Abstract
Debris flows are among the most hazardous phenomena in mountain areas. To cope with debris flow hazard, it is common to delineate the risk-prone areas through routing models. The most important input to debris flow routing models are the topographic data, in the form of Digital Elevation Models (DEMs). The quality of the DEMs depends on the accuracy, density, and spatial distribution of the sampled points; on the characteristics of the surface; and on the gridding method used to obtain them. Therefore, the choice of the DEMs interpolation method affects the realistic representation of the channel and fan morphology, and thus reasonably the debris flow routing modeling outcomes. In this paper, we initially investigate the performance of common interpolation methods (i.e. linear triangulation, natural neighbour, nearest neighbour, inverse distance to a power, ANUDEM, Radial Basis Functions, and ordinary kriging) in building DEMs with the complex topography of a debris flow channel located in the Venetian Dolomites (North-eastern Italian Alps), by using small footprint full-waveform Light Detection And Ranging (LiDAR) data. The investigation is carried out through a combination among statistical analysis of vertical accuracy, algorithm robustness, and spatial clustering of vertical errors, and multi-criteria shape reliability assessment. After that, we examine the influence of the tested interpolation algorithms on the performance of a Geographic Information System (GIS)-based cell model for simulating stony debris flows. In detail we investigate both the correlation between the DEMs heights uncertainty resulting from the gridding procedure and that on the corresponding simulated erosion/deposition depths, both the effect of interpolation algorithms on simulated areas, erosion and deposition volumes, solid-liquid discharges, and channel morphology after the event. The comparison among the tested interpolation methods highlights that the ANUDEM and ordinary kriging algorithms are inadequate in building DEMs with complex topography. Conversely, the linear triangulation, the natural neighbour algorithm, and the thin-plate spline plus tension and completely regularized spline functions ensure the best trade-off among accuracy and shape reliability. Anyway, the evaluation of the effects of gridding techniques on debris flow routing modeling reveals that the choice of the interpolation algorithm does not significantly affect the model outcomes.
Highlights
Taking up the definition proposed by Iverson (2005), “debris flows can be defined as turbulent flowing mixtures of sediment and liquid in nearly equal proportions”
To evaluate the influence of the gridding methods on debris flows routing modeling, we initially explored the relationship between the uncertainties on digital elevation and on the model results
In this study we compared the performance of twelve gridding algorithms in building DEMs with the complex topography of a debris flow channel located in the Venetian Dolomites
Summary
Taking up the definition proposed by Iverson (2005), “debris flows can be defined as turbulent flowing mixtures of sediment and liquid in nearly equal proportions”. Debris flows are found in a wide variety of mountainous environments worldwide (Berti et al, 1999), and in particular in the Dolomites area (Northeastern Italian Alps) they mainly initiate by mobilization of the channel-bed material due to surface runoff (Berti et al, 1999; Berti and Simoni, 2005; Gregoretti and Dalla Fontana, 2008; Theule et al, 2012; Tiranti and Deangeli, 2015). Hazard mapping consists in identifying the areas that are threatened either historically or potentially by debris flows. Since the topography is the major control over fluxes of water and sediments (Moore and Grayson, 1991; Hancock, 2006; Saksena and Merwade, 2015), the topographic data usually in the form of DEMs represent the most important input in debris flows routing models (e.g., Rickenmann et al, 2006; Sodnik et al, 2012)
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