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., landslide-triggering 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.</p

A strategy for GIS-based 3-D slope stability modelling over large areas

Abstract. GIS-based deterministic models may be used for landslide susceptibility mapping over large areas. However, such efforts require specific strategies to (i) keep computing time at an acceptable level, and (ii) parameterize the geotechnical data. We test and optimize the performance of the GIS-based, 3-D slope stability model r.slope.stability in terms of computing time and model results. The model was developed as a C- and Python-based raster module of the open source software GRASS GIS and considers the 3-D geometry of the sliding surface. It calculates the factor of safety (FoS) and the probability of slope failure (Pf) for a number of randomly selected potential slip surfaces, ellipsoidal or truncated in shape. Model input consists of a digital elevation model (DEM), ranges of geotechnical parameter values derived from laboratory tests, and a range of possible soil depths estimated in the field. Probability density functions are exploited to assign Pf to each ellipsoid. The model calculates for each pixel multiple values of FoS and Pf corresponding to different sliding surfaces. The minimum value of FoS and the maximum value of Pf for each pixel give an estimate of the landslide susceptibility in the study area. Optionally, r.slope.stability is able to split the study area into a defined number of tiles, allowing parallel processing of the model on the given area. Focusing on shallow landslides, we show how multi-core processing makes it possible to reduce computing times by a factor larger than 20 in the study area. We further demonstrate how the number of random slip surfaces and the sampling of parameters influence the average value of Pf and the capacity of r.slope.stability to predict the observed patterns of shallow landslides in the 89.5 km2 Collazzone area in Umbria, central Italy

70 years of lake evolution and glacial lake outburst floods in the Cordillera Blanca (Peru) and implications for the future

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordData availability: Data are available on request from the corresponding author.Climate change, glacier retreat and glacial lake outburst floods (GLOFs) are intertwined. The Cordillera Blanca in Peru has one of the world's longest GLOF records and here we assess the evolution of glacial lakes in the region between 1948 and 2017 and investigate the links to documented GLOFs. We also model future lake evolution under two climate scenarios to provide an assessment of current and future GLOF triggering potential. Our analysis shows that the number of lakes as well as the total lake area has increased during the historical period. The formation of new lakes is, however, not uniform among different lake types with bedrock-dammed lakes exhibiting the largest increase in recent decades. We argue that moraine-dammed lakes have already formed at the majority of potential locations in the Cordillera Blanca and that the next generation of lakes which are expected to form in response to glacier retreat over topographically suitable areas will be predominantly bedrock-dammed. Based on a regional GLOF inventory, we show that the peak frequency of GLOFs occurred from the late 1930s to early 1950s. While GLOFs originating from moraine-dammed lakes dominated in this period, recent GLOFs have originated from bedrock-dammed lakes. At the same time, the majority of GLOFs originated from lakes in a proglacial phase (i.e. in contact with glacier), even though the share of proglacial lakes did not exceed 12% at any time step during the analysed period. While many moraine-dammed lakes evolved into the glacier-detached evolutionary phase, bedrock-dammed lakes became a major lake dam type among proglacial lakes. Over the remainder of the 21st century, a further increase in lake area of up to 10% is anticipated, with up to 50 new bedrock dammed lakes likely to develop as glaciers retreat. There is little difference in lake development and GLOF triggering potential under climate scenarios driven by RCP 2.6 and 8.5. Based on topographic disposition, recent and future lakes do not individually appear more or less susceptible to landslide impact than lakes that already developed earlier in the 20th century. Synthesizing these findings, we forecast that bedrock-dammed lakes will become the dominant source of GLOFs in the next decades. Because such dams are inherently more stable, we expect overall lower GLOF magnitudes compared to documented GLOFs from moraine-dammed lakes.Ministry of Education, Youth and Sports of the Czech RepublicCzech Academy of SciencesSwiss Agency for Development and Cooperation (SDC)Swiss National Science FoundationRCUK-CONICY

A massive rock and ice avalanche caused the 2021 disaster at Chamoli, Indian Himalaya

On 7 Feb 2021, a catastrophic mass flow descended the Ronti Gad, Rishiganga, and Dhauliganga valleys in Chamoli, Uttarakhand, India, causing widespread devastation and severely damaging two hydropower projects. Over 200 people were killed or are missing. Our analysis of satellite imagery, seismic records, numerical model results, and eyewitness videos reveals that ~27x106 m3 of rock and glacier ice collapsed from the steep north face of Ronti Peak. The rock and ice avalanche rapidly transformed into an extraordinarily large and mobile debris flow that transported boulders &gt;20 m in diameter, and scoured the valley walls up to 220 m above the valley floor. The intersection of the hazard cascade with downvalley infrastructure resulted in a disaster, which highlights key questions about adequate monitoring and sustainable development in the Himalaya as well as other remote, high-mountain environments

Vegetation and vegetation-environment relationships at Grootbos Nature Reserve, Western Cape, South Africa

