Multi-step hazard assessment of debris flows in an Alpine region

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1 Multi-step hazard assessment of debris flows in an Alpine region R. Genevois Department of Geosciences, University of Padova, Padova, Italy P.R. Tecca CNR-IRPI, Padova, Italy M. Floris, C. Squarzoni & A. D Alpaos Department of Geosciences, University of Padova, Padova, Italy ABSTRACT: This article proposes a three-staged method for a debris-flow hazard analysis which includes design volume assessment, determination of the hydrograph for predefined return periods, numerical simulations to predict the spatial distribution of deposits. A final hazard map, with the delineation of low, medium and high hazard is obtained combining within a GIS-environment the different hazard classes of the individual rheology-specific hazard maps. This hazard analysis includes both the concepts of intensity and probability of occurrence of debris flow, proving that the use of GIS implements complex forecasting methods by combining the output data obtained by numerical models. 1 INTRODUCTION Debris-flow prone areas can be easily identified through field experience and evidence of previous events. Upon initiation, debris flows can travel considerable distances especially in confined channels, representing the most active geomorphic risk to public safety in mountainous areas. However, the understanding of triggering, transport and depositional processes of debris flow is still scientifically incomplete. Much effort has been thus put in defining some debris-flow parameters that can turn out to be quite relevant for both debris-flow modelling and prediction of the areas most probably affected by future debris flows. It is indeed the accurate prediction of runout distances and velocities, and the knowledge of flow rheology, including specifications for the related probability of occurrence, that can reduce damages, providing a means to produce hazard maps, to estimate hazard intensities and to provide parameters for the design of protective measures. During the last decade, the bidimensional model FLO-2D (O Brien et al., 1993) is being used increasingly for debris-flow simulation as a useful tool for predictive purposes and hazard map delineation, in many studies on hazard and risk assessment at the local scale (Chuang et al., 2000; Hubl and Steinwendtner, 2001; Bertolo and Wieczoreck, 2002; Aleotti and Polloni, 2003; Bello et al., 2003; O Brien, 2003; Garcia et al., 2004; Lin et al., 2004; Rickenmann et al., 2005; D Agostino and Tecca, 2006; Tecca et al., 2006; Armento et al., 2007). The aim of this paper is to present a procedure to carry out a debris-flow hazard assessment at a local scale using FLO-2D to model the propagation and spreading of debris flows. The methodology has been applied to the Cortina d Ampezzo area (Italian Eastern Alps). In this paper we present the methodology and the results obtained in one sample basin located on the western slope of the Mount Pomagagnon. The hazard analysis includes both the concepts of intensity and probability of occurrence of debris flow, proving that the use of GIS systems allows implementing complex forecasting models by combining the output data obtained by numerical simulations. 2 STUDY AREA The sample debris-flow basin is located on the left side of the Boite River Valley, in the Eastern Dolomites, Italy (Fig. 1). 325 debris-flow prone watersheds have been mapped in the geomorphological hazard map of this area, characterized by the presence of high rock cliffs, made of Triassic dolomites and limestones. The bedrock is covered by quaternary deposits, mainly screes and landslides deposits, having on a whole a thickness of 40 m at least in the lower slope as evidenced by borehole logs carried out in a site a few hundred meters far. The scree slopes are formed by coarse granular soils from sands to blocks with slope angles ranging from 35-40, at the base of the cliff, to at the valley bottom. The debris flows occur during intense summer rainstorms with a biennial or higher frequency; -291-

