Proposal of Estimation Method for Debris Flow Potential Considering Eruptive Activity

Watershed landslide evolution combined with topographic factors to delineate the spatio-temporal distribution of sediment sources in central Taiwan

Controls on spatiotemporal heterogeneity and evolution of debris flows along a traffic corridor affected by the strong Wenchuan earthquake

The steep, tectonically active terrain along the Central California (USA) coast is well known to produce deadly and destructive debris flows. However, the extent to which fire affects debris-flow susceptibility in this region is an open question. We documented the occurrence of postfire debris floods and flows following the landfall of a storm that delivered intense rainfall across multiple burn areas. We used this inventory to evaluate the predictive performance of the US Geological Survey M1 likelihood model, a tool that presently underlies the emergency assessment of postfire debris-flow hazards in the western USA. To test model performance, we used the threat score skill statistic and found that the rainfall thresholds estimated by the M1 model for the Central California coast performed similarly to training (Southern California) and testing (Intermountain West) data associated with the original model calibration. Model performance decreased when differentiating between “minor” and “major” postfire hydrologic response types, which weigh effects on human life and infrastructure. Our results underscore that the problem of false positives is a major challenge for developing accurate rainfall thresholds for the occurrence of postfire debris flows. As wildfire activity increases throughout the western USA, so too will the demand for the assessment of postfire debris-flow hazards. We conclude that additional collection of field-verified inventories of postfire hydrologic response will be critical to prioritize which model variables may be suitable candidates for regional calibration or replacement.

Impact of Chi-Chi earthquake on the occurrence of landslides and debris flows: example from the Chenyulan River watershed, Nantou, Taiwan

Debris flows generated by rainfall runoff can occur in rocky alpine landscapes and burned steeplands. Runoff-generated debris-flow events are commonly composed of a series of dense granular surge fronts separated by water-rich flows. Owing to this intra-event variability in flow composition and mechanics, post-event interpretations of preserved sedimentary deposits, or lack thereof, can result in a dizzying mix of interpretations that range from clearwater flow to debris flow. Accurate identification of the presence or absence of a debris flow during a runoff event is critical for building empirical models used to predict likelihood of debris-flow occurrence, rainfall thresholds, and flow properties. Here, we propose a simple, quantitative method to identify the occurrence of a runoff-generated debris flow, based on a dimensionless discharge Q* calculated as the ratio of the peak event discharge Qp to the theoretical maximum clearwater runoff rate Qw. Using a preliminary compilation of Q* values from floods and runoff-generated debris flows, we find 98% of floods have Q* values < 1.6, whereas 91% of debris flows have Q* values greater than 1.6. Estimating Q* is typically straightforward as part of standard post-event reconnaissance if suitable rainfall estimates are available, and appears to be a robust indicator that runoff-generated debris flows traversed a particular portion of a valley network.

Debris flow is the gravity-propelled movement of sediment-water mixtures, in which grains are supported above the non-moving bed by the strength and buoyancy of a clay-water matrix. The competence (largest supported grain size) of a debris flow is thereby determined by the magnitudes of matrix strength and density, which vary primarily and directly with matrix clay content. Strength also varies with the type of clay mineral and with the cation content of the water. Experiments reported here indicate that as little as 1.5 to 4 wt. % clay mixed into water is sufficient to support finest sand. The experiments also show that competence is less in flowing debris than in static debris, and that competence decreases with flow duration for durations less than about one hour but remains essent ally constant for durations greater than one hour. Competence apparently is independent of flow velocity or velocity gradient, although low velocities and gradients were not examined here. Calculations based on the experimental data reveal that marine sediments with finest sand as their coarsest material and with bulk clay contents as low as 2 wt. %, or less, can move as debris flows. Sediments with coarsest sand can move as debris flows if they contain as little as 19% clay, or less. Considering that these values are high estimates, many finegrained marine sediments have clay contents great enough in order to move as debris flows. Zones of various competences should exist within a debris flow because of the nature of the velocity profile and the dependence of competence on shear and flow duration. These zones are preserved during deposition and therefore, debris-flow deposits expectably should have layers of various grain sizes, and perhaps be normally and/or inversely graded. Debris flow is discussed in this paper as an idealized concept, where grain support is wholly by strength and buoyancy. In real flows, support also may be provided by graininteraction dispersive pressure and by turbulence, increasing the competence of the flows. Debris-flow mobility, in terms of the forces required to keep the flow moving, was not considered here but is equally significant to competence in evaluating the occurrence of real debris flows.

