American Society of Civil Engineers


Spectral Sampling Method for Uncertainty Propagation in Long-Wave Runup Modeling


by Liang Ge, (Coastal/Ocean Engineer, Oceanit Inc., Honolulu, HI 96813; formerly, Graduate Research Assistant, Dept. of Ocean and Resources Engineering, Univ. of Hawaii, Honolulu, HI 96822.) and Kwok Fai Cheung, (corresponding author), (Professor, Dept. of Ocean and Resources Engineering, Univ. of Hawaii, Honolulu, HI 96822 E-mail: cheung@hawaii.edu)

Journal of Hydraulic Engineering, Vol. 137, No. 3, March 2011, pp. 277-288, (doi:  http://dx.doi.org/10.1061/(ASCE)HY.1943-7900.0000301)

     Access full text
     Purchase Subscription
     Permissions for Reuse  

Document type: Journal Paper
Abstract: This paper presents a stochastic approach to model input uncertainty with a general statistical distribution and its propagation through the nonlinear long-wave equations. A Godunov-type scheme mimics breaking waves as bores for accurate description of the energy dissipation in the runup process. The polynomial chaos method expands the flow parameters into series of orthogonal modes, which contain the statistical properties in stochastic space. A spectral projection technique determines the orthogonal modes from ensemble averages of systematically sampled events through the long-wave model. This spectral sampling method generates an output statistical distribution using a much smaller sample of events comparing to the Monte Carlo method. Numerical examples of long-wave transformation over a plane beach and a conical island demonstrate the efficacy of the present approach in describing uncertainty propagation through nonlinear and discontinuous processes for flood-hazard mapping.


ASCE Subject Headings:
Floods
Long waves
Monte Carlo method
Shallow water
Stochastic models
Polynomials
Sampling

Author Keywords:
Floods
Long waves
Monte Carlo method
Polynomials
Shallow water
Stochastic models