Example of a debris-flow risk analysis from Vancouver Island,British Columbia,Canada

In July 2005, a debris flow and a water flood occurred on two adjacent gullies in the White River area, on northern Vancouver Island in British Columbia, Canada. The 16,000 m³ debris flow buried approximately 7.5 ha of second-growth trees, buried approximately 500 m of a forestry road, and reached two fish-bearing streams. The water flood eroded approximately 240 m of the same forestry road and plugged four culverts before overtopping and inundating the road. To better plan for future events, risk analyses of debris flows, debris floods, and water floods were carried out for the two gullies involved, plus a third adjacent gully. The elements at risk that were analyzed included, in order of priority: users of the forestry road, the fish-bearing streams, the forestry road itself, and a timber bridge. Using a series of qualitative, but defined, relative-risk matrices, the following components of specific risk were estimated for each of the three types of events on each of the three gullies for each of the four elements at risk: probability of occurrence, probability that the event will reach or otherwise affect the site of the element at risk, the probability that the element at risk will be at the site when the event occurs, and the probability of loss or damage resulting from the element being at the site when the event occurs.     

Kuskonook Creek, an example of a debris flow analysis

Two debris flows occurred on Kuskonook Creek in British Columbia, Canada, in August and September 2004. The initiation factors included a major forest fire in the catchment in 2003, in association with relatively small rainfall events and the accumulation of sediment in the creek channels since the last large debris flow event. Previous regional studies and morphometric comparisons with other similar catchments indicate that Kuskonook Creek has characteristics predisposed to debris flows, even without the affects of a forest fire. Based on the investigations and analyses, a magnitude/frequency relationship for future debris events on Kuskonook Creek was developed, and this information was used to carry out a partial risk assessment. It is suggested that for design purposes, a 1/50-year return period and the corresponding debris flow magnitude of 15,000 m³ would provide conservative protection to the users of the provincial highway at the mouth of the creek.     

A procedure for making objective preliminary assessments of outburst flood hazard from moraine-dammed lakes in southwestern British Columbia

Existing methods of evaluating the hazard posed by moraine-dammed lakes are unsystematic, subjective, and depend on the expertise and biases of the geoscientist. In this paper, we provide a framework for making objective preliminary assessments of outburst flood hazard in southwestern British Columbia. Our procedure relies on remote sensing methods and requires only limited knowledge of glacial processes so that evaluations of outburst flood hazard can be incorporated into routine hazard assessments of glaciated regions. We describe objective approaches, which incorporate existing empirical relations applicable to the study region, for estimating outburst peak discharge, maximum volume, maximum travel distance, maximum area of inundation, and probability. Outburst flood hazard is greatest for moderately large lakes that are impounded by large, narrow, ice-free moraine dams composed of sedimentary rock debris and drain into steep, sediment-filled gullies above major river valleys. We demonstrate the application of the procedure using three case studies and show that flood hazard varies, especially with major changes in lake level. Our assessment scheme yields reproducible results and enables engineers and geoscientists to prioritize potentially hazardous lakes for more detailed field investigation.     

Application of back-propagation networks in debris flow prediction

Debris flows have caused serious loss of human lives and a lot of damage to properties in Taiwan over the past decades. Moreover, debris flows have brought massive mud causing water pollution in reservoirs and resulted in water shortage for daily life locally and affected agricultural irrigation and industrial usages seriously. A number of methods for prediction of debris flows have been studied. However, the successful prediction ratio of debris flows cannot always maintain a stable and reliable level. The objective of this study is to present a stable and reliable analytical model for occurrence predictions of debris flows. This study proposes an Artificial Neural Networks (ANN) model that was constructed by seven significant factors using back-propagation (BP) algorithm. These seven factors include (1) length of creek, (2) average slope, (3) effective watershed area, (4) shape coefficient, (5) median size of soil grain, (6) effective cumulative rainfall, and (7) effective rainfall intensity. A total of 178 potential cases of debris flows collected in eastern Taiwan were fed into the ANN model for training and testing. The average ratio of successful prediction reaching 93.82% demonstrates that the presented ANN model with seven significant factors can provide a stable and reliable result for the prediction of debris flows in hazard mitigation and guarding systems.     

