scholarly journals Creating a national scale debris flow susceptibility model for Great Britain: a GIS-based heuristic approach

2019 ◽  
Author(s):  
Emma J. Bee ◽  
Claire Dashwood ◽  
Catherine Pennington ◽  
Roxana L. Ciurean ◽  
Katy Lee
Keyword(s):  
Great Britain ◽  
Debris Flow ◽  
Debris Flows ◽  
Methodological Approach ◽  
Slope Angle ◽  
Transport Infrastructure ◽  
Stream Channels ◽  
National Scale ◽  
Susceptibility Model ◽  
Debris Flow Susceptibility

Abstract. Debris flows in Great Britain have caused damage to transport infrastructure, buildings, and disruption to businesses and communities. This study describes a GIS-based heuristic model developed by the British Geological Survey (BGS) to produce a national scale spatial assessment of debris flow susceptibility for Great Britain. The model provides information on the potential for debris flow occurrence using properties and characteristics of geological materials (permeability, material availability and characteristics when weathered), slope angle and proximity to stream channels as indicators of susceptibility. Building on existing knowledge, the model takes into account the presence or absence of glacial scouring. As determined by the team of geologists and geomorphologists, the model ranks the availability of debris material and slope as the two dominant factors important for potential debris flow initiation, however it also considers other factors such as geological controls on infiltration. The resultant model shows that over 90 % of the mapped debris flows in the BGS inventory occurred in areas with the highest potential for instability and approximately 6 % were attributed to areas where the model suggested that debris flows are unlikely or not thought to occur. Model validation in the Cairngorm Mountains indicated a better performance, with 93.50 % in the former and less than 3 % in the latter category. Although the quality of the input datasets and selected methodological approach bear limitations and introduce a number of uncertainties, overall, the proposed susceptibility model performs better than previous attempts, representing a useful tool in the hands of policy-makers, developers and engineers to support regional or national scale development action plans and disaster risk reduction strategies.

scholarly journals Debris flow susceptibility mapping using a qualitative heuristic method and Flow-R along the Yukon Alaska Highway Corridor, Canada

2016 ◽  
Vol 16 (2) ◽  
pp. 449-462 ◽  
Author(s):  
A. Blais-Stevens ◽  
P. Behnia
Keyword(s):  
Debris Flow ◽  
Slope Angle ◽  
Heuristic Method ◽  
Northern Region ◽  
Slope Aspect ◽  
Research Activity ◽  
Susceptibility Model ◽  
Alaska Highway Corridor ◽  
Kluane Lake ◽  
Debris Flow Susceptibility

Abstract. This research activity aimed at reducing risk to infrastructure, such as a proposed pipeline route roughly parallel to the Yukon Alaska Highway Corridor (YAHC), by filling geoscience knowledge gaps in geohazards. Hence, the Geological Survey of Canada compiled an inventory of landslides including debris flow deposits, which were subsequently used to validate two different debris flow susceptibility models. A qualitative heuristic debris flow susceptibility model was produced for the northern region of the YAHC, from Kluane Lake to the Alaska border, by integrating data layers with assigned weights and class ratings. These were slope angle, slope aspect, surficial geology, plan curvature, and proximity to drainage system. Validation of the model was carried out by calculating a success rate curve which revealed a good correlation with the susceptibility model and the debris flow deposit inventory compiled from air photos, high-resolution satellite imagery, and field verification. In addition, the quantitative Flow-R method was tested in order to define the potential source and debris flow susceptibility for the southern region of Kluane Lake, an area where documented debris flow events have blocked the highway in the past (e.g. 1988). Trial and error calculations were required for this method because there was not detailed information on the debris flows for the YAHC to allow us to define threshold values for some parameters when calculating source areas, spreading, and runout distance. Nevertheless, correlation with known documented events helped define these parameters and produce a map that captures most of the known events and displays debris flow susceptibility in other, usually smaller, steep channels that had not been previously documented.

scholarly journals Debris flow susceptibility mapping using a qualitative heuristic method and Flow-R along the Yukon Alaska Highway Corridor, Canada

