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Debris Flows Research: Hazard and Risk Assessments
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Debris Flows Research: Hazard and Risk Assessments

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydraulics and Hydrodynamics".

Deadline for manuscript submissions: closed (15 October 2021) | Viewed by 29348

Special Issue Editors

Dr. Matthias Jakob

E-Mail Website
Guest Editor
BGC Engineering Inc., Canada
Interests: debris flow hazard and risk assessments
Dr. Scott McDougall

E-Mail Website
Guest Editor
Department of Earth, Ocean and Atmospheric Sciences Faculty of Science, Vancouver, Canada
Interests: rock avalanches; debris flows; debris floods; tailings dam breaches; shoreline erosion and landslide-generated waves

Special Issue Information

Dear Colleagues,

Substantial advances have been made in various aspects of debris-flow hazard and risk assessments over the past decade. These include sophisticated ways to date previous events, two and three-dimensional runout models including multiphase flows and debris entrainment options, and applications of extreme value statistics to assemble frequency–magnitude analyses. Quantitative risk management (QRM) has emerged as the most rational and defensible method to assess debris-flow risk and optimize mitigation efforts. The pertinent questions, of course, have remained the same: How often, how big, how fast, how deep, how intense, how far, and how bad? Similarly, while major life loss attributable to debris flows can often, but not always, be avoided in developed nations, debris flows remain one of the principal geophysical killers in mountainous terrains. Substantial differences persist between nations in hazard or risk management. Some rely on a design magnitude associated with a specific return period, others use relationships between intensity and frequency, and some allow for, but do not mandate, in-depth quantitative risk assessments. The range in return periods considered in hazard and risk assessments vary over two orders of magnitude from 1:100 to 1:10,000. Similarly, profound differences exist in the management of debris-flow risks, from highly sophisticated and nationwide applied protocols and funding formulae to a largely retroactive approach in which catastrophic debris flows occur before they are being considered for mitigation. In many nations, access to funding and lack of at least regional prioritization provides the biggest obstacles to widespread safeguarding against debris flows. Two factors conspire to challenge future generations of debris flow researchers, practitioners, and decision makers: Population growth and climate change. The former will invariably invite continued development in debris-flow prone areas, especially fans, floodplains, and terraces subject to lahars or landslide/moraine dam/glacial outburst floods which, at times, assume debris-flow characteristics. As far as debris flows are concerned, climate change is manifesting itself increasingly by augmenting hydroclimatic extremes, especially a several-fold increase in the frequency of short-duration high-intensity rainfall that may soon exceed historical precedents. Increases in magnitude of extreme rainfall scale closely related to the Clausius–Clapeyron relationship, though exceptions to this generalization have been noted.

This Special Issue focuses on significant advances in hazard and risk assessments of debris flows, which aresubjects of intense study. Contributions are encouraged that present studies in which a new method has been advanced, or an existing method is being used in an innovative way in solving old puzzles. Special focus should be placed on the direct applicability of such methods in practice and their testing on well-researched debris-flow locations.

Dr. Matthias Jakob
Dr. Scott McDougall
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Hazard assessment
  • Risk assessment
  • Quantitative methods
  • Empirical relationships
  • Runout models

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Published Papers (7 papers)

