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International Journal for Uncertainty Quantification
IF: 3.259 5-Year IF: 2.547 SJR: 0.417 SNIP: 0.8 CiteScore™: 1.52

ISSN Print: 2152-5080
ISSN Online: 2152-5099

Open Access

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2019029044
pages 589-605


Arpan Mukherjee
Materials Design and Innovation Department of University at Buffalo-SUNY, Buffalo, NY
Rahul Rai
Mechanical and Aerospace Engineering Department of University at Buffalo-SUNY, Buffalo, New York, 14260, USA
Puneet Singla
Mechanical and Aerospace Engineering Department of University at Buffalo-SUNY, Buffalo, New York, 14260, USA; Aerospace Engineering Dept. of Pennsylvania State University, State College, PA
Tarunraj Singh
Mechanical and Aerospace Engineering Department of University at Buffalo-SUNY, Buffalo, New York, 14260, USA
Abani K. Patra
Mechanical and Aerospace Engineering Department of University at Buffalo-SUNY, Buffalo, New York, 14260, USA


With the recent advent of aerial photography, capturing high-resolution terrain information has provided new opportunities to simulate geophysical mass flow on high-resolution digital elevation models (DEMs). This gives a better understanding of the flow of debris that has a wide range of size. However, performing uncertainty quantification (UQ) of debris flow on an uncertain terrain profile, especially creating a hazard map, still poses a challenge. Even though there exist advanced statistical methods to model the DEM, UQ on the DEM requires the generation of a huge number of realizations that make the problem intractable. The current paper focuses on the usefulness of a recently developed UQ methodology that identifies Strongly Coupled Subsystems (SCS) in a large-scale uncertain dynamical system using suitable graph-clustering techniques. The method is used to create a parallel sampling scheme for a high-resolution DEM to enable faster UQ by integrating with traditional sampling methods, such as Monte Carlo or Latin hypercube sampling. The realizations are used to propagate the uncertainty in DEMs via a geophysical mass flow model simulated in TITAN2D. The accuracy of the UQ framework in estimating hazard maps is demonstrated by applying it to the block-and-ash flows resulting from the 1991 Colima Volcano, Mexico.


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