scholarly journals Applications of simulation technique on debris-flow hazard zone delineation: a case study in Hualien County, Taiwan

2010 ◽  
Vol 10 (3) ◽  
pp. 535-545 ◽  
Author(s):  
S. M. Hsu ◽  
L. B. Chiou ◽  
G. F. Lin ◽  
C. H. Chao ◽  
H. Y. Wen ◽  
...  
Keyword(s):  
Debris Flow ◽  
Yield Stress ◽  
Empirical Model ◽  
Water Conservation ◽  
Debris Flows ◽  
Sediment Concentration ◽  
Hazard Zone ◽  
Debris Flow Hazard ◽  
Debris Flow Disaster ◽  
Soil And Water

Abstract. Debris flows pose severe hazards to communities in mountainous areas, often resulting in the loss of life and property. Helping debris-flow-prone communities delineate potential hazard zones provides local authorities with useful information for developing emergency plans and disaster management policies. In 2003, the Soil and Water Conservation Bureau of Taiwan proposed an empirical model to delineate hazard zones for all creeks (1420 in total) with potential of debris flows and utilized the model to help establish a hazard prevention system. However, the model does not fully consider hydrologic and physiographical conditions for a given creek in simulation. The objective of this study is to propose new approaches that can improve hazard zone delineation accuracy and simulate hazard zones in response to different rainfall intensity. In this study, a two-dimensional commercial model FLO-2D, physically based and taking into account the momentum and energy conservation of flow, was used to simulate debris-flow inundated areas. Sensitivity analysis with the model was conducted to determine the main influence parameters which affect debris flow simulation. Results indicate that the roughness coefficient, yield stress and volumetric sediment concentration dominate the computed results. To improve accuracy of the model, the study examined the performance of the rainfall-runoff model of FLO-2D as compared with that of the HSPF (Hydrological Simulation Program Fortran) model, and then the proper values of the significant parameters were evaluated through the calibration process. Results reveal that the HSPF model has a better performance than the FLO-2D model at peak flow and flow recession period, and the volumetric sediment concentration and yield stress can be estimated by the channel slope. The validation of the model for simulating debris-flow hazard zones has been confirmed by a comparison of field evidence from historical debris-flow disaster data. The model can successfully replicate the influence zone of the debris-flow disaster event with an acceptable error and demonstrate a better result than the empirical model adopted by the Soil and Water Conservation Bureau of Taiwan.

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.

Using Fuzzy Inference System to the Analysis of Debris Flow Hazard

2009 ◽  
Author(s):  
Pao H. Lin ◽  
K. H. Chen
Keyword(s):  
Debris Flow ◽  
Interface Design ◽  
Debris Flows ◽  
Evaluation System ◽  
Fuzzy Inference ◽  
Hazard Evaluation ◽  
Graphic User Interface ◽  
Design Environment ◽  
Inference System ◽  
Debris Flow Hazard

In this study 11 factors influential to the evolvement of debris flows are identified via literature review and a thorough comparison among previous studies. Aided by MATLAB software and the concept of property in Fuzzy logic theory, an evaluation system for debris flow hazard is developed. Also, the proposed inference system is facilitated with Graphic User Interface Design Environment, so that observers or researchers may easily become familiar with system operation and utilize the system’s estimation as references for hazard judgment. Validation results with simulated cases of three different degrees of hazard severity evidenced that the present evaluation system on debris flows was effective with debris flows of high, low, and median hazards, as well as acceptable feasibility. Further, based on data gathered from rivers subject to debris flow and several actual cases in Taiwan, this proposed system was proved to achieve acceptable precision on the hazard evaluation of debris flow.

Debris flow hazard mapping considering the effect of mitigation structure – a case study in Taiwan based on numerical simulation

2020 ◽  
Author(s):  
Chih-Hao Hsu ◽  
Chuan-Yi Huang ◽  
Ting-Chi Tsao ◽  
Hsiao-Yuan Yin ◽  
Hsiao-Yu Huang ◽  
...  
Keyword(s):  
Debris Flow ◽  
Water Conservation ◽  
Large Scale ◽  
Mass Movement ◽  
Hazard Mapping ◽  
Hazard Map ◽  
Inundation Depth ◽  
Central Taiwan ◽  
Debris Flow Hazard ◽  
Typhoon Herb

