Description and analysis of the debris flows occurred during 2008 in the Eastern Pyrenees

Abstract. Rainfall-triggered landslides taking place in the Spanish Eastern Pyrenees have usually been analysed on a regional scale. Most research focussed either on terrain susceptibility or on the characteristics of the critical rainfall, neglecting a detailed analysis of individual events. In contrast to other mountainous regions, research on debris flow has only been performed marginally and associated hazard has mostly been neglected. In this study, five debris flows, which occurred in 2008, are selected; and site specific descriptions and analysis regarding geology, morphology, rainfall data and runout were performed. The results are compared with worldwide data and some conclusions on hazard assessment are presented. The five events can be divided into two in-channel debris flows and three landslide-triggered debris flows. The in-channel generated debris flows exceeded 10 000 m3, which are unusually large mass movements compared to historic events which occurred in the Eastern Pyrenees. In contrast, the other events mobilised total volumes less than 2000 m3. The geomorphologic analysis showed that the studied events emphasize similar patterns when compared to published data focussing on slope angle in the initiation zone or catchment area. Rainfall data revealed that all debris flows were triggered by high intensity-short duration rainstorms during the summer season. Unfortunately, existing rainfall thresholds in the Eastern Pyrenees consider long-lasting rainfall, usually occurring in autumn/winter. Therefore, new thresholds should be established taking into account the rainfall peak intensity in mm/h, which seems to be a much more relevant factor for summer than the event's total precipitation. The runout analysis of the 2008 debris flows confirms the trend that larger volumes generally induce higher mobility. The numerical simulation of the Riu Runer event shows that its dynamic behaviour is well represented by Voellmy fluid rheology. A maximum front velocity of 7 m/s was back-analysed for the transit section and even on the fan velocities larger than 2 m/s were obtained. This preliminary analysis of the major Eastern Pyrenean debris flows represents the first background for future studies. Additional research on other events is necessary to support the results presented herein, and to properly assess and reduce hazard related to debris flows.

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Debris-flow forecasting at regional scale by combining susceptibility mapping and radar rainfall

Natural Hazards and Earth System Science ◽

10.5194/nhess-15-587-2015 ◽

2015 ◽

Vol 15 (3) ◽

pp. 587-602 ◽

Cited By ~ 24

Author(s):

M. Berenguer ◽

D. Sempere-Torres ◽

M. Hürlimann

Keyword(s):

Debris Flow ◽

Debris Flows ◽

Regional Scale ◽

Early Warning Systems ◽

Warning Systems ◽

Susceptibility Assessment ◽

Radar Rainfall ◽

Eastern Pyrenees ◽

Rainfall Map ◽

Rainfall Estimates

Abstract. This work presents a technique for debris-flow (DF) forecasting able to be used in the framework of DF early warning systems at regional scale. The developed system is applied at subbasin scale and is based on the concepts of fuzzy logic to combine two ingredients: (i) DF subbasin susceptibility assessment based on geomorphological variables and (ii) the magnitude of the rainfall situation as depicted from radar rainfall estimates. The output of the developed technique is a three-class warning ("low", "moderate" or "high") in each subbasin when a new radar rainfall map is available. The developed technique has been applied in a domain in the eastern Pyrenees (Spain) from May to October 2010. The warning level stayed "low" during the entire period in 20% of the subbasins, while in the most susceptible subbasins the warning level was at least "moderate" for up to 10 days. Quantitative evaluation of the warning level was possible in a subbasin where debris flows were monitored during the analysis period. The technique was able to identify the three events observed in the catchment (one debris flow and two hyperconcentrated flow events) and produced no false alarm.

