فهرست مطالب

فصلنامه پژوهش های فرسایش محیطی
سال هفتم شماره 1 (پیاپی 25، بهار 1396)

  • تاریخ انتشار: 1396/03/25
  • تعداد عناوین: 7
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  • مقاله پژوهشی
  • مرضیه مکرم*، سعید نگهبان صفحات 1-25
    حرکات توده ای دامنه ها یکی از مهمترین مخاطراتی است که همه ساله حیات انسان ها را تهدید می کند و پرداختن به این موضوع از اهمیت زیادی برخوردار است. یکی از مهمترین حرکات توده ای دامنه ای، زمین لغزش است که تهیه ی نقشه های حساسیت به آن به منظور مدیریت مخاطرات، هدف مهمی در علوم طبیعی به حساب می آید. با توجه به اهمیت موضوع، هدف از این مطالعه استفاده از الگوریتم انتخاب ویژگی به منظور تعیین موثرترین پارامترها در پیش بینی زمین لغزش در جنوب غرب ایران است. برای این منظور از روش های بهترین انتخاب، رتبه بندی و گام به گام استفاده شد. نتایج حاصل از روش بهترین انتخاب نشان داد که موثرترین داده ها برای زمین لغزش SAR، ارتفاع، شاخص TWI و فاصله از رودخانه است. همچنین نتایج حاصل از روش گام به گام، مشابه با روش بهترین انتخاب به شمار می رود؛ در حالی که موثرترین داده ها برای روش رتبه بندی، شاخص TWI، ارتفاع، فاصله از جاده و فاصله از رودخانه است. داده های انتخاب شده توسط روش رتبه بندی با کمترین میزان خطا و حداکثر ضریب همبستگی (5/87)، با طبقه بندی LMT به عنوان موثرترین داده ها برای تعیین زمین لغزش به شمار می رود. همچنین با توجه به اینکه هدف از این مطالعه بررسی زمین لغزش به طور مکانی است؛ بنابراین بعد از تعیین پارامترهای موثر در زمین لغزش، نقشه های پهنه بندی آن با استفاده از موثرترین داده ها در محیط GIS تهیه شد. نتایج ناشی از تهیه ی زمین لغزش با استفاده از داده های انتخاب شده، توسط الگوریتم انتخاب ویژگی نشان داد که بخش هایی از مناطق شمالی و جنوب شرق منطقه مورد مطالعه در معرض خطر لغزش بیشتری قرار دارند.
    کلیدواژگان: الگوریتم انتخاب ویژگی، زمین لغزش، جنوب غرب ایران
  • پرویز کرمی *، مهندس امید امیری، حامد جنیدی جعفری صفحات 20-34
    این تحقیق به منظور بررسی اثر تغییر کاربری مرتع بر عملکرد اکوسیستم و ویژگی های فرسایش پذیری خاک با استفاده از روش LFA در مراتع سنندج انجام شد. ابتدا دو چشم انداز مرتع دست نخورده و دیم زار رها شده ی همجوار مشخص شد. براساس روش LFA، در هر چشم انداز سه ترانسکت 50 متری در جهت شیب مستقر و در طول هر ترانسکت، قطعات اکولوژیکی بر اساس فرم رویشی بوته ای، گراس، فورب، ترکیبی (ترکیبی از قطعات اکولوژیکی بوته، گراس و فورب) و فضای بین قطعات مشخص شد. از هر قطعه به صورت تصادفی 5 تکرار تعیین و 11 پارامتر سطح خاک برای هر تکرار اندازه گیری شد. برای اندازه گیری پارامترها از نرم افزار LFA و برای مقایسه ی لک های اکولوژیکی دو چشم انداز، از آزمون T جفتی استفاده شد. نتایج نشان داد در چشم انداز مرتع دست نخورده از لحاظ شاخص پایداری، بوته و از لحاظ شاخص چرخه ی عناصر و نفوذپذیری، فرم گراس دارای بیشترین مقدار بود، ولی در چشم انداز دیم زار رها شده از نظر هر سه شاخص، قطعه ترکیب بیشترین مقدار را داشت. مقایسه ی شاخص پایداری، نفوذپذیری و چرخه ی عناصر غذایی کل نشان داد که مرتع دست نخورده از لحاظ هر سه شاخص بیش از دیم زار رها شده است؛ به عبارتی، تغییر کاربری باعث کاهش عملکرد اکوسیستم و افزایش پتانسیل فرسایش پذیری خاک شده است. بنابراین برای جلوگیری از کاهش عملکرد اکوسیستم، هدررفت و فرسایش خاک، بایستی بیش از پیش از تبدیل مرتع به دیم زار با جدیت بیشتر جلوگیری شود.
