تحلیل کیفیت آب‌های زیرزمینی دشت آمل-بابل و پهنه‌بندی سدیم با استفاده از سیستم اطلاعات جغرافیایی
محورهای موضوعی : آب و محیط زیست
1 - استادیار مهندسی محیط زیست، گروه عمران، دانشکده فنی و مهندسی، دانشگاه خوارزمی، تهران، ایران. *(مسوول مکاتبات)
2 - کارشناسی ارشد مهندسی عمران- محیط زیست، دانشکده فنی و مهندسی، دانشگاه خوارزمی، تهران، ایران.
کلید واژه: دشت آمل-بابل, استاندارد FAO, سدیم, سیستم اطلاعات جغرافیایی, پهنه‌بندی,
چکیده مقاله :
چکیده زمینه و هدف: امروزه توجه به کیفیت آب های زیرزمینی و روند تغییرات آن برای مصارف مختلف شرب و کشاورزی و سلامت عمومی بسیار حایز اهمیت است. آلودگی آب های زیرزمینی اغلب به دلیل فاضلاب های سمی ناشی از صنایع و یا از چاه‌های جذبی فاضلاب اتفاق می افتد. روش بررسی: در این پژوهش به منظور بررسی تغییرات کیفی منابع آب زیرزمینی، از داده های کیفیت شیمیایی دشت آمل-بابل در بازه زمانی 1365 تا 1388 استفاده گردید. در دشت آمل-بابل کاربری اراضی عموما کشاورزی است و برای ارزیابی کیفیت از استاندارد FAO استفاده شده است. پارامترهای مختلفی از جمله هدایت الکتریکی، Cl-, Na+, HCO3- و pH بررسی گردید و طی آن سدیم به عنوان یکی از عوامل مهم مورد توجه بیش‌تر قرار گرفت. سپس با استفاده از سیستم اطلاعات جغرافیایی وضعیت سدیم در منطقه پهنه بندی و تحلیل گردید. بحث و نتیجه‌گیری: نتایج به‌دست آمده نشان داد که وضعیت آلودگی با توجه به کاربری اراضی در اطراف مناطق صنعتی و شهرهای پرجمعیت بحرانی تر می باشد. هم‌چنین با بررسی وضعیت آب‌دهی و تشخیص سال های ترسالی و خشک‌سالی و نرمال رابطه افزایش آلودگی در سال های با دبی کم‌تر کاملا مشهود می‌باشد.
Abstract Background and Objective: Nowadays, paying attention to the quality of groundwater and its trend is very important for various purposes such as drinking, agriculture, and public health. Groundwater pollution is often formed due to toxic industrial wastewaters and disposing wells of urban wastewaters. Method: In this study, the qualitative data of Amol-Babol plain within1986-2009 was used in order to evaluate qualitative changes of groundwater resources. In the study area, the main groundwater consumption was found to be agricultural irrigation. Several parameters of electrical conductivity, Cl-, Na+, HCO3-, and pH were investigated to assess groundwater quality and Na+ was detected as the most important one. Then, Na+ was zonned in the area using geographic information system (GIS). Discussion and Conclusion: The results showed that most of the polluted areas are close to urban and industrial landuses. Also, the highest contamination of groundwater was found in dry years due to low flow conditions of the main river in the area.
Reference
1- Vathananukij, H. 1994. Water Quality Analysis on the chao-phra-ya Estuary using remote sensing data, Kasetsart University, RIO Thailand.
2- Alizadeh A, 1998, Principles of Irrigation Systems Design, Fourth Edition, Imam Reza University Press, Pages 1-100. (In persian)
3- Mohammadi. and Soltani J, 2011, Investigation of the Effect of Drought on the Process of Quantitative and Qualitative Water Resources Reduction for Agricultural Use in Jiroft Plain, Eleventh Irrigation Seminar and Evaporation Reduction, University of Kerman Shahid Bahonar, pp. 1-15. (In persian)
4- Rahmani. Gh, 2011, Groundwater quality in terms of drinking water in the Izeh-Pyong plain aquifer in Khuzestan province, estimating by GQI index, 4th Iranian Water Management Conference, Amir Kabir University of Technology. (In persian)
5- Gallichand, j., Bouckland D., Marcotte D. and Hendry, M. J., 1992. Spatial Interpolation of Soil Salinity and Sodicity for a salin soil in southern Alberta, Can. J. Soil Sci. 72:503-516.
6- Juang K.W., Lee D.Y., and Ellsworth, T.R. 2001. Using rank-order geostatistics for spatial interpolation of highly skewed data in a heavy metal contaminated site, J. Environ. Qual. 30:894-903.
7- Wu J., Norvell W.A., and Welch, R.M., 2006. Kriging on highly skewed data for DTPA-extractable soil Zn with auxiliary information for pH and organic carbon, Geoderma, 134: 187–199.
