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.

Rainfall thresholds of the debris flows based on various rainfall intensity types in Beijing

2021 ◽  
Author(s):  
Haizhi Wang ◽  
Qingli Zeng ◽  
Bing Xu ◽  
Luqing Zhang
Keyword(s):  
Debris Flows ◽  
Rainfall Intensity ◽  
High Water ◽  
Rainfall Threshold ◽  
Limited Information ◽  
Rainfall Thresholds ◽  
Occurrence Time ◽  
Water Flows ◽  
Average Rainfall ◽  
Concert Works

Abstract Empirical rainfall thresholds derived from various types of rainfall intensities have widely used in characterizing rainfall conditions that cause debris flows and landslides. However, few works have studied the differences among these various thresholds, due to limited information on the instantaneous intensity triggering debris flows. The detail records of the storms on 21 July, 2012, 20 July, 2016, and 16 July, 2018, together with the occurrence time of debris flows, provide an opportunity to evaluate the thresholds based on various rainfall intensities. Based these data, a new rainfall threshold of debris flows is derived from the instantaneous rainfall intensity in Beijing. At the same time, the thresholds based on average rainfall intensities as used in most previous studies, including the average over the periods from the beginnings of rainfall to the occurrences of the debris flows and over the whole period of the rainstorms, are reconstructed. The result shows that the instantaneous rainfall threshold has a higher ability in separating the rainstorms inducing from those without reducing debris flows than those derived from average intensities, indicating a high accurate of the instantaneous threshold. Our data also indicate that the debris flows in Beijing should be triggered by the concert works of rainfall intensity and cumulative precipitation. Only when enough water to infiltrate, saturate, mobilize the debris sediments, and sufficient high water flows and surges caused by intensive storms to incorporate and retain the mobilized sediments, are satisfied simultaneously do the debris flows occur.

scholarly journals Rainfall threshold calculation for debris flow early warning in areas with scarcity of data

2018 ◽  
Vol 18 (5) ◽  
pp. 1395-1409 ◽  
Author(s):  
Hua-Li Pan ◽  
Yuan-Jun Jiang ◽  
Jun Wang ◽  
Guo-Qiang Ou
Keyword(s):  
Debris Flow ◽  
Wenchuan Earthquake ◽  
Early Warning ◽  
Debris Flows ◽  
Early Warning Systems ◽  
Rainfall Threshold ◽  
Warning Systems ◽  
Mountainous Areas ◽  
Rainfall Thresholds ◽  
Initiation Mechanism

Abstract. Debris flows are natural disasters that frequently occur in mountainous areas, usually accompanied by serious loss of lives and properties. One of the most commonly used approaches to mitigate the risk associated with debris flows is the implementation of early warning systems based on well-calibrated rainfall thresholds. However, many mountainous areas have little data regarding rainfall and hazards, especially in debris-flow-forming regions. Therefore, the traditional statistical analysis method that determines the empirical relationship between rainstorms and debris flow events cannot be effectively used to calculate reliable rainfall thresholds in these areas. After the severe Wenchuan earthquake, there were plenty of deposits deposited in the gullies, which resulted in several debris flow events. The triggering rainfall threshold has decreased obviously. To get a reliable and accurate rainfall threshold and improve the accuracy of debris flow early warning, this paper developed a quantitative method, which is suitable for debris flow triggering mechanisms in meizoseismal areas, to identify rainfall threshold for debris flow early warning in areas with a scarcity of data based on the initiation mechanism of hydraulic-driven debris flow. First, we studied the characteristics of the study area, including meteorology, hydrology, topography and physical characteristics of the loose solid materials. Then, the rainfall threshold was calculated by the initiation mechanism of the hydraulic debris flow. The comparison with other models and with alternate configurations demonstrates that the proposed rainfall threshold curve is a function of the antecedent precipitation index (API) and 1 h rainfall. To test the proposed method, we selected the Guojuanyan gully, a typical debris flow valley that during the 2008–2013 period experienced several debris flow events, located in the meizoseismal areas of the Wenchuan earthquake, as a case study. The comparison with other threshold models and configurations shows that the selected approach is the most promising starting point for further studies on debris flow early warning systems in areas with a scarcity of data.

scholarly journals Assessment of Rainfall Thresholds for Rain-Induced Landslide Activity in North Sikkim Road Corridor in Sikkim Himalaya, India

