Debris flows and debris avalanches are rapid to extremely rapid landslides that tend to travel considerable distances from their source areas. One of the critical challenges to overcome with respect to debris flow risk is, therefore, the credible prediction of their size, travel path, runout distance, and depths of erosion and deposition. In this study, a quantitative modelling approach based on cellular automata methods, wherein individual cells move across a digital elevation model (DEM) landscape following behavioral rules defined probabilistically, is proposed and tested. The adopted model is able to estimate erosion and deposition soil volumes along a debris flow path by deploying at the source areas autonomous subroutines, called agents, over a 5 m spatial resolution DEM, which provides the basic information to each agent in each time-step.
" }
{
"headline": "A probabilistic model for assessing debris flow propagation at regional scale: a case study in Campania region, Italy",
"subhead": "April 20, 2021",
"breadcrumbs": [
{
"url": "\/en\/ideas.html",
"text": "Ideas"
}
]
}
{
"pdf": "\/content\/dam\/stantec\/files\/PDFAssets\/technical\/001\/egu\u002Dgeneral\u002Dassembly\u002Dprobabalistic\u002Dmodel\u002Ditaly\u002D2021.pdf",
"pdfJs": "/static/scripts/pdf.js",
"pdfViewer": "/static/scripts/pdf_viewer.js",
"worker": "/static/scripts/pdf.worker.js",
"gatedContentId": "gated\u002Dcontent\u002D378d1c84\u002Dc470\u002D4ce9\u002Da093\u002Dcd87bb4ae145",
"gatedContentType": "",
"gatedContentTitle": " ",
"gatedContentDesc": "",
"subscribeCTALabel": "",
"marketoList": "Select List",
"paginationStyle": "pdf\u002Dviewer__viewbox\u002D2",
"frontCover": true,
"backCover": true,
"authorMode": false,
"labels": {
"downloadPdf": "Download PDF",
"viewFullscreen": "View in Full Screen",
"previous": "Previous",
"next": "Next",
"skip": "Skip this",
"subscribe": "Subscribe",
"hardGatedSubscribe": "Subscribe to Continue",
"cancel": "Cancel",
"email": "Email",
"firstName": "First Name",
"lastName": "Last Name",
"company": "Company",
"optIn": "Check to receive this content and marketing emails from Stantec. You can unsubscribe at any time.",
"successTitle": "Thank you for subscribing",
"successDescription": "You have been added to our list.",
"continue": "Continue",
"failTitle": "There was an error submitting your form.",
"failDescription": "Please try again later.",
"tryAgain": "Try Again"
}
}
By registering, you confirm that you agree with Stantec's Privacy Policy for managing your personal data.
{
"description": "",
"ideasArticleShareLabel": "Share",
"projectShareLabel": "Share",
"networks": [
"linkedin",
"twitter",
"email"
]
}
{
"byLabel": "By",
"andLabel": "and",
"authors": [
{
"personFirstName": "Richard",
"personLastName": "Guthrie",
"url": "\/en\/people\/g\/guthrie\u002Drichard.html"
}
]
}
{
"text": "Dr. Richard Guthrie and associates present a quantitative modelling approach based on cellular automata methods at the EGU 2021 General Assembly"
}
{
"text": "
{
"description": "",
"ideasArticleShareLabel": "Share",
"projectShareLabel": "Share",
"networks": [
"linkedin",
"twitter",
"email"
]
}
{
"headline": "A probabilistic model for assessing debris flow propagation at regional scale: a case study in Campania region, Italy",
"contactLabel": "Contact",
"authors": [
{
"promotionalImage": "\/content\/dam\/stantec\/images\/people\/g\/richard\u002Dguthrie\u002Dheadshot.jpg",
"personFirstName": "Richard",
"personLastName": "Guthrie",
"mappedPromoText": "Backed by 30 years of geotechnical experience, Richard leads a group of specialists who provide practical, science-based solutions to reduce the impacts of geohazards on communities, infrastructure, lives, and the environment.",
"contactEmail": "rick.guthrie@stantec.com"
}
]
}
{ "ariaLabel": "Back To Top", "topElementClass": "cq-article-header",
"bottomElementClass": "bottom-threshold" }