    کلیدواژگان: عملکرد اکوسیستم، شاخص های گیاهی و خاکی، تغییر کاربری، فرسایش خاک، استان کردستان
  • حمیدرضا کوه بنانی، جمال دشتی امیرآباد، شیما نیکو*، علی تایا صفحات 35-49
    بیابان زایی یکی از مهمترین مخاطرات محیطی در زمان ماست. غالبا راهبردهای ارزیابی شدت تخریب و بیابان زایی در ایران، به صورت بخشی نگری و بر مبنای نظر کارشناسی ها بود و معمولا روش های ارزیابی بر مبنای مدل تصمیم گیری چند معیاره چندان قابل توجه نبوده است. در پژوهش حاضر، رویکرد فازی یکی از روش های کارآمد در ارزیابی برخی معیارهای مهم در زمینه ی تخریب و بیابان زایی است. بدین منظور پس از تهیه ی واحدهای کاری، نمونه های میدانی در محیط های همگن برداشت و با استفاده از روش های زمین آمار و کریجینگ به تهیه ی نقشه های رستری پیوسته اولیه در محیط GIS پرداخته شد. در گام بعدی با استفاده از توابع خطی عضویت فازی، لایه ها به صورت فازی تبدیل گردید. در نهایت با استفاده از عملگرهای فازی و اپراتور گاما، نقشه ی نهایی شدت بیابان زایی در مقیاس صفر تا یک ارائه شد. به منظور تسهیل و تفهیم بهتر نتایج، نقشه ی نهایی در 4 کلاس شدت کم تا شدت خیلی زیاد مجددا طبقه بندی شد. نتایج حاصل شده نشان می دهد که تقریبا 5/14 درصد از عرصه ی مورد مطالعه در شدت بالای تخریب و 5/3 درصد هم در شدت خیلی زیاد قرار دارد. ذکر این امر لازم است که طبقه بندی فوق در سناریوهای مختلف مدیریتی می تواند مورد بازبینی مجدد قرار گیرد.
    کلیدواژگان: پهنه بندی، بیابان زایی، منطق فازی، تابع عضویت خطی، دیهوک
  • غلامحسین عبدالله زاده *، نادیا فراهی، محمد شریف شریف زاده صفحات 50-68
    هدف این مطالعه، بررسی عوامل موثر بر پذیرش عملیات حفاظت خاک به منظور کنترل فرسایش در باغ های اراضی حوضه ی آبخیز چهل چای در استان گلستان است. جامعه ی آماری مشمول بر 623 نفر از باغداران این حوضه در سال 1394 است که از بین آنها 241 نفر به عنوان نمونه، از طریق روش نمونه گیری خوشه ایدر 12 روستا انتخاب شدند. ابزار گردآوری داده ها پرسشنامه ای بود که روایی آن از طریق نظر گروهی از متخصصان و پایایی آن، از طریق محاسبه ی آلفای کرونباخ برای گویه های ادراک از مزایا (78/0) و معایب (81/0) استفاده از روش های حفاظت خاک تایید شد. نتایج نشان داد که 5/53 درصد پاسخگویان معتقدند که باغ آنها به اقدامات حفاظت خاک نیاز فوری دارد؛ در حالی که فقط 8/37 درصد پاسخگویان از یکی از روش های حفاظت خاک استفاده می کردند که در این بین، پوشش دائمی خاک توسط کشت های همزمان و نواری از جمله اصلی ترین روش های حفاظتی مورد استفاده بوده است. نتایج نشان داد 1/48 درصد از آنها با روش های حفاظت خاک میزان آشنایی کمی داشتند. از بین گویه های منافع کشاورزی حفاظتی مواردی مانند افزایش حاصلخیزی خاک و کاهش آلودگی در رواناب، اهمیت بیشتر و از بین گویه های هزینه های حفاظت خاک نیز گویه های ریسک بالای روش های جدید و افزایش هزینه ی نیروی کار، اولویت بالاتری داشته اند. نتایج اجرای مدل لوجیت نشان داد که سابقه ی کشاورزی، سن و ادراک از هزینه های کشاورزی حفاظتی بر پذیرش روش های حفاظت خاک تاثیر منفی دارد و متغیرهای دفعات وقوع سیلاب، آشنایی با روش های حفاظت خاک، استفاده از نتایج آزمایش خاک در باغ، وجود فرسایش خاک، مساحت زمین های شیب دار، مساحت زمین و درآمد دارای تاثیر مثبت و معنی دار بودند.
    کلیدواژگان: فرسایش خاک، حفاظت خاک، پذیرش، حوضه ی آبخیز چهل چای
  • سمیرا قربانی *، امید رحمتی، فرهاد نورمحمدی صفحات 69-89
    وقوع فرسایش های آبکندی به دلیل تولید رسوب بالا در حوضه های آبخیز، یکی از مشکلات منابع طبیعی در زمینه ی مدیریت و حفاظت خاک تلقی می شود. در این تحقیق، پتانسیل وقوع فرسایش آبکندی براساس مدل های آنتروپی شانون و شاخص آماری در منطقه ی سیمره استان لرستان ارزیابی شد. ابتدا لایه های رقومی عوامل موثر در پتانسیل مناطق حساس به فرسایش شامل ارتفاع، سنگ شناسی، شیب، جهت شیب، کاربری اراضی، فاصله از رودخانه، رده خاک شناسی، شاخص رطوبت توپوگرافی و شاخص توان جریان در محیط نرم افزار ArcGIS 10.2 تهیه شد. از 100 آبکند موجود، گروه آموزشی (70 درصد) و اعتبارسنجی (30 درصد) به صورت تصادفی تفکیک شد. سپس وزن کلاس های هر یک از عوامل موثر، براساس تجزیه وتحلیل احتمالاتی مدل های شاخص آماری (SI) و آنتروپی شانون تعیین گردید. نقشه ی حساسیت به فرسایش آبکندی نیز براساس این مدل ها تهیه شد. در نهایت، اعتبارسنجی نقشه ی نهایی براساس داده های گروه اعتبارسنجی و روش منحنی مشخصه ی عامل گیرنده (ROC) انجام شد. نتایج نشان داد نقشه ی حساسیت به فرسایش آبکندی که براساس مدل های آنتروپی شانون و شاخص آماری تهیه شده، به ترتیب دارای میزان اعتبار 3/77 درصد و 8/79 درصد است؛ این امر بیانگر قابلیت بالای این مدل ها در شناسایی مناطق حساس به فرسایش آبکندی است. علاوه بر آن براساس نتایج مدل آنتروپی شانون، عوامل سنگ شناسی، ارتفاع و کاربری اراضی بیشترین تاثیر را در وقوع فرسایش های آبکندی داشتند. تعیین میزان حساسیت مناطق مختلف نسبت به فرسایش آبکندی برای اجرای برنامه های حفاظتی ضروری است که تحقیق حاضر این مهم را فراهم می کند.