2019 ◽  
pp. 1-14 ◽  
Author(s):  
Bappaditya Koley ◽  
Anindita Nath ◽  
Subhajit Saraswati ◽  
Kaushik Bandyopadhyay ◽  
Bidhan Chandra Ray
Keyword(s):  
Rainfall Intensity ◽  
Lower Boundary ◽  
Daily Rainfall ◽  
Rainfall Threshold ◽  
Rainfall Data ◽  
Antecedent Rainfall ◽  
Rainfall Thresholds ◽  
Sikkim Himalaya ◽  
North East ◽  
The North

Land sliding is a perennial problem in the Eastern Himalayas. Out of 0.42 million km2 of Indian landmass prone to landslide, 42% fall in the North East Himalaya, specially Darjeeling and Sikkim Himalaya. Most of these landslides are triggered by excessive monsoon rainfall between June and October in almost every year. Various attempts in the global scenario have been made to establish rainfall thresholds in terms of intensity – duration of antecedent rainfall models on global, regional and local scale for triggering of the landslide. This paper describes local aspect of rainfall threshold for landslides based on daily rainfall data in and around north Sikkim road corridor region. Among 210 Landslides occurring from 2010 to 2016 were studied to analyze rainfall thresholds. Out of the 210 landslides, however, only 155 Landslides associated with rainfall data which were analyzed to yield a threshold relationship between rainfall intensity-duration and landslide initiation. The threshold relationship determined fits to lower boundary of the Landslide triggering rainfall events is I = 4.045 D - 0.25 (I=rainfall intensity (mm/h) and D=duration in (h)), revealed that for rainfall event of short time (24 h) duration with a rainfall intensity of 1.82 mm/h, the risk of landslides on this road corridor of the terrain is expected to be high. It is also observed that an intensity of 58 mm and 139 mm for 10-day and 20-day antecedent rainfall are required for the initiation of landslides in the study area. This threshold would help in improvement on traffic guidance and provide safety to the travelling tourists in this road corridor during the monsoon.

How to account for misclassification costs in shallow-landslide rainfall thresholds?

2021 ◽  
Author(s):  
Paolo Frattini ◽  
Gianluca Sala ◽  
Camilla Lanfranconi ◽  
Giulia Rusconi ◽  
Giovanni Crosta
Keyword(s):  
False Alarm ◽  
Rainfall Intensity ◽  
Rainfall Threshold ◽  
Shallow Landslides ◽  
False Alarms ◽  
Rainfall Thresholds ◽  
Rainfall Events ◽  
Misclassification Costs ◽  
Triggering Events ◽  
The Cost

<p>Rainfall is one of the most significant triggering factors for shallow landslides. The early warning for such phenomena requires the definition of a threshold based on a critical rainfall condition that may lead to diffuse landsliding. The developing of these thresholds is frequently done through empirical or statistical approaches that aim at identifying thresholds between rainfall events that triggered or non-triggered landslides. Such approaches present several problems related to the identification of the exact amount of rainfall that triggered landslides, the local geo-environmental conditions at the landslide site, and the minimum rainfall amount used to define the non-triggering events. Furthermore, these thresholds lead to misclassifications (false negative or false positive) that always induce costs for the society. The aim of this research is to address these limitations, accounting for classification costs in order to select the optimal thresholds for landslide risk management.</p><p>Starting from a database of shallow landslides occurred during five regional-scale rainfall events in the Italian Central Alps, we extracted the triggering rainfall intensities by adjusting rain gouge data with weather radar data. This adjustment significantly improved the information regarding the rainfall intensity at the landslide site and, although an uncertainty related to the exact timing of occurrence has still remained. Therefore, we identified the rainfall thresholds through the Receiver Operating Characteristic (ROC) approach, by identifying the optimal rainfall intensity that separates triggering and non-triggering events. To evaluate the effect related to the application of different minimum rainfall for non-triggering events, we have adopted three different values obtaining similar results, thus demonstrating that the ROC approach is not sensitive to the choice of the minimum rainfall threshold. In order to include the effect of misclassification costs we have developed cost-sensitive rainfall threshold curves by using cost-curve approach (Drummond and Holte 2000). As far as we know, this is the first attempt to build a cost-sensitive rainfall threshold for landslides that allows to explicitly account for misclassification costs. For the development of the cost-sensitive threshold curve, we had to define a reference cost scenario in which we have quantified several cost items for both missed alarms and false alarms. By using this scenario, the cost-sensitive rainfall threshold results to be lower than the ROC threshold to minimize the missed alarms, the costs of which are seven times greater than the false alarm costs. Since the misclassification costs could vary according to different socio-economic contexts and emergency organization, we developed different extreme scenarios to evaluate the sensitivity of misclassification costs on the rainfall thresholds. In the scenario with maximum false-alarm cost and minimum missed-alarm cost, the rainfall threshold increases in order to minimize the false alarms. Conversely, the rainfall thresholds decreases in the scenario with minimum false-alarm cost and maximum missed-alarm costs. We found that the range of variation between the curves of these extreme scenarios is as much as half an order of magnitude.</p>

