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توسعۀ شاخص کیفی برای ارزیابی آب زیرزمینی و پیش بینی تغییرات آن با مدل شبکۀ بیزین (مطالعۀ موردی: دشت زنجان) | ||
| اکوهیدرولوژی | ||
| مقاله 20، دوره 7، شماره 1، فروردین 1399، صفحه 263-275 اصل مقاله (1.12 M) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ije.2020.295810.1268 | ||
| نویسندگان | ||
| سعید مظفری1؛ محمد ابراهیم بنی حبیب* 2؛ سامان جوادی3؛ حمید کاردان مقدم4 | ||
| 1دانشجوی کارشناسی ارشد مهندسی منابع آب، گروه مهندسی آبیاری و زهکشی، پردیس ابوریحان، دانشگاه تهران | ||
| 2استاد گروه مهندسی آبیاری و زهکشی، پردیس ابوریحان، دانشگاه تهران | ||
| 3دانشیار گروه مهندسی آبیاری و زهکشی، پردیس ابوریحان، دانشگاه تهران | ||
| 4کارشناس پژوهشی پژوهشکدۀ مطالعات و تحقیقات منابع آب، مؤسسۀ تحقیقات آب، تهران | ||
| چکیده | ||
| آب‌های زیرزمینی یکی از منابع مهم تأمین آب به‌خصوص در مناطق خشک و کم‌بارش به شمار میرود. از این‌رو، تعیین کیفیت و پیشبینی آن امری ضروری است. مطالعۀ حاضر به ارزیابی کیفیت منابع آب زیرزمینی و پیشبینی آن در آبخوان زنجان میپردازد. شاخص GWQI در پژوهش‌های پیشین، وزن‌دهی ساده بر پایۀ دیدگاه‌های کارشناسی بوده است. از این‌رو، در شاخص جدید (C-GWQI) برای تعیین وزنها، از روش آنتروپی شانون و از تصمیمگیری چندمعیارۀ COPRAS، به منظور توسعۀ این شاخص استفاده شد. با تعریف دو محدودۀ کیفی مجاز و مطلوب برای مصارف شرب طبق استاندارد WHO، کیفیت آبخوان در سه محدودۀ مطلوب، مجاز و غیرمجاز برای طبقهبندی آب شرب استفاده شد. نتایج نشان داد در همۀ دورههای زمانی سطح کیفیت آب زیرزمینی در محدودۀ شهری پایینتر از سایر نقاط است. با این حال، در بیشتر چاههای بررسی‌شده، کیفیت آب برای شرب ارزیابی مطلوب شد. شاخص توسعه داده‌شده با استفاده از مدل شبکۀ بیزین تحت ۸ راهبرد ساختاری ارزیابی و پیشبینی شد و از بین راهبردهای مختلف، با توجه به معیارهای میانگین مطلق خطای نسبی (MARE) و ضریب همبستگی (R) راهبرد برتر انتخاب شد. راهبرد برتر کیفیت آب زیرزمینی در مرحلۀ آموزش و آزمون به‌ترتیب دارای مقادیر ۹۳۲/۱ و ۹۹۲/۰ درصد از نظر شاخص MARE ارزیابی شد. پارامترهای پیشبینیکنندۀ راهبرد منتخب شامل آب برگشتی، تخلیه، بارش، دما و کیفیت این ماه توانستند با دقت زیادی کیفیت ماه بعد را پیشبینی کنند. نتایج مطالعۀ حاضر میتواند به مدیران برای حفظ و مدیریت بهتر آبخوان کمک کند. | ||
| کلیدواژه‌ها | ||
| آبخوان زنجان؛ شبکۀ بیزین؛ کیفیت آب زیرزمینی؛ COPRAS | ||
| عنوان مقاله [English] | ||
| Development Bayesian Model for Forecasting Groundwater Quality Index (Case Study: Zanjan Plain) | ||
| نویسندگان [English] | ||
| Saeed Mozaffari1؛ Mohammad Ebrahim Banihabib2؛ Saman Javadi3؛ Hamid Kardan Moghaddam4 | ||
| 1MSc Student, Department of Irrigation and Drainage Engineering, Aburaihan Campus, University of Tehran, Iran | ||
| 2Professor, Department of Irrigation and Drainage Engineering, Aburaihan Campus, University of Tehran, Iran | ||
| 3Associate Professor, Department of Irrigation and Drainage Engineering, Aburaihan Campus, University of Tehran, Iran | ||
| 4Department of Water Resources Research, Water Research Institute, Tehran, Iran | ||
| چکیده [English] | ||
| Determining and forecasting groundwater quality can be a primary step for managing aquifer sustainability. This study investigates and forecasts groundwater quality in Zanjan Aquifer. In the previous studies, the GWQI index is a simple weighting based on expert opinions. Thus, in the developing a new index (C-GWQI), for weighting, the Shannon entropy method and the COPRAS multi-criteria decision-making technique were used. In this research, COPRAS Multi Criteria Decision Making Technique was utilized to develop the new index (C-GWQI). By defining two permissible and desirable points of drinking water according to the WHO standard, aquifer quality was classified into three ranges including, desirable, permissible and non-permissible for drinking water. The results showed that in all periods of time, groundwater quality is lower in urban areas than in other areas. However, in most of the wells surveyed, the water quality was evaluated in desirable range for drinking. The developed index was forecasted using the Bayesian network model under eight structural strategies and the best-case strategy was selected according to mean absolute relative error (MARE) and correlation coefficient (R). The best strategy was forecasted next month's groundwater quality with MARE of training and test respectively of 1.932% and 0.992%. This strategy was able to forecast the following month with good accuracy with predictor parameters such as return water, discharge, precipitation, temperature, and quality of this month. The results of this study can assist managers to better conserve and manage the aquifer. | ||
| کلیدواژه‌ها [English] | ||
| Bayesian network, COPRAS, groundwater quality, Zanjan Aquifer | ||
| مراجع | ||
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