Potential Release Areas Research Articles

AutoATES v2.0: Automated Avalanche Terrain Exposure Scale mapping

Abstract. Avalanche risk assessment is complex and challenging, with terrain assessment as one of the most fundamental factors. To aid people's terrain assessment, Parks Canada developed the Avalanche Terrain Exposure Scale (ATES), a system that classifies the severity of avalanche terrain into five classes from non-avalanche terrain to extreme terrain. Manual classification is laborious and dependent on expert's assessments. To ease the process Larsen et al. (2020) developed an automated ATES model (AutoATES v1.0). Although the model allowed large-scale mapping, it had some significant limitations. This paper presents an improved AutoATES v2.0 model improving the potential release area (PRA) model, utilizing the new Flow-Py runout simulation package. Furthermore, it incorporates forest density data in the PRA, in Flow-Py, and in a newly developed post-forest-classification step. AutoATES v2.0 has also been rewritten in open-source software, making it more widely available. The paper includes a validation of the model measured against two consensus maps made by three experts at two different locations in western Canada. For Bow Summit, the F1 score (a measure of how well the model performs) improved from 64 % to 77 %. For Connaught Creek, the F1 score improved from 40 % to 71 %. The main challenge limiting large-scale ATES classification is the determination of optimal input parameters for different regions and climates. In areas where AutoATES v2.0 is applied, it can be a valuable tool for avalanche risk assessment and decision-making. Ultimately, our goal is for AutoATES v2.0 to enable efficient, regional-scale, and potentially global ATES mapping in a standardized manner rather than based solely on expert judgment.

GIS-based determination of potential snow avalanche areas: A case study of Rize Province of Türkiye

Natural hazards are a part of critical issues affecting people and the environment. One of these natural hazards is snow avalanches. With the increase in the world population, it has emerged that decision-makers should take precautions against such natural hazards for population movements, construction, transportation, and tourism. Essential solution parts of this problem lay behind surveying, GIS, and spatial analysis-planning. This situation will be primarily due to the snow conditions, but certain terrain areas are susceptible. Snow avalanches' release mechanism depends on many factors, such as terrain, meteorological reports, snowpack, and other triggering parameters. Areas with certain topographical features that allow the deposition of snow masses are called avalanche-release areas. GIS helps to make decisions concerning spatial planning within avalanche release areas and finding risky zones. This study aimed to determine the potential avalanche release areas in the GIS environment in Rize, Türkiye, which was chosen as the pilot region. In the study, the detection of these avalanche areas was estimated using a mathematical equation model proposed by Hreško (1998) and determined with the help of GIS. Factors such as elevation, curvature, aspect, slope, and land cover type were used to estimate avalanche risk areas. A Model Builder workflow has also been created to automate the process stages. As a result of the study, avalanche risk areas were determined and mapped for the Rize mountainous region.

Mapping release and propagation areas of permafrost-related rock slope failures in the French Alps: A new methodological approach at regional scale

Rock slope failure (RSF) from permafrost-affected rockwall is an emerging threat for human lives and infrastructure which raises a need for RSF hazard assessments in the alpine environment. This study proposes the first mapping approach to RSF release and propagation areas in the French Alps.By analysing a unique RSF database (1389 recent events in the Mont Blanc massif), we determine three levels of RSF Susceptibility Indexes (RSI) to map the potential release areas. We highlight a strong correlation between RSF and permafrost: 99 % of RSFs occurred from rockwalls with a Mean Annual Rock Surface Temperature (MARST) ≤ 3 °C and 35 % with MARST from −2 to 0 °C.The release area maps (34 km2 to 284 km2 depending on the RSI) are entered into a simple propagation model (RockavELA), using a dimensionless area-based energy line principle (i.e. reach susceptibility) to map propagation areas of potential RSFs. Three propagation limits are proposed, fitting the propagation characteristics of another RSF database containing 3497 events observed across the European Alps with heterogeneous propagation substrates, and merged with 48 additional events from high mountains in the French Alps. RockavELA reproduced the runout extent of 20 high mountain RSFs with <50 % of frontal and lateral error. Output maps show little sensitivity to the propagation limits (<25 % difference between the high and low propagation limits).This work is a preliminary step to identify potential hazard hot spots in the French Alps, and proposes a novel approach that could be applied in other mountain ranges.

