A physics-based model to derive rainfall intensity-duration threshold for debris flow

Geomorphology ◽  
2020 ◽  
Vol 351 ◽  
pp. 106930 ◽  
Author(s):  
S.J. Zhang ◽  
C.X. Xu ◽  
F.Q. Wei ◽  
K.H. Hu ◽  
H. Xu ◽  
...  
Keyword(s):  
Debris Flow ◽  
Rainfall Intensity ◽  
Duration Threshold

Simulating debris flows triggered by rainfall in Shiyang gully, China

2020 ◽  
Author(s):  
Jiaoyang Li
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Rainfall Intensity ◽  
Intensity Increase ◽  
Short Term ◽  
Rain Area ◽  
Cumulative Rainfall ◽  
Event Flow ◽  
Warning Time ◽  
Main Factor

<p>A debris flow occurred in Shiyang gully, located between Hebei Province and Beijing, on 8 June 2017, resulting in 6 people dead or injured. Short-term heavy rainfall is the main factor that triggered this event, however, the meteorological agency didn’t forecast this event very well. In this study, numerical simulation using FLO-2D was performed to reproduce the debris flow event (flow depths, flow velocities, and sediment depositions)occurred in 2017. The results of the field survey showed that the influential range of debris flow is consistent with the simulation results. Simulated depth accuracy is greater than 70%. Then, we used FLO-2D is calibrated to simulate debris flows disasters under different rainfall scenarios. The results showed that, the Beijing needs to be warned when the accumulated precipitation is 40mm at the rainfall intensity of 1mm/min. As cumulative rainfall and rainfall intensity increase, the risk of Shiyang gully is increasing.  This study used FLO-2D simulated process of debris flows triggered by rainfall. The results showed the early warning time and influential range for different intensity ,accumulated precipitation, and rain area, which is beneficial to the debris flow management in the western mountainous areas of Beijing.</p>

scholarly journals Uji Laboratorium Pengaruh Kemiringan Lereng Terhadap Kejadian Longsoran Aliran Debris Pasir Merapi

2020 ◽  
Vol 16 (1) ◽  
pp. 23-34
Author(s):  
Bayu Seto Waseso Utomo ◽  
Jati Iswardoyo ◽  
Ruzardi Ruzardi
Keyword(s):  
Debris Flow ◽  
Laboratory Test ◽  
Early Warning ◽  
Debris Flows ◽  
Rainfall Intensity ◽  
Laboratory Scale ◽  
Artificial Rainfall ◽  
Rain Simulator

The debris flow that happen on the of Mount Merapi is really hard to be seen, therefore, it is necessary to conduct laboratory-scale simulations to know when debris flows will happen as regard to rainfall intensity and the slope of Mount of Merapi. This research examines the correlation between the slope and the potential for debris flow at 25 mm/h rainfall intensity. This will be a reference for early warning of landslides on Mount of Merapi. This research uses a tool such as flume that sized 3 x 5 x 0,15 m as a model of slope of Mount of Merapi, and artificial rainfall apparatus as the rain simulator. The simulation is conducted using five years rainfall intensity of 25 mm/h in combination of slope i.e. 15, 20, 25, 30 and 35 degrees whereas the material used to represent the sediment is in form of sand taken from Gendol River upstream with 4,75 mm passing mesh sieves. The result of this simulation is the steeper the slope is, the faster the duration for the rain to cause debris flow. This research can be continued with change variation of rainfall intensity to understand the debris flows behavior. Keywords: Debris flow, Mount of Merapi, laboratory test, rainfall intensity, flume model

scholarly journals Evaluating methods for debris-flow prediction based on rainfall in an Alpine catchment

2021 ◽  
Vol 21 (9) ◽  
pp. 2773-2789
Author(s):  
Jacob Hirschberg ◽  
Alexandre Badoux ◽  
Brian W. McArdell ◽  
Elena Leonarduzzi ◽  
Peter Molnar
Keyword(s):  
Random Forest ◽  
Debris Flow ◽  
Debris Flows ◽  
Rainfall Intensity ◽  
Multiple Scales ◽  
Learning Algorithm ◽  
Predictive Performance ◽  
Early Warning Systems ◽  
Antecedent Rainfall ◽  
Data Set