2001 debris flow and debris flood in Nam Ko area, Phetchabun province, central Thailand

The factors of the debris flow and debris flood (debris flow-flood) occurrence on 11 August 2001 on the active Nam Ko alluvial fan in Phetchabun province, central Thailand, were studied. Evidences of past activity registered in the alluvial fan, and the debris flow-flood event were reconstructed. The disastrous debris flow-flood event was not the work of the unusual high amount of rainfalls alone, as previously theorized, but is a work of combined factors from the terrain characteristics with specific land covers to the time delay for accumulation of debris and sediments. This combination of factors could lead to a debris flow-flood after a high amount of precipitation. The process could also be worse if a landslide formed a natural dam, then the dam was destroyed under the weight of impounded water. After such a disastrous event, it would take time for more plant debris and sediments in the sub-catchment area to accumulate before the next debris flow-flood.     

Risk degree of debris flow applying neural networks

A number of methods for prediction of debris flows have been studied. However, the successful prediction ratios of debris flows cannot always maintain a stable and reliable level. The objective of this study is to present a stable and reliable analytical model for risk degree predictions of debris flows. This study proposes an Artificial Neural Networks (ANN) model that was constructed by seven significant factors using back-propagation (BP) algorithm. These seven factors include (1) length of creek, (2) average slope, (3) effective watershed area, (4) shape coefficient, (5) median size of soil grain, (6) effective cumulative rainfall, and (7) effective rainfall intensity. A total of 171 potential cases of debris flows collected in eastern Taiwan were fed into the ANN model for training and testing. The average ratio of successful prediction reaching 99.12% demonstrates that the presented ANN model with seven significant factors can provide a highly stable and reliable result for the prediction of debris flows in hazard mitigation and guarding systems.     

The Zymoetz River landslide, British Columbia, Canada: description and dynamic analysis of a rock slide–debris flow

The Zymoetz River landslide is a recent example of an extremely mobile type of landslide known as a rock slide–debris flow. It began as a failure of 900,000 m³ of bedrock, which mobilized an additional 500,000 m³ of surficial material in its path, transforming into a large debris flow that traveled over 4 km from its source. Seasonal snow and meltwater in the proximal part of the path were important factors. A recently developed dynamic model that accounts for material entrainment, DAN3D, was used to back-analyze this event. The two distinct phases of motion were modeled using different basal rheologies: a frictional model in the proximal path and a Voellmy model in the distal path, following the initiation of significant entrainment. Very good agreement between the observed and simulated results was achieved, suggesting that entrainment capabilities are essential for the successful simulation of this type of landslide.     

Slurry-flow deposits in the Britannia Formation (Lower Cretaceous), North Sea: a new perspective on the turbidity current and debris flow problem

