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Tracing shallow longitudinal preferential pathways of fluid movement using electrical geophysic

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posted on 2022-03-28, 18:27 authored by Anthony Finn
Assessment of gullies is essential in understanding the effects soil erosion has on resource management, urban planning, agricultural productivity and local environmental conditions. Commonly, prediction of gully head cut retreat has been disregarded due to the inherent complexities; this study proposes a method of analysing data to interpret potential pathways of Gully retreat. Through the implementation of electrical geophysics (Electrical Resistivity Imaging & Frequency Domain Electromagnetics) surveys positioned uphill of existing gullies shallow conductor's representative of Longitudinal preferential pathways (LPP) will be detected. ERI results detected conductors uphill of the head cut at varying distances showing resistivity values of 1 - 4 0 Ωm; these identified anomalous zones were confidently linked to form an LPP. Integrated geophysical datasets were generated allowing for interpreted traces of LPP to be drawn which are representative of the future pathway of head cut retreat. Through comparing currently existing gully assessment techniques it is suggested that a combination of geophysical prediction of LPP and LiDAR data is necessary for a complete understanding of existing gullies. Based on the results of this integration, informed and targeted management decisions can be developed to remediate current landforms and mitigate future gullying.


Table of Contents

Chapter 1: Introduction & background -- Chapter 2: Site overview -- Chapter 3: Methods -- Chapter 4: Results -- Chapter 5: Discussion -- Chapter 6: Conclusions.


Theoretical thesis. Bibliography: pages i-iii

Awarding Institution

Macquarie University

Degree Type

Thesis MRes


MRes, Macquarie University, Faculty of Science and Engineering, Department of Earth and Planetary Sciences

Department, Centre or School

Department of Earth and Planetary Sciences

Year of Award


Principal Supervisor

Mark Lackie


Copyright Anthony Finn 2018. Copyright disclaimer:




1 online resource (v, 48, iii pages)

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