    کلیدواژگان: اعتبارسنجی، پیش بینی مکانی، مدیریت و حفاظت خاک، متغیرهای زمین، محیطی
  • صدیقه محمدی* صفحات 90-113
    تحقیق فوق با هدف تعیین کارایی مدل های شبکه عصبی مصنوعی، عصبی- فازی و رگرسیون چند متغیره در شبیه سازی حجم رواناب و میزان فرسایش در سه زیر حوضه از حوزه های آبخیزشمال غرب ایران اجرا شد. در این پژوهش، براساس خصوصیات بارش مشابه از نظر میزان شدت بارندگی نیم ساعته با دوره بازگشت 10 ساله، با استفاده از دستگاه باران ساز مصنوعی انجام شد. برای این منظور، استقرار دستگاه باران ساز در 86 سایت انجام و از 21 متغیر محیطی (از خصوصیات توپوگرافی، خاک شناسی، پوشش گیاهی و تنوع گونه ای) به عنوان ورودی مدل استفاده شد. اعتبارسنجی مدل ها با 18 درصد داده ها انجام شد. نتایج تحقیق حاضر نشان داد که مدل رگرسیونی چندمتغیره می تواند به توجیه 68 و 46 درصد تغییرات به ترتیب متغیرهای حجم رواناب و میزان فرسایش بپردازد و کارایی آن در شبیه سازی پایین است. طبق نتایج، مدل شبکه عصبی تابع پایه شعاعی در مقایسه با روش پرسپترون چندلایه و مدل نروفازی با سناریو روش خوشه ای(رویه هیبرید) در مقایسه با روش شبکه، می توانند به پیش بینی دقیق تر بپردازند؛ به طوری که شاخص های RMSE، MAE و NSE در مدل بهینه شبکه عصبی، به ترتیب معادل 135/0، 114/0 و 99/0 برای حجم رواناب و 011/0، 009/0 و 98/0 برای میزان فرسایش و در مدل بهینه نروفازی، به ترتیب معادل 132/0، 111/0 و 92/0 برای حجم رواناب و 013/0، 011/0 و 98/0 برای میزان فرسایش حاصل شد. لذا مدل های شبکه عصبی با روش تابع پایه شعاعی و نروفازی با سناریو روش خوشه ای- رویه هیبرید به دلیل کارایی بالا، بهترین مدل ها برای شبیه سازی فرسایش و رواناب است.
    کلیدواژگان: پرسپترون چندلایه، تابع پایه شعاعی، شبیه ساز باران، نروفازی
  • فردین مرادزاده، سید عطاالله حسینی*، احسان عبدی، عطاالله کاویان صفحات 114-126
    جنگل اکوسیستمی پایدار از تعادل بالایی برخوردار است و خاک های فرسایش نیافته و آب های بدون رسوب، از مشخصات بارز آن به شمار می رود. جاده بزرگترین فعالیت عمرانی در جنگل و جزئی ترین فعالیت اضافه شده به آن تلقی می شود که با ایجاد سطحی بدون پوشش، می تواند نقطه ی شروع رواناب، عامل قطع و منحرف کردن جریان طبیعی و تمرکز تصادفی و ناگهانی آب، انحراف از مسیر زهکشی طبیعی به پایین شیب، تمرکز و انتقال آب به زیرحوضه های دیگر، تغییر الگوی رواناب و حمل مقداری رسوب به دلیل افزایش سرعت آب و... و در نهایت به تخریب جنگل منجر شود. تحقیق حاضر به منظور بررسی تاثیر شیب طولی در جاده ی جنگلی (درجه یک و دو) در سری گردشی بر مقدار رواناب و هدر رفت خاک اجرا شد. این پژوهش با استفاده از تکنیک شبیه سازی باران در سطح پلات یک متر مربعی، در قالب طرح کاملا تصادفی در 3 کلاس شیب و در هر جاده با 4 تکرار با شدت ثابت 60 میلی متر در ساعت به مدت 30 دقیقه اندازه گیری شد. نتایج آنالیز واریانس نشان داد بین مقدار رواناب و رسوب طبقات شیب مختلف در جاده که تفاوت معنی داری وجود دارد. نتایج آزمون توکی نیز نشان داد که با افزایش شیب، مقدار رواناب و رسوب به طور معنی داری افزایش می یابد. نتایج آزمون تی مستقل نیز نشان داد که به ترتیب میانگین حجم رواناب، ضریب رواناب و غلظت رسوب با مقادیر 33/23 لیتر، 71% و 84/11 گرم در لیتر، در جاده ی درجه دو بیش از این مقادیر در جاده ی جنگلی درجه یک به ترتیب 23/17 لیتر، 57% و 18/9 گرم در لیتر است. نتایج این آزمون نشان داد که در میزان رواناب و ضریب رواناب در سطح کلاسه های شیب دو نوع جاده ی جنگلی درجه ی یک و دو اختلاف معنی داری وجود دارد (05/0>p ، 85/0F=). همچنین نتایج این آزمون نشان داد که در میزان غلظت رسوب در سطح کلاسه های شیب دو نوع جاده ی جنگلی درجه ی یک و دو اختلاف معنی داری وجود ندارد (05/0

    کلیدواژگان: باران ساز، جاده های جنگلی، سری گردشی، رسوب، رواناب، شیب طولی جاده

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  • Pages 1-25
    Introduction
    Nowadays people have an increased sensitivity towards landslides especially in mountainous areas using change in the land use and the expansion of communication networks (Gvrsysky et al., 2006). In the twentieth century, Asia has allocated the highest incident of landslides (220 landslides). Latin America has had the highest number of casualties (more than 2,500) and Europe has experienced the highest loss (Karami, 2012). Landslide is one of the significant phenomena in the environment, watershed management, and natural resources. The importance of landslides can be discussed and analyzed from various perspectives. The most important reason refers to human and