Rainfall threshold calculation method for debris flow pre-warning in data-poor areas

2013 ◽  
Vol 24 (5) ◽  
pp. 854-862 ◽  
Author(s):  
Huali Pan ◽  
Jiangcheng Huang ◽  
Ren Wang ◽  
Guoqiang Ou
Keyword(s):  
Debris Flow ◽  
Calculation Method ◽  
Rainfall Threshold

Variability in rainfall threshold for debris flow after the Chi-Chi earthquake in central Taiwan, China

2009 ◽  
Vol 24 (2) ◽  
pp. 177-188 ◽  
Author(s):  
C.L. SHIEH ◽  
Y.S. CHEN ◽  
Y.J. TSAI ◽  
J.H. WU
Keyword(s):  
Debris Flow ◽  
Rainfall Threshold ◽  
Central Taiwan

scholarly journals Construction of 3D Rainfall Threshold Surface for Debris Flow Warning

2018 ◽  
Vol 10 (3) ◽  
pp. 249-253
Author(s):  
Chien-Yuan Chen ◽  
◽  
Ho-Wen Chen
Keyword(s):  
Debris Flow ◽  
Rainfall Threshold

scholarly journals Estimation of debris flow critical rainfall thresholds by a physically-based model

2012 ◽  
Vol 9 (11) ◽  
pp. 12797-12824 ◽  
Author(s):  
M. N. Papa ◽  
V. Medina ◽  
F. Ciervo ◽  
A. Bateman
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Rainfall Threshold ◽  
Richards Equation ◽  
Reduced Form ◽  
Physically Based Model ◽  
Rainfall Characteristics ◽  
South Italy ◽  
Infinite Slope Stability Model ◽  
Physically Based

Abstract. Real time assessment of debris flow hazard is fundamental for setting up warning systems that can mitigate its risk. A convenient method to assess the possible occurrence of a debris flow is the comparison of measured and forecasted rainfall with rainfall threshold curves (RTC). Empirical derivation of the RTC from the analysis of rainfall characteristics of past events is not possible when the database of observed debris flows is poor or when the environment changes with time. For landslides triggered debris flows, the above limitations may be overcome through the methodology here presented, based on the derivation of RTC from a physically based model. The critical RTC are derived from mathematical and numerical simulations based on the infinite-slope stability model in which land instability is governed by the increase in groundwater pressure due to rainfall. The effect of rainfall infiltration on landside occurrence is modelled trough a reduced form of the Richards equation. The simulations are performed in a virtual basin, representative of the studied basin, taking into account the uncertainties linked with the definition of the characteristics of the soil. A large number of calculations are performed combining different values of the rainfall characteristics (intensity and duration of event rainfall and intensity of antecedent rainfall). For each combination of rainfall characteristics, the percentage of the basin that is unstable is computed. The obtained database is opportunely elaborated to derive RTC curves. The methodology is implemented and tested on a small basin of the Amalfi Coast (South Italy).

The Calculating Method of Deposition Thickness of Viscous Debris Flow

2012 ◽  
Vol 524-527 ◽  
pp. 808-812
Author(s):  
Yong You ◽  
Xue Ping Lin ◽  
Jin Feng Liu
Keyword(s):  
Debris Flow ◽  
Calculation Method ◽  
Flow Cell ◽  
Force Analysis ◽  
Slope Gradient ◽  
Calculating Method ◽  
Maximum Value ◽  
Viscous Debris Flow ◽  
Deposition Thickness ◽  
Theoretical Mechanics

The deposition thickness is one of the most important parameters of debris flow. How to define the deposition shape along the viscous debris flow gully and how to calculate deposition thickness rationally were rarely studied in previous researches. This paper discussed the calculation method of deposition thickness of viscous debris flow based on theoretical deduction. Firstly, force analysis was carried out for a debris flow cell selected from the deposition. Then, the formula for calculating the deposition thickness of viscous debris flow was constructed based on deduction from the viewpoint of theoretical mechanics. At last, the deposition thickness under different slope gradients, yield stresses and densities was calculated based on the deduced formula. The results showed that the deposition thickness decreases with the increasing of the slope gradient and density, and increases with the increasing of the yield stress before the deposition thickness reaches to the maximum value.

scholarly journals Early warning of debris flow using optimized self-organizing feature mapping network

2020 ◽  
Vol 20 (7) ◽  
pp. 2455-2470
Author(s):  
Xuedong Wang ◽  
Cui Wang ◽  
Chaobiao Zhang
Keyword(s):  
Neural Network ◽  
Debris Flow ◽  
Early Warning ◽  
Rainfall Threshold ◽  
Liaoning Province ◽  
Feature Mapping ◽  
Threshold Method ◽  
Flow Area ◽  
Competitive Neural Network ◽  
Self Organizing

