Theo van Asch

Deterministic Modelling in Gis-Based Landslide Hazard Assessment

Deterministic models are based on physical laws of conservation of mass, energy or momentum. In the case of deterministic landslide hazard zonation, distributed hydrological and slope stability programs are used to calculate the spatial distribution of groundwater levels, pore pressures and safety factors. This paper is concentrated on the integration of two-dimensional, raster-based, geographic information systems (GIS) and deterministic models, with emphasis on deterministic hydrological models. Three examples of deterministic landslide hazard zonation are presented; one from Costa Rica and two from Colombia. In the example from Costa Rica, a one- dimensional external hydrological model is used to calculate the height of perched water tables in the upper metre of the soil for different soil types and different rainstorms. In the first example from Colombia, an external two-dimensional hydrological model is used to calculate the maximum groundwater level, for a 20 year period, in different slopes with a sequence of volcanic ashes overlying impermeable residual soils. In the second example from Colombia, a three-dimensional hydrologic model is used in a GIS to simulate groundwater fluctuations during one rainy season. In examples 1 and 2 the results of the hydrologic calculations are used in stability calculations to obtain maps which give the spatial distribution of safety factors and the probability of failure, with the use of distribution functions of the input parameters. In example 3 the calculated groundwater levels are exported to an external slope stability model to calculate the safety factor along slope profiles.

Modelling gully erosion for a small catchment on the Chinese Loess Plateau

The rolling hills region of the Chinese Loess Plateau is one of the areas with the highest erosion rates on earth. A striking feature of this area is the occurrence of many large, permanent gullies. A 3.5-km2 catchment was selected to study the processes of erosion and to adapt the storm-based Limburg Soil Erosion Model (LISEM) to the conditions prevailing on the Loess Plateau. Part of this work consisted of mapping and measuring the largest gully headcuts. The amount of loose soil material beneath the headcuts was also estimated. Observations suggest that gully headcuts are relatively stable (i.e., do not migrate rapidly), but that gullies can nevertheless produce significant amounts of sediment during overland flow events. Erosion of headcuts occurs mainly by soil falls in between storms. The loose soil material produced by these soil falls accumulates on the gully bottom. As the LISEM simulates storm erosion, the development of gullies over time can be ignored, and only the amount of material produced by them during runoff events needs to be studied. A digital elevation model (DEM) was used to estimate the position of existing gully heads by applying an adapted form of the Montgomery and Dietrich [Science 255 (1992) 826] index. Using the assumption that headcuts are vertical, it is possible to calculate headcut height from the slope angle map. A simple stability model, which assumes soil falls on gully headcuts to be a function of soil moisture content and headcut height, was applied. This daily-based model can then be used to simulate the accumulation of loose soil material below the headcut. The results show that while the DEM is not accurate enough to allow the detection of individual headcuts, this method can be used to produce a reasonable estimate of the amount of loose soil material available. A map showing the amount of loose soil material accumulated can then serve as input for a storm-based erosion model such as LISEM.

Modelling the erosional susceptibility of landslide catchments in thick loess: Chinese variations on a theme by Jan de Ploey

Abstract In his 1990 paper (Catena, 17: 175–183), Jan de Ploey proposed a system whereby catchments are viewed as functional units in which geomorphic work results from the combined effects of water erosion and mass movements. His measure of erosional susceptibility of catchments, ES, introduced the gravitational potential in addition to the kinetic energy of the eroding agents. This modelling of the erosional susceptibility of catchments in terms of energy was being used to explore time-dependent variations of ES when Jan de Ploey died. Also at this time, he extended an invitation to the present authors to test and extend his model using our data base on the landslide-dominated catchments in the thick loess country of north-central China. This paper presents a series of new equations expressing variations in ES using a data base for over 200 landslides in the loess-covered mountainous terrain (relative relief up to 1500 m) of the Lanzhou region of eastern Gansu Province. These equations express the loss of potential energy of the landslide mass in relation to the relative relief and the pressure energy input in the form of rainfall. These indices of erosional susceptibility can be used to analyse the differences in response, from one catchment to another and through time, between the characteristics of vegetation cover including land use, hydrology, geomechanical behaviour, and mechanisms of movement on slopes. Using certain assumptions on percentage area of catchments affected by mass movement and long-term mean annual precipitation in the Lanzhou region, the Es equation suggests an estimate for non-clayey materials of about 10−4 m−2/s−2, which is a significantly higher susceptibility value than the mean worldwide value for non clayey materials obtained by De Ploey.

