مقایسۀ روش‌های سیستم استنتاج فازی- عصبی تطبیقی (ANFIS)، وزن‌دهی معکوس فاصله و زمین‌آمار در تخمین سطح ایستابی (مطالعۀ موردی: دشت دهگلان، استان کردستان)

نوع مقاله : پژوهشی

نویسندگان

1 استادیار گروه علوم زمین، دانشکدۀ علوم پایه، دانشگاه کردستان

2 دانشجوی کارشناسی ارشد رشتۀ هیدروژئولوژی، دانشگاه ارومیه

3 استادیار گروه زمین‌شناسی، دانشکدۀ علوم زمین، دانشگاه ارومیه

چکیده

افت سطح ایستابی از نظر مدیریتی بسیار اهمیت دارد و می‏تواند تأثیرات منفی مانند نشست زمین، افزایش هزینۀ برداشت و کاهش کیفیت آب زیرزمینی را در پی داشته باشد. آب زیرزمینی مهم‏ترین منبع تأمین آب در دشت دهگلان بوده و برداشت زیاد، سبب کاهش سطح ایستابی در این دشت شده است. این دشت با وسعتی حدود 780 کیلومترمربع، یکی از دشت‏های ممنوعۀ استان است و با افت سطح آبخوان نزدیک به 37 متر، بین دشت‏های استان بیشترین افت را داشته است. هدف از پژوهش حاضر، مدل‏سازی سطح آب زیرزمینی و مقایسۀ عملکرد روش سیستم استنتاج فازی- عصبی تطبیقی با روش‏های وزن‏دهی معکوس فاصله، کریجینگ و کوکریجینگ است. به این منظور، از داده‏های سطح ایستابی 44 حلقه پیزومتر دشت دهگلان مربوط به شهریور 1395استفاده شده است. نتایج به‌دست‌آمده بیان می‌کند که رفتار بار هیدرولیکی در قسمت‏های مختلف آبخوان، متفاوت است و در نتیجه به‌کار‏گیری صرف داده‏های مکانی بار هیدرولیکی برای مدل‏سازی، نتایج رضایت‏بخشی ندارد. سطح ایستابی در دشت دهگلان، با توپوگرافی بیشترین همبستگی را دارد و سیستم استنتاج فازی- عصبی تطبیقی با به‌کارگیری پارامتر کمکی توپوگرافی دارای 07/0RMSE=، 005/0MSE=، 06/0MAE=، 04/0MBE= و 88/0=R2 بوده و نسبت به سایر روش‏ها عملکرد بهتری داشته است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Comparison of Adaptive Neuro-Fuzzy Inference System (ANFIS), Inverse Distance Weighting and Geostatistics Methods for Estimating the Water Table (Case Study: Dehgolan Plain, Kurdistan Province)

نویسندگان [English]

  • Mehdi Kord 1
  • Nasrin Yuosefi 2
  • Esfandiar Abbas Novinpour 3
1 Assistant Professor, Department of Earth Science, Faculty of Science, University of Kurdistan
2 M.Sc. of Hydrogeology, Department of Geology, Faculty of Sciences, Urmia University
3 Assistant Professor, Department of Geology, Faculty of Sciences, Urmia University
چکیده [English]

The decline of water table is very important in from a managerial point of view and might cause negative impacts such as land subsidence, raising costs and reducing groundwater quality. Groundwater is the most important source of water supply in Dehgolan plain. Increasing water requirements and extractions, has declined water table. This plain with an area of about 780 km2 is one of the protected plains of the Kurdistan province and with decrease in water table about 37 meters, it has the most decline between the plains of the province. The purpose of this study is to model the groundwater level and compare the performance of the method of Adaptive Neuro-Fuzzy Inference System (ANFIS) with Inverse Distance Weighted (IDW), Kriging and Cokriging methods. For this purpose, in September 2016, the water table data relating to the 44 Piezometer digged in Dehgolan plain has been used for modeling. The results show that the hydraulic head behavior is different across the aquifer, so the use of spatial data (h) for modeling doesn’t lead to satisfactory outputs. The water table in Dehgolan plain has the highest correlation with topography conditions and the ANFIS with a RMSE = 0.07, MSE = 0.005, MAE = 0.06, MBE = 0.04 and = 0.88 R2, has presented better performance than other methods.

کلیدواژه‌ها [English]

  • Dehgolan Plain
  • Groundwater
  • adaptive neuro-fuzzy inference system (ANFIS)
  • Geostatistics
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