Integrating biogeographic approach into classical biological control: Assessing the climate matching and ecological niche overlap of two natural enemies against common ragweed in China

Plant invasion is considered a high priority threat to biodiversity, ecosystems, the environment, and human health worldwide. Classical biological control (biocontrol) is a generally safer and more environmentally benign measure than chemical controls in managing invasive alien plants (IAPs). However, the impacts of climate change and the importance of climate matching in ensuring the efficiency of biocontrol candidates in controlling IAPs are likely to be underestimated. Here, based on the ensemble model and n-dimensional hypervolumes concepts, we estimated the overlapping areas between Ambrosia artemisiifolia and its two most effective natural enemies (Ophraella communa and Epiblema strenuana) under climate change in China. Moreover, we compared their ecological niches, further assessing the impact of climate change on the efficiency of two natural enemies in controlling A. artemisiifolia in China. We found that the potentially suitable areas of the two natural enemies and A. artemisiifolia were primarily influenced by temperature and human influence index variables. Under near-current climate, the overlapping area between O. communa and A. artemisiifolia was the largest, followed by E. strenuana and A. artemisiifolia, and both two natural enemies and A. artemisiifolia. The ecological niche between A. artemisiifolia and O. communa was most similar (0.64), followed by A. artemisiifolia and E. strenuana (0.55). The separate control (the niche separation areas of the two natural enemies against A. artemisiifolia) and joint-control (the niche overlap areas of the two natural enemies against A. artemisiifolia) efficiencies of the two natural enemies against A. artemisiifolia will both increase in future climates (the 2030s and 2050s) in northern and northeastern China. Our findings demonstrate a new approach to assess control efficiency and screen potential release areas of two natural enemies against A. artemisiifolia in China without the need for actual field release or experimentation. Moreover, our findings provide important clues for ensuring the classical biocontrol of IAPs worldwide.

Large-scale risk assessment on snow avalanche hazard in alpine regions

Abstract. Snow avalanches are recurring natural hazards that affect the population and infrastructure in mountainous regions, such as in the recent avalanche winters of 2018 and 2019, when considerable damage was caused by avalanches throughout the Alps. Hazard decision makers need detailed information on the spatial distribution of avalanche hazards and risks to prioritize and apply appropriate adaptation strategies and mitigation measures and thus minimize impacts. Here, we present a novel risk assessment approach for assessing the spatial distribution of avalanche risk by combining large-scale hazard mapping with a state-of-the-art risk assessment tool, where risk is understood as the product of hazard, exposure and vulnerability. Hazard disposition is modeled using the large-scale hazard indication mapping method RAMMS::LSHIM (Rapid Mass Movement Simulation::Large-Scale Hazard Indication Mapping), and risks are assessed using the probabilistic Python-based risk assessment platform CLIMADA, developed at ETH Zürich. Avalanche hazard mapping for scenarios with a 30-, 100- and 300-year return period is based on a high-resolution terrain model, 3 d snow depth increase, automatically determined potential release areas and protection forest data. Avalanche hazard for 40 000 individual snow avalanches is expressed as avalanche intensity, measured as pressure. Exposure is represented by a detailed building layer indicating the spatial distribution of monetary assets. The vulnerability of buildings is defined by damage functions based on the software EconoMe, which is in operational use in Switzerland. The outputs of the hazard, exposure and vulnerability analyses are combined to quantify the risk in spatially explicit risk maps. The risk considers the probability and intensity of snow avalanche occurrence, as well as the concentration of vulnerable, exposed buildings. Uncertainty and sensitivity analyses were performed to capture inherent variability in the input parameters. This new risk assessment approach allows us to quantify avalanche risk over large areas and results in maps displaying the spatial distribution of risk at specific locations. Large-scale risk maps can assist decision makers in identifying areas where avalanche hazard mitigation and/or adaption is needed.

