Reverse flood routing in natural channels using genetic algorithm

dc.contributor.author Zucco, Graziano
dc.contributor.author Tayfur, Gökmen
dc.contributor.author Moramarco, Tommaso
dc.coverage.doi 10.1007/s11269-015-1058-z
dc.date.accessioned 2017-07-06T12:53:33Z
dc.date.available 2017-07-06T12:53:33Z
dc.date.issued 2015
dc.description.abstract Establishing a clear overview of data discharge availability for water balance modelling in basins is a priority in Europe, and in the particular in the framework of the system of Economic and Environmental Accounts for Water (SEEAW) developed by the EU Directorate-General for the Environment. However, accurate discharge estimation at a river site depends on rating curve reliability usually defined by recording the water level at a gauged section and carrying out streamflow measurements. Local stage monitoring is fairly straightforward and relatively inexpensive compared to the cost to carry out flow velocity measurements which are, in addition, hindered by high flow. Moreover, hydraulic models may not be ideally suitable to serve the purpose of rating curve extension or its development at a river site upstream/downstream where the discharge is known due to their prohibitive requirement of channel cross-section details and roughness information at closer intervals. Likewise, rainfall-runoff transformation might be applied but its accuracy is tightly linked to detailed information in terms of geomorphological characteristics of intermediate basins as well as rainfall pattern data. On this basis, a procedure for reverse flood routing in natural channels is here proposed for three different configurations of hydrometric monitoring of a river reach where lateral flow is significant and no rainfall data are available for the intermediate basin. The first considers only the downstream channel end as a gauged site where discharge and stages are recorded. The second configuration assumes the downstream end as a gauged site but only in terms of stage. The third configuration envisages both channel ends equipped to recording stages. The channel geometry is known only at channel ends. The developed model has basically four components: (1) the inflow hydrograph is expressed by a Pearson Type-III distribution, involving parameters of peak discharge, time to peak, and a shape factor; (2) the basic continuity equation for flow routing written in the characteristic form is employed; (3) the lateral flow is related to stages at channel ends. (4) the relation between local stage and remote discharge as found by Moramarco et al. (2005b) is exploited. The parameters, coefficients and exponents of the model are obtained, for each configuration, using the genetic algorithm method. Three equipped river branches along the Tiber River in central Italy are used to validate the procedure. Analyses are carried out for three significant flood events occurred along the river and where the lateral flow was significant. Results show the good performance of the procedure for all three monitoring configurations. Specifically, the discharge hydrographs assessed at channel ends are found satisfactory both in terms of shape with a Nash-Sutcliffe ranging overall in the interval (0.755–0.972) and in the reproduction of rating curves at channel ends. Finally, by a synthetic test the performance of the developed procedure is compared to that of the hydraulic model coupled with a hydrologic model. Two river reaches are considered, the first along the Tiber River and the second one located in the Rio Grande basin which is a tributary of the Tiber River. Detailed channel geometry data are available for both the river sections. Results showed the effectiveness of the reverse flood routing to reproducing fairly well the hydrographs simulated by the hydraulic model in the three monitoring investigated configurations. en_US
dc.identifier.citation Zucco, G., Tayfur, G., and Moramarco, T. (2015). Reverse flood routing in natural channels using genetic algorithm. Water Resources Management, 29(12), 4241-4267. doi:10.1007/s11269-015-1058-z en_US
dc.identifier.doi 10.1007/s11269-015-1058-z
dc.identifier.doi 10.1007/s11269-015-1058-z en_US
dc.identifier.issn 0920-4741
dc.identifier.issn 1573-1650
dc.identifier.scopus 2-s2.0-84938964818
dc.identifier.uri https://doi.org/10.1007/s11269-015-1058-z
dc.identifier.uri https://hdl.handle.net/11147/5877
dc.language.iso en en_US
dc.publisher Springer Verlag en_US
dc.relation.ispartof Water Resources Management en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Flood wave en_US
dc.subject Genetic algorithms en_US
dc.subject Hydraulic modelling en_US
dc.subject Hydrograph generation en_US
dc.subject Reverse routing en_US
dc.subject Rivers en_US
dc.title Reverse flood routing in natural channels using genetic algorithm en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.institutional Tayfur, Gökmen
gdc.bip.impulseclass C4
gdc.bip.influenceclass C4
gdc.bip.popularityclass C4
gdc.coar.access open access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department İzmir Institute of Technology. Civil Engineering en_US
gdc.description.endpage 4267 en_US
gdc.description.issue 12 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q1
gdc.description.startpage 4241 en_US
gdc.description.volume 29 en_US
gdc.description.wosquality Q1
gdc.identifier.openalex W936368647
gdc.identifier.wos WOS:000359417500003
gdc.index.type WoS
gdc.index.type Scopus
gdc.oaire.accesstype BRONZE
gdc.oaire.diamondjournal false
gdc.oaire.impulse 10.0
gdc.oaire.influence 4.3595145E-9
gdc.oaire.isgreen true
gdc.oaire.keywords Flood wave
gdc.oaire.keywords Hydrograph generation
gdc.oaire.keywords Peak rate
gdc.oaire.keywords River reach
gdc.oaire.keywords Genetic algorithms
gdc.oaire.keywords Hydraulic modelling
gdc.oaire.keywords Time to peak
gdc.oaire.keywords Rivers
gdc.oaire.keywords Genetic algorithm
gdc.oaire.keywords Reverse routing
gdc.oaire.keywords Simulation
gdc.oaire.popularity 1.3607755E-8
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 0208 environmental biotechnology
gdc.oaire.sciencefields 0207 environmental engineering
gdc.oaire.sciencefields 02 engineering and technology
gdc.openalex.collaboration International
gdc.openalex.fwci 2.83195893
gdc.openalex.normalizedpercentile 0.9
gdc.opencitations.count 26
gdc.plumx.crossrefcites 13
gdc.plumx.mendeley 24
gdc.plumx.scopuscites 28
gdc.scopus.citedcount 28
gdc.wos.citedcount 27
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relation.isOrgUnitOfPublication.latestForDiscovery 9af2b05f-28ac-4020-8abe-a4dfe192da5e

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