ارزیابی وضعیت سیل خیزی شهرهای استان خوزستان

ﺑﺮآورد دﺑﯽ ﺑﺎر رﺳﻮﺑﺎت ﻣﻌﻠﻖ رودﺧﺎﻧﻪﻫﺎ ﺑﻪدﻟﯿﻞ ﺗﺄﺛﯿﺮﮔﺬاری ﺑﺮ ﻃﺮاﺣﯽ و ﻣﺪﯾﺮﯾﺖ ﺳﺎزهﻫﺎی آﺑﯽ، در ﻣﻬﻨﺪﺳﯽ آب، ﻫﯿﺪروﻟﯿﮏ و ﻣﺤﯿﻂ ﻃﺒﯿﻌﯽ ﻣﻬﻢ ﻣﯽﺑﺎﺷﺪ. ﺗﺎﮐﻨﻮن ﺗﻼشﻫﺎی ﮔﻮﻧﺎﮔﻮﻧﯽ ﺟﻬﺖ ﺑﺮآورد دﻗﯿﻖ ﺑﺎر رﺳﻮﺑﺎت ﻣﻌﻠﻖ ﺗﻮﺳﻂ ﭘﮋوﻫﺸﮕﺮان اﻧﺠﺎم ﺷﺪه اﺳﺖ ﮐﻪ ﺑﺮای ﻣﺜﺎل ﻣﯽﺗﻮان ﺑﻪ ﺑﺮﻗﺮاری راﺑﻄﻪ ﺑﯿﻦ دﺑﯽ ﺟﺮﯾﺎن و دﺑﯽ رﺳﻮب اﺷﺎره ﻧﻤﻮد. ﻣﺸﮑﻞ اﯾﻦ روش ﻋﺪم ﻗﻄﻌﯿﺖ آن ﻣﯽﺑﺎﺷﺪ. از اﯾﻦرو، ﺷﻤﺎری از ﻣﺤﻘﻘﺎن ﺑﻪ روشﻫﺎی ﻫﻮﺷﻤﻨﺪ و اﻟﮕﻮرﯾﺘﻢﻫﺎی ﺗﮑﺎﻣﻠّﯽ روی آوردهاﻧﺪ. در ﭘﮋوﻫﺶ ﺣﺎﺿﺮ ﺑﻪ ﻣﻨﻈﻮر ﺑﺮرﺳﯽ ﮐﺎرآﯾﯽ و دﻗﺖ روش ﺑﺮﻧﺎﻣﻪرﯾﺰی ﺑﯿﺎن ژن در ﭘﯿﺶﺑﯿﻨﯽ رﺳﻮب ﺑﺎر ﻣﻌﻠﻖ رودﺧﺎﻧﻪ ﻧﺎورود در اﺳﺘﺎن ﮔﯿﻼن ﺑﺎ اﺳﺘﻔﺎده از ﻧﺮم اﻓﺰار (gep)، از دادهﻫﺎی ﻣﺘﻮﺳﻂ ﺑﺎرﻧﺪﮔﯽ، ﻣﯿﺎﻧﮕﯿﻦ دﺑﯽ رواﻧﺎب، ﻣﺘﻮﺳﻂ دﻣﺎی ﺣﺪاﮐﺜﺮ، ﻣﺘﻮﺳﻂ دﻣﺎی ﺣﺪاﻗﻞ و ﻣﯿﺎﻧﮕﯿﻦ دﻣﺎی ﺳﺎﻻﻧﻪ ﺣﻮﺿﻪ، ﺑﻪ ﻋﻨﻮان ﻣﺘﻐﯿﺮﻫﺎی ورودی و ﻫﻤﭽﻨﯿﻦ دادهﻫﺎی رﺳﻮب ﺑﺎر ﻣﻌﻠﻖ ﻣﺸﺎﻫﺪهای در اﯾﺴﺘﮕﺎه ﻫﯿﺪروﻣﺘﺮی ﺧﺮﺟﮕﯿﻞ اﺳﺎﻟﻢ، ﺑﻪﻋﻨﻮان ﻣﺘﻐﯿﺮ ﺧﺮوﺟﯽ در دوره آﻣﺎری ﻣﺸﺘﺮک 20 ﺳﺎﻟﻪ (از ﺳﺎل آﺑﯽ 74-75 ﻟﻐﺎﯾﺖ 93-94) اﺳﺘﻔﺎده ﮔﺮدﯾﺪ. ﺑﺮای اﯾﻦ ﮐﺎر، ﻣﻘﺎدﯾﺮ رﺳﻮﺑﺎت ﺑﺎر ﻣﻌﻠﻖ ﺣﻮﺿﻪ از روش ﻣﻨﺤﻨﯽ ﺳﻨﺠﻪ، ﻣﻘﺎدﯾﺮ ﻣﺘﻮﺳﻂ ﺑﺎرﻧﺪﮔﯽ از روش ﻣﻨﺤﻨﯽﻫﺎی ﻫﻢﺑﺎران ﺑﺎ اﺳﺘﻔﺎده از ﻣﺪل kriging در ﻣﺤﯿﻂ ﻧﺮماﻓﺰار gis و ﻣﻘﺎدﯾﺮ ﺳﻪ ﺷﺎﺧﺺ درﺟﻪ ﺣﺮارت ﺳﺎﻻﻧﻪ از ﻃﺮﯾﻖ رواﺑﻂ ﮔﺮادﯾﺎن ﺣﺮارﺗﯽ ﻣﻨﻄﻘﻪ ﺑﺮای ﺳﺎلﻫﺎی آﻣﺎری ﻣﺨﺘﻠﻒ ﺑﺮآورد ﮔﺮدﯾﺪ. ﺟﻬﺖ دﺳﺖﯾﺎﺑﯽ ﺑﻪ ﺳﺎﺧﺘﺎر ﻣﻨﺎﺳﺐ ﺑﯿﻦ ورودیﻫﺎ و ﺧﺮوﺟﯽ ﻣﺪل، اﻃﻼﻋﺎت 13 ﺳﺎل اول آﻣﺎری ﺑﺮای آﻣﻮزش ﺑﺮﻧﺎﻣﻪ و 7 ﺳﺎل ﺑﺎﻗﯽﻣﺎﻧﺪه ﺑﺮای ﺻﺤﺖﺳﻨﺠﯽ آن ﺑﻪ ﮐﺎر ﮔﺮﻓﺘﻪ ﺷﺪ و ﺑﻪ ﻣﻨﻈﻮر ﺷﻨﺎﺳﺎﯾﯽ ورودیﻫﺎی ﻣﺆﺛﺮ، ﺗﻌﺪاد 6 اﻟﮕﻮی ﻣﺨﺘﻠﻒ ﺑﺮ اﺳﺎس ﺗﺮﮐﯿﺐ دادهﻫﺎی ورودی ﻃﺮاﺣﯽ ﮔﺮدﯾﺪ. در ﻧﻬﺎﯾﺖ، ﺑﺮای ﺗﻌﯿﯿﻦ ﻣﻨﺎﺳﺐﺗﺮﯾﻦ راﺑﻄﻪ ﺟﻬﺖ ﭘﯿﺶﺑﯿﻨﯽ رﺳﻮﺑﺎت ﺣﻮﺿﻪ، از دو ﺷﺎﺧﺺ ﻣﻌﺘﺒﺮ ﺟﺬر ﻣﯿﺎﻧﮕﯿﻦ ﻣﺮﺑﻌﺎت ﺧﻄﺎ )rmse( و ﺿﺮﯾﺐ ﻫﻤﺒﺴﺘﮕﯽ )r2( اﺳﺘﻔﺎده ﮔﺮدﯾﺪ. ﻧﺘﺎﯾﺞ ﻧﺸﺎن داد، ﺑﺎ ﺳﺎﺧﺘﺎر ﻣﺘﻮﺳﻂ ﺑﺎرﻧﺪﮔﯽ، ﻣﯿﺎﻧﮕﯿﻦ دﺑﯽ رواﻧﺎب، ﻣﺘﻮﺳﻂ ﺣﺪاﮐﺜﺮ و ﻣﯿﺎﻧﮕﯿﻦ دﻣﺎی ﺳﺎﻻﻧﻪ ﺣﻮﺿﻪ، ﺿﺮﯾﺐ ﻫﻤﺒﺴﺘﮕﯽ )r2( ﺑﯿﻦ دادهﻫﺎی ﻣﺤﺎﺳﺒﺎﺗﯽ و ﻣﺸﺎﻫﺪهای در دوره ﺻﺤﺖﺳﻨﺠﯽ ﺑﻪ ﺑﯿﺸﺘﺮﯾﻦ ﻣﻘﺪار ﺧﻮد )%84( و ﻣﻘﺪار ﺷﺎﺧﺺ rmse ﺑﻪ ﮐﻤﺘﺮﯾﻦ ﻣﻘﺪار ﺧﻮد )1.06( ﻣﯽرﺳﺪ. در ﻧﺘﯿﺠﻪ ﺳﺎﺧﺘﺎر ﻓﻮق ﺑﻪﻋﻨﻮان ﻣﻨﺎﺳﺐﺗﺮﯾﻦ اﻟﮕﻮی ورودی ﺟﻬﺖ ﺗﺨﻤﯿﻦ رﺳﻮﺑﺎت ﺳﺎﻻﻧﻪ ﺣﻮﺿﻪ ﭘﺬﯾﺮﻓﺘﻪ ﺷﺪه و ﺑﺮ اﯾﻦ اﺳﺎس و ﺑﺎ اﺳﺘﻔﺎده از زﺑﺎن ﺑﺮﻧﺎﻣﻪﻧﻮﯾﺴﯽ matlab و ﺑﻪ ﮐﺎرﮔﯿﺮی ﭼﻬﺎر ﻋﻤﻠﮕﺮ اﺻﻠﯽ ﺣﺴﺎﺑﯽ، راﺑﻄﻪ ﻧﻬﺎﯾﯽ ﺑﺮای ﺗﺨﻤﯿﻦ رﺳﻮب ﺣﻮﺿﻪ اﺳﺘﺨﺮاج ﮔﺮدﯾﺪ.

assessment of the flooding situation in the cities of khuzestan province

flooding is one of the natural hazards that threatens many cities in iran, including those in khuzestan province. given that floods are always associated with significant human and financial losses, the purpose of this study is to identify flood-prone areas in khuzestan province and then assess the flood situation in its cities. in this research, modis, chirps satellite images and 30-meter digital elevation model were used as the most important research data. the most important research tools were google earth engine system and arcgis, expert choice and terrset software. in this research, using the owa-ahp model, the flood-prone areas in khuzestan province were identified and the flood-prone status of its cities was assessed. based on the results obtained, about 65% of the area of khuzestan province, which mainly includes the central and southern regions of this province, has high flood-surge potential due to its low elevation and slope and proximity to rivers. the results of this study also showed that out of a total of 43 cities in khuzestan province, 14 cities are in the very high flood potential class, 16 cities are in the high flood potential class, 12 cities are in the low flood potential class, and only one city is in the low flood potential class. the overall results of this study have shown that many cities in khuzestan province are at risk of flooding, so it is necessary to reduce the probability of flooding in this province by using structural and non-structural measures.