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LABS: an agent-based run-out program for shallow landslides

10.5194/nhess-2020-233 ◽

2020 ◽

Author(s):

Richard Guthrie ◽

Andrew Befus

Keyword(s):

Predictive Model ◽

Debris Flows ◽

Flow Behavior ◽

Regional Scale ◽

Path Selection ◽

Agent Based ◽

Mountainous Regions ◽

Debris Avalanches ◽

First Case ◽

Landslide Runout

Abstract. Credible models of landslide runout are a critical component of hazard and risk analysis in the mountainous regions worldwide. Hazard analysis benefits enormously from the number of available landslide runout models that can recreate events and provide key insights into the nature of landsliding phenomena. Regional models that are easily employed, however, remain a rarity. For debris flows and debris avalanches, where the impacts may occur some distance from the source, there remains a need for a practical, predictive model that can be applied at the regional scale. We present, herein, an agent-based simulation for debris flows and debris avalanches called LABS. A fully predictive model, LABS employs autonomous sub-routines, or agents, that act on an underlying DEM using a set of probabilistic rules for scour, deposition, path selection, and spreading behavior. Relying on observations of aggregate debris flow behavior, LABS predicts landslide runout, area, volume, and depth along the landslide path. The results can be analyzed within the program or exported in a variety of useful formats for further analysis. A key feature of LABS is that it requires minimal input data, relying primarily on a 5 m DEM and user defined initiation zones, and yet appears to produce realistic results. We demonstrate the applicability of LABS using two very different case studies from distinct geologic, geomorphic, and climatic settings. The first case study considers sediment production from the steep slopes of Papua, the island province of Indonesia; the second considers landslide runout as it affects a community on Vancouver Island off the west coast of Canada. We show how LABS works, how it performs compared to real world examples, what kinds of problems it can solve, and how the outputs compare to historical studies. Finally, we discuss its limitations and its intended use as a predictive regional landslide runout tool. LABS is freely available to not for profit groups including universities, NGOs and government organizations.

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An early warning system for rainfall-triggered shallow slides and debris flows. Application in Catalonia, Spain and Canton of Bern, Switzerland

10.5194/egusphere-egu2020-479 ◽

2020 ◽

Author(s):

Rosa M Palau ◽

Marc Berenguer ◽

Marcel Hürlimann ◽

Daniel Sempere-Torres ◽

Catherine Berger ◽

...

Keyword(s):

Early Warning ◽

Debris Flows ◽

Risk Mitigation ◽

Regional Scale ◽

Slope Angle ◽

Early Warning Systems ◽

Warning Systems ◽

Radar Rainfall ◽

Susceptibility Maps ◽

Landslide Event

Risk mitigation for rainfall-triggered shallow slides and debris flows at regional scale is challenging. Early warning systems are a helpful tool to depict the location and time of future landslide events so that emergency managers can act in advance. Recently, some of the regions that are recurrently affected by rainfall triggered landslides have developed operational landslide early warning systems (LEWS). However, there are still many territories where this phenomenon also represents an important hazard and lack this kind of risk mitigation strategy.The main objective of this work is to study the feasibility to apply a regional scale LEWS, which was originally designed to work over Catalonia (Spain), to run in other regions. To do so we have set up the LEWS to Canton of Bern (Switzerland).The LEWS combines susceptibility maps to determine landslide prone areas and in real time high-resolution radar rainfall observations and forecasts. The output is a qualitative warning level map with a resolution of 30 m.Susceptibility maps have been derived using a simple fuzzy logic methodology that combines the terrain slope angle, and land use and land cover (LULC) information. The required input parameters have been obtained from regional, pan-European and global datasets.Rainfall inputs have been retrieved from both regional weather radar networks, and the OPERA pan-European radar composite. A set of global rainfall intensity-duration data has been used to asses if a rainfall event has the potential of triggering a landslide event.The LEWS has been run in the region of Catalonia and Canton of Bern for specific rainfall events that triggered important landslides. Finally, the LEWS performance in Catalonia has been assessed.Results in Catalonia show that the LEWS performance strongly depends on the quality of both the susceptibility maps and rainfall data. However, in both regions the LEWS is generally able to issue warnings for most of the analysed landslide events.

