پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 161 |
| تعداد شماره‌ها | 6,532 |
| تعداد مقالات | 70,500 |
| تعداد مشاهده مقاله | 124,087,398 |
| تعداد دریافت فایل اصل مقاله | 97,190,488 |
تحلیل مکانی متغیرهای کیفیت آب زیرزمینی مبتنی بر زمین‌آمار، آنالیز آماری و معادلات ساختاری | ||
| اکوهیدرولوژی | ||
| مقاله 26، دوره 5، شماره 4، دی 1397، صفحه 1385-1399 اصل مقاله (1.43 M) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ije.2018.271739.1006 | ||
| نویسندگان | ||
| مسلم برجی حسن گاویار1؛ مهناز ابوالقاسمی2؛ سیده مهسا موسوی رینه2؛ فاطمه روزبهانی3؛ حسین یوسفی* 4 | ||
| 1دانشجوی دکتری آبخیزداری، دانشکدۀ منابع طبیعی، دانشگاه تهران | ||
| 2دانشجوی کارشناسی ارشد اکوهیدرولوژی، دانشکدۀ علوم و فنون نوین، دانشگاه تهران | ||
| 3کارشناس مهندسی بهداشت محیط، دانشگاه آزاد اسلامی، واحد علوم پزشکی تهران | ||
| 4دانشیار، دانشکدۀ علوم و فنون نوین، دانشگاه تهران | ||
| چکیده | ||
| امروزه، پایش کمی و کیفی منابع آب شیرین در مناطق خشک و نیمه‌خشک از ضروریات هر سیستم مدیریتی، پایش و نظارتی است. وجود متغیرهای کیفی فراوان در استانداردهای بین‌المللی سبب شده است که مدیران برحسب شرایط اقتصادی و زمانی فقط به اندازه‌گیری چند متغیر کیفی بپردازند، پس انتخاب این تعداد متغیر برای بررسی استاندارد کیفیت آب اهمیت زیادی دارد. هدف از تحقیق حاضر، تعیین متغیرهای منحصربه‌فرد و تأثیرگذار بر آلودگی دشت قلعه‌قاضی استان هرمزگان با استفاده از روشهای آماری و زمین‌آمار است. نتایج تحلیل خوشه نشان داد چاه‌های بررسی‌شده در دو خوشه قرار میگیرند که از نظر موقعیت مکانی قابل تفکیک‌اند. نتایج PCA/FA نشان داد 77/72 درصد از واریانس دادهها در دو فاکتور توجیه میشوند. همچنین، تحلیل مکانی با استفاده از زمین‌آمار نشان داد میزان تعامل آب و سنگ در عامل نخست بیان‌کنندۀ کارکرد مؤثر سازندهای تبخیری بر آلودگی دشت است. نتایج ANOVA نیز وجود اختلاف معنادار در غلظت عناصر فاکتور اول و دوم تحلیل عاملی را تأیید کرد. بر این اساس، متغیرهای EC، Cl، SO42، Mg و Na برای بررسی توسط SEM انتخاب شد. نتایج این روش یافتههای روشهای آماری را تأیید کرد. | ||
| کلیدواژه‌ها | ||
| تحلیل عاملی؛ خوشه‌بندی؛ زمین‌آمار؛ کیفیت آب زیرزمینی؛ معادلات ساختاری؛ ANOVA یک‌طرفه | ||
| عنوان مقاله [English] | ||
| Spatial Analysis of Important Variables of Groundwater Quality Based on Geostatistical, Statistical Analysis and Structural Equation Modeling | ||
| نویسندگان [English] | ||
| Moslem Borji Hassangavyar1؛ Mahnaz Abolghasemi2؛ Seyedeh Mahsa Mousavi Reineh2؛ Fateme Rouzbahani3؛ Hossein Yousefi4 | ||
| 1PhD Candidate, Department of Arid And Mountainous Reclamation Regions, Faculty of Natural Resources, University of Tehran, Karaj, Iran | ||
| 2MSc Student, Echohydrology, Faculty of New Science and Technologies, University of Tehran, Iran | ||
| 3MSc in Environmental Health, Islamic Azad University, Tehran Medical Science Branch, Iran | ||
| 4Associate Professor, Faculty of New Science and Technologies, University of Tehran, Iran | ||
| چکیده [English] | ||
| Today, the quantitative and qualitative monitoring of fresh water resources in arid and semi-arid areas is one of the requirements of every management, monitoring, and monitoring system. However, the existence of many qualitative variables in international standards has led managers to consider only quantitative variables in terms of economic and temporal conditions. So, selecting this variable is important for assessment the water quality standard. Therefore, the purpose of this study was to determine the variables that are unique and affect the pollution of Qaleh Ghazi Plain of Hormozgan by statistical methods (Principle Components Analysis, Cluster Analysis, Piper diagrams, one way ANOVA, Structural Equation Modeling (SEM)) and Geostatistical. The results of cluster analysis showed that the wells are located in two clusters that can be distinguished by location. The results of PCA / FA showed that 72.77% of the data variance was justified in two factors, and the spatial analysis using Geostatistical showed that the interaction of water-rock in factor score 1 is an evidence of the effective role of evaporative formations on plain contamination. ANOVA results also showed a significant difference between the concentrations of factor score 1 and factor score 2 in factor analysis. Accordingly, the variables EC, Cl, SO42, Mg and Na were selected for review by SEM. The results of this method confirmed the findings of statistical methods. | ||
