Zeynep Irem OzenBerk Sadettin TengerlekDamla YukselEfthymia StaiouMir Jafar Sadegh SafariYüksel, DamlaSafari, Mir Jafar SadeghÖzen, Zeynep İremTengerlek, Berk SadettinStaiou, EfthymiaNM DurakbasaMG Gencyilmaz2025-10-062022978-3-030-90421-0, 978-3-030-90420-3978303090420397830309042102195-43562195-436410.1007/978-3-030-90421-0_592-s2.0-85119865946http://dx.doi.org/10.1007/978-3-030-90421-0_59https://gcris.yasar.edu.tr/handle/123456789/5724https://doi.org/10.1007/978-3-030-90421-0_59The world's water resources are decreasing day by day due to factors such as climate change drought inefficient pricing policies implemented by the government population growth uncontrolled water consumption technological developments and industrialization. A decrease in water resources causes water scarcity in the long-term period. This study is conducted to analysis the meteorological drought in Izmir district Turkey. Inspired by the real-life problem drought estimation models are developed through artificial neural network-based artificial intelligence techniques incorporating a decision support system. The Z-score index (ZSI) values are computed using precipitation data collected from five meteorological station in Kucuk Menderes basin and several developed models are compared according to the variety of statistical performance metrics.Englishinfo:eu-repo/semantics/closedAccessDrought, Artificial neural networks, Feed forward backpropagation, Generalized regression, Radial basis function, Z-Score IndexNEURAL-NETWORKSFeed Forward BackpropagationArtificial Neural NetworksGeneralized RegressionRadial Basis FunctionZ-Score IndexDroughtConference Object