Development and evaluation of a method to identify potential release areas of snow avalanches based on watershed delineation

Abstract. Snow avalanches are a prevalent threat in mountain territories. Large-scale mapping of avalanche-prone terrain is a prerequisite for land-use planning where historical information about past events is insufficient. To this aim, the most common approach is the identification of potential release areas (PRAs) followed by numerical avalanche simulations. Existing methods for identifying PRAs rely on terrain analysis. Despite their efficiency, they suffer from (i) a lack of systematic evaluation on the basis of adapted metrics and past observations over large areas and (ii) a limited ability to distinguish PRAs corresponding to individual avalanche paths. The latter may preclude performing numerical simulations corresponding to individual avalanche events, questioning the realism of resulting hazard assessments. In this paper, a method that accurately identifies individual snow avalanche PRAs based on terrain parameters and watershed delineation is developed, and confusion matrices and different scores are proposed to evaluate it. Comparison to an extensive cadastre of past avalanche limits from different massifs of the French Alps used as ground truth leads to true positive rates (recall) between 80 % and 87 % in PRA numbers and between 92.4 % and 94 % in PRA areas, which shows the applicability of the method to the French Alps context. A parametric study is performed, highlighting the overall robustness of the approach and the most important steps/choices to maximize PRA detection, among which the important role of watershed delineation to identify the right number of individual PRAs is highlighted. These results may contribute to better understanding avalanche hazard in the French Alps. Wider outcomes include an in-depth investigation of the issue of evaluating automated PRA detection methods and a large data set that could be used for additional developments, and to benchmark existing and/or new PRA detection methods.

Automated snow avalanche release area delineation in data-sparse, remote, and forested regions

Abstract. Potential avalanche release area (PRA) modeling is critical for generating automated avalanche terrain maps which provide low-cost, large-scale spatial representations of snow avalanche hazard for both infrastructure planning and recreational applications. Current methods are not applicable in mountainous terrain where high-resolution (≤5 m) elevation models are unavailable and do not include an efficient method to account for avalanche release in forested terrain. This research focuses on expanding an existing PRA model to better incorporate forested terrain using satellite imagery and presents a novel approach for validating the model using local expertise, thereby broadening its application to numerous mountain ranges worldwide. The study area of this research is a remote portion of the Columbia Mountains in southeastern British Columbia, Canada, which has no pre-existing high-resolution spatial datasets. Our research documents an open-source workflow to generate high-resolution digital elevation models (DEMs) and forest land cover datasets using optical satellite data processing. We validate the PRA model by collecting a polygon dataset of observed potential release areas from local guides, using a method which accounts for the uncertainty in human recollection and variability in avalanche release. The validation dataset allows us to perform a quantitative analysis of the PRA model accuracy and optimize the PRA model input parameters to the snowpack and terrain characteristics of our study area. Compared to the original PRA model our implementation of forested terrain and local optimization improved the percentage of validation polygons accurately modeled by 11.7 percentage points and reduced the number of validation polygons that were underestimated by 14.8 percentage points. Our methods demonstrate substantial improvement in the performance of the PRA model in forested terrain and provide means to generate the requisite input datasets and validation data to apply and evaluate the PRA model in vastly more mountainous regions worldwide than was previously possible.