| کلیدواژه‌ها [English] | ||
| Groundwater quality, Cluster Analysis, factor analyses, One-way ANOVA, Geostatistical, Structural Equation Modeling | ||
| مراجع | ||
|
[1]. H. P. Moghadas, “A STUDY OF GROUND WATER QUALITY IN LENJAN TOWNSHIP OF ISFAHAN PROVINCE,” sjsph YR - 2003, no. 4. p. 31–40 K1–Lenjcm township water K1–Quality G. (In Persian) [2]. T. S. Narany, M. F. Ramli, A. Z. Aris, W. N. A. Sulaiman, and K. Fakharian, “Spatiotemporal variation of groundwater quality using integrated multivariate statistical and geostatistical approaches in Amol--Babol Plain, Iran,” Environ. Monit. Assess., vol. 186, no. 9, pp. 5797–5815, 2014. (In Persian) [3]. N. M. Fakhari M, Asghari Moghadam A, Barzegar R, Kazemian N, “nvestigation of the Origin of Some Heavy Metals in Groundwater of Marand Plain Aquifer Using Multivariate Statistical Methods,”. J. Water Soil, vol. 26, no. 2, pp. 237–253, Aug. 2016. (In Persian) [4]. L. Belkhiri and T. S. Narany, “Using multivariate statistical analysis, geostatistical techniques and structural equation modeling to identify spatial variability of groundwater quality,” Water Resour. Manag., vol. 29, no. 6, pp. 2073–2089, 2015. [5]. A. Facchinelli, E. Sacchi, and L. Mallen, “Multivariate statistical and GIS-based approach to identify heavy metal sources in soils,” Environ. Pollut., vol. 114, no. 3, pp. 313–324, 2001. [6]. A. Menció and J. Mas-Pla, “Assessment by multivariate analysis of groundwater–surface water interactions in urbanized Mediterranean streams,” J. Hydrol., vol. 352, no. 3–4, pp. 355–366, 2008. [7]. K. Dragon, “Application of factor analysis to study contamination of a semi-confined aquifer (Wielkopolska Buried Valley aquifer, Poland),” J. Hydrol., vol. 331, no. 1–2, pp. 272–279, 2006. [8]. A. Z. Aris, M. H. Abdullah, A. Ahmed, and K. K. Woong, “Controlling factors of groundwater hydrochemistry in a small island’s aquifer,” Int. J. Environ. Sci. Technol., vol. 4, no. 4, pp. 441–450, 2007. (In Persian) [9]. M. Kumar, A. L. Ramanathan, M. S. Rao, and B. Kumar, “Identification and evaluation of hydrogeochemical processes in the groundwater environment of Delhi, India,” Environ. Geol., vol. 50, no. 7, pp. 1025–1039, 2006. [10]. B. Tlili-Zrelli, M. Gueddari, and R. Bouhlila, “Geochemistry and quality assessment of groundwater using graphical and multivariate statistical methods. A case study: Grombalia phreatic aquifer (Northeastern Tunisia),” Arab. J. Geosci., vol. 6, no. 9, pp. 3545–3561, 2013. [11]. I. Gundogdu and O. Esen, “The importance of secondary variables for mapping of meteorological data. 3rdinternational conference on cartography and GIS,” Nessebar, Bulg., 2010. [12]. P. P. Adhikary, H. Chandrasekharan, D. Chakraborty, and K. Kamble, “Assessment of groundwater pollution in West Delhi, India using geostatistical approach,” Environ. Monit. Assess., vol. 167, no. 1–4, pp. 599–615, 2010. [13]. D. Machiwal, A. Mishra, M. K. Jha, A. Sharma, and S. S. Sisodia, “Modeling short-term spatial and temporal variability of groundwater level using geostatistics and GIS,” Nat. Resour. Res., vol. 21, no. 1, pp. 117–136, 2012. [14]. B. Bayard and C. Jolly, “Environmental behavior structure and socio-economic conditions of hillside farmers: a multiple-group structural equation modeling approach,” Ecol. Econ., vol. 62, no. 3–4, pp. 433–440, 2007. [15]. M. A. Kenney, G. B. Arhonditsis, L. C. Reiter, M. Barkley, and K. H. Reckhow, “Using structural equation modeling