تحليل روند و پهنه بندي زماني-مكاني بارش حوضه درياچه اروميه و انتخاب ايستگاه هاي شاخص با روش هاي آماري چند متغيره

Trend Analysis and Spatio-Temporal Zoning of Urmia Lake Basin Precipitation and Selection of Indicator Stations by Multivariate Statistical Methods

درﯾﺎﭼﻪ اروﻣﯿﻪ ﺑﻪ ﻋﻨﻮان ﯾﮑﯽ از ﻣﻬﻢﺗﺮﯾﻦ درﯾﺎﭼﻪﻫﺎي ﮐﺸﻮر ﺑﻪ ﻋﻠﺖ ﻣﺼﺮف ﺑﯿﺶ از ﺣﺪ آب و ﺗﻐﯿﯿﺮ اﻗﻠﯿﻢ داراي وﺿﻌﯿﺖ ﻧﺎﻣﻨﺎﺳﺐ زﯾﺴﺖﻣﺤﯿﻄﯽ ﺷﺪه اﺳﺖ. ﺑﺮرﺳﯽ ﺗﻐﯿﯿﺮات اﻗﻠﯿﻤﯽ و ﻧﺤﻮه ﺗﻮزﯾﻊ ﺑﺎرش در اﯾﻦ ﻣﻨﻄﻘﻪ ﻣﯽﺗﻮاﻧﺪ در ﺟﻬﺖ ﻣﺪﯾﺮﯾﺖ ﺑﻬﺘﺮ اﯾﻦ ﺣﻮﺿﻪ آﺑﺮﯾﺰ ﺑﻪ ﮐﺎر رود. در اﯾﻦ ﻣﻄﺎﻟﻌﻪ، ﺑﺮاي ﭘﻬﻨﻪﺑﻨﺪي ﻧﻮاﺣﯽ ﺑﺎرش ﺣﻮﺿﻪ درﯾﺎﭼﻪ اروﻣﯿﻪ از اﻃﻼﻋﺎت 65 اﯾﺴﺘﮕﺎه ﻫﻮاﺷﻨﺎﺳﯽ در دوره آﻣﺎري 1376-1395 اﺳﺘﻔﺎده ﺷﺪ. ﺑﺮاي اﯾﻦ ﻣﻨﻈﻮر، دادهﻫﺎي ﻫﺮ ﻣﺎه اﺳﺘﺎﻧﺪارد ﺷﺪه اﺳﺖ و در ﻣﺎﺗﺮﯾﺲ ﺑﺎ اﺑﻌﺎد )n*m( ﮐﻪ در آن n ﺗﻌﺪاد اﯾﺴﺘﮕﺎهﻫﺎ )65( و m ﺗﻌﺪاد ﻣﺎهﻫﺎ )12( اﺳﺖ، ﻧﻮﺷﺘﻪ ﺷﺪﻧﺪ. ﺗﺠﺰﯾﻪ ﻣﺆﻟﻔﻪﻫﺎي اﺻﻠﯽ )PCA( روي ﻣﺎﺗﺮﯾﺲ دادهﻫﺎ اﻧﺠﺎم ﺷﺪ و ﺑﺎ ﺗﻮﺟﻪ ﺑﻪ ﻣﻌﯿﺎر دارا ﺑﻮدن ﻣﻘﺪار وﯾﮋه ﺑﺎﻻي ﯾﮏ، ﻣﺆﻟﻔﻪﻫﺎي اﺻﻠﯽ اﻧﺘﺨﺎب ﺷﺪﻧﺪ. آﻧﮕﺎه ﻣﻘﺎدﯾﺮ اﻣﺘﯿﺎزات ﻣﺆﻟﻔﻪﻫﺎي اﺻﻠﯽ )PCS( ﺑﺮاي ﻣﺆﻟﻔﻪﻫﺎي ﻣﻨﺘﺨﺐ ﻣﺤﺎﺳﺒﻪ ﺷﺪ. اﯾﻦ ﻣﻘﺎدﯾﺮ ﺑﻪﻋﻨﻮان ورودي روش ﺗﺠﺰﯾﻪ ﺧﻮﺷﻪاي ﺑﺎ روش وارد اﺳﺘﻔﺎده ﺷﺪﻧﺪ. ﺳﭙﺲ ﺟﻬﺖ ﺗﻌﯿﯿﻦ اﯾﺴﺘﮕﺎهﻫﺎي ﺷﺎﺧﺺ از روش ﭘﺮوﮐﺮاﺳﺘﺲ اﺳﺘﻔﺎده ﺷﺪ. ﻧﺘﺎﯾﺞ ﻧﺸﺎن داد ﮐﻪ دو ﻣﺆﻟﻔﻪ اﺻﻠﯽ اول، 87 درﺻﺪ وارﯾﺎﻧﺲ ﮐﻞ دادهﻫﺎ را ﺗﻮﺟﯿﻪ ﻣﯽﮐﻨﻨﺪ. ﺑﺮاﺳﺎس ﻣﺆﻟﻔﻪﻫﺎي ﻣﻨﺘﺨﺐ، در ﮐﻞ ﺣﻮﺿﻪ، ﺷﺶ ﻧﺎﺣﯿﻪ ﺑﺎرﺷﯽ ﻣﺘﻤﺎﯾﺰ ﺗﺸﺨﯿﺺ داده ﺷﺪ. ﻫﻤﭽﻨﯿﻦ ﻣﻌﻠﻮم ﺷﺪ ﮐﻪ ﭼﻬﺎر اﯾﺴﺘﮕﺎه واﻗﻊ در ﻧﻘﺎط ﻣﺨﺘﻠﻒ ﺣﻮﺿﻪ آﺑﺮﯾﺰ درﯾﺎﭼﻪ اروﻣﯿﻪ ﺷﺎﻣﻞ ﻣﻬﻤﺎﻧﺪار، ﺳﺮاب، ﺑﺎﺑﺎرود و ﺳﻨﺘﻪ ﻣﯽﺗﻮاﻧﻨﺪ ﺑﻪﻋﻨﻮان اﯾﺴﺘﮕﺎهﻫﺎي ﺷﺎﺧﺺ در ﻧﻈﺮ ﮔﺮﻓﺘﻪ ﺷﻮﻧﺪ. اﯾﻦ اﯾﺴﺘﮕﺎهﻫﺎ ﺑﯿﺶ از %84 وارﯾﺎﻧﺲ ﮐﻞ دادهﻫﺎي اﯾﺴﺘﮕﺎهﻫﺎي ﺣﻮﺿﻪ را در ﺑﺮ داﺷﺘﻨﺪ. آزﻣﻮن روﻧﺪ ﻣﻦ-ﮐﻨﺪال ﻧﺸﺎن داد ﮐﻪ ﺑﺎرش در ﻓﺼﻞ ﭘﺎﯾﯿﺰ داراي روﻧﺪ اﻓﺰاﯾﺸﯽ ﻣﻌﻨﯽدار ﻣﯽﺑﺎﺷﺪ، درﺣﺎﻟﯽﮐﻪ ﺑﺎرش ﺳﺎﻻﻧﻪ ﻓﻘﻂ در ﯾﮑﯽ از ﺧﻮﺷﻪﻫﺎ داراي روﻧﺪ اﻓﺰاﯾﺸﯽ ﻣﻌﻨﯽدار ﻣﯽﺑﺎﺷﺪ.

Lake Urmia, as one of the most important lakes in the country, has an inappropriate environmental condition due to excessive consumption of water and climate change. The study of climate change and rainfall distribution in this area can improve water management in this basin. In this study, the information of 65 weather stations in the period of 1997-2016 were used for precipitation zoning of Urmia lake basin. For this purpose, the data of each month were standardized and arranged in a matrix with dimensions of (n*m) in which n is the number of stations (65) and m is the number of months (12). Principal Component Analysis (PCA) was performed on data matrix and the main components were determined according to their Eigen values greater than one. Then the principal component score (PCS) values were calculated for the selected components. These values were used as inputs in the Ward cluster analysis method. Then, the Procrustes method was used to determine the index stations. The results showed that the first two main components incorporated more than 87% of the all data variances. Based on the selected components, six distinct precipitation regions were identified throughout the basin. Moreover, it was found that four stations located in different points of the Urmia lake basin namely Mehmandar, Sarab, Babaroud and Santeh can be considered as indicator stations. These stations incorporated more than 84% of the all data variances of basin stations. The Mann-Kendall trend test showed that the rainfall in the autumn season has a significant increase trend, while annual precipitation has only a significant increase trend in one of the clusters.