Runout modelling and hazard assessment of Tangni debris flow in Garhwal Himalayas, India

Debris flows are frequently occurring natural processes in geologically complex terrains of the Indian Himalayas. Debris flow runout modelling leading to hazard assessment is essential for planning, designing, and execution of mitigation measures. In the present context, debris flow hazard assessment has been carried out for the Tangni debris flow in Garhwal Himalayas, India. Runout modelling was carried out using a Voellmy model-based 3D numerical simulation for estimation of flow intensity parameters such as runout distance, flow velocity, height and pressure along the propagation path. For calibration of the model inputs, back analysis of Tangni debris flow event that occurred in 2013, with its known runout length and deposition volume as the criteria, has been conducted. The best calibrated values of frictional parameters are obtained at μ = 0.10 and ξ = 400 m/s2. Using the best calibrated values of frictional parameters, hazard assessment was carried out for two potential release areas separately, with different initial volumes, and in combination to derive the probable runout distance along with other flow intensity parameters for different scenarios that may happen in the future. It has been observed that this debris flow scenario including the combination of two potential release areas will block the Alaknanda River, forming a landslide dam with a probable height of 6 m. Debris flow runout modelling-based hazard assessment will be helpful in determining quantitative information on flow intensity parameters, where complete data on past events are generally not available or were not possible to capture for the Indian Himalayan region.

Monitoring the Preonzo Rock Slope Instability Using Resonance Mode Analysis

AbstractReliable monitoring of unstable rock slopes is a prerequisite for successful mitigation of landslide hazards. However, most state‐of‐the art techniques rely on measuring the local surface displacement in the potential release area. In contrast, recording ambient vibration data allows for analyzing structural dynamic parameters of the unstable slope, such as resonance frequency, polarization of vibration, and energy dissipation. These parameters can be linked to properties of the instability, for example, to rock stiffness and fracture network orientation. We developed a processing method for continuous seismic data based on enhanced frequency domain decomposition modal analysis and applied it to the unstable rock slope Preonzo in Switzerland (∼140,000 m3). Four years of ambient vibration data recorded at two permanent seismometers on the instability were analyzed, providing the resonance frequency, damping ratio, and normal mode shapes of the fundamental (∼3.5 Hz) and the first higher (∼4.2 Hz) vibrational mode. We found that modal analysis can be reliably used to monitor the dynamic response of an unstable rock slope. We observed annual changes of all parameters with a damping ratio varying between 6.0% and 9.7% for the fundamental mode. The dynamic parameters appear to be primarily driven by temperature and only secondarily by opening and closing of fractures. No large slope failure was registered during the observation period. However, the data provide a baseline model for ongoing slope monitoring to recognize structural changes before a future collapse. The setup proposed builds a complementary monitoring system to displacement‐based surveying.

Simulation and Analysis of a Snow Avalanche Accident in Lower Western Himalaya, India

In Western Himalaya, an average 49 person die every year due to snow avalanche activities and this death rate is very high as compared to other Asian countries. A snow avalanche accident was observed on 5 January 2018 on Chowkibal–Tangdhar (CT) road axis at avalanche site number CT-8 located near Chowkibal village in Kupwara district, union territory Jammu and Kashmir, India. In the present paper, we discuss snow avalanche simulation, the climatic condition, avalanche debris height and length, and suggested solutions to handle avalanche situations. Rapid Mass MovementS numerical model in combination with digital elevation model and potential release area has been used to simulate avalanche accident occurred on 5 January 2018 at CT-8. The analysis demonstrates maximum snow avalanche velocity, impact of pressure and height of flow to be ~ 25 ms−1, ~ 9.39 × 104 kgm−1 s−2, and ~ 3.0 m respectively on 5 January 2018 at CT-8. Further simulated avalanche debris height and length form road has been validated with ground observed data. Ground reconnaissance of the location was conducted by a team of Snow and Avalanche Study Establishment, Chandigarh and it has been observed that lack of ‘avalanche awareness and Standard Operating Procedures during movement in avalanche prone areas’ among the travellers on the road cause accident . The present paper seems to be first to investigate snow avalanche accident in Western Himalaya and recommend that proper campaigning of avalanche awareness among the people residing in avalanche prone areas of Himalaya could reduce such accidents significantly.