The Lower Cretaceous Britannia Formation (North Sea) includes an assemblage of sandstone beds interpreted here to be the deposits of turbidity currents, debris flows and a spectrum of intermediate flow types termed slurry flows. The term ‘slurry flow’ is used here to refer to watery flows transitional between turbidity currents, in which particles are supported primarily by flow turbulence, and debris flows, in which particles are supported by flow strength. Thick, clean, dish‐structured sandstones and associated thin‐bedded sandstones showing Bouma T_b–e divisions were deposited by high‐ and low‐density turbidity currents respectively. Debris flow deposits are marked by deformed, intraformational mudstone and sandstone masses suspended within a sand‐rich mudstone matrix. Most Britannia slurry‐flow deposits contain 10–35% detrital mud matrix and are grain supported. Individual beds vary in thickness from a few centimetres to over 30 m. Seven sedimentary structure division types are recognized in slurry‐flow beds: (M₁) current structured and massive divisions; (M₂) banded units; (M₃) wispy laminated sandstone; (M₄) dish‐structured divisions; (M₅) fine‐grained, microbanded to flat‐laminated units; (M₆) foundered and mixed layers that were originally laminated to microbanded; and (M₇) vertically water‐escape structured divisions. Water‐escape structures are abundant in slurry‐flow deposits, including a variety of vertical to subvertical pipe‐ and sheet‐like fluid‐escape conduits, dish structures and load structures. Structuring of Britannia slurry‐flow beds suggests that most flows began deposition as turbidity currents: fully turbulent flows characterized by turbulent grain suspension and, commonly, bed‐load transport and deposition (M₁). Mud was apparently transported largely as hydrodynamically silt‐ to sand‐sized grains. As the flows waned, both mud and mineral grains settled, increasing near‐bed grain concentration and flow density. Low‐density mud grains settling into the denser near‐bed layers were trapped because of their reduced settling velocities, whereas denser quartz and feldspar continued settling to the bed. The result of this kinetic sieving was an increasing mud content and particle concentration in the near‐bed layers. Disaggregation of mud grains in the near‐bed zone as a result of intense shear and abrasion against rigid mineral grains caused a rapid increase in effective clay surface area and, hence, near‐bed cohesion, shear resistance and viscosity. Eventually, turbulence was suppressed in a layer immediately adjacent to the bed, which was transformed into a cohesion‐dominated viscous sublayer. The banding and lamination in M₂ are thought to reflect the formation, evolution and deposition of such cohesion‐dominated sublayers. More rapid fallout from suspension in less muddy flows resulted in the development of thin, short‐lived viscous sublayers to form wispy laminated divisions (M₃) and, in the least muddy flows with the highest suspended‐load fallout rates, direct suspension sedimentation formed dish‐structured M₄ divisions. Markov chain analysis indicates that these divisions are stacked to form a range of bed types: (I) dish‐structured beds; (II) dish‐structured and wispy laminated beds; (III) banded, wispy laminated and/or dish‐structured beds; (IV) predominantly banded beds; and (V) thickly banded and mixed slurried beds. These different bed types form mainly in response to the varying mud contents of the depositing flows and the influence of mud on suspended‐load fallout rates. The Britannia sandstones provide a remarkable and perhaps unique window on the mechanics of sediment‐gravity flows transitional between turbidity currents and debris flows and the textures and structuring of their deposits.     

基于熵权-正态云模型的泥石流灾害易发性评价

近年来,由于极端天气事件频发和工程建设活动加剧,泥石流灾害对人类的威胁愈加严峻。因此,在综合分析泥石流灾害发育特征及形成机理的基础上,进行泥石流灾害易发性评价对防灾减灾工程活动具有指导意义。选取沟谷岸坡坡度、沟床纵坡比降、植被覆盖率、单位面积固体物源储量、汇水面积、雨季降雨量建立评价指标体系,采用熵权法确定评价指标权重,将泥石流灾害易发性分为高易发、中易发、低易发和不易发四级,建立基于正态云模型的泥石流灾害易发性评价方法,并以西秦岭地区5条泥石流沟为例验证了该评价模型的合理性。进一步将该模型用于陕西吴堡井沟泥石流灾害易发性评价,结果表明井沟泥石流具有中易发性,评价结果与实际相符。     

Velocity and runout simulation of destructive debris flows and debris avalanches in pyroclastic deposits,Campania region,Italy