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DebrisFlow Predictor: an agent-based runout program for shallow landslides

Natural Hazards and Earth System Science ◽

10.5194/nhess-21-1029-2021 ◽

2021 ◽

Vol 21 (3) ◽

pp. 1029-1049

Author(s):

Richard Guthrie ◽

Andrew Befus

Keyword(s):

Predictive Model ◽

Debris Flows ◽

Flow Behavior ◽

Regional Scale ◽

Path Selection ◽

Agent Based ◽

Mountainous Regions ◽

Debris Avalanches ◽

First Case ◽

Landslide Runout

Abstract. Credible models of landslide runout are a critical component of hazard and risk analysis in the mountainous regions worldwide. Hazard analysis benefits enormously from the number of available landslide runout models that can recreate events and provide key insights into the nature of landsliding phenomena. Regional models that are easily employed, however, remain a rarity. For debris flows and debris avalanches, where the impacts may occur some distance from the source, there remains a need for a practical, predictive model that can be applied at the regional scale. We present, herein, an agent-based simulation for debris flows and debris avalanches called DebrisFlow Predictor. A fully predictive model, DebrisFlow Predictor employs autonomous subroutines, or agents, that act on an underlying digital elevation model (DEM) using a set of probabilistic rules for scour, deposition, path selection, and spreading behavior. Relying on observations of aggregate debris flow behavior, DebrisFlow Predictor predicts landslide runout, area, volume, and depth along the landslide path. The results can be analyzed within the program or exported in a variety of useful formats for further analysis. A key feature of DebrisFlow Predictor is that it requires minimal input data, relying primarily on a 5 m DEM and user-defined initiation zones, and yet appears to produce realistic results. We demonstrate the applicability of DebrisFlow Predictor using two very different case studies from distinct geologic, geomorphic, and climatic settings. The first case study considers sediment production from the steep slopes of Papua, the island province of Indonesia; the second considers landslide runout as it affects a community on Vancouver Island off the west coast of Canada. We show how DebrisFlow Predictor works, how it performs compared to real world examples, what kinds of problems it can solve, and how the outputs compare to historical studies. Finally, we discuss its limitations and its intended use as a predictive regional landslide runout tool. DebrisFlow Predictor is freely available for non-commercial use.

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Recent debris flows in the Portainé catchment (Eastern Pyrenees, Spain): analysis of monitoring and field data focussing on the 2015 event

Landslides ◽

10.1007/s10346-017-0832-9 ◽

2017 ◽

Vol 14 (3) ◽

pp. 1161-1170 ◽

Cited By ~ 9

Author(s):

Rosa M. Palau ◽

Marcel Hürlimann ◽

Jordi Pinyol ◽

José Moya ◽

Ane Victoriano ◽

...

Keyword(s):

Debris Flows ◽

Field Data ◽

Eastern Pyrenees

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Development of an initiation criterion for debris flows based on local topographic properties and applicability assessment at a regional scale

Engineering Geology ◽

10.1016/j.enggeo.2017.09.017 ◽

2017 ◽

Vol 230 ◽

pp. 64-76 ◽

Cited By ~ 13

Author(s):

Sinhang Kang ◽

Seung-Rae Lee ◽

Nikhil N. Vasu ◽

Joon-Young Park ◽

Deuk-Hwan Lee

Keyword(s):

Debris Flows ◽

Regional Scale

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Geohazards Susceptibility Assessment along the Upper Indus Basin Using Four Machine Learning and Statistical Models

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10050315 ◽

2021 ◽

Vol 10 (5) ◽

pp. 315

Author(s):

Hilal Ahmad ◽

Chen Ningsheng ◽

Mahfuzur Rahman ◽

Md Monirul Islam ◽

Hamid Reza Pourghasemi ◽

...

