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).

scholarly journals Derivation of critical rainfall thresholds for shallow landslides as a tool for debris flow early warning systems

2013 ◽  
Vol 17 (10) ◽  
pp. 4095-4107 ◽  
Author(s):  
M. N. Papa ◽  
V. Medina ◽  
F. Ciervo ◽  
A. Bateman
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Early Warning Systems ◽  
Shallow Landslides ◽  
Slope Instability ◽  
Richards Equation ◽  
Warning Systems ◽  
Rainfall Characteristics ◽  
Infinite Slope Stability Model ◽  
Critical Rainfall

Abstract. Real-time assessment of debris-flow hazard is fundamental for developing warning systems that can mitigate risk. A convenient method to assess the possible occurrence of a debris flow is to compare measured and forecasted rainfalls to critical rainfall threshold (CRT) curves. Empirical derivation of the CRT from the analysis of past events' rainfall characteristics is not possible when the database of observed debris flows is poor or when the environment changes with time. For debris flows and mud flows triggered by shallow landslides or debris avalanches, the above limitations may be overcome through the methodology presented. In this work the CRT curves are derived from mathematical and numerical simulations, based on the infinite-slope stability model in which slope instability is governed by the increase in groundwater pressure due to rainfall. The effect of rainfall infiltration on landside occurrence is modelled through a reduced form of the Richards equation. The range of rainfall durations for which the method can be correctly employed is investigated and an equation is derived for the lower limit of the range. A large number of calculations are performed combining different values of 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 CRT curves. The methodology is implemented and tested in a small basin of the Amalfi Coast (South Italy). The comparison among the obtained CRT curves and the observed rainfall amounts, in a playback period, gives a good agreement. Simulations are performed with different degree of detail in the soil parameters characterization. The comparison shows that the lack of knowledge about the spatial variability of the parameters may greatly affect the results. This problem is partially mitigated by the use of a Monte Carlo approach.

scholarly journals Predicting the Initiation Area of a Debris Flow Using Geomorphological Characteristics and a Physically-Based Model

2021 ◽  
Vol 21 (2) ◽  
pp. 137-147
Author(s):  
Chang-Ho Song ◽  
Ji-Sung Lee ◽  
Yun-Tae Kim
Keyword(s):  
Debris Flow ◽  
Debris Flows ◽  
Physically Based Model ◽  
Index Analysis ◽  
Geotechnical Characteristics ◽  
Deposition Area ◽  
Significant Damage ◽  
Physically Based ◽  
Error Index ◽  
Success Index

A debris flow is a phenomenon in which sediment matter and water become mixed and flow down to a deposition area, thereby causing significant damage to people and property. In Korea, majority of the past debris flows initiated in the form of shallow landslides during rainfall. To address the hazards associated with debris flows, it is necessary to establish a method for predicting the location of the debris flow initiation. In this study, we propose a method for predicting the source of a debris flow by incorporating geomorphological characteristics and designing a physically-based model. The geomorphological characteristics associated with the initiation area of the debris flow were determined by analyzing previous literature. The physically-based model was developed by incorporating landslide inventory data, rainfall data, and geotechnical characteristics, and the map of safety factor less than 1.2 was thereby established. Furthermore, the region prone to the occurrence of debris flows was identified by the superposition of each unstable pixel obtained from the geomorphological characteristics and the physically-based model. The proposed method was validated through quantitative index analysis. The obtained results indicate that compared to other methods, the proposed method has a high success index and a low error index for predicting the source of a debris flow.

scholarly journals A new approach to mapping landslide hazards: a probabilistic integration of empirical and physically based models in the North Cascades of Washington, USA

2019 ◽  
Vol 19 (11) ◽  
pp. 2477-2495
Author(s):  
Ronda Strauch ◽  
Erkan Istanbulluoglu ◽  
Jon Riedel
Keyword(s):  
Statistical Approach ◽  
Joint Probability ◽  
North Cascades ◽  
Physically Based Model ◽  
New Approach ◽  
The North ◽  
Debris Avalanches ◽  
Landslide Hazards ◽  
Infinite Slope Stability Model ◽  
Physically Based