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Research

22 pages, 21411 KiB  
Article
Modelling Debris Flow Runout: A Case Study on the Mesilau Watershed, Kundasang, Sabah
by Muhammad Iylia Rosli, Faizah Che Ros, Khamarrul Azahari Razak, Sumiaty Ambran, Samira Albati Kamaruddin, Aznah Nor Anuar, Aminaton Marto, Tetsuo Tobita and Yusuke Ono
Water 2021, 13(19), 2667; https://doi.org/10.3390/w13192667 - 27 Sep 2021
Cited by 12 | Viewed by 4735
Abstract
Debris flows are among the fatal geological hazards in Malaysia, with 23 incidents recorded in the last two decades. To date, very few studies have been carried out to understand the debris flow processes, causes, and runouts nationwide. This study simulated the debris [...] Read more.
Debris flows are among the fatal geological hazards in Malaysia, with 23 incidents recorded in the last two decades. To date, very few studies have been carried out to understand the debris flow processes, causes, and runouts nationwide. This study simulated the debris flow at the Mesilau watershed of Kundasang Sabah caused by the prolonged rainfall after the 2015 Ranau earthquake. Several interrelated processing platforms, such as ArcGIS, HEC-HMS, and HyperKANAKO, were used to extract the parameters, model the debris flow, and perform a sensitivity analysis to achieve the best-fit debris flow runout. The debris flow travelled at least 18.6 km to the Liwagu Dam. The best-fit runout suggested that the average velocity was 12.5 m/s and the lead time to arrive at the Mesilau village was 4.5 min. This high debris flow velocity was probably due to the high-water content from the watershed baseflow with a discharge rate of 563.8 m3/s. The flow depth and depositional thickness were both lower than 5.0 m. This study could provide crucial inputs for designing an early warning system, improving risk communication, and strengthening the local disaster risk reduction and resilience strategy in a tectonically active area in Malaysia. Full article
(This article belongs to the Special Issue Debris Flows Research: Hazard and Risk Assessments)
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23 pages, 14921 KiB  
Article
Forecasting of Debris Flow Using Machine Learning-Based Adjusted Rainfall Information and RAMMS Model
by Cheong-Hyeon Oh, Kyung-Su Choo, Chul-Min Go, Jung-Ryel Choi and Byung-Sik Kim
Water 2021, 13(17), 2360; https://doi.org/10.3390/w13172360 - 27 Aug 2021
Cited by 4 | Viewed by 3335
Abstract
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, [...] Read more.
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. Full article
(This article belongs to the Special Issue Debris Flows Research: Hazard and Risk Assessments)
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20 pages, 27702 KiB  
Article
Debris Flow Susceptibility Assessment Using the Integrated Random Forest Based Steady-State Infinite Slope Method: A Case Study in Changbai Mountain, China
by Alu Si, Jiquan Zhang, Yichen Zhang, Emmanuel Kazuva, Zhenhua Dong, Yongbin Bao and Guangzhi Rong
Water 2020, 12(7), 2057; https://doi.org/10.3390/w12072057 - 20 Jul 2020
Cited by 8 | Viewed by 3219
Abstract
Debris flow events often pose significant damage and are a threat to infrastructure and even livelihoods. Recent studies have mainly focused on determining the susceptibility of debris flow using deterministic or heuristic/probabilistic models. However, each type of model has its own significant advantages [...] Read more.
Debris flow events often pose significant damage and are a threat to infrastructure and even livelihoods. Recent studies have mainly focused on determining the susceptibility of debris flow using deterministic or heuristic/probabilistic models. However, each type of model has its own significant advantages with some irreparable disadvantages. The random forest model, which is sensitive to the region where the terrain conditions are suitable for the occurrence of debris flow, was applied along with the steady-state infinite slope method, which is capable of describing the initiation mechanism of debris flow. In this manner, a random-forest-based steady-state infinite slope method was used to conduct susceptibility assessment of debris-flow at Changbai mountain area. Results showed that the assessment accuracy of the proposed random-forest-based steady-state infinite slope method reached 90.88%; however, the accuracy of just the random forest model or steady-state infinite slope method was only 88.48% or 60.45%, respectively. Compared with the single-model assessment results, the assessment accuracy of the proposed method improved by 2.4% and 30.43%, respectively. Meanwhile, the debris-flow-prone area of the proposed method was reduced. The random-forest-based steady-state infinite slope method inherited the excellent diagnostic performance of the random-forest models in the region where the debris flow disaster already occurred; meanwhile, this method further refined the debris-flow-prone area from the suitable terrain area based on physico-mechanical properties; thus, the performance of this method was better than those of the other two models. Full article
(This article belongs to the Special Issue Debris Flows Research: Hazard and Risk Assessments)
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23 pages, 11284 KiB  
Article
Rockfall and Debris Flow Hazard Assessment in the SW Escarpment of Montagna del Morrone Ridge (Abruzzo, Central Italy)
by Monia Calista, Valeria Menna, Vania Mancinelli, Nicola Sciarra and Enrico Miccadei
Water 2020, 12(4), 1206; https://doi.org/10.3390/w12041206 - 23 Apr 2020
Cited by 21 | Viewed by 4365
Abstract
The purpose of this research is to estimate the rockfall and debris flow hazard assessment of the SW escarpment of the Montagna del Morrone (Abruzzo, Central Italy). The study investigated the geomorphology of the escarpment, focusing on the type and distribution of the [...] Read more.