2015 ◽  
Vol 3 (5) ◽  
pp. 3509-3541 ◽  
Author(s):  
A. Blais-Stevens ◽  
P. Behnia
Keyword(s):  
Debris Flow ◽  
Slope Angle ◽  
Heuristic Method ◽  
Northern Region ◽  
Slope Aspect ◽  
Research Activity ◽  
Susceptibility Model ◽  
Alaska Highway Corridor ◽  
Kluane Lake ◽  
Debris Flow Susceptibility

Abstract. This research activity aimed at reducing risk to infrastructure, such as a proposed pipeline route roughly parallel to the Yukon Alaska Highway Corridor (YAHC) by filling geoscience knowledge gaps in geohazards. Hence, the Geological Survey of Canada compiled an inventory of landslides including debris flow deposits, which were subsequently used to validate two different debris flow susceptibility models. A qualitative heuristic debris flow susceptibility model was produced for the northern region of the YAHC, from Kluane Lake to the Alaska border, by integrating data layers with assigned weights and class ratings. These were slope angle, slope aspect (derived from a 5 m × 5 m DEM), surficial geology, permafrost distribution, and proximity to drainage system. Validation of the model was carried out by calculating a success rate curve which revealed a good correlation with the susceptibility model and the debris flow deposit inventory compiled from air photos, high resolution satellite imagery, and field verification. In addition, the quantitative Flow-R method was tested in order to define the potential source and debris flow susceptibility for the southern region of Kluane Lake, an area where documented debris flow events have blocked the highway in the past (e.g., 1988). Trial and error calculations were required for this method because there was not detailed information on the debris flows for the YAHC to allow us to define threshold values for some parameters when calculating source areas, spreading, and runout distance. Nevertheless, correlation with known documented events helped define these parameters and produce a map that captures most of the known events and displays debris flow susceptibility in other, usually smaller, steep channels that had not been previously documented.

scholarly journals The Development of a 1-D Integrated Hydro-Mechanical Model Based on Flume Tests to Unravel Different Hydrological Triggering Processes of Debris Flows

Water ◽  
2018 ◽  
Vol 10 (7) ◽  
pp. 950 ◽  
Author(s):  
Theo van Asch ◽  
Bin Yu ◽  
Wei Hu
Keyword(s):  
Debris Flow ◽  
Mechanical Model ◽  
Debris Flows ◽  
Overland Flow ◽  
Slope Angle ◽  
Great Influence ◽  
Flume Experiments ◽  
Triggering Mechanisms ◽  
Bed Material ◽  
Triggering Process

Many studies which try to analyze conditions for debris flow development ignore the type of initiation. Therefore, this paper deals with the following questions: What type of hydro-mechanical triggering mechanisms for debris flows can we distinguish in upstream channels of debris flow prone gullies? Which are the main parameters controlling the type and temporal sequence of these triggering processes, and what is their influence on the meteorological thresholds for debris flow initiation? A series of laboratory experiments were carried out in a flume 8 m long and with a width of 0.3 m to detect the conditions for different types of triggering mechanisms. The flume experiments show a sequence of hydrological processes triggering debris flows, namely erosion and transport by intensive overland flow and by infiltrating water causing failure of channel bed material. On the basis of these experiments, an integrated hydro-mechanical model was developed, which describes Hortonian and saturation overland flow, maximum sediment transport, through flow and failure of bed material. The model was calibrated and validated using process indicator values measured during the experiments in the flume. Virtual model simulations carried out in a schematic hypothetical source area of a catchment show that slope angle and hydraulic conductivity of the bed material determine the type and sequence of these triggering processes. It was also clearly demonstrated that the type of hydrological triggering process and the influencing geometrical and hydro-mechanical parameters may have a great influence on rainfall intensity-duration threshold curves for the start of debris flows.

scholarly journals Debris-flow susceptibility assessment through cellular automata modeling: an example from 15–16 December 1999 disaster at Cervinara and San Martino Valle Caudina (Campania, southern Italy)

2003 ◽  
Vol 3 (5) ◽  
pp. 457-468 ◽  
Author(s):  
G. Iovine ◽  
S. Di Gregorio ◽  
V. Lupiano
Keyword(s):  
Cellular Automata ◽  
Debris Flow ◽  
Urban Areas ◽  
Debris Flows ◽  
Soil Cover ◽  
Southern Italy ◽  
Landslide Risk ◽  
Campania Region ◽  
Optimal Values ◽  
Debris Flow Susceptibility

