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 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-scale GIS-models for assessment of hazards from glacier lake outbursts: evaluation and application in the Swiss Alps

2003 ◽  
Vol 3 (6) ◽  
pp. 647-662 ◽  
Author(s):  
C. Huggel ◽  
A. Kääb ◽  
W. Haeberli ◽  
B. Krummenacher
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Flow Direction ◽  
Regional Scale ◽  
Satellite Image ◽  
Swiss Alps ◽  
Special Focus ◽  
High Mountain ◽  
Mountain Areas ◽  
Single Flow

Abstract. Debris flows triggered by glacier lake outbursts have repeatedly caused disasters in various high-mountain regions of the world. Accelerated change of glacial and periglacial environments due to atmospheric warming and increased anthropogenic development in most of these areas raise the need for an adequate hazard assessment and corresponding modelling. The purpose of this paper is to pro-vide a modelling approach which takes into account the current evolution of the glacial environment and satisfies a robust first-order assessment of hazards from glacier-lake outbursts. Two topography-based GIS-models simulating debris flows related to outbursts from glacier lakes are presented and applied for two lake outburst events in the southern Swiss Alps. The models are based on information about glacier lakes derived from remote sensing data, and on digital elevation models (DEM). Hydrological flow routing is used to simulate the debris flow resulting from the lake outburst. Thereby, a multiple- and a single-flow-direction approach are applied. Debris-flow propagation is given in probability-related values indicating the hazard potential of a certain location. The debris flow runout distance is calculated on the basis of empirical data on average slope trajectory. The results show that the multiple-flow-direction approach generally yields a more detailed propagation. The single-flow-direction approach, however, is more robust against DEM artifacts and, hence, more suited for process automation. The model is tested with three differently generated DEMs (including aero-photogrammetry- and satellite image-derived). Potential application of the respective DEMs is discussed with a special focus on satellite-derived DEMs for use in remote high-mountain areas.

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 Formation time and mean movement velocities of the 7 August Zhouqu debris flows extracted from broadband seismic records

2015 ◽  
Vol 3 (1) ◽  
pp. 675-695
Author(s):  
Z. Li ◽  
X. Huang ◽  
Q. Xu ◽  
J. Fan ◽  
D. Yu ◽  
...  
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Flow Direction ◽  
Seismic Station ◽  
Satellite Image ◽  
Development Stage ◽  
Maturity Stage ◽  
Seismic Signals ◽  
Seismic Records ◽  
First Time

Abstract. The catastrophic Zhouqu debris flows, which were induced by heavy rainfall, occurred at approximately midnight of 7 August 2010 (Beijing time, UTC + 8) and claimed 1765 lives. Broadband seismic signals recorded by the Zhouqu seismic station nearby are acquired and analyzed in this paper. The seismic signals are divided into two separate parts for the first time using the crucial time of 23:33:10 (Bejing time, UTC +8), with distinctly different frequency characteristics on time-by-time normalized spectrograms and amplitude increasing patterns on smoothed envelopes. They are considered to be generated by the development stage and the maturity stage of the Sanyanyu debris flow respectively. Seismic signals corresponding to the development stage have a broader main frequency band of approximately 0–15 Hz than that of the maturity stage, which is around 1–10 Hz. The N–S component can detect the development stage of the debris flow about 3 min earlier than other components due to its southward flow direction. Two sub-stages within the maturity stage are recognized from best-fitted amplitude increasing velocities and the satellite image of the Sanyanyu flow path and the mean movement velocities of the Sanyanyu debris flow during these two sub-stages are estimated to be 9.2 and 9.7 m s−1 respectively.

scholarly journals Bag-of-words-based anomaly-detection principal component analysis and stochastic optimization for debris flow detection and evacuation planning

2017 ◽  
Author(s):  
Chia-Chun Kuo ◽  
Yi-Ren Yeh ◽  
Kuan-wen Chou ◽  
Chien-Lin Huang ◽  
Ming-Che Hu
Keyword(s):  
Principal Component Analysis ◽  
Anomaly Detection ◽  
Debris Flow ◽  
Stochastic Optimization ◽  
Debris Flows ◽  
Principal Component ◽  
Evacuation Planning ◽  
Bag Of Words ◽  
Flow Prediction ◽  
Flow Detection

