Open AccessEstimation of flow accumulation uncertainty by Monte Carlo stochastic simulations
Author(s) -
Nenad Visnjevac,
Zeljko Cvijetinovic,
Branislav Bajat,
Boris Radić,
Ratko Ristić,
Vukašin Milčanović
Publication year - 2013
Publication title -
glasnik šumarskog fakulteta - univerzitet u beogradu/glasnik šumarskog fakulteta
Language(s) - English
Resource type - Journals
eISSN - 2217-8600
pISSN - 0353-4537
DOI - 10.2298/gsf1308007v
Subject(s) - monte carlo method , variogram , uncertainty analysis , flow (mathematics) , computer science , stochastic process , stochastic modelling , process (computing) , mathematical optimization , mathematics , statistical physics , econometrics , algorithm , statistics , kriging , simulation , physics , geometry , operating system
Very often, outputs provided by GIS functions and analysis are assumed as exact results. However, they are influenced by certain uncertainty which may affect the decisions based on those results. It is very complex and almost impossible to calculate that uncertainty using classical mathematical models because of very complex algorithms that are used in GIS analyses. In this paper we discuss an alternative method, i.e. the use of stochastic Monte Carlo simulations to estimate the uncertainty of flow accumulation. The case study area included the broader area of the Municipality of Čačak, where Monte Carlo stochastic simulations were applied in order to create one hundred possible outputs of flow accumulation. A statistical analysis was performed on the basis of these versions, and the "most likely" version of flow accumulation in association with its confidence bounds (standard deviation) was created. Further, this paper describes the most important phases in the process of estimating uncertainty, such as variogram modelling and chooses the right number of simulations. Finally, it makes suggestions on how to effectively use and discuss the results and their practical significance