Developing nationwide avalanche terrain maps for Norway

Snow avalanches are a significant natural hazard in Norway. One method to manage the backcountry avalanche hazard is through detailed mapping of avalanche terrain. Avalanche terrain can be mapped using a variety of methods, including using the Avalanche Terrain Exposure Scale (ATES); however, manual classification of terrain using ATES is time consuming. This study has developed and compared a fully automated algorithm to provide ATES mapping for all of Norway. Our new algorithm is based on the technical model for ATES mapping. This model has specific terrain-based thresholds that can be applied for automated terrain-based modeling. Our algorithm expands on prior work by including the potential release area (PRA) model to identify and calculate the likelihood of an avalanche releasing from a start zone. We also use the raster-based TauDEM-model to determine the avalanche runout length. The final product is a 10-m resolution ATES map. We compared this nationwide ATES map with areas that have been manually mapped by avalanche experts, and find that the automated approach yields similar and reliable results. In addition to comparing mapped areas, we also examine manually mapped linear routes and compare these with the automated mapped ATES areas. Our results suggest that for open terrain, the vast majority of the manually classified tracks are predominantly in the same ATES class as our algorithm. For forested areas, we get mixed results, which can be attributed to a lack of suitable vegetation data at an appropriate scale. Despite this limitation, the current ATES algorithm and resulting spatial data are already valuable as a large portion (~ 70%) of the Norwegian backcountry terrain is above tree line. The automated algorithm is also useful to ensure consistent manual classification across different regions in Norway, or globally, and will permit greater reproducibility and easier updating of mapping for the future.

Harmonized mapping of forests with a protection function against rockfalls over European Alpine countries

Forest covers 40% of the European Alpine region and contributes to the protection of human beings and infrastructures against natural hazards such as rockfalls. However, despite the recognition of this ecosystem service, most mountain territories do not have a map of protection forests. When a map exists, it generally depends on data restricted to a limited extent, which prevents any replication or comparison on other areas. The aim of this study is to develop a method using harmonized and open data to produce the first map of protection forests against rockfalls at the European Alpine region scale. Based on these data, we first identified potential rockfall release areas and calibrated the model according to 2812 real rockfall events located around the Alps. Second, 46.5 billion 3-D rockfall propagation simulations, taking into account topography, land use and human assets, were computed on the entire area. Protection forest is defined as being located on at least one rockfall trajectory that had impacted human assets. Our results show that 14% of the forests have a potential protection function against rockfalls in the Alpine Space region. This proportion goes up to 21.5%, if we consider only the core of the Alpine area. 80% of the protection forest area contributes to mitigate rockfall hazard on road network, 55% on buildings and only 6% on railways. This work provides a robust, objective and reproducible method for locating protection forests on a large geographical scale. Such a map may serve as a basis for national and European risk management policies.

How is rockfall risk impacted by land-use and land-cover changes? Insights from the French Alps

Due to intense urban sprawl in rockfall-prone areas, a precise rockfall risk assessment has become a crucial issue for public authorities and stakeholders. In this context, quantitative risk analysis (QRA) procedures, accounting for the specificities of the rockfall process, have been developed. For the last few decades, several studies have examined the impacts of global warming on rockfall activity, especially at high-altitude sites. However, the influence of land-use and land-cover (LULC) changes, very frequent at lower altitudes and in the vicinity of urbanised areas, on rockfall propagation and associated risks has received little attention.This study proposes a holistic QRA on a municipality scale (the municipality of Crolles, in the French Alps) that includes both all the potential release areas at the whole cliff scale and a wide spectrum of rockfall volumes randomly extracted from volume classes distributed between 1 and 20 m(3). In addition, to quantify precisely the effect of LULC changes on rockfall risk, four characteristic scenarios representative of LULC changes observed in the municipality and more generally in the Alps since the mid-19th century, have been included in the analysis.The results demonstrate the significant impacts of landscape reorganisation on the spatial distribution of risk with increasing forest cover, which can be counterbalanced by evolving LULC in a transition unit located between the forest strip and the urban front. They also evidence that a large proportion of the risk is explained by small block volumes, which are the most affected by landscape structure and evolution. From a practical point of view, and despite several uncertainties related to different modelling assumptions, the results reported herein clearly demonstrate the applicability and the value of QRA for rockfall risk management at a municipality scale in a context of rapid and intense environmental changes.

