Phil Flentje

Uncertainties in rainfall-induced landslide hazard

The paper addresses the main uncertainties associated with the occurrence of rainfall induced landslides. Spatial variability of site conditions, local geology and rainfall contributes significantly to the uncertainty of landslide hazard. Urban landslide problems require the management of slopes of marginal stability. Assessment of hazard, vulnerability and risk require the use of observational approaches, the analysis of rainfall data and the relationship between rainfall magnitudes on the one hand and slope movement on the other. Details of research carried out in the Illawarra area of New South Wales, Australia are provided. Reference is made to the comprehensive database enabling the determination of landslide frequencies. The concept of antecedent rainfall percentage exceedence time (ARPET) is explained. The use of inferred threshold rainfall magnitudes for real-time prediction and warning is explained. Uncertainties concerned with this approach are explored with particular reference to rainfall distributions in the study area.

An evaluation of airborne laser scan data for coalmine subsidence mapping

The accurate mapping of coalmine subsidence is necessary for the continued management of potential subsidence impacts. The use of airborne laser scan (ALS) data for subsidence mapping provides an alternative method to traditional ground‐based approaches that affords increased accessibility and complete spatial coverage. This paper evaluates the suitability and potential of ALS data for subsidence mapping, primarily through the examination of two pre‐mining surveys in a rugged, densely vegetated study site. Data quality, in terms of mean point spacing and coverage, is evaluated, along with the impact of interpolation methods, resolution and terrain. It was assumed that minimal surface height changes occurred between the two pre‐mining surfaces. Therefore any height changes between digital elevation models of the two ALS surveys were interpreted as errors associated with the use of ALS data for subsidence mapping. A mean absolute error of 0.23 m was observed, though this error may be exaggerated by the presence of a systematic 0.15 m offset between the two surveys. Very large (several metres) errors occur in areas of steep or dynamic terrain, such as along cliff lines and watercourses. Despite these errors, preliminary subsidence mapping, performed using a third, post‐mining dataset, clearly demonstrates the potential benefits of ALS data for subsidence mapping, as well as some potential limitations and the need for further careful assessment and validation concerning data errors.

Consideration of optimal pixel resolution in deriving landslide susceptibility zoning within the Sydney Basin, New South Wales, Australia

This paper discusses the progress of the landslide susceptibility mapping in the wider Sydney Basin area to facilitate engineering and geological studies and land-use zoning; using induced decision trees. This study investigates the effect of the basic unit of this spatial modelling work (pixel resolution) on the accuracy of the modelling outcome, and reports on the effectiveness of using See5 pruned decision trees to model the landslide susceptibility of the Sydney Basin. Landslide susceptibility was determined from the landslide confidence value derived from the Laplace ratio of the rule based predicted classes. The modelling work has been carried out at 2m, 5m, 10m, 15m, 20m, 25m, 30m, and 40m pixel resolutions for a trial area within the Sydney Basin. Ten different GIS based datasets derived from the same original datasets have been used each time as landslide causative factors. The optimum tree pruning parameters for each pixel resolution were identified by analysing the behaviour of misclassification errors. Performance of the models at different pixel resolutions was compared using ROC curves and five-fold cross validation accuracy. High density ALS elevation point clouds and large scale datasets allowed model development at a higher resolution (2m) but the decision tree model at 10m resolution performed better than the rest. The ratio between the square root of the mean landslide area of the inventory and the area covered by a single pixel has been developed as a worthwhile quantitative measurement of the adequacy of the model resolution. The validation results of the final modelling outcome show that landslide susceptibility descriptors fulfil the requirements of the LRM guidelines. The model has a conservative success of 90% according to the field validation and a cross validation accuracy of 92%. Slide category landslide susceptibility zoning over the 30,603km2 Sydney Basin.Methodology to derive the optimum pixel resolution for this spatial analysis.Introduces MEMO curves to determine pruning parameters for See5 decision trees.Introduces delta (?) parameter ratio to compare the modelling rigour.Field validation methodology to evaluate the susceptibility model.

