Spatiotemporal Analysis of Precipitation and its Relationship with Teleconnection Patterns (Case study: Urmia Lake basin))

Temporal and spatial variations in rainfall play a key role in the balance of water resources. The catchment area of Lake Urmia, as the largest inland lake in Iran, is the destination of the most important rivers in the northwest of the country. Accordingly, in the present study, the temporal and spatial distribution of rainfall in the Lake Urmia basin was investigated. The data used are the total frequency of seasonal and annual precipitation of 59 meteorological stations and data related to 11 teleconnection patterns during 1992-2016 and the main methods, statistical characteristics (first quartile, third quartile, and seasonal and annual Coefficient of variation), principal component analysis, Ward hierarchical cluster analysis, Kriging geostatistical method, and Pearson correlation. In the study of statistical features, it was found that the highest coefficient of variation in summer and the highest numerical value of the first and third quartile in winter were calculated and the highest coefficient of variation in the middle, central and southern parts, more values of the first quartile in the northern and western parts and higher quartile values are observed in the western and southern halves. Based on the results of temporal and spatial analysis, it was determined that the highest amount of precipitation occurs in the spring in the western half. Performing principal component analysis determined that the six main factors explain about 95% of the variance of the data and the most important influential components are the first and third quartile of autumn, winter, and annual. The results of cluster analysis identified three groups in central and southern regions, western and southwestern and northern half. The study of the relationship between winter rainfall and teleconnection patterns showed that this relationship is significant with NAO, EAWR, and MOI patterns.