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Application of first-order and Monte Carlo analysis in watershed water quality models

Bobba, A. G.; Singh, V. P. and Bengtsson, Lars LU (1996) In Water Resources Management 10(3). p.219-240
Abstract
Functional analysis and Monte Carlo simulation were used to quantify uncertainties in model simulation of pollution behaviour and effects. The first-order part of the functional analysis method provides a measure of uncertainties in dependent variables in terms of uncertainties in independent variables. The procedure is based on first-order terms in the Taylor series expansion of the dependent variable about its mean value with respect to one or more independent variables. The major assumption is that all independent and dependent variables are the second moment variables (SMV), which means that the behaviour of any SMV is completely described by its mean and standard deviation. The mathematical simplicity of the procedure allows... (More)
Functional analysis and Monte Carlo simulation were used to quantify uncertainties in model simulation of pollution behaviour and effects. The first-order part of the functional analysis method provides a measure of uncertainties in dependent variables in terms of uncertainties in independent variables. The procedure is based on first-order terms in the Taylor series expansion of the dependent variable about its mean value with respect to one or more independent variables. The major assumption is that all independent and dependent variables are the second moment variables (SMV), which means that the behaviour of any SMV is completely described by its mean and standard deviation. The mathematical simplicity of the procedure allows application by simple input-output models. Consequently, it has been applied to many environmental simulators, e.g. hydrological models, stream water quality models, lake water quality models and ground water pollution models. The Monte Carlo simulation method uses a large number of repeated trials or simulations with the values for stochastic inputs or uncertain variables selected at random from their assumed parent probability distributions to establish an expected range of model uncertainty. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Water Resources Management
volume
10
issue
3
pages
219 - 240
publisher
Springer
external identifiers
  • Scopus:0030158836
ISSN
0920-4741
DOI
10.1007/BF00424204
language
English
LU publication?
yes
id
6f1567d5-7daf-463a-9678-313339615c5f (old id 2595342)
date added to LUP
2012-05-31 16:53:34
date last changed
2017-01-01 07:51:01
@article{6f1567d5-7daf-463a-9678-313339615c5f,
  abstract     = {Functional analysis and Monte Carlo simulation were used to quantify uncertainties in model simulation of pollution behaviour and effects. The first-order part of the functional analysis method provides a measure of uncertainties in dependent variables in terms of uncertainties in independent variables. The procedure is based on first-order terms in the Taylor series expansion of the dependent variable about its mean value with respect to one or more independent variables. The major assumption is that all independent and dependent variables are the second moment variables (SMV), which means that the behaviour of any SMV is completely described by its mean and standard deviation. The mathematical simplicity of the procedure allows application by simple input-output models. Consequently, it has been applied to many environmental simulators, e.g. hydrological models, stream water quality models, lake water quality models and ground water pollution models. The Monte Carlo simulation method uses a large number of repeated trials or simulations with the values for stochastic inputs or uncertain variables selected at random from their assumed parent probability distributions to establish an expected range of model uncertainty.},
  author       = {Bobba, A. G. and Singh, V. P. and Bengtsson, Lars},
  issn         = {0920-4741},
  language     = {eng},
  number       = {3},
  pages        = {219--240},
  publisher    = {Springer},
  series       = {Water Resources Management},
  title        = {Application of first-order and Monte Carlo analysis in watershed water quality models},
  url          = {http://dx.doi.org/10.1007/BF00424204},
  volume       = {10},
  year         = {1996},
}