Abstract. On 15–16 December 1999, heavy rainfall severely stroke Campania region (southern Italy), triggering numerous debris flows on the slopes of the San Martino Valle Caudina-Cervinara area. Soil slips originated within the weathered volcaniclastic mantle of soil cover overlying the carbonate skeleton of the massif. Debris slides turned into fast flowing mixtures of matrix and large blocks, downslope eroding the soil cover and increasing their original volume. At the base of the slopes, debris flows impacted on the urban areas, causing victims and severe destruction (Vittori et al., 2000). Starting from a recent study on landslide risk conditions in Campania, carried out by the Regional Authority (PAI –Hydrogeological setting plan, in press), an evaluation of the debris-flow susceptibility has been performed for selected areas of the above mentioned villages. According to that study, such zones would be in fact characterised by the highest risk levels within the administrative boundaries of the same villages ("HR-zones"). Our susceptibility analysis has been performed by applying SCIDDICA S3–hex – a hexagonal Cellular Automata model (von Neumann, 1966), specifically developed for simulating the spatial evolution of debris flows (Iovine et al., 2002). In order to apply the model to a given study area, detailed topographic data and a map of the erodable soil cover overlying the bedrock of the massif must be provided (as input matrices); moreover, extent and location of landslide source must also be given. Real landslides, selected among those triggered on winter 1999, have first been utilised for calibrating SCIDDICA S3–hex and for defining "optimal" values for parameters. Calibration has been carried out with a GIS tool, by quantitatively comparing simulations with actual cases: optimal values correspond to best simulations. Through geological evaluations, source locations of new phenomena have then been hypothesised within the HR-zones. Initial volume for these new cases has been estimated by considering the actual statistics of the 1999 landslides. Finally, by merging the results of simulations, a deterministic susceptibility zonation of the considered area has been obtained. In this paper, aiming at illustrating the potential for debris-flow hazard analyses of the model SCIDDICA S3–hex, a methodological example of susceptibility zonation of the Vallicelle HR-zone is presented.

scholarly journals Regional debris flow susceptibility analysis in mountainous peri-urban areas through morphometric and land cover indicators

2014 ◽  
Vol 14 (11) ◽  
pp. 3043-3064 ◽  
Author(s):  
M. C. Rogelis ◽  
M. Werner
Keyword(s):  
Land Cover ◽  
Debris Flow ◽  
Flood Risk ◽  
Urban Areas ◽  
Debris Flows ◽  
Flood Hazard ◽  
Flow Direction ◽  
Hazard Analysis ◽  
Principal Component ◽  
Debris Flow Susceptibility

Abstract. A method for assessing regional debris flow susceptibility at the watershed scale, based on an index composed of a morphometric indicator and a land cover indicator, is proposed and applied in 106 peri-urban mountainous watersheds in Bogotá, Colombia. The indicator of debris flow susceptibility is obtained from readily available information common to most peri-urban mountainous areas and can be used to prioritise watersheds that can subsequently be subjected to detailed hazard analysis. Susceptibility is considered to increase with flashiness and the possibility of debris flows occurring. Morphological variables recognised in the literature to significantly influence flashiness and occurrence of debris flows are used to construct the morphometric indicator by applying principal component analysis. Subsequently, this indicator is compared with the results of debris flow propagation to assess its capacity in identifying the morphological conditions of a watershed that make it able to transport debris flows. Propagation of debris flows was carried out using the Modified Single Flow Direction algorithm, following identification of source areas by applying thresholds identified in the slope–area curve of the watersheds. Results show that the morphometric variables can be grouped into four indicators: size, shape, hypsometry and (potential) energy, with energy being the component that best explains the capability of a watershed to transport debris flows. However, the morphometric indicator was found to not sufficiently explain the records of past floods in the study area. Combining the morphometric indicator with land cover indicators improved the agreement and provided a more reliable assessment of debris flow susceptibility in the study area. The analysis shows that, even if morphometric parameters identify a high disposition to the occurrence of debris flow, improving land cover can reduce the susceptibility. However, if favourable morphometric conditions are present but deterioration of the land cover in the watershed takes place, then the susceptibility to debris flow events increases. The indicator of debris flow susceptibility is useful in the identification of flood type, which is a crucial step in flood risk assessment especially in mountainous environments, and it can be used as input for prioritisation of flood risk management strategies at regional level and for the prioritisation and identification of detailed flood hazard analysis. The indicator is regional in scope, and therefore it is not intended to constitute a detailed assessment but to highlight watersheds that could potentially be more susceptible to damaging floods than others in the same region.

