ارزيابي آسيب‌پذيري زمين‌لغزش‌هاي كم عمق با استفاده از مدل تلفيقي SIM و AHP در حوزۀ آبخيز خياوچاي

Application of SIM and AHP techniques for assessing of shallow landslide susceptibility in Khiov-chai watershed

ﺑﺮاي درك وﯾﮋﮔﯽﻫﺎي ا ﺳﺎ ﺳﯽ داﻣﻨﻪﻫﺎﯾﯽ ﮐﻪ ﻣ ﺴﺘﻌﺪ زﻣﯿﻦﻟﻐﺰشاﻧﺪ، ارزﯾﺎﺑﯽ آ ﺳﯿﺐﭘﺬﯾﺮي زﻣﯿﻦﻟﻐﺰش اﺑﺰار ا ﺻﻠﯽ ﻣﯽﺑﺎ ﺷﺪ. در اﯾﻦ ﻣﻄﺎﻟﻌﻪ، ارزﯾﺎﺑﯽ آﺳﯿﺐﭘﺬﯾﺮي زﻣﯿﻦﻟﻐﺰش ﺑﺎ اﻧﻄﺒﺎق روشﻫﺎي ﺷﺎﺧﺺ آﻣﺎري و ﻓﺮآﯾﻨﺪ ﺗﺤﻠﯿﻞ ﺳﻠﺴﻠﻪ ﻣﺮاﺗﺒﯽ اﻧﺠﺎم ﺷﺪ. 10 ﻋﺎﻣﻞ اﯾﺠﺎد زﻣﯿﻦﻟﻐﺰش در ﻧﻈﺮ ﮔﺮﻓﺘﻪ ﺷــﺪ ﮐﻪ ﻋﺒﺎرﺗﻨﺪ از: ارﺗﻔﺎع، ﺷــﯿﺐ، ﺟﻬﺖ، ﺳــﻨﮓﺷــﻨﺎﺳــﯽ، ﮐﺎرﺑﺮي اراﺿــﯽ، ﺗﺮاﮐﻢ زﻫﮑﺸــﯽ، اﻧﺤﻨﺎي ﺳــﻄﺢ ﺑﺎرﻧﺪﮔﯽ، رﺧﺴﺎرهﻫﺎي ژﺋﻮﻣﺮﻓﻮﻟﻮژي و ﺣﺴﺎﺳﯿﺖ واﺣﺪﻫﺎي ﺳﻨﮕﯽ ﺑﻪ ﻓﺮﺳﺎﯾﺶ. روش ﺷﺎﺧﺺ آﻣﺎري ﺑﺮاي ﺗﻌﯿﯿﻦ ارزش وزﻧﯽ )Si( ﺑﺮاي ﮐﻼسﻫﺎي ﻫﺮ ﻓﺎﮐﺘﻮر اﯾﺠﺎد ﻟﻐﺰش اﺳﺘﻔﺎده ﺷﺪ، روش ﺗﺤﻠﯿﻞ ﺳﻠﺴﻠﻪ ﻣﺮاﺗﺒﯽ ﺑﻪﻣﻨﻈﻮر ﺗﻌﯿﯿﻦ ارزش وزﻧﯽ )Wi( ﺑﺮاي ﻫﺮ ﻓﺎﮐﺘﻮر اﺳﺘﻔﺎده ﺷﺪ. ﻣﺠﻤﻮع ﺣﺎﺻﻞ Si و Wi ارزش ﺷﺎﺧﺺ آﺳﯿﺐﭘﺬﯾﺮي ﻟﻐﺰش )LSI( را ﺑﺮاي ﻫﺮ ﭘﯿﮑﺴﻞ اراﺋﻪ ﻧﻤﻮد. ﺑﺮ ﻣﺒﻨﺎي LSI ﺑﻪدﺳﺖآﻣﺪه ﻧﻘﺸﮥ آﺳﯿﺐﭘﺬﯾﺮي زﻣﯿﻦﻟﻐﺰش ﺗﻬﯿﻪ ﺷﺪ، ﺳﭙﺲ ﻣﻨﻄﻘﮥ ﻣﻄﺎﻟﻌﺎﺗﯽ در 5 ﮐﻼس آﺳﯿﺐﭘﺬﯾﺮي ﮔﺮوهﺑﻨﺪي ﺷﺪ. ﺗﺮاﮐﻢ زﻣﯿﻦﻟﻐﺰش ﺑﺮاي 5 ﮐﻼس آﺳﯿﺐﭘﺬﯾﺮي ﺣﺎﮐﯽ از وﺟﻮد ﺗﻄﺎﺑﻖ ﮐﺎﻓﯽ ﺑﯿﻦ ﻧﻘﺸﮥ آﺳﯿﺐﭘﺬﯾﺮي و دادهﻫﺎي واﻗﻌﯽ ﻟﻐﺰش ﻣﯽﺑﺎﺷﺪ. در اداﻣﻪ، ﻧﺘﺎﯾﺞ ﻧﻘﺸﮥ آﺳﯿﺐﭘﺬﯾﺮي زﻣﯿﻦﻟﻐﺰش ﺑﺎ اﺳﺘﻔﺎده از دادهﻫﺎي ﻣﺸﺎﻫﺪاﺗﯽ زﻣﯿﻦﻟﻐﺰش و روش ROC ﺑﻪﺻﻮرت ﮐﻤﯽ ﺻﺤﺖﺳﻨﺠﯽ ﺷﺪ. ﻧﺘﺎﯾﺞ ﺻﺤﺖﺳﻨﺠﯽ ﻧﺸﺎن داد ﮐﻪ AUC ﺑﺮاي ﭘﯿﺶﺑﯿﻨﯽ ﻣﺪل 95/2% ﻣﯽﺑﺎﺷﺪ. ﻧﻘﺸﮥ آﺳﯿﺐﭘﺬﯾﺮي ﻧﺸﺎن داد ﻣﻨﺎﻃﻖ ﺑﺎ ﺳﻨﮓﺷﻨﺎﺳﯽ ﺗﺮاسﻫﺎي آﺑﺮﻓﺘﯽ ﻗﺪﯾﻤﯽ و ﺟﻮان، ﻻﻫﺎر و ﺗﺮاﮐﯽآﻧﺪزﯾﺖ-ﺗﺮاﮐﯿﺖ ﭘﻮرﻓﯿﺮي ﺑﺎ درﺟﮥ ﻣﺘﻔﺎوﺗﯽ از ﺣﺴــﺎﺳــﯿﺖ ﺑﻪ ﻓﺮﺳــﺎﯾﺶ ﮐﻪ در ﺷــﯿﺐﻫﺎي 10 ﺗﺎ 40 و ﺑﯿﺶ از 60 درﺻــﺪ ﭘﺮاﮐﻨﺶ دارﻧﺪ ﺑﺴــﯿﺎر ﻣﺴــﺘﻌﺪ ﺷــﮑﺴــﺖ ﺷــﯿﺐ ﻣﯽﺑﺎﺷــﻨﺪ. ﻧﻬﺎﯾﺘﺎً ﻣﺸــﺨﺺ ﺷــﺪ ﻣﺪلﻫﺎي SIM و AHP ﺑﺮاي ﺑﺎزﻧﻤﺎﯾﯽ آﺳــﯿﺐﭘﺬﯾﺮي زمين لغزش موثر مي باشد

