ارزیابی و بهکارگیری روشهای کریجینگ و شبکه عصبی مصنوعی در پیشبینی تراز آب زیرزمینی (مطالعه موردی: دشت رودان)
محورهای موضوعی : علوم آب
وحید سهرابی
1
,
محمدابراهیم عفیفی
2
,
کامران واحدی
3
,
احسان مرادی
4
1 - دکترای جغرافیا و برنامهریزی شهری، واحد لارستان، دانشگاه آزاد اسلامی، لارستان، ایران
2 - دانشیار گروه جغرافیا، واحد لارستان، دانشگاه آزاد اسلامی، لارستان، ایران
3 - مربی گروه عمران، واحد میناب، دانشگاه آزاد اسلامی، میناب، ایران
4 - دانشجوی دکترای جغرافیا و برنامهریزی شهری، واحد لارستان، دانشگاه آزاد اسلامی، لارستان، ایران؛
کلید واژه: آب زیرزمینی, مدلهای کریجینگ, شبکههای عصبی, رودان,
چکیده مقاله :
با افزایش جمعیت و افزایش نیاز انسان به آب طی هفتاد سال گذشته مصرف آب 6 برابر شده است. . امروزه كمبود آب و هجوم به سـفرههـاي آب زيرزمينـي، زنـدگي بشـر را بـا تهديد روبرو ساخته و نياز فزاينده به آب، از بين رفتن منابع طبيعي و توسعه بيابانها، بشر را به سوي بحران جهاني آب سوق مي دهـد. وقوع خشكسالیهای متوالی در دهه اخیر لزوم برنامه ریزي صحیح و همه جانبه جهت مقابله با مسئله کم آبی را افزایش داده است. هدف اصلی پژوهش مدلسازی مکانی - زمانی تراز آب زیرزمینی دشت رودان طی سالهای 1385 الی 1401 است با تهیه نقشه تراز آب زیرزمینی در سالهای مورد نظر و بررسی قرار دادن آنها به شناسایی و تحلیل الگوی مکانی و زمانی تراز آب زیر زمینی دشت رودان و تحلیل حساسیت و ارزیابی قابلیت اعتماد نتایج روشهای پیشنهادی دست پیدا میکنیم.روش کار از نوع کاربردی و رویکرد حاکم بر آن توصیفی-تحلیلی می باشد که در این پژوهش از اطلاعات چاههای مشاهدهای مربوط به سالهای 1385 تا 1401 به عنوان نمونه معلوم استفاده گردید و با استفاده از تکنیک های زمین آمار و شبکه عصبی مدل های درون یابی اجرا و تغییرات به صورت زمانی و مکانی در سطح دشت رودان مورد کنکاش قرار گرفت. نتایج این تحقیق نشان می دهد روش کریجینگ بهتر از روش RBF توانسته است تا تراز آب زیر زمینی بین سالهای 1385 تا 1401 را مدل سازی کند. باید این نکته را در نظر داشت که در این منطقه مدل کریجینگ بهتر بوده است.
With population growth and the increasing human demand for water, water consumption has multiplied sixfold over the past seventy years. Today, water scarcity and the overexploitation of groundwater resources have posed serious threats to human life. The growing demand for water, the destruction of natural resources, and the expansion of deserts are driving humanity toward a global water crisis. The occurrence of consecutive droughts in recent decades has further highlighted the need for comprehensive and strategic planning to address water scarcity.
The main objective of this study is the spatio-temporal modeling of groundwater levels in the Rudan Plain from 2006 to 2022. By preparing groundwater level maps for the mentioned years and examining them, the spatial and temporal patterns of groundwater level changes in the Rudan Plain are identified and analyzed. Furthermore, the study evaluates the sensitivity and reliability of the proposed methods.
This is an applied study with a descriptive-analytical approach. Observation well data from 2006 to 2022 were used as known samples. Using geostatistical techniques and artificial neural networks, interpolation models were implemented and groundwater level changes were examined both spatially and temporally across the Rudan Plain.
The results of this research indicate that the kriging method outperformed the RBF (Radial Basis Function) method in modeling groundwater levels from 2006 to 2022. It should be noted that in this particular region, the kriging model proved to be more effective
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