scholarly journals Spatial Predictions of Debris Flow Susceptibility Mapping Using Convolutional Neural Networks in Jilin Province, China

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2079
Author(s):  
Yang Chen ◽  
Shengwu Qin ◽  
Shuangshuang Qiao ◽  
Qiang Dou ◽  
Wenchao Che ◽  
...  
Keyword(s):  
Neural Networks ◽  
Debris Flow ◽  
Statistical Methods ◽  
Convolutional Neural Networks ◽  
Debris Flows ◽  
Susceptibility Mapping ◽  
Jilin Province ◽  
Support Vector ◽  
Validation Set ◽  
Debris Flow Susceptibility

Debris flows are a major geological disaster that can seriously threaten human life and physical infrastructures. The main contribution of this paper is the establishment of two–dimensional convolutional neural networks (2D–CNN) models by using SAME padding (S–CNN) and VALID padding (V–CNN) and comparing them with support vector machine (SVM) and artificial neural network (ANN) models, respectively, to predict the spatial probability of debris flows in Jilin Province, China. First, the dataset is randomly divided into a training set (70%) and a validation set (30%), and thirteen influencing factors are selected to build the models. Then, multicollinearity analysis and gain ratio methods are used to quantify the predictive ability of factors. Finally, the area under the receiver operatic characteristic curve (AUC) and statistical methods are utilized to measure the accuracy of the models. The results show that the S–CNN model gets the highest AUC value of 0.901 in the validation set, followed by the SVM model, the V–CNN model, and the ANN model. Three statistical methods also show that the S–CNN model produces minimum errors compared with other models. The S–CNN model is hailed as an important means to improve the accuracy of debris–flow susceptibility mapping and provides a reasonable scientific basis for critical decisions.

Why are some alpine catchments debris-flow active and others not? - the influence of geomorphology on debris-flow initiation

2020 ◽  
Author(s):  
Philipp Aigner ◽  
Leonard Sklar ◽  
Markus Hrachowitz ◽  
Roland Kaitna
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Regional Scale ◽  
Alpine Regions ◽  
Order Of Magnitude ◽  
Elevation Changes ◽  
Alpine Catchments ◽  
Flow Activity ◽  
The Impact ◽  
Debris Flow Susceptibility

<p>Processes like flash floods or debris flows, which typically occur in small headwater catchments, represent a substantial natural hazard in alpine regions. Due to the entrainment of sediment, the discharge of debris flows can be up to an order of magnitude larger compared to 100-year fluvial flood events in the same channel, which poses a great threat to affected communities. Besides the triggering rainfall, the initiation of debris flows depends on the watershed’s hydrological and geomorphological susceptibility, which makes it hard to predict and understand where and when debris flows occur.</p><p>In this study we aim to quantify the influence of geomorphologic characteristics and long-term sediment dynamics on debris flow activity in the Austrian Alps. Based on a database of debris-flow events within the last 60+ years, a geomorphological assessment of active and non-active sub-catchments in different study regions is carried out. In a first step, we derive geomorphological characteristics, such as terrain roughness, Melton number as well as weathering potential of geological units found within the watersheds. Based on the findings of the terrain shape analysis, a set of representative watersheds will be selected for systematic monitoring of surface elevation changes over the project period of three years. This will be achieved by comparing digital surface models based on photogrammetric UAV surveys and monitoring of channel reaches with cameras.</p><p>In order to project these findings onto a larger regional scale, the derived terrain parameters will be used to integrate and extend a previously designed hydro-meteorological debris-flow susceptibility model (Prenner et al., 2018) with a sediment-disposition-model. This will form the basis for an advanced debris flow forecasting tool and help to better assess the impact of climate change on the magnitude and frequency of future debris flows.</p><p> </p><div><span>References:</span></div><div><span>Prenner, D.</span>, <span>Kaitna, R.</span>, <span>Mostbauer, K.</span>, & <span>Hrachowitz, M.</span> ( <span>2018</span>). <span>The value of using multiple hydrometeorological variables to predict temporal debris flow susceptibility in an Alpine environment</span>. <em>Water Resources Research</em>, <span>54</span>, <span>6822</span>– <span>6843</span>. </div><p> </p>