8- Babiker, I. S., Mohamed, M. A. A., and Hiyama, T. 2007. Assessing groundwater quality using GIS, Water Resources Management, 21: 699–715.
9- Ramakrishnaiah C., Sadashivalah C., and Ranganna G., 2009. Assessment of water quality index for the groundwater in Tumkur Taluk, Karnataka State, India. E-Journal of Chemistry, 6(2), pp.523-530
10- Karayusufoglu, S., Eris, E., and Coskun, H.G. 2010. Estimation of basin parameters and precipitation distribution of solalki basin, turkey. Wseas transactions on environment and development. Issue 5, 6: 385-394.
11- Kasmaei M, 2010, Climate and Architecture, Sixth Edition, Soil Publishing, pp. 83, 87, 129. (In persian)
12- WHO (World Health Organization). 2004. Guidelines for drinking-water quality, vol 1, 3rd ed, Geneva, Switzerland.
13- Habibi M and Masoumi A, 2006, Water Quality, Publications of Soil and Water Conservation Research Institute, pp. 28. (In persian)
14- Hasani Pak A. A, 1998, Geostatistics, Tehran University Press, p. 314. (In persian)
15- Laleh Zari. R, 2009, Monthly review of nitrate changes in Shahrekord plain and zoning using Geographic Information System, Iranian Journal of Water Research, Third Year, No. 4. (In persian)
16- ESRI, 2008. ArcGIS Spatial Analyst Tutorial, United States of America, ESRI Inc.
17- ESRI Inc. 2008. ArcMapTM. Version10.
18- Alizadeh A., 2002, Principles of Applied Hydrology, 21st Edition, Imam Reza University Press, Pages 276-279. (In persian)
_||_
Reference
1- Vathananukij, H. 1994. Water Quality Analysis on the chao-phra-ya Estuary using remote sensing data, Kasetsart University, RIO Thailand.
2- Alizadeh A, 1998, Principles of Irrigation Systems Design, Fourth Edition, Imam Reza University Press, Pages 1-100. (In persian)
3- Mohammadi. and Soltani J, 2011, Investigation of the Effect of Drought on the Process of Quantitative and Qualitative Water Resources Reduction for Agricultural Use in Jiroft Plain, Eleventh Irrigation Seminar and Evaporation Reduction, University of Kerman Shahid Bahonar, pp. 1-15. (In persian)
4- Rahmani. Gh, 2011, Groundwater quality in terms of drinking water in the Izeh-Pyong plain aquifer in Khuzestan province, estimating by GQI index, 4th Iranian Water Management Conference, Amir Kabir University of Technology. (In persian)
5- Gallichand, j., Bouckland D., Marcotte D. and Hendry, M. J., 1992. Spatial Interpolation of Soil Salinity and Sodicity for a salin soil in southern Alberta, Can. J. Soil Sci. 72:503-516.
6- Juang K.W., Lee D.Y., and Ellsworth, T.R. 2001. Using rank-order geostatistics for spatial interpolation of highly skewed data in a heavy metal contaminated site, J. Environ. Qual. 30:894-903.
7- Wu J., Norvell W.A., and Welch, R.M., 2006. Kriging on highly skewed data for DTPA-extractable soil Zn with auxiliary information for pH and organic carbon, Geoderma, 134: 187–199.
8- Babiker, I. S., Mohamed, M. A. A., and Hiyama, T. 2007. Assessing groundwater quality using GIS, Water Resources Management, 21: 699–715.
9- Ramakrishnaiah C., Sadashivalah C., and Ranganna G., 2009. Assessment of water quality index for the groundwater in Tumkur Taluk, Karnataka State, India. E-Journal of Chemistry, 6(2), pp.523-530
10- Karayusufoglu, S., Eris, E., and Coskun, H.G. 2010. Estimation of basin parameters and precipitation distribution of solalki basin, turkey. Wseas transactions on environment and development. Issue 5, 6: 385-394.
11- Kasmaei M, 2010, Climate and Architecture, Sixth Edition, Soil Publishing, pp. 83, 87, 129. (In persian)
12- WHO (World Health Organization). 2004. Guidelines for drinking-water quality, vol 1, 3rd ed, Geneva, Switzerland.
13- Habibi M and Masoumi A, 2006, Water Quality, Publications of Soil and Water Conservation Research Institute, pp. 28. (In persian)
14- Hasani Pak A. A, 1998, Geostatistics, Tehran University Press, p. 314. (In persian)
15- Laleh Zari. R, 2009, Monthly review of nitrate changes in Shahrekord plain and zoning using Geographic Information System, Iranian Journal of Water Research, Third Year, No. 4. (In persian)
16- ESRI, 2008. ArcGIS Spatial Analyst Tutorial, United States of America, ESRI Inc.
17- ESRI Inc. 2008. ArcMapTM. Version10.
18- Alizadeh A., 2002, Principles of Applied Hydrology, 21st Edition, Imam Reza University Press, Pages 276-279. (In persian)
