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پژوهش های ژئومورفولوژی کمی - سال هفتم شماره 2 (پاییز 1397)
  • سال هفتم شماره 2 (پاییز 1397)
  • تاریخ انتشار: 1397/07/17
  • تعداد عناوین: 12
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  • سیدرضا حسین زاد، مهناز جهادی طرقی، فریبا پاک نژاد* صفحات 1-18
    حوضه آبریز تنگراه واقع در استان گلستان، یکی از زیر حوضه های رودخانه دوغ، به عنوان یکی از نواحی تحت خطر جریان مواد شناخته شده است. در سال های 1380 و 1381 طی یک بارش ناگهانی ، منطقه مورد نظر جریان مواد جبران ناپذیری را تجربه کرده است و خسارات جانی و مالی زیادی را محتمل شده است جهت بازسازی جریانات مواد قدیمی و اثبات وقوع این جریانات در حوضه از روش دندروژئومورفولوژی استفاده گردید، دندروژئومورفولوژی از تغییرات بوجود آمده در ساختار و حلقه های رشد درختان برای بازسازی زمان و نحوه عملکرد فرایند های ژئومورفیک استفاده می کند. بعد از عملیات میدانی و تعیین محدوده مطالعاتی نمونه برداری های لازم انجام شد. پس از آماده سازی نمونه ها، سطح نمونه ها با سمباده نرم صیقل داده شد و شمارش حلقه ها با میکروسکوپ اندازه گیری و ضخامت آنها پس از ترسیم روی کاغذ میلیمتری تغییر یافته، با دقت 1/0 میلی متر اندازه گیری شد و سال وقوع جریان مواد براساس تغییرات در حلقه ها و همچنین تعداد حلقه های رشد یافته در بافت پینه ای باسازی شد. همچنین مقاطع عرضی از محدوده نمونه برداری شده گرفته شده است که نتایج حاصل از آن حاکی از آن است که بیشترین زخم های ایجاد شده ناشی از جریان مواد سال 1380 با دبی پیک 64/850 حاصل شده است. با جمع آوری پانزده نمونه برداشتی و تجزیه و تحلیل حاصل از آن مشخص گردید که آنها مربوط به جریانات مواد سال 1380 و 1381 می باشند. با توجه به بررسی های انجام گرفته روی نمونه های گردآوری شده در حوضه آبریز تنگراه و تهیه پرسشنامه جهت تعیین اطلاع از وقوع جریانات مواد رخ داده در دهه های قبل به این نتیجه رسیدیم که در طی هفتاد سال اخیر جریانات مواد سال های نامبرده تنها سیلاب های رخ داده از نوع جریان مواد در این منطقه هستند.
    کلیدواژگان: حوضه آبریز تنگ راه، جریان مواد، بارش های ناگهانی، دندروژئومورفولوژی
  • فریبا اسفندیاری ، مسعود رحیمی، منصور خیری زاده صفحات 19-45
    پهنه بندی خطر وقوع زمین لغزش از جمله اقدامات اساسی در جهت مقابله و کاهش اثرات وقوع زمین لغزش می باشد. مناطق واقع در پیرامون جاده خلخال - سرچم از جمله مناطقی از استان اردبیل هستند که در معرض مخاطرات زمین لغزش می باشند. در این پژوهش، خطر وقوع زمین لغزش در این مناطق ارزیابی شده و به پهنه بندی و پیش بینی مکانی زمین لغزش های منطقه پرداخته می شود. داده های مورد نیاز از روی نقشه های توپوگرافی مقیاس 1:25000، نقشه های زمین شناسی مقیاس 1:100000 و 1:250000، تصاویر مدل ارتفاعی رقومی (DEM) ، تصاویر ماهواره ای Google Earth و Sentinel2 و مطالعات میدانی حاصل گردید. برای پیش بینی مکانی و پهنه بندی خطر زمین لغزش از مدل های آماری رگرسیون لجستیک و احتمالاتی فاکتور قطعیت استفاده شد. نتایج، نشان دهنده کارایی زیاد این مدل های کمی در پیش بینی مکانی و پهنه بندی خطر وقوع زمین لغزش منطقه مطالعاتی می باشد. نتایج نشان می دهد که در حدود 23 درصد از کل منطقه مورد مطالعه در کلاس خطر زیاد و بسیار زیاد قرار می گیرد. بخشی از جاده ارتباطی خلخال - سرچم به طول تقریبی 23 کیلومتر در پهنه های با خطر زیاد و بسیار زیاد احداث شده است. این جاده علاوه بر آسیب پذیر بودن در مقابل مخاطره زمین لغزش، به عنوان یک متغیر محرک باعث افزایش ناپایداری نیز شده است. در مقیاس کلی، زمین لغزش های منطقه توسط متغیر لیتولوژی کنترل می شوند. اکثر زمین لغزش ها بر روی دو واحد سنگ شناسی «تراکی بازالت - تراکی آندزیت» و «توف سنگی - برش آتشفشانی - لاهار» رخ داده اند. در مقیاس محلی، چندین متغیر دیگر بر توزیع فضایی زمین لغزش ها موثر بوده اند. متغیرهای شیب، جهت شیب، ارتفاع، دوری و نزدیکی به آبراهه های منطقه و مجاورت با جاده ها از جمله این متغیرهای مهم می باشند.
    کلیدواژگان: زمین لغزش، رگرسیون لجستیک، فاکتور قطعیت، سیستم اطلاعات جغرافیایی (GIS)، جاده خلخال - سرچم
  • لیلا کاشی زنوزی، هایده آرا *، محمد رحیمی صفحات 46-59
    این پژوهش به منظور بررسی رابطه واحدهای ژئومرفولوژی با پوشش گیاهی حوزه آبخیز زیلبرچای انجام یافته است. برای دستیابی به هدف تحقیق، با استفاده از عکس های هوایی، نقشه پوگرافی و تصاویر ماهواره لندست 8 نقشه واحدهای ژئومرفولوژی استخراج و طی بازدیدهای میدانی تصحیح هندسی شدند و نوع واحدها مطابقت داده شد. نقشه پوشش گیاهی با استفاده از شاخص NDVI از تصاویر ماهواره لندست 8 تهیه شد. معادله رگرسیونی خط خاک در هر یک از واحدهای ژئومرفولوژی با تاکید بر بازتاب باند مادون قرمز نزدیک و باند قرمز برآورد شد. سپس ضرایب همبستگی بین واحدهای ژئومرفولوژی، پوشش گیاهی و شیب معادله خط خاک با سطح معنی داری 01/0 درصد محاسبه شدند. پس از محاسبه ضرایب همبستگی به تفکیک برای هر یک از واحدهای ژئومرفولوژی، واحد Qt بیشترین همبستگی منفی با شیب خط خاک به میزان 948/0- و همبستگی مثبت با پوشش گیاهی به میزان 81/0 داشت و واحد mic دارای با شیب خط خاک همبستگی معنی دار درسطح 01/0 نداشت در حالیکه با پوشش گیاهی همبستگی مثبت 39/0 را نشان داد. با توجه به نتایج تحقیق چنین اسنتباط شد که با رابطه معنی داری بین پوشش گیاهی و شیب معادله خط خاک و واحدهای ژئومرفولوژی برقرار است بطوری که با افزایش شیب خط خاک، پوشش گیاهی همبستگی منفی بیشتری خواهد داشت و واحدهای ژئومرفولوژی که مبین پوشش گیاهی منطقه نیز می باشند، بنا به یافته های تحقیق رابطه معکوس با شیب معادله خط خاک دارند.
    کلیدواژگان: رخساره ژئومرفولوژی، ضریب خط خاک، پوشش گیاهی
  • کامران چپی، داود طالب پور* ، عطا الله شیرزادی صفحات 60-81
    هدف از انجام این پژوهش ارائه روش ترکیبی بیزین رگرسیون لجستیک و مقایسه کارایی آن با روش رگرسیون لجستیک به منظور تهیه نقشه پیش بینی مکانی وقوع حرکت های توده ای در استان کردستان می باشد. در ابتدا، بر اساس مرور منابع 18 عامل تاثیرگذار بر وقوع حرکت های توده ای شامل: درجه شیب، جهت شیب، ارتفاع، انحنای معمولی شیب، انحنای عرضی شیب، انحنای طولی شیب، شاخص توان حمل جریان، شاخص نمناکی توپوگرافی، شاخص طول و زاویه شیب، لیتولوژی، بارش، کاربری ارضی، فاصله از گسل، تراکم گسل، فاصله از رودخانه، تراکم رودخانه، فاصله از جاده و تراکم جاده انتخاب شدند. سپس، در روش رگرسیون لجستیک (LR) بر اساس سطح معنی داری آماری 7 عامل و در روش بیزین لجستیک رگرسیون (BLR) بر اساس شاخص Information Gain Ratio، 11 عامل به عنوان عوامل موثر انتخاب و جهتمدل سازی به کار گرفته شدند. ارزیابی مدل ها (داده های تعلیمی و داده های تست) توسط معیارهای Specificity، Sensitivity، Accuracy، درصد مساحت زیر منحنی ROC و ریشه میانگین مربعات خطا انجام شدند. نتایج ارزیابی مدل های مورد استفاده در این تحقیق نشان داد که اختلاف معنی داری در سطح 95 درصد بین کارایی و نقشه های پیش بینی مکانی تهیه شده برای مناطق حساس به وقوع حرکت های توده ای خاک با روش های BLR و LR مشاهده نشد و می توان از مدل BLR نیز به مانند مدل LR به عنوان یک مدل معیار استفاده نمود. لذا با روش LR حدود 26 درصد از مساحت استان کردستان در معرض حساسیت زیاد و خیلی زیاد به وقوع حرکت های توده ای (54 درصد مجموع حرکتهای توده ای) قرار دارد و با روش BLR حدود 33 درصد از مساحت استان کردستان در معرض حساسیت زیاد و خیلی زیاد به وقوع حرکت های توده ای (64 درصد مجموع حرکتهای توده ای) قرار دارد که نواحی غرب استان دارای پتانسیل بیشتری هستند.
    کلیدواژگان: زمین لغزش، تئوری بیزین، رگرسیون لجستیک، استان کردستان
  • مهران مقصودی *، کامیار امامی، عادل رسولی، عباس درخشان، یاسمن جلالی، سعید مرادی پور، فاطمه مرادی پور صفحات 82-96
    در تحقیق حاضر، پنج تاقدیس در بخش جنوبی گسل میناب و شرق آن توسط سه پارامتر مورفومتری تاقدیس شامل رویه های سه گوش، دره های شرابی و سینوسیته ی جبهه ی تاقدیس مورد بررسی و اندازه گیری قرار گرفته است؛ ضمن اینکه شواهد تکتونیکی و ژئومورفیک موجود در محدوده ی بررسی نیز مورد ارزیابی قرار گرفته است. داده های مورداستفاده شامل Dem 30 m منطقه، تصاویر ماهواره ای لندست و همین طور نقشه های زمین شناسی محدوده ی موردمطالعه است. روش تحقیق به صورت دو مرحله ی، محاسبه ی شاخص ها و ارزیابی شواهد انجام گرفته است. هدف از انجام این تحقیق ارزیابی منطقه از نظر میزان فعالیت تکتونیکی می باشد. نتایجی که از تحلیل محاسبه ی شاخص ها به دقت آمد نشان دهنده ی این است که از منظر ارزیابی و تحلیل شاخص رویه های سه گوش و دره های ساغری، یال های جنوبی تاقدیس ها و برحسب نتایج حاصل شده از بررسی شاخص سینوسیته ی جبهه ی تاقدیس، یال های شمالی، دارای بیشترین میزان فعالیت تکتونیکی می باشند. به طورکلی نتایج نشان می دهد که میزان فعالیت تکتونیکی در یال های جنوبی تاقدیس ها بیشتر می باشد و از میان تاقدیس های موردبررسی در دو شاخص دره های ساغری و سینوسیته ی جبهه ی کوهستان، تاقدیس شماره یک دارای بیشترین میزان فعالیت تکتونیک می باشد و بر اساس شواهد موردبررسی و پراکنش این شواهد، مشخص گردید که بیشترین تراکم شواهد مورفوتکتونیکی نظیر جابه جایی سازندها، گسل های پلکانی و تغییر مسیر رودخانه ها در محدوده و اطراف تاقدیس شماره 1 مشاهده شده است که این موضوع بر فعالیت های بیشتر تکتونیک در این منطقه دلالت دارد؛ بنابراین بر اساس نتایج به دست آمده از مجموعه ی عوامل موردبررسی، منطقه ی موردمطالعه از نظر تکتونیک فعال است و اثرات این فعالیت در شواهد مورفوتکتونیکی مشهود می باشد.
    کلیدواژگان: مورفوتکتونیک، رویه های سه گوش، دره های شرابی شکل، سینوسیته ی جبهه ی کوهستان، گسل میناب
  • حسن جعفری* ، هژیر محمدی صفحات 97-116
    شرایط آبگیری و سیکل هیدرولوژیکی حوضه های آبریز علاوه بر اقلیم به شرایط فیزیوگرافی و زمین شناسی نیز وابسته است. پیدایش دریاچه های متعدد با علل مختلف در محدوده های وسیع، امکان پذیر است ولی در حوضه ای به وسعت قزل اوزن، یک امر نادر و کم نظیر است. شناسایی هویت بعضی از آن ها فقط بادید فضایی امکان پذیر است. در این پژوهش مورفوژنز و چندنگارگی فرایندهای ژئومورفولوژیکی در پیدایش دریاچه های حوضه ی آبریز قزل اوزن، از زیرحوضه های دریای خزر، موردبررسی قرارگرفته است. تنوع لیتولوژی و گسل باعث شکل گیری شرایط متفاوتی در این حوضه شده که بالطبع در شکل گیری لندفرم‏های مختلف نقش داشته است. برای بررسی فضایی عوامل موثر در ایجاد یا سرریز شدن دریاچه های حوضه آبریز قزل اوزن، از DEM 30*30 مستخرج از سایت USGS و نقشه های توپوگرافی 1:50000 و زمین شناسی 1:100000 و 1:250000 استفاده شد. سپس با استفاده از نرم افزار Arc GIS & Arc map اقدام به رقومی نمودن لایه هایی همچون آبراهه ها و لیتولوژی و گسل گردید. با استفاده از نرم افزار Google earth محل های تجمیع آب شناسایی شد و محدوده ی آن ها ترسیم یا بازسازی گردید و طول، عرض و مساحت هریک از آن ها محاسبه شد. برای مستدل شدن دریاچه های یخچالی برف مرز دائمی کواترنری با استفاده از روش رایت و پورتر برآورد گردید و بر اساس آن، ارتفاع خط تعادل آب ویخ منطقه نیز مشخص شد. در منطقه قلعه چای بیش از 9 دریاچه یخچالی شناسایی گردید. برای تایید و مستند کردن دریاچه های یخچالی بر روی نمونه رسوبات محلی، عمل گرانولومتری انجام شد. نتایج دال بر این است که در حوضه ای به وسعت 50 هزار کیلومترمربع، دریاچه هایی با منشا یخچال، آتش فشان، لغزش، شیمیایی و توپوگرافیک شکل گرفته است. دراین بین، دریاچه های لغزشی کردآباد، بهترین شرایط را برای مطالعه دریاچه هایی فراهم می آورد که سرریز شده و از بین رفته اند.
    کلیدواژگان: دریاچه، کردآباد، لغزش، آتش فشان، یخچال
  • محمد معتمدی را، لیلا گلی مختاری*، شهرام بهرامی، محمدعلی زنگنه اسدی صفحات 117-139
