Martin Mergili

Simulation of debris flows in the Central Andes based on Open Source GIS: possibilities, limitations, and parameter sensitivity

A GIS-based model framework, designed as a raster module for the Open Source software GRASS, was developed for simulating the mobilization and motion of debris flows triggered by rainfall. Designed for study areas up to few square kilometres, the tool combines deterministic and empirical model components for infiltration and surface runoff, detachment and sediment transport, slope stability, debris flow mobilization, and travel distance and deposition. The model framework was applied to selected study areas along the international road from Mendoza (Argentina) to Central Chile. The input parameters were investigated at the local scale. The model was run for a number of rainfall scenarios and evaluated using field observations and historical archives in combination with meteorological data. The sensitivity of the model to a set of key parameters was tested. The major scope of the paper is to highlight the capabilities of the model—and of this type of models in general—as well as its limitations and possible solutions.

Recent Cases and Geomorphic Evidence of Landslide-Dammed Lakes and Related Hazards in the Mountains of Central Asia

Evidence of former landslide-dammed lakes exists in several places of the Central Asian mountains, both from historic and prehistoric times. Geomorphic records help to understand recent processes: large landslides repeatedly dam lakes which then threaten the population downstream. Even though most dam failures occur in the first few months after formation, lakes may also drain suddenly at later stages. Two case studies from Northern Pakistan are employed to exemplify the involved phenomena regarding dam formation, outburst mechanisms and options for hazard mitigation.

CHANGES OF THE CRYOSPHERE AND RELATED GEOHAZARDS IN THE HIGH-MOUNTAIN AREAS OF TAJIKISTAN AND AUSTRIA: A COMPARISON

Mergili, M., Kopf, C., Müllebner, B. and Schneider, J.F., 2012. Changes of the cryosphere and related geohazards in the high‐mountain areas of Tajikistan and Austria: a comparison. Geografiska Annaler: Series A, Physical Geography, 93, 79–96. doi:10.1111/j.1468‐0459.2011.00450.x ABSTRACT This paper quantifies recent glacier changes and possible future permafrost retreat in the Austrian Alps and the Pamir and Alai Mountains of Tajikistan (Central Asia), two mountainous areas with striking differences in climate and hypsometry, but also in economy and research history. The aim of the comparative study is to improve the understanding of regional differences as a baseline for further research and for a differentiated evaluation of possible socio‐economic implications. Besides a review of the available literature, multi‐temporal remote sensing of glaciers of selected areas as well as additional helicopter and field surveys were conducted. The Tajik glaciers displayed a differentiated behaviour during the investigation period 1968–2009, with a strong trend to retreat – at least since 2002. More than 100 pro‐ and supraglacial lakes have been forming or growing in the southwestern Pamir. Destructive outburst floods of such lakes have occurred there in the recent past. Almost all Austrian glaciers are in an advanced stage of retreat, a trend which continues at enhanced rates. Comparatively few glacial lakes exist in the direct forefields of the glaciers. Potential permafrost distribution maps for the present and the future were produced for Tajikistan and Austria by adapting an empirical model developed in Switzerland. In absolute terms, the highest loss was predicted for the Pamir. The expected relative loss in the same area is moderate compared to the rest of Tajikistan and particularly to Austria, where the model predicted the disappearance of more than 90% of the potential permafrost until the end of the twenty‐first century.

How well can we simulate complex hydro-geomorphic process chains? The 2012 multi-lake outburst flood in the Santa Cruz Valley (Cordillera Blanca, Perú): How well can we simulate complex hydro-geomorphic process chains?

Abstract Changing high‐mountain environments are characterized by destabilizing ice, rock or debris slopes connected to evolving glacial lakes. Such configurations may lead to potentially devastating sequences of mass movements (process chains or cascades). Computer simulations are supposed to assist in anticipating the possible consequences of such phenomena in order to reduce the losses. The present study explores the potential of the novel computational tool r.avaflow for simulating complex process chains. r.avaflow employs an enhanced version of the Pudasaini (2012) general two‐phase mass flow model, allowing consideration of the interactions between solid and fluid components of the flow. We back‐calculate an event that occurred in 2012 when a landslide from a moraine slope triggered a multi‐lake outburst flood in the Artizón and Santa Cruz valleys, Cordillera Blanca, Peru, involving four lakes and a substantial amount of entrained debris along the path. The documented and reconstructed flow patterns are reproduced in a largely satisfactory way in the sense of empirical adequacy. However, small variations in the uncertain parameters can fundamentally influence the behaviour of the process chain through threshold effects and positive feedbacks. Forward simulations of possible future cascading events will rely on more comprehensive case and parameter studies, but particularly on the development of appropriate strategies for decision‐making based on uncertain simulation results.

Does parameterization influence the performance of slope stability model results? A case study in Rio de Janeiro, Brazil

We produce factor of safety (FOS) and slope failure susceptibility index (SFSI) maps for a 4.4-km2 study area in Rio de Janeiro, Brazil, in order to explore the sensitivity of the geotechnical and geohydraulic parameterization on the model outcomes. Thereby, we consider parameter spaces instead of combinations of discrete values. SFSI is defined as the fraction of tested parameter combinations within a given space yielding FOS <1. We repeat our physically based calculations for various parameter spaces, employing the infinite slope stability model and the sliding surface model of the software r.slope.stability for testing the geotechnical parameters and the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model (TRIGRS) for testing the geohydraulic parameters. Whilst the results vary considerably in terms of their conservativeness, the ability to reproduce the spatial patterns of the observed landslide release areas is relatively insensitive to the variation of the parameterization as long as there is sufficient pattern in the results. We conclude that landslide susceptibility maps yielded by catchment-scale physically based models should not be interpreted in absolute terms and suggest that efforts to develop better strategies for dealing with the uncertainties in the spatial variation of the key parameters should be given priority in future slope stability modelling efforts.