Abstract. The prediction of debris flows is relevant because this type of natural hazard can pose a threat to humans and infrastructure. Debris-flow (and landslide) early warning systems often rely on rainfall intensity–duration (ID) thresholds. Multiple competing methods exist for the determination of such ID thresholds but have not been objectively and thoroughly compared at multiple scales, and a validation and uncertainty assessment is often missing in their formulation. As a consequence, updating, interpreting, generalizing and comparing rainfall thresholds is challenging. Using a 17-year record of rainfall and 67 debris flows in a Swiss Alpine catchment (Illgraben), we determined ID thresholds and associated uncertainties as a function of record duration. Furthermore, we compared two methods for rainfall definition based on linear regression and/or true-skill-statistic maximization. The main difference between these approaches and the well-known frequentist method is that non-triggering rainfall events were also considered for obtaining ID-threshold parameters. Depending on the method applied, the ID-threshold parameters and their uncertainties differed significantly. We found that 25 debris flows are sufficient to constrain uncertainties in ID-threshold parameters to ±30 % for our study site. We further demonstrated the change in predictive performance of the two methods if a regional landslide data set with a regional rainfall product was used instead of a local one with local rainfall measurements. Hence, an important finding is that the ideal method for ID-threshold determination depends on the available landslide and rainfall data sets. Furthermore, for the local data set we tested if the ID-threshold performance can be increased by considering other rainfall properties (e.g. antecedent rainfall, maximum intensity) in a multivariate statistical learning algorithm based on decision trees (random forest). The highest predictive power was reached when the peak 30 min rainfall intensity was added to the ID variables, while no improvement was achieved by considering antecedent rainfall for debris-flow predictions in Illgraben. Although the increase in predictive performance with the random forest model over the classical ID threshold was small, such a framework could be valuable for future studies if more predictors are available from measured or modelled data.

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.

Consideration of the Validity of Debris-flow Bulking Factors

2017 ◽  
Vol 23 (4) ◽  
pp. 291-298
Author(s):  
Holly Brunkal ◽  
Paul Santi
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Rainfall Intensity ◽  
Peak Discharge ◽  
Data Set ◽  
Burned Areas ◽  
The Given ◽  
Basin Area ◽  
Bulking Factor ◽  
Significant Underestimation

Abstract Compilation of a database of debris-flow peak discharges (Q) allowed for a comparison with the expected basin discharge, as computed using the rational equation, Q=CIA. The observed values of Q for debris flows in unburned and burned areas were divided by the computed Q values of runoff using the rational method. This ratio is the bulking factor for that debris-flow event. Unburned and burned basins constitute two distinct populations; analysis shows that the bulking factors for burned areas are consistently higher than those for unburned basins. Previously published bulking factors for unburned areas fit the data set in about 50 percent of the observed cases in our compiled data set. Bulking factors for burned areas that were found in the published literature were well below the observed increases in peak discharge in over 50 percent of the cases investigated. If used for design purposes, these bulking factors would result in a significant underestimation of the peak discharge from a burned basin for the given rainfall intensity. Peak discharge bulking rates were found to be inversely related to basin area.

Debris-flow hazards in the Blue Ridge of central Virginia

2000 ◽  
Vol 6 (1) ◽  
pp. 3-23 ◽  
Author(s):  
G. F. Wieczorek ◽  
B. A. Morgan ◽  
R. H. Campbell
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Rainfall Intensity ◽  
Granitic Rocks ◽  
Blue Ridge ◽  
Eastern United States ◽  
Storm Events ◽  
Gis Technology ◽  
Madison County ◽  
Physical Examinations

Abstract The June 27, 1995, storm in Madison County, Virginia produced debris flows and floods that devastated a small (130 km 2 ) area of the Blue Ridge in the eastern United States. Although similar debris-flow inducing storm events may return only approximately once every two thousand years to the same given locale, these events affecting a similar small-sized area occur about every three years somewhere in the central and southern Appalachian Mountains. From physical examinations and mapping of debris-flow sources, paths, and deposits in Madison County, we develop methods for identifying areas subject to debris flows using Geographic Information Systems (GIS) technology. We examined the rainfall intensity and duration characteristics of the June 27, 1995, and other storms, in the Blue Ridge of central Virginia, and have defined a minimum threshold necessary to trigger debris flows in granitic rocks. In comparison with thresholds elsewhere, longer and more intense rainfall is necessary to trigger debris flows in the Blue Ridge.

scholarly journals Characteristics of landslides in unwelded pyroclastic flow deposits, southern Kyushu, Japan