and expert elicitation to select nutrient criteria variables for south-central Florida lakes,” Lake Reserv. Manag., vol. 25, no. 2, pp. 119–130, 2009. [16]. B. Zarrabi, M. E. F. Valipour, and M. Javanbakht, “Investigation of Geologic factors affecting runoff quality of Qaleh Ghazi Plain,” Second Int. Congr. Appl. Geol., vol. IAGC02_229, no. Department of Geology, Islamic Azad University, Mashhad, 2015. (In Persian) [17]. S. M. Yidana, D. Ophori, and B. Banoeng-Yakubo, “A multivariate statistical analysis of surface water chemistry data The Ankobra Basin, Ghana,” J. Environ. Manage., vol. 86, no. 1, pp. 80–87, 2008. [18]. E. J. Usunoff and A. Guzmán-Guzmán, “Multivariate analysis in hydrochemistry: an example of the use of factor and correspondence analyses,” Groundwater, vol. 27, no. 1, pp. 27–34, 1989. [19]. A. Mustapha and A. Z. Aris, “Multivariate Statistical Analysis and Environmental Modeling of Heavy Metals Pollution by Industries.,” Polish J. Environ. Stud., vol. 21, no. 5, 2012. [20]. K. Schaefer and J. W. Einax, “Analytical and chemometric characterization of the Cruces River in South Chile,” Environ. Sci. Pollut. Res., vol. 17, no. 1, pp. 115–123, 2010. [21]. P. A. Rogerson, Statistical methods for geography: a students guide. Sage, 2014. [22]. J. B. Grace, Structural equation modeling and natural systems. Cambridge University Press, 2006. [23]. R. B. Kline, “Principles and Practice of Structural Equation Modeling The Guilford Press New York Google Scholar,” 1998. [24]. M. share pour, “Structural equation modeling (SEM):: Meet applications LISREL program (LISREL) in Social Research,” Soc. Sci., vol. 8, no. 13.14, pp. 204–231, 2001. (In Persian) [25]. R. E. Rossi, D. J. Mulla, A. G. Journel, and E. H. Franz, “Geostatistical tools for modeling and interpreting ecological spatial dependence,” Ecol. Monogr., vol. 62, no. 2, pp. 277–314, 1992. [26]. H. Assaf and M. Saadeh, “Geostatistical assessment of groundwater nitrate contamination with reflection on DRASTIC vulnerability assessment: the case of the Upper Litani Basin, Lebanon,” Water Resour. Manag., vol. 23, no. 4, pp. 775–796, 2009. [27]. R. M. Lark, “Estimating variograms of soil properties by the method-of-moments and maximum likelihood,” Eur. J. Soil Sci., vol. 51, no. 4, pp. 717–728, 2000. [28]. H. Hosseini Poor, J. Ghaioomeyan, A. R. Ghasemi, and S. Choopani, “Investigating salt sources in Sarchahan aquifer in Hormozghan province using ion ratios,” Watershed Eng. Manag., vol. 1, no. 4, pp. 212–226, 2010. (In Persian) [29]. J. Shi et al., “Spatial distribution of heavy metals in soils: a case study of Changxing, China,” Environ. Geol., vol. 52, no. 1, pp. 1–10, 2007. [30]. H. W. Marsh, K.-T. Hau, and Z. Wen, “In search of golden rules: Comment on hypothesis-testing approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler’s (1999) findings,” Struct. Equ. Model., vol. 11, no. 3, pp. 320–341, 2004. [31]. A. E. Sutton-Grier, M. A. Kenney, and C. J. Richardson, “Examining the relationship between ecosystem structure and function using structural equation modelling: A case study examining denitrification potential in restored wetland soils,” Ecol. Modell., vol. 221, no. 5, pp. 761–768, 2010. [32]. L. Hu and P. M. Bentler, “Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives,” Struct. Equ. Model. a Multidiscip. J., vol. 6, no. 1, pp. 1–55, 1999. [33]. R. H. Hoyle, Handbook of structural equation modeling. Guilford press, 2012. [34]. D. Hooper, J. Coughlan, and M. Mullen, “Structural equation modelling: Guidelines for determining model fit,” Articles, p. 2, 2008. [35]. J. S. Hanor and J. E. Bailey, “Use of hydraulic head and hydraulic gradient to characterize geopressured sediments and the direction of fluid migration in the Louisiana Gulf Coast,” 1983. | ||
|
آمار تعداد مشاهده مقاله: 862 تعداد دریافت فایل اصل مقاله: 489 |
||