The private Grootbos Nature Reserve is located at the Western edge of the Agulhas Plain in the Cape Floristic Region of South Africa, an area characterized by high habitat and floristic diversity. The Reserve is covered in near-natural fynbos shrublands with a few patches of forest and wetland. The main objective of this study was to classify the vegetation into discrete units and relate them to the prevailing environmental conditions. The vegetation was analysed by numerical means (TWINSPAN, DC A, CCA) and mapped on GIS. At the vegetation type level. Forest & Thicket and Fynbos formed distinctive clusters, whereas the wetland releves were intermixed, but without relationships to one of these units. Fire incidence served as the major determinant of the forest-fynbos boundary. The Forest & Thicket grouping was separated into Thicket (as transitional to fynbos), Afromontane Forest and Milkwood Scrub Forest. Two broad complexes were distinguished within the Fynbos grouping, the Alkaline Sand Fynbos Complex corresponding to Coastal Fynbos. and the Acid Sand Fynbos Complex corresponding to Mountain Fynbos. They discriminated along gradients of pH. soil depth and rock cover. The complexes were further subdivided into formations by using one or a few subjectively chosen dominant species as indicators. The transitions between these formations were rather continuous than discrete. The vegetation type and complex levels correspond well to existing fynbos-wide classifications. Comparing the formations to the results of other vegetation studies is problematic even on the scale of the Agulhas Plain, due to the high regional plant diversity in the Fynbos Biome

Regional-scale analysis of lake outburst hazards in the southwestern Pamir, Tajikistan, based on remote sensing and GIS

This paper presents an analysis of the hazards emanating from the sudden drainage of alpine lakes in South-Western Tajik Pamir. In the last 40 yr, several new lakes have formed in the front of retreating glacier tongues, and existing lakes have grown. Other lakes are dammed by landslide deposits or older moraines. In 2002, sudden drainage of a glacial lake in the area triggered a catastrophic debris flow. Building on existing approaches, a rating scheme was devised allowing quick, regional-scale identification of potentially hazardous lakes and possible impact areas. This approach relies on GIS, remote sensing and empirical modelling, largely based on medium-resolution international datasets. Out of the 428 lakes mapped in the area, 6 were rated very hazardous and 34 hazardous. This classification was used for the selection of lakes requiring in-depth investigation. Selected cases are presented and discussed in order to understand the potentials and limitations of the approach used. Such an understanding is essential for the appropriate application of the methodology for risk mitigation purposes

Regional-scale analysis of high-mountain multi-hazard and risk indicators in the Pamir (Tajikistan) with GRASS GIS

We present a model framework for the regional-scale analysis of high-mountain multi-hazard and -risk indicators, implemented with the open-source software package GRASS GIS. This framework is applied to a 98 300 km2 study area centred in the Pamir (Tajikistan). It includes (i) rock slides, (ii) ice avalanches, (iii) periglacial debris flows and (iv) lake outburst floods. First, a hazard indicator is assigned to each relevant object (steep rock face, glacier or periglacial slope, lake). This indicator depends on the susceptibility and on the possible event magnitude. Second, the possible travel distances, impact areas and, consequently, impact hazard indicators for all types of processes are computed using empirical relationships. The impact hazard indicators are finally superimposed with an exposure indicator derived from the type of land use, resulting in a raster map of risk indicators finally discretized at the community level. The analysis results are presented and discussed at different spatial scales. The major outcome of the study, a set of comprehensive regional-scale hazard and risk indication maps, shall represent an objective basis for the prioritization of target communities for further research and risk mitigation measures

r.randomwalk v1, a multi-functional conceptual tool for mass movement routing

We introduce r.randomwalk, a flexible and multi-functional open-source tool for backward and forward analyses of mass movement propagation. r.randomwalk builds on GRASS GIS (Geographic Resources Analysis Support System – Geographic Information System), the R software for statistical computing and the programming languages Python and C. Using constrained random walks, mass points are routed from defined release pixels of one to many mass movements through a digital elevation model until a defined break criterion is reached. Compared to existing tools, the major innovative features of r.randomwalk are (i) multiple break criteria can be combined to compute an impact indicator score; (ii) the uncertainties of break criteria can be included by performing multiple parallel computations with randomized parameter sets, resulting in an impact indicator index in the range 0–1; (iii) built-in functions for validation and visualization of the results are provided; (iv) observed landslides can be back analysed to derive the density distribution of the observed angles of reach. This distribution can be employed to compute impact probabilities for each pixel. Further, impact indicator scores and probabilities can be combined with release indicator scores or probabilities, and with exposure indicator scores. We demonstrate the key functionalities of r.randomwalk for (i) a single event, the Acheron rock avalanche in New Zealand; (ii) landslides in a 61.5 km2 study area in the Kao Ping Watershed, Taiwan; and (iii) lake outburst floods in a 2106 km2 area in the Gunt Valley, Tajikistan

Causas, características e impacto de los procesos de remoción en masa, en áreas contrastantes de la región Andina

In the Andean region, landslides are common geomorphological agents that can cause disasters. The occurrence and properties of landslides in this region are determined by the interactions of several geological, topographic and climatic factors as well as by anthropogenic activities. A better understanding of the characteristics of landslides can be obtained from comparative studies on climatic, geomorphological and socioeconomic issues. Colombia, which has a tropical, wet climate and a high population density, has one of the highest landslide risks in the world. These landslides are induced by displacements and flows caused by La Niña or the activity of glaciated volcanoes; in contrast, in central-western Argentina, which is arid and sparsely populated, landslides are triggered by rock falls and debris flows\ud and are generally associated with El Niño