Quantitative landslide hazard and risk assessment: a case study

This paper is concerned with landslide hazard and risk assessment along a railway line south of Sydney in the State of New South Wales, Australia. Attention is focused on a quantitative assessment at a specific site where landslide movements have been triggered by significant rainfall. Although small in magnitude such movements are sufficient to cause train derailment and hence human casualty. Utilizing all available data, the relationship of slope instability to rainfall is first established. Slope stability analyses are carried out to validate the proposed geological-geotechnical model. The concept of landslide triggering critical rainfall magnitude (specific to a given site) is proposed in this paper. Detailed rainfall analysis reported elsewhere (Ko Ko 2001) leads to the conclusion that the most significant period of antecedent cumulative rainfall for this site is 15 days. The historical rainfall data then leads to an estimation of landslide frequency or hazard. The risk to human casualty is then based on an analysis of train operations and their frequency. Different results are obtained for the tourist train service and the freight train service. Some attention is given to tolerable risk criteria proposed elsewhere in the literature.

Landsliding in an urban area

The city of Wollongong is nestled within a narrow coastal plain approximately 70 km south of Sydney in the state of New South Wales (NSW), Australia (Fig. 1 ). Over the last 150 years of settlement the population of the Wollongong area, extending from Helensburgh in the north to Windang in the south has increased to about 200 000 people. The coastal plain is triangular in shape with a coastal length of 25 km. It is widest in the south at Yallah (14 km) and narrows sharply towards the north, disappearing north of Thirroul. The coastal plain is bounded to the north, west and south by an erosional escarpment ranging in height from 300 m up to 500 m. Fig. 1 Location plan. The escarpment consists of slopes with moderate to steep inclinations with several intermediate benches and cliff lines. Spectacular cliffs of Hawkesbury Sandstone (Middle Triassic) cap the escarpment and there is dense vegetation over most of the escarpment below these cliffs (Fig. 2 ). Fig. 2 Escarpment with large rock fall debris flow near Dombarton railway siding, 1974. Photo by Young. The main road link to Sydney is the F6 freeway that traverses the escarpment via Mount Ousley Road. There are …

Total Landslide Susceptibility Modelling

This paper outlines the status of the landslide susceptibility modelling of the Sydney Basin region within the state of NSW, Australia. This area extends from Newcastle in the north to Batemans Bay in the south and west to include the Blue Mountains, an area of approximately 31,000 km2. The University of Wollongong NSW Landslide Inventory includes 1863 landslides (134 falls, 278 flows and 1451 slides) to date. The region supports approximately one quarter of the population of Australia. Individual susceptibility models for both slide category and flow category landslides have been developed for the entire Sydney Basin region. Rockfall Susceptibility has also been developed for portions of the Wollongong Local Government Area. The susceptibility models are suitable for use at local scale, Advisory level Local Government Area Development Control Plans. As the models cover the three dominant landslide types identified within the inventory, a trial Total Landslide Susceptibility model has now been developed. As each landslide susceptibility model is a 10 m pixel resolution numerical grid, with values ranging from 0 to 1, the total susceptibility model has been developed, quite simply, by summing the three individual models producing a Total Susceptibility numerical grid. However, classifying this grid into zones is not simple. Furthermore, the Australian regulatory requirements are varied and the outcomes often complex involving a spatial query of the total susceptibility grid and its three contributing landslide susceptibility grids.

What Does Hazard Mean? Seeking to Provide Further Clarification to Commonly Used Landslide Terminology

Concepts and definitions for landslide susceptibility, hazard and risk zoning as-assessment have been defined in the paper entitled “Guidelines for Landslide Susceptibility, Hazard and Risk Zoning for Land Use Planning” and the associated Commentary by produced by JTC-1, the Technical Committee for Landslides and Engineered Slopes (Fell et al. 2008a, b. These papers are largely based on earlier work by the Australian Geomechanics Society (AGS 2007). However the authors believe the use, meaning and intent of some landslide terminology remains an issue in effectively communicating concepts amongst the geoscience and engineering communities, land use planners and inevitably the general public. Recent experience within Australia during the 2011 National LRM Roadshow and at the 11th International and 2nd North American Symposium on Landslides in Banff, Canada in 2012 noted different interpretations and applications for the commonly used term ‘hazard’, and the associated terms ‘hazard maps’, ‘hazard mapping’ and ‘hazard assessment’ even within such specialist technical groups. It is then vitally important when relating such information and knowledge to non-technical people outside ‘our’ community, that we use clear and consistent terminology and language with appropriate clarification when needed. This paper seeks to provide clarification around the term ‘hazard’ in an attempt to inform and correct the widespread ambiguous use of this basic term when used in connection with landslide risk. We seek to provide clarifying context so as to promote better communication and understanding between all users concerned with a knowledge of areas that have been affected by landslides (inventories), areas that could be affected (susceptibility), how likely they may be to occur (frequency analysis) and what might happen if they do occur (consequences).