پیش بینی سطح آب زیرزمینی با استفاده از مدل ترکیبی سری زمانی-موجک (مطالعه موردی: دشت فیروزآباد)

نوع مقاله: مقاله پژوهشی

نویسندگان

1 فارغ التحصدانشجوی کارشناسی ارشد مهندسی منابع آب دانشگاه شهید چمران اهواز.یل دانشگاه شهید چمران اهواز

2 دانشیار گروه هیدرولوژی و منابع آب دانشگاه شهید چمران اهواز

3 دانشگاه شهدانشیار گروه هیدرولوژی و منابع آب دانشگاه شهید چمران اهواز.ید چمران اهواز

4 استادیار گروه آمار دانشگاه شهید چمران اهواز.

5 دانشجوی دکترای مهندسی منابع آب دانشگاه شهید چمران اهواز.

چکیده

در سال­های اخیر، پدیده تغییراقلیم، خشک­سالی، برداشت بی­رویه آب­های زیرزمینی،... باعث افت شدید سطح آب­های زیرزمینی شده است؛ که خطراتی هم­چون نشست زمین و افزایش کویری شدن را در پی داشته است. لذا پیش­بینی قابل اطمینان سطح آب­های زیرزمینی برای مدیریت این منابع، حائز اهمیت است. امروزه تبدیل موجک از طریق تجزیه سیگنال­ها به زمان و فرکانس شیوه نوینی را برای پردازش سیگنال ارائه می­دهد. در پژوهش حاضر، به بررسی کاربرد استفاده از مدل­های سری زمانی و مدل ترکیبی سری زمانی-موجک برای پیش­بینی سطح آب زیرزمینی دشت فیروزآباد اقدام گردید. برای این منظور سری زمانی با استفاده از تبدیل موجک، توابع مختلف موجک (هار، سیملت، کویفلت، دی بی و دی بی4)، در سطوح متفاوت تجزیه، به زیرسری­هایی تبدیل شد. سپس به­عنوان ورودی مدل سری زمانی آریما درنظرگرفته شد. سپس نتایج آن با نتایج مدل سری زمانی مقایسه شد. نتایج نشان­دهنده کارایی بهتر و خطای کمتر مدل ترکیبی سری زمانی-موجک بود.

کلیدواژه‌ها


عنوان مقاله [English]

A combined Time Series – Wavelet Model For Prediction of Ground Water Level (Case Study: Firuzabad Plain)

نویسندگان [English]

  • Seyedeh Marziyeh Salehi 1
  • Feridon Radmanesh 2
  • Heidar Zarei 3
  • Behzad Mansouri 4
  • Abazar Solgi 5
1 MSc of Water resource Engineering Department of Shahid Chamran University of Ahvaz, Iran.
2 Associate Professor, Water Engineering Department, Shahid Chamran University of Ahvaz, Iran
3 Associate Professor, Water Engineering Department, Shahid Chamran University of Ahvaz, Iran.
4 Assistant Professor, Faculty of Mathematics and Computer Sciences, Shahid Chamran University of Ahvaz, Iran.
5 PhD Candidate, Faculty of Water Sciences, Shahid Chamran University of Ahvaz, Iran.
چکیده [English]

Recently, the phenomenon of climate change, drought, the exploitation of the ground water has caused a sharp decline in groundwater levels, which has also led to groundwater related subsidence and desertification. Therefore, reliable prediction of groundwater level for managing these resources is of prime importance. Nowadays wavelet transforms through signal decomposition to time and frequency has created an exceptional method for signal processing, with the help of the transformation of the wavelet that has the ability to split the time series into a multi-dimensional substrate with different scales.
One of the useful characteristics of wavelet transforms is the filtering algorithm, which divids the data into two groups of approximation and details by passing them through the wavelet filter. In this study, monthly groundwater surface, rainfall, and temperature data were used. Using the program code written in MATLAB software, it is necessary to analyze the time series data of all three parameters of temperature, precipitation, and water level. The values ​​of the parameters were selected as inputs and placed in the wavelet function. For analyzing all the parameters, according to various mother-wavelet experiments, and considering the above mentioned point, five mother-wavelets (Haar, Coif, Symlet, Db, Db4) were selected. For this purpose, the program was first implemented for each of the following wavelets with 4 different decomposition levels. After several software runs under specific conditions and scenarios and then comparing them with each other, results were obtained.

کلیدواژه‌ها [English]

  • Wavelet
  • Time series
  • ARIMA
  • Ground water
  • Firuzabad

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