Meteorological drought analysis using data-driven models for the Lakes District, Turkey

Autor:	Derya Kucukyaman, M. Erol Keskin, Oezlem Terzi, E. Dilek Taylan
Rok vydání:	2009
Předmět:	Hydrology Adaptive neuro fuzzy inference system Hydrology (agriculture) Fuzzy inference system Climatology Environmental science Contrast (statistics) Time series modelling Precipitation index Fuzzy logic Water Science and Technology Data-driven
Zdroj:	Hydrological Sciences Journal. 54:1114-1124
ISSN:	2150-3435 0262-6667
DOI:	10.1623/hysj.54.6.1114
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::6443465f0a518b467d66b551362dd2e5 https://doi.org/10.1623/hysj.54.6.1114 Zobrazit plný text záznamu