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 Regional flood susceptibility analysis in mountainous areas through the use of morphometric and land cover indicators

2013 ◽  
Vol 1 (6) ◽  
pp. 7549-7593 ◽  
Author(s):  
M. C. Rogelis ◽  
M. Werner
Keyword(s):  
Land Cover ◽  
Debris Flow ◽  
Debris Flows ◽  
Flow Direction ◽  
Principal Component ◽  
Mountain Watersheds ◽  
Flood Susceptibility ◽  
Morphological Variables ◽  
Flow Propagation ◽  
Single Flow

Abstract. A classification of susceptibility to flooding of 106 mountain watersheds was carried out in Bogotá (Colombia) through the use of an index composed of a morphometric indicator and a land cover indicator. Susceptibility was considered to increase with flashiness and the possibility of debris flows. Morphological variables recognised in literature to significantly influence flashiness and occurrence of debris flows were used to construct the morphometric indicator by applying principal component analysis. Subsequently, this indicator was compared with the results of debris flow propagation to assess its capacity in indentifying 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 in four categories: size, shape, hypsometry and 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, showing that even if morphometric parameters identify a high disposition to the occurrence of debris flow, improving land cover can reduce the susceptibility. On the contrary, if good morphometric conditions are present but deterioration of the land cover in the watershed takes place then the susceptibility to debris flow events increases.

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 Debris flow hazard modelling on medium scale: Valtellina di Tirano, Italy

2010 ◽  
Vol 10 (11) ◽  
pp. 2379-2390 ◽  
Author(s):  
J. Blahut ◽  
P. Horton ◽  
S. Sterlacchini ◽  
M. Jaboyedoff
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Flow Direction ◽  
Hazard Analysis ◽  
Regional Scale ◽  
Aerial Photographs ◽  
Hazard Zonation ◽  
Conditioning Factors ◽  
Medium Scale ◽  
Debris Flow Hazard

Abstract. Debris flow hazard modelling at medium (regional) scale has been subject of various studies in recent years. In this study, hazard zonation was carried out, incorporating information about debris flow initiation probability (spatial and temporal), and the delimitation of the potential runout areas. Debris flow hazard zonation was carried out in the area of the Consortium of Mountain Municipalities of Valtellina di Tirano (Central Alps, Italy). The complexity of the phenomenon, the scale of the study, the variability of local conditioning factors, and the lacking data limited the use of process-based models for the runout zone delimitation. Firstly, a map of hazard initiation probabilities was prepared for the study area, based on the available susceptibility zoning information, and the analysis of two sets of aerial photographs for the temporal probability estimation. Afterwards, the hazard initiation map was used as one of the inputs for an empirical GIS-based model (Flow-R), developed at the University of Lausanne (Switzerland). An estimation of the debris flow magnitude was neglected as the main aim of the analysis was to prepare a debris flow hazard map at medium scale. A digital elevation model, with a 10 m resolution, was used together with landuse, geology and debris flow hazard initiation maps as inputs of the Flow-R model to restrict potential areas within each hazard initiation probability class to locations where debris flows are most likely to initiate. Afterwards, runout areas were calculated using multiple flow direction and energy based algorithms. Maximum probable runout zones were calibrated using documented past events and aerial photographs. Finally, two debris flow hazard maps were prepared. The first simply delimits five hazard zones, while the second incorporates the information about debris flow spreading direction probabilities, showing areas more likely to be affected by future debris flows. Limitations of the modelling arise mainly from the models applied and analysis scale, which are neglecting local controlling factors of debris flow hazard. The presented approach of debris flow hazard analysis, associating automatic detection of the source areas and a simple assessment of the debris flow spreading, provided results for consequent hazard and risk studies. However, for the validation and transferability of the parameters and results to other study areas, more testing is needed.

scholarly journals The importance of entrainment and bulking on debris flow runout modeling: examples from the Swiss Alps

2015 ◽  
Vol 15 (11) ◽  
pp. 2569-2583 ◽  
Author(s):  
F. Frank ◽  
B. W. McArdell ◽  
C. Huggel ◽  
A. Vieli
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Field Data ◽  
Average Rate ◽  
Hazard Analysis ◽  
Maximum Shear Stress ◽  
Empirical Relationship ◽  
Swiss Alps ◽  
Field Site ◽  
Practical Applications

Abstract. This study describes an investigation of channel-bed entrainment of sediment by debris flows. An entrainment model, developed using field data from debris flows at the Illgraben catchment, Switzerland, was incorporated into the existing RAMMS debris-flow model, which solves the 2-D shallow-water equations for granular flows. In the entrainment model, an empirical relationship between maximum shear stress and measured erosion is used to determine the maximum potential erosion depth. Additionally, the average rate of erosion, measured at the same field site, is used to constrain the erosion rate. The model predicts plausible erosion values in comparison with field data from highly erosive debris flow events at the Spreitgraben torrent channel, Switzerland in 2010, without any adjustment to the coefficients in the entrainment model. We find that by including bulking due to entrainment (e.g., by channel erosion) in runout models a more realistic flow pattern is produced than in simulations where entrainment is not included. In detail, simulations without entrainment show more lateral outflow from the channel where it has not been observed in the field. Therefore the entrainment model may be especially useful for practical applications such as hazard analysis and mapping, as well as scientific case studies of erosive debris flows.

scholarly journals Combined fluvial and pluvial urban flood hazard analysis: method development and application to Can Tho City, Mekong Delta, Vietnam

