ارزیابی کیفیت منابع آب زیرزمینی با استفاده از آنالیزهای چند متغیره (مطالعه موردی: دشت بهبهان)
محورهای موضوعی : برگرفته از پایان نامهبهزاد عادلی 1 , احسان کمالی مسکونی 2 , محسن آرمین 3
1 - دانشجوی دکتری آبخیزداری، دانشکده کشاورزی و منابع طبیعی، دانشگاه هرمزگان
2 - عضو باشگاه پژوهشگران جوان و نخبگان. دانشگاه آزاد، واحد جیرفت، ایران
3 - استادیار دانشکده کشاورزی و منابع طبیعی، دانشگاه یاسوج
کلید واژه: کیفیت آب, مؤلفه های اصلی, دشت بهبهان, آزمون KMO, روش PCA,
چکیده مقاله :
منابع آب زیرزمینی نقش مهمی در توسعه و پایداری یک سرزمین ایفا میکنند. بنابراین در مناطقی که دسترسی به منابع آب سطحی، محدود و بارش‌ها کم و نامنظم می‌باشد، مدیریت کمی و کیفی منابع آب زیرزمینی جزء لاینفک اصول توسعه‌ی پایدار می‌باشد. در این بین یکی از ارکان اصلی مدیریت منابع آبی، ارزیابی خصوصیات کیفی این منابع می‌باشد. در این تحقیق از روش آنالیز مؤلفه‌های اصلی (PCA) جهت تحلیل کیفیت آب زیرزمین دشت بهبهان. استفاده شده است. بدین منظور ۱۲ متغیر کیفی برای تجزیه و تحلیل خصوصیات کیفیت آب دشت بهبهان انتخاب شد. آزمون KMO و بارتلت نشان داد که امکان استفاده از روش PCA برای تجزیه و تحلیل خصوصیات کیفی آب زیرزمینی دشت با استفاده از پایگاه داده ساخته شده براساس متغیرهای انتخاب شده وجود دارد. بنابراین با استفاده از PCA دو محور (مؤلفه) اصلی که ۳۰۷/۸۵ درصد از واریانس کل داده‌های مشاهداتی را پوشش می‌داد، استخراج گردید. مؤلفه اول ۶۸/۷۶ درصد واریانس داده‌ها را در بر گرفته و عمدتا تحت تاثیر 10 متغیر (TH، SAR، K، Na، Mg، Ca، Cl، SO4، TDS و EC ) و محور دوم با توضیح ۶۲۲/۸ درصد واریانس کل، دارای همبستگی مثبت بالا با HCO3 و همبستگی منفی با pH می‌باشد. در این تحقیق همچنین الگوی تغییرات مکانی هر متغیر و ارتباط آن با کاربری اراضی مورد بررسی قرار گرفت.
Groundwater resources play a vital role in the development and sustainability of a territory. Therefore, in areas with low and irregular precipitation and limited access to surface water resources, the management of groundwater resources, in terms of quantity and quality, is the inseparable part of sustainable development. In the present study, principal components analysis (PCA) was used to assess the quality of groundwater resources of Behbahan Plain, Khuzestan province, Iran. In order to perform a groundwater quality analysis, 12 hydro-chemical variables were selected in order. Results of the KMO index and the Bartlett's test illustrate that this is reasonable to use the PCA on the dataset, which is constructed based on the selected variables, for characterization and analysis of groundwater quality in the study area. According to outcomes of the PCA, the first two axes (PC1 and PC2) captured 85.31% of the total variance in the dataset. The first PCA axis (PC1) explained 76.68% of the variation in the hydro-chemical data that was mainly affected by 10 variables (TH, SAR, K, Na, Mg, Ca, Cl, SO, TDS and EC). The second component (PC2) contributes 8.622% of the total variance in the dataset that indicated strong positive correlation with HCO3 and negative correlation with pH. Also, in this study, the relationship between spatial variation of each selected variable and land use were investigated.
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