Modeling the Spatial Distribution of Debris Flows and Analysis of the Controlling Factors: A Machine Learning Approach

Debris flows are a major geological hazard in mountainous regions. For improving mitigation, it is important to study the spatial distribution and factors controlling debris flows. In the Bailong River Basin, central China, landslides and debris flows are very well developed due to the large differences in terrain, the complex geological environment, and concentrated rainfall. For analysis, 52 influencing factors, statistical, machine learning, remote sensing and GIS methods were used to analyze the spatial distribution and controlling factors of 652 debris flow catchments with different frequencies. The spatial distribution of these catchments was divided into three zones according to their differences in debris flow frequencies. A comprehensive analysis of the relationship between various factors and debris flows was made. Through parameter optimization and feature selection, the Extra Trees classifier performed the best, with an accuracy of 95.6%. The results show that lithology was the most important factor controlling debris flows in the study area (with a contribution of 26%), followed by landslide density and factors affecting slope stability (road density, fault density and peak ground acceleration, with a total contribution of 30%). The average annual frequency of daily rainfall > 20 mm was the most important triggering factor (with a contribution of 7%). Forest area and vegetation cover were also important controlling factors (with a total contribution of 9%), and they should be regarded as an important component of debris flow mitigation measures. The results are helpful to improve the understanding of factors influencing debris flows and provide a reference for the formulation of mitigation measures.

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Effectiveness of debris flow mitigation strategies in mountainous regions

Progress in Physical Geography Earth and Environment ◽

10.1177/0309133316655304 ◽

2016 ◽

Vol 40 (6) ◽

pp. 768-793 ◽

Cited By ~ 14

Author(s):

Muqi Xiong ◽

Xingmin Meng ◽

Siyuan Wang ◽

Peng Guo ◽

Yajun Li ◽

...

Keyword(s):

Debris Flow ◽

Debris Flows ◽

Civil Engineering ◽

Robinia Pseudoacacia ◽

Climatic Conditions ◽

Mitigation Strategies ◽

Mitigation Measures ◽

Material Source ◽

Mountainous Regions ◽

Check Dams

Debris flows represent major hazards in most mountainous regions of the world where they repeatedly result in disasters. In order to protect people and infrastructure against future debris flows, many debris flow catchments have been artificially intervened by employing various mitigation measures, including civil engineering works. However, the commonly adapted engineering measures, such as check dams, are not effective for every debris flow catchment, and the failure of such measures even causes more damage, e.g. the Sanyanyu debris flow catchment in Zhouqu, China, killed 1756 people. In order to research the effectiveness of engineering strategies and explore much more effective mitigation works for debris flows in the mountainous regions, we took the Bailong River catchment of Southern Gansu of China as study area, with special emphasis on Sanyanyu debris flow catchment (with civil engineering works) and Goulinping debris flow catchment (without civil engineering works), and comparatively analysed the two catchments. The comparative results show that both catchments have similar material source, geomorphological/environmental and climatic conditions, however, vegetation cover and rock hardness are poorer in Goulinping than in Sanyanyu, the catchment that underwent larger-scale debris flows, suggesting that the mitigation measures had been applied in Sanyanyu catchment were inappropriate. Subsequently, we simulated the effectiveness of controlling debris flow peak discharge with check dams at the lower part of Sanyanyu and Goulinping catchment using the Kanako simulator, and summarised argument based on the hypothesis and facts from positive and negative aspects. We draw the conclusion that it is not reasonable to build check dams in the two catchments and instead, drainage channels should be primarily considered for reducing debris flow hazards in such densely populated areas. Finally, we undertook detailed field investigations and experiments on the native plants in the region, and found that the ecological mitigation measure with planting Robinia Pseudoacacia on the debris flow deposits is an effective method to alleviate debris flow hazards. It is concluded that channel works combined with ecological measures are the preferable approaches to minimize the debris flow damage in debris flow catchments characterised with high mountains, concentrated rainfalls and active neotectonic movement.

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Spatial distribution and controlling factors of snow avalanche and debris flow in Parâng Mountains

10.15551/prgs.2017.53 ◽

2017 ◽

Author(s):

Ionela Gavrilă ◽

Olimpiu Pop ◽

Csaba Horvath ◽

Flaviu Meseșan ◽

Iulian Holobâcă

Keyword(s):

Spatial Distribution ◽

Debris Flow ◽

Controlling Factors ◽

Snow Avalanche

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Mitigation of Debris Flows—Research and Practice in Hong Kong

Environmental and Engineering Geoscience ◽

10.2113/eeg-d-20-00009 ◽

2021 ◽

Vol 27 (2) ◽

pp. 231-243

Author(s):

Ken K. S. Ho ◽

Raymond C. H. Koo ◽

Julian S. H. Kwan

Keyword(s):