Landslide susceptibility assessment is a primary tool for understanding the basic characteristics of slopes that are prone to landslides. In this study, a landslide susceptibility assessment was accomplished, by adopting the Statistical Index Method (SIM) and the Analytic Hierarchy Process (AHP). Ten landslide causing factors were considered including: elevation, slope, aspect, lithology, land use, drainage density, plan curvature, precipitation, geomorphologic faces, and rock unit’s sensitivity to erosion. The SIM was used to determine the weighted value (Si) for classes of every landslide causing factor, the AHP was utilized to determine the weighted value (Wi) for every factor. The summation of the product of Si by Wi represent the landslide Susceptibility Index (LSI) value for every pixels. Based on the derived LSI, landslide susceptibility map (LSM) was produced then the study area was grouped into five susceptibility classes. The densities of landslide for five susceptibility classes implying there is a satisfactory agreement between the susceptibility map and the actual landslide data. In the following, the results of the LSM were quantitatively validated using observed landslide dataset and the receiver operating characteristic (ROC) method. The validation results showed that the AUC for prediction rate of model was 95.2%. The landslide susceptibility showed the areas with lithology of old terraces, young terraces, lahar, and porphyritic trachyandesite-trachyte with different degrees of sensitivity to erosion which distribute between 10–40% slope and more than 60% are very prone to slope failure. Therefore, SIM and AHP were found to be effective models for landslide susceptibility mapping.