financial loss (Rajab Zadeh, 2013). Research on the dynamic relationships between factors in landslides has a high role in the investigation of the respective risk. In fact, much research has been conducted in the realm of determining the relationship between environmental factors and the occurrence of landslide (Anbalagan, 1992, Liu Min, 2001, Ayvahashy et al., 2003, Yalv and Yamagyshy, 2005). Some of such research is consistent with the relationship between the distribution of geological and geomorphological factors and landslides observed. However, to analyze the results and predict the likelihood of landslides, there are common tools that are used in statistical calculations.
    THEORETICAL FRAMEWORK: A landslide, also known as a landslip, is a form of mass wasting that includes a wide range of ground movements, such as rock falls, deep failure of slopes, and shallow debris flows. Slope, fine sediments and ground moisture have important roles in the occurrence of landslides; given that many parameters affect the landslide, a more effective choice to reduce time and costs is important. The subject of feature selection is the one of the issues identified in the machine learning and statistics. The problem in many applications (such as classification) is very important. Because in these applications, there are a large number of features that many of them are unused. In fact, if they are not removed, these features will not create problems, but save a lot of useless and useful information together.
    Methodology
    This study was carried out in the southwest of Iran (a part of Khuzestan, Khorramabad, Ilam, Kermanshah and Hamedan). It includes an area of about 154272.48 km2 and is located at the longitude of N 29° 56΄to 35° 46΄and the latitude of E 45° 24΄ to 52° 1΄. The altitude of the study area ranges from the lowest 30 m to the highest 4,415 m.
    There are different methods that try to find better subsets among the 2T subsets. In all of these methods, the selection of the subset is based on the type of application and type of definition that can optimize the value of an evaluation function. In fact, each way tries to make the best attributes of choices, but according to the extent of answers and increasing the answer with T, finding the optimal solution and T medium is costly. Feature selection process has four steps: Generation function: this function find sub-candidates for the procedure.
    Elevation function: it is based on data subset to be evaluated and a number as the method returns. Different methods try to find a subset that optimizes the amount.
    Stopping criterion: it is used to decide when to stop the algorithm.
    Results
    The results show that the case study is located in 6 classes increasing sensitivity as the number of class increases. So that the areas located in the South, East, and parts of the West regions are most sensitive to landslide. Motevali et al., (2008) show that using a new method such as LMT can prepare landslide map with low data. So, in the research of geomorphology and geology, feature selection can be used. Rasaie et al (2015) used regression in GIS software to prepare landslide map. The results showed that using effective parameters of landslide can find landslide map easily and quirkily.
    CONCLUSIONS AND SUGGESTIONS: The results of feature selection method show that the Ranker method with Gain-Ratio-Attribute-Eval, with low error, with highly significant correlation (87.5), and with LMT classification is the best method for the selection of the most effective data to determine landslide. Also, the results indicated that some parts of North and South-East of the study area are located at greater risk of landslide. Also, principal components showed that curvature, profile, plan and SPI were the most important data for determining landslide. In the study, it was attempted to use low data selected by feature selection, and save time and money via determining important data for landslide. Using the data, landslide map was prepared spatially.