The Campanian Apennines are characterized by the presence of monocline ridges, mainly formed by limestone. During the periods of volcanic activity of the Somma-Vesuvius and Phlegrean Fields, the ridges were mantled with pyroclastic materials in varying thickness. The pyroclastics have been involved in destructive landslides both in historical time and in the recent past (1997, 1998, 1999). The landslides occur following intense and prolonged rainfalls. In some cases, landslides extended up to 4 km into the surrounding lowlands and reached towns, causing severe destruction and over 200 deaths. Generally, the landslides begin as small debris slides that develop into large, shallow debris avalanches or debris flows involving pyroclastic horizons and colluvial soils (0.5–2 m thick) on steep and vegetated slopes, often at the heads of gullies. During motion, the landslide materials eroded vegetation and soils from the slope, so that the moving material volume tended to increase. Then, proceeding towards and beyond the base of the slopes, the phenomena evolved into hyperconcentrated streamflow due to dilution by incorporating water. The results of motion analyses are described. An empirical rheological relationship was used including two principal terms that depend on the total normal stress and on the flow velocity. On this basis, the model has simulated the velocity and duration of debris avalanches and the distribution of the deposits. The selected areas were those of Sarno/Quindici and Cervinara, where a large amount of data is available both on the material properties and geomorphological setting. It was found that the majority of the cases at the two sites can be simulated successfully with only one specific pair of rheologic parameters. This provides the possibility for first-order predictions to be made of the motion of future landslides. Such predictions will be a valuable tool for outlining potential hazard areas and designing remedial measures.     

Neural network modeling for regional hazard assessment of debris flow in Lake Qionghai Watershed, China

This paper presents a neural network (NN) based model to assess the regional hazard degree of debris flows in Lake Qionghai Watershed, China. The NN model was used as an alternative for the more conventional linear model MFCAM (multi-factor composite assessment model) in order to effectively handle the nonlinearity and uncertainty inherent in the debris flow hazard analysis. The NN model was configured using a three layer structure with eight input nodes and one output node, and the number of nodes in the hidden layer was determined through an iterative process of varying the number of nodes in the hidden layer until an optimal performance was achieved. The eight variables used to represent the eight input nodes include density of debris flow gully, degree of weathering of rocks, active fault density, area percentage of slope land greater than 25° of the total land (APL25), frequency of flooding hazards, average covariance of monthly precipitation by 10 years (ACMP10), average days with rainfall >25 mm by 10 years (25D10Y), and percentage of cultivated land with slope land greater than 25° of the total cultivated land (PCL25). The output node represents the hazard-degree ranks (HDR). The model was trained with the 35 sets of data obtained from previous researches reported in literatures, and an explicit uncertainty analysis was undertaken to address the uncertainty in model training and prediction. Before the NN model is extrapolated to Lake Qionghai Watershed, a validation case, different from the above data, is conducted. In addition, the performances of the NN model and the MFCAM were compared. The NN model predicted that the HDRs of the five sub-watersheds in the Lake Qionghai Watershed were IV, IV, III, III, and IV–V, indicating that the study area covers normal hazard and severe hazard areas. Based on the NN model results, debris flow management and economic development strategies in the study are proposed for each sub-watershed.     

Erosion and morphology of a debris flow caused by a glacial lake outburst flood,Western Norway

This article documents a 240,000-m³ debris flow resulting from a glacial lake outburst flood in Fjærland, Western Norway, May 8, 2004. The event started when a glacial lake breached a moraine ridge. The ensuing debris flow was able to erode material along its path, increasing in volume from about 25,000 to 240,000 m³ before depositing about 3 km from its starting point. Field investigations, pre- and post-flow aerial photographs as well as airborne laser scanning (LIDAR) were used to describe and investigate the flow. The most striking and unusual feature of this case study is the very pronounced erosion and bulking. We have made a detailed study of this aspect. Erosion and entrainment is quantified and the final volume of the debris flow is determined. We also present geometrical and sedimentological features of the final deposit. Based on the Fjærland data, we suggest that a self-sustaining mechanism might partly explain the extreme growth of debris flows traversing soft terrain.     

Identification of the affected areas by mass movement through a physically based model of landslide hazard combined with an empirical model of debris flow

In tropical areas, mass movements are common phenomena, especially during periods of heavy rainfall, which frequently take place in the summer season. These phenomena have caused loss of life and serious damage to infrastructure and properties. The most prominent of these phenomena are landslides that can produce debris flows. Thus, this article aims at determining affected areas using a model to predict landslide prone areas (SHALSTAB) combined with an empirical model designed to define the debris flow travel distance and area of deposition. The methodology of this work consists of the following steps: (a) elaboration of a digital elevation model (DEM), (b) application of the deterministic SHALSTAB model to locate the landslide prone areas, (c) identification of the debris flow travel distance and area of deposition, and (d) mapping of the affected areas (landslides and debris flows). This work was developed in an area in which many mass movements occurred after intense rainfall during the summer season (February 1996) in the state of Rio de Janeiro, southeast Brazil. All of the scars produced by that event were mapped, allowing for validation of the applied models. The model results show that the mapped landslide locations can adequately be simulated by the model.     

