Perceived risks of mountain landslides in Italy: stated choices for subjective risk reductions

Thiene, Mara; Shaw, W. Douglass; Scarpa, Raffaele

doi:10.1007/s10346-016-0741-3

Cited by 25 publications

(16 citation statements)

References 39 publications

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“…The results of this study also show that risk perception has a direct impact on WBDI and that possibility perception and fear perception are both positively correlated with WBDI. Individuals' lack of understanding of geological disaster knowledge is one of the reasons for the irrational risk perception and the passive acceptance of disaster losses (Thiene, Shaw, & Scarpa, ). Mastering knowledge of disasters will help form an objective level of perception and subjective judgment.…”

Section: Discussionmentioning

confidence: 99%

Understanding sustainable disaster mitigation of stakeholder engagement: Risk perception, trust in public institutions, and disaster insurance

Tan

Lin

et al. 2019

Sustainable Development

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Many rural settlements in China's western mountainous regions are affected by mountain disasters, such as landslides and mudslides. For residents living in landslide‐prone areas, behaviors related to disaster risk mitigation (such as purchasing disaster insurance) are inevitably affected by disaster risk perception. Due to the substantial differences in disaster occurrence patterns, landslide‐related insurance research is relatively rare compared with insurance research focused on other types of natural disasters (e.g., floods and droughts). Based on the results of questionnaires administered in landslide‐prone areas in Chongqing, China, this paper uses partial least squares structural equation modeling (PLS‐SEM) to investigate the relationships among the questionnaire respondents' risk perception, trust in public institutions (TPI), and willingness to buy disaster insurance (WBDI). The results reveal that risk perception and TPI directly affect WBDI. Here, competence, participation, possibility perception, and fear perception are significantly positively correlated to WBDI, whereby fear perception has the largest impact, followed by possibility perception, competence, and participation. In addition, TPI indirectly affects WBDI through risk perception. Here, competence reduces fear perception and indirectly reduces WBDI. The implications of these results for theory are discussed. This study introduces a new method to support disaster risk mitigation‐related decision making that can be useful to governments and individuals.

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Section: Discussionmentioning

confidence: 99%

Understanding sustainable disaster mitigation of stakeholder engagement: Risk perception, trust in public institutions, and disaster insurance

Tan

Lin

et al. 2019

Sustainable Development

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“…Debris flows seem to have increased in occurrence in the last few years, possibly by the rise of extreme rainfall events (Easterling et al, 2000;Floris et al, 2010), and the availability of debris material provided by the retreat of the glaciers and the permafrost areas to higher elevations owing to the global climatic change. In order to reduce debris flows hazard and the related socio-economic impact (Mattea et al, 2016;Thiene et al, 2017), it is common to couple structural and non-structural measurements, such as the zoning of risk prone areas and the development of emergency plans (Ghilardi et al, 2001).…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Differences of Gridding Techniques for Digital Elevation Models Generation and Their Influence on the Modeling of Stony Debris Flows Routing: A Case Study From Rovina di Cancia Basin (North-Eastern Italian Alps)

2018

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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, usually in the form of Digital Elevation Models (DEMs). The quality of DEMs depends on the accuracy, density, and spatial distribution of the sampled points; on the characteristics of the surface; and on the applied gridding methodology. Therefore, the choice of the interpolation method affects the realistic representation of the channel and fan morphology, and thus potentially the debris flow routing modeling outcomes. In this paper, we initially investigate the performance of common interpolation methods (i.e., linear triangulation, natural neighbor, nearest neighbor, 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 fullwaveform Light Detection And Ranging (LiDAR) data. The investigation is carried out through a combination of 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 routing. 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 not suitable for building DEMs with complex topography. Conversely, the linear triangulation, the natural neighbor algorithm, and the thin-plate spline plus tension Boreggio et al.Interpolation Influence on Routing Modeling 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.

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“…The reliable prediction of runoff is thus of great importance for risk assessment and mitigation purposes. This is particularly relevant in the context of Italian Alps, owing to the strong socio‐economic impacts of debris flow in such area [ Mattea et al ., ; Thiene et al ., ]. In addition, the availability of a solid‐liquid hydrograph to be prescribed as input to numerical models is a crucial step for simulating correctly the downstream routing of debris flows [ Rickenmann et al ., ; Medina et al ., ; Armanini et al ., ; Pudasaini , ; Gregoretti et al ., ].…”

Section: Introductionmentioning

confidence: 99%

Runoff of small rocky headwater catchments: Field observations and hydrological modeling

et al. 2016

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In dolomitic headwater catchments, intense rainstorms of short duration produce runoff discharges that often trigger debris flows on the scree slopes at the base of rock cliffs. In order to measure these discharges, we placed a measuring facility at the outlet (elevation 1770 m a.s.l.) of a small, rocky headwater catchment (area ∼0.032 km2, average slope ∼320%) located in the Venetian Dolomites (North Eastern Italian Alps). The facility consists of an approximately rectangular basin, ending with a sharp‐crested weir. Six runoff events were recorded in the period 2011–2014, providing a unique opportunity for characterizing the hydrological response of the catchment. The measured hydrographs display impulsive shapes, with an abrupt raise up to the peak, followed by a rapidly decreasing tail, until a nearly constant plateau is eventually reached. This behavior can be simulated by means of a distributed hydrological model if the excess rainfall is determined accurately. We show that using the Soil Conservation Service Curve‐Number (SCS‐CN) method and assuming a constant routing velocity invariably results in an underestimated peak flow and a delayed peak time. A satisfactory prediction of the impulsive hydrograph shape, including peak value and timing, is obtained only by combining the SCS‐CN procedure with a simplified version of the Horton equation, and simulating runoff routing along the channel network through a matched diffusivity kinematic wave model. The robustness of the proposed methodology is tested through a comparison between simulated and observed timings of runoff or debris flow occurrence in two neighboring alpine basins.

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Perceived risks of mountain landslides in Italy: stated choices for subjective risk reductions

Cited by 25 publications

References 39 publications

Understanding sustainable disaster mitigation of stakeholder engagement: Risk perception, trust in public institutions, and disaster insurance

Understanding sustainable disaster mitigation of stakeholder engagement: Risk perception, trust in public institutions, and disaster insurance

Evaluating the Differences of Gridding Techniques for Digital Elevation Models Generation and Their Influence on the Modeling of Stony Debris Flows Routing: A Case Study From Rovina di Cancia Basin (North-Eastern Italian Alps)

Runoff of small rocky headwater catchments: Field observations and hydrological modeling

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