Abstract. We developed a new approach for mapping landslide hazards by combining probabilities of landslide impacts derived from a data-driven statistical approach and a physically based model of shallow landsliding. Our statistical approach integrates the influence of seven site attributes (SAs) on observed landslides using a frequency ratio (FR) method. Influential attributes and resulting susceptibility maps depend on the observations of landslides considered: all types of landslides, debris avalanches only, or source areas of debris avalanches. These observational datasets reflect the detection of different landslide processes or components, which relate to different landslide-inducing factors. For each landslide dataset, a stability index (SI) is calculated as a multiplicative result of the frequency ratios for all attributes and is mapped across our study domain in the North Cascades National Park Complex (NOCA), Washington, USA. A continuous function is developed to relate local SI values to landslide probability based on a ratio of landslide and non-landslide grid cells. The empirical model probability derived from the debris avalanche source area dataset is combined probabilistically with a previously developed physically based probabilistic model. A two-dimensional binning method employs empirical and physically based probabilities as indices and calculates a joint probability of landsliding at the intersections of probability bins. A ratio of the joint probability and the physically based model bin probability is used as a weight to adjust the original physically based probability at each grid cell given empirical evidence. The resulting integrated probability of landslide initiation hazard includes mechanisms not captured by the infinite-slope stability model alone. Improvements in distinguishing potentially unstable areas with the proposed integrated model are statistically quantified. We provide multiple landslide hazard maps that land managers can use for planning and decision-making, as well as for educating the public about hazards from landslides in this remote high-relief terrain.

Research on Motion Characteristics and Formation Mechanism of Debris Flow

2014 ◽  
Vol 711 ◽  
pp. 388-391
Author(s):  
Ji Wei Xu ◽  
Ming Dong Zhang ◽  
Mao Sheng Zhang
Keyword(s):  
Debris Flow ◽  
Formation Mechanism ◽  
Debris Flows ◽  
Catchment Area ◽  
Large Scale ◽  
Large Range ◽  
Extreme Rainfall ◽  
Small Catchment ◽  
Rainfall Characteristics ◽  
Motion Characteristics

On July 9 2013, debris flows occurred around Longchi town with large scale and wide harm, which was a great threat to people's life and property as well as reconstruction work. Debris flow ditch in the surrounding town was studied. This paper focused on loose materials, topography and rainfall characteristics, and explored the formation mechanism of debris flow in Longchi town. The result shows that: a small catchment area in valleys also have the risk of large range of accumulation of debris flow, the debris flow is caused by a lot of loose materials in mountains after earthquake and extreme rainfall. Research results contribute to a better understanding of trigger condition of debris flow after earthquake.

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>

Time Since Burning and Rainfall Characteristics Impact Post-Fire Debris-Flow Initiation and Magnitude

2021 ◽  
Vol 27 (1) ◽  
pp. 43-56
Author(s):  
Luke A. McGuire ◽  
Francis K. Rengers ◽  
Nina Oakley ◽  
Jason W. Kean ◽  
Dennis M. Staley ◽  
...  
Keyword(s):  
Numerical Modeling ◽  
Debris Flow ◽  
Debris Flows ◽  
Numerical Models ◽  
Ground Cover ◽  
Temporal Changes ◽  
Infiltration Capacity ◽  
Rainfall Characteristics ◽  
San Gabriel Mountains ◽  
Fire Debris

ABSTRACT The extreme heat from wildfire alters soil properties and incinerates vegetation, leading to changes in infiltration capacity, ground cover, soil erodibility, and rainfall interception. These changes promote elevated rates of runoff and sediment transport that increase the likelihood of runoff-generated debris flows. Debris flows are most common in the year immediately following wildfire, but temporal changes in the likelihood and magnitude of debris flows following wildfire are not well constrained. In this study, we combine measurements of soil-hydraulic properties with vegetation survey data and numerical modeling to understand how debris-flow threats are likely to change in steep, burned watersheds during the first 3 years of recovery. We focus on documenting recovery following the 2016 Fish Fire in the San Gabriel Mountains, California, and demonstrate how a numerical model can be used to predict temporal changes in debris-flow properties and initiation thresholds. Numerical modeling suggests that the 15-minute intensity-duration (ID) threshold for debris flows in post-fire year 1 can vary from 15 to 30 mm/hr, depending on how rainfall is temporally distributed within a storm. Simulations further demonstrate that expected debris-flow volumes would be reduced by more than a factor of three following 1 year of recovery and that the 15-minute rainfall ID threshold would increase from 15 to 30 mm/hr to greater than 60 mm/hr by post-fire year 3. These results provide constraints on debris-flow thresholds within the San Gabriel Mountains and highlight the importance of considering local rainfall characteristics when using numerical models to assess debris-flow and flood potential.