<p>This study added the dams and retain basin according to their dimensions measured with UAV onto the original 5m-resolition DEM to compare the effect of mitigation structures to debris flow hazard. The original and the modified DEMs were both applied to simulate the consequences by using RAMMS::Debris Flow (RApid Mass Movement Simulation) model.</p><p>Hazard map is the best tool to provide the information of debris flow hazard in Taiwan. It has an important role to play in evacuating the residents within the affected zone during typhoon season. For the reason, debris flow hazard maps become a useful tool for local government to execute the evacuation. As the mitigation structure is constructed, the intensity of debris flow hazard reduces.</p><p>The Nantou DF190 debris flow potential torrent is located in central Taiwan. In 1996 when Typhoon Herb stroke, 470,000 cubic-meter of debris were washed out and deposited in 91,200 square-meter area (Yu et al., 2006), and the event caused the destruction of 10 residential houses with 2 fatalities. After the event the Soil and Water Conservation Bureau constructed a 100-meter long sabo dam and sediment retain basin with capacity of 60,000 cubic-meters. In order to compare the difference of affected zone before and after the construction of mitigation structures, the study applies RAMMS to simulate the above-mentioned event.</p><p>The result shows when large-scale debris flow occurs, most of the sediments still overflow and deposit on the fan with shape similar to the 1996 Typhoon Herb event. However, the intensity has reduced significantly with 50% less in area, several meters less in inundation depth and 50% less in flow velocity approximately. The comparison shows the effect of mitigation structures and could provide valuable information for debris flow hazard mapping.</p><p>Key Words: Debris flow, RAMMS, Hazard map, Mitigation, Taiwan</p>

scholarly journals GIS-based modelling of landslide and debris flow hazard in mountainous terrain of Agra Khola watershed, central Nepal

2006 ◽  
Vol 34 ◽  
pp. 117-128
Author(s):  
P. B. Thapa ◽  
T. Esaki ◽  
B. N. Upreti
Keyword(s):  
Debris Flow ◽  
Prediction Model ◽  
Debris Flows ◽  
Flow Distribution ◽  
Spatial Prediction ◽  
Distribution Map ◽  
Central Nepal ◽  
Landslides And Debris Flows ◽  
Debris Flow Hazard ◽  
Hazard Levels

A comprehensive GIS-based analytical approach was followed to derive a spatial database of landslides and debris flows in the Agra Khola watershed of central Nepal which suffered from the hydrological disaster of 1993. For this purpose, the landslides and debris flows occurring in that area between 1993 and 2006 were delineated. From the database, the influence of geological and geomorphic variables was quantified and a spatial prediction model for landslide and debris flow hazard was worked out. In this process, quantitative statistical analysis (bivariate, multivariate) as applied to predict elements or observations between stable and unstable zones. The predicted results were classified into various hazard levels m a hazard map and were validated by comparing it with the landslide and debris flow distribution map of the Agra Khola watershed. Also the GIS-based hazard prediction model has objectivity in the procedure and reproducibility of the results in the mountainous terrains.

scholarly journals Debris-Flow Hazard Assessments: A Practitioner's View

2021 ◽  
Author(s):  
Matthias Jakob
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Three Dimensional ◽  
Extreme Value Statistics ◽  
Major Life ◽  
Two Factors ◽  
Hazard Assessments ◽  
Cost Efficient ◽  
Multi Phase ◽  
Debris Flow Hazard

ABSTRACT Substantial advances have been achieved in various aspects of debris-flow hazard assessments over the past decade. These advances include sophisticated ways to date previous events, two- and three-dimensional runout models including multi-phase flows and debris entrainment options, and applications of extreme value statistics to assemble frequency–magnitude analyses. Pertinent questions have remained the same: How often, how big, how fast, how deep, how intense, and how far? Similarly, although 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 in debris-flow hazard persist between nations. 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. Differences exist in the management of debris-flow risks, from highly sophisticated and nation-wide applied protocols to retroaction in which catastrophic debris flows occur before they are considered for mitigation. Two factors conspire to challenge future generations of debris-flow researchers, practitioners, and decision makers: Population growth and climate change, which are increasingly manifested by augmenting hydroclimatic extremes. While researchers will undoubtedly finesse future remote sensing, dating, and runout techniques and models, practitioners will need to focus on translating those advances into practical cost-efficient tools and integrating those tools into long-term debris-flow risk management.

scholarly journals Combining TRIGRS and DEBRIS-2D Models for the Simulation of a Rainfall Infiltration Induced Shallow Landslide and Subsequent Debris Flow

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 890 ◽  
Author(s):  
Yu-Charn Hsu ◽  
Ko-Fei Liu
Keyword(s):  
Debris Flow ◽  
Depth Distribution ◽  
Shallow Landslide ◽  
Rainfall Infiltration ◽  
The Real ◽  
Hazard Zone ◽  
Before And After ◽  
Flow Motion ◽  
Debris Flow Hazard ◽  
Area And Volume

