The Association between Meteorological Drought and the State of the Groundwater Level in Bursa, Turkey

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dc.authorid0000-0001-8427-5965
dc.authorid0000-0002-4767-6660
dc.authorid0000-0003-0559-5261
dc.contributor.authorVaheddoost, Babak
dc.contributor.authorMohammadi, Babak
dc.contributor.authorSafari, Mir Jafar Sadegh
dc.date.accessioned2026-02-12T21:05:09Z
dc.date.available2026-02-12T21:05:09Z
dc.date.issued2023
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractThis study addressed the intricate interplay between meteorological droughts and groundwater level fluctuations in the vicinity of Mount Uludag in Bursa, Turkey. To achieve this, an exhaustive analysis encompassing monthly precipitation records and groundwater level data sourced from three meteorological stations and eight groundwater observation points spanning the period from 2007 to 2018 was performed. Subsequently, this study employed the Standard Precipitation Index (SPI) and Standard Groundwater Level (SGL) metrics, meticulously calculating the temporal extents of drought events for each respective time series. Following this, a judicious application of both the Thiessen and Support Vector Machine (SVM) methodologies was undertaken to ascertain the optimal groundwater observation wells and their corresponding SGL durations, aligning them with SPI durations tied to the selected meteorological stations. The SVM technique, in particular, excelled in the identification of the most pertinent observation wells. Additionally, the Elman Neural Network (ENN) and its optimized version through the Firefly Algorithm (ENN-FA), demonstrated their prowess in accurately predicting SPI durations based on SGL durations. The results were favorable, as evidenced by the commendable performance metrics of the Normalized Root Mean Square Error (NRMSE), the Nash-Sutcliffe Efficiency (NSE), the product of the coefficient of determination and the slope of the regression line (bR2), and the Kling-Gupta Efficiency (KGE). Consequently, the favorable simulation results were construed as evidence supporting the presence of a discernible association between SGL and the duration of the SPI. As we substantiate the concordance between the temporal extent of meteorological droughts and the perturbations in groundwater levels, this unmistakably underscores the fact that the historical fluctuations in groundwater levels within the region were predominantly attributable to climatic influences, rather than being instigated by anthropogenic activities. Nevertheless, it is imperative to underscore that this revelation should not be misconstrued as an endorsement of future heedless exploitation of groundwater resources.
dc.description.sponsorshipThe authors wish to extend their gratitude to the State Hydraulic Works and the State Meteorological Services for generously providing the data utilized in this study.
dc.description.sponsorshipThe authors wish to extend their gratitude to the State Hydraulic Works and the State Meteorological Services for generously providing the data utilized in this study.
dc.identifier.doi10.3390/su152115675
dc.identifier.issn2071-1050
dc.identifier.issue21
dc.identifier.scopus2-s2.0-85186224188
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.3390/su152115675
dc.identifier.urihttps://hdl.handle.net/20.500.12885/6825
dc.identifier.volume15
dc.identifier.wosWOS:001099556300001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherMdpi
dc.relation.ispartofSustainability
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20260212
dc.subjectdrought duration
dc.subjectElman neural network
dc.subjectfirefly algorithm
dc.subjectgroundwater level
dc.subjectsupport vector machine
dc.titleThe Association between Meteorological Drought and the State of the Groundwater Level in Bursa, Turkey
dc.typeArticle

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