ASCHFLOW : a dynamic landslide run-out model for medium scale hazard analysis

BackgroundLandslides hazard analyses entail a scale-dependent approach in order to mitigate accordingly the damages and other negative consequences at the respective scales of occurrence. Medium or large scale landslide run-out modelling for many possible landslide initiation areas has been a very difficult task in the past. This arises from the inability of the run-out models to compute the displacement with a large amount of individual initiation areas as it turns out to be computationally strenuous. Most of the existing physically based run-out models have difficulties in handling such situations. For this reason, empirical methods have been used as a practical mean to predict landslides mobility at a medium scale (1: 10,000 to 1: 50,000). They are the most widely used techniques to estimate the maximum run-out distance and affected zones not only locally but also regionally. In this context, a medium scale numerical model for flow-like mass movements in urban and mountainous areas was developed.Results“AschFlow” is 2-D one-phase continuum model that simulates, the entrainment, spreading and deposition process of a landslide or debris flow at a medium scale. The flow is thus treated as a single phase material, whose behavior is controlled by rheology (e.g., Voellmy or Bingham). The model has been developed and implemented in a dynamic GIS environment. The deterministic nature of the approach makes it possible to calculate the velocity, height and increase in mass by erosion, resulting in the estimation of various forms of impacts exerted by debris flows at the medium scale.ConclusionsThe developed regional model “AschFlow” was applied and evaluated in well documented areas with known past debris flow events. The “AschFlow” model outputs can be considered as an indication of areas possibly affected with a defined intensity for one or more landslide events. From a user perspective the “AschFlow” model can be seen as a standalone model which can be utilized for a first assessment of potentially impact areas.

Introduction: The components of Risk Governance

This introductory chapter discusses key issues related to aspects of hazards and risks of natural processes in Mountain areas and discusses the framework of risk governance, which aims to integrate these elements.

Methods for Debris Flow Hazard and Risk Assessment

Debris flow events yield a threat to different components of mountainous environments not only as the result of the process evolution but of the interaction with human systems and their coupled vulnerabilities. A variety of models exists for characterising the hazard that the different mass-flow phenomena present. In the case of dynamic run-out models, they are able to forecast the propagation of material after the initial failure and to delineate the zone where the elements at risk will suffer an impact with a certain level of intensity. The results of these models are an appropriate input for vulnerability and risk assessments. An important feature of using run-out models is the possibility to perform forward analyses and forecast changes in hazards. However, still most of the work using these models is based on the calibration of parameters doing a back calculation of past events. Given the number of unknown parameters and the fact that most of the rheological parameters cannot be measured in the laboratory or in the field, it is very difficult to parameterize the run-out models. For this reason the application of run-out models is mostly used for back analysis of past events and very few studies attempts to achieve a forward modelling with the available run-out models. A reason for this is the substantial degree of uncertainty that still characterizes the definition of the run-out model parameters. Since a variety of models exists for simulating mass-flows and for identifying the intensity of the hazardous phenomena, it is important to assess these models, perform a parameterization and reduce their uncertainties. This will enable to improve the understanding to assess the hazard and will provide the link with vulnerability curves that will lead eventually to generate risk curves and quantify the risk.

Techniques for the modelling of the process systems in slow and fast-moving landslides

This chapter reviews some of the current strategies for landslide modelling. Main physical processes in landslides are first recalled. Numerical tools are then introduced for the analysis of the behaviour of slow- and fast-moving landslides. Representative case studies are introduced through the chapter to highlight how different modelling strategies can be used depending on the physical processes that the modeller wants to take into account.