The accurate prediction of debris flows occurrence that will allow the reduction or prevention of economic losses and human casualties is presently the most difficult aspect of debris flows studies but also the aspect that receives most attention. Most prediction methods are based on rainfall as the basic parameter, with the moment of occurrence as only result, and without a prediction of debris flow travel time and size. This paper takes Jiangjia Gully in Dongchuan of Yunnan Province as an example, and considers, on the basis of the fulfillment of the essential condition: the abundant availability of loose materials, the conditions for the formation of debris flows. Based on the mechanism of the initiation of debris flows in channels and the volume of rainfall in the basin, this paper also gives a systematic analysis on the travel time and size of the debris flow and suggests that the hydrological condition for forming debris flow is the unit discharge of the flood ≥0.35 m3/s.m. It uses the 10-min rainfall intensity to calculate both the run-off of the rainfall and the unit discharge caused by the run-off, thus predicting the occurrence of debris flows. The velocity and the travel time of a debris flow can also be determined using the unit discharge of the run-off. The total volume of debris flows can be calculated using the 10-min intensity of rainfall and the total volume of the run-off, together with the volume concentration of the sediment in a debris flow.

Climate change has increased the amount and intensity of rainfall, increasing debris flow risk. Debris flow damage has become a social issue in Korea, and the need for research related to rainfall thresholds for debris flow has increased. In this study, an automatic calculation algorithm was developed to derive criteria suitable for the Korean region for the rainfall thresholds of debris flow. The study area selected was Gangwon-do, where a significant amount of debris flow occurred recently, and information on rainfall and the occurrence of debris flow were collected. As a result of applying an algorithm based on the R programming language, an equation for the relationship between the rainfall intensity and duration in Gangwon-do was automatically derived using debris flow occurrence point information and meteorological rainfall information.

Mountain highways in China are located in various natural geographical areas with intense tectonic activity, steep topography and a high frequency of extreme precipitation events. These conditions make the highways vulnerable to the occurrence of multiple large debris flows simultaneously during heavy rainfall. To manage this hazard risk, a broader understanding of the hazard effects of debris flows and the vulnerability of highways is needed to reduce the losses resulting from these hazardous events. Accordingly, we analysed the effects of debris flow hazards on mountain highways and established an updated systematic indicator system to describe the vulnerability of highway infrastructure and movable hazard-affected objects. Next, we proposed a new integrated model of highway vulnerability based on the environmental sensibility, structural properties and functional effects of the highway infrastructure and on the exposure probability and quantity of movable hazard-affected objects. By analysing the characteristics of elements affected by debris flows, we developed a systematic and quantitative method of vulnerability assessment for mountain highways. Finally, this implemented method was applied to a case study in the Xiqu section of the Sichuan-Tibet Highway, an area seriously affected by debris flows during each rainy season. The hazard characteristics of disasters were analysed, and the affected highway sections were divided into four vulnerability levels. The analysis of the results indicated that the calculated vulnerability coincides with the actual effects of the disaster, which strongly suggests that the vulnerability assessment generated by the proposed method can serve as a pertinent guide for route selection, road rehabilitation and hazard mitigation of highways affected by debris flows in mountainous regions.

Abstract. The occurrence of debris flows has been recorded for more than a century in the European Alps, accounting for the risk to settlements and other human infrastructure that have led to death, building damage and traffic disruptions. One of the difficulties in the quantitative hazard assessment of debris flows is estimating the run-out behavior, which includes the run-out distance and the related hazard intensities like the height and velocity of a debris flow. In addition, as observed in the French Alps, the process of entrainment of material during the run-out can be 10–50 times in volume with respect to the initially mobilized mass triggered at the source area. The entrainment process is evidently an important factor that can further determine the magnitude and intensity of debris flows. Research on numerical modeling of debris flow entrainment is still ongoing and involves some difficulties. This is partly due to our lack of knowledge of the actual process of the uptake and incorporation of material and due the effect of entrainment on the final behavior of a debris flow. Therefore, it is important to model the effects of this key erosional process on the formation of run-outs and related intensities. In this study we analyzed a debris flow with high entrainment rates that occurred in 2003 at the Faucon catchment in the Barcelonnette Basin (Southern French Alps). The historic event was back-analyzed using the Voellmy rheology and an entrainment model imbedded in the RAMMS 2-D numerical modeling software. A sensitivity analysis of the rheological and entrainment parameters was carried out and the effects of modeling with entrainment on the debris flow run-out, height and velocity were assessed.

The occurrence of debris flows are a significant threat to human lives and property. Estimating the debris flow scale is a crucial parameter for assessing disaster losses in such events. Currently, the commonly used method for estimating debris flow runoff relies on fitting techniques, which often yield low prediction accuracy and limited data representation capabilities. Addressing these challenges, this study proposes an improved grey wolf algorithm optimized support vector machine prediction model. The model’s effectiveness is validated using data from 72 debris flow events in Beichuan County. The results demonstrate a prediction accuracy of 95.9% using this approach, indicating its strong predictive capabilities for debris flow scale. Additionally, it is observed that the basin area, the basin relative, and the main channel length are the key factors influencing debris flow scale in Beichuan County.

