ارزیابی و مقایسه حساسیت مدلهای NSFWQI و IRWQISC نسبت به پارامترهای کیفیت آب

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استاد /گروه مهندسی آب، دانشکده فنی و مهندسی، دانشگاه بین‌المللی خمینی (ره)، قزوین، ایران.

2 عضو هیئت علمی/ گروه پایش منابع آب، پژوهشکده محیط زیست جهاد دانشگاهی،رشت، ایران

چکیده

‌ این مطالعه با هدف ارزیابی و مقایسه حساسیت دو مدل کیفیت آب NSFWQI و IRWQISC نسبت به پارامترهای کیفی با استفاده از روشهای مبتنی بر واریانس، روی رودخانه پسیخان با نمونه برداری ماهانه در سال 94 در 13 ایستگاه، منتخب انجام شده است. براساس نتایج تحلیل حساسیت فصلی پارامتر BOD بیشترین حساسیت را در هر دو مدل نشان داد. کیفیت آب براساس شاخص NSFWQI در ایستگاههای بالادست "متوسط" و در ایستگاههای پایین دست، "بد" بود در حالیکه شاخص IRWQISC کیفیت آب رودخانه در بالادست را "خوب" و در پایین دست "نسبتا بد" گزارش نمود. آنالیز حساسیت مدل NSFWQI به صورت مکانی براساس رویکرد Factor Prioritization پارامتر DO را مؤثرترین عامل بر واریانس خروجی مدل معرفی کرد و برهمین اساس به کمک رویکرد Factor Fixing نشان داده شد که با ثابت کردن پارامتر DO می توان واریانس خروجی را تا حد زیادی کنترل و عدم قطعیت مدل مزبور را تا حد زیادی کاهش داد. در مدل IRWQISC در ایستگاههای بالادست، پارامتر DO و در ایستگاههای پایین دست پارامتر BOD بیشترین تاثیر را در واریانس خروجی مدل داشت. بر این اساس در ارزیابی کیفی با شاخص IRWQISC تعداد دفعات و اندازه گیری دقیق دو پارامترDO و BOD دارای اهمیت زیادی در مقابل 9 پارامتر دیگر قلمداد گردید. نتیجه مهم دیگر مطالعات آن است که ضرایب وزنی پارامترهای کیفی در مدل IRWQISC تطابق مناسبی با اثرگذاری آنها درخروجی مدل برای نمایش وضعیت کیفی ندارد و این امر مطالعه بیشتری برای پذیرش آن به عنوان یک استاندارد بومی در ایران گوشزد می نماید.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Evaluating and Comparing the Sensitivity of NSFWQI and IRWQISC Models to Water Quality Parameters

نویسندگان [English]

  • A.R. Shokoohi 1
  • Hadi Modaberi 2
1 Professor, Department of Water Engineering, Faculty of engineering and technology, Khomeini International University, Qazvin, Iran.
2 Academic member, Water Resources Monitoring Department, Environmental Research Center, Jihade Daneshgahi, Rasht, Iran
چکیده [English]

In this paper, using variance based methods, the sensitivity analysis of the two well recognized water quality indices, namely NSFWQI and IRWQISC, is presented in a comparative approach. The research was conducted by employing monthly sampling at thirteen stations on Pasikhan River during 2015. Sensitivity analysis of the two models’ parametres could lead to recognize the most important ones for their better measurement and also to evaluatie the correctness of the parametrs’ weights used in the Iranianian model. In the seasonal analysis, BOD was determined as the most sensitive parameter for both indices. In spatial analysis, NSFWQI classified the river water quality as “Good” and “Bad” in upstream and downstream Pasikhan River, respectively. Using Factor prioritization approach, it was found that DO was the most effective parameter in NSFWQI, for which applying the approach minimized the uncertainty of the model output. In IRWQISC, Do at U/S stations and BOD at D/S stations were the most influencing parameters on the model output variance, which emphasized the importance of the frequency and precision of sampling of these two factors against the other nine employed factors . Another important achievement of the present research was revealing the inconsistency of the weights used in IRWQISC, with respect to the parameters’ sensitivity and their influence on the model output in Pasikhan River.

