The Impact of the Uncertain Input Data of Multi-Purpose Reservoir Volumes under Hydrological Extremes

Simple item page
dc.contributor.authorPaseka, Stanislavcs
dc.contributor.authorMarton, Danielcs
dc.coverage.issue10cs
dc.coverage.volume13cs
dc.date.accessioned2021-08-13T10:52:53Z
dc.date.available2021-08-13T10:52:53Z
dc.date.issued2021-05-16cs
dc.description.abstractThe topic of uncertainties in water management tasks is a very extensive and highly discussed one. It is generally based on the theory that uncertainties comprise epistemic uncertainty and aleatoric uncertainty. This work deals with the comprehensive determination of the functional water volumes of a reservoir during extreme hydrological events under conditions of aleatoric uncertainty described as input data uncertainties. In this case, the input data uncertainties were constructed using the Monte Carlo method and applied to the data employed in the water management solution of the reservoir: (i) average monthly water inflows, (ii) hydrographs, (iii) bathygraphic curves and (iv) water losses by evaporation and dam seepage. To determine the storage volume of the reservoir, a simulation-optimization model of the reservoir was developed, which uses the balance equation of the reservoir to determine its optimal storage volume. For the second hydrological extreme, a simulation model for the transformation of flood discharges was developed, which works on the principle of the first order of the reservoir differential equation. By linking the two models, it is possible to comprehensively determine the functional volumes of the reservoir in terms of input data uncertainties. The practical application of the models was applied to a case study of the Vír reservoir in the Czech Republic, which fulfils the purpose of water storage and flood protection. The obtained results were analyzed in detail to verify whether the reservoir is sufficiently resistant to current hydrological extremes and also to suggest a redistribution of functional volumes of the reservoir under conditions of measurement uncertainty.en
dc.formattextcs
dc.format.extent1-25cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationWater. 2021, vol. 13, issue 10, p. 1-25.en
dc.identifier.doi10.3390/w13101389cs
dc.identifier.issn2073-4441cs
dc.identifier.other171656cs
dc.identifier.urihttp://hdl.handle.net/11012/200983
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofWatercs
dc.relation.urihttps://www.mdpi.com/2073-4441/13/10/1389/htmcs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/2073-4441/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectmulti-purpose reservoiren
dc.subjectfunctional volumeen
dc.subjectuncertaintiesen
dc.subjectMonte Carlo methoden
dc.subjecthydrological extremesen
dc.subjectsimulation-optimization modelen
dc.subjectoptimal storage volumeen
dc.subjectsimulation modelen
dc.subjectretention volumeen
dc.subjecttransformation of flood dischargesen
dc.titleThe Impact of the Uncertain Input Data of Multi-Purpose Reservoir Volumes under Hydrological Extremesen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-171656en
sync.item.dbtypeVAVen
sync.item.insts2021.12.13 12:55:09en
sync.item.modts2021.12.13 12:16:23en
thesis.grantorVysoké učení technické v Brně. Fakulta stavební. Ústav vodního hospodářství krajinycs
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
water1301389v2.pdf
Size:
4.65 MB
Format:
Adobe Portable Document Format
Description:
water1301389v2.pdf
Download
Collections
Ústav vodního hospodářství krajiny