    Keywords: Feature Selection Algorithm, Landslide, Southwest of Iran
  • Dr Parviz Karami*, En. Omid Amiri, Dr Hamed Joneidi Jaafari Pages 20-34
    Introduction
    Over the past few decades, the objective of the evaluation and monitoring of the optimal utilization of sustainable natural resource services and ecosystem performance has been the successor to the ecosystem structure. Tongway and Hindley introduced a Landscape Function Analysis (LFA) method in 2004 to evaluate the ecosystem Function. In the new method, soil is considered as the most important element in rangeland ecosystems in order to determine the spectacle function, because the ecosystem status can be determined by examining the changes in the soil surface indexes, and this was possible for the expert to judge the changes brought about by the management and ecological practices of the rangeland.This research was carried out with the aim of evaluating the effect of change of rangeland conversion to farmland and its land use change effect on ecosystem function in rangelands of Navar area in the suburbs of Sanandaj.
    THEORETICAL FRAMEWORK: The importance of soil surface indexes has been expressed by various researchers such as the high correlation between basal cover and disruption of water flow, the importance of canopy size as an indicator of the distribution of soil resources, the effect of plant composition on organic carbon changes, soil permeability, the effect of bare soil on the potential of erosion and the importance of cryptogam cover in soil stabilization. Landscape Performance Analysis (LFA) is a method of monitoring with quantitative indicators. In this method, 11 indicators of soil surface area have been used to evaluate three functional properties including stability, permeability and elemental cycle.
    Methodology
    The study area was divided into two landscapes. Based on the LFA method, three 50-meter transects were deployed in a 10-meter intervals along the slopes. During each transect, the length and width of patches included shrub, grass, forb and combination (combination of all patches and space between pieces (bare soil) were recorded. For each patch and inter-patch, five replicates were determined and for each replication the 11 soil surface parameters were evaluated. The soil surface parameters were evaluated for each ecological patch and inter-patch according to the LFA method. To evaluate three functional properties including stability, permeability and elemental cycle, and calculating 11 soil surface indexes, the LFA guidelines and the LFA software designed in the Excel environment were used.
    Results
    The results showed that the total stability index in the rangeland (47.2%) was higher than that of the dryland (24.4%) and their difference was significant (p CONCLUSIONS AND SUGGESTIONS: In general, the two landscapes have different functions depending on environmental factors and vegetative forms. The presence of independent grass patches in the rangeland (ecological indicator of rangeland) and the presence of a small number of combined patches (3 pieces) and shrub patches in the abandoned dryland (the ecologically indicator of this landscape) are due to the difference in the function of these landscapes. The rangeland has the highest function and the abandoned dryland has the lowest function. It can also be argued that LFA is a simple and fast method for assessing the function of rangeland ecosystems. In fact, saving time and cost of decision-making on management projects will reduce the risk of any operation at natural ecosystems.
    According to the results, it can be stated that the change in the utilization of the rangeland to dryland has reduced the ecosystem stability index and thus provided the soil surface with more soil erosion. Therefore, we must strictly prevent rangeland conversion to dryland.
    Keywords: Ecosystem Function, Vegetation, Soil Indices, land use change, Soil Erosion, Kurdistan Province
  • Hamidreza Koohbanani, Jamal Dashti Amirabad, Dr Shima Nikoo*, Ali Taya Pages 35-49
    Introduction
    Destructive phenomenon of desertification is one of the serious ecological crises at the present time. In order to improve efficiency of combating desertification projects and inhibiting destruction of natural resources and our asset, it sounds considerably meaningful to reach a systematic and comprehensive method that can use different criteria and indicators to provide optimal solutions. Traditional models of desertification assessment are based on defined thresholds and limits and in the real nature of ecosystems, there are no boundaries and contractors. So, there is always a level of uncertainty in the phenomena such as desertification mapping.
    THEORETICAL FRAMEWORK: Land degradation assessment strategies are based on experts’ opinions, and usually the evaluation methods based on multi-criterion decision-making models are not concerned in Iran. Until now, clear and uniform procedures for the classification of desertification have not been provided based on desertification processes. In this regard, the identification and evaluation processes, and the identification of current state of desertification intensity are generally among the basic requirements of desert areas. In the present paper, the fuzzy approach, as one of the effective ways to assess desertification, has been used. For this purpose, it should be noted that in fuzzy methods, the thresholds of each class can be reviewed in different management scenarios.
    Methodology
    Some indices of climate, soil and water criteria were selected to be considered for each condition of the region. The samples were collected in homogeneous units in Deyhook basin. The next step was converting layers to fuzzy layers by linear functions of fuzzy membership. Final desertification intensity was calculated based on fuzzy overlaying via gamma operators of the selected criteria and their indices on a scale of zero to one. The numerical value was reclassified into 4 levels including low, medium, severe and very severe, and the desertification intensity map was drawn using GIS in the studied period. For the vegetation and precipitation indices, the decreasing fuzzy function, and for the others, the increasing fuzzy function were used.
    Results
    According to the results, among the studied areas, approximately 14.5% of the area was very severely degraded and 3.5 percent was in the intensity of severe class. Most of the basin was allocated to the moderate intensity of desertification class and if the current trends continued increasing desertification, it would be under more severe desertification risk. It is important that severely and very severely degraded areas have the largest population centers. In fact, these areas are located mainly in rural areas, and it seems that the population pressure makes an improper use of surface and underground water resources. According to the results, 81 percent of the basin, sodium adsorption ratio is higher than 32. Aside from sodium ion toxicity effects on plants, along with increasing SAR, available water for plants is reduced subsequently. According to the results of the current study, 91 percent of the basin Deyhook, EC soil is more than 17 dS m. High salt levels lead to plant growth reduction and biomass loss.