    نیاز روزافزون به آب به ویژه آب شیرین، اهمیت شناسایی مناطق نفوذ و توسعه کارست که از ذخایر ارزشمند آبهای زیرزمینی می باشد، را ضروری می نماید. لذا هدف پژوهش حاضر بررسی پتانسیل نفوذ آب زیرزمینی حوضه آبریز روئین اسفراین با استفاده از مدلهای تحلیل سلسله مراتبی، آپلیس و آپلیس اصلاح شده می باشد. در این پژوهش، ابتدا لایه های اطلاعاتی شامل: لیتولوژی، تراکم خطواره و گسل، پوشش گیاهی، تراکم شبکه زهکشی، بارش، دما، شیب، جهت شیب، ارتفاع از سطح دریا، لندفرم های موثر در تغذیه، نوع خاک و فاکتور تصحیح (Fh) تهیه و مدلهای AHP، APLIS وModified-APLIS اجرا گردید. نتایج حاصل از اجرای مدل AHP که در 5 کلاس طبقه بندی شد نشان می دهد که مساحت ناحیه با پتانسیل نفوذ کم در سطح حوضه ناچیز و نزدیک به صفر است. پتانسیل نفوذ کم، متوسط، زیاد و خیلی زیاد به ترتیب0، 1/8، 1/15، 7/47 و 1/29 درصد سطح حوضه را به خود اختصاص داده اند و طبقه با پتانسیل نفوذ زیاد بیشترین وسعت حوضه و حدود نیمی از آن را پوشانده است. در روش APLIS نیز مساحت نواحی با درصد نفوذ خیلی کم، کم، متوسط، زیاد و خیلی زیاد به ترتیب برابر با 1/15، 9/17، 1/65 و 9/1 و در مدل APLIS اصلاح شده نیز به ترتیب 9/20، 1، 4/13، 4/63 و 5/1 درصد سطح حوضه را به خود اختصاص داده اند. به طور کلی می توان گفت که نخست مدل APLIS اصلاح شده با (85/0) و سپس مدل AHP (82/0) ، توانسته اند بالاترین ضریب همبستگی بین تعداد چشمه و مساحت طبقه و بیشترین ضریب شناسایی پتانسیل نفوذ در منطقه را به خود اختصاص دهند با این وجود هر سه مدل وضعیت قابل قبولی را از نظر ارزیابی نفوذ بویژه در طبقه زیاد در سطح حوضه به نمایش می گذارند. مناطق با نفوذ بالا در هر سه مدل منطبق بر قسمت های مرکزی و شرقی حوضه است که با مقایسه آن با زمین شناسی منطقه عمدتا بر سازند مزدوران-لار که در آنها خلوص آهک و دولومیت بیشتر است مطابقت دارند. همچنین مناطق با پتاسیل بالای نفوذ بر مناطق با تراکم زهکشی کم، منطبق هستند.
    کلیدواژگان: آب زیرزمینی، AHP، APLIS اصلاح شده، سازند مزدوران-لار، حوضه روئین
  • دنیا رابطی، مریم ده بزرگی *، سعید حکیمی اسیاب، رضا نوزعیم صفحات 140-157
    تکتونیک ژئومورفولوژی به عنوان دانشی ارزشمند در بررسی زمین ساخت پویاست که می تواند تاثیر تکتونیک فعال را بر رودخانه مشخص نماید. مطالعات مورفومتری به عنوان سنجش و توصیف کمی شکل ها و چشم اندازهای زمین تعریف شده اند. اندازه گیری های کمی شرایطی را فراهم می آورد تا با استفاده از آن ها به شناسایی وضعیت مناطق دارای تکتونیک فعال پرداخته شود. استخراج شاخص های ژئومورفیکی با استفاده از مدل های ارتفاع رقومی در محیط GISدر دو دهه گذشته، روشی سریع و دقیق در تحلیل حوضه زهکشیبوده است. به طوری که از این شاخص ها برای ارزیابی سریع فعالیت تکتونیکی اخیر در یک ناحیه خاص استفاده شده است. در این مطالعه زمین ساخت فعال البرز غربی درحوضه سپیدرود با اندازه گیری هفت شاخص ژئومورفولوژی ناهنجاری سلسله مراتبی (Da) ، انشعابات (R) ، انتگرال و منحنی فرازسنجی (Hi) ، برجستگی نسبی (Bh) ، تراکم زهکشی (Dd) ، ضریب شکل (Ff) و گرادیان طولی رود (SL) مورد ارزیابی قرار گرفت. ابتدا با استفاده از مدل ارتفاعی رقومی؛ حوضه ها و آبراهه های منطقه مورد مطالعه استخراج شد. پس از محاسبه شاخص ها در هر حوضه، فعالیت زمین ساختی آن به پنج رده تقسیم گردید. سپس برای هر شاخص نقشه پهنه بندی سطح فعالیت زمین ساختی اخیر در گستره مورد مطالعه ترسیم شد. در نهایت شاخص زمین ساخت فعال نسبی (Iat) به منظور تعیین سطح فعالیت زمین ساختی کل محاسبه گردید و منطقه مورد مطالعه به چهار رده فعالیت زمین ساختی بسیار بالا، بالا، متوسط و کم تقسیم شد. شاخص های اندازه گیری شده در هر زیرحوضه نشان می دهد که در زیرحوضه های منطبق بر گسل های منجیل، جیرنده، درفک و دیلمان و همچنین مناطق با تراکم گسلی بالا شاخص های اندازه گیری شده مقادیر بالایی را نشان می دهند که نشان دهنده تاثیر گسل های مذکور بر منطقه مورد مطالعه است.
    کلیدواژگان: تکتونیک ژئومورفولوژی، شاخص ژئومورفیک، فعالیت تکتونیکی، گسلش، البرز غربی
  • صیاد اصغری سراس کان رود *، ایمان علی بلواسی صفحات 158-182
    زمین لغزش به عنوان یکی از مخاطرات طبیعی در مناطق کوهستانی هر ساله منجر به خسارات زیادی می شود. حوضه آبریز سیمره چنار، با داشتن ویژگی های کوهستانی و شرایط طبیعی مختلف دارای استعداد بالقوه زمین لغزش است. هدف از این پژوهش، مقایسه مدل شبکه عصبی مصنوعی با مدل منطق فازی، جهت ارزیابی خطر زمین لغزش در حوضه سیمره چنار است. بدین جهت ابتدا پارامترهای موثر در وقوع زمین لغزش استخراج و سپس لایه های مربوطه تهیه شده است. سپس نقشه پراکنش زمین لغزش های رخ داده شده حوضه تهیه و با تلفیق نقشه عوامل موثر بر لغزش با نقشه پراکنش زمین لغزش ها، تاثیر هر یک از عوامل شیب، جهت شیب، سنگ شناسی، بارش، فاصله از گسل، کاربری اراضی، خاک، فاصله از آبراهه در محیط نرم افزار ArcGIS محاسبه گردید. در این مطالعه به منظور مقایسه مدل ها، در پهنه بندی خطر زمین لغزش حوضه سیمره چنار، از مدل های شبکه عصبی مصنوعی و منطق فازی استفاده گردید. در مدل شبکه عصبی مصنوعی الگوریتم پس انتشار خطا و تابع فعال سازی سیگموئید بکار گرفته شد. ساختار نهایی شبکه دارای 8 نرون در لایه ورودی، 14 نرون در لایه پنهان و 1 نرون در لایه خروجی گردید. پس از بهینه شدن ساختمان شبکه، کل اطلاعات منطقه در اختیار شبکه قرار گرفت و در نهایت با توجه به وزن خروجی، نقشه پهنه بندی زمین لغزش تهیه شد. در مدل منطق فازی از اپراتورهای عملگراجتماعفازی، عملگراشتراکفازی، عملگرضربجبری فازی، عملگرجمعجبری فازی، عملگرگاما فازی مدل منطق فازی استفاده شد. برای ارزیابی نتایج خروجی مدل های مورد استفاده در برآورد خطر لغزش منطقه از ضریب آماری کاپا استفاده شد. نتایج بدست آمده نشان می دهد که مدل شبکه عصبی مصنوعی با ضریب کاپای 91/0 مدل کارآمدتری نسبت به مدل منطق فازی در تهیه نقشه خطر لغزش های حوضه سیمره چنار است. از میان عوامل تاثیرگذار بر زمین لغزش در منطقه مورد مطالعه عامل شیب به عنوان مهمترین عامل و عوامل سنگ شناسی و خاک در مراتب بعدی قرار گرفتند. بر اساس پهنه بندی صورت گرفته با استفاده از مدل شبکه عصبی مصنوعی، به ترتیب 12/10، 92/22، 04/31، 76/20، 16/15 درصد از مساحت منطقه در کلاس های خطر خیلی کم، کم، متوسط، زیاد و خیلی زیاد قرار گرفته است.
    کلیدواژگان: زمین لغزش، شبکه عصبی مصنوعی، حوضه سیمره چنار، سیستم اطلاعات جغرافیایی، مدل منطق فازی
  • معصومه رجبی، میر اسدالله حجازی، شهرام روستایی، نگین عالی * صفحات 183-195
    حوادثی که به طور ناگهانی روی می دهند و موجب وارد آمدن خسارت به انسان و محیط می شوند، به عنوان مخاطرات طبیعی شناخته می شوند. این مخاطرات به دلیل ماهیت غیر منتظره ی خود، در بیشتر موارد خسارت مالی و جانی بسیاری بر جایی می گذارند. در بین مخاطرات طبیعی، زلزله و سیل جزو ویران گرترین مخاطرات به شمار می آیند. این مخاطرات در جوامع روستایی به دلیل ارتباط تنگاتنگ با محیط طبیعی و توان محدود در مقابله با این گونه تهدیدات، دارای شدت و قدرت آسیب رسانی بیشتری می باشند. لذا شناسایی مناطقی که دارای آسیب پذیری بیشتری از مخاطرات طبیعی هستند، می تواند در جهت برنامه ریزی برای مقابله با کاهش اثرات این حوادث موثر باشد. پژوهش حاضر با هدف پهنه بندی آسیب پذیری مخاطرات طبیعی سیل و زلزله به بررسی تاثیر عوامل ژئومورفولوژیکی بر رخداد مخاطرات طبیعی پرداخته است. تحقیق کاربردی و روش انجام آن توصیفی _ تحلیلی می باشد؛ آمار و اطلاعات مورد نیاز از طریق مطالعات کتابخانه ای و داده های سنجش از دور جمع آوری گردیده است. برای پهنه بندی آسیب پذیری مخاطرات طبیعی سیل و زلزله، محاسبه نقش هرکدام از فاکتورهای ژئومورفولوژیکی تاثیرگذار در وقوع این مخاطرات طبیعی از روش AHP استفاده شده است. سپس با استفاده از قابلیت های تحلیل مکانی GIS لایه های نهایی پهنه بندی خطر زلزله و سیل تهیه گردیده است. یافته های تحقیق نشان می دهد از کل روستاهای موجود در شهرستان سقز 145 روستا در پهنه با خطر نسبتا بالا و 135 روستا در پهنه باخطر نسبتا متوسط زلزله قرار گرفته اند. همچنین پهنه بندی روستاها بر اساس احتمال وقوع زمین لرزه نشان داد 240روستا در پهنه با احتمال وقوع کم و 40 روستا نیز درپهنه با احتمال وقوع متوسط قرار دارند، سایر روستاها در پهنه با احتمال ضعیف خطر وقوع زلزله قرار دارند.
    کلیدواژگان: شهرستان سقز، مخاطرات طبیعی
  • داریوش ابوالفتحی، عقیل مددی *، صیاد اصغری صفحات 196-208
    رسوبات رودخانه ای به دو صورت منتقل میشوند: یا این مواد درون جریان آب غوطه ور هستند و همراه با آب در حرکت می باشند که به آنها مواد رسوبی معلق گفته می شود و میزان مواد رسوبی معلق را که در واحد زمان از یک مقطع رودخانه عبور کند، بار معلق مینامند، یا اینکه به یکی از صور لغزش، غلتیدن، پرش حرکت مینمایند که به آنها بار بستر می گویند. شبکه عصبی مصنوعی روشی است که بر پایه شبیه سازی عملکرد مغز انسان برای حل مسایل متنوع ارایه و از لایه های نرون ورودی، خروجی و میانی و وزنهای مربوط به مقادیر ورودی و بایاس و تابع تحریک تشکیل شده است. منطقه مورد مطالعه در این پژوهش حوضه آبریز رودخانه گلرود است. این منطقه در شهرستان بروجرد، در استان لرستان در غرب ایران واقع شده است، پژوهش حاضرازنوع کاربردی ست. بدین صورت که، ابتدا مشخصات زیرحوضه های این رودخانه استخراج شده است این مشخصات شامل مشخصات فیزیکی زیرحوضه ها از جمله مساحت، محیط و طول آبراهه ها و مشخصات مربوط به دبی رودخانه و میزان رسوب آن است. در ادامه با روش های رگرسیون خطی چند متغیره، شبکه عصبی پیش خور چندلایه (MLP) و شبکه عصبی برپایه تابع شعاعی (RBF) به مدل سازی تخمین رسوب پرداخته شده است. پس از محاسبه شاخص های RMSE و MAE با توجه به این امر که هرچقدر میزان این شاخص ها کمتر باشد مقدار پیش بینی شده به مقادیر واقعی نزدیکتر است بنابراین باتوجه به شواهد حاصله مدل شبکه عصبی مصنوعی MLP دقت بهتری را نسبت به دو مدل دیگر در تخمین میزان رسوب منطقه نشان میدهد. از سوی دیگر با توجه به مقدار شاخص R2 که برای سه مدل محاسبه شده است دقت تخمین مدل به مقدار 0. 409 برای مدل MLP محاسبه شده است، مقدار R2 برای این مدل برابر 0. 88 است. پس از مدل شبکه عصبی مصنوعی MLP، مدل شبکه مصنوعی RBF نتایج بهتری ارائه می دهد. در این مدل مقدار R2 برابر است با 0. 4 که نشان دهنده دقت تخمین حدود نصف مدل MLP است. و در رتبه سوم نیز مدل رگرسیون خطی چند متغیره با مقدار R2 برابر با 0. 3 قرار دارد. مدل رگرسیون خطی نیز به علت این امر که تنها روابط خطی بین متغیر ها را در نظر می گیرد دارد بیشترین میزان خطا است.
    کلیدواژگان: گلرود، شبکه عصبی، تخمین رسوب، رگرسیون خطی، MLP، RBF
  • محمد شریفی کیا، سیاوش شایان، مجتبی یمانی، علی رضا عرب عامری * صفحات 209-223
    الگوی شبکه زهکشی از بارزترین لندفرم های سطح زمین محسوب می گردد که تحت تاثیر فرآیندهای دامنه ای شکل می گیرند و گسترش مکانی این عارضه به میزان عملکرد این فرآیندها بستگی دارد. هدف از این پژوهش قابلیت سنجی داده های فرکانس پایین راداری در استخراج الگوی زهکشی دامنه ها در نواحی فشرده جنگلی می باشد، بدین منظور به ارزیابی مقایسه ای مدل های رقومی ارتفاعی ASTER، SRTM و مدل رقومی ارتفاعی حاصل از داده های فرکانس پایین راداری PALSAR در استخراج شبکه های زهکشی پرداخته شده است. ابتدا مدل های رقومی ارتفاعی در محیط Archydro اصلاح و شبکه های زهکشی در محیط ArcGIS10. 2 استخراج گردید. جهت استخراج شبکه های زهکشی از آستانه های سلولی 100، 500، 1000 و 2000 استفاده گردید. طبق نتایج مدل رقومی ارتفاعی داده های فرکانس پایین راداری PALSAR با آستانه سلولی 100 با استخراج 8025326 متر آبراهه بهترین دقت را نسبت به مدل های رقومی و آستانه های سلولی دیگر داشته است. نتایج بررسی تراکم زهکشی نیز نشان داد که در مدل رقومی ارتفاعی حاصل از داده های راداری PALSAR 71/ 1026 کیلومتر مربع (83/70 درصد) از منطقه مطالعاتی در طبقه تراکم خیلی زیاد (بیش از 8) قرار گرفته است که این موضوع بیانگر کارایی بالاتر مدل رقومی ارتفاعی حاصل از داده های فرکانس پایین راداری PALSAR در استخراج شبکه های زهکشی می باشد. نتایج بررسی تراکم زهکشی استخراج شده در مناطق جنگلی فشرده نشان داد که از کل مساحت 06/717 کیلومتر مربع جنگل های فشرده در منطقه، بر اساس نتایج حاصل از مدل رقومی ارتفاعی فرکانس پایین راداری، 62/73 درصد (97/520 کیلومتر مربع) از مساحت جنگل های فشرده در کلاس تراکم زهکشی بسیار بالا (بالاتر از 8) قرار گرفته است در حالی این مساحت در مدل رقومی ASTER، تنها 033/0 درصد (240/0 کیلومتر مربع) و در مدل رقومی ارتفاعی SRTM، 672/0 درصد (827/4 کیلومتر مربع) می باشد که این موضوع نشانگر توانایی داده های فرکانس پایین راداری در نفوذ از مناطق جنگلی و استخراج شبکه های زهکشی زیر جنگل با دقت بالا می باشد.
    کلیدواژگان: الگوی زهکشی، تصاویر راداری، جنگل متراکم، بهشهر
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  • seyedreza hoseinzadeh, mahnaz jahadi toroghi, fariba paknejad Pages 1-18
     