Automated snow avalanche release area delineation – validation of existing algorithms and proposition of a new object-based approach for large-scale hazard indication mapping

Abstract. Snow avalanche hazard is threatening people and infrastructure in all alpine regions with seasonal or permanent snow cover around the globe. Coping with this hazard is a big challenge and during the past centuries, different strategies were developed. Today, in Switzerland, experienced avalanche engineers produce hazard maps with a very high reliability based on avalanche database information, terrain analysis, climatological data sets and numerical modeling of the flow dynamics for selected avalanche tracks that might affect settlements. However, for regions outside the considered settlement areas such area-wide hazard maps are not available mainly because of the too high cost, in Switzerland and in most mountain regions around the world. Therefore, hazard indication maps, even though they are less reliable and less detailed, are often the only spatial planning tool available. To produce meaningful and cost-effective avalanche hazard indication maps over large regions (regional to national scale), automated release area delineation has to be combined with volume estimations and state-of-the-art numerical avalanche simulations. In this paper we validate existing potential release area (PRA) delineation algorithms, published in peer-reviewed journals, that are based on digital terrain models and their derivatives such as slope angle, aspect, roughness and curvature. For validation, we apply avalanche data from three different ski resorts in the vicinity of Davos, Switzerland, where experienced ski-patrol staff have mapped most avalanches in detail for many years. After calculating the best fit input parameters for every tested algorithm, we compare their performance based on the reference data sets. Because all tested algorithms do not provide meaningful delineation between individual PRAs, we propose a new algorithm based on object-based image analysis (OBIA). In combination with an automatic procedure to estimate the average release depth (d0), defining the avalanche release volume, this algorithm enables the numerical simulation of thousands of avalanches over large regions applying the well-established avalanche dynamics model RAMMS. We demonstrate this for the region of Davos for two hazard scenarios, frequent (10–30-year return period) and extreme (100–300-year return period). This approach opens the door for large-scale avalanche hazard indication mapping in all regions where high-quality and high-resolution digital terrain models and snow data are available.

Estimating the number of airports potentially contaminated with perfluoroalkyl and polyfluoroalkyl substances from aqueous film forming foam: A Canadian example

Assessing the extent to which emerging contaminants (ECs) such as perfluoroalkyl and polyfluoroalkyl substances (PFAS) have been released into the environment is one of the foundations for developing effective management and remediation strategies for impacted sites. PFAS are known to have caused the contamination of soil, groundwater, and surface water as a result of aqueous film forming foam (AFFF) being accidentally or intentionally released into the environment. To date, the scope of the issue has not been evaluated in Canada. In this study we developed a framework, in the form of a decision tree, to estimate the number of potentially PFAS impacted airport sites in Canada as a result of AFFF releases. The screening process was completed using publicly available resources including airport websites, the Canadian Owners and Pilots Association website, Sky Vector, Transport Safety Board of Canada aviation investigation reports, the Aviation Safety Network website, and Google maps. The methodology presented in this study could be used to identify additional PFAS impacted sites in Canada or other jurisdictions worldwide. 2071 airport/heliport sites in Canada were investigated with indications that 152 (7%) of these sites likely have PFAS contamination as a result of the use of AFFF at firefighter training areas (FFTAs) and/or accidents where fires occurred. In addition, another 268 sites (13%) were identified as possibly impacted with PFASs primarily as a result of the location having the ability to store and dispense petroleum products, and therefore having AFFF systems onsite. Surficial geology was also identified for all sites determined to likely have PFAS contamination. An estimated 42.8% had surficial geology composed of sand, 27% had clay, 19.7% organic-based, with the remaining sites found on cryosols or rock. Methodological validation was also completed. The procedure used in this study successfully predicted occurrences of PFAS contamination at 25 sites where contamination, as a result of AFFF use, was confirmed by Canadian governmental departments. For these 25 sites, the distance from potential release areas to the nearest surface water was calculated. Five of the sites were within 200 meters of surface water, 19 were within one kilometer, and all 25 were within 2.5 kilometers. This suggests that surface water may have been historically impacted by PFAS at as many as 152 to 420 different airport locations in Canada.

