تعیین توابع مفصل دو بعدی بهینه در تحلیل تغییرات سطح آب زیرزمینی با استفاده از الگوریتم های فرا ابتکاری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانش آموخته دکتری منابع آب، گروه علوم و مهندسی آب، دانشگاه بیرجند

2 دانشیار گروه علوم و مهندسی آب، دانشگاه بیرجند

3 استاد گروه عمران، دانشگاه پلی‌تکنیک میلان

4 دانشیار گروه مهندسی آب ، دانشگاه شهرکرد.

چکیده

کاهش بارش­ها و حتی حدی شدن آن­ها می­تواند تاثیرات زیادی در کاهش سطح آب زیرزمینی داشته باشد که در پی آن آسیب­های جدی به سفره­ها و ساختمان آن­ها وارد می­شود. در این مطالعه ضمن بررسی روش­ها و الگوریتم­های فراابتکاری مختلف برآورد و تخمین توابع مفصل به تحلیل دو بعدی سیگنال­های کمبود بارش و سطح آب زیرزمینی در محدوده زیرحوضه ایستگاه هیدرومتری تپیک در حوضه آبریز نازلوجای در دوره آماری 95-1382 پرداخته شد. نتایج مقایسه الگوریتم­های مختلف و روش معمول تخمین پارامترهای توابع مفصل نشان داد که بر اساس معیار جذر میانگین مربعات خطا، روش معمول IFM نسبت به الگوریتم­های فراابتکاری از دقت بالاتری در برآورد ضریب مفصل­های مورد استفاده برخوردار می­باشد. هم­چنین نتایج نشان داد که از بین الگوریتم­های ژنتیک، بهینه­یاب ملخ، چندجهانی، ازدحام ذرات و بهینه­یاب نهنگ، الگوریتم ژنتیک دقت به نسبت بالاتری را ارایه نموده و دقت تمامی این الگوریتم­ها یکسان و در حدود 2/0 بود. با نسبت برتری 131 درصد روش IFM نسبت به الگوریتم­های مورد بررسی نتایج نشان داد که مفصل گامبل-هوگارد دقت قابل قبولی برای تحلیل دو بعدی سیگنال­های کمبود در منطقه دارد. نتایج تحلیل دو بعدی سیگنال­های مورد بررسی نشان داد که با افزایش سیگنال کاهش بارش، احتمال افزایش سیگنال افت سطح آب زیرزمینی نیز به شدت افزایش می­یابد. با بررسی دوره بازگشت شرطی سیگنال کمبود سطح آب زیرزمینی و با در نظر گرفتن سیگنال کمبود بارش در مدت دوام پیوسته سی روزه می­توان با احتمال 90 درصد، شاهد حداقل افت سطح آب زیرزمینی برابر با 6/0 متر در سال بود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Determination of Optimum Two-Dimensional Copula Functions in Analyzing Groundwater Changes Using Meta Heuristic Algorithms

نویسندگان [English]

  • Mohammad Nazeri Tahrudi 1
  • Yousef Ramezani 2
  • Carlo De Michele 3
  • Rasoul Mirabbasi 4
1 1- Ph.D Student of Water Resources Management, University of Birjand, Iran.
2 Associate Professor, Department of Water Engineering, University of Birjand, Iran.
3 3- Professor, Department of Civil and Environmental Engineering, Politecnico di Milano, Italy.
4 4- Associate Professor, Department of Water Engineering, Shahrekord University, Iran.
چکیده [English]

One of the important factors in recharging the groundwater aquifers in each region is rainfall. Reducing rainfall, and even extreme values of it, can have a huge impact on reducing groundwater levels, which can cause serious damage to aquifers and their construction. Hydrological frequency analysis methods mainly consist of two steps, including selection of an appropriate sample distribution and estimation of selected distribution parameters. Using distribution functions for univariate hydrological analysis has been discussed by many researchers. Different probability distribution models have been used in hydrological studies including the two-parameter distribution such as those by Gumbel, Weibull, Gamma, and Lognormal in several studies (Du et al., 2005; Giraldo Osorio & García Galiano, 2012; Jiang et al., 2015; Villarini, 2009), the distribution of three parameters, such as GEV in other studies (Cannon, 2010; El Adlouni et al., 2007), and the Pearson-type III distribution in the studies by  Chen et al., (2010 , 2015). Therefore, due to the importance of drought and its effects on groundwater level, there are two objectives in this paper. The first is to investigate the artificial intelligence methods and meta-heuristic algorithms to determine the parameters of the copula functions, and the second is the bivariate analysis of precipitation and groundwater shortage signatures in the Nazloochai sub-basin located in the west of Lake Urmia.

کلیدواژه‌ها [English]

  • Copula
  • Joint Analysis
  • Lake Urmia
  • Rainfall Deficiency
  • Water Resources signatures
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