ﺗﺤﻠﯿﻞ ﺧﺸﮑﺴﺎﻟﯽ ﮐﺸﺎورزي اﺳﺘﺎن ﻣﺎزﻧﺪران ﺑﺎ اﺳﺘﻔﺎده از ﺷﺎﺧﺺﻫﺎي ﻣﻨﺎﺳﺐ ﺳﻨﺠﺶ از دور و ﻫﻮاﺷﻨﺎﺳﯽ

Analyzing Agricultural Drought in Mazandaran Province Using Remote Sensing and Meteorological Ind

ﺧﺸﮑﺴﺎﻟﯽ ﮐﺸﺎورزي ﺑﻪ دﻟﯿﻞ ﺗﺎﺛﯿﺮ ﺷﺪﯾﺪ ﺑﺮ روي ﻣﺤﺼﻮﻻت زراﻋﯽ و ﺗﺎﺛﯿﺮ ﻏﯿﺮﻣﺴﺘﻘﯿﻢ ﺑﺮ اﺷﺘﻐﺎل و ﻫﻤﭽﻨﯿﻦ درآﻣﺪ ﺳﺮاﻧﻪ، در ﺳـﺮاﺳـﺮ ﺟﻬﺎن ﺑﻪ ﯾﮏ ﻧﮕﺮاﻧﯽ اﺻـﻠﯽ ﺗﺒﺪﯾﻞ ﺷـﺪه اﺳـﺖ. اﺳـﺘﻔﺎده از روشﻫﺎي ﺳـﻨﺠﺶ از دور اﻧﻌﮑﺎﺳـﯽ، ﺟﻬﺖ ارزﯾﺎﺑﯽ اﺛﺮات ﺧﺸـﮑﺴـﺎﻟﯽ، ﺑﻪ ﻋﻨﻮان ﯾﮑﯽ از ﮐﺎرآﻣﺪﺗﺮﯾﻦ روشﻫﺎ ﺷـﻨﺎﺧﺘﻪ ﺷـﺪه اﺳـﺖ. ﺑﻨﺎﺑﺮاﯾﻦ ﻫﺪف از ﭘﮋوﻫﺶ ﺣﺎﺿـﺮ ﺗﺤﻠﯿﻞ ﺧﺸـﮑﺴـﺎﻟﯽ ﮐﺸـﺎورزي اﺳـﺘﺎن ﻣﺎزﻧﺪران ﺑﺎ اﺳـﺘﻔﺎده از ﺷـﺎﺧﺺﻫﺎي ﻣﻨﺎﺳـﺐ ﺳـﻨﺠﺶ از دور و ﻫﻮاﺷـﻨﺎﺳـﯽ ﻣﯽﺑﺎﺷـﺪ. اﺑﺘﺪا ﺷـﺎﺧﺺﻫﺎي SPI، ZSI و EDIدر ﻣﻘﯿﺎسﻫﺎي زﻣﺎﻧﯽ ﻣﺨﺘﻠﻒ ﻣﺤﺎﺳـﺒﻪ ﮔﺮدﯾﺪ و ﺑﻬﺘﺮﯾﻦ ﻧﻤﺎﯾﻪ ﺑﺮ اﺳـﺎس روش ﺗﻮزﯾﻊ ﻧﺮﻣﺎل اﻧﺘﺨﺎب ﮔﺮدﯾﺪ. ﺳـﭙﺲ ﺑﺎ اﺳـﺘﻔﺎده از ﺗﺼـﺎوﯾﺮ ﺳـﺮي ﻣﺎﻫﻮارهﻫﺎي ﻟﻨﺪﺳـﺖ 5، 7 و 8، ﺷـﺎﺧﺺﻫﺎي ﺳـﻨﺠﺶ از دور EVI ،NDVIو VCI اﺳـﺘﺨﺮاج ﮔﺮدﯾﺪ و ﺑﻬﺘﺮﯾﻦ ﻧﻤﺎﯾﻪ ﺑﺮاﺳـﺎس ﺑﯿﺸـﺘﺮﯾﻦ ﻫﺒﺴـﺘﮕﯽ ﺑﺎ ﺷـﺎﺧﺺ ﺧﺸـﮑﺴـﺎﻟﯽ ﻣﻨﺎﺳـﺐ اﻧﺘﺨﺎب ﮔﺮدﯾﺪ. در ﻧﻬﺎﯾﺖ ﺑﺎ اﺳـﺘﻔﺎده از ﺑﻬﺘﺮﯾﻦ ﻧﻤﺎﯾﻪ ﻫﻮاﺷﻨﺎﺳﯽ و ﺳﻨﺠﺶ از دور، ﺧﺸﮑﺴﺎﻟﯽ ﮐﺸﺎورزي اﺳﺘﺎن ﻣﺎزﻧﺪران در دو ﺳﺎل ﺧﯿﻠﯽ ﺧﺸﮏ )89( و ﺧﯿﻠﯽ ﻣﺮﻃﻮب )92( ﺑﺮاي ﻓﺼــﻮل ﻣﺨﺘﻠﻒ ﻣﻮرد ﺑﺮرﺳــﯽ ﻗﺮار ﮔﺮﻓﺖ. ﻧﺘﺎﯾﺞ ﭘﮋوﻫﺶ ﺣﺎﺿــﺮ ﻧﺸــﺎن داد ﮐﻪ ﺑﺮاﺳــﺎس روش ﺗﻮزﯾﻊ ﻧﺮﻣﺎل، ﻣﺠﻤﻮع اﺧﺘﻼف از ﺗﻮزﯾﻊ ﻧﺮﻣﺎل ﺑﺮاي ﺷـﺎﺧﺺ SPIﻧﺴـﺒﺖ ﺑﻪ ﺷـﺎﺧﺺﻫﺎي دﯾﮕﺮ ﮐﻤﺘﺮ ﻣﯽﺑﺎﺷـﺪ. ﻫﻤﭽﻨﯿﻦ ﻧﺘﺎﯾﺞ ﻧﺸـﺎن داد ﮐﻪ ﺑﺎﻻﺗﺮﯾﻦ ﻫﻤﺒﺴـﺘﮕﯽ ﺑﯿﻦ ﻧﻤﺎﯾﻪ ﻃﯿﻔﯽ VCIو ﻧﻤﺎﯾﻪﻫﺎي ﻫﻮاﺷــﻨﺎﺳــﯽ SPIﺑﺎ ﺗﺎﺧﯿﺮ زﻣﺎﻧﯽ ﺳــﻪ و ﺷــﺶ ﻣﺎﻫﻪ ﻣﯽﺑﺎﺷــﺪ. ﻫﻤﭽﻨﯿﻦ ﻧﺘﺎﯾﺞ ﻧﺸــﺎن داد، ﻣﯿﺎﻧﮕﯿﻦ VCIدر ﺗﻤﺎم ﻓﺼـــﻮل ﺳـــﺎل ﺧﯿﻠﯽ ﺧﺸـــﮏ )89( ﺑﺮاي ﻫﻤﻪ اﯾﺴـــﺘﮕﺎهﻫﺎ ﻣﻨﻄﻘﻪ ﻣﻮرد ﻣﻄﺎﻟﻌﻪ زﯾﺮ 0/50 و ﺣﺪاﮐﺜﺮ اﯾﺴــﺘﮕﺎهﻫﺎ داراي ارزش VCIﮐﻤﺘﺮ از 0/35 اﻣﺎ در ﺗﻤﺎم ﻓﺼــﻮل ﺳــﺎل ﺧﯿﻠﯽ ﻣﺮﻃﻮب )92( ﺑﺮاي اﮐﺜﺮ اﯾﺴــﺘﮕﺎﻫﻬﺎ ﺑﺎﻻي 0/50 ﻣﯽﺑﺎﺷﺪ.

Agricultural drought has become a major concern worldwide due to the severe impact on crops and the indirect impact on occupation as well as per capita income. The use of reflective remote sensing techniques to evaluate the effects of drought is recognized as one of the most efficient methods. Therefore, the purpose of the present study is to analyze agricultural drought in Mazandaran province using Remote sensing and meteorological indicators. At the first, SPI, ZSI and EDI indices were calculated at different time scales and the best index was selected based on the normal distribution method. Then, using Landsat 5, 7 and 8 satellite images, NDVI, EVI and VCI remote sensing indices were extracted and the best index was selected based on the highest correlation with appropriate drought index. Finally, using the best meteorological and remote sensing indices, the agricultural drought in Mazandaran province was evaluated in two very dry (89) and very wet (92) years for different seasons. The results showed that based on the normal distribution method, the sum of the difference from normal distribution for the SPI index is lower than the other indices. The results also showed that the highest correlation was observed between VCI spectral index and SPI meteorological index with time delay of three and six months. The results also showed that the mean VCI in all seasons of very dry year (89) for all stations was below 0.50 and maximum stations had a VCI value of less than 0.35 but in all seasons of very wet year (92) for most stations is above 0.5.