2015 ◽  
Vol 3 (10) ◽  
pp. 6351-6378 ◽  
Author(s):  
M. Yamao ◽  
R. C. Sidle ◽  
T. Gomi ◽  
F. Imaizumi
Keyword(s):  
Pyroclastic Flow ◽  
Slope Failure ◽  
Rainfall Intensity ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Antecedent Rainfall ◽  
Rainfall Characteristics ◽  
Antecedent Conditions ◽  
Duration Threshold ◽  
Different Types

Abstract. We investigated 184 landslides that occurred in unwelded pyroclastic flow deposits (Shirasu) on southern Kyushu Island, Japan, that included detailed data on the rainfall characteristics and the timing of slope failure. Localized rainfall intensity, antecedent rainfall, and topography affected the hydrologic processes that triggered landslides. Antecedent rainfall (adjusted for evapotranspiration losses) for large (> 200 mm) storms that triggered landslides was much lower than for smaller (≤ 200 mm) storms. Mean storm intensity and antecedent 7 day rainfall (API7) thresholds of > 5 mm h-1 and ≤ 30 mm (or API30 ≤ 60 mm), respectively, were useful to identify landslides triggered by rapid pore water pressure response, especially for shorter (< 20 h) duration events. During smaller storms with lower intensity, landslides are likely affected by a combined increase in soil weight and loss of suction when API30 ≥ 150 mm; simulations indicated that these weight and suction changes due to rainfall accumulation decreased factor of safety in steep Shirasu slopes, but did not necessarily trigger the landslides. All but two of the 21 landslides that plotted below a general rainfall intensity-duration threshold for landslide initiation had API30 values > 235 mm, indicating that they were highly influenced by the combined effects of the accumulated weight of rainfall and loss of suction. Our findings show that both event rainfall characteristics and antecedent conditions affect the hydrogeomorphic processes that trigger different types of landslides in Shirasu. This knowledge and the thresholds we have identified are useful for predicting the occurrence of different types of landslides in Shirasu deposits and improving sediment disaster prevention practices, including real-time warning systems.

scholarly journals A Rainfall Intensity-Duration Threshold for Mass Movement in Badulla, Sri Lanka

2017 ◽  
Vol 05 (12) ◽  
pp. 135-152 ◽  
Author(s):  
E. N. C. Perera ◽  
D. T. Jayawardana ◽  
Pathmakumara Jayasinghe
Keyword(s):  
Sri Lanka ◽  
Rainfall Intensity ◽  
Mass Movement ◽  
Duration Threshold

scholarly journals EVALUATION ON THE IMPLEMENTATION OF EARLY WARNING SYSTEM FOR LAHAR IN MERAPI AREA (CASE STUDY AT BOYONG RIVER)

2015 ◽  
Vol 1 (3) ◽  
pp. 77
Author(s):  
Ali Cahyadi Achmad
Keyword(s):  
Debris Flow ◽  
Qualitative Analysis ◽  
Volcanic Activity ◽  
Early Warning ◽  
Early Warning System ◽  
Rainfall Intensity ◽  
Warning System ◽  
Actual Condition ◽  
Telemetry System ◽  
Debris Flood

One of disasters caused by volcanic activity of Mount Merapi is secondary disaster. The disaster usually occurs after eruption and this volcanic activity produces volcanic and pyroclastic material deposit around the top of the mountain as a result of previous eruption. This material might collapse downward in the form of debris flow as it is affected by natural event such as high intensity rainfall. Therefore, a research is needed to analyze whether existing forecasting and early warning system are capable to provide information for the people living in hazardous area before the debris flood occur. This research was carried out using field survey, observation and interview method. Data analysis used qualitative descriptive method by making description of actual condition of the researched location general condition and qualitative analysis of telemetry system installed on Mount Merapi. The qualitative analysis of telemetry system covers network, hardware, software, power supply, security system, operation and maintenance, also human resources. Research analysis used primary and secondary data. Research results revealed that mean rainfall intensity above of 60 mm/hour might trigger debris flood. Early warning should be given at the rainfall intensity level of 50-55 mm/hour, and debris flood time travel from the upstream to the observed location in Pulowatu Village is 45 minute. Based on the analysis of the present forecasting and early warning system, it is known that some of the equipment is not well functioned, so that debris flow cannot be predicted and detected. This is caused by the lack of human resource quality of the officers in operating and maintaining the equipment. Concerning that matter, it is necessary to conduct some improvement to achieve better forecasting and early warning system in order to give information regarding occurrence of debris flow.

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