Optimal groundwater remediation under uncertainty using multi-objective optimization

Mantoglou, A; Kourakos, G

dc.contributor.author	Mantoglou, A	en
dc.contributor.author	Kourakos, G	en
dc.date.accessioned	2014-03-01T01:26:49Z
dc.date.available	2014-03-01T01:26:49Z
dc.date.issued	2007	en
dc.identifier.issn	0920-4741	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/18240
dc.subject	Critical realizations	en
dc.subject	MonteCarlo simulation	en
dc.subject	Multi-objective optimization	en
dc.subject	Qroundwater remediation	en
dc.subject	Uncertain hydraulic conductivity	en
dc.subject.classification	Engineering, Civil	en
dc.subject.classification	Water Resources	en
dc.subject.other	Aquifers	en
dc.subject.other	Computer simulation	en
dc.subject.other	Genetic algorithms	en
dc.subject.other	Hydraulic conductivity	en
dc.subject.other	Monte Carlo methods	en
dc.subject.other	Multiobjective optimization	en
dc.subject.other	Random variables	en
dc.subject.other	Recharging (underground waters)	en
dc.subject.other	Uncertainty analysis	en
dc.subject.other	Critical realizations	en
dc.subject.other	Pareto front	en
dc.subject.other	Penalty function	en
dc.subject.other	Remediation	en
dc.subject.other	Aquifers	en
dc.subject.other	Computer simulation	en
dc.subject.other	Genetic algorithms	en
dc.subject.other	Hydraulic conductivity	en
dc.subject.other	Monte Carlo methods	en
dc.subject.other	Multiobjective optimization	en
dc.subject.other	Random variables	en
dc.subject.other	Recharging (underground waters)	en
dc.subject.other	Remediation	en
dc.subject.other	Uncertainty analysis	en
dc.subject.other	aquifer pollution	en
dc.subject.other	genetic algorithm	en
dc.subject.other	groundwater	en
dc.subject.other	hydraulic conductivity	en
dc.subject.other	Monte Carlo analysis	en
dc.subject.other	optimization	en
dc.subject.other	probability	en
dc.subject.other	pumping	en
dc.subject.other	recharge	en
dc.subject.other	remediation	en
dc.subject.other	simulation	en
dc.title	Optimal groundwater remediation under uncertainty using multi-objective optimization	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/s11269-006-9109-0	en
heal.identifier.secondary	http://dx.doi.org/10.1007/s11269-006-9109-0	en
heal.language	English	en
heal.publicationDate	2007	en
heal.abstract	A methodology is developed for optimal remediation of groundwater aquifers under hydraulic conductivity uncertainty. A multi-objective management method based on a pump-and-treat remediation technology, is proposed. The pumping rates and well locations are the decision variables and two objectives are chosen: minimization of contaminated groundwater in the aquifer and minimization of remediation cost. A Monte Carlo simulation method is used to cope with hydraulic conductivity uncertainty. A number of equally probable realizations of hydraulic conductivity are created and a Pareto front is obtained using a modified multi-objective Genetic Algorithm. A penalty function is utilized to maintain the algebraic sum of pumping and recharging rates equal to zero. Since Monte Carlo simulations are CPU time consuming, a method is proposed to identify the few significant realizations which have an effect on the optimal solution (critical realizations). A Pareto front with an assigned probability is derived, so that the decision maker can make decisions with specified reliability. In a case study with 100 realizations, only 11 realizations were found critical and need be considered. The remaining 89 realizations consistently obtain low ranks for all designs considered and do not affect decisions at 95% reliability level. Thus these realizations need not be considered which implies a 89% savings in computer time. The designs obtained using the critical realizations, retain a similar reliability for new realizations not considered in the design process. © Springer Science+Business Media, Inc. 2006.	en
heal.publisher	SPRINGER	en
heal.journalName	Water Resources Management	en
dc.identifier.doi	10.1007/s11269-006-9109-0	en
dc.identifier.isi	ISI:000245980100007	en
dc.identifier.volume	21	en
dc.identifier.issue	5	en
dc.identifier.spage	835	en
dc.identifier.epage	847	en