HESS Opinions ""A random walk on water""

Koutsoyiannis, D

dc.contributor.author	Koutsoyiannis, D	en
dc.date.accessioned	2014-03-01T01:33:35Z
dc.date.available	2014-03-01T01:33:35Z
dc.date.issued	2010	en
dc.identifier.issn	1027-5606	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20474
dc.subject	Initial Condition	en
dc.subject	Natural Phenomena	en
dc.subject	Stochastic Representation	en
dc.subject.classification	Geosciences, Multidisciplinary	en
dc.subject.classification	Water Resources	en
dc.subject.other	hydrology	en
dc.subject.other	mathematical theory	en
dc.subject.other	numerical method	en
dc.subject.other	stochasticity	en
dc.subject.other	theoretical study	en
dc.subject.other	uncertainty analysis	en
dc.title	HESS Opinions ""A random walk on water""	en
heal.type	journalArticle	en
heal.identifier.primary	10.5194/hess-14-585-2010	en
heal.identifier.secondary	http://dx.doi.org/10.5194/hess-14-585-2010	en
heal.language	English	en
heal.publicationDate	2010	en
heal.abstract	According to the traditional notion of randomness and uncertainty, natural phenomena are separated into two mutually exclusive components, random (or stochastic) and deterministic. Within this dichotomous logic, the deterministic part supposedly represents cause-effect relationships and, thus, is physics and science (the ""good""), whereas randomness has little relationship with science and no relationship with understanding (the ""evil""). Here I argue that such views should be reconsidered by admitting that uncertainty is an intrinsic property of nature, that causality implies dependence of natural processes in time, thus suggesting predictability, but even the tiniest uncertainty (e.g. in initial conditions) may result in unpredictability after a certain time horizon. On these premises it is possible to shape a consistent stochastic representation of natural processes, in which predictability (suggested by deterministic laws) and unpredictability (randomness) coexist and are not separable or additive components. Deciding which of the two dominates is simply a matter of specifying the time horizon and scale of the prediction. Long horizons of prediction are inevitably associated with high uncertainty, whose quantification relies on the long-term stochastic properties of the processes.	en
heal.publisher	COPERNICUS GESELLSCHAFT MBH	en
heal.journalName	Hydrology and Earth System Sciences	en
dc.identifier.doi	10.5194/hess-14-585-2010	en
dc.identifier.isi	ISI:000276178100015	en
dc.identifier.volume	14	en
dc.identifier.issue	3	en
dc.identifier.spage	585	en
dc.identifier.epage	601	en