تحلیل سطح تغذیه گرایی مخزن سد شیرین دره با استفاده از رویکرد آنتروپی فازی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشگاه علوم کشاورزی و منابع طبیعی گرگان

2 دانشگاه کشاورزی و منابع طبیعی گرگان

چکیده

تغذیه‌‌گرایی فرایندی طبیعی است که افزایش دخالت‌‌های انسانی سبب تسریع این پدیده و کاهش سریع کیفیت آب و پیر شدن مخزن سد می‌‌شود و همواره یکی از مهمترین مشکلات مخازن در دنیا بوده است. از آنجایی که تعیین سطح تغذیه‌‌گرایی مخزن امری پیچیده و مبهم است در این تحقیق از تحلیل ترکیبی فازی با روش وزن‌‌دهی آنتروپی برای تعیین سطح تغذیه‌‌گرایی در مخزن سد شیرین‌‌دره در استان خراسان شمالی و در یک بازه زمانی یک ساله استفاده شده است. به همین منظور از مقادیر فازی‌‌ شده متغیرهای اصلی شامل غلظت کلروفیل آ، فسفر کل، اکسیژن اشباع و نیتروژن کل برای تعیین تابع عضویت و از روش آنتروپی شانون برای تعیین وزن‌‌ متغیرهای شاخص استفاده شد. در نهایت، نتایج این رویکرد با نتایج روش توزیع یکسان و روش کارلسون مقایسه شد. نتایج نشان داد که مخزن سد در ماه‌‌های آذر تا اسفند در شرایط الیگوتروفیک، در ماه آبان مزوتروفیک و در بقیه ماه‌‌ها در سطح یوتروفیک قرار دارد. با توجه به قابلیت این رویکرد که قادر به بیان درجه قطعیت و شدت هر سطح در ماه‌‌های مختلف است مشاهده شد که ماه‌‌های تیر، مرداد و شهریور با بیشترین قطعیت، مخزن را در شرایط یوتروفیک شدید قرار می‌‌دهند. همچنین نتایج رویکرد به کار گرفته شده در مقایسه با روش کارلسون و فازی با توزین یکسان منطقی و واقع‌‌بینانه‌‌تر است.

کلیدواژه‌ها


عنوان مقاله [English]

Eutrophication Level Analysis of Shirin- Darreh Dam Reservoir Using Entropy-Based Fuzzy Approach

نویسندگان [English]

  • Mehdi Teimouri 1
  • Vahed berdi Sheikh 2
  • amir Sadoddin 1
1 Gorgan University of Agricultural Sciences and Natural Resources
2 Gorgan University of Agricultural Sciences and Natural Resources
چکیده [English]

Eutrophication is a natural process which can be increased by human interferences and finally lead to water quality degradation and reservoir aging, and always is one of the challenging problems of reservoir across the world. Since determining of the trophic status of the reservoir is a complex and intriguing process, this study used fuzzy synthetic evaluation method with entropy weighting technique to determine eutrophication level in the Shirin-darreh dam reservoir in the North Khorasan province for a one year period of time. To this end, fuzzified data of main variable including chlorophyll-a concentration, total phosphorous, saturation oxygen and total nitrogen were used to determine membership function and the Shannon entropy technique was used for weighting index variables. Finally, results of this approach was compared with the results of equal weighting technique and Carlson method. The results showed that from December to March the reservoir was in oligotrophic status, during November in mesotrophic status and during other months it experienced an eutrophic condition. Considering the capability of this approach to express the degree of certainty and intensity at different levels and months, it was observed that July, August and September have the highest eutrophication level with most degree of certainty. Also, this approach has reasonable and realistic results in comparing with Carlson method and equal weighting fuzzy technique.

کلیدواژه‌ها [English]

  • Eutrophication Level
  • Water Quality
  • Fuzzy Synthetic Evaluation
  • Shannon Entropy
  • Shirin-darreh Dam

Abdolabadi, H. & Niksokhan, M.H. 2014. Evaluation of Eutrophication in the Ilam Reservoir Using Fuzzy Approach. Journal of Water and Soil, 27(6): 1260-1269 (in Persian).

Ansari, H. & Davary, K. 2010. Estimating Precipitation Data Using a Fuzzybased Technique. Iran-Water Resources Research, 6(1): 39-47 (in Persian).

Carlson, R.E. 1977. A trophic state index for lakes. Limnological Oceanography, 22(2): 361-369.

Carlson, R.E. 1992. Expanding the trophic state concept to identify non-nutrient limited lakes and reservoirs. In Proceedings of a National Conference on Enhancing the States’ Lake Management Programs. Monitoring and Lake Impact Assessment, Chicago, IL. 59-71.

