ENSO MODULATIONS ON STREAMFLOW CHARACTERISTICS

Earth sciences research journal

Yerdelen, Cahit¹  Kahya, Ercan²  Marti, Ali Ihsan³ 

[1] Ege University;Istanbul Technical University Hydraulics Division, Istanbul, Turkey;Selcuk University Campus, Konya, Turkey

关键词: Streamflow;    ENSO Modulation;    Radial Based Artificial Neural Network Model;    Turkey;   

DOI  :  

学科分类：天文学(综合)

来源: Universidad Nacional de Colombia * Departamento de Geociencias

【 摘 要 】

El Niño Southern Oscillation (ENSO) has been linked to climate and hydrologic anomalies throughout the world. This paper presents how ENSO modulates the basic statistical characteristics of streamflow time series that is assumed to be affected by ENSO. For this we first considered hypothetical series that can be obtained from the original series at each station by assuming non-occurrence of El Niño events in the past. Instead those data belonging to El Niño years were simulated by the Radial Based Artificial Neural Network (RBANN) method. Then we compared these data to the original series to see a significant difference with respect to their basic statistical characteristics (i.e., variance, mean and autocorrelation parameters). Various statistical hypothesis testing methods were used for four different scenarios. Consequently if there exist a significant difference, then it can be inferred that the ENSO events modulate the major statistical characteristics of streamflow series concerned. The results of this research were in good agreement with those of the previous studies.

【 授权许可】

CC BY