Mountain Risks: From Prediction to Management and Governance

One of the most interesting aspects of large-scale funding from the European Union over the last 30 years has been the potential to create extensive, international, multidisciplinary research programs that tackle substantial problems facing society. Whilst in the early days, these programs mostly consisted of teams of experienced researchers, more recently, the Marie Curie Intensive Training Network (ITN) schemehas facilitated thedevelopment of teams of early-career researchers: students undertaking doctoral research and those in the immediate postdoctoral phase. These ITNs provide a double benefit, not only permitting large teams of dedicated researchers to tackle in detail an important topic, but also offering the opportunity to develop a group of researchers who have been trained to a very high level in that specific area. The evaluation of risk in high mountains is one such substantial area, and this volume represents the outcome of a recent ITN, the Mountain Risks consortium, which ran from 2007 to 2011, with 14 partners. The program sought to provide research and training on mountain hazards and their associated risks and management strategies. The editors of the book are well known in this field, and most of the papers have been written by a combination of established experts (the supervisors) and earlycareer researchers (the students and postdoctoral researchers). The evaluation of mountain risk is complex. The book is based on a conventional (but almost universally adopted) approach to risk assessment: a simple equation that views risk as the product of the hazard, the vulnerability of the assets in question, and their exposure to the peril. Such an approach is best suited to simple physical assets such as buildings and roads. However, there is increasing concern that this type of approach struggles to deal with the complex nature of risk, especially for remote communities in high mountain areas. Risk in such an environment is a nebulous, multifaceted entity that, critically, is highly dynamic. Thus, the vulnerability of a community depends not only on its physical attributes but also on the degree of social cohesion, from the local to the national level. The risk to a particular community may vary greatly in time, as social conditions and structures change: For example, losses to landslides in Nepal increased substantially during the civil war in the early part of the last decade, when social cohesion collapsed in remote mountain communities. Capturing this in a conventional risk assessment is extremely difficult. Inevitably, the 15 papers are a slightly eclectic mix, but the quality is high. A notable strength is that most draw heavily upon the literature reviews that the doctoral students had undertaken as a part of their theses, providing a very useful oversight of the state of knowledge in each area. Some of the papers examine in some detail specific aspects of mountain risks, such as the use of ground-based interferometric synthetic aperture radar (InSAR) for landslide monitoring, whilst others are more broadly based reviews of key topics. The most interesting passages are those that focus on the vulnerability and exposure aspects of the risk equation, although the approach is generally quite conventional. There are a number of useful chapters that consider how vulnerability and exposure can be built into a quantitative risk evaluation, and on the implications of the outcomes for the management of those risks. Some aspects of the volume are a little frustrating. Critically, most of the hazards that are considered are those associated withmass movements, from individual rockfalls to large-scale landslides. Other mountain risks, such as snow avalanches, glacial lake outbursts, earthquakes, and flash floods, are barely considered. Thus, the book is perhaps slightly poorly titled. The book has a very strong European focus, largely with a western European slant. It is perhaps a shame that more consideration is not given to approaches in, for example, Canada and Japan, both of which have been innovative in this field. Finally, a few of the chapters are disappointingly short. For example, a chapter on lessons learnt from past disasters is potentially very interesting; that the text in the chapter itself, excluding the abstract, references, diagrams, etc, is only 5 pages feels slightly disappointing. In summary, this is a very interesting and useful volume that represents an important contribution to the field. The great strengths are the ways in which the book integrates both natural and social sciences and provides useful reviews of the state of the art in a wide variety of areas of risk assessment and management. Several of the chapters that examine different aspects of risk assessment are very valuable and deserve to be widely read. It will be of interest to both the research and the practitioner communities. However, the most important outcome from the ITN Mountain Risks consortium is probably the development of a large number of early-career professionals with high-level skills in the field of mountain risk. This book is a testament to their knowledge and skills.