Chang, N.B.; Chen, H.W. & Ning, S.k. 2001. Identification of river water quality using the Fuzzy Synthetic Evaluation approach. Journal of Environmental Management. 63:293-305.
Ding, X.; Chong, X.; Bao, Z.; Xue, Y. & Zhang, S. 2017. Fuzzy Comprehensive Assessment Method Based on the Entropy Weight Method and Its Application in the Water Environmental Safety Evaluation of the Heshangshan Drinking Water Source Area, Three Gorges Reservoir Area, China. Water. 9(5): 1-15.
Dodds, W.K.; Johnson, K.R. & Priscu, L.C. 1989. Simultaneous nitrogen and phosphorous deficiency in natural phytoplankton assemblages: Theory, empirical evidence and implications for lake management. Lakes and Reservoir Management, 5: 21-26.
Ehrampush, M.H.; Mehrjerdi, A.Z.; Ghaneian, M.T.; Mehrizi, E.A. & Saghi, M.H.  2015. Qualitative assessment of Bojnurd main water supply by using water quality indices in 2013: Case study of Shirin Dareh reservoir dam.  Journal of North Khorasan University of Medical Sciences, 7(3): 475-484 (in Persian).
Khajehepour, M.E.; Karimi, L.; Shiasi Arani, M. & Ansari, H. 2014. Eutrophication Check of Reservoirs with CE-QUAL-W2 (Case study: Shirin Darre dam reservoir). Iranian Journal of lrrigation and Drainage, 8(1): 96-107 (in Persian).
Lin, R. & Huang, W. 2015. Fuzzy assessment on reservoir water quality. Journal of Marine Science and Technology 23(2): 231-239.

Lu, R.; Lo, L. & Hu, J. 1999. Analysis of reservoir water quality using fuzzy synthetic evaluation, Stochastic Environmental Research and Risk Assessment, 13: 327-336.

McIntyre, N. R.; Wagener, T.; Wheater, H.S. & Chapra, S.C. 2003. Risk based modelling of surface water quality: A case study of the Charles River, Massachusetts, Journal of Hydrology, 274(1): 225 – 247.
Mourhir, A.; Rachidi, T. & Karim, M. 2014. River water quality index for Morocco using a Fuzzy inference system. Environmental Systems Research. 3(21):1-12.
Nalamutt, T. & Karmakar, S. 2014. Modeling Impreciseness of Trophic State Levels for Eutrophication Assessment. Journal of Clean Energy Technologies. 2(2): 140-144.
OECD. 1982. Eutrophication of Water: Monitoring, Assessment and Control, Organization for Economic Cooperation and Development, Paris.

Silvert, W. 2000. Fuzzy indices of environmental conditions, Ecological Modeling. 130: 111–119.

Singh, V. 1997. The use of entropy in hydrology and water resources. Hydrological Processes. 11:587-626.

Shannon, C. 1948. A Mathematical Theory of Communication. The Bell System Technical Journal. 27: 379-423.

Taheriyoun, M.; Karamouz, M. & Baghvand, A., 2010. Development of an entropy-based fuzzy eutrophication index for reservoir water quality evaluation. Iranian journal of Environmental Health. Science engineering. 7(1):1-14.

U.S. EPA. 1999. Protocol for Developing Nutrient TMDLs (First Edition).

Vollenweider, R.A. & Kerekes, J.J. 1980. Background and summary results of the OECD cooperative program on eutrophication. International Symposium on Inland Waters and Lake Restoration. EPA 440/5-81-010. U.S. Environmental Protection Agency, Washington, DC.

Wang, D.; Singh, V. & Zhu, Y. 2007. Hybrid fuzzy and optimal modeling for water quality evaluation. Water Resources Research. 43(5):1-10.

Wang, J.; Xiangouo, L.U; Jinghan, T. & Ming, J. 2008. Fuzzy synthetic evaluation of water quality of Naoli River using parameter correlation Analysis, Chinese Geographical Science. 18(4): 361-368.
Yan, H.; Wang, G.; Zhang, X.; Dong, J.; Shan, K.; Wu, D.; Huang, Y.; Zhou, B. & Su, Y. 2016. A fast method to evaluate water eutrophication. Journal of Central South University. 23(12): 3204–3216.
Zhi Hong, Z.; Yi, Y. & Jing Nan, S. 2006. Entropy method for determination of weight of evaluating in fuzzy synthetic evaluation for water quality assessment. Journal of environmental sciences. 18(5): 120-1023.