Regressive-stochastic models for predicting water level in Lake Urmia

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dc.authorid0000-0002-4767-6660en_US
dc.authorscopusid57113743700en_US
dc.contributor.authorVaheddoost, Babak
dc.contributor.authorAksoy, Hafzullah
dc.date.accessioned2022-04-21T06:45:07Z
dc.date.available2022-04-21T06:45:07Z
dc.date.issued2021en_US
dc.departmentBTÜ, Mühendislik ve Doğa Bilimleri Fakültesi, İnşaat Mühendisliği Bölümüen_US
dc.description.abstractThis study develops a set of models to investigate the water budget of Lake Urmia in Iran, a permanent hypersaline lake that has suffered a declining water level since the late 1990s. The models are of the regressive-stochastic type, a combination of multilinear regression and autoregressive integrated moving average stochastic models. The multilinear regression models were used to construct the core of the relationship of lake water level to streamflow, precipitation, evaporation and groundwater depth. Afterward, stochastic models were used to generate data for each independent variable to estimate the oscillation in the lake water depth. Several criteria were used to compare the performance of the models in the aggregated and disaggregated cases with which the pre- and post-encroachment periods are considered, respectively. The regressive-stochastic models are found to be competitive with the existing models developed so far for Lake Urmia water level.en_US
dc.identifier.doi10.1080/02626667.2021.1974447en_US
dc.identifier.endpage1906en_US
dc.identifier.issn02626667
dc.identifier.issue13en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1892en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12885/1952
dc.identifier.volume66en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorVaheddoost, Babak
dc.language.isoenen_US
dc.publisherTaylor and Francis Ltd.en_US
dc.relation.ispartofHydrological Sciences Journalen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectautoregressive modelen_US
dc.subjectLake Urmiaen_US
dc.subjectmultiple regressionen_US
dc.subjectstochastic modelsen_US
dc.subjectwater levelen_US
dc.titleRegressive-stochastic models for predicting water level in Lake Urmiaen_US
dc.typeArticleen_US

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