Kyle Mercer

Year

2019

Degree Name

BEnviSci Hons

Advisor(s)

Kerrylee Rogers

Abstract

Erosion and sedimentation present a significant problem in catchments across the world. The Minnamurra River catchment prior to European colonisation was a well-vegetated landscape with established forests and swamplands. The area was cleared for timber and established as a dairy farming region in the early 1900s. As of 2015, 57.3% of the catchment is considered grazing pastureland. The aim of this study is to identify the erosion patterns of the Minnamurra River catchment and identify sub-basins that require management attention using a GIS modelling approach. The model selected was the Revised Universal Soil Loss Equation (RUSLE). This choice was based on the model’s ability to address the two major classes of erosion, sheet and rill, as well its low data requirement and success in similar catchments. The model accounts for primary factors contributing to erosion without the need for extensive input parameters. These factors are rainfall, soil composition, land use and landscape topography.

The RUSLE hillslope erosion model calculated in the report uses a combination of four factors, rainfall intensity (R) and length slope factors (LS), determined using theoretical equations extracted from rain gauge data and digital elevation models (DEMs). In addition, two weighted nominal factors were determined from lookup tables which account for land use (C) and soil erodibility (K). Validation of the model was undertaken using field water sampling, model comparison and site inspections.

The results of modelling showed that the catchment is eroding at a mean rate of 0.82tons/ha/yr. More importantly, the RUSLE model revealed that areas of highest erosion occur on the cleared slopes of the northern and southern sections of the catchment, whereas the upper catchment is significantly protected from erosion by forest cover. RUSLE identifies broad scale erosion trends effectively but is limited when small-scale erosion occurs due to factors such as bank failures and poor riparian vegetation. Improvements to the model could include the addition of higher resolution input data for the R, C and K factors and a full coverage LiDAR program. Ongoing management in the catchment should focus on the improvement of hillslope and riparian vegetation in the Curramore, Rocklow, Jerrara, Fountaindale and Hyams sub-basins. With specific recommendations to address a sever bank erosion site in the Curramore basin and remediate the water quality in Fountaindale Creek.

FoR codes (2008)

040607 Surface Processes

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Unless otherwise indicated, the views expressed in this thesis are those of the author and do not necessarily represent the views of the University of Wollongong.