GIS-Based Deterministic Analysis of Deep-Seated Slope Stability in a Complex Geological Setting

The r.slope.stability computer model evaluates the slope stability for large areas making use of a modification of the three-dimensional sliding surface model proposed by Hovland and revised and extended by Xie and co-workers. The initial version of the model was modified both to reduce computing time (parallel processing of tiles) and to explore the possibilities to perform slope stability modelling in a complex geological setting. The model was applied to the 10 km2 Ripoli area in Umbria, central Italy to demonstrate the importance of the setting of the geological layers as well as of the seepage direction of the groundwater for the model outcome of deep-seated slope stability modelling. Parallel processing allows reducing the computing time by approx. one order of magnitude.

Process Chain Modelling with r.avaflow: Lessons Learned for Multi-hazard Analysis

Open image in new window Multi-hazard configurations—including chains or interactions of landslide processes—have increasingly concerned scientists and practitioners in the last years. However, theoretical concepts have not yet fully evolved to effective modelling strategies suitable for anticipating the occurrence of particular multi-hazard events in space and time. The two-phase mass flow simulation tool r.avaflow would facilitate such a task. We employ r.avaflow along with a generic landscape including an initial landslide release mass, a reservoir, an erodible dam, a canyon with erodible bed and a horizontal plane in the foreland in order to analyze scenarios of process chains triggered by the release of the initial landslide. The analysis demonstrates that the simulation results are highly sensitive to changes in the initial conditions (release volumes), and the material parameters such as basal friction angle or entrainment coefficient. Minor parameter changes may lead to a complete change in the characteristics of the process chain due to threshold effects (dam overtopping) and strong positive feedbacks (entrainment of the dam and increased outflow). Since the parameters tested are often highly uncertain in real-world cases, we conclude that forward predictions of process chains are susceptible to failure unless (i) the system under investigation is well known; (ii) the parameter sets are derived from thorough back-calculations of well-documented events; and (iii) appropriate strategies to express the uncertainty of the results are applied. Whilst these criteria are relevant for all types of landslide processes, they are more important, but also more challenging to implement for process chains and other types of multi-hazard processes due to (i) their higher level of complexity; and (ii) their lower frequency (few reference cases).

Probabilistic landslide ensemble prediction systems: lessons to be learned from hydrology

Landslide forecasting and early warning has a long tradition in landslide research and is primarily carried out based on empirical and statistical approaches, e.g., landslidetriggering rainfall thresholds. In the last decade, flood forecasting started the operational mode of so-called ensemble prediction systems following the success of the use of ensembles for weather forecasting. These probabilistic approaches acknowledge the presence of unavoidable variability and uncertainty when larger areas are considered and explicitly introduce them into the model results. Now that highly detailed numerical weather predictions and high-performance computing are becoming more common, physically based landslide forecasting for larger areas is becoming feasible, and the landslide research community could benefit from the experiences that have been reported from flood forecasting using ensemble predictions. This paper reviews and summarizes concepts of ensemble prediction in hydrology and discusses how these could facilitate improved landslide forecasting. In addition, a prototype landslide forecasting system utilizing the physically based TRIGRS (Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability) model is presented to highlight how such forecasting systems could be implemented. The paper concludes with a discussion of challenges related to parameter variability and uncertainty, calibration and validation, and computational concerns.

Gridded precipitation mapping in mountainous terrain combining GRASS and R

The article deals with the generation of gridded regional-scale precipitation maps for the mountainous Tyrol region (Eastern Alps), covering an area of 39,600 km2. The authors consider mean annual and seasonal precipitation for the period 1961–1990. The input data were collected from 533 rain gauges. To strengthen the sparse high-elevation data network, the precipitation at the equilibrium line altitude (ELA) of glaciers was calculated using an empirical temperature-precipitation relationship. For the interpolation from points to grid cells the authors developed and applied the open source algorithm gradgrid4, combining GRASS GIS and R functions. The computation of mean annual precipitation for each cell includes (1) calculating local averages of precipitation and elevation, (2) calculating the local vertical precipitation gradient, and (3) combining the results of (1) and (2) to generate a precipitation map at a cell size of 250 m. Mean seasonal precipitation was computed from the percentage of mean annual precipitation for each season. The modelled mean annual precipitation for 86.1% of the evaluated data points ranges within ±20% of the observed values. They authors conclude that gradgrid4 is highly suitable for regional-scale gridded precipitation mapping in mountain areas, given a sufficiently dense network of high-elevation data points.

Three-Dimensional Modelling of Rotational Slope Failures with GRASS GIS

Landslides starting from unstable slopes threat people, buildings and infrastructures all over the world and are therefore intensively studied. On the one hand, engineers use sophisticated models to identify hazardous slopes, mostly based on longitudinal sections. On the other hand, less sophisticated infinite slope stability models are used in combination with Geographic Information Systems (GIS) in order to cover larger areas. The present paper describes an attempt to combine these two philosophies and to come up with a spatially distributed, three-dimensional model for slope stability going beyond the widely used infinite slope stability concept. Both models are applied to artificial topographies in order to compare the outcomes of different slip surface assumptions and to benchmark the validity of the infinite slope stability model. It was found out that the resulting factor of safety is highly sensitive to the type of model used and to the slip surface geometry. In complex terrain, the performance of the infinite slope stability model strongly depends on the specific situation, particularly on slope curvature and slip surface depth.