The Siwalik hill of Nepal lies in between the two major thrusts; Main boundary Thrust and Main Frontal Thrust. Thrusting and continuous erosion of material from surface causes several landslides and debris flow problem in the Siwalik region. Debris flow commonly occurs after landslide during heavy rainfall in the steep slope. This paper described about the topographical and geological controls on debris flow occurring in gullies in the Siwaliks of the Malai River catchment of mid-Western Nepal. The length of gully, length of debris channel, area of debris channel, area of catchment of debris flow, area of gully without debris flow were found using Google earth pro, a free version online database. Similarly, a form factor (F), average gradient of stream, slope area ratio and a topographical factor (T) were calculated. Lithology and geological structure were studied in the field. The relation between each factor was identified.
 Gully having larger debris flow event had T value greater than 0.01 and that having small debris flow event had T value less than 0.01. Gully without debris flow had T value less than 0.001. Gully having debris flow had F more than 0.1 and that free from debris flow had F less than 0.1. Both topographic and form factors were found greater than 0.1 at the hanging wall of the Malai Thrust, where large size debris flows were encountered. The T and F values obtained from the Middle and Upper Siwaliks were greater than 0.1.The number of debris flow events and large debris flows were found high the in the Middle and the Upper Siwaliks, and hanging wall of the Malai Thrust.

In Santa Catarina State (Brazil), Rio dos Cedros is one of the cities that suffered from natural disasters triggered by very intense rainfall in November 2008.According to the Municipal Civil Defense, this event caused economic losses of US$2.1 million and 96 homeless, directly affecting 90% of the municipal population.The principal phenomenon responsible for these disasters was the debris flow.In this context, field surveys were conducted throughout the city in order to investigate the possibility for houses to be affected by landslides and debris flows.After the preliminary evaluation, two cases of debris flow whose extensions were over 1 km were chosen for a more detailed survey.The objective of the present study was to analyze the meteorological and geomorphic aspects of these cases.The total rainfall in Rio dos Cedros in November 2008 and the entire year of 2008 were 644 mm and 2509 mm, respectively.An analysis of the daily rainfall during October and November 2008 and the debris flow occurrence time indicates that the factor triggering debris flows in Rio dos Cedros in 2008 was the accumulated rainfall, not its intensity.Two debris flows analyzed in the present study had different geomorphic conditions, one being confined in the channel and showing ordinal debris flow (Debris A), and the other unconfined, presenting the debris avalanche feature (Debris B).The larger density of clastic blocks was observed at the depositional area of Debris B. Both the localities are characterized with migmatite.Topographic analysis showed that the volume of the mass movement is related with topographic parameters (elevation difference and travel distance).This relationship implies that the two cases of Rio dos Cedros had similar behavior to other cases reported in temperate and cold regions.It is, therefore, concluded that there is geomorphic control on www.witpress.com,

Depositional characteristics of debris flows in a rectangular channel with an abrupt change in slope

There is an increased risk in post-fire debris flow (DF) occurrences in the western USA with recent increase in wildfire frequencies. DFs are destructive, causing high loss to lives and infrastructure. A lot of effort is going into possible preventive and/or mitigation measures. Recent research efforts in this niche focus on developing statistical models that assist emergency responders in isolating high-hazard locations after fires. There are two general approaches to this statistical modeling: linear and nonlinear. This study has looked into applying a linear-based logistic regression model and a nonlinear-based C5.0 decision tree model to assess the strength of each in predicting the locations within the Thomas Fire boundary that produced DFs. To do this, DF scars were delineated by running a change detection protocol known as delta normalized difference vegetation index (dNDVI), using high spatial resolution data from Planet Labs. These scars were further validated with data gathered by Santa Barbara County officials on affected areas. Results from the two statistical models were then overlain on the delineated DF scars and compared against each other to determine predictive strengths. The results revealed both models to perform well in predicting high probabilities for locations that were shown to produce DFs. The logistic regression model predicted an overall ~ 44,800 ha (49%) more high-hazard coverage compared to the C5.0 tree and therefore showed greater urgency. However, a closer look at the basin predictions with the delineated DF scars showed that most of these high-hazard basins identified by the logistic regression did not to have any discernible scars. It was projected that most of these locations were likely false positives and further fine-tuning of the model was recommended. Further recommendation was made concerning the development of additional models to predict potential DF inundation paths. Combining origination and inundation models will be most beneficial since the greatest associated danger with DFs is not necessarily where they start, but rather further downstream where most communities and infrastructure are situated.