    CONCLUSIONS AND SUGGESTIONS: The strength of fuzzy method is that the indices map and the final map of desertification have a dynamic and continuous nature, and therefore, the intensity class boundaries can be changed according to the user requirements in various management and land reclamation scenarios. Given that environmental restrictions in the basin Deyhook are very intense, so changes in the cropping pattern, dependent reduction in livestock pastures, reduction of human dependence on nature and the use of varieties resistant to drought and salinity are among the cases that can be offered to slow the desertification Deyhook basin. It is recommended in the mentioned basin that halophytes species and tolerant species such as Salsola and Atriplex be utilized in agricultural and rangeland management plans.
    Keywords: Zoning, desertification, fuzzy logic, linear membership function, Gis
  • Dr Gholamhossien Abdollahzadeh*, Miss Nadia Farahi, Dr Mohammad Sharif Sharifzadeh Pages 50-68
    Introduction
    Soil as one of the most important inputs in agricultural production process plays an important role in the quality of production operation, food security and sustainable development. On the other hand, soil erosion as one of the environmental agriculture issues has been intensified with increasing population and transforming to intensive forms of agriculture in recent years. Minodasht County in Golestan province of Iran is faced daily with the phenomenon of erosion which contributes to weakening agro-silvo-pastoral production. According to many previous investigations, soil degradation is one of the basic problems facing villages within Minodasht County in their efforts to increase production and reduce poverty and food insecurity. In order to avoid or mitigate these detrimental environmental effects, a number of conservation measures can be undertaken by farmers. Hence, the purpose of this study was to investigate factors affecting the adoption of soil conservation practices in horticulture lands of Chehel-Chai watershed basin.
    THEORETICAL FRAMEWORK: There are three groups of adoption models: (i) the innovation-diffusion model, (ii) the economic constraints model, and (iii) user-technique characteristics model. The third group is of interest to us principally because of the difficulties involved in collecting data for the first two, and because of our working hypotheses. According to this model, the characteristics of the technique, within the institutional and socio-economic context of production, play a central role in the adoption process. In the same way, it takes into consideration the diversity of activities having an influence on adoption. Moreover, this user-technique model integrates the perception of the individual, which has rarely been studied.
    Methodology
    The target population of this research consisted of 623 fruit growers of Chehel-Chai watershed, out of which 241 samples were selected through cluster sampling from 12 villages. Chehel-Chai watershed is characterized by a high degree of soil degradation and common practices of soil conservation, i.e. the use of strip crops and crop rotation. The data were collected via questionnaire whose validity was confirmed by some experts’ comments, and also its reliability was confirmed through calculating Cronbach Alpha for perception items of benefits (0.78) and cost using of soil conservation measures. The data collected through survey were processed using Statistical Package for Social Sciences (SPSS) and Eviews.
    Results
    The results showed that 53.5 percent of the respondents stated that their garden needs urgent soil conservation measures, while only 37.8 percent of respondents using one of the soil conservation methods among which permanent soil cover by simultaneous cultivation and strip cropping were the main conservation methods that are mostly used. The results showed that 48.1 percent had little awareness regarding the soil conservation methods. Among the items related to benefits of conservation agriculture, the items such as, increase soil fertility and reduce runoff pollution were more important, and the items related to cost of soil conservation such as high risk of new methods and increasing labor costs have a higher priority. The results of running logit model showed that agricultural experience, age, and perceived costs of conservational agriculture have a negative impact while the variables frequency of flooding, awareness of soil conservation methods, using soil tests in the garden, existence of soil erosion, area of slop land, land size and income have a positive and significant impact on the adoption of soil conservation methods.
    CONCLUSIONS AND SUGGESTIONS: Soil degradation due to erosion in the study area was increased which led to a significant decrease in land performance and that is why the respondents had a great desire to the adoption of soil conservation measures. The combination of individual variables, farm level, perception of costs and benefits of conservational agriculture, and knowledge and awareness of soil erosion influences the adoption soil conservation methods. These components must be considered in the design of extension programs to increase the effectiveness of this program to encourage the adoption and use of conservation methods.
    Keywords: Soil erosion, soil conservation, adoption, Chehel-Chay watershed
  • Pages 69-89
    Introduction
    The gully erosion occurrence, due to the high rate of sediment production in the watershed, is one of the problems of natural resources management in the context of soil management and protection. It is known as an important signature of land degradation and forming as well as a source of sediment in a range of environments. Gully erosion often has severe environmental and economic ramifications worldwide such as destroying soil, damaging agricultural fields, undermining infrastructure, altering transportation corridors, and degrading surface water quality, which can be difficult to reverse. In this study, the potential of gully erosion occurrence was evaluated using Shannon entropy and statistical index models in the Seymareh region of Lorestan province. Firstly, digital layers of gully conditioning factors including altitude, lithology, slope angle, slope aspect, land use, distance from river, soil, topographic wetness index and stream power index were produced using ArcGIS 10.2. In modeling the gully erosion occurrence, the mentioned factors were regarded as independent variables and gully erosion occurrence was considered as dependent variable, whose interrelations will be determined based on Statistical Index and Shannon's entropy models.
