Calibration of subsurface batch and reactive-transport models involving complex biogeochemical processes

In this study, the calibration of subsurface batch and reactive-transport models involving complex biogeochemical processes was systematically evaluated. Two hypothetical nitrate biodegradation scenarios were developed and simulated in numerical experiments to evaluate the performance of three calib...

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Vydané v:	Advances in water resources Ročník 31; číslo 2; s. 269 - 286
Hlavní autori:	Matott, L.S, Rabideau, A.J
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Oxford Elsevier Science 01.02.2008
Predmet:	algorithms aquifers biodegradation biogeochemistry calibration chemical reactions Earth sciences Earth, ocean, space Exact sciences and technology groundwater groundwater flow Hydrogeology hydrologic models Hydrology. Hydrogeology ions mathematical models minerals organic compounds reactive transport simulation models subsurface batch and reactive transport modeling experimental studies algorithms models Parameter estimation Multi- start nonlinear regression biodegradation transport Reactive transport nitrates subsurface Particle swarm optimization water resources optimization regression Subsurface modeling Biogeochemical processes particles calibration uncertainties performances
ISSN:	0309-1708, 1872-9657
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Shrnutí:	In this study, the calibration of subsurface batch and reactive-transport models involving complex biogeochemical processes was systematically evaluated. Two hypothetical nitrate biodegradation scenarios were developed and simulated in numerical experiments to evaluate the performance of three calibration search procedures: a multi-start non-linear regression algorithm (i.e. multi-start Levenberg-Marquardt), a global search heuristic (i.e. particle swarm optimization), and a hybrid algorithm that combines the particle swarm procedure with a regression-based ''polishing'' step. Graphical analysis of the selected calibration problems revealed heterogeneous regions of extreme parameter sensitivity and insensitivity along with abundant numbers of local minima. These characteristics hindered the performance of the multi-start non-linear regression technique, which was generally the least effective of the considered algorithms. In most cases, the global search and hybrid methods were capable of producing improved model fits at comparable computational expense. In other cases, the multi-start and hybrid calibration algorithms yielded comparable fitness values but markedly differing parameter estimates and associated uncertainty measures.
Bibliografia:	http://dx.doi.org/10.1016/j.advwatres.2007.08.005 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	0309-1708 1872-9657
DOI:	10.1016/j.advwatres.2007.08.005