JWSS - Journal of Water and Soil Science

In this study, in order to analyze the trends of annual precipitation, the information from 21 synoptic meteorological stations located in the Urmia Lake basin in a 30-year time period (1986-2015) was used. For this purpose, the Sequential Mann-Kendall test was used. The date of sudden change (if exist) in the precipitation time series of each station was identified. Significance of the trend in each of the time series and its direction (decrease or increase) in each of the stations were tested at 0.05 level. The results showed that 10 out of the 21 stations had a significant decreasing trend. Three stations (Sarab, Bostanabad and Sardasht) had significant increasing trends. Precipitation trends of eight stations were insignificant. Also, the study of sudden breaking points in the annual rainfall time series of the selected stations revealed that about 57.143 percent of the stations (12 stations) showed a significant sudden change in their annual rainfall series. In other words, more than half of the selected stations exhibited a   sudden change in their time series. The date of the sudden change of precipitation in eight stations (namely, Bonab, Sarab, Urmia, Oshnavieh, Kahrizi, Miyandoab, Bokan and Saghez) belonged to the middle part of the time series (i.e. 1996-2005). The sudden change date  of t hree stations (namely, Sardasht, Nagade and Tekab) belonged to the first decade of time series (i.e. 1986-1995) and only the sudden change date of  one station (namely, Maragheh) belonged to the last decade of time series (i.e. 2006-2015).

Regionalization is one of the useful tools for carrying out effective analyses in regions lacking data or with having only incomplete data. One of the regionalization methods widely used in the hydrological studies is the clustering approach. Moreover, another effective factor on clustering is the degree of importance and participation level for each of these attributes. In this study, it was tried to use a broad range of attributes to compare their performance in regionalization. Then, according to the importance and role of each attribute in regionalization, the appropriate weight for each of the attributes in each category was determined using the principal component analysis (PCA) method, and the effect of this weighting in forming the homogenous regions was investigated by the Ward's clustering method. In this regard, the maximum 24-hour rainfall data of 63 meteorological stations located in Urmia Lake Basin (ULB) was used in this study during a time period of 30 years (1979-2008). Furthermore, seven categories of attributes were defined in order to regionalize the rainfall. The results showed that by considering different attributes and combining them with each other, a different clustering is obtained in each category in terms of the number of clusters and stations. Among seven categories of attributes, it was found that the geographical and climatic-geographical categories of attributes showed a more appropriate clustering over the ULB. Additionally, the weighting of attributes could have more effect on improving homogeneity and forming the independent clusters in most cases in terms of the scattering of station and how to locate over the basin.