Meteorological drought analysis using data-driven models for the Lakes District, Turkey Analyse des sécheresses météorologiques à l'aide de modèles conditionnés par les données dans la Région des Lacs, Turquie

Erol Keskin M., TERZİ Ö., Dilek Taylan E., Küükyaman D.

Hydrological Sciences Journal, cilt.54, sa.6, ss.1114-1124, 2009 (SCI-Expanded, Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 54 Sayı: 6
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1623/hysj.54.6.1114
  • Dergi Adı: Hydrological Sciences Journal
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1114-1124
  • Anahtar Kelimeler: Adaptive neural-based fuzzy inference system (ANFIS), Drought, Fuzzy logic, Standardized precipitation index (SPI), The lakes district, Turkey
  • Isparta Uygulamalı Bilimler Üniversitesi Adresli: Hayır

Özet

Droughts may be classified as meteorological, hydrological or agricultural. When meteorological drought appears in a region, agricultural and hydrological droughts follow. In this study, the standardized precipitation index (SPI) was applied for meteorological drought analysis at nine stations located around the Lakes District, Turkey. Analyses were performed on 3-, 6-, 9-and 12-month-long data sets. The SPI drought classifications were modelled by Adaptive Neural-Based Fuzzy Inference System (ANFIS) and Fuzzy Logic, which has the advantage that, in contrast to most of the time series modelling techniques, it does not require the model structure to be known a priori. Comparison of the observed values and the modelling results shows a better agreement with SPI-12 and ANFIS models than with fuzzy logic models. Copyright © 2009 IAHS Press.