Potential slab avalanche release area identification from estimated winter terrain: a multi-scale, fuzzy logic approach

Abstract. Avalanche hazard assessment requires a very precise estimation of the release area, which still depends, to a large extent, on expert judgement of avalanche specialists. Therefore, a new algorithm for automated identification of potential avalanche release areas was developed. It overcomes some of the limitations of previous tools, which are currently not often applied in hazard mitigation practice. By introducing a multi-scale roughness parameter, fine-scale topography and its attenuation under snow influence is captured. This allows the assessment of snow influence on terrain morphology and, consequently, potential release area size and location. The integration of a wind shelter index enables the user to define release area scenarios as a function of the prevailing wind direction or single storm events. A case study illustrates the practical usefulness of this approach for the definition of release area scenarios under varying snow cover and wind conditions. A validation with historical data demonstrated an improved estimation of avalanche release areas. Our method outperforms a slope-based approach, in particular for more frequent avalanches; however, the application of the algorithm as a forecasting tool remains limited, as snowpack stability is not integrated. Future research activity should therefore focus on the coupling of the algorithm with snowpack conditions.

Linking snow depth to avalanche release area size: measurements from the Vallée de la Sionne field site

Abstract. One of the major challenges in avalanche hazard assessment is the correct estimation of avalanche release area size, which is of crucial importance to evaluate the potential danger that avalanches pose to roads, railways or infrastructure. Terrain analysis plays an important role in assessing the potential size of avalanche releases areas and is commonly based on digital terrain models (DTMs) of a snow-free summer terrain. However, a snow-covered winter terrain can significantly differ from its underlying, snow-free terrain. This may lead to different, and/or potentially larger release areas. To investigate this hypothesis, the relation between avalanche release area size, snow depth and surface roughness was investigated using avalanche observations of artificially triggered slab avalanches over a period of 15 years in a high-alpine field site. High-resolution, continuous snow depth measurements at times of avalanche release showed a decrease of mean surface roughness with increasing release area size, both for the bed surface and the snow surface before avalanche release. Further, surface roughness patterns in snow-covered winter terrain appeared to be well suited to demarcate release areas, suggesting an increase of potential release area size with greater snow depth. In this context, snow depth around terrain features that serve as potential delineation borders, such as ridges or trenches, appeared to be particularly relevant for release area size. Furthermore, snow depth measured at a nearby weather station was, to a considerable extent, related to potential release area size, as it was often representative of snow depth around those critical features where snow can accumulate over a long period before becoming susceptible to avalanche release. Snow depth – due to its link to surface roughness – could therefore serve as a highly useful variable with regard to potential release area definition for varying snow cover scenarios, as, for example, the avalanche hazard assessment for transport routes or ski resorts.

Rockfall trajectory modeling combined with heuristic analysis for assessing the rockfall hazard along the Maratea SS18 coastal road (Basilicata, Southern Italy)