Numerical simulation of debris flow with application on hazard area mapping

A numerical program developed for field application is presented in this paper. We use the generalized Julien and Lan [8] rheological model to simulate debris flows. Due to the derivative discontinuous nature of the constitutive law, flow is separated into plug region and bottom region (with stress greater than yield stress). The program solves the plug flow layer solution first, and then corrects the solution with the bottom layer approximation. Numerical scheme with upwind method and central difference in space and Adam–Bashforth third-order scheme in time is used for both layers. The scheme is tested against analytical solutions and laboratory experiments with very good results. Application to a field case with more complicated geometry also achieves good agreement, with error less than 5% compared to field measurements. The final example demonstrates how this numerical program is used in a preliminary design.     

Hydrometeorological thresholds for landslide initiation and forest operation shutdowns on the north coast of British Columbia

Debris flows and debris avalanches are the most widespread and hazardous types of landslides on the British Columbia north coast. Triggered by heavy rain, they pose risks to forestry workers in sparsely developed regions. The scarcity of long-term quality rain gauges and the lack of weather radar information create significant challenge in predicting the timing of landslides, which could be used to warn and, when necessary, evacuate forestry personnel. Traditional methods to relate rainfall antecedents and rainfall intensity to known landslide dates have proven to be unsatisfactory in this study due to extreme spatial variability of rainfall, enhanced by the orographic effect and the scarcity of rain gauges in a very large area. This has led to an integration of meteorological variables in a landslide advisory system that classifies three types of approaching storms by the 850-mbar wind speed and direction, the occurrence of subtropical moisture flow, and the existence of a warm layer characterized by high thickness values of the 500- to 1,000-mbar pressure levels. The storm classification was combined with a 4-week antecedent rainfall and the 24-h rainfall measured near or in the watershed where logging operations are taking place. This system, once implemented, is thought to reduce loss of life, injury, and economic losses associated with forestry works in the study area.     

Post-disaster assessment of hazard mitigation for small and medium-magnitude debris flow disasters in Bali,Indonesia and Jimani,Dominican Republic

This article explores whether past exposure to debris flow disasters with a human dimension (e.g. caused in part by deforestation) results in adaptive hazard mitigation and improved environmental and resource management practices in affected areas. When guiding hazard mitigation practice, the ‘adaptive hazard mitigation’ approach views mitigation as a multi-dimensional experiment, with the associated need for post-experiment monitoring, evaluation, learning and adjustment, and attention paid to multiple scales (Bogardi 2004). This article explores how the concept of ‘adaptive hazard mitigation’ has emerged, linking this ‘adaptive management’ used increasingly in resource and environmental management. Two case studies of disasters linked to human-induced environmental change are examined, and the mitigation responses of local communities, NGOs and Government agencies are documented. Data sources include secondary data (journal articles, web-based disaster reports and grey literature) on each disaster, key informant interviews (n = 8) and direct observation over the 2005–2006 period of post-disaster mitigation actions implemented after each disaster. The research indicates that in both case studies, a limited range of hazard mitigation actions was employed, including both structural and non-structural approaches. However, the research also found that causal factors involving human-induced environmental change (e.g. deforestation) were not addressed, and overall, the hazard mitigation strategies adopted lacked monitoring, learning and adjustment. In both case studies, responses to disaster were judged to be examples of ‘trial and error’ adaptation, rather than either ‘passive’ or ‘active’ adaptation.