Abstract. Debris flows are natural disasters, with soil mass, rocks, and water traveling down a mountainside slope. Debris flows are extremely dangerous; their occurrence incurs huge losses to life and property. The purpose of this research is to develop debris flow detection and emergency evacuation systems. A bag-of-words model is established for analyzing the features of debris flow events, and an anomaly-detection principal component analysis (PCA) model is proposed to detect debris flow. Using real-time debris flow prediction and monitoring, a stochastic optimization model for evacuation planning is formulated. Case studies of debris flow detection in Shenmu village and Fengchiu, central Taiwan, are conducted. Shenmu village and Fengchiu are areas of high potential debris flow, and each has a population of around 800 people. The results show that combining bag-of-words and anomaly-detection PCA methods could predict 6 out of 8 occurrences of actual events, providing a prediction rate of 75 %. In addition, the models make 13 predictions, and 6 of them are correct, providing a prediction accuracy of 46 %. Optimal parameters (including window size, bag length, filter ratio of training data, and anomaly threshold) of the models are also examined to increase the accuracy of debris flow prediction.

scholarly journals Learning Case Study of a Shallow-Water Model to Assess an Early-Warning System for Fast Alpine Muddy-Debris-Flow

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 750
Author(s):  
Antonio Pasculli ◽  
Jacopo Cinosi ◽  
Laura Turconi ◽  
Nicola Sciarra
Keyword(s):  
Debris Flow ◽  
Shallow Water ◽  
Early Warning ◽  
Debris Flows ◽  
Early Warning System ◽  
Warning System ◽  
Extreme Weather Events ◽  
Water Model ◽  
Computational Time ◽  
Processing Unit

The current climate change could lead to an intensification of extreme weather events, such as sudden floods and fast flowing debris flows. Accordingly, the availability of an early-warning device system, based on hydrological data and on both accurate and very fast running mathematical-numerical models, would be not only desirable, but also necessary in areas of particular hazard. To this purpose, the 2D Riemann–Godunov shallow-water approach, solved in parallel on a Graphical-Processing-Unit (GPU) (able to drastically reduce calculation time) and implemented with the RiverFlow2D code (version 2017), was selected as a possible tool to be applied within the Alpine contexts. Moreover, it was also necessary to identify a prototype of an actual rainfall monitoring network and an actual debris-flow event, beside the acquisition of an accurate numerical description of the topography. The Marderello’s basin (Alps, Turin, Italy), described by a 5 × 5 m Digital Terrain Model (DTM), equipped with five rain-gauges and one hydrometer and the muddy debris flow event that was monitored on 22 July 2016, were identified as a typical test case, well representative of mountain contexts and the phenomena under study. Several parametric analyses, also including selected infiltration modelling, were carried out in order to individuate the best numerical values fitting the measured data. Different rheological options, such as Coulomb-Turbulent-Yield and others, were tested. Moreover, some useful general suggestions, regarding the improvement of the adopted mathematical modelling, were acquired. The rapidity of the computational time due to the application of the GPU and the comparison between experimental data and numerical results, regarding both the arrival time and the height of the debris wave, clearly show that the selected approaches and methodology can be considered suitable and accurate tools to be included in an early-warning system, based at least on simple acoustic and/or light alarms that can allow rapid evacuation, for fast flowing debris flows.

scholarly journals Numerical Simulation of Non-Homogeneous Viscous Debris-Flows Based on the Smoothed Particle Hydrodynamics (SPH) Method

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2314 ◽  
Author(s):  
Shu Wang ◽  
Anping Shu ◽  
Matteo Rubinato ◽  
Mengyao Wang ◽  
Jiping Qin
Keyword(s):  
Debris Flow ◽  
Water Content ◽  
Smoothed Particle Hydrodynamics ◽  
Debris Flows ◽  
Sph Method ◽  
Particle Hydrodynamics ◽  
Sph Model ◽  
Smoothed Particle ◽  
The Impact ◽  
Kinetic And Potential Energies

Non-homogeneous viscous debris flows are characterized by high density, impact force and destructiveness, and the complexity of the materials they are made of. This has always made these flows challenging to simulate numerically, and to reproduce experimentally debris flow processes. In this study, the formation-movement process of non-homogeneous debris flow under three different soil configurations was simulated numerically by modifying the formulation of collision, friction, and yield stresses for the existing Smoothed Particle Hydrodynamics (SPH) method. The results obtained by applying this modification to the SPH model clearly demonstrated that the configuration where fine and coarse particles are fully mixed, with no specific layering, produces more fluctuations and instability of the debris flow. The kinetic and potential energies of the fluctuating particles calculated for each scenario have been shown to be affected by the water content by focusing on small local areas. Therefore, this study provides a better understanding and new insights regarding intermittent debris flows, and explains the impact of the water content on their formation and movement processes.

