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Stochastic Simulation of Snow Cover

Authors:
Markéta Průšová
Lucie Juřikovská

Keywords: interpolation; stochastic simulation

Abstract:
The presented paper deals with a stochastic simulation of snow cover. This study aims to find the best settings of a stochastic simulation to be able to determine the parameters of the snow cover for any point of a given territory. Next, basic statistical analyses of parameters are documented, including an analysis of relationships between the snow parameters and altitude, slope and aspect. Most current methods of spatial interpolation and multifactor evaluation are based on the weighted regression relationships. That leads to smooth results and degrades our ability to properly evaluate the existence and the probability of extreme situations and their impact on the research problem. Neither alternative techniques use neural networks to bring major improvements. This research is exploring the possibility of stochastic simulation to assess the development of values, evaluating the occurrence of extreme events, monitoring the probability of exceeding the set limits, compared with application kriging errors, the use of additional qualitative information. The variants of conditional stochastic simulation were tested in particular. The application area was chosen on data of snow cover, many land-bound factors and the results are the regular mapping of forest damage. The aim is to compare and determine the best method of interpolation of snow cover, which was succeeded.

Pages: 1 to 6

Copyright: Copyright (c) IARIA, 2011

Publication date: October 23, 2011

Published in: conference

ISSN: 2308-4537

ISBN: 978-1-61208-169-4

Location: Barcelona, Spain

Dates: from October 23, 2011 to October 29, 2011