2 volume estimation of past events in the studied area range between 6000 and m 3. Discharges of debris often affect building related to farming, small factories and tourism, and dam the Boite River. Figure 1. Location and topographical map of the sample debris flow channel. Basic morphometric parameters of the sample basin are listed in Table 1. Table 1. Main morphometric parameters of the sample basin. Rock basin area (km 2 ) 0.13 Basin maximum elevation (m a.s.l.) 2348 Minimum elevation of the flow channel (m a.s.l.) 1655 Channel length (m) 774 Mean channel slope ( ) 23 3 METHODOLOGY In this study, we established a three-step approach to assess debris-flow hazards. 3.1 Geomorphologic and geologic analysis The first step consisted of a geomorphologic and geologic analysis by photo interpretation and field surveys, in order to identify potential debris-flow initiation zones and the availability of loose material, and the assessment of the design debris flow, e.g. the maximum potential total volume of the process (V tot ), for each basin. V tot has been assessed for each basin as the sum of the initial volume (V i ), and the scour volume along the flow channel (V c ) (Hungr et al., 1984), based on scour rate of m 3 /m for the Dolomitic area (Marchi and Tecca, 1996); the initial volume (V i ) has been estimated as the product of the area of the localized sediment source in the initiation zone and its average thickness. 3.2 Numerical simulations The second step predicts the runout and depth of deposits, through numerical simulations using the FLO-2D code, a two-dimensional finite difference routing model for water and non-newtonian flows on alluvial fans. The model can predict the area of inundation, flow velocity and depth, maintaining mass conservation for both the water and sediment volumes, solving the continuity equation and the two-dimensional equations of motion in both orthogonal flow directions (O Brien et al., 1993). The friction slope components have been written as a function of bed gradient, pressure gradient and convective and local accelerations. The theoretical equation for the total friction slope S f (the quadratic rheologic model of Julien and Lan, 1991), based on a combination of yield, viscous, collision and turbulent stresses, is expressed by: 2 2 τ y K lη v n v S f = (1) ρhg 8ρh g h where τ y and η are respectively the Bingham yield stress and viscosity functions of sediment concentration, ρ the flow density, g the gravitational acceleration, v the mean flow velocity, K l a laminar flow resistance coefficient, and n the pseudo-manning s resistance coefficient accounting for collisional and turbulent frictional losses. For a complete discussion of the model, see the User s Manual (FLO-2D Software Inc., 2006). The design debris flows have been routed for three different rheologies. The range of variability of input parameters has been selected based on the rheological properties calculated through the analysis of flow depth and velocity data for similar debris flow (Tecca et al., 2003). Table 2. Calculated yield stress and viscosity for C v =0.55. Rheology Viscosity η (Pa s) Yield stress τ y (Pa) R R R The rheological properties values, calculated for a sediment concentration by volume of 0.55, are listed in Table 2. A roughness n-value of 0.18 was assumed, typical for open ground with debris; the density of the mixture ρ m and the resistance parameter for laminar flow K, were assumed equals to 2650 kg/m 3 and 2285 respectively, suggested values for debris flows (FLO-2D Software Inc. 2006). The hydrologic model Hec-HMS (Scharffenberg & Fleming, 2008) has been used to predict the design storm rainfall-runoff hydrographs. The EV1 distribution has been applied to maximum annual rainfall of durations of 5, 10, 15, 30,

3 and 60 minutes recorded from 1984 to 2004 at the rain gauge of Faloria, the closest to the debris-flow site. Total rainfall amounts of and mm for duration of one hour have been obtained for return periods of 30 and 200 years, respectively. Triangular hyetographs have been built for the two return periods, with maximum intensities over 30 minutes of 7.46 mm (30 years) and mm (200 years). Rainfall excess has been computed using the SCS curve number, and runoff hydrograph has been obtained by means of the SCS dimensionless unit hydrograph. Peak water discharges of 2.40 and 4.00 m 3 /s for the 30 years and 200 years rainfall, respectively, have been obtained. A sediment concentration by volume was assigned to the hydrographs, ranging between not less than 0.2 along the rising and falling limbs of the hydrographs, and a maximum of 0.55 corresponding to a mature debris flow. The peak discharge was assigned a sediment concentration slightly less than the frontal wave to account for water dilution. The results have allowed producing, for each rheology, the debris-flow hazard maps (Figures 2 and 3), based on a methodology developed by Garcia et al. (2003). The hazard areas were classified into different hazard levels defined in terms of a combination of flow depth h and the momentum of the flow, that is the product of h and velocity v (OFEE et al. 1997). Figure 3. Prediction maps based on the three different rheologies for return period (T) of 200 years: a) rehology R1, b) rehology R2, c) rehology R3. Table 3 shows the hazard degree ranges; h and v values have been chosen based on literature data and our own experience from Dolomites debris flows. Table 3. Hazard degree ranges. Definition of Mud or debris-flow Intensity Maximum Maximum depth h times depth h (m) maximum velocity v (m 2 /s) High h>= 1.0 m OR v h > =1.0 m 2 /s Medium h>= 0.4 m AND v h > =0.4 m 2 /s Low h>= 0.2 m OR v h > =0.2 m 2 /s Figure 2. Prediction maps based on the three different rheologies for return period (T) of 30 years: a) rehology R1, b) rehology R2, c) rehology R Hazard mapping As final step, a final hazard map associated to a certain return period was obtained within GIS environment by superimposition of the three hazard maps, one for each rheology, combining the different hazard classes, and delineate comprehensive low, medium and high hazard areas for the site (Figures 4a and 4b). The single maps for each rheology have been combined with the same procedure used to obtain the final hazard map. The procedure to produce the final hazard maps with return period of 30 and 200 years, consists of the creation of a raster data set, taking, for a same pixel, the maximum value of hazard level (1: low; 2; medium; 3: high) amongst the three single maps for the same return period. That is, if a pixel is associated at low level (1) with rheology 1, high level (3) with rheology 2 and medium level (2) for rheology 3, in the final map that pixel will be associated to a final value of 3 (high hazard level)