    Introduction
    Flash floods are localized hydrological phenomena occurring in small catchments of a few to a few hundred square kilometers, with response times typically being a few hours or less As a result, they represent one of the most significant natural hazards with serious death tolls and economic damage at a worldwide level in general and in Mediterranean mountain catchments in particular.( Villanueva, 2010:383). Dendrogeomorphology is one of the subdivisions of dendrochronology (bah rami, 1389:1). Which is based on the analysis of the annual growth trees of trees for the age of geomorphic processes (Butler,2013:717). Geomorphic processes may influence trees in various ways The impact of rocks and boulders or abrasion processes may cause scars to the stem surface or even decapitate trees. Unilateral pressure of flowing material can result in a tilting of the stem. Finally material may bury the stem base when deposited. Affected conifer trees react to these impacts with callus tissue, tangential rows of traumatic resin ducts the formation of reaction wood or with an abrupt growth suppression or release gives an overview of the different impacts of debris flows on trees and their reactions to the disturbances(Bollschweiler,2007:340).
    Methods and material
    To collect tree samples (dendrogeomorphology), the following is done. Primary visits (from wounded trees in the main bed of the region) were carried out for sampling in April, June and July, 2014 and April, 2016. In field operations, instruments such as GPS to record sample locations, meters are used to measure sample diameter and hand saw for sample sampling. During the sampling operation, 15 samples of damaged trees were selected. During the sampling, the sample was attempted from the main canal to reduce the probable extent of other damage (human injury) and, of course, the damage was caused by the collision of the coarse sediments of the debris flow on the trees . After sampling, they were exposed to sunlight for drying for one month. After drying, each fifteen samples were polished by soft molding and transferred to the lab for examination, and their age was precisely determined using a microscope.

