Fitting hydrological models on multiple responses using the multiobjective evolutionary annealing simplex approach

Efstratiadis, A; Koutsoyiannis, D

dc.contributor.author	Efstratiadis, A	en
dc.contributor.author	Koutsoyiannis, D	en
dc.date.accessioned	2014-03-01T02:54:10Z
dc.date.available	2014-03-01T02:54:10Z
dc.date.issued	2008	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36681
dc.title	Fitting hydrological models on multiple responses using the multiobjective evolutionary annealing simplex approach	en
heal.type	conferenceItem	en
heal.publicationDate	2008	en
heal.abstract	Most complex hydrological modelling schemes, when calibrated on a single observed response (e.g. river flow at a point), provide poor predictive capability, due to the fact that the rest of variables of basin response remain practically uncontrolled. Current advances in modelling point out that it is essential to take into account multiple fitting criteria, which correspond to different observed responses or to different aspects of the same response. This can be achieved through multiobjective calibration tools, thus providing a set of solutions rather than a single global optimum. Besides, actual multiobjective optimization methods are rather inefficient, when real-world problems with many criteria and many control variables are involved. In hydrological applications there are some additional issues, due to uncertainties related to the representation of complex processes and the observation errors. The multiobjective evolutionary annealing-simplex (MEAS) method implements an innovative scheme, particularly developed for the optimization of such problems. Its features and capabilities are illustrated by solving a challenging parameter estimation problem, dealing with hydrological modelling and water resources management in a karstic basin in Greece.	en