The purpose of this research is to estimate the rockfall and debris flow hazard assessment of the SW escarpment of the Montagna del Morrone (Abruzzo, Central Italy). The study investigated the geomorphology of the escarpment, focusing on the type and distribution of the present landforms. Particular attention was devoted to the slope gravity landforms widely developed in this area, where the effective activity of the gravitational processes is mainly related to the rockfall and debris flows and documented by numerous landslides over time. Working from orography, hydrography, lithology, and geomorphology, the landslide distribution and their potential invasion areas were evaluated through two specific numerical modeling software. RAMMS and Rockyfor3D calculation codes were used in order to analyze the debris flow and rockfall type of landslides, respectively. The obtained results are of great interest when evaluating the hazard assessment in relation to the potential landslides. Moreover, the geographic information systems (GIS) provide a new geomorphological zonation mapping, with the identification of the detachment and certain and/or possible invasion areas of the landslide blocks. This method provides an effective tool to support the correct territorial planning and the management of the infrastructural settlements present in the area and human safety. Full article
(This article belongs to the Special Issue Debris Flows Research: Hazard and Risk Assessments)
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18 pages, 5511 KiB  
Article
Debris Flow Generation Based on Critical Discharge: A Case Study of Xiongmao Catchment, Southwestern China
by Lingfeng Gong, Chuan Tang, Jiang Xiong and Ning Li
Water 2020, 12(2), 552; https://doi.org/10.3390/w12020552 - 15 Feb 2020
Cited by 8 | Viewed by 3813
Abstract
Generation of debris flows is related to poorly sorted mixtures of soil, catchment topography, and rainfall characteristics. Runoff in a valley resulting from intensive rainfall can induce sediment movement within stream beds or along adjacent banks. The water flow in channels is affected [...] Read more.
Generation of debris flows is related to poorly sorted mixtures of soil, catchment topography, and rainfall characteristics. Runoff in a valley resulting from intensive rainfall can induce sediment movement within stream beds or along adjacent banks. The water flow in channels is affected by rainfall parameters such as duration, intensity, cumulative rainfall, etc., and is the key factor in debris movement. In this paper, the rainfall characteristics and occurrence conditions of debris flow in Xiongmao Gully on 26 July 2016 were explored. Using data from field surveys and indoor simulation experiments, evaluations of critical discharge parameters for debris movement were performed. Furthermore, debris distribution and the critical discharge characteristics were analyzed via investigation of the catchment topography and cause of the debris flow, and analysis was made of the critical discharge parameters initiating channel debris movement. A K-value clustering analysis method was applied to characterize the rainfall pattern of the study area and its effects on calculation of debris flow. The results showed that for the debris flow in Xiongmao Gully, the debris initiation in the middle reaches of the gully provided the majority of solid particles for the disaster on 26 July 2016, and the upstream confluent provided catchment. Based on the relationship determined by laboratory tests, the calculated critical discharge was 43.8 m3/s, less than the peak discharge (Qc = 66.7 m3/s) calculated by morphological method. In addition, it was indicated that the dominant rainfall patterns of the studied area were first-quartile and second-quartile, i.e., the rainfall occurred primarily at the early or middle stage of this rainfall event. The critical discharge for the debris flow on 26 July was achieved at 5% rainfall frequency, and the larger runoff volume was generated from a short heavy rainfall. According to specific catchment characteristics, such as distributed hydrological analysis, critical discharge, and rainfall pattern of debris flow, forewarning of a damaging debris flow could be made more effective. Full article
(This article belongs to the Special Issue Debris Flows Research: Hazard and Risk Assessments)
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24 pages, 6648 KiB  
Article
Hazard Assessment Based on the Combination of DAN3D and Machine Learning Method for Planning Closed-Type Barriers against Debris-Flow
by Enok Cheon, Seung-Rae Lee and Deuk-Hwan Lee
Water 2020, 12(1), 170; https://doi.org/10.3390/w12010170 - 7 Jan 2020
Viewed by 4142
Abstract
If a slope located near a densely populated region is susceptible to debris-flow hazards, barriers are used as a mitigation method by placing them in flow channels; i.e., flowpaths. Selecting the location and the design of a barrier requires hazard assessment to determine [...] Read more.
If a slope located near a densely populated region is susceptible to debris-flow hazards, barriers are used as a mitigation method by placing them in flow channels; i.e., flowpaths. Selecting the location and the design of a barrier requires hazard assessment to determine the width, volume, and impact pressure of debris-flow at the moment of collision. DAN3D (Three-Dimensional Dynamic Analysis), a 3D numerical model for simulating debris-flow, has been widely used to perform hazard assessment; however, solely using DAN3D would be both insufficient and inefficient in finding the optimal barrier location. Therefore, the present study developed a framework that interprets the results from DAN3D simulation without considering any barriers. Then, the framework generates hazard assessment maps showing the impact parameters of debris-flow along the flowpath by various algorithms and machine learning methods, such as the k-means clustering algorithm, and also computes the width of the debris-flow, which is not explicitly calculated in DAN3D. A case study of the debris-flow at Umyeon mountain, Korea, in 2011, was used to generate hazard assessment maps. The maps were demonstrated to be a tool to quickly compute the impact parameters for conceptual barrier design with the aim of finding potential barrier locations. Full article
(This article belongs to the Special Issue Debris Flows Research: Hazard and Risk Assessments)
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23 pages, 5462 KiB  
Article
Development of Nomogram for Debris Flow Forecasting Based on Critical Accumulated Rainfall in South Korea
by Dong-Ho Nam, Suk-Ho Lee and Byung-Sik Kim
Water 2019, 11(10), 2181; https://doi.org/10.3390/w11102181 - 19 Oct 2019
Cited by 5 | Viewed by 3962
Abstract
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 [...] Read more.
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 ( R c ) 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. Full article
(This article belongs to the Special Issue Debris Flows Research: Hazard and Risk Assessments)
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