In this paper, a study aimed to assess the rockfall hazard along a portion of the SS18 coastal road, located in the coastal area of Maratea (Basilicata Region, Southern Italy), is presented. The relevance of this study derives from the location of the study area, because the SS18 is a strategic roads in a touristic area, and, since the hazard assessment was performed in 2004 within a project financed by the Viability Regional Department of Autonomous National Company of Roads (ANAS), from the possibility to validate the results by using real rockfall events occurred after 2004. The procedure for assessing the rockfall hazard was composed of four sequential analyses: (i) geomechanical and kinematic characterization of rock mass, (ii) implementation of Romana’s (1985) Slope Mass Rating (SMR) method for identifying the potential boulder release areas (rockfall initiation areas), (iii) determination of rockfall trajectories by using a 3D numerical model (ROTOMAP), (iv) calculation and mapping of the hazard index by combining three factors, i.e., (a) lithological features of outcropping materials on rock faces, (b) kinematic compatibility defined by simulating the rockfall trajectories, and (c) spatial distribution of occurred rockfall events. Finally, the proposed methodology was validated by combining the distribution of the hazard levels along the road with the location on the SS18 of the rockfall events occurred from 2004 to 2014.

Automated identification of potential snow avalanche release areas based on digital elevation models

Abstract. The identification of snow avalanche release areas is a very difficult task. The release mechanism of snow avalanches depends on many different terrain, meteorological, snowpack and triggering parameters and their interactions, which are very difficult to assess. In many alpine regions such as the Indian Himalaya, nearly no information on avalanche release areas exists mainly due to the very rough and poorly accessible terrain, the vast size of the region and the lack of avalanche records. However avalanche release information is urgently required for numerical simulation of avalanche events to plan mitigation measures, for hazard mapping and to secure important roads. The Rohtang tunnel access road near Manali, Himachal Pradesh, India, is such an example. By far the most reliable way to identify avalanche release areas is using historic avalanche records and field investigations accomplished by avalanche experts in the formation zones. But both methods are not feasible for this area due to the rough terrain, its vast extent and lack of time. Therefore, we develop an operational, easy-to-use automated potential release area (PRA) detection tool in Python/ArcGIS which uses high spatial resolution digital elevation models (DEMs) and forest cover information derived from airborne remote sensing instruments as input. Such instruments can acquire spatially continuous data even over inaccessible terrain and cover large areas. We validate our tool using a database of historic avalanches acquired over 56 yr in the neighborhood of Davos, Switzerland, and apply this method for the avalanche tracks along the Rohtang tunnel access road. This tool, used by avalanche experts, delivers valuable input to identify focus areas for more-detailed investigations on avalanche release areas in remote regions such as the Indian Himalaya and is a precondition for large-scale avalanche hazard mapping.

Diclidophlebia smithi (Hemiptera: Psyllidae), a potential biocontrol agent for Miconia calvescens in the Pacific: Population dynamics, climate-match, host-specificity, host-damage and natural enemies

Diclidophlebia smithi (Hemiptera: Psyllidae) has been proposed as a candidate biological control agent for Miconia calvescens (Melastomataceae), a neotropical tree regarded as one of the worst threats to the rainforest ecosystems of several Pacific islands. Populations of D. smithi monitored over three years at three sites in the state of Minas Gerais, Brazil were found to peak during the cooler, drier months from April to July, with air temperatures as the factor most strongly correlated (negatively) with population density. A biologically significant match of climate conditions (+0.7 CMI, using CLIMEX regional matching) was found between the study region in Brazil and 3 of 9 weather stations in the potential release area of Hawaii. This result coupled with the wide variation in climatic conditions under which D. smithi populations have been found in Brazil suggest that D. smithi has good potential to establish in at least some regions of Hawaii. No significant predator, parasitoids or entomopathogens were found attacking D. smithi in its native range. No nymphs or adults of D. smithi were found on any plant belonging to a list of 102 species of 58 plant families growing in the vicinity of colonized M. calvescens individuals. Conversely, potted sentinel plants of the Hawaiian biotype of M. calvescens were readily colonized by D. smithi during an experimental six-month field exposure. Greenhouse no-choice tests with nine species of Melastomataceae also demonstrated that D. smithi has a host-range restricted to M. calvescens. A study of the morphological changes caused on tissues of M. calvescens by D. smithi showed that attack on leaves caused a collapse in the epidermis, cell disorganization and degeneration of the vascular system. This study confirms that D. smithi has significant potential as a biocontrol agent for M. calvescens.