2015 ◽  
Vol 3 (8) ◽  
pp. 4967-5013 ◽  
Author(s):  
H. Apel ◽  
O. M. Trepat ◽  
N. N. Hung ◽  
D. T. Chinh ◽  
B. Merz ◽  
...  
Keyword(s):  
Hydrodynamic Model ◽  
Urban Areas ◽  
Large Scale ◽  
Method Development ◽  
Flood Hazard ◽  
Hazard Analysis ◽  
Mekong Delta ◽  
Rain Gauge ◽  
Convective Precipitation ◽  
Can Tho City

Abstract. Many urban areas experience both fluvial and pluvial floods, because locations next to rivers are preferred settlement areas, and the predominantly sealed urban surface prevents infiltration and facilitates surface inundation. The latter problem is enhanced in cities with insufficient or non-existent sewer systems. While there are a number of approaches to analyse either fluvial or pluvial flood hazard, studies of combined fluvial and pluvial flood hazard are hardly available. Thus this study aims at the analysis of fluvial and pluvial flood hazard individually, but also at developing a method for the analysis of combined pluvial and fluvial flood hazard. This combined fluvial-pluvial flood hazard analysis is performed taking Can Tho city, the largest city in the Vietnamese part of the Mekong Delta, as example. In this tropical environment the annual monsoon triggered floods of the Mekong River can coincide with heavy local convective precipitation events causing both fluvial and pluvial flooding at the same time. Fluvial flood hazard was estimated with a copula based bivariate extreme value statistic for the gauge Kratie at the upper boundary of the Mekong Delta and a large-scale hydrodynamic model of the Mekong Delta. This provided the boundaries for 2-dimensional hydrodynamic inundation simulation for Can Tho city. Pluvial hazard was estimated by a peak-over-threshold frequency estimation based on local rain gauge data, and a stochastic rain storm generator. Inundation was simulated by a 2-dimensional hydrodynamic model implemented on a Graphical Processor Unit (GPU) for time-efficient flood propagation modelling. All hazards – fluvial, pluvial and combined – were accompanied by an uncertainty estimation considering the natural variability of the flood events. This resulted in probabilistic flood hazard maps showing the maximum inundation depths for a selected set of probabilities of occurrence, with maps showing the expectation (median) and the uncertainty by percentile maps. The results are critically discussed and ways for their usage in flood risk management are outlined.

scholarly journals The importance of erosion for debris flow runout modelling from applications to the Swiss Alps

2015 ◽  
Vol 3 (4) ◽  
pp. 2379-2417 ◽  
Author(s):  
F. Frank ◽  
B. W. McArdell ◽  
C. Huggel ◽  
A. Vieli
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Field Data ◽  
Hazard Analysis ◽  
Maximum Shear Stress ◽  
Swiss Alps ◽  
Erosion Model ◽  
Practical Applications ◽  
Bed Erosion ◽  
The Relationship

Abstract. This study describes an investigation of channel-bed erosion of sediment by debris flows. An erosion model, developed using field data from debris flows at the Illgraben catchment, Switzerland, was incorporated into the existing RAMMS debris-flow model, which solves the 2-D shallow-water equations for granular flows. In the erosion model, the relationship between maximum shear stress and measured erosion is used to determine the maximum potential erosion depth. Additionally, the maximum rate of erosion, measured at the same field site, is used to constrain the erosion rate. The model predicts plausible erosion values in comparison with field data from highly erosive debris flow events at the Spreitgraben torrent channel, Switzerland in 2010, without any adjustment to the coefficients in the erosion model. We find that by including channel erosion in runout models a more realistic flow pattern is produced than in simulations where entrainment is not included. In detail, simulations without channel bed erosion show more lateral outflow from the channel where it has not been observed in the field. Therefore the erosion model may be especially useful for practical applications such as hazard analysis and mapping, as well as scientific case studies of erosive debris flows.

scholarly journals Development of Nomogram for Debris Flow Forecasting Based on Critical Accumulated Rainfall in South Korea

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2181
Author(s):  
Nam ◽  
Lee ◽  
Kim
Keyword(s):  
South Korea ◽  
Debris Flow ◽  
Urban Areas ◽  
Debris Flows ◽  
Rainfall Intensity ◽  
Extreme Weather Events ◽  
Weather Events ◽  
Accumulated Rainfall ◽  
Landslides And Debris Flows ◽  
Heavy Rains

Climate change causes extreme weather events worldwide such as increasing temperatures and changing rainfall patterns. With South Korea facing growing damage from the increased frequency of localized heavy rains. In particular, its steep slope lands, including mountainous areas, are vulnerable to damage from landslides and debris flows. In addition, localized short-term heavy rains that occur in urban areas with extremely high intensity tend to lead a sharp increase in damage from soil-related disasters and cause huge losses of life and property. Currently, South Korea forecasts landslides and debris flows using the standards for forecasting landslides and heavy rains. However, as the forecasting is conducted separately for rainfall intensity and accumulated rainfall, this lacks a technique that reflects both amount and intensity of rainfall in an episode of localized heavy rainfall. In this study, aims to develop such a technique by collecting past cases of debris flow occurrences and rainfall events that accompanied debris flows to calculate the rainfall triggering index (RTI) reflecting accumulated rainfall and rainfall intensity. In addition, the RTI is converted into the critical accumulated rainfall (Rc) to use rainfall information and provide real-time forecasting. The study classifies the standards for flow debris forecasting into three levels: ALERT (10–50%), WARNING (50–70%), and EMERGENCY (70% or higher), to provide a nomogram for 6 h, 12 h, and 24 h. As a result of applying this classification into the actual cases of Seoul, Chuncheon, and Cheongju, it is found that about 2–4 h of response time is secured from the point of the Emergency level to the occurrence of debris flows.

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.

Sign in / Sign up

Export Citation Format

Share Document