Abstract Early warning of debris flow is one of the core contents of disaster prevention and mitigation work for debris flow disasters. There are few early warning methods based on the combination of rainfall threshold and geological environment conditions. In this paper, we presented an early warning method for debris flow based on the infinite irrelevance method (IIM) and self-organizing feature mapping (SOFM), and applied it to Liaoning Province, China. The proposed model consisted of three stages. Firstly, eight geological environmental conditions and two rainfall-inducing conditions were selected by analyzing the factors affecting the development of debris flow in the study area, and the rainfall threshold for debris flow outbreak was 150 mm. Secondly, the correlation between various factors was analyzed by IIM, which prevented the blindness of parameter selection and improved the prediction accuracy of the model. Finally, SOFM was employed to predict the test data. Experimental results showed that the IIM-SOFM model had a strong early warning ability. When 25 samples of low-frequency debris flow area were selected, the accuracy rate of the IIM-SOFM model with optimized network structure parameters was 100%, which it was obviously superior to the rainfall threshold method, BP neural network and competitive neural network. Consequently, it is feasible to use the IIM-SOFM model for early warning of debris flow, outperforming traditional machine learning methods.

scholarly journals Quantitative Analysis of the Effects of an Earthquake on Rainfall Thresholds for Triggering Debris-Flow Events

2021 ◽  
Vol 9 ◽  
Author(s):  
Shuang Liu ◽  
Kaiheng Hu ◽  
Qun Zhang ◽  
Shaojie Zhang ◽  
Xudong Hu ◽  
...  
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Rainfall Intensity ◽  
Focal Depth ◽  
Rainfall Threshold ◽  
Effective Rainfall ◽  
Rainfall Thresholds ◽  
Jiuzhaigou Earthquake ◽  
The Wenchuan Earthquake ◽  
The Moment

The impacts of destructive earthquakes on rainfall thresholds for triggering the debris flows have not yet been well investigated, due to lacks of data. In this study, we have collected the debris-flow records from the Wenchuan, Lushan, and Jiuzhaigou earthquake-affected areas in Sichuan Province, China. By using a meteorological dataset with 3 h and 0.1° resolutions, the dimensionless effective rainfall and rainfall intensity-duration relationships were calculated as the possible thresholds for triggering the debris flows. The pre- and post-seismic thresholds were compared to evaluate the impacts of the various intensities of earthquakes. Our results indicate that the post-quake thresholds are much smaller than the pre-seismic ones. The dimensionless effective rainfall shows the impacts of the Wenchuan, Lushan, and Jiuzhaigou earthquakes to be ca. 26, 27, and 16%, respectively. The Wenchuan earthquake has the most significant effect on lowering the rainfall intensity-duration curve. Rainfall threshold changes related to the moment magnitude and focal depth are discussed as well. Generally, this work may lead to an improved post-quake debris-flow warning strategy especially in sparsely instrumented regions.

scholarly journals Mechanisms of Initiation, Runout, and Rainfall Thresholds of Extreme-Precipitation-Induced Debris Flows

2021 ◽  
Author(s):  
Srikrishnan Siva Subramanian ◽  
Ali. P. Yunus ◽  
Faheed Jasin ◽  
Minu Treesa Abraham ◽  
Neelima Sathyam ◽  
...  
Keyword(s):  
Debris Flow ◽  
Extreme Precipitation ◽  
Debris Flows ◽  
Maximum Velocity ◽  
Rainfall Threshold ◽  
Rainfall Thresholds ◽  
Long Runout ◽  
Loss Of Life ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract The frequency of unprecedented extreme precipitation events is increasing, and consequently, catastrophic debris flows occur in regions worldwide. Rapid velocity and long-runout distances of debris flow induce massive loss of life and damage to infrastructure. Despite extensive research, understanding the initiation mechanisms and defining early warning thresholds for extreme-precipitation-induced debris flows remain a challenge. Due to the nonavailability of extreme events in the past, statistical models cannot determine thresholds from historical datasets. Here, we develop a numerical model to analyze the initiation and runout of extreme-precipitation-induced runoff-generated debris flows and derive the Intensity-Duration (ID) rainfall threshold. We choose the catastrophic debris flow on 6 August 2020 in Pettimudi, Kerala, India, for our analysis. Our model satisfactorily predicts the accumulation thickness (7 m to 8 m) and occurrence time of debris flow compared to the benchmark. Results reveal that the debris flow was rapid, traveling with a maximum velocity of 9 m/s for more than 9 minutes. The ID rainfall threshold defined for the event suggests earlier thresholds are not valid for debris flow triggered by extreme precipitation. The methodology we develop in this study is helpful to derive ID rainfall thresholds for debris flows without historical data.

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