Algebraic sensitivity analysis of environmental models

被引:39
作者
Norton, J. P. [1 ,2 ]
机构
[1] Australian Natl Univ, Fenner Sch Environm & Soc, Canberra, ACT 0200, Australia
[2] Australian Natl Univ, Inst Math Sci, Canberra, ACT 0200, Australia
基金
澳大利亚研究理事会;
关键词
sensitivity analysis; simulation; environmental models;
D O I
10.1016/j.envsoft.2007.11.007
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The paper aims to demonstrate the relative ease of algebraic sensitivity analysis in many cases and to discuss its advantages and limitations in situations typical of environmental models. Sensitivity results for the operations in an equation can be combined to find algebraically the sensitivities of its output to variations in contributing factors. Algebraic sensitivity analysis has the advantage that it yields insight not readily available from numerical experiments alone. It exploits the fact that a simulation model is fully known and not a black box. By producing relations valid for changes of any size, it can save much computational experiment. The paper gives sensitivity results for common operations on one or more arguments (parameters and/or input variables). A second-order approximation is also given for each. An illustrative example of algebraic sensitivity analysis in a model of pathogen generation and transport in a catchment is presented. Two formulae useful in first- or second-order approximations to normalized sensitivity relations are presented: a Taylor expansion relating the proportional change in effect on a scalar variable to the proportional changes in a number of causal factors and a chain rule for propagating normalized sensitivities through a series of submodels. (c) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:963 / 972
页数:10
相关论文
共 22 条
[1]   STATISTICAL SENSITIVITY ANALYSIS OF MODELS FOR CHEMICAL-KINETICS [J].
ATHERTON, RW ;
SCHAINKER, RB ;
DUCOT, ER .
AICHE JOURNAL, 1975, 21 (03) :441-448
[2]   An effective screening design for sensitivity analysis of large models [J].
Campolongo, Francesca ;
Cariboni, Jessica ;
Saltelli, Andrea .
ENVIRONMENTAL MODELLING & SOFTWARE, 2007, 22 (10) :1509-1518
[3]   STUDY OF SENSITIVITY OF COUPLED REACTION SYSTEMS TO UNCERTAINTIES IN RATE COEFFICIENTS .1. THEORY [J].
CUKIER, RI ;
FORTUIN, CM ;
SHULER, KE ;
PETSCHEK, AG ;
SCHAIBLY, JH .
JOURNAL OF CHEMICAL PHYSICS, 1973, 59 (08) :3873-3878
[4]  
Ferguson CM, 2007, J WATER HEALTH, V5, P187, DOI [10.2166/wh.2007.013b, 10.2166/wh.2007.013]
[5]  
Frank P. M., 1978, INTRO SYSTEM SENSITI
[6]   UNCERTAINTY AND SENSITIVITY ANALYSIS TECHNIQUES FOR USE IN PERFORMANCE ASSESSMENT FOR RADIOACTIVE-WASTE DISPOSAL [J].
HELTON, JC .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 1993, 42 (2-3) :327-367
[7]   Adaptive approach for nonlinear sensitivity analysis of reaction kinetics [J].
Horenko, I ;
Lorenz, S ;
Schütte, C ;
Huisinga, W .
JOURNAL OF COMPUTATIONAL CHEMISTRY, 2005, 26 (09) :941-948
[8]   MODELING THE EFFECTS OF ACID DEPOSITION - UNCERTAINTY AND SPATIAL VARIABILITY IN ESTIMATION OF LONG-TERM SULFATE DYNAMICS IN A REGION [J].
HORNBERGER, GM ;
COSBY, BJ ;
GALLOWAY, JN .
WATER RESOURCES RESEARCH, 1986, 22 (08) :1293-1302
[9]  
HORNBERGER GM, 1981, J ENVIRON MANAGE, V12, P7
[10]   Distance-based and stochastic uncertainty analysis for multi-criteria decision analysis in Excel using Visual Basic for Applications [J].
Hyde, K. M. ;
Maier, H. R. .
ENVIRONMENTAL MODELLING & SOFTWARE, 2006, 21 (12) :1695-1710