Uncertainty in debris flow rainfall thresholds

2021 ◽  
Author(s):  
Matteo Berti ◽  
Alessandro Simoni
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Measurement Errors ◽  
Critical Conditions ◽  
Model Parameters ◽  
Average Intensity ◽  
Rainfall Thresholds ◽  
Sources Of Uncertainty ◽  
Time Space ◽  
Physically Based

<p>Rainfall is the most significant factor for debris flows triggering. Water is needed to saturate the soil, initiate the sediment motion (regardless of the mobilization mechanism) and transform the solid debris into a fluid mass that can move rapidly downslope. This water is commonly provided by rainfall or rainfall and snowmelt. Consequently, most warning systems rely on the use of rainfall thresholds to predict debris flow occurrence. Debris flows thresholds are usually empirically-derived from the rainfall records that caused past debris flows in a certain area, using a combination of selected precipitation measurements (such as event rainfall P, duration D, or average intensity I) that describe critical rainfall conditions. Recent years have also seen a growing interest in the use of coupled hydrological and slope stability models to derive physically-based thresholds for shallow landslide initiation.</p><p>In both cases, rainfall thresholds are affected by significant uncertainty. Sources of uncertainty include: measurement errors; spatial variability of the rainfall field; incomplete or uncertain debris flow inventory; subjective definition of the “rainfall event”; use of subjective criteria to define the critical conditions; uncertainty in model parameters (for physically-based approaches). Rainfall measurement is widely recognized as a main source of uncertainty due to the extreme time-space variability that characterize intense rainfall events in mountain areas. However, significant errors can also arise by inaccurate information reported in landslide inventories on the timing of debris flows, or by the criterion used to define triggering intensities.</p><p>This study analyzes the common sources of uncertainty associated to rainfall thresholds for debris flow occurrence and discusses different methods to quantify them. First, we give an overview of the various approaches used in the literature to measure the uncertainty caused by random errors or procedural defects. These approaches are then applied to debris flows using real data collected in the Dolomites (Northen Alps, Itay), in order to estimate the variabilty of each single factor (precipitation, triggering timing, triggering intensity..). Individual uncertainties are then combined to obtain the overall uncertain of the rainfall threshold, which can be calculated using the classical method of “summation in quadrature” or a more effective approach based on Monte Carlo simulations. The uncertainty budget allows to identify the biggest contributors to the final variability and it is also useful to understand if this variability can be reduced to make our thresholds more precise.</p><p> </p>

scholarly journals Analysis of River Blocking Induced by a Debris Flow

Geofluids ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Lijuan Wang ◽  
Ming Chang ◽  
Xiangyang Dou ◽  
Guochao Ma ◽  
Chenyuan Yang
Keyword(s):  
Debris Flow ◽  
Return Period ◽  
Debris Flows ◽  
Small Volume ◽  
Disaster Prevention ◽  
Intense Rainfall ◽  
Residential Areas ◽  
The Wenchuan Earthquake ◽  
Movement Characteristics ◽  
Blocking Event

Both the Wenchuan earthquake on May 12, 2008, and the Lushan earthquake on April 12, 2013, produced many coseismic landslides along the Nanya River in Shimian City. Subsequent debris flows that initiated from these landslides and are triggered by intense rainfall become the secondary hazard in the years after the earthquake; in particular, some debris flows led to a serious river blocking event. For example, the Guangyuanbao debris flow which occurred on July 04, 2013, partly blocked the Nanya River, presenting a major threat to the national highway and residential areas. To analyze the pattern of landslide damming, we analyzed numerical simulations of the movement characteristics of the Guangyuanbao debris flow using rainfall intensities with varying recurrence periods of 5, 20, and 50 years. The accuracy of the spreading of the numerical simulation is about 90%. The simulation indicated a small volume of sediment entering the river for a rainfall under 5-year return period. A debris flow induced by rainfall under 20-year return period partly blocked the river, while rainfall under 50-year return period has potential to block the river completely. This proposed analysis of river blocking induced by a debris flow could be used for disaster prevention in earthquake-stricken area.

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 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).

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