an integrated study to evaluate debris flow hazard in alpine environment

an integrated study to evaluate debris flow hazard in alpine environment

;Davide Tiranti;Stefano Crema;Marco Cavalli;Chiara Deangeli
ratio juris 2018 Vol. 6 pp. -
174
tiranti2018frontiersan

Abstract

Debris flows are among the most dangerous natural processes affecting the alpine environment due to their magnitude (volume of transported material) and the long runout. The presence of structures and infrastructures on alluvial fans can lead to severe problems in terms of interactions between debris flows and human activities. Risk mitigation in these areas requires identifying the magnitude, triggers, and propagation of debris flows. Here, we propose an integrated methodology to characterize these phenomena. The methodology consists of three complementary procedures. Firstly, we adopt a classification method based on the propensity of the catchment bedrocks to produce clayey-grained material. The classification allows us to identify the most likely rheology of the process. Secondly, we calculate a sediment connectivity index to estimate the topographic control on the possible coupling between the sediment source areas and the catchment channel network. This step allows for the assessment of the debris supply, which is most likely available for the channelized processes. Finally, with the data obtained in the previous steps, we modeled the propagation and depositional pattern of debris flows with a 3D code based on Cellular Automata. The results of the numerical runs allow us to identify the depositional patterns and the areas potentially involved in the flow processes. This integrated methodology is applied to a test-bed catchment located in Northwestern Alps. The results indicate that this approach can be regarded as a useful tool to estimate debris flow related potential hazard scenarios in an alpine environment in an expeditious way without possessing an exhaustive knowledge of the investigated catchment, including data on historical debris flow events.

Citation

ID: 239371
Ref Key: tiranti2018frontiersan
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
239371
Unique Identifier:
10.3389/feart.2018.00060
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet