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  • بررسی خودپالایی و مدل‌سازی تغییرات نیتروژن و فسفر در طول رودخانه دز (بازه سد دز تا پل بند قیر)

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کد مقاله : JEST-1710-3948 (R1) بازدید : 147 صفحه: 301 - 315

10.22034/jest.2020.31130.3948

نوع مقاله: پژوهشی

بررسی خودپالایی و مدل‌سازی تغییرات نیتروژن و فسفر در طول رودخانه دز (بازه سد دز تا پل بند قیر)

محورهای موضوعی : آب و محیط زیست

امید بابامیری 1 , صفر معروفی 2 , آرش آذری 3

1 - کاندیدای دریافت درجه دکتری مهندسی منابع آب، گروه مهندسی آب، دانشگاه بوعلی سینا همدان.
2 - استاد مهندسی منابع آب، گروه مهندسی آب، دانشگاه بوعلی سینا همدان *(مسوول مکاتبات)
3 - استادیار مهندسی آب، گروه مهندسی آب، دانشگاه رازی کرمانشاه

تاریخ دریافت : 1396/07/23 تاریخ پذیرش : 1397/03/13 تاریخ انتشار : 1399/03/01

کلید واژه: N-NH4, P-PO4 و Qual2kw, شبیه‌سازی, کیفیت آب, N-NO3,

چکیده مقاله :

زمینه و هدف: برای تعیین عکس العمل قابل انتظار رودخانه بر اثر ورود آلاینده، استفاده از مدل های ریاضی ضروری است. این مدل ها قادرند آثار بارگذاری های موجود و آینده را شبیه سازی نموده و مدیران و مسئولان را در تصمیم گیری های خود یاری نمایند. هدف از مطالعه حاضر شبیه سازی و آگاهی از روند تغییرات نیتروژن و فسفر در طول رودخانه ذر (بازه سد دز تا پل بند قیر ) با مدل Qual2kw و همچنین محاسبه درصد خودپالایی رودخانه می باشد. روش بررسی: در این مطالعه با توجه به آمار و داده های اندازه گیری شده در مورد کیفیت آب رودخانه دز در سه ایستگاه دزفول، حرمله و بامدژ و مقایسه آنها با استانداردهای موجود، وضعیت این رودخانه مورد بررسی قرار گرفت. مدل شبیه ساز رودخانه با ورود مشخصات کمی و کیفی در ایستگاه های تعیین شده و پساب های ورودی به آن در فصل کم آب ساخته و کالیبره شد. یافته ها: نتایج نشان داد که قدرت خودپالایی رودخانه کم است، بیشترین مقدار خودپالایی مربوط به پارامتر N-NH4 در سال 2014 معادل 45% می باشد. میزان فسفر غیرآلی در طول رودخانه روند رو به رشدی داشته است. بحث و نتیجه گیری: میزان نیتروژن نیتراتی و نیتروژن آمونیاکی در بازه کیلومتر 173 تا 90 رودخانه، به علت هجوم فاضلاب ها روند افزایشی دارد. بهترین شبیه سازی برای پارامتر N-NH4 در سال 2016 می باشد که خطای استاندارد آن معادل 02/0 می باشد.

چکیده انگلیسی:

Background and Objective: It is necessary to use mathematical models to determine the expected reaction of a river to the effects of entrance of pollutants. Such models can simulated the effects of current and future loadings and help managers and authorities make their final decisions. The purpose of this study is to simulate and be aware of the trend of nitrogen and phosphorus changes along the Dez River (Dez Dam to Ghir Dam Bridge) using the Qual2kw model and also to calculate the percentage of river self-purification. Method: The present study was aimed at measuring and comparing the data of the quality of Dez River water collected from three stations. Self-purification model of the river was determined by inserting qualitative and quantitative data retrieved from the stations, and the entering wastewaters in the dry season were created and calibrated. Findings: The results of the present study showed that the river has poor self-purification power. The highest self-purification power was related to N-NH4 parameter in 2014 (45%). The level of non-organic phosphor along the river had an increasing trend. Discussion and Conclusion: The level of nitrate nitrogen and ammonia nitrogen within the distance of 173 to 90 km of the river had an increasing trend due to influx of sewage. The best modelling for N-NH­4 parameter was related to 2016 with a standard error of 0.02.  

منابع و مأخذ:

 

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_||_

  1. Hanfeng, Y. E., Shuhai, GUO., Fengmei, LI. And LI. Gang., 2013. Water Quality Evaluation in Tidal River Reaches of Liaohe River Estuary, China Using a Revised QUAL2K Model. Chinese Geographical Science, 23(3): 301–311
    2.
  2. Kalburgi, P. B., Shareefa, R. N. and U. B. Deshannavar., 2015. Development and Evaluation of BOD–DO Model for River Ghataprabha near Mudhol (India), using QUAL2K. I.J Engineering and Manufacturing, 5(1): 15-25.
    3.
  3. Hayes, D. F., Labadie, J. W., Sanders, T. G. and J. K. Brown., 1998. Enhancing water quality in hydropower system operations. Water Research, 34: 471–483.
    4.
  4. Herbay, J. P., Smeers, Y. and D. Tyteca., 1983. Water quality management with time varying river flow and discharger control. Water Research, 19: 1481–1487.
    5.
  5. Noshadi, M., Hatmizade, M.R., 2010. Qualitative measurement and simulation of Kor river using the Qual2k model. Iranian Journal of Irrigation and Drainage 3: 338-349. (In Persian).
    6.
  6. Shahriari, F., Javadifar, N., Akhondali, A.M. 2010. Changes in flow rate on water quality in Karoon river using Qual2kw model. The fifth national congress and specialized environmental exhibition. Tehran. 50:1-10. (In Persian)
    7.
  7. Razaghian. F., Sabziparwar. B., Sarang, A. 2015. Qualitative modeling of Qarasoo river in Kermanshah using Qual2kw model. Tenth international congress on civil engineering Tabriz . 10:1-8. (In Persian)
    8.
  8. Xiaobo, F., Jianying, Z., Yingxu, C. and X. Xiangyang. 2008. QUAL2K model used in the water quality assessment of Qiantang River, China. Water Environment Research, 80: 2125–2133.
    9.
  9. Fan, C., Ko, C. and W.Wang. 2009. An innovative modeling approach using Qual2K and HEC-RAS integration to assess the impact of tidal effect on River Water quality simulation. Journal of Environmental Management, 90(5): 1824–1832.
    10.
  10. Grabiç, J., Bezdan, A., Benka, P. and A. Salvai. 2011. Spreading and transformation of nutrients in the Reacg of the Becej-Bogojeco Canal, Serbia. Carpathian Journal of Earth and Environmental Sciences, 6(1): 277–284.
    11.
  11. Rafiee, M., Akhondali, A. M., Moazed. H., Lyon, S. W., Jaafarzadeh, N. e. and B. Zahraie. 2013. A Case Study of Water Quality Modeling of the Gargar River, Iran. Journal of hydraulic structures, 1(2): 10-22.
    12.
  12. Oliveira, B., Bola, J., Quinteiro, P., Nadais, H. and L. Arroja. 2012. Application of Qual2Kw model as a tool for water quality management: Cértima River as a case study. Environ Monti Assess, 184: 6197–6210.
    13.
  13. Gupta R.C., Gupta A.K and Shrivastava R.K., 2013. Water quality modeling of a stretch of river Kshipra India. Nature Environment and Pollution Technology, 123: 511-516.
    14.
  14. Hossain, M. A., Sujaul, I. M. and M. A. Nasly., 2014. Application of QUAL2Kw for water quality modeling in the Tunggak River, Kuantan, Pahang, Malaysia. Research Journal of Recent Sciences, 3(6): 6-14.
    15.
  15. Bagherian, Marzouni M., Akhoundalib, A.M., Moazed, H., Jaafarzadeh N., Ahadian J. and Hasoonizadeh, H. 2014. Evaluation of Karun river water quality scenarios using simulation model results. International journal of Advanced Biological and Biomedical Research, 22: 339-358.
    16.
  16. Mehrasbi, M.R. and Farahmand, Kia. Z. 2015. Water quality modeling and evaluation of nutrient control strategies using qual2k in the small sivers, J. Hum. Environ. Health Promot. 11: 1-11
    17.
  17. Vivin, S.I., Wahyono, H., Masduqi, A. 2016. Identifikasi Daya Tampung Beban Pencemaran Air Kali Surabaya Segmen Jembatan Canggu- Tambangan Bambe dengan Pemodelan QUAL2Kw, JURNAL TEKNIK ITS Vol. 5, No. 2, PP. 857-861. (2016) ISSN: 2337-3539 (2301-9271 Print).
    18.
  18. Dulaimi, G.A. 2017. Evaluation of BOD and DO for Diyala River by Using Stream Water Quality Model. International Journal of Environmental Science and Development, Vol 8. N. pp 1-6.
    19.
  19. Chapra, S.C., Pelletier, G.J. and H.Tao. 2008. “QUAL2K – a modeling framework for Simulation river and streams water quality (Version 2.11)”. Documentation and User Manual, pp 1-109.
    20.
  20. Azimi, M., Gawasie, A., Hashemi, S., Barketin, S. 2010. Assessing the power of self-purification of the river with help of result of qualitative simulation (case study: Sefidrood River). National water conference with clean water approach. University of Water and power industry. 1:1-10. (In Pesian)
    21.
  21. Sentelhas, P., Gillespie, T., and Santos, E.A. 2010. Evaluation of FAO Penman-Monteith and alternative methods for estimating reference evapotranspiration with missing data in southern Ontario, Canada. Agricultural Water Management 97: 635-644.
    22.
  22. Zhang, R., Qain, X., Li, H., Xingcheng, Y., Rui, Y., 2012. Selection of River Water Basin Chin. Scienee of theTotal Envairoment 431, 278-285.
    23.
  23. Chang, H. 2004. Water quality impacts of climate andland use changes on Southeastern Pennsylvania. Theprofessional Geographer. vol. 56. pp. 240­257
    24.
  24. Carney, E. 2009. Relative influence of lake age and watershed land use on tropic state and water quality of       artificial lakes in Kansas. J. Lake Reserve. Manage. vol. 25. pp. 199 ­207.
    25.
  25. Mahamah, D. S., 1998. Simplifying assumptions in water quality modeling. Ecological Modelling, 109(3): 295–300.
    26.

 
 

 
 

 

 

 

 

 

 

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