    Results and discussion
    The purpose of this study was to determine the aging of floods with debris flow that occurred in pre-flood years in 2001 and 2002 in the region, as well as the reconstruction of debris flows in the catchment area of ​​Tangrah. Due to lack of station in the basin, the dendrogeomorphology method is the best method for accurate estimation of heavy floods in this area. The area under study is located in a mountainous forest covered area. During the years 2001 and 2002, with the advent of a sudden precipitation, the region experienced various currents. Because of this, trees and stones have been damaged by these currents. Due to these injuries, the precise age of these floods and floods that occurred in the past can be determined. Samples taken more than the original bedding, it is certain that these trees were most affected by the flood. Also, using the dendrogeodomorphological method of damaged tree rings and determining the age of wounds in the region, the maximum instantaneous flow of two flows was calculated using Manning method.

    Discussion and
    conclusion

    The results of this study indicate that the most injuries caused by the flow of debris flow in 2001 with Volumetric flow rate 840.68 m3/s. The analyzing of Fifteen samples showed that these flows were related to 2001-2002 debris flows. According to surveys on the gathered samples in the tan drainage basin and questionnaire for determining the debris flow occurrence in previous periods, we concluded that during the past seventy years, the debris flows of 2001 and 2002 are the only large in this debris floods the tangrah catchment
    Keywords: Tangrah Catchment basin, Debris Flow, Storm rain falls, Dendrogeomorphology
  • fariba esfandiyari*, masoud rahimi, mansour kheirizadeh Pages 19-45
     
    Introduction
    The occurrence of landslides is the result of the interaction of complex and diverse environmental factors. These factors are divided into the trigger and the primary cause. Landslide occurrence triggers include weathering, earthquakes, rainfall and snow melting. Human activity like construction of roads and buildings on steep slopes and dispersal of water from supply systems and sewers could also trigger the occurrence of the phenomena (Cubito et al., 2005). Landslide susceptibility mapping involves handling, processing and interpreting a large amount of territorial data. Thus, Geographical Information Systems (GIS) have proved to be very useful in susceptibility evaluation (Aleotti and Chowdhury, 1999; Ayalew et al., 2005), as it allows frequent updating of the database related to spatial distribution of the landslide events and their predisposing factors, as well as the susceptibility assessment procedures (Aleotti and Chowdhury, 1999). Landslide susceptibility mapping relies on a rather complex knowledge of slope movements and their controlling factors. The reliability of landslide susceptibility maps depends mostly on the amount and quality of available data, the working scale and the selection of the appropriate methodology of analysis and modeling. In this research, several quantitative approaches in order to landslide hazard zonation were used for the area along the Khalkhal-Sarcham Road. The study area with geographic coordinates between 37º 19′ to 37º 36′ N latitudes and 48º 50′ to 21º 01′ E longitudes is located in Ardabil province.

    Materials and Methods
    In this research, for assessment and landslide zonation ten factors affecting landslide occurrence, which include: elevation, slope, aspect, streams, faults, topographic features, lithology, land use, vegetation and communication road was considered. Required data were obtained from the topographic maps with scale of 1:25000, geological maps with scale of 1:100000, digital elevation model (DEM) 12.5 meter from ALOS – PALSAR satellite, Sentinel (Spatial resolution of 10 meter), Google Earth satellite images and field studies. In landslide hazard zonation using the GIS, the most important part of the study is preparation of the landslide distribution map or landslide inventory. Therefore, field works was done in order to identification of landslides and preparation of landslide inventory. In this study for assessment and landslide zonation were used certainty factor and logistic regression quantitative approaches.
    Results and discussion
    In this research, landslide events risk use certainty factor and logistic regression quantitative approaches was evaluated. Certainty factor model is a probabilistic bivariate model and suitable for landslide hazard zonation. This model provides reasonable results for the study area. Also for zonation by using multivariate statistical methods, was used logistic regression, which is one of the most suitable methods for landslide hazard zonation. The results from this method were detected as the most favorable model among the investigated models. For the studied area, 98 large and small landslides were identified and delineated through satellite images of high resolution satellite image and field observations. Most of these landslides have occurred from the north-east, south-west trend, from the Kahran and Esmarud villages to the Gheshlag and Gorjagh villages. A significant number of landslides have occurred around the Khalkhal-Sarcham communication road between of Kabodchi to Gheshlagh villages. The results show that total landslide area of the region is about 650 hectares. In terms of percentage of high and very high risk class area, these methods represent fairly similar results, so that can say that approximately 23 percentage of the study area is located in the high and very high risk class.

    Conclusion
    This research has been carried out to identify areas of potential Landslide in the Khalkhal-Sarcham communication road. In this regard, logistic regression and certainty factor model were used. This communication road is very important for landslide occurrence. According to the results that between the factors affecting the occurrence of landslides in the region, lithological conditions play an important role. Construction of a communication road on these landslide sensitive units has increased the risk of landslide events. The slope and elevation variables also have a large effect on the landslide occurrence in the area. The impact of other conditions can be considered locally. Therefore, slope instabilities in all of the spatial planning should be considered in this area
    Keywords: Landslide Zonation, Certainty Factor, Logistic Regression, Geographic Information System, Ardabil-Khalkal Road
  • laila kashi zenoozi, haydeh Ara, mohammad rahimi Pages 46-59
     
    Introduction
    Over the past few decades, various vegetation indices derived from the reflection of various satellite wavelengths (generally a combination of near infrared and infrared bands) have been used to estimate biophysical characteristics of vegetation such as leaf area index (LAI), biomass, Plant growth and percentage of coverage, each of which, depending on the conditions in the study area, has shown good results (Qi et al.,1994; Rondeaux et al., 1996; Huete et al., 1997; Rouse et al., 1974) Generally, vegetation density is affected by a variety of environmental conditions such as climate, soil, geology and geomorphology (Abbate et al., 2006)

    Materials and Methods
    Determination of geomorphologic units, types and facies Providing vegetation map To prepare a vegetation map, Landsat 8 satellite imagery was prepared from Google Earth in 2017 and previewed images containing geometric and radiometric corrections. The NDVI index was extracted from 4 and 5 bands of Landsat 8 satellite images of Zilberchay watershed and classified into 12 classes. In the next step, the canopy measurements in the studied area were carried out within a representative area along the transect line. The purpose of vegetation is the shading level of any one. For this purpose, 1 × 1 m plot was used for vegetation diversity and vegetation form.


    Calculation of soil gradient in each geomorphologic unit
    In this study, in order to calculate the soil line equation, the geomorphic units were matched with satellite imagery. In each geomorphologic unit 60 pixels and in the amount of 720 pixels of soil were extracted using the position of geomorphic units and by plotting the reflection values of these pixels in the range The red and infrared bands near the soil line coefficients were calculated for each unit of geomorphology.

    Calculation of correlation coefficient
    To study the type and severity of relationships between geomorphic units and vegetation of the region, as well as the slope of the correlation coefficient line between them. Pearson correlation coefficient was calculated between vegetation values and gradient of soil line and geomorphic units (after encoding them).