Hong Kong ◽

Debris Flow ◽

Debris Flows ◽

Geotechnical Engineering ◽

Mitigation Strategies ◽

Mitigation Measures ◽

Landslide Risk ◽

Engineering Practice ◽

Design Methodologies ◽

Technical Framework

ABSTRACT Dense urban development on a hilly terrain coupled with intense seasonal rainfall and heterogeneous weathering profiles give rise to acute debris-flow problems in Hong Kong. The Geotechnical Engineering Office (GEO) of the Hong Kong SAR Government has launched a holistic research and development (R&D) programme and collaborated with various tertiary institutes and professional bodies to support the development of a comprehensive technical framework for managing landslide risk and designing debris-flow mitigation measures. The scope of the technical development work includes compilation of landslide inventories, field studies of debris flows, development and calibration of tools for landslide run-out modelling, back analysis of notable debris flows, physical and numerical modelling of the interaction between debris flows and mitigation measures, formulation of a technical framework for evaluating debris-flow hazards, and development of pragmatic mitigation strategies and design methodologies for debris-flow countermeasures. The work has advanced the technical understanding of debris-flow hazards and transformed the natural terrain landslide risk management practice in Hong Kong. New analytical tools and improved design methodologies are being applied in routine geotechnical engineering practice.

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Morphometrical analysis of Debris flow fans and torrential catchments in mountainous terrain in the northern Colombian Andes by machine learning techniques.

10.5194/egusphere-egu21-3680 ◽

2021 ◽

Author(s):

Emanuel Castillo Cardona ◽

Edier Aristizábal

Keyword(s):

Machine Learning ◽

Debris Flow ◽

Land Use Planning ◽

Machine Learning Techniques ◽

Main Stream ◽

Mountain Range ◽

Mountainous Regions ◽

Colombian Andes ◽

Learning Techniques ◽

Qualitative Variables

<p>Debris flow fans are commonly occupied by urban and rural settlements in mountainous regions such as in the northern Colombian Andes. Those fans are originated by violent surges of high sediment concentration that are then mobilized downstream by strong currents during torrential events highly destructive. Then, characterization and understanding of the dynamics that give rise to fans in tropical and mountainous regions such as Andean zone is a fundamental tool for land use planning. This research focuses on cartography of fans and catchments using digital elevation models in the central and western mountain range of the northern part of the Andean mountain belt. The methodology considered: morphometric measurements of the catchments and fans, lithological aspects of the catchments, type of catchments (torrential or no torrential). Then the correlation between morphometric parameters of fans and catchments is carried out, including relationships with qualitative variables by multivariate statistical analysis and machine learning techniques to find patterns between quantitative and qualitative variables. The results indicate that slope of the fans has a high correlation with Melton index of the catchments and with the slope of the main stream of the catchments. About the qualitative classification of the catchments in torrential and no torrential, it is observed that there are good discriminations for slope of the fan, volume of the deposits(fans), the relationship between the relief of the catchments and other variables. On the other hand, the lithology of the catchments does not have strong influences on the morphometry of the fans.</p>

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Debris Flow Damage Assessment by Considering Debris Flow Direction and Direction Angle of Structure in South Korea

Water ◽

10.3390/w11020328 ◽

2019 ◽

Vol 11 (2) ◽

pp. 328 ◽

Cited By ~ 4

Author(s):

Dong Nam ◽

Man-Il Kim ◽

Dong Kang ◽

Byung Kim

Keyword(s):

South Korea ◽

Debris Flow ◽

Debris Flows ◽

Impact Force ◽

Mountainous Areas ◽

Mountainous Regions ◽

Impact Forces ◽

The Impact

Recently, human and property damages have often occurred due to various reasons—such as landslides, debris flow, and other sediment-related disasters—which are also caused by regional torrential rain resulting from climate change and reckless development of mountainous areas. Debris flows mainly occur in mountainous areas near urban living communities and often cause direct damages. In general, debris flows containing soil, rock fragments, and driftwood temporarily travel down to lower parts along with a mountain torrent. However, debris flows are also often reported to stream down from the point where a slope failure or a landslide occurs in a mountain directly to its lower parts. The impact of those debris flows is one of the main factors that cause serious damage to structures. To mitigate such damage of debris flows, a quantitative assessment of the impact force is thus required. Moreover, technologies to evaluate disaster prevention facilities and structures at disaster-prone regions are needed. This study developed two models to quantitatively analyze the damages caused by debris flows on structures: Type-1 model for calculating the impact force, which reflected the flow characteristics of debris flows and the Type-2 model, which calculated the impact force based on the topographical characteristics of mountainous regions. Using RAMMS a debris flow runoff model, the impact forces assessed through Type-1 and Type-2 models were compared to check reliability. Using the assessed impact forces, the damage ratio of the structures was calculated and the amount of damage caused by debris flows on the structures was ultimately assessed. The results showed that the Type-1 model overestimated the impact force by 10% and the Type-2 model by 4% for Mt. Umyeon in Seoul, compared to the RAMMS model. In addition, the Type-1 model overestimated the impact force by 3% and Type-2 by 2% for Mt. Majeok in Chuncheon, South Korea.