The Debris Flow Disaster Faster-Than-Early Forecast System (DFS) with Multi-Sensors Integrated Wireless Sensor Networks

2013 ◽  
Vol 347-350 ◽  
pp. 975-979
Author(s):  
Rong Zhao ◽  
Cai Hong Li ◽  
Yun Jian Tan ◽  
Jun Shi ◽  
Fu Qiang Mu ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Debris Flow ◽  
Real Time ◽  
Debris Flows ◽  
Base Station ◽  
Base Stations ◽  
Wireless Sensor ◽  
Forecast System ◽  
Debris Flow Disaster

This paper presents a Debris Flow Disaster Faster-than-early Forecast System (DFS) with wireless sensor networks. Debris flows carrying saturated solid materials in water flowing downslope often cause severe damage to the lives and properties in their path. Faster-than-early or faster-than-real-time forecasts are imperative to save lives and reduce damage. This paper presents a novel multi-sensor networks for monitoring debris flows. The main idea is to let these sensors drift with the debris flow, to collect flow information as they move along, and to transmit the collected data to base stations in real time. The Raw data are sent to the cloud processing center from the base station. And the processed data and the video of the debris flow are display on the remote PC. The design of the system address many challenging issues, including cost, deployment efforts, and fast reaction.

scholarly journals Geohazards Susceptibility Assessment along the Upper Indus Basin Using Four Machine Learning and Statistical Models

2021 ◽  
Vol 10 (5) ◽  
pp. 315
Author(s):  
Hilal Ahmad ◽  
Chen Ningsheng ◽  
Mahfuzur Rahman ◽  
Md Monirul Islam ◽  
Hamid Reza Pourghasemi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Land Cover ◽  
Debris Flows ◽  
Regional Scale ◽  
Indus Basin ◽  
Annual Rainfall ◽  
Slope Aspect ◽  
Topographic Wetness Index ◽  
Susceptibility Maps ◽  
Landslides And Debris Flows

The China–Pakistan Economic Corridor (CPEC) project passes through the Karakoram Highway in northern Pakistan, which is one of the most hazardous regions of the world. The most common hazards in this region are landslides and debris flows, which result in loss of life and severe infrastructure damage every year. This study assessed geohazards (landslides and debris flows) and developed susceptibility maps by considering four standalone machine-learning and statistical approaches, namely, Logistic Regression (LR), Shannon Entropy (SE), Weights-of-Evidence (WoE), and Frequency Ratio (FR) models. To this end, geohazard inventories were prepared using remote sensing techniques with field observations and historical hazard datasets. The spatial relationship of thirteen conditioning factors, namely, slope (degree), distance to faults, geology, elevation, distance to rivers, slope aspect, distance to road, annual mean rainfall, normalized difference vegetation index, profile curvature, stream power index, topographic wetness index, and land cover, with hazard distribution was analyzed. The results showed that faults, slope angles, elevation, lithology, land cover, and mean annual rainfall play a key role in controlling the spatial distribution of geohazards in the study area. The final susceptibility maps were validated against ground truth points and by plotting Area Under the Receiver Operating Characteristic (AUROC) curves. According to the AUROC curves, the success rates of the LR, WoE, FR, and SE models were 85.30%, 76.00, 74.60%, and 71.40%, and their prediction rates were 83.10%, 75.00%, 73.50%, and 70.10%, respectively; these values show higher performance of LR over the other three models. Furthermore, 11.19%, 9.24%, 10.18%, 39.14%, and 30.25% of the areas corresponded to classes of very-high, high, moderate, low, and very-low susceptibility, respectively. The developed geohazard susceptibility map can be used by relevant government officials for the smooth implementation of the CPEC project at the regional scale.

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