كليدواژه :
ﺗﺤﻠﯿﻞ زﻣﺎﻧﯽ- ﻣﮑﺎﻧﯽ , اﻟﮕﻮﻫﺎي ﭘﯿﻮﻧﺪ از دور , ﺑﺎرش و ﺗﺤﻠﯿﻞ ﺧﻮﺷﻪاي , ﺗﺤﻠﯿﻞ ﻣﻮﻟﻔﻪﻫﺎي اﺻﻠﯽ , ﺣﻮﺿﻪ آﺑﺮﯾﺰ درﯾﺎﭼﻪ اروﻣﯿﻪ
چكيده فارسي :
ﭼﮑﯿﺪه
ﺗﻐﯿﯿﺮات زﻣﺎﻧﯽ و ﻣﮑﺎﻧﯽ ﺑﺎرش ﻧﻘﺶ اﺳﺎﺳﯽ در ﺑﯿﻼن ﻣﻨﺎﺑﻊ آﺑﯽ اﯾﻔﺎ ﻣﯽﮐﻨﺪ. ﺣﻮﺿﻪ آﺑﺮﯾﺰ درﯾﺎﭼﻪ اروﻣﯿﻪ ﻧﯿﺰ ﺑﻪ ﻋﻨﻮان ﺑﺰرگﺗﺮﯾﻦ درﯾﺎﭼﻪ داﺧﻠﯽ اﯾﺮان ﻣﻘﺎﺻﺪ ﻣﻬﻤﺘﺮﯾﻦ رودﺧﺎﻧﻪﻫﺎي ﺷﻤﺎل ﻏﺮﺑﯽ ﮐﺸﻮر اﺳﺖ، ﺑﻪ ﻫﻤﯿﻦ ﻣﻨﻈﻮر ﺷﻨﺎﺳﺎﯾﯽ ﻣﺘﻐﯿﺮﻫﺎي ﻣﻮﺛﺮ در ﺗﻮزﯾﻊ زﻣﺎﻧﯽ و ﻣﮑﺎﻧﯽ ﺑﺎرش و ﻧﺎﺣﯿﻪﺑﻨﺪي ﻣﻨﺎﻃﻖ ﺑﺎرﺷﯽ در اﯾﻦ ﻣﻨﻄﻘﻪ ﺿﺮورت ﻣﯽﯾﺎﺑﺪ. ﺑﺮ اﯾﻦ اﺳﺎس در ﭘﮋوﻫﺶ ﺣﺎﺿﺮ ﺑﻪ ﺑﺮرﺳﯽ ﺗﻮزﯾﻊ زﻣﺎﻧﯽ و ﻣﮑﺎﻧﯽ ﺑﺎرش ﺣﻮﺿﻪ درﯾﺎﭼﻪ اروﻣﯿﻪ ﭘﺮداﺧﺘﻪ ﺷﺪ. دادهﻫﺎي ﻣﻮرد اﺳﺘﻔﺎده، ﻣﺠﻤﻮع ﻓﺮاواﻧﯽ ﺑﺎرش ﻓﺼﻠﯽ و ﺳﺎﻻﻧﻪ 59اﯾﺴﺘﮕﺎه ﻫﻮاﺷﻨﺎﺳﯽ و دادهﻫﺎي ﻣﺮﺑﻮط ﺑﻪ 11اﻟﮕﻮي ﭘﯿﻮﻧﺪ از دور در ﺳﺎلﻫﺎي 1370-1394و روشﻫﺎي اﺻﻠﯽ، وﯾﮋﮔﯽﻫﺎي آﻣﺎري )ﭼﺎرك اول، ﭼﺎرك ﺳﻮم و ﺿﺮﯾﺐ ﺗﻐﯿﯿﺮات ﻓﺼﻠﯽ و ﺳﺎﻻﻧﻪ(، ﺗﺤﻠﯿﻞ ﻣﻮﻟﻔﻪﻫﺎي اﺻﻠﯽ، ﺗﺤﻠﯿﻞ ﺧﻮﺷﻪ اي ﺳﻠﺴﻠﻪ ﻣﺮاﺗﺒﯽ وارد، روش زﻣﯿﻦ آﻣﺎر ﮐﺮﯾﺠﯿﻨﮓ و ﻫﻤﺒﺴﺘﮕﯽ ﭘﯿﺮﺳﻮن ﻫﺴﺘﻨﺪ. در ﺑﺮرﺳﯽ وﯾﮋﮔﯽﻫﺎي آﻣﺎري ﻣﺸﺨﺺ ﺷﺪ ﮐﻪ ﺑﯿﺸﺘﺮﯾﻦ ﺿﺮﯾﺐ ﺗﻐﯿﯿﺮات در ﺗﺎﺑﺴﺘﺎن و ﺑﯿﺸﺘﺮﯾﻦ ﻣﻘﺪار ﻋﺪدي ﭼﺎرك اول و ﺳﻮم در زﻣﺴﺘﺎن ﻣﺤﺎﺳﺒﻪ ﺷﺪه