    Results
    Since there is a reverse relationship between vegetation and slope of the soil, geomorphology of Zilberchay watershed has a positive correlation with the vegetation cover and showed a negative correlation with the gradient of the soil coefficient. After calculating the correlation coefficients for each geomorphology unit, Qt had the highest negative correlation with the slope of the soil line to -0.988 and positive correlation with vegetation was 0.18 and the mic unit with soil gradient correlation There was no significant difference in the level of 0.01, while the vegetation showed positive correlation of 0.39. Also, the hio unit with the gradient of soil and vegetation cover was Pearson correlation coefficient of -0.45 and 0.62, respectively. The hio unit has more levels of rocky and vegetation-free extinction and a weaker correlation with other units.

    Discussion
    Due to changes in soil characteristics, vegetation cover vegetation indices, which are presented in remote sensing sciences, often have errors. According to studies conducted by some researchers, the NDVI index can not quite accurately indicate the percentage of vegetation in arid regions, and the indicators that consider soil reflection can more accurately determine the percentage of vegetation in the study estimate (Darvishade et al., 2008). The findings of the research also show that each of the geomorphologic facies that have better vegetation cover have a more negative correlation with the soil line coefficient. Regular domain facies, in comparison with irregular domain facies that are better off of vegetation, have the same negative correlation with soil line factor. The soil factor coefficient is a Therefore, for the assessment of vegetation using remote sensing, it is better to use the modified indicators that have been applied to the land line, such as MSAVI, MCARI2, MTVI2 (Alavi Panah, 1390).for reducing the effects of spectral properties of soil on spectral reflections of the crown
    Keywords: Geomorphologic unit, Soil coefficient, Vegetation cover
  • kamran chapi, davod taleb poor*, ataolah shirzadi Pages 60-81
     
    Introduction
    Geomorphological hazards such as mass movements are one of the potentially harmful phenomena. Landslides as one of the most traditional earth movements involved all slope failures in which a mass of materials (soil and rock) moves down the slope due to decreasing of safety factor and overcoming of the destructive forces on the resistance forces on a slope.
    Kurdistan province has been frequently exposed to mass movement hazards owing to its characteristics of topography, geomorphology, pedology, geology and climatology. Therefore, the objective of this study is 1) to prepare the spatial prediction map of mass movements for the Kurdistan province to manage the areas prone to the hazards and to use the map in the land use planning projects and development of the rural regions 2) to introduce the Bayesian logistic regression (BLR) ensemble and to compare its efficiency with the logistic regression (LR), and 3) to identify the most significant conditioning factors on mass movements occurrence in the Kurdistan province.
    Methodology
    Based on the literature review, 18 factors affecting landslide susceptibility were selected for modeling including slope degree, slope aspect, elevation above sea, curvature, profile curvature, plan curvature, stream power index, topographic wetness index, length-angle of slope, lithology, rainfall, land use, distance to fault, fault density, distance to stream, stream density, distance to road, and road density. A total of 895 mass movements in the Kurdistan province were divided into 70 % (626 locations) for modelling using training dataset and 30% (269 locations) to evaluate based on the validation dataset. Additionally, 626 locations were randomly selected as areas where mass movements have not occurred and they were classified into 70% and 30% for training and validation in modelling process. Based on the Information Gain Ratio index to modelling process, 7 factors were then applied to the LR method and 11 factors were used in the BLR method. The evaluation of models were performed using Specificity, Sensitivity, Accuracy, the area under the Receiver Operating Characteristic Curve (AUROC), and the Root Mean Square of Errors (RMSE) indices.
    Result and
    discussion
    According to the results of spatial prediction of mass movements by quantile approach, about 8.06% of the Kurdistan province area is very sensitive to mass movement occurrence using the LR model; while, the BLR model shows a sensitive area of about 12.46%.
    The majority of very sensitive and sensitive areas are located to the west of the province. These regions include Oramanat mountainous areas, Kosalan and Chelchama highlands, the Salvatabad Saddle (East of Sanandaj), the Morvarid Saddle (between Sanandaj and Kamyaran), The Khan Saddle (between Saghez and Baneh), and the Arez Saddle (between Sanandaj and Marivan).
    In order to assess the spatial map accuracy of mass movement sensitive areas prediction, both training and validating datasets were used. The results showed that the area under the curve of SRC is 0.714 in LR based on training data, indicating that this approach has a potential of 71.4 percent to predict sensitive areas to mass movement. BLR showed a value of 0.672 using the same data which implies a potential of 67.2% for prediction of sensitive areas.
    Based on the validating dataset, the area under the curve of PRC was 0.732 and 0.729 for LR and BLR, respectively. These results confirmed the accuracy of the maps prepared by both models; however, it should be noted that LR was slightly providing better results.
    To analyze the probability of mass movement occurrence, the potential of the LR and BLR models were evaluated using Friedman test at 5% significant level. The test revealed that there is no significant difference between these two models and both are reasonably able to evaluate spatial prediction of mass movements.
    Conclusion
    The results showed that there is no significant difference (95% level of significance) between the efficiency and the susceptibility maps prepared by the two models for spatial predicting of landslide in the study area; therefore, the BLR model can be applied as an index model for the study area and other similar areas.
    Therefore the hybrid model of Bayesian Logistic Regression has a high capability of identifying sensitive areas to mass movement such that it can be compared with previously successfully testes methods such as artificial neural network, fuzzy logic, decision tree algorithms (Naïve, Random Forest, Baes Forest, …)
    Keywords: Landslide, Bayesian Theory, Logistic Regression, Kurdistan Province
  • mehran maghsoudi*, kamyar emami, adel rasouli, abbas derakhshan, yasaman jalali, saeed moradipoor, fatemeh moradi poor Pages 82-96
     
    Introduction
    Sudden movement towards the development of quantitative geomorphology in recent decades was, leading to the development of statistical methods and mathematical models to describe the geomorphological processes. This led to the establishment of a wide range of geomorphological little useful the interpretation of changing processes - poured have been tectonic activity in the study areas. (Avena et al, 1967; Buonasorte et al, 1991; pike, 1993; Merta, et al, 2005). Assessment of buildings and landforms of earth during its foundation, subject knowledge has been a tectonic geomorphology (Stanley et al., 2000). Endless competition between tectonic processes that have the desire to create ripples and surface processes that tend to eliminate and smooth out unevenness, the core concept of is tectonic geomorphology.
    Eastern region strait of Hormuz (MINAB fault on its eastern and southern part of the fault system) affected by tectonic forces are, a variety of forms that morphotectonic check how the emergence of and these shapes correlated with tectonics of the region can help to solve many of the questions about the evolution of tectonic and geomorphological is related to the in area of Iran.

    Methodology
    The data used in this research includes the geological maps 1:250000 and 1:100000 of the region for identification of the faults, the digital elevation model data (DEM of 30 meters of the region) for mapping the location of the region, and the information of Landsite Satellite and Google Earth images to measure the parameters and assess the tectonic evidences of the region. With the help of the listed data, as well as GIS and Google Earth applications, the morphometric parameters of the anticline is computed, which contains this three main parameters: the triangular facets, wine glass, and anticline front sinuosity.

    Result and
    discussion
    In this study, a total of 251 triangular facets on 5 anticline were identified of these a number 88 triangular facets in the anticline 1, 32 triangular facets in the anticline 2, 43 triangular facets in the 3,65 triangular facets in the 4, and 23 triangular facets in the anticline 5 Identify and were measured. Also in this the study, 185 wine glass valley identified in the anticlines, the number of there were , 64 wine glass valley in the anticline 1, 18 wine glass valley in the anticline 2, 28 wine glass valley in the anticline 3, 47 wine glass valley in the anticline 4, and 28 wine glass valley in the anticline 5. According to Table 4, Sinuosity index in anticline 1 is less on the northern slopes of the southern slopes; also the index of the anticlines number 2 and 3 is less on the northern slopes of the southern slopes. But the index, in the anticline 4 and 5 this less in the southern slope.

    Conclusion
    Generally, the results indicate that the tectonic activity in the southern edges of the anticlines is higher, and among the studied anticlines in the two parameters of wine glass valleys and mountain front sinuosity, the anticline number 1 has the highest tectonic activity (Table 5), and according to the reviewed evidences, and the dispersal of these evidences showed in Figures 3 and 4, it was determined that the most density of the morphotectonic evidences, like the displacement of the formations, the staircase faults, and the redirection of the rivers, has been observed in the area of and around the anticline 1, which indicates that the tectonic activity in this region has been more. In general, the results of parameters and the examined evidences indicate that the active tectonic has been dominant in the area. After anticline 1, the anticlines that have had the most tectonic activity are anticline number 4, anticline number 3, and anticline number 2, respectively, and anticline number 5 has had the lowest tectonic activity. The concordance between the conducted field studies and literature review, and the results of the parameters, and the distribution and type of evidences, indicate the proper application that these parameters have in evaluating the tectonic activity. The results of this study can be used for land use planning including risk mapping, prioritization of immunization in areas with higher risk measures, in order to achieve the stabilization of the environment. Based on the conducted field surveys, an earthquake of magnitude 5 on the Richter scale (May 1392) in the upstream basin of the studied anticlines caused the evacuation of many rural housing by residents because of fear of recurrence of the earthquake. The evacuation was to the extent that some of the villages lost more than 80 percent of their population, and the evacuated population flooded in the neighboring towns. The loss of agricultural land in rural areas, the increase of the potential for soil loss, and the loss of self-employment opportunities in the villages are the other consequences of this earthquake and the same earthquakes that may hit the area in the future.
    Keywords: Morphotectonics, triangular facets, wine glass, sinuosity of the mountain front, MINAB fault
  • hasan jafari*, hazhir mohamadi Pages 97-116
     