scholarly journals Application of Machine Learning to Debris Flow Susceptibility Mapping along the China–Pakistan Karakoram Highway

2020 ◽  
Vol 12 (18) ◽  
pp. 2933
Author(s):  
Feng Qing ◽  
Yan Zhao ◽  
Xingmin Meng ◽  
Xiaojun Su ◽  
Tianjun Qi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Debris Flow ◽  
Debris Flows ◽  
Susceptibility Mapping ◽  
Support Vector ◽  
Safe Operation ◽  
Extreme Gradient Boosting ◽  
Karakoram Highway ◽  
Debris Flow Susceptibility

The China–Pakistan Karakoram Highway is an important land route from China to South Asia and the Middle East via Pakistan. Due to the extremely hazardous geological environment around the highway, landslides, debris flows, collapses, and subsidence are frequent. Among them, debris flows are one of the most serious geological hazards on the Karakoram Highway, and they often cause interruptions to traffic and casualties. Therefore, the development of debris flow susceptibility mapping along the highway can potentially facilitate its safe operation. In this study, we used remote sensing, GIS, and machine learning techniques to map debris flow susceptibility along the Karakoram Highway in areas where observation data are scarce and difficult to obtain by field survey. First, the distribution of 544 catchments which are prone to debris flow were identified through visual interpretation of remote sensing images. The factors influencing debris flow susceptibility were then analyzed, and a total of 17 parameters related to geomorphology, soil materials, and triggering conditions were selected. Model training was based on multiple common machine learning methods, including Ensemble Methods, Gaussian Processes, Generalized Linear models, Navies Bayes, Nearest Neighbors, Support Vector Machines, Trees, Discriminant Analysis, and eXtreme Gradient Boosting. Support Vector Classification (SVC) was chosen as the final model after evaluation; its accuracy (ACC) was 0.91, and the area under the ROC curve (AUC) was 0.96. Among the factors involved in SVC, the Melton Ratio (MR) was the most important, followed by drainage density (DD), Hypsometric Integral (HI), and average slope (AS), indicating that geomorphic conditions play an important role in predicting debris flow susceptibility in the study area. SVC was used to map debris flow susceptibility in the study area, and the results will potentially facilitate the safe operation of the highway.

scholarly journals Sedimentological characteristics of debris flow Deposits within ice−cored moraine of Ebbabreen, central Spitsbergen

2015 ◽  
Vol 36 (2) ◽  
pp. 125-144 ◽  
Author(s):  
Krzysztof Pleskot
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Slope Angle ◽  
Parent Material ◽  
Original Structure ◽  
Sediment Layer ◽  
Local Conditions ◽  
Thin Sections ◽  
Sedimentary Characteristics ◽  
Deposition Area

Abstract The Ebbabreen ice−cored moraine area is covered with a sediment layer of up to 2.5 m thick, which mostly consists of massive diamicton. Due to undercutting by lateral streams, debris flow processes have been induced in marginal parts of this moraine. It was recognized that the sedimentology of deposits within the deposition area of debris flows is the effect of: (1) the origin of the sediments, (2) the nature of the debris flow, and (3) post−debris flow reworking. Analysis of debris flow deposits in microscale (thin sections) suggests a common mixing during flow, even though a small amount of parent material kept its original structure. The mixing of sediments during flow leads to them having similar sedimentary characteristics across the deposition area regardless of local conditions (i.e. slope angle, water content, parent material lithology). After the deposition of sediments that were transported by the debris flow, they were then reworked by a further redeposition process, primarily related to meltwater stream action.

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