Quantifying location error to define uncertainty in volcanic mass flow hazard simulations

نویسندگان

چکیده

Abstract. The use of mass flow simulations in volcanic hazard zonation and mapping is often limited by model complexity (i.e. uncertainty correct values parameters), a lack quantification, approaches to incorporate this into maps. When quantified, simulation errors are typically evaluated on pixel-pair basis, using the difference between simulated observed (“actual”) map-cell evaluate performance model. However, these comparisons conflate location quantification errors, neglecting possible spatial autocorrelation errors. As result, assessments yield moderate accuracy values. In paper, similarly were found assessment three depth-averaged numerical models 2012 debris avalanche from Upper Te Maari crater, Tongariro Volcano, as benchmark. To provide fairer covariance we fuzzy set approach indicate proximity valued map cells. This “fuzzification” results yields improvements targeted metrics relative length scale parameter at expense decreases opposing (e.g. fewer false negatives result more positives) reduction resolution. generate zones incorporating identified associated trade-offs demonstrated indicates potential for informed stakeholders reducing estimation supporting decision-making data.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Quantifying geocode location error using GIS methods

BACKGROUND The Metropolitan Atlanta Congenital Defects Program (MACDP) collects maternal address information at the time of delivery for infants and fetuses with birth defects. These addresses have been geocoded by two independent agencies: (1) the Georgia Division of Public Health Office of Health Information and Policy (OHIP) and (2) a commercial vendor. Geographic information system (GIS) me...

متن کامل

Quantifying uncertainty and sampling quality in biomolecular simulations.

Growing computing capacity and algorithmic advances have facilitated the study of increasingly large biomolecular systems at longer timescales. However, with these larger, more complex systems come questions about the quality of sampling and statistical convergence. What size systems can be sampled fully? If a system is not fully sampled, can certain "fast variables" be considered well-converge...

متن کامل

Fluid flow dynamics under location uncertainty

We present a derivation of a stochastic model of Navier Stokes equations that relies on a decomposition of the velocity fields into a differentiable drift component and a time uncorrelated uncertainty random term. This type of decomposition is reminiscent in spirit to the classical Reynolds decomposition. However, the random velocity fluctuations considered here are not differentiable with resp...

متن کامل

Quantifying uncertainty on Pareto fronts with Gaussian process conditional simulations

Multi-objective optimization algorithms aim at finding Pareto-optimal solutions. Recovering Pareto fronts or Pareto sets from a limited number of function evaluations are challenging problems. A popular approach in the case of expensive-to-evaluate functions is to appeal to metamodels. Kriging has been shown efficient as a base for sequential multi-objective optimization, notably through infill...

متن کامل

Caldera rim collapse: A hidden volcanic hazard

Following the emblematic fl ank collapse of Mount St Helens in 1981, numerous models of flank sliding have been proposed. These models have allowed to largely improve the understanding of mechanisms involved in such landslides, which represent a tremendous risk for populations living around volcanoes. In this article, a new mode of landslide formation, related to buried calderas, is described. ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Natural Hazards and Earth System Sciences

سال: 2021

ISSN: ['1561-8633', '1684-9981']

DOI: https://doi.org/10.5194/nhess-21-2447-2021