    Introduction
    The dewatering and hydrological conditions of the basins, in addition to the climate, depend on the physiographic and geological conditions. The emergence of numerous lakes with different origins in large areas is possible, but in a basin with an area of the Ghezloosen, it is a rare and uncommon thing. Known identity some of them are just spatial viwepoint. In this study, with a spatial viewpoint, the classification of the lake's morphogenesis and the multivariate effects of the environment and geomorphologic processes in the emergence of each of them. The basins area of Qezelowzan is among the Caspian Sea sub basins. The variation in lithology and faults has led to the formation of different conditions in this basin, so that has contributed to the formation of different landforms. One of the processes involved in the formation of landforms is stagnant waters, which is referred to as the process of the lake.
    Materials and Methods
    For investigate the factors to create or to change of Qezelowzan basin lakes, the DEM 30 * 30 and extracted from the USGS, and topographic maps of 1: 50,000 and 1: 100000 geological and 1: 250000 was used. Using Arc GIS & an Arc map was digitized the layers such as waterway network, lithology, and faults. Using the Google Earth software, water aggregation sites were identified and their area was mapped or reconstructed, and the length, width, and area of each of them were calculated. For the reasoning of glacial lakes, the quaternary permanent boundary was estimated using the Wright and Porter method and based on this, the height of the equilibrium line was also determined. In Qaleh chai area more than 9 glacial lakes were identified. Granulometry was performed to confirm and document glacier lakes on local sediment samples.
    Discussion and
    results
    The basin area of Qezelowzan is more than 50 thousand square kilometers. The location of this basin is such that the junction and interference of morphtectonic land units of Central Iran, Alborz, Northwest of Iran, Sanandaj-Sirjan and Zagros. Such a situation leads to the emergence of different landforms influenced by many internal and external processes such as volcanoes, fracture, rupture, glacial, landslide, and changing levels are basically in the basins. Among these landforms, what is discussed in this article is landforms related to stagnant waters. The location of the accumulation of runoff in a region is recognizable by the convergent waterway network, which can be scarified after the evolution of the lake, with the help of the surface levels and the drains and the remaining convergent drainage network (Fig. 3). According to such evidence, 22 lakes were identified in the catchment area of Qezelowzan. 2 Kurd bad lakes in the Tarom area, 2 lakes in the southeastern slopes of the Sahand volcano, 9 lakes in Qalehchai, 6 lakes in Dandy, and 6 lakes as geonurons in the Qezelowzan.
    Conclusion
    The results indicate that lakes of glacier, volcanic, landslid, chimestry and topographic origin are formed in 50,000-square-meter basins. The fault lines and mountins trands in this basin are such that Qezelowzan has to cut off their axis to reach the Caspian Sea. These conditions have triggered a period of time from places such as Bijar, Zanjan, Mianeh and Tarom as local lakes. Volcanic activity has caused the formation of two Almalo and Chogar Lakes in the this basin. The hight elevation of the different parts of the basin and the latitude above that area have provided for the quaternary glacial processes. In the part of the basin where the height and lithology conditions were favorable, the glacial could create U-shaped valleys, with the retreat of the glacier, the conditions for the capture of some of them were provided and created a lake. Most of these lakes have disappeared at the time of glacier retreat by changing the level of local rivers and domination of desertification erosion in the region. The earthquake of 1986 in the Tarom-Manjil region has created several lakes, one of which is the Kurd bad or Baklour Lake, which has slipped lakes by blocking part of the Ghangolichay River route. Changes in the water inputs of these lakes have caused them to become lakes only during the year. These lakes can be a living proof that during the Quaternary, Pasadenian orogeny movements created the final form of the Alpine-Himalayan fissures, causing numerous lakes to land on strikes that have been lost due to overflow.
    Keywords: Lake, Kurdabad, slip, volcano, Glacier
  • mohammad motamedi rad, laila goli mokhtari*, shahram bahrami, mohamadali zanganeh asadi Pages 117-139
     
    Introduction
    Groundwater resources are the most important parts of the available freshwater to humans. Due to the uneven distribution of time and location of surface waters and the high potential of these waters pollution, demand for groundwater for drinking, agricultural and industrial purposes is increasing. Therefore, it can be noted that groundwater resources and groundwater recharge are very important and identification of groundwater infiltration zones is a key component in arid and semi-arid regions studies. One of the most important methods of groundwater study is the study of factors affecting this process such as lithology, lineaments and fault density, vegetation, drainage system density, precipitation, temperature, slope, aspect, elevation, effective landforms in infiltration, soil type, infiltration coefficient is a survey of geological and topographic maps using remote sensing tools with satellite data processing, geological mapping and topography. In this study, we evaluated the infiltration potential using the AHP, APLIS and Modified APLIS models in the Roein Esfarayen basin. The basin has an area of ​​127.8 km in the eastern Alborz Zone (Binalud-Aladagh Zone), where significant lithology variation is evident. This basin is a part of the Aladagh-Binalud earth-tectonic zone, due to its large and tectonics, which is hard-fisted, faulty, and friable, with a large or large reverse fault angle.
    Methodology
    Initially, according to various studies about the recharge of groundwater resources, the factors controlling nutrition in the study area include lithology, lineament and fault density, vegetation cover, drainage system density, elevation, precipitation, temperature, soil cover, slope, aspect, intensity of vegetation cover (NDVI), effective landforms in nutrition and correction factor have been evaluated. The abovementioned data are from geological maps of the Organization of Geology and Mineral Exploration of the country with a scale of 1: 100,000, topographic maps with a scale of 1: 25,000 mapping organizations, precipitation data and annual temperature of the Ministry of Energy, land use map of the Natural Resources Organization, Landsat satellite images The ETM + sensor is derived from frames with passes and rows of 161-034 for 2017 (at appropriate times without cloudy and dusty images) and analyzed in ArcGIS 10.4, ERDAS IMAGINE 9.1 and EXPERT CHOICE 11.0 software packages.
    Results and discussion
    After preparing thematic maps of different layers of information, it is necessary to combine them together to produce the final map. An important issue in integrating these layers is to determine the relative importance of each layer of information, which varies depending on the model used. In this study, three models of AHP, APLIS and modified APLIS were used.
    In present study, a pair comparison method was used in the AHP model. By multiplying weights in the factor, then their summation was obtained in accordance with the following equation of the potential influence map. The map was then classified in five qualitative classes, from very low Infiltration potential to very high Infiltration potential.
    RP = 0.444 * L + 0.080 * S + 0.056 * A + 0.122 * P + 0.203 * F + 0.023 * T + 0.049 * V + 0.023 * D
    In which L is lithology, S is slope, A is aspect, P is precipitation, F is lineament density, T is temperature, V is vegetation, D is drainage network density and RP is recharge potential.
    In APLIS model, according to the weights table, the different classes and the quantitative relationship developed by Andreo et al. (2008), the final Infiltration potential map was obtained. The map was then classified in five qualitative classes, from very low Infiltration potential to very high Infiltration potential.
    R = (A + P + 3 * L + 2 * I + S) /0.9
    In modified APLIS model, according to the weights table, the different classes and the quantitative relationship developed by Andrew et al. (2008), the final Infiltration potential map was obtained. The map was then classified in five qualitative classes, from very low infiltration potential to very high infiltration potential. Marin (2009) modified the APLIS method with the introduction of a new factor called correction factor (Fh), as well as the extension of the "Effective Feed Layers (I)" domain name and modified it to Modified-APLIS. With regard to this, the relationship between the apple model and the following was changed. Then, based on the weights table, different classes and modified quantitative relationship, the final map of infiltration potential was prepared and classified into five qualitative classes.
    R = [(A + P + 3 * L + 2 * I + S) /0.9] * Fh
    Conclusion
    The results of the AHP model, with five classes of infiltration capacity, indicate that the ​​ area with low infiltration potential in the basin is negligible and close to zero. The infiltration potential of low, moderate, high and very high classes are, respectively 8.1%, 15.1%, 47.7% and 29.1%, and the high infiltration class has the highest area of the basin (about 50%). In the APLIS methods, the ​​areas of very low, moderate, high and very high infiltration classes are 15.1%, 17.9%, 65.1% and 1.9%, respectively, and in the modified APLIS model, respectively 20.9, 1.0, 13, 63.4% and 1.5% of the basin area. In general, it can be noted that the modified APLIS model with the highest correlation coefficient (0.85) and then the AHP model (0.82), have the highest coefficient of identification of Infiltration potential in the region. However, all three models show an acceptable prediction of basin infiltration assessment. Highly influential areas in these three models are located on the central and eastern part of the basin, which, by comparing it with the geology of the area, mainly correspond of the mozdoran-Lar Formation, in which the purity of lime and dolomite is higher. Also, areas with high Infiltration Potential are consistent with low drainage areas
    Keywords: Groundwater, AHP, Modified APLIS, Mozdoran-Lar Formation, Roein basin
  • donya rabeti, *maryam dehbozorgi, saeed hakimi asiyabor, reza nozaeim Pages 140-157

    Tectonic geomorphology is a valuable knowledge in the study of active tectonics that can determine the effect of active tectonics on the river. Morphometric studies are defined as quantitative measurements of the shape and landscape of the earth. With the advent of tectonic science of geomorphology, Active tectonic processes can affect the shape and performance of the river. The extraction of geomorphic indices using digital elevation map (DEM) in the GIS in the past two decades has been a fast and accurate method for drainage basin analysis, so that these indices are used for quick evaluation of recent tectonic activity in a particular region. The morphometric characteristics of the drainage system of many basins and sub basins in various parts of the world have been studied extensively. With the study of topographic landforms and the model of drainage systems by using geomorphic indices and the geological structure of each area, it is possible to evaluate the active tectonic performance and to determine the absence of active tectonic movements. The quantitative measurements provide conditions that allow them to identify the status of active tectonics areas. From the natural scenery, rivers are the first environmental forms that show a relatively rapid response to changes in the bedding or changes in the outflow of the bed. Regarding the proved reactions of rivers to the occurrence of normal changes, it is possible to analyze them by using geomorphic indices in the study of the effects of tectonic on the river's route to the results of them. Geomorphic indices are especially used for active tectonic studies. According to the tectonic position of the area and the location of the SefidRud River, the study of morphometric indices in determining the tectonic activities of area is useful. In this study, active tectonics of the western Alborz in Rudbar and Rasht basins with measuring morphometric indices has been surveyed. The study area is located in Western Alborz and Manjil, Jirandeh, Deylaman, Dorfak faults are some of the most important faults in this area. There are many inferred faults in different parts of the study area. General trend of study area is NE- SW. To assess tectonic activities in the area, seven morphometric indices of the Hierarchical anomaly (Δa), Bifurcation (R), Hypsometric integral and curve (Hi), Relative relief (Bh), Drainage density (Dd) and Form factor (Ff) and Stream gradient index (SL) have been assessed. First, by using Arc GIS and digital elevation maps (DEM) with a horizontal resolution of 30 m; basins and streams of the study area was extracted and 19 sub basins were formed. Then, using geological maps 1:100,000 of the study area, structural units including fold and faults were extracted. In the next step, each of the indices was calculated for 19 studied basins. Each index was divided into five classes in terms of tectonic activity. In fact, indices of the Hierarchical anomaly (Δa), Bifurcation (R), Hypsometric integral and curve (Hi), Relative relief (Bh), Drainage density (Dd) and Form factor (Ff) and Stream gradient index (SL) were classified according to their values. Class 1 (very high tectonic activity), class 2 (high activity), class 3 (intermediate), class 4 (low), class 5 (very low). According to the values of the calculated indices, to determine the total tectonic activity, the relative active tectonics index (Iat) was evaluated. Then, for each index, the map of the tectonic activity level was plotted in the study area. Based on (Iat), the area was divided into 4 categories. Category 1 (very high tectonic activity), Category 2 (high tectonic activity), Category 3 (intermediate), Category 4 (low). Almost half of the total area of the basins is in the high and very high activity. Indices measured in each sub basin indicate that in the sub basins corresponding to Manjil, Jirandeh, Dorfak, Deylman, as well as areas with high fault density, the measured indices exhibit high anomaly. The above anomalies indicate the effect of the above faults on the region and high tectonic activity in the study area. In addition, Field observations show the existence of several generations of alluvial drainage, several knickpoints, triangular facets and narrow and tight valleys. According to the results of field observations and calculation of morphological indices, it can be concluded that the study area is active due to the performance of Manjil, Rudbar, Jirandeh, Deylaman faults
    Keywords: Tectonic geomorphology, Geomorphic indexes, Tectonic activity, Faulting, Western Alborz
  • sayyad asghari*, imanali balvasi Pages 158-182
     
