تولید نقشه پتانسیل وقوع گرفتگی شبکه فاضلاب شهری با استفاده از شبکه عصبی و GIS (مطالعه موردی: منطقه 2 آبفای تهران)

نوع مقاله : مطالعه موردی

نویسندگان

1 دانشجوی دکترا، گروه سنجش از دور و سیستم اطلاعات جغرافیایی، دانشکده جغرافیا، دانشگاه تهران، تهران، ایران

2 دانشیار، گروه سنجش از دور و سیستم اطلاعات جغرافیایی، دانشکده جغرافیا، دانشگاه تهران، تهران، ایران

چکیده

شبکه فاضلاب به‌عنوان یکی از مهم‌ترین تأسیسات زیربنایی، می‌تواند نقش مهمی را در دستیابی به توسعه پایدار از طریق ارتقای سطح بهداشت عمومی و حفاظت از محیط‌زیست با جلوگیری از آلودگی منابع آبهای سطحی و زیرزمینی داشته باشد. یکی از شایع‌ترین حوادثی که به مقدار قابل‌توجهی در این شبکه اتفاق می‌افتد، گرفتگی در لوله‌های جمع‌آوری فاضلاب است. شناخت عوامل تأثیرگذار در وقوع گرفتگی در شبکه، تأثیر قابل‌توجهی در پیش‌بینی صحیح حوادثی که در آینده برای شبکه ممکن است اتفاق بیافتد، دارد. در این پژوهش، به‌منظور پیش‌بینی و تهیه نقشه پتانسیل وقوع گرفتگی در شبکه فاضلاب، از ابزارهای GIS و شبکه عصبی مصنوعی استفاده شد. فاکتورهای مهم در بروز گرفتگی شامل، کاربری، قطر سیفون، عمق سیفون، عمق و جنس و سن لوله در تحلیل شبکه عصبی استفاده شدند. از داده‌های ورودی به‌ترتیب 70، 15و 15 درصد برای آموزش، اعتبارسنجی و تست مدل استفاده شد. نتایج حاصل از شبیه‌سازی با استفاده از شبکه‌ عصبی با شاخص توافق 9/0R2= تناسب زیادی بین مکان‌های پیش‌بینی شده و مشاهده شده گرفتگی را نشان داد و همچنین در نقشه پتانسیل گرفتگی، محدوده‌هایی با تراکم جمعیت زیاد، بافت فرسوده و ساخت‌و‌سازهای غیرمجاز (به‌دلیل نصب انشعابات غیرمجاز) پتانسیل زیاد گرفتگی مشاهده شد.

کلیدواژه‌ها

عنوان مقاله [English]

Production of Potential Blockage Event Map for Urban Sewer Networks Using Neural Network and GIS (Case Study: Region 2 of ABFA of Tehran City)

نویسندگان [English]

  • Farimah Bakhshizadeh 1
  • Mohammadreza Jelokhani-Niaraki 2
  • Somaye Mahmoudi 1
1 PhD Student, Dept. of Remote Sensing and Geographic Information System, Faculty of Geography, University of Tehran, Tehran, Iran
2 Assoc. Prof., Dept. of Remote Sensing and Geographic Information System, Faculty of Geography, University of Tehran, Tehran, Iran
چکیده [English]

Wastewater network as one of the most important infrastructure facilities can play an important role in achieving sustainable development by improving public health and environmental protection by preventing pollution of surface and groundwater resources. One of the most common incidents that occurs significantly in this network is blockage of the sewer pipes. Recognizing the factors influencing the occurrence of network blockage has a significant impact on accurately predicting what may happen to the network in the future. In the present study, GIS tools and artificial neural network were used to predict and mapping the potential for blockage in the sewer network. Important factors in the occurrence of blockage including, land use, siphon diameter, siphon depth, depth, materials and age of the pipe were used in neural network analysis. From input data of 70%, 15% and 15%, respectively, were used for training, validation and model testing. The results of the simulation using a neural network with a Performance Indicator of R2=0.9 showed a high fitness between the predicted and observed locations of the blockage. Also, in the blockage potential map, areas with high population density, worn texture and unauthorized constructions (due to the installation of unauthorized branches) were observed blockage potential.

کلیدواژه‌ها [English]

  • Wastewater Network
  • GIS
  • Blockage Map
  • Region Two of the ABFA
  • Artificial Neural Network

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مجله آب و فاضلاب
دوره 32، شماره 6 - شماره پیاپی 137
بهمن و اسفند 1400
صفحه 115-129

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