On optimal model complexity in inverse modeling of heterogeneous aquifers

Mantoglou, A

dc.contributor.author	Mantoglou, A	en
dc.date.accessioned	2014-03-01T01:22:51Z
dc.date.available	2014-03-01T01:22:51Z
dc.date.issued	2005	en
dc.identifier.issn	0022-1686	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/16686
dc.subject	Groundwater simulations	en
dc.subject	Heterogeneous aquifers	en
dc.subject	Inverse groundwater modeling	en
dc.subject	Parameter estimation	en
dc.subject	Random fields	en
dc.subject	Stochastic groundwater modeling	en
dc.subject.classification	Engineering, Civil	en
dc.subject.classification	Water Resources	en
dc.subject.other	Computer simulation	en
dc.subject.other	Correlation methods	en
dc.subject.other	Groundwater flow	en
dc.subject.other	Mathematical models	en
dc.subject.other	Optimization	en
dc.subject.other	Parameter estimation	en
dc.subject.other	Random processes	en
dc.subject.other	Groundwater simulations	en
dc.subject.other	Heterogeneous aquifers	en
dc.subject.other	Inverse groundwater modeling	en
dc.subject.other	Random fields	en
dc.subject.other	Stochastic groundwater modeling	en
dc.subject.other	Aquifers	en
dc.subject.other	flow modeling	en
dc.subject.other	groundwater	en
dc.subject.other	stochastic method	en
dc.subject.other	flow modeling	en
dc.subject.other	groundwater flow	en
dc.subject.other	stochasticity	en
dc.title	On optimal model complexity in inverse modeling of heterogeneous aquifers	en
heal.type	journalArticle	en
heal.identifier.primary	10.1080/00221680509500156	en
heal.identifier.secondary	http://dx.doi.org/10.1080/00221680509500156	en
heal.language	English	en
heal.publicationDate	2005	en
heal.abstract	This paper investigates the prediction ability of models of various complexities and the optimal model structure depending on the real system complexity and the quality of measurements. A simulation approach is used where the underlying transmissivity map is assumed a member of a random field and realizations of transmissivity maps are generated using stochastic simulation. For each simulation run, several models with different structures and complexities, based on zonation parameterization, are calibrated and the model transmissivities are estimated using measurements of head data. Then, using the calibrated models, the heads and the flow terms are evaluated in the numerical cells of the aquifer. The corresponding prediction the heads and flow terms are calculated and the optimal models having the lowest prediction errors are determined. The method is applied study of a two-dimensional aquifer with steady groundwater flow with pumpage. For small correlation lengths of transmissivity variability, the numerical results indicate that a simple singlezone model yields the best predictions and outperforms complex models with more parameters. For larger correlation lengths however, models of medium complexity have best prediction characteristics and should be preferred. It is further shown quantitatively that as the quality of measurements decreases the number of parameters and the complexity of the optimal model decreases. The reduced flexibility of a model with fewer parameters protects it from being adversely affected from the errors contained in the measurements. © 2005 International Association of Hydraulic Engineering and Research.	en
heal.publisher	INT ASSN HYDRAULIC RESEARCH	en
heal.journalName	Journal of Hydraulic Research	en
dc.identifier.doi	10.1080/00221680509500156	en
dc.identifier.isi	ISI:000234808500014	en
dc.identifier.volume	43	en
dc.identifier.issue	5	en
dc.identifier.spage	574	en
dc.identifier.epage	583	en