اﺳﺖ و ﺑﯿﺸﺘﺮﯾﻦ ﺿﺮﯾﺐ ﺗﻐﯿﯿﺮات در ﺑﺨﺶﻫﺎي ﻣﯿﺎﻧﯽ، ﻣﺮﮐﺰي و ﺟﻨﻮﺑﯽ، ﻣﻘﺎدﯾﺮ ﺑﯿﺸﺘﺮ ﭼﺎرك اول در ﺑﺨﺶﻫﺎي ﺷﻤﺎﻟﯽ و ﻏﺮﺑﯽ و ﻣﻘﺎدﯾﺮ ﺑﺎﻻﺗﺮ ﭼﺎرك ﺳﻮم درﻧﯿﻤﻪ ﻏﺮﺑﯽ و ﺟﻨﻮﺑﯽ ﻣﺸﺎﻫﺪه ﺷﺪه اﺳﺖ. ﺑﺮاﺳﺎس ﻧﺘﺎﯾﺞ ﺗﺤﻠﯿﻞﻫﺎي زﻣﺎﻧﯽ و ﻣﮑﺎﻧﯽ ﻣﻌﯿﻦ ﮔﺮدﯾﺪ ﺑﯿﺸﺘﺮﯾﻦ ﻣﻘﺪار ﺑﺎرش در ﻓﺼﻞ ﺑﻬﺎر در ﻧﯿﻤﻪ ﻏﺮﺑﯽ رخ ﻣﯽدﻫﺪ. اﺟﺮاي ﺗﺤﻠﯿﻞ ﻣﻮﻟﻔﻪﻫﺎي اﺻﻠﯽ ﻣﻌﯿﻦ ﮐﺮد ﮐﻪ ﺷﺶ ﻋﺎﻣﻞ اﺻﻠﯽ ﺣﺪود 95درﺻﺪ وارﯾﺎﻧﺲ دادهﻫﺎ را ﺗﺒﯿﯿﻦ ﻣﯽﻧﻤﺎﯾﺪ و ﻣﻬﻤﺘﺮﯾﻦ ﻣﻮﻟﻔﻪﻫﺎي ﺗﺎﺛﯿﺮﮔﺬار ﭼﺎرك اول و ﺳﻮم ﻓﺼﻮل ﭘﺎﺋﯿﺰ، زﻣﺴﺘﺎن و ﺳﺎﻻﻧﻪ ﻫﺴﺘﻨﺪ. ﻧﺘﺎﯾﺞ ﺗﺤﻠﯿﻞ ﺧﻮﺷﻪ اي ﺳﻪ ﮔﺮوه را در 1-ﻧﻮاﺣﯽ ﻣﯿﺎﻧﯽ و ﺟﻨﻮﺑﯽ 2-ﻏﺮﺑﯽ و ﺟﻨﻮب ﻏﺮﺑﯽ و 3- ﻧﯿﻤﻪ ﺷﻤﺎﻟﯽ ﻣﺸﺨﺺ ﮐﺮد. ﺑﺮرﺳﯽ ارﺗﺒﺎط ﺑﺎرش ﻓﺼﻞ زﻣﺴﺘﺎن ﺑﺎ اﻟﮕﻮﻫﺎي ﭘﯿﻮﻧﺪ از دور ﻣﻌﯿﻦ ﻧﻤﻮد ﮐﻪ اﯾﻦ ارﺗﺒﺎط ﺑﺎ اﻟﮕﻮﻫﺎي EAWR ،NAO و MOI ﻣﻌﻨﺎدار اﺳﺖ.
چكيده لاتين :
Temporal and spatial variations in precipitation 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 precipitation 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 precipitation and teleconnection
patterns showed that this relationship is significant with NAO, EAWR,
and MOI patterns.