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Spatial Distribution Features of Debris Flows at Active Fault Zone Along Ya-Lu Highway, China

The Open Civil Engineering Journal ◽

10.2174/1874149501711010563 ◽

2017 ◽

Vol 11 (1) ◽

pp. 563-571

Author(s):

Dingying Yang ◽

Zheng Han ◽

Yange Li

Keyword(s):

Spatial Distribution ◽

Debris Flow ◽

Debris Flows ◽

Active Fault ◽

Active Faults ◽

Western China ◽

Polar Coordinate System ◽

Vertical Distance ◽

Distribution Features ◽

In Situ Investigation

Introduction: Active faults and accompanied tectonic activities are a key triggering factor for debris flows in mountainous region. In this paper, the spatial distribution of 19 debris flows along Ya-Lu highway in western China was analyzed. Method: We collected basic data of these 19 debris-flow gullies in the in-situ investigation work, and documented key parameters including watershed area, the averaged slope gradient, gully type, debris-flow magnitude, and developing stage of the gully. Based on the DTM data from SRTM database, the overall spatial distribution features of these debris flows are analyzed. Result and Conclusion: We used a polar coordinate system to illustrate the relationship between debris flow magnitude and the direct distance to the active fault. In this system, the spatial distribution of these debris flows is represented by the vertical distance to the fault and the angle between gullies to the fault. It is revealed that the debris-flow magnitude has a close positive relationship with the vertical distance to the active fault, that generally debris-flow magnitude increases as closing to the active fault.

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Forecasting of Debris Flow Using Machine Learning-Based Adjusted Rainfall Information and RAMMS Model

Water ◽

10.3390/w13172360 ◽

2021 ◽

Vol 13 (17) ◽

pp. 2360

Author(s):

Cheong-Hyeon Oh ◽

Kyung-Su Choo ◽

Chul-Min Go ◽

Jung-Ryel Choi ◽

Byung-Sik Kim

Keyword(s):

Machine Learning ◽

Debris Flow ◽

Debris Flows ◽

Precipitation Forecast ◽

Main Body ◽

Observation Data ◽

Flow Models ◽

The Past ◽

Quantitative Precipitation Forecast ◽

Heavy Rainfalls

In recent years, climate change and extreme weather conditions have caused natural disasters of various sizes and forms across the world. The increase in the resulting flood damage and secondary damage has also inflicted massive social and economic harm. Korea is no exception, where debris flows created by typhoons and localized heavy rainfalls have caused human injuries and property damage in the Wumyeonsan Mountain in Seoul, Majeoksan Mountain in Chuncheon, Sinnam in Samcheok, Gokseong in Jeollanam-do, and Anseong in Gyeonggi-do. Disaster damage needs to be minimized by preparing for typhoons and heavy rainfalls that cause debris flow. To that end, we need accurate prediction of rainfall and flooding through simulations based on debris flow models. Most of the previous literature analyzed debris flows using rainfall events in the past before debris flow occurrence, rather than analyzing and predicting based on rainfall predictions. The main body of this study assesses the applicability of hydrological quantitative precipitation forecast (HQPF) generated through a machine learning method named the Random Forest (RF) method to debris flow analysis models. To that end, this study uses scatter plots to compare and analyze the precipitation observation data collected from the areas hit by debris flows in the past, and the quantitative precipitation forecast (QPF) and HQPF data from the Korea Meteorological Administration (KMA). Based on the verified HQPF data, runoff was calculated using the spatial runoff assessment tool (S-RAT) model, and the soil amount was calculated to simulate the debris flow damage with a two-dimensional rapid mass movements (RAMMS) model. The debris flow simulation based on the said data indicated varying degrees of flow depth, impact force, speed, and damage area depending on the precipitation. The correction of the HQPF was verified by measuring and comparing the spatial location accuracy by analyzing the Lee Sallee shape index (LSSI) of the damage areas. The findings confirm the correction of the HQPF based on machine learning and indicate its applicability to debris flow models.

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Characteristics of the Disastrous Debris Flow of Chediguan Gully in Yinxing Town, Sichuan Province, on August 20, 2019

10.21203/rs.3.rs-798905/v1 ◽

2021 ◽

Author(s):

Li Ning ◽

Tang Chuan ◽

Zhang Xianzheng ◽

Chang Ming ◽

Shu Zhile ◽

...