    Introduction
    Landslide is considered as one of the natural hazards ever occurring throughout the world and is of great importance. This phenomenon is one of the major geomorphic processes affecting the evolutionary landscape in mountainous regions, which has caused catastrophic accidents. Due to the special climate conditions, physiography and change of the country, Iran has always faced with the problem of mass movements, and it is necessary to pay attention to this natural limitation. Lorestan province also has diverse geological features such as petrography, land management, seismicity and special climate conditions, including areas with slip potential. The topographic and geological conditions of the study area are such that the slip of rock and soil fragments from small to large scale has been provided.
    Methodology
    Fuzzy logic is a logic of several values, that is, its parameters and variables, in addition to the number of 0 or 1, can take all the values between these two numbers. The basis of the difference between fuzzy methods and other methods is to define the membership function. The membership function can be used to determine the degree of attribution of the elements of the reference set to its subset. The operator of the fuzzy society is the collection community.In this way, it extracts the maximum membership membership. The fuzzy subscription operator is the collection subscription. In that way, it extracts the minimum degree of membership. Fuzzy algebraic multiplication multiplies all the information layers together. Because of the nature of the numbers between zero and one, which is the same as the membership membership in a fuzzy set, the operator makes the number of the numbers smaller and goes down to zero. The complementary fuzzy algebra operator is obtained by the algebraic multiplication. Therefore, in the outbound map, unlike the fuzzy algebraic operator, the value of pixels goes toward one. The fuzzy gamma operator is the product of multiplication, fuzzy coherent multiplication in the fuzzy algebraic summation. The results obtained from this operator are more accurate than other operators.An artificial neural network is a computational mechanism that can provide a series of new information by gathering information and calculating them. In the artificial neural network, the structure of the human brain and the body's neural network is similar to that of a brain that has the power to learn, make and decide. In the neural network model for preparing the network from the layers, along with a number of real samples, they entered the network as inputs, and with this method a pattern was obtained between the input parameters and the areas where the landslide was located. A probability ratio was used to determine the land slide sensitivity index. In order to facilitate artificial neural network convergence, the values ​​of the input neurons were normalized. To estimate the accuracy of artificial neural network, the mean squared error error was used.
    Results and discussion
    An artificial neural network with multilayer perceptron structure with error propagation algorithm and non-linear sigmoid function as an activation function was used. The simple learning factor was ignored because of convergence and failure to make a valid error. Also, the error rate of the variable learning coefficient was higher than the Levenberg-Marquard method, which is why the Levenberg-Marquard method was used. For training and network testing, 80% of the data was used for training and 20% for testing. The final structure of the 1-14-8 grid was considered appropriate and based on this structure, the final zoning was performed.The operators of the fuzzy logic model were used. The result of the fuzzy community operator generated the maximum membership membership membership. The fuzzy share operator extracts the minimum membership membership. The result of the operator of the fuzzy algebraic multiplication is reduced to zero numbers. The output map of the operator of the fuzzy algebra sum of the value of the pixels is close to the maximum. In order to modulate the very high sensitivity of the fuzzy algebraic operator and the very low accuracy of the fuzzy algebraic operator, a 0.9% gamma-gamma operator was used. Kappa coefficient for artificial neural network model was 0.83 and for fuzzy logic model 0.66.
    Conclusion
    The evaluation of the results obtained from the fuzzy logic model and the artificial neural network using kappa statistical coefficient shows that the artificial neural network with Kappa statistical coefficient is 0.91 compared to the fuzzy logic model with a kappa coefficient of 0.88 more than the prediction of the risk of landslide In the Seymareh Chenar Basin. Based on the zoning, the artificial neural network model was 10.12, 22.92, 31.44, 20.76, 15.16 percent of the area in the low, medium, high and very high risk classes has it.
    Keywords: Landslide, Artificial Neural Network, Seymareh Chinar Basin, Geographic Information System, Fuzzy Logic Model
  • Masoume Rajabi, Mirasadallah Hejazi, Shahram roostaei, Negin aali* Pages 183-195

    The refore the necessity of understanding of effective environmental factors has an important role in the formation of rural settlements.The importance of this lies in the fact that each year a large budget is spent on the constructing of rural settlements organization, developing of connecting roads and services, etc.Unfortunately, many of the expenses are made without considering the ( Factoe (and identifying areas with a high risk of natural disasters, on which the villages are located.
    The importance of the study lies in the fact that environmental conditions affecting the formation of rural settlements and the villages which are at the risk of natural disasters should be identified.Therefore investigating the effects of environmental factors associated with rural settlements and identifying the natural disasters in these areas are essential.In this research rural settlements of Marivan in one of the most active tectonic regions of Iran are considered as a Case Study which are identified for a variety of natural disasters in Iran.This city is located in the West of Kurdistan, on the western border with Iraq.This area is relatively located in position with a high seismic risk. And in terms of tectonic it is located on Marivan- Esfandaghe fault.Therefore, the identification of factors affecting the sustainability of rural settlements is very important.
    Materials and methods of research:A variety of instruments and methods has been used to achieve the aims of the research; In the first stage Research instruments including: topographic maps 1:25000, geological map 1:100000, surface water with a scale of 1: 50,000 and data on groundwater as well as ETM satellite images were collected from different organizations. In the second stage by using ARC GIS software, required layers were derived from digital maps mentioned above.
    At this stage, layers such as watershed, Canals and surface water, Province fault Maps, places about to slip and silde were determined.And then by using GIS spatial analysis capabilities the classification Map was prepared and the position of rural areas was determined on it.
    In the third stage to study for studied natural hazards under investigation, in order to determine the role of each of the various factors in the occurrence of natural disasters, the AHP method was used.At first Raster maps related to any of the factors in cell size of 20 x 20 m was produced by the use of vector information.
    After producing raster maps, fuzzy standardization was applied on each map so that the effective range on the occurrence of any phenomenon is defined between 0-1. In addition to the standardization of map`s unit, it specifies the role of special ranges in each factor. Linear standardization functions were used to define the effective ranges between 0-1. Standardized layers were multiplied by the weights which were given to them based on experts` opinions and the final weight was obtained for each layer. Finally the final weight of each of the effective layers on the occurrence of natural hazards was collected together and the final map of each phenomenon was prepared in the studied area.
    In the fourth stage, by the use of the final earthquake hazard zonation layers landslide and flood and combining the layers with an index overlap, the final layer of natural hazards of Marivan was prepared and rural areas were transferred on it. Finally the villages at risk of natural hazards were identified.
    Research findings:Because of being mountainous and locating in a tectonically active region the area of study (Marivan_Asfandeqhe) is the most seismic areas in the country. And as a result of the earthquake, various natural hazards occur there. That's why it’s unstable in terms of environmental factors. And this issue has also been effective in distribution of rural settlements.
    To investigate the relationship between the natural factors and the formation of rural settlements, first the position of the villages to the three factors is reviewed. Then the zoning of the risks caused by environmental factors is investigated. Investigating the relationship between environmental factors and the position of rural settlements and finally zoning of natural hazards in the city of Marivan shows that the formation of rural settlements in this city has taken place due to its natural sources and fertile soil and the possibility of having gardening activities.
    Local climate and the possibility of having gardening activities have caused the Continuity of Living in rural areas in this city. Having access to water sources has happened without considering the risk of flooding, So that villages near the main river routes have faced with the risk of floods. It also seems that Location selection in this area has been regardless of Natural hazards such as earthquakes. Because this area is one of the most Earthquake-prone regions in Iran. While Most of the villages are close to the main fault and relatively in high risk of earthquake.
    Conclusion
    Investigating the environmental factors in association with Distribution or accumulation of rural areas and the role of these factors in occurrence of natural hazards in the city of Marivan shows that, slope, due to its direct effect on other environmental factors is the most important factor in the stability of villages.
    Since most old villages are located in areas with high slope.And this factor in addition to the activities of gardening and handicrafts was very effective in residence continuation of people.Moreover, the natural hazards occurred in low slope areas.
    The results of Bahrami’s research have revealed that the establishment system in the rural environment of Kurdistan, specifically the city of Sanandaj, is not compatible with the requirements of modern developments. In the city of Sanandaj, natural causes (Climate, high altitude and steep) despite the limitations of Locational- Spatial subsistence and lack of logical ideas in rural planning have also doubled the problems of countryside development in Sanandaj
    Keywords: Key words: Saqez city, natural hazards
  • Dariush Abolfathi, Aghil Madadi*, Sayyad Asghari Pages 196-208
     
