مدل‌سازی نفوذپذیری در رده های گوناگون بافت خاک با الگوریتم‌های یادگیری در آبخیز کشکان، استان لرستان

نوع مقاله : پژوهشی

نویسندگان

1 دانشجوی دکترا، گروه مهندسی مرتع و آبخیزداری، دانشکده ی کشاورزی و منابع طبیعی، دانشگاه لرستان

2 استادیار گروه مهندسی مرتع و آبخیزداری، دانشکده ی کشاورزی و منابع طبیعی، دانشگاه لرستان

چکیده

نفوذپذیری یکی از مهم‌ترین اجزای چرخه ­ی آب­ شناسی است که نقش مهمی در جریان رودخانه­ یی، تغذیه ­ی آب ­های زیرزمینی، جریان­ های زیرسطحی و سطحی، و کمیت و کیفیت آب­ های زیرزمینی دارد. هدف این پژوهش بررسی تغییرات نفوذپذیری و مدل­ سازی سرعت آن در بافت­ های گوناگون خاک در آبخیز کشکان استان لرستان بود. استوانه ­های دوگانه برای اندازه­ گیری نفوذ به‌کار برده‌شد. برای مدل­ سازی از الگوریتم ­های یادگیری GP و SVM (با دو هسته‌ی PUK و RBF)، MLP و RF بهره برده‌شد. مقایسه‌ی نتیجه‌ی مدل­ های گوناگون و انتخاب بهترین مدل با معیار­های سنجش خطای ریشه‌ی میانگین مربع‌های خطا، ضریب همبستگی  و ضریب نش-ساتکلیف انجام شد. نتیجه‌ی ارزیابی نشان داد که بیش‌ترین ضریب کارآیی نش-ساتکلیف (0/98622) و کم‌ترین اندازه‌ی خطا (0/0177) در مدل RF با ضریب همبستگی 0/9953 بود، که دقت زیادی است. تحلیل حساسیت ویژگی ­های ورودی مدل RF نشان داد که زمان مهم‌ترین ویژگی ورودی در پیش ­بینی سرعت نفوذ خاک برای این مجموعه از داده­ های به‌کاررفته در پژوهش است. نتیجه‌های این پژوهش نشان داد که نفوذپذیری در بافت­ های گوناگون خاک تغییرپذیر است، و برای مدیریت‌کردن بهتر تغذیه ­ی سفره ­های آب زیرزمینی باید این سنجه را درنظر گرفت.

کلیدواژه‌ها


عنوان مقاله [English]

Modelling of Infiltration Rate in Different Soil Textures using Soft Computing Techniques in Kashkan Watershed, Lorestan Province

نویسندگان [English]

  • Leili Soleimani 1
  • Bahram Mir Derikvand 1
  • Alireza Sepahvand 2
1 Ph.D. Student, Department of Range and Watershed Management, Faculty of Agriculture and Natural Resources, Lorestan University, Khorramabad, Lorestan Province, Iran
2 Assistant professor, Department of Range and Watershed Management, Faculty of Agriculture and Natural Resources, Lorestan University, Khorramabad, Lorestan Province, Iran
چکیده [English]

Infiltration is one of the most parameters of hydrology that plays a fundamental role in streamflow, groundwater recharge, subsurface flow, and surface and subsurface water quality and quantity. According to the importance of the mentioned subject, the infiltration changes and modeling were investigated in the different soil textures in Kashkan watershed, Lorestan province. In this study, the double-ring infiltrometer was used to measure the infiltration in the different soil textures. Also, Support vector regression (SVM), Gaussian Process (GP), Multi-Layer Perceptron (MLP), and Random Forest (RF) were used to Modeling of infiltration rate in different soil textures. Three statistical comparison criteria including root mean square error (RMSE), coefficient of correlation (C.C), and Nash Sutcliffe (NSE) were used to determine the best-performing infiltration model. The results showed that Random Forest model better estimated infiltration rate (C.C= 0.9912, NSE= 0.98622, and RMSE = 0.0177) compared to the other models. Thus, RF was found to be the most suitable for modeling infiltration in the study area. Also, sensitivity analysis concludes that the parameter time is the most effective parameter for the estimation of infiltration rate. The results indicated that the infiltration varies in the different soil textures, which should be considered in the management of groundwater recharge.

کلیدواژه‌ها [English]

  • Gaussian process
  • infiltration modeling
  • Kashkan watershed
  • Lorestan province
  • random forest
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