برآورد سرعت نفوذ نهایی خاک با استفاده از الگوریتم خوشه‌بندی فازی، روش نرو-فازی (ANFIS) و نظام استنتاج فازی (FIS)

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری

2 دانشیار دانشکده منابع طبیعی دانشگاه علوم کشاورزی و منابع طبیعی ساری

3 فارغ التحصیل کارشناسی ارشد آبخیزداری، دانشکده منابع طبیعی دانشگاه علوم کشاورزی و منابع طبیعی ساری

چکیده

نفوذ در هیدرولوژی سطحی و زیر سطحی نقش مهمی ایفا کرده و عامل کلیدی در معادلات بارش و رواناب است. استفاده از روش‌هایی که محدودیت‌های روش‌های تئوری و تجربی متداول تعیین روابط نفوذ را نداشته باشد، لزوم انجام آزمایش‌های پرهزینه و زمان‌بر تعیین مقادیر نفوذپذیری را به حداقل رسانده و تخمین مقادیر کاربردی آن را ممکن خواهد ساخت. در همین راستا در این تحقیق، میزان نفوذپذیری خاک در دشت ساحلی بهشهر-گلوگاه واقع در استان مازندران با استفاده از روش فازی، الگوریتم خوشه‌بندی فازی و همچنین شبکه عصبی-فازی انطباقی (نرو-فازی) برآورد گردید به‌طوری‌که درصد رطوبت وزنی پیشین خاک، درصد مواد آلی خاک و درصد آهک خاک به عنوان پارامترهای ورودی و سرعت نفوذ نهایی خاک به عنوان پارامتر خروجی مدل‌ها در نظر گرفته شدند و نتایج به­دست آمده از این سه روش با مقادیر مشاهده‌ای نفوذ نهایی به روش تک‌ استوانه مورد مقایسه قرار گرفت. بر اساس نتایج به­دست آمده، روش نرو-فازی با میانگین انحراف 0042/0سانتی‌متر در دقیقه، میانگین اختلاف 67/0 سانتی‌متر در دقیقه، ریشه­ میانگین مربعات خطای 21/1 سانتی‌متر در دقیقه و ضریب همبستگی 92/0 بهترین عملکرد را در تخمین سرعت نفوذ نهایی خاک در بین مدلهای مورد مطالعه نشان داد، در‌‌ حالی‌که الگوریتم خوشه­بندی فازی با میانگین انحراف 0075/0، میانگین اختلاف 12/2، ریشه­ میانگین مربعات خطای 02/2 و ضریب همبستگی 88/0 و سیستم استنتاج فازی با میانگین انحراف 016/0، میانگین اختلاف50/2، ریشه­ میانگین مربعات خطای 45/2 و ضریب همبستگی 82/0 به ترتیب در رتبه‌های بعد قرار گرفتند. همچنین بیشترین همبستگی میان مقادیر مشاهده‌ای و برآورد شده در مدل نرو-فازی (85/0=R2) مشاهده گردید و پس از آن، مدل‌های الگوریتم خوشه‌بندی فازی (77/0=R2) و سیستم استنتاج فازی (66/0=R2) قرار گرفتند. در پایان این تحقیق پیشنهاد گردیده است تا با تهیه داده­های بیشتر از مشخصات فیزیکی و شیمیایی خاک‌ها و مقادیر نفوذپذیری محدوده مطالعات زمینه تخمین و مقایسه دقیق‌تر مدل‌های مورد مطالعه فراهم گردد.

کلیدواژه‌ها


عنوان مقاله [English]

Estimation of Final Soil Infiltration Rate Using Fuzzy Clustering Algorithm, Nero Fuzzy (ANFIS) and Fuzzy Inference System (FIS) (A Case Study: Behshahr Plain, Galougah, Mazandaran, Iran)

نویسندگان [English]

  • Iman Saleh 1
  • Ataollah Kavian 2
  • Zeynab Jafarian 2
  • Reza Ahmadi 3
چکیده [English]

Infiltration plays an important role in surface and subsurface hydrology and it is a key factor in the rainfall and runoff equations. The use of new approaches that have no limitations of common theoretical and empirical methods to determine infiltration relationships, will minimize the necessity of time consuming and costly experiments to determine permeability values and will make it possible to estimate the functional values. In this regard, in the present study the amount of soil permeability was estimated in Behshahr plain of Galougah located in Mazandaran province, using Fuzzy Inference System (FIS), Fuzzy Clustering Algorithm (FCA) and Nero-Fuzzy (ANFIS); so that, initial soil moisture content, soil organic matter content and soil lime content were considered as input parameters, and final soil infiltration rate was considered as output parameters of the models. Finally, the results obtained by the three mentioned modes were compared to the observed values by single-ring approach. According to the achieved results, Nero-Fuzzy approach with a mean deviation of 0.0042 cm/min, BIAS value of 0.6754 cm/min, Root-Mean-Square Error of 1.2096 cm/min and correlation coefficient of 0.9233 showed the most appropriate performance to estimate soil infiltration rate among the studied models; while, Fuzzy Clustering Algorithm with a mean deviation of 0.0075 cm/min, BIAS value of 2.1165 cm/min, Root-Mean-Square Error of 2.0244 cm/min and correlation coefficient of 0.8776, and Fuzzy Inference System with a mean deviation of 0.0161 cm/min, BIAS value of 2.5042 cm/min, Root-Mean-Square Error of 2.4533 cm/min and correlation coefficient of 0.8167 were placed in the next ranks respectively. Also, the highest correlation between observed and estimated values was seen in Nero-Fuzzy model (R2=0.85), and the two other studied models including Fuzzy Clustering Algorithm (R2=0.77) and Fuzzy Inference System (R2=0.66) are at the next ranks respectively. At the end of this research providing more data of soil physical and chemical characteristics as well as permeability amounts has been recommended in order to more accurate estimation of the studied models.

کلیدواژه‌ها [English]

  • Behshahr-Galougah
  • Permeability
  • Soil lime percentage
  • Soil moisture content
  • Soil organic matter
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