Keyword(s):

Debris Flow ◽

Wenchuan Earthquake ◽

Debris Flows ◽

Warning System ◽

Mitigation Measures ◽

High Definition ◽

Flood Peak ◽

The Wenchuan Earthquake ◽

Minjiang River ◽

Monitoring And Early Warning

Abstract On August 20, 2019, at 2 a.m., a disastrous debris flow occurred in Chediguan gully in Yinxing town, China. The debris flow destroyed the drainage groove and the bridge at the exit of the gully. In addition, the debris flow temporarily blocked the Minjiang River during the flood peak, flooding the Taipingyi hydropower station 200 m upstream and leaving two plant workers missing. To further understand the activity of the debris flow after the Wenchuan earthquake, the characteristics of this debris flow event were studied. Eleven years after the Wenchuan earthquake, a disastrous debris flow still occurred in the Chediguan catchment, causing more severe losses than those of earlier debris flows. In this paper, the formation mechanism and dynamic characteristics of this debris flow event are analysed based on a drone survey, high-definition remote sensing interpretations and other means. The catastrophic debris flow event indicates that debris flows in the Wenchuan earthquake area are still active. A large amount of dredging work in the main gully could effectively reduce the debris flow risk in the gully. In addition, it is also important to repair or rebuild damaged mitigation measures and to establish a real-time monitoring and early warning system for the high-risk gully.

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Contribution of Excessive Supply of Solid Material to a Runoff-Generated Debris Flow during Its Routing Along a Gully and Its Impact on the Downstream Village with Blockage Effects

Water ◽

10.3390/w11010169 ◽

2019 ◽

Vol 11 (1) ◽

pp. 169 ◽

Cited By ~ 10

Author(s):

Ming-liang Chen ◽

Xing-nian Liu ◽

Xie-kang Wang ◽

Tao Zhao ◽

Jia-wen Zhou

Keyword(s):

Debris Flow ◽

Debris Flows ◽

Large Scale ◽

Residential Buildings ◽

Solid Material ◽

Sediment Supply ◽

Mitigation Measures ◽

Dry Land ◽

Field Investigations ◽

Abundant Supply

On 8 August 2017, a runoff-generated debris flow occurred in the Puge County, Sichuan Province of southwestern China and caused huge property damage and casualties (25 people died and 5 people were injured). Emergency field investigations found that paddy fields, dry land, residential buildings and roads suffered different degrees of impact from the debris flow. This paper reveals the formation process of the debris flow by analyzing the characteristics of rainfall precipitation and sediment supply conditions in the study area and it approaches the practical application of hazard prevention and mitigation constructions. Doppler weather radar analysis indicates that a very high intensity rainfall occurred in the middle and upper zones of the basin, illustrating the importance of enhancing rainfall monitoring in high-altitude areas. The abundant supply of deposits in gully channels is among the significant causes of a transformation from mountain floods to large-scale debris flows. It was also found that the two culverts played an important role in the movement affecting the processes of debris flows which has substantially aggravated the destructive outcome. The excessive supply of solid material and local blockage with outburst along a gully must receive significant attention for the prediction of future debris flows, hazard prevention and mitigation measures.

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Debris-flow velocity and volume estimations based on seismic data

10.5194/nhess-2020-411 ◽

2021 ◽

Author(s):

Andreas Schimmel ◽

Velio Coviello ◽

Francesco Comiti

Keyword(s):

Debris Flow ◽

Flow Velocity ◽

Seismic Data ◽

Debris Flows ◽

Cross Correlation ◽

Sampling Rate ◽

Early Warning Systems ◽

Velocity Estimation ◽

Mitigation Measures ◽

Strong Control

Abstract. The estimation of debris-flow velocity and volume is a fundamental task for the development of early warning systems, the design of control structures and other mitigation measures. Previous analysis of the seismic energy produced by debris flows showed that the peak amplitudes are representative of the kinetic energy of each surge and debris-flow discharge can be therefore estimated based on seismic signals. Also, the debris-flow velocity can be calculated using seismic data recorded at two spatial separated stations located along the channel by the use of cross-correlation. This work provide a first approach for estimating the total volume of debris flows based on the seismic signal detected with simple, low-cost geophones installed along the debris-flow channel. The developed methods was applied to seismic data collected on three different test sites in the Alps: Gadria (IT), Lattenbach (AT), and Cancia (IT). An adaptable cross-correlation time window was used, which can offer a better estimation of the velocity compared to a constant window length. The analyses of the seismic data of 14 debris flows that occurred from 2014 to 2018 shows the strong control of the sampling rate and the sensor-distance on the velocity estimation. A simple approach based on a linear relation between square of the seismic amplitude and the event magnitude is proposed for a first order estimation of the debris-flow magnitude.

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