تأثیر الگوهای پیوند از دور بر پیش بینی نوسانات آب زیرزمینی (مطالعه موردی: دشت گرمسار)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانش آموخته کارشناسی ارشد/ گروه بیابانزدایی-مهندسی آب، هواشناسی کشاورزی، دانشکده کویرشناسی، دانشگاه سمنان، سمنان، ایران.

2 دانشیار/گروه بیابانزدایی، دانشکده کویرشناسی، دانشگاه سمنان، سمنان، ایران.

3 استادیار/ گروه بیابانزدایی، دانشکده کویرشناسی، دانشگاه سمنان، سمنان، ایران.

چکیده

سیگنال‌های آب و هوایی با منشأ خارجی به نام پیوند از دور نیز می‌توانند موجب تغییرات شرایط آب و هوایی شوند و از این طریق بر روی منابع آب زیرزمینی تأثیر ‌گذارند. هدف از انجام پژوهش حاضر پیش‌بینی تأثیر الگوهای پیوند از دور بر نوسانات سطح آب زیرزمینی دشت گرمسار می‌باشد. برای انجام این تحقیق از آمار چاه‌های مشاهداتی، پارامترهای آب و هواشناسی منطقه و همچنین 16 شاخص پیوند از دور طی یک دوره‌ی آماری 1372 تا 1395 استفاده گردید. برای آنالیز حساسیت و تعیین ترکیب بهینه ورودی‌ها برای مدل‌سازی از آزمون گاما استفاده گردید. مدلسازی با رگرسیون چندگانه و همچنین شبکه عصبی مصنوعی پرسپترون چندلایه (MLP) با دو الگوریتم لونبرگ-مارکوارت و تنظیم بیزین انجام گرفت. نتایج آنالیز حساسیت ورودی های مدل با آزمون گاما نشان داد، که از بین پارامترهای آب و هوای منطقه، پارامتر دمای حداکثر ایستگاه فیروزکوه و شاخص های پیوند از دور SOI، EA، NP و WP بیشترین تاثیر را در بین ورودهای منتخب داشته اند. همچنین بهترین مدل، روش شبکه عصبی با الگوریتم یادگیری تنظیم بیزین می باشد، که در مرحله تست مدل در چاه سردره، مقدار خطایی برابر 36/0 و ضریب تبیین 93/0 و در چاه شماره 26 این مقدار به ترتیب برابر 038/0 و 85/0 می باشد. همچنین نتایج بدست آمده نشان داد، که استفاده از شاخص های دور پیوندی برای پیش‌بینی نوسانات سطح آب زیرزمینی در چاه سردره، میزان خطا را 6/5 درصد و در چاه شماره 26، تا 24 درصد کاهش می دهد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Influence of teleconnection patterns on prediction of groundwater level fluctuations (Case Study: Garmsar Plain)

نویسندگان [English]

  • Zahra Azizi 1
  • Mohammadreza Yazdani 2
  • Mohammad kia kianian 3
1 M.Sc. Graduate of Water Engineering, Agriculture Meteorology, Faculty of Desert Studies, Semnan Unversity, Semnan, Iran.
2 Associate Professor, Faculty of Desert Studies, Semnan Unversity, Semnan, Iran.
3 Assistant Professor, Faculty of Desert Studies, Semnan Unversity, Semnan, Iran.
چکیده [English]

External source of weather signals is also called teleconnections that can change weather conditions and thus affect groundwater resources. The purpose of this study is to predict the effect of teleconnection patterns on groundwater level fluctuations in Garmsar plain. Data of groundwater level, climatic parameters of the study area, as well as 16 teleconnection indices from 1993 to 2016 were used for this study. Gamma test was used to analyze inputs sensitivity and so determine the optimal combination of inputs. Modeling was performed with multiple regression as well as multilayer perceptron artificial neural network (MLP) with two learning algorithms of Levenberg-Marquardt and Bayesian.
Sensitivity analysis of model inputs with gamma test showed that among the climate parameters of the region, maximum temperature of Firoozkooh station and also teleconnection indices of SOI, EA, NP and WP had the most influence among the selected inputs. The results of the modeling using the most effective inputs showed that the best model is the neural network method with Bayesian learning algorithm, that in the model testing stage in Sardareh well, the MSE and the R2 were 0.36 and 0.93 respectively. In well 26, these values were 0.038 and 0.85, respectively. Also, rsults indicated that the use of teleconnections indices to predict groundwater level fluctuations in Sardareh well and in well 26 reduced the error rate by 5.6% and by 24% respectively.

کلیدواژه‌ها [English]

  • Teleconnection indices
  • Groundwater
  • Artificial Neural Network
  • Gamma Test
  • Sensitivity analysis
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