نوع مقاله : مقاله پژوهشی

نویسندگان

استادیار دانشگاه بین المللی امام خمینی (ره)

چکیده

مقالة حاضر به بررسی و مقایسه روش­های تأمین اطلاعات برای مدلسازی آب­های زیرزمینی، در دو دسته زمین­آماری و احتمالاتی پرداخته است.  برای داده‌های هدایت هیدرولیکی در سطح سفره، بعد از مقایسة روش­های زمین آماری با یکدیگر، بهترین روش بر اساس حفظ خصوصیات آماری اولیه و همچنین روش ارزیابی حذفی انتخاب و داده‌ها و برای منطقة مورد مطالعه به­صورت شبکه‌ای از سلول­ها تولید شد.  در این تحقیق با بررسی وضعیت همبستگی مکانیضعیف میان داده‌های مشاهده‌ای امکان استفاده از روش­های احتمالاتی بررسی شده است.  در این خصوص با توجه به توزیع فراوانی پارامترهای مورد مطالعه، با استفاده از روش مونت­کارلو داده‌سازی لازم تهیه شده است و سرانجام نتایج حاصل از روش زمین‌آماری منتخب با روش احتمالاتی مقایسه و توانایی روش احتمالاتی در شبیه‌سازی هدایت هیدرولیکی و ضریب ذخیرة سفره نشان شده است.  مدل آب زیرزمینی مورد استفاده در این تحقیق PMWIN 5.3 (MODFLOW) است که با استفاده از اطلاعات مورد بحث و سری زمانی وقایع اقلیمی، وضعیت آینده سفرة آب زیرزمینی در مطالعة موردی را پیش­بینی کند.  برای پردازش اطلاعات ورودی موجود، تولید داده‌های ورودی با روش­های زمین آمار و احتمالاتی و همچنین نمایش خروجی مدل، از نرم­افزار ARC/INFOGRID و توابع موجود در آن استفاده شده است. 

عنوان مقاله [English]

Comparison of Aquifer Hydraulic Conductivity Estimation Methods for Use in Simulation Models

چکیده [English]

The current study investigated and compared data generation methods for groundwater modeling. These
methods can be divided into two classes; geostatistic and probabilistic. By comparing geostatistic methods,
the best method was chosen and the hydraulic conductivity of the aquifer was generated for a study area in
a grid (9-cell) format. After observing weak spatial correlation between the data, the probabilistic method
was then considered. The Monte Carlo technique was used for data generation for the governing
distribution function using the probabilistic method. Finally, the results of the two methods were compared.
The ground water model used in this research was PMWIN 5.3 (MODFLOW). This model was used to
predict the future state of an aquifer by using the generated data and time series of precipitation. Existing
input data processing, data generation by geostatistic/stochastic methods and representation of model
output were performed using ARC/INFO GRID.

کلیدواژه‌ها [English]

  • Data Generation
  • Geostatistical Method
  • GIS
  • Groundwater Modeling
  • Probabilistic Methods
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