    Methodology
    Initially, a gully erosion inventory was prepared through a field survey. An inventory of 100 gullies was randomly divided into training group (70 %) and validation group (30 %). The weight of each conditioning factor was determined through the probability analysis of Statistical Index and Shannon's entropy models. The weights of gully conditioning factors were specified in each model based on the frequency and density of gullies. These weights were associated to each class of conditioning factors in GIS environment. Then, the map of gully-prone areas was produced using both models. Subsequently, the produced maps were validated using receiver operating characteristic (ROC) curve method and validation group. The area under this curve (AUC) was calculated for the quantitative comparison of models performances. Finally, the gully erosion potential values were reclassified into four levels, including ‘low’, ‘medium’, ‘high’, and ‘very high’ susceptibility, using the natural breaks.
    Results
    The results showed that the generated maps based on Statistical Index and Shannon's entropy models have the prediction accuracy rate of 77.3 % and 79.8 %, respectively, implying that these models are capable of detecting gully-erosion-prone areas. In addition, according to the Shannon entropy results, lithology, elevation, and land use were represented as having significant effects on the gully erosion occurrences. Visually, the highest gully erosion susceptibility of the Seymareh region was located on the center, eastern and western parts of the study area where the lithology and land use are Quaternary deposits and agriculture, respectively. From a geomorphological point of view, the areas with gentle slopes, located in high TWI and near the streams show a high gully erosion susceptibility.
    Discussion and
    Conclusions
    These models exhibited acceptable cases of accuracy for the area under study, indicating that they are highly appropriate for gully erosion susceptibility mapping. This study, not only analyzed the relationship between the gully erosion inventory and geo-environmental variables, but also illustrated susceptibility to gully erosion based on statistical analysis of conditional probability technique. Determining the susceptibility level of different regions in terms of gully erosion occurrence in order to measure the soil erosion protection is necessary, which was provided in the current study. The results of the study can provide useful information to understand gully erosion mechanisms and scientific policy-planning and decision-making in the semi-arid regions.
    Keywords: management, protection of soil, validation, geo-environmental variables, spatial prediction
  • Dr Sedigheh Mohamadi* Pages 90-113
    Introduction
    According to the complexity of environmental factors related to erosion and runoff, correct simulation of these variables find importance under rain intensity domain of watershed areas. Although modeling of erosion and runoff by Artificial Neural Network and Neuro-Fuzzy based on rainfall-runoff and discharge-sediment models were widely applied by researchers, scrutinizing Artificial Neural Network and Neuro-Fuzzy models based on environmental factors has been paid less attention. Therefore, this study aimed at determining the efficiency of different models including Artificial Neural Network, Neuro-Fuzzy and Multivariate Regression for runoff and erosion simulation using rainfall simulator in some catchments of the North-West of Iran selected in terms of the same rain intensity of half an hour with a 10-year return.
    THEORETICAL FRAMEWORK: Modeling runoff and erosion relations with environmental factors under prevelant rainfall intensity in a watershed scale are considered as the novel aspect of recognition of these complex relations. In this regard, implementation of determined rainfall intensity in a watershed scale is needed in the utilization of rainfall simulator apparatus. Also, the complexity of runoff and erosion relations with the environmental factors is the reason for the application of different models including Artificial Neural Network, Neuro-Fuzzy and Multivariate Regression. In fact Artificial Neural Network models are able to recognize the complex and unknown relations based on working as human brain. The simulation by these models finds importance when these relation have a non-linear feature. Parallel and Distributive processing of information and interpolation ability are major properties of Artificial Neural Network and Neuro-Fuzzy models characterized in the utilization of these models in the correct simulation of complex relations.
    Methodology
    The establishment of rainfall simulator conducted at 86 sites and 21 environmental variables (the characteristics of topography, pedology, vegetation and species diversity) were used as inputs to models. In this regard, Topographic characteristics (including elevation, slope and …) of established sites of rainfall simulator apparatus were first recorded. Then sampling of soil was done from 4 corners of each site and compounded in order to eliminate soil heterogenic effects. After providing one soil sample from each site, all samples were sent to soil laboratory for measurement and analysis of different pedology properties including soil organic matter, total nitrogenous, absorbable phosphorus, available potassium, pH, electrical conductivity, soil moisture, calcareous content, gypsum content, Ca cation, Na cation, soil texture, distribution of clay, silt and sand percentage of soil. Also, vegetation characteristics including canopy cover, pavement and stone percentage and species abundance of each site was investigated in plot of simulator apparatus. Abundance parameter of species in each site was used for determining different species diversity indices (including species number, Simpson, Shannon-wiener and dominance indices) in PAST software package. Implementation of determined rainfall intensity of each site by simulator apparatus was finally performed for the measurement of runoff and erosion variable. Analysis of data was done through Multivariate Regression in SPSS software package, simulation via Artificial Neural Network (multi - layer perceptron and radial basis function methods), and Neuro-Fuzzy models was performed via MATLAB software package. Model validation conducted on 18 percent of the data based on Root of Mean Square Error, Nash–Sutcliffe Efficiency and Mean Absolute Error indices.