Keyword(s):

Machine Learning ◽

Land Cover ◽

Debris Flows ◽

Regional Scale ◽

Indus Basin ◽

Annual Rainfall ◽

Slope Aspect ◽

Topographic Wetness Index ◽

Susceptibility Maps ◽

Landslides And Debris Flows

The China–Pakistan Economic Corridor (CPEC) project passes through the Karakoram Highway in northern Pakistan, which is one of the most hazardous regions of the world. The most common hazards in this region are landslides and debris flows, which result in loss of life and severe infrastructure damage every year. This study assessed geohazards (landslides and debris flows) and developed susceptibility maps by considering four standalone machine-learning and statistical approaches, namely, Logistic Regression (LR), Shannon Entropy (SE), Weights-of-Evidence (WoE), and Frequency Ratio (FR) models. To this end, geohazard inventories were prepared using remote sensing techniques with field observations and historical hazard datasets. The spatial relationship of thirteen conditioning factors, namely, slope (degree), distance to faults, geology, elevation, distance to rivers, slope aspect, distance to road, annual mean rainfall, normalized difference vegetation index, profile curvature, stream power index, topographic wetness index, and land cover, with hazard distribution was analyzed. The results showed that faults, slope angles, elevation, lithology, land cover, and mean annual rainfall play a key role in controlling the spatial distribution of geohazards in the study area. The final susceptibility maps were validated against ground truth points and by plotting Area Under the Receiver Operating Characteristic (AUROC) curves. According to the AUROC curves, the success rates of the LR, WoE, FR, and SE models were 85.30%, 76.00, 74.60%, and 71.40%, and their prediction rates were 83.10%, 75.00%, 73.50%, and 70.10%, respectively; these values show higher performance of LR over the other three models. Furthermore, 11.19%, 9.24%, 10.18%, 39.14%, and 30.25% of the areas corresponded to classes of very-high, high, moderate, low, and very-low susceptibility, respectively. The developed geohazard susceptibility map can be used by relevant government officials for the smooth implementation of the CPEC project at the regional scale.

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The Development of a 1-D Integrated Hydro-Mechanical Model Based on Flume Tests to Unravel Different Hydrological Triggering Processes of Debris Flows

Water ◽

10.3390/w10070950 ◽

2018 ◽

Vol 10 (7) ◽

pp. 950 ◽

Cited By ~ 5

Author(s):

Theo van Asch ◽

Bin Yu ◽

Wei Hu

Keyword(s):

Debris Flow ◽

Mechanical Model ◽

Debris Flows ◽

Overland Flow ◽

Slope Angle ◽

Great Influence ◽

Flume Experiments ◽

Triggering Mechanisms ◽

Bed Material ◽

Triggering Process

Many studies which try to analyze conditions for debris flow development ignore the type of initiation. Therefore, this paper deals with the following questions: What type of hydro-mechanical triggering mechanisms for debris flows can we distinguish in upstream channels of debris flow prone gullies? Which are the main parameters controlling the type and temporal sequence of these triggering processes, and what is their influence on the meteorological thresholds for debris flow initiation? A series of laboratory experiments were carried out in a flume 8 m long and with a width of 0.3 m to detect the conditions for different types of triggering mechanisms. The flume experiments show a sequence of hydrological processes triggering debris flows, namely erosion and transport by intensive overland flow and by infiltrating water causing failure of channel bed material. On the basis of these experiments, an integrated hydro-mechanical model was developed, which describes Hortonian and saturation overland flow, maximum sediment transport, through flow and failure of bed material. The model was calibrated and validated using process indicator values measured during the experiments in the flume. Virtual model simulations carried out in a schematic hypothetical source area of a catchment show that slope angle and hydraulic conductivity of the bed material determine the type and sequence of these triggering processes. It was also clearly demonstrated that the type of hydrological triggering process and the influencing geometrical and hydro-mechanical parameters may have a great influence on rainfall intensity-duration threshold curves for the start of debris flows.