Rain-induced debris and mudflow triggering factors assessment in the Santiago cordilleran foothills,Central Chile

Debris and mudflows are some of the main geological hazards in the mountain foothills of the Chilean capital city of Santiago. There, the risk of flows triggered in the basins of ravines that drain the range into the city increases with time due to the city growth. A multivariate statistical study based on the logistic regression method is presented. The model provides equations that allow the computation of combined meteorological triggering factors associated with a probability of rain-induced flow occurrence. Daily rainfall, accumulated rainfall and the snowfall level, traditionally considered as the relevant factors, are analysed for a 25-year period. The results show a strong relevance of the rainfall on the day of the flow event over the other factors. However, the relatively low probabilities returned for some real flow events suggest that the model does not capture all the significant variables and the problem is more complex than as it has been traditionally assumed, and further investigations are needed to develop predictive models of flow triggering.     

GIS-based hazard mapping and zonation of debris flows in Xiaojiang Basin,southwestern China

Debris flow sites were identified at 140 locations in the Xiaojiang Basin in Yunnan province, southwestern China. Their spatial distribution and catchment characteristics are described in detail on the basis of previous research, air photo interpretation, field investigation and mapping using Geographical Information Systems (GIS). Using a statistical approach, a quantitative model of hazards assessment and zonation was developed through synthesis analysis of basin areas, gradients, and the relative reliefs of these debris flow sites. In terms of debris flow hazard assessment, areas within the Xiaojiang Basin can be classified as severe, heavy and light hazard regions.     

Passage of debris flows and turbidity currents through a topographic constriction: seafloor erosion and deflection of flow pathways

Some of the Earth's largest submarine debris flows are found on the NW African margin. These debris flows are highly efficient, spreading hundreds of cubic kilometres of sediment over a wide area of the continental rise where slopes angles are often <1°. However, the processes by which these debris flows achieve such long run‐outs, affecting tens of thousands of square kilometres of seafloor, are poorly understood. The Saharan debris flow has a run‐out of ≈700 km, making it one of the longest debris flows on Earth. For its distal 450 km, it is underlain by a relatively thin and highly sheared basal volcaniclastic layer, which may have provided the low‐friction conditions that enabled its extraordinarily long run‐out. Between El Hierro Island and the Hijas Seamount on the continental rise, an ≈25‐ to 40‐km‐wide topographic gap is present, through which the Saharan debris flow and turbidites from the continental margin and flanks of the Canary Islands passed. Recently, the first deep‐towed sonar images have been obtained, showing dramatic erosional and depositional processes operating within this topographic `gap' or `constriction'. These images show evidence for the passage of the Saharan debris flow and highly erosive turbidity currents, including the largest comet marks reported from the deep ocean. Sonar data and a seismic reflection profile obtained 70 km to the east, upslope of the topographic `gap', indicate that seafloor sediments to a depth of ≈30 m have been eroded by the Saharan debris flow to form the basal volcaniclastic layer. Within the topographic `gap', the Saharan debris flow appears to have been deflected by a low (≈20 m) topographic ridge, whereas turbidity currents predating the debris flow appear to have overtopped the ridge. This evidence suggests that, as turbidity currents passed into the topographic constriction, they experienced flow acceleration and, as a result, became highly erosive. Such observations have implications for the mechanics of long run‐out debris flows and turbidity currents elsewhere in the deep sea, in particular how such large‐scale flows erode the substrate and interact with seafloor topography.     

UNESCO World Heritage sites in Italy affected by geological problems, specifically landslide and flood hazard

A National Research Council, Research Institute for Hydrogeological Protection (IRPI) study on Italian monuments included in the UNESCO World Heritage List has revealed that many are affected by geological, geomorphological, and engineering geological problems. These monuments are static entities set in an environment that often manifests highly dynamic processes. As part of the efforts to protect sites of cultural and natural heritage, this study has applied a preliminary and empirical Geographical Information System-based method developed to characterize the environmental hazards at the sites where the monuments are located. Because the study of hydrogeological degradation falls within the province of IRPI, this hazard zoning focuses on river and mountain slope dynamics specifically concerning landslides and floods.