TRIGRS revealed the responses of the total pressure heads and factors of safety with a depth change under a rainfall infiltration occurring on the Daniao tribe’s hill. The depth distribution of the collapsed zone could be identified under the condition where the factors of safety Fs = 1, and the results could calculate the area and volume. Afterward, DEBRIS-2D used TRIGRS’s results to assess the hazard zone of the subsequent debris flow motion. In this study, the DTM variation analysis results from both of before and after the Daniao tribe’s landslide are used to validate TRIGRS’s simulation, the area and the volume of the collapse zone within 8% and 23% errors, respectively. The real disaster range was depicted from the aerial photo used to validate the hazard zone simulation of DEBRIS-2D within 25% errors. In spite of that, the hazard zone from the simulation still included the real disaster range. The combining method for a rainfall infiltration induced a shallow landslide and subsequent debris flow, which was well-matched on a real disaster range on the Daniao tribe’s hill. Therefore, we believe that the TRIGRS and DEBRIS-2D combining methods would provide a better solution for an assessment of a rainfall infiltration inducing shallow landslide and subsequent debris flow motion. TRIGRS could, therefore, provide the area and depth distribution of the collapsed zone, and DEBRIS-2D could use TRIGRS’s results for subsequent debris flow hazard assessment. Furthermore, these results would be of great help in the management of slope disaster prevention.

Multiple debris flow surges monitored directly by DFLP system at Kamikamihori Creek

2021 ◽  
Author(s):  
Takahiro Itoh ◽  
Takahiko Nagayama ◽  
Satoru Matsuda ◽  
Takahisa Mizuyama
Keyword(s):  
Debris Flow ◽  
Volcanic Activity ◽  
Debris Flows ◽  
Sediment Concentration ◽  
Relative Mass ◽  
Geophysical Research ◽  
Monitoring Method ◽  
Flow Measurements ◽  
Flow Monitoring ◽  
Sediment Particles

<p>The monitoring method for direct debris flow measurements using loadcells and so on, that were preliminary developed by WSL in Switzerland (McArdell et al., 2007), was firstly installed in Sakura-jima Island in Japan, where volcanic activity was severe, and many debris flows took place due to deposition of falling ash after eruptions. Debris Flow measurements with Loadcells and Pressure sensors (DFLP) system was installed referring to the method by WSL, and debris flow characteristics such as specific weight and volumetric sediment concentration have been obtained (e.g., Osaka et al., 2014).</p><p> In Japan, as well as in Sakura-jima island, attempts for debris flow monitoring were also carried out at KamiKamihori Creek since 1970s (e.g., Okuda et al., 1980), and there were a lot of debris flow events due to heavy rainfall. KamiKamihori Creek is at western side of Mt. Yake, where volcanic activity was severe at those time. The DFLP system was modified and installed there in November in 2014, because there were a lot of sediment deposition and debris flows took place though volcanic activity has been inactive. Present research could report the following results.  </p><p>(1) Multiple debris floe over five surges were monitored using DFLP system installed in 2014 during 15 minutes in debris flow events on August 29th, 2019. Rainfall intensity for 10 minutes was 12 mm and accumulated depth was 56 mm just before those events. Antecedent time before those events was 4.5 hours.</p><p>(2) The DFLP system measured multiple debris flow surges in events on August 29th, 2019, and sediment concentration was calculated temporary and continuously. Time-averaged sediment concentration and relative mass density are calculated as 0.470 and 1.73, respectively, under flow discharge obtained by images analysis of CCTV video camera. Equilibrium sediment concentration of coarse sediment particles is estimated 0.160 for bed slope of 0.141 (8 degrees) and calculated value using the DFLP system is over than the equilibrium value because of mud phase due to fine sediment particles.</p><p> </p><p>References</p><p>McArdell B.W., Bartelt P., Kowalski J. (2007). Field observations of basal forces and fluid pore pressure in a debris flow, Geophysical Research Letters, Vo. 34, L07406.</p><p>Okuda, S., Suwa, H., Okunishi, K., Yokoyama, K., and Nakano, M. (1980). Observation of the motion of debris flow and its geomorphological effects, Zeitschrift fur Geomorphology, Suppl.-Bd.35, pp. 142–163.</p><p>Osaka T., Utsunomiya R., Tagata S., Itoh T., Mizuyama T. (2014). Debris Flow Monitoring using Load Cells in Sakurajima Island, Proceedings of the Interpraevent 2014 in the Pacific Rim (edited by Fujita, M. et al.), Nov. 25-28, Nara, Japan, 2014, O-14.pdf in DVD.</p>

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.

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