کمی‌سازی عدم قطعیت سهم منابع رسوب تپه‌های ماسه‌ای با استفاده از روش انگشت‌نگاری مونت‌کارلو (مطالعه موردی: تپه‌های ماسه‌ای جازموریان، جنوب استان کرمان)

نوع مقاله : علمی -پژوهشی

نویسندگان

1 دانشگاه هرمزگان، بندرعباس، ایران.

2 سازمان انرژی اتمی، تهران، ایران.

3 استاد گروه جغرافیای طبیعی، دانشگاه اکستر، اکستر، انگلستان. Professor of Physical Geography, University of Exeter, Exeter, UK.

4 دانشگاه گنبد کاووس، گنبد، ایران

10.29252/esrj.9.1.14

چکیده

امروزه استفاده از تکنیک انگشت­نگاری رسوب در تعیین سهم منابع رسوبات در حال افزایش می­باشد، بنابراین توجه به آنالیز عدم قطعیت در طی فرآیند مدل­سازی ضروری می­باشد. در این تحقیق به منظور بررسی عدم قطعیت سهم منابع رسوبات تپه­های ماسه­ای در منطقه جازموریان، استان کرمان از تکنیک انگشت­نگاری مونت­کارلو مورد استفاده قرار گرفت. بدین منظور، پس از انتخاب ترکیب بهینه از ردیاب­ها توسط یک فرآیند آماری دو مرحله­ای شامل آزمون­های کروسکال والیس و آنالیز تابع تشخیص، مدل ترکیبی Collins با 10000 بار تکرار در MATLAB اجرا گردید و محدوده­ی عدم قطعیت مربوط به سهم منابع رسوبات تپه­های ماسه­ای در سطح اطمینان 95 درصد (صدک­های 5/2 و 5/97 درصد) محاسبه گردید. بر طبق نتایج، از بین ده ردیاب اندازه­گیری شده، 4 ردیاب شامل Cr، Ni، Li و Co به­عنوان ترکیب بهینه انتخاب شدند و در نهایت به­عنوان پارامتر ورودی به فرآیند مدل­سازی در نظر گرفته شدند. عدم قطعیت کامل (%100-0) در سهم منابع به­ویژه در Qs و Qal و برای برخی نمونه­های رسوب دیگر، منبع Qt محاسبه گردید و دو منبع اول در بیشتر نمونه­های رسوب بیشترین عدم قطعیت نشان دادند و هم­چنین به علت وزش بادهای چند جهته در منطقه، منابع تامین­کننده رسوب برای نمونه­های مختلف تپه­های ماسه­ای نیز متغیر می­­باشد. با توجه به کارایی بالای این تکنیک، استفاد از این روش در مناطقی با تپه­های ماسه­ای فعال به منظور شناسایی منابع آنها، کمی کردن سهم منابع و بررسی عدم قطعیت آنها توصیه می­شود.

کلیدواژه‌ها


عنوان مقاله [English]

Determining uncertainty associate to source contributions of sand dune sediments using a Monte Carlo fingerprinting technique

نویسندگان [English]

  • Mojtaba Dolat Kordestani 1
  • Hamid Gholami 1
  • Javad Ahamdi 2
  • Desmond Walling 3
  • Abolhassan Fathabadi 4
1 Department of Natural Resources Engineering, University of Hormozgan, Bandar-Abbas, Hormozgan, Iran.
2 Professor of Nuclear Atomic Research Institute, Iran Atomic Energy Organization, Tehran, Iran.
3 Professor of Physical Geography, University of Exeter, Exeter, UK.
4 Department of Rangeland and Watershed Management Engineering, University of Gonbad, Gonbad, Iran.
چکیده [English]

Todays, sediment fingerprinting have been increasingly used to determine source contributions of sediments, but there is a need to continue refining procedure especially with respect to uncertainty analysis during modeling. In this research, we applied a Monte Carlo fingerprinting framework to exploring of uncertainty associate to source contributions of sand dune sediments in the Jazmurian region, Kerman province. In order to, after selecting optimum composite fingerprints using a two-stage statistical procedure including Kruskal-Wallis H test and discriminant function analysis, Collins mixing model was solved 10000 times in the MATLAB with 95% confidence levels (percentiles 2.5% and 97.5%). Among of 10 tracers, four tracers including Cr, Ni, Li and Co were selected as optimum composite fingerprints and then they entered as modeling procedure. Full uncertainty (0-100%) calculated for some sources especially Qs and Qal, and also for some sediment samples, Qt recognized as main source. Variability on the source for sand dune sediment samples is due to winds with multiple directions. The effectiveness of this technique to sand dune sediment fingerprinting suggests that they will be useful in other desert regions with active dune fields for recognition of their sources, quantifying source contributions and studying uncertainty of source contributions.

کلیدواژه‌ها [English]

  • Fingerprinting-Uncertainty- Monte Carlo
  • -Source Contribution
  • -Jazmurian
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