    Introduction
    River sediments are transmitted in two ways: either these substances are immersed in the flow of water, and they move with water, which is called suspended sediment, and the amount of suspended sediment that passes through a section of the river at a time They call a suspended load, or they move a slip, slide, jump, to which they say the bed load. Artificial neural network is a method that is based on the simulation of human brain function for solving various problems and the input, output, and median of the neuron layers and the weights associated with the input values ​​and the bias and the stimulation function. The study area in this study is the catchment area of ​​Golrood River.
    Artificial neural network is a method whichwasprovided based on the simulation of human brain function for solving various problems and formed from the input, output, and median neuron layers and the weights associated with the input values and the bias and the stimulation function. One of the features of the artificial neural network can be referred to as the calculation of a definite function, the approximation of an unknown mapping, pattern recognition, signal processing, and learning (American Society of Civil Engineers, 2000). The disadvantages of neural network methods are that it does not provide a function which can be used explicitly. Many studies have not been conducted on sedimentation using a neural network (Govindaraju&Ramachandra, 2000; Sarangi & Bhattacharya, 2005).Feedforward error back propagation neural networks with nonlinear functions (sigmoid) has high flexibility and can be very effective in approximating a function, finding the relation between input and output, and so on. In hydrology, the use of these networks is highly recommended considering the turbulence dominating runoff-sediment data, (Flood &Kartam, 1994).
    Javadi and others (2015) in an article compared river sediment estimation method using two methods of artificial neural network and SVM in Iran. Then, the output of these models was compared with the experimental models and eventually the RMSE and R indices to compare these models were used. The results indicated that SVM model has better estimation than artificial neural network model. The RMSE was 75 for this model.
    Semkol et al. (2016) estimated the amount of sediment in the Shiwan River in Taiwan. In this study, artificial neural network model and sediment rating curve method were used. The results showed that the MLP neural network model was able to provide an appropriate estimation of the amount of sediment with R value of 0.97 (Tfwala& Wang, 2016).Afan et al. (2016) also estimated the amount of river sediment in the Johouw River. In this study, two models of neural network RBF and FFNN were used. Finally, it was found that the FFNN model showed a much better performance than the RBF model. The R index of this study for the FFNN model was 0.92 and its RMSE was 26, while the RBF model had R value of 0.86 and a RMSE of 32 (Afan et al., 2015).
    Summarizing the research history showed that the static regression methods did not have high accuracy in estimating the suspended sediment load discharge.In recent years, the focus of predictive models has also changed from linear regression to neural network models. Most researchers have been providing comparisons between different models of the neural network during these years and also, in their final modeling, tried to use the domain morphology factors in the final model to improve the accuracy of the final model. Therefore, the use of artificial neural network method and considering the dynamic behavior of sediment suspension load and considering the flow of previous days as an effective variable has been evaluated in this research.

    Materials & methods
    The study area
    The study area in this research is the Gelerood river basin. This area is located in Borujerd, Lorestan province, west of Iran. The basin is between longitudes 48.30 to 48.55 degrees and latitudes 33.45 to 34.00 degrees. GeleroodRiver drains waters of an area of 70 square kilometers. The average height of this basin is 2350 meters. The river originates from a number of headwaters in the village of Vanai in the west of this city and receives other branch in the western part of the Boroujerd city in the vicinity of the Chogha hill from the north.
    There are 8 stations named such as Doroud-Tireh, Doroud-Marbareh, DarehTakht-Marbareh, Vanai-Gelerood, Biatoun, Rahim-Abad, Water Organization and Chogha hill in the area of Silakhor plain in Dorood-Boroujerd area. In Gelerood river basin, two stations of Vanai and Water Organization have been used to estimate the amount of river sediment. The position of these two stations in relation to the Gelerood River and its sub-basins is shown in Fig 1.
    Data used
    In this study, the instantaneous flow rate- instantaneous sediment statistics recorded deposition related to the period 1971 to 2002 were used. These figures include the instantaneous daily flow rate per cubic meter per second and the instantaneous daily sediment per day that were measured simultaneously. Morphological characteristics of the basin including the area, length of the river and its environment using ArcGIS software and geomorphologic parameters of the basin using natural features of the basin have been calculated based on the guidelines of Singh et al. (2009) using the ArcHydro plugin installed on the above software.

    Results
    So far, different prediction models have been used to estimate the sediment volume of rivers. Some of these models estimated the amount of sediment by combining various physical parameters of the domain, climate, and even satellite image outputs. Artificial neural network models are widely used today to predict geographic models. In this study, three models of artificial neural network RBF, artificial neural network MLP and multivariate linear regression model have been used to estimate river sediment.
    After calculating the RMSE and MAE indices, given the lower the rate of these indicators, the predicted value is closer to the actual values, so MLP artificial neural network models have a better accuracy than the other two other models in estimating the region's sediment. On the other hand, according to the value of the index calculated for the three models, the accuracy of the model estimation is calculated 90.44 for the MLP model, the value for this model is 0.88. After the MLP artificial neural network model, the RBF artificial network model provides better results. In this model, the value of is 0.4, which indicates the estimate accuracy of the half of the MLP model. In the third place, the multivariate linear regression model with value is 0.3.
    Two neural network models of MLP and RBF were also studied in this research. The MLP model was able to estimate sediment data with a better accuracy than other models. Thus, the feasibility of using feedforward neural network models in the estimation of sediment load can be confirmed. Based on the available time series, more accurate estimates require long periods of time, as well as considering climate changes in this research can help improve the results and accurately predict the amount of sediment. On the other hand, taking into account the soil type-specific parameters of the area and the potential for water penetration in the soil for each sub-basin can be effective in improving the results. The results of this study indicated that there is a significant relationship between the amount of suspended sediment production with the number and severity of runoff events. Among the physical characteristics, the area of the basin and the length of the main river are other factors that affect the estimation of the river downstream sedimentation rate.
    As well as, recurrent neural network models can be used in the following studies, given that the stations are located along the other stations. Moreover, the combination of satellite imagery data can lead to more accurate models, given the fact that this data is also available to users from past periods
    Keywords: Gelerood, artificial neural network, estimation of sediment, liner regration, MLP, RBF
  • Ali Reza Arab Ameri* Pages 209-223
     
    Introduction
    Synthetic aperture radar (SAR) systems have been widely used in the past two decades to produce high-resolution mapping and other remote sensing applications (Calabro et al. 2010; Sun et al. 2011). The ability of penetrating to the cloud , snow dry soil as well as day and-night operation made the SAR systems with more capability compared to optical imagery (after Karjalainen et al. 2012). SAR data are widely applied for several studies geophysical and geographical approach forestry and vegetation, biomass measurements, soil moisture, natural hazards and etc. (Lardeux et al. 2011,Herrera et al. 2013). The present study deal with morphological landform Identification over the area covered with dense forest. Where is the landform assessing and mapping almost appeared as big task due to difficulty of observing true the optical images. The high penetration potential of SAR signals through the vegetation cover can be obtained using the L band of the ALOS PALSAR satellite with nearly 24 cm signal wavelength (Herrera et al. 2013. Furuta et al. 2005) Furthermore, it is mention that ALOS PALSAR data is very useful for producing accurate digital elevation models (DEMs) and deformation monitoring, as well as disaster monitoring and hazard prevention. Topography is a key controlling factor in the operation of a variety of natural processes (Montgomery and Brandon 2002). Hence it needs to be quantitatively analyzed (Lague et al. 2003), to ascertain the relative efficacy of its constituents and operative mechanisms, and to gauge the response of geomorphic systems to different stimuli (Ahmed et al. 2010). Rivers are one of the most sensitive elements of the landscape (Smedberg et al. 2009). The systematic evaluation of land surfaces and drainage pattern characteristics remains as a main study object in geomorphology. Consequently in geo-morphometry (Prasannakumar et al. 2013). Digital elevation models (DEMs) have been frequently used for the above morphometric analysis of river basins through the extraction of topographic parameters and stream. The biggest advantage of DEMs over traditional topographical maps is the rehabilitee, coverage and data multiplying. Due to their wide applicability and rehabilitee, DEMs have been used in a variety of studies where terrain and drainage factors play prominent roles. The aim of this research is Extraction of Hillsides Drainage pattern in density forest area using Low-frequency radar data.
    Methodology
    Dense forests of Behshahr South are a rainforest which is geographically located at a latitude of 36° 25’ 30” up to 36° 43’ 30” N and longitude 53° 04’ 15” up to 53° 54’ 15” E. The Average elevation of the area is 704.58 m above mean sea level. The rainfall received over the basin area varies from 700 to 1000 mm annually. This paper provides a comparative study of different available or derived DEMs (SRTM, ASTER, ALOS-POLSAR), through extraction of stream networks and their eventual comparison. A flowchart schematically shows the methodology followed for the extraction of drainage networks from DEMs in a GIS environment (Fig. 2). The DEMs of the study area is first preprocessed through the operations of Flow Direction, sink dems and filling the data gaps, pit removal–depression filling, and finding outlet cells in an iterative manner. Pit removal and depression filling is a method of filtering the digital elevation data. This is done to overcome any data voids that may be present in the DEM tile and to also ensure proper channel network connectivity. Sometimes, there are some pixels in the continuous array of digital data where the value of the pixel is abnormally low or high in comparison to other neighbouring cells. These are known as data sinks or spikes respectively and these are inherent in any DEM. These need to be removed before carrying out any sort of analysis in the data. After extraction of drainage networks to use Digital Elevation Models, The ability of Digital Elevation Models were evaluated in the extraction of drainage networks. And in the last step, Drainage density was calculated in each of the land covers.
    Results and discussion
    The average elevation with a standard deviation of the study area extracted from the different DEMs have been calculated and subsequently presented in Table 2 and figure 3. The results showed that PALSAR digital elevation model has the lowest standard deviation. Figures 4,5 and tables 3,4 depict the comparisons of drainage networks derived from the different DEMs with respect to total stream lengths and Drainage density respectively. It is observed that the maximum lengths of streams and maximum area of high Drainage dendity are generated by PALSAR DEM. Integration of land use and drainage density map also showed that in PALSAR DEM, 73.62 percentage (520.97 K2) of dense forest area have been located in very high Drainage density class. While, in ASTER and SRTM DEMS only 0.033 and 0.672 percentage of dense forest area have been located in very high Drainage density class, respectively.
    Conclusion
    Digital Elevation Models (DEMs) have been a subject of increasing attention and utilization in the last few decades because of the relative ease in delineation, extraction and calculation of various drainage and terrain morphometric parameters from them. The present study was carried out in order to find the best possible DEM for extraction the drainage pattern in density forest area. After analyzing the different parameters derived from these DEMs, it can be said that the DEM derived from the Low-frequency radar datasets is relatively more accurate and consistent than ASTER and SRTM DEMS. The results showed that Low-frequency radar datasets have High capability for penetration through the vegetation cover and extraction of drainage pattern
    Keywords: ‎ drainage, Radar imagery, dense forest, Behshahr.‎