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تعیین مناطق آسیب‌پذیر آبخوان دشت عجب‌شیر با استفاده از بهینه‌سازی روش دراستیک با الگوریتم ژنتیک و منطق فازی | ||
| اکوهیدرولوژی | ||
| مقاله 6، دوره 8، شماره 2، تیر 1400، صفحه 381-395 اصل مقاله (1.59 M) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ije.2021.314208.1425 | ||
| نویسندگان | ||
| ثریا نوری سنگراب1؛ اصغر اصغری مقدم* 2؛ علی کدخدایی3؛ فاطمه کدخدایی4 | ||
| 1دانشجوی کارشناسی ارشد هیدروژئولوژی، دانشکدۀ علوم طبیعی، دانشگاه تبریز | ||
| 2استاد گروه علوم زمین، دانشکدۀ علوم طبیعی، دانشگاه تبریز | ||
| 3دانشیار گروه علوم زمین، دانشکدۀ علوم طبیعی، دانشگاه تبریز، ایران | ||
| 4دانشجوی دکتری هیدروژئولوژی، گروه علوم زمین، دانشکدۀ علوم طبیعی، دانشگاه تبریز | ||
| چکیده | ||
| در دهههای اخیر، رشد روز‌افزون جمعیت و توسعۀ تکنولوژی و به تبع آن، فعالیتهای شدید کشاورزی و صنعتی منابع آب زیرزمینی را در معرض انواع آلایندههای ناشی از آنها قرار داده است. دشت عجب‌شیر واقع در جنوب غربی استان آذربایجان شرقی و جنوب شرقی دریاچۀ ارومیه، یکی از مناطقی است که با آلودگی آب زیرزمینی مواجه شده است و نیاز مبرم به بررسیهای کیفی دارد. به همین منظور، در تحقیق حاضر، ابتدا از روش دراستیک معمولی برای بررسی پتانسیل آلودگی دشت عجب‌شیر به نیترات استفاده شد. سپس، با استفاده از روشهای الگوریتم ژنتیک و منطق فازی (ساجنو) فرایند بهینه‌سازی صورت گرفت. مقدار شاخص در روش دراستیک معمولی از 87 تا 145، همچنین مقادیر شاخص دراستیک با در نظر گرفتن وزنهای الگوریتم ژنتیک و بهینه‌سازی با منطق فازی به‌ترتیب 47 تا 74 و 01/0 تا 6/0به دست آمد که مطابق تقسیم‌بندی آلر دراستیک معمولی در محدودههای کم، کم تا متوسط و متوسط تا زیاد، قرار گرفته است که در آن منطقهای از شمال دشت و شمال شهر عجب‌شیر دارای شاخص آسیبپذیری متوسط تا زیاد بودند. همچنین، دراستیک بهینه‌شده با الگوریتم ژنتیک و منطق فازی به علت کمتر بودن مقادیر شاخص از 79 در محدودۀ بدون خطر از نظر پتانسیل آلودگی قرار دارند. ضریب همبستگی دراستیک معمولی، روش الگوریتم ژنتیک و روش منطق فازی با غلظت نیترات به‌ترتیب 273/0، 57/0 و 796/0 حاصل شد. بنابراین، نتایج برتری روش منطق فازی نسبت به سایر روشها را نشان میدهد. | ||
| کلیدواژه‌ها | ||
| آبخوان دشت عجب شیر؛ آسیب پذیری آب زیرزمینی؛ الگوریتم ژنتیک؛ دراستیک؛ منطق فازی | ||
| عنوان مقاله [English] | ||
| Determining Vulnerable Areas of Ajabshir Plain Aquifer Using Drastic Method Optimization by Genetic Algorithm and Fuzzy Logic | ||
| نویسندگان [English] | ||
| Sorayya Nouri Sangarab1؛ Asghar Asghari Moghaddam2؛ Ali Kadkhodaie Ilkhchi3؛ Fatemeh Kadkhodaie4 | ||
| 1Department of Earth Sciences, Faculty of Natural Sciences, University of Tabriz, Tabriz, Iran | ||
| 3Department of Earth Sciences, Faculty of Natural Sciences, University of Tabriz, Tabriz, Iran | ||
| 4Department of Earth Sciences, Faculty of Natural Sciences, University of Tabriz, Tabriz, Iran | ||
| چکیده [English] | ||
| In recent decades, increasing of population and development of technology and, consequently, intense agricultural and industrial activities have exposed groundwater resources to a variety of pollutants. Ajabshir plain, located in the southwest of East Azarbaijan province and southeast of Urmia Lake, is one of the areas that has faced groundwater contamination and needs more qualitative studies. In this study, first, the conventional drastic method was used to investigate the potential of nitrate contamination in Ajabshir plain, and then the optimization process was performed using the methods of genetic algorithm and fuzzy logic (Sugeno). The index values in the conventional drastic method were obtained from 87 to 145, as well as the drastic index values obtained by considering the weights of the genetic algorithm and optimization with fuzzy logic, from 47 to 74 and 0.01 to 0.6, respectively. According to the allergy classification the ordinary drastic is located in low, low to medium, and medium to high ranges, in which areas from the north of the plain and the north of Ajabshir city had moderate to high vulnerability index. Also, the optimized variables with genetic algorithm and fuzzy logic are in the safe zone in terms of contamination potential due to lower index values than 79. The normal drastic correlation coefficient, genetic algorithm, and fuzzy logic method with nitrate concentration were 0.2,73, 0.57, and 0.796, respectively. Therefore, the results show the superiority of the fuzzy logic method over other methods. | ||
| کلیدواژه‌ها [English] | ||
| Ajabshir Plain Aquifer, groundwater vulnerability, DRASTIC, genetic algorithm, Fuzzy logic | ||
| مراجع | ||
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