4 Figure 4. Prediction maps for return periods (T) of 30 (a) and 200 (b) years. This approach is very conservative, but it is necessary because of the uncertainty related to the spatial variability of flow depending on the different rheology. 4 RESULTS AND DISCUSSION Design debris volumes of about 9000 m 3 and m 3 of total, were estimated by field survey and routed with the numerical simulations, for 30 years and 200 years return periods respectively. Three runs with three different rheologies were calculated for both hydrographs. Considering that a debris flow may change its rheology even during the same event, a choice of the rheological properties based on the back-simulation of one only well documented past event can be conservative or underestimating the hazardous zones rather than a choice based on measured properties of a very similar debris flow. Both the approaches affect the uncertainty related to the produced hazard maps, but, eventually, the use of reasonable, experimental data supported rheologies, seems a most reliable approach. In order to compare the single hazard maps for the three different rheologies, two cell-by-cell statistics in the output rasters have been calculated. Variety (Figures 5a and 6a) determines the number of unique values on a cell-by-cell basis considering the three single maps for the same return period, indicating if and where there are differences related to the different input parameters. Range (figures 5b and 6b) determines the range of values on a cell-by-cell basis between input rasters, and quantifies the differences between the single maps The main differences in the associated hazard are displayed in the middle and lower flow path. For both return periods we observed a variability of hazard level values at the element at risk, a national road and a secondary forest road. In some points, the variations were extreme, turning from a pixel value of 0 (null hazard) to a pixel value of 3 (high level hazard). This results show how much hazard conditions are determined by the flow rheology. 5 CONCLUSIONS Debris flows represent a significant hazard in mountainous areas such as the Dolomites. The fast growth of urbanisation and the limited space in the valley floors have created a need to construct buildings on the debris fans. This study establishes a multi-step procedure to evaluate the debris-flow hazard at a local scale

5 Figure 5. Variety (a) and range (b) calculated by comparison of the prediction images obtained with three different rheologies for return period (T) of 30 years. Figure 6. Variety (a) and range (b) calculated by comparison of the prediction images obtained with three different rheologies for return period (T) of 200 years

6 The multi-step approach established for hazard assessment combines the results obtained from a geomorphologic geologic study, numerical simulations and GIS representation and analysis. The use of a two-dimensional numerical model, enabling the simulation of the debris-flow spreading on the fan, is rather problematic when historic data, for calibration of rheological properties, are missing. This difficulty can be overcome performing a parametric analysis with alternative rheologies, that provides a spatial and quantitative prediction of flows and takes into account the whole range of hazard conditions, especially in the most vulnerable areas. The approach for the delineation of the final hazard map is therefore a conservative approach, but can become quite realistic if the choice of alternative rheologies is made within a range of experimental data for similar debris flows. This methodology shows that the use of GIS techniques improve and implement complex predictional models, combining the output data of the simulation code. Because of its simplicity and the very low cost benefit rate, the present approach can be applied to debris-flow hazard assessment at larger, as long as homogeneous, areas. Furthermore, through the statistics embedded in the GIS systems, it is possible to compare the results of parametric analyses, and as a consequence, to verify the suitability and applicability of the performed predictions. REFERENCES Aleotti, P. & Polloni, G Two-dimensional model of the 1998 Sarno debris flows (Italy): preliminary results. In Rickenmann & Chen, (eds): Third International Conference on Mud and Debris Flows, Proceedings of Debris Flow Hazards Mitigation: Mechanics, Prediction, and Assessment, Davos, Switzerland. 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