scholarly journals A simple and feasible process for using multi-stage high-precision DTMs, field surveys and rainfall data to study debris flow occurrence factors of Shenmu area, Taiwan

2012 ◽  
Vol 12 (11) ◽  
pp. 3407-3419 ◽  
Author(s):  
W.-C. Lo ◽  
B.-S. Lin ◽  
H.-C. Ho ◽  
J. Keck ◽  
H.-Y. Yin ◽  
...  
Keyword(s):  
Debris Flow ◽  
High Precision ◽  
Debris Flows ◽  
Airborne Lidar ◽  
Rainfall Characteristics ◽  
Field Surveys ◽  
Sensing Technology ◽  
Multi Stage ◽  
Catchment Areas ◽  
Typhoon Herb

Abstract. The occurrence of typhoon Herb in 1996 caused massive landslides in the Shenmu area of Taiwan. Many people died and stream and river beds were covered by meters of debris. Debris flows almost always take place in the Shenmu area during the flood season, especially in the catchment areas around Tsushui river and Aiyuzih river. Anthropogenic and natural factors that cause debris flow occurrences are complex and numerous. The precise conditions of initiation are difficult to be identified, but three factors are generally considered to be the most important ones, i.e. rainfall characteristics, geologic conditions and topography. This study proposes a simple and feasible process that combines remote sensing technology and multi-stage high-precision DTMs from aerial orthoimages and airborne LiDAR with field surveys to establish a connection between three major occurrence factors that trigger debris flows in the Shenmu area.

scholarly journals A critical assessment of simple recharge models: application to the UK Chalk

2013 ◽  
Vol 17 (6) ◽  
pp. 2083-2096 ◽  
Author(s):  
A. M. Ireson ◽  
A. P. Butler
Keyword(s):  
Water Table ◽  
Unsaturated Zone ◽  
Groundwater Resources ◽  
Richards Equation ◽  
Unknown Parameters ◽  
Monthly Basis ◽  
Physically Based Model ◽  
Flow Processes ◽  
Physically Based ◽  
The Uk

Abstract. Quantification of the timing and magnitude of point-scale groundwater recharge is challenging, but possible at specific sites given sufficient high spatial and temporal resolution field observations, and a suitable physically based model. Such models are generally too computationally intensive and have too many unknown parameters to be practically applicable within distributed, larger-scale hydrological or groundwater models. This motivates the need for simpler recharge models, which are widely used within groundwater models. However, it is important that these models are able to capture adequately the unsaturated zone flow processes. We perform an inter-comparison of recharge simulated by a detailed physically based model and a simple recharge model, with both models applied to a field site in the fractured porous Chalk in the UK. Flow processes are simulated convincingly using a dual permeability, equivalent continuum, vertically heterogeneous, Richards' equation model, applied to a 2-D hillslope transect. A simple conventional recharge model was then calibrated to reproduce the water table response simulated by the physically based model. The performance in reproducing the water table was surprisingly good, given the known discrepancies between the actual processes and the model representation. However, comparisons of recharge fluxes simulated by each model highlighted problems with the process representations in the simple model. Specifically, bypass flow events during the summer were compensating for recharge that should have come from slow, continual drainage of the unsaturated zone. Such a model may still be useful for assessment of groundwater resources on a monthly basis, under non-extreme climatic conditions. However, under extreme wet or dry conditions, or under a changed climate the predictive capacity of such models is likely to be inadequate.

Identification of the affected areas by mass movement through a physically based model of landslide hazard combined with an empirical model of debris flow

2008 ◽  
Vol 45 (2) ◽  
Author(s):  
Roberto A. T. Gomes ◽  
Renato F. Guimarães ◽  
Osmar A. Carvalho ◽  
Nelson F. Fernandes ◽  
Eurípedes A. Vargas ◽  
...  
Keyword(s):  
Debris Flow ◽  
Empirical Model ◽  
Mass Movement ◽  
Landslide Hazard ◽  
Physically Based Model ◽  
Physically Based
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