsat), and UAV data enables the detection of landscape changes before and after flood events. These observations are coupled with catchment-scale erosion modelling approaches, including RUSLE and Trends.Earth indicators, to assess long-term land degradation patterns and identify erosion hotspots.
Additionally, 2D hydrodynamic models (e.g., HEC-RAS 2D or TUFLOW) simulate flood extent, depth, velocity, and shear stress. These outputs are integrated with sediment transport and erosion proxies to improve the understanding of erosion mechanisms and validate model performance against observed changes.

The project delivers a multi-scale, data-driven framework to support improved flood-impact assessment, inform land-management strategies, and enhance the resilience of rangeland ecosystems under increasing climate variability.

Project Team and Collaborators:
Laleh Jafari (PhD Candidate), supervised by Dr Ben Jarihani, Dr Jack Koci, Dr Stephanie Duce, Dr Ioan Stanislav, and Dr Dipak Paudyal at James Cook University (JCU). The project may also involve collaboration with remote sensing specialists, hydrologists, and regional land management stakeholders in Northern Queensland.

Funding Sources to be Acknowledged:

Australia’s Economic Accelerator (AEA) Seed and Ignite Funding