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نوع مقاله : مقالات پژوهشی

نویسندگان

1 گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند، بیرجند، ایران

2 دانشیار، گروه علوم و مهندسی آب، دانشگاه بیرجند، بیرجند، ایران،

3 دانشیار گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند، بیرجند، ایران

چکیده

زمینه و هدف: با توجه به نیاز روزافزون جوامع بشری به منابع آب زیرزمینی، حفاظت و جلوگیری از آلودگی این منابع امری ضروری تلقی می‌گردد. مطالعه حاضر با هدف ارزیابی آسیب‌پذیری آبخوان آب زیرزمینی آبخوان دشت آستانه- کوچصفهان استان گیلان، با استفاده از روش دراستیک و مدل‌های ناپارامتریک انجام شد.
مواد و روش‌ها:در این پژوهش، پارامترها به صورت 7 لایه در محیط نرم‌افزار سیستم اطلاعات جغرافیایی (GIS) برای دشت تهیه و پس از وزن‌دهی و ترکیب رتبه‌های استاندارد، نقشه آسیب‌پذیری آب‌های زیرزمینی دشت با استفاده از روش دراستیک تعیین گردید. برای صحت‌سنجی مدل، از داده‌های نیترات در منطقه استفاده شد. سپس با کمک مدل‌های ناپارامتریک یادگیری بر پایه نمونه با پارامتر K و درخت تصمیم M5 مقدار نیترات تخمین زده شد. همچنین آزمون گاما برای یافتن بهترین ترکیب پارامترهای ورودی اجرا گردید.  
یافتهها: بر اساس نتایج این پژوهش، آسیب‎پذیری آبخوان دشت کوچصفهان در 56/18% دارای آسیب‌پذیری اندک، 29/51% دارای آسیب‎پذیری اندک تا متوسط، 46/28% دارای آسیب‎پذیری متوسط تا زیاد و 67/1% دارای آسیب‎پذیری زیاد می‎باشد. همچنین هر دو مدل ناپارامتریک به‌کار گرفته شده تخمین مناسبی از مقدار نیترات می‎دهند، اما مدل M5 بهترین نتایج را دربرداشت (98/0=R2).
نتیجهگیری:مدل‌های ناپارامتریک، روشی کارا در تخمین آسیب‌پذیری آبخوان محسوب می‌شوند و نتایج دقیقی از برآورد پتانسیل آلودگی در منطقه می‌دهند. این نکته برتری مدل M5 نسبت به سایر روش‌های مورد بررسی در آسیب‌پذیری آبخوان را نشان می‌دهد.
نوع مقاله: پژوهشی

کلیدواژه‌ها

عنوان مقاله [English]

Comparison of Standard Drastic and Nonparametric Models Instance-Based Learning with parameter K (IBK) and the Tree Decision M5 in Determination of Groundwater Pollution Potential (Case study: Kuchesfahan- Astane plain)

نویسندگان [English]

  • Samira Rahnama 1
  • Hossein Khozeymehnezhad 2
  • Abbas KhasheiSiuki 3

1 Water Engineering Department, College of Agriculture, University of Birjand, Birjand, Iran.

2 Associate professor, Department of Water Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran.

3 Associate professor, Water Engineering Department, College of Agriculture, University of Birjand, Birjand, Iran

چکیده [English]

Background and Aim:Due to the increasing demands of the human population to groundwater, protection and prevention of these water resources from pollution are necessary. The purpose of this study was to evaluate the vulnerability of groundwater aquifer in Kuchesfahan- Astane plain located in Gilan province using DRASTIC method and nonparametric models.
Materials and Methods:In this study, seven layers were prepared for parameters in GIS software, and after weighting and combining standard ranks, the groundwater vulnerability maps for the study area were prepared. Nitrate data were used to validate the model in this region. Subsequently, by using the nonparametric models, Instance-Based Learning with parameter K (IBK) and the Tree Decision M5, the amount of nitrate was estimated. Meanwhile, Gamma test was conducted to find the best combination of input parameters.
ResultsThe results revealed that the vulnerability of groundwater aquifer in this plain has 4 classes including 18.56 % in low vulnerability, 51.29 % in low to medium vulnerability, 28.46% in medium to high vulnerability, and 1.67% in high vulnerability classes. Also, the results showed that both of the nonparametric models have suitable estimates of the nitrate content, but the M5 decision tree model yielded the best results (R2=0.98).
Conclusion:The results showed that nonparametric models are efficient method to estimate the aquifer vulnerability and provide accurate results to estimate the potential of contamination in the study area.This demonstrates the superiority of the M5 model over other aquatic vulnerability assessment methods.

کلیدواژه‌ها [English]

  • Decision tree
  • Geographic Information System
  • Groundwater
  • Population
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