Using high-resolution topography for spatial prioritisation of gully erosion management across catchments of the Great Barrier Reef, Australia

Abstract

The Great Barrier Reef (GBR) running along ~2 000km of the north-eastern coast of Australia is a UNESCO World Heritage site and is the largest living structure on Earth. The GBR is at the forefront of environmental issues currently faced by Australia, with significant economic, environmental, social, and cultural value. Terrigenous fine sediment affects water quality in the GBR and contributes to the degradation of significant marine environments. Gully erosion is believed to be an important contributor of this fine sediment, and this has garnered recent attention from the Australian Government. A key challenge to managing gully erosion across catchments of the GBR is the large scale of the combined area (>400 000 km2). Recent advances in Light Detection and Ranging (LiDAR) have enabled generation of high-resolution (~1 m) digital elevation models (DEMs) over large areas. Over recent years airborne LiDAR data captures have covered many areas of the GBR catchments, with ~50 000 km2 of topography data with a spatial resolution of 1 m or finer. This newly available source of high-resolution data presents an opportunity to map and predict locations of gully erosion across large areas, reducing the need for time-consuming fieldwork. However, there is a need for further development of suitable methods to exploit this data. The core aim of this PhD has been to develop a set of tools and algorithms for using high-resolution topography data to map gullies and areas susceptible to future gully erosion. Novel analysis methods were developed into open-source computer programs with a general focus on creating resources to assist researchers and practitioners managing and assessing gully erosion over large areas. The overall approach is split into to two broad categories of analysis. The first focuses on gully management at small scales (tens of square kilometres), and the second focuses on large scales (hundreds to thousands of square kilometres). The algorithms developed from each of the two halves are designed to work in unison to prioritise gully erosion management first at large scales and subsequently at small scales. This PhD has developed and assessed novel methods for using high-resolution topography data to map and predict gully erosion across catchments of the GBR. A core focus has been on proposing 'standard' methods for computing the required inputs for topographic models of gully occurrence in the landscape. The broader goal of this was to help move the field closer to a set of tools that allow researchers to readily compare model results between landscapes and regions free of bias introduced by variations in sampling procedures. This work has highlighted the potential benefit of using high-resolution topography, particularly airborne LiDAR, but that consistency with methodologies is key to enabling comparisons across landscapes. The methods developed also have applications to other environments, particularly semi-arid regions, and have all been developed in open-source programming languages to help facilitate adoption. Results from applying two different topographic models of gullies showed that land clearing and a transition from natural forests to agricultural landscapes has likely led to increased gullying across catchments of the GBR. This finding is consistent with other studies globally and provides important context for gully management priorities in this region. Show more