    Results
    The results of Multivariate Regression model of this research showed that variables such as soil moisture, absorbable phosphorus, canopy cover percentage and soil sand percentage caused for runoff content and variables as calcareous content, total nitrogenous, canopy cover percentage, soil organic carbon and land slope determined erosion variable. In this regard, Multivariate Regression model was able to explain 68% and 46 % of changes in the runoff and soil erosion variables and its efficacy was lower in the simulation. As a result, Radial Basis Function neural network model compared with Multi Layer Perceptron as well as Neuro-Fuzzy model with scenarios of cluster (hybrid procedure) compared to grid method was able to predict more accurately. As indicators of RMSE, MAE and NSE were gained on optimum model of neural networks of 0.135, 0.114 and 0.99 for runoff volume, 0.011, 0.009 and 0.98 for the erosion and on optimum model of neuro-fuzzy models of 0.132, 0.111 and 0.92 for the volume of runoff and 0.013, 0.011 and 0.98 for the erosion, respectively.
    CONCLUSIONS AND SUGGESTIONS: In general, it can be concluded that according to the presence of the complex environmental relations of erosion and runoff variables, Artificial Neural Network model with Radial Basis Function method and Neuro-Fuzzy model with scenarios of cluster (hybrid procedure) are recommended to be simulated based on ecological factors.
    Keywords: Multi Layer Perceptron, Radial Basis Function, Neuro-Fuzzy, rainfall simulator
  • Fardin Moradzadeh, Seyed Ataollah Hosseini*, Ehsan Abdie, Ataollah Kavian Pages 114-126
    Introduction
    Forest is a sustainable ecosystem with a high balance, and is characterized by non-eroded soils and sediment-free water. Forest roads serve as the largest construction activities and a component added to the forests which are required for the accessibility to forests and forest resources, logging, transportation, conservation, tourism, etc. However, these changes in the dynamic environment of forest structure cause many disruptions in the natural behaviors of environmental factors affecting the forest structure. Roads create surfaces without vegetation which can serve as a starting point for runoff, disrupting and diverting the natural flow and sudden accumulation of water, diverting the natural down-slope drainage route, accumulation of water and transmitting it to other sub-basins, changing the runoff pattern and carrying deposits due to the increased water velocity and ultimately the destruction of the forest. Studies have shown that forest roads are among the main sources of sediment transport into rivers, and approximately 90% of the sediment coming from a forested area into rivers originates from forest roads. Increased sediment transport into rivers can cause irreparable damages to water quality, ecosystems and aquatic organisms. Therefore, forest road experts should consider not only the road construction costs but also the environmental damages caused by the road operation.
    Methodology
    Among the challenges for forest managers is the accurate design and construction of forest roads with required standards and minimum possible costs. Ignoring these defined measures and standards will result in the financial and environmental damages. One of the most important standards for road construction is road longitudinal slope angle. Determining the relationship between road longitudinal slope angle with runoff amount and the volume of produced sediment helps to manage the road network for constructing new roads in accordance with the standards, to define new standards, and to predict the maintenance of roads.
    This research aims at evaluating the impact of road longitudinal slope angle in the forest roads (Main Access and Main Roads) of Gardeshi district (Sari, Mazandaran Province) on runoff and soil loss through applying simulation techniques and artificial rainfall simulator in a completely randomized design on 1 m2 plots with 4 replicates in 3 slope classes in each road. Then, sediment and runoff during rainfall simulation performed with a constant intensity of 60 mm h-1 was measured for 30 minutes in each slope class. The district was selected so that the other parameters such as road surface area, traffic, and rainfall were fixed, and only the effect of road longitudinal slope angle on runoff and sediment was addressed.
    Results
    Results showed the average produced runoff, runoff coefficient and sediment concentration in slope classes of 1 (3 – 5%), 2 (5 – 8%) and 3 (more than 8%) on grade 1 road. The runoff volumes were 15.9, 17, and 18.78 L m2, with the corresponding runoff coefficients of 53%, 56.66%, and 62.58% and soil loss values of 6.12, 9.05, and 12.38 g L-1, respectively. Results also showed the average produced runoff, runoff coefficient and sediment concentration in slope classes of 1 (0-3%), 2 (3-6%) and 3 (6-9%) on grade 2 road. The runoff volumes were 19.92, 21.25, and 22.8 L m2, with the corresponding runoff coefficients of 66.41%, 70.83%, and 76% and soil loss values of 8.51, 10.17, and 16.82 g L-1, respectively. Results of ANOVA showed a significant difference between the amount of runoff and sediment in road slope classes. The results of Tukey test indicated that runoff and sediment significantly increased with an increase in the slope. Results of Independent t-test showed that the mean values of runoff volume, runoff coefficient and sediment concentration were 23.33 L, 71% and 11.84 g per liter in the grade 2 road compared to 17.23 L, 57% and 9.18 g per liter in the grade 1 road. According to the F (0.85) and P (Discussion &
    Conclusions
    It can be concluded that road longitudinal slope angle is one of the most important factors determining the amount of runoff and sediment on the road, so that the amount of runoff and sediment will increase with an increase in the slope, which should be considered according to the location of road.
    Keywords: rain simulator, forest roads, Gardeshi district, sediment, runoff, road longitudinal slope angle