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Empirical atmospheric thresholds for debris flows and flash floods in the southern French Alps

Natural Hazards and Earth System Science ◽

10.5194/nhess-14-1517-2014 ◽

2014 ◽

Vol 14 (6) ◽

pp. 1517-1530 ◽

Cited By ~ 15

Author(s):

T. Turkington ◽

J. Ettema ◽

C. J. van Westen ◽

K. Breinl

Keyword(s):

Debris Flows ◽

Warning System ◽

Flash Floods ◽

Rain Gauge ◽

Reanalysis Data ◽

Specific Humidity ◽

Atmospheric Conditions ◽

Convective Rainfall ◽

French Alps ◽

Mountainous Regions

Abstract. Debris flows and flash floods are often preceded by intense, convective rainfall. The establishment of reliable rainfall thresholds is an important component for quantitative hazard and risk assessment, and for the development of an early warning system. Traditional empirical thresholds based on peak intensity, duration and antecedent rainfall can be difficult to verify due to the localized character of the rainfall and the absence of weather radar or sufficiently dense rain gauge networks in mountainous regions. However, convective rainfall can be strongly linked to regional atmospheric patterns and profiles. There is potential to employ this in empirical threshold analysis. This work develops a methodology to determine robust thresholds for flash floods and debris flows utilizing regional atmospheric conditions derived from ECMWF ERA-Interim reanalysis data, comparing the results with rain-gauge-derived thresholds. The method includes selecting the appropriate atmospheric indicators, categorizing the potential thresholds, determining and testing the thresholds. The method is tested in the Ubaye Valley in the southern French Alps (548 km2), which is known to have localized convection triggered debris flows and flash floods. This paper shows that instability of the atmosphere and specific humidity at 700 hPa are the most important atmospheric indicators for debris flows and flash floods in the study area. Furthermore, this paper demonstrates that atmospheric reanalysis data are an important asset, and could replace rainfall measurements in empirical exceedance thresholds for debris flows and flash floods.

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Optimal Rainfall Estimation by Considering Elevation in the Han River Basin, South Korea

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-11-0147.1 ◽

2013 ◽

Vol 52 (4) ◽

pp. 802-818 ◽

Cited By ~ 12

Author(s):

Seong-Sim Yoon ◽

Deg-Hyo Bae

Keyword(s):

South Korea ◽

River Basin ◽

Flood Control ◽

Rainfall Data ◽

Spatiotemporal Variability ◽

Radar Rainfall ◽

Mountainous Regions ◽

Han River ◽

Orographic Rainfall ◽

Han River Basin

AbstractMore than 70% of South Korea has mountainous terrain, which leads to significant spatiotemporal variability of rainfall. The country is exposed to the risk of flash floods owing to orographic rainfall. Rainfall observations are important in mountainous regions because flood control measures depend strongly on rainfall data. In particular, radar rainfall data are useful in these regions because of the limitations of rain gauges. However, radar rainfall data include errors despite the development of improved estimation techniques for their calculation. Further, the radar does not provide accurate data during heavy rainfall in mountainous areas. This study presents a radar rainfall adjustment method that considers the elevation in mountainous regions. Gauge rainfall and radar rainfall field data are modified by using standardized ordinary cokriging considering the elevation, and the conditional merging technique is used for combining the two types of data. For evaluating the proposed technique, the Han River basin was selected; a high correlation between rainfall and elevation can be seen in this basin. Further, the proposed technique was compared with the mean field bias and original conditional merging techniques. Comparison with kriged rainfall showed that the proposed method has a lesser tendency to oversmooth the rainfall distribution when compared with the other methods, and the optimal mean areal rainfall is very similar to the value obtained using gauges. It reveals that the proposed method can be applied to an area with significantly varying elevation, such as the Han River basin, to obtain radar rainfall data of high accuracy.

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