کلیدواژه‌ها [English]

  • Sensitivity analysis
  • Water Quality Index
  • NSFWQI
  • IRWQI
  • Pasikhan River
Alizadeh M, Mirzaei R, Kia SH (2017) Determining the spatial trend of water quality indices
across Kan and Karaj River Basins. Journal of Environmental Health Engineering 4(3):243-256 (In persian)
Aminpour S, Mohammadi M, Khaledian M, Mir Roshandel A (2017) Water quality assessment of the Ghazrodbar River using the NSFWQI qualitative index and Liou Pollution Index. Journal of Wetland Ecobiology 22:31-40 (In persian)
APHA (2005) Standard methods for the examination of water and wastewater, 23th edition. American Public Health Association, Washington, DC. USA, 541p
Brown RM, McLelland NJ, Deininger RA, Tozer RG (1970) A water quality index ­ do we dare? Water and Sewage Works 339-343
Fabiano DS, Altair BM, Marcia CB, Sonia MNG, Maria JSY (2008) Water quality index as a simple indicator of aquaculture efects on aquatic bodies. Ecological indicators 8:476-484
Hashemi S, Farzampour T, Ramzani S, Khoshroo Gh (2012) Guidelines for calculating Iran Water Quality Index. Department of Environment, 42 p (In persian)
Herman J, Reed P, Wagener T (2013) Time‐varying sensitivity analysis clarifies the effects of watershed model formulation on model behavior. Water Resources Research 49:1400-1414
Massmann C, Holzmann H (2012) Analysis of the behavior of a rainfall–runoff model using three global sensitivity analysis methods evaluated at different temporal scales. Journal of Hydrology 475:97-110
Mohammadi K, Razdar B, Samani J (2006) Investigation of the quality of water of the Pasikhan River using CE-QUAl-W2 Model, Nitrate and Phosphate parameters and comparing the results of simulation with WASP software. In Proc. of Fourth National Congress of Civil Engineering, May 2008, Tehran, Iran,1-8 (In persian)
Mohseni-Bandpey A, Majlesi M, Kazempour A (2014) Evaluation of Golgol river water quality in Ilam province based on the National Sanitation Foundation Water Quality Index (NSFWQI). Journal of Health in the Field 1(4):1-7 (In persian)
Panahande M, Rahbar Hashemi M, Ashournia M, Modaberi H (2016) Investigation on the effects of toxicity and potential ecological risks of lead and cadmium in sediments of Anzali Wetland usingTUI and Haksnson models. In Proc. of First International Conference on Environmental Engineering, Feb. 2014, Tehran, Iran, 1-9 (In persian)
Pappenberger F, Beven KJ, Ratto M, Matgen P (2008) Multi-method global sensitivity analysis of flood inundation models. Advances in Water Resources 31:1-14
Parastar S, Poureshgh B, Dargahhi A, Poreshgh Y, Vosoughi M (2013) Quality assessment of Hiroo River by NSFWQI and WILCOX indices in Khalkhal. Health Journal 4(3):273-283 (In persian)
Sadeghi M, Bay A, Bay N, Soflaie N, Mehdinejad MH, Mallah M (2015) The survey of Zarin-Gol River water quality in Golestan Province using NSF-WQI and IRWQISC. Journal of Health in the Field 3(3):27-33 (In persian)
Saltelli A (1999) Sensitivity analysis: Could better methods be used? Journal of Geophysical Research: Atmospheres 104:3789-3793
Saltelli A, Ratto M, Andres T, Campolongo F, Cariboni J, Gatelli D, Saisana M, Tarantola S (2008) Global sensitivity analysis: the primer. John Wiley & Sons, 305p
Saltelli A, Ratto M, Tarantola S, Campolongo F (2012) Update 1 of: Sensitivity analysis for chemical models. Chemical Reviews 112:PR1-PR21
Saltelli A, Tarantola S, Campolongo F, Ratto M (2004) Sensitivity analysis in practice: A guide to assessing scientific models. John Wiley & Sons, Ltd. 232p
Samadi J (2015) Survey of spatial-temporal impact of quantitative and qualitative of land use wastewaters on Choghakhor Wetland pollution using IRWQI Index and statistical methods. Iranian Water Resources Research 11(3):159–171 (In persian)
Sánchez E, Colmenarejo M, Vicente J, Rubio A, García M, Travieso L, Borja R (2007) Use of the water indicators of watersheds pollution. Journal of Ecological Indicators 7(2):315-28
Sharifdini NG, Amirnezhad R, Saeb K (2014) Qualification zoning of the Dohezar River according
to NSFWQI and using GIS. J Mazandaran Univ Med Sci. 24(118):29-39 (In persian)
Shokuhi R, Hosinzadeh E, Roshanaei G, Alipour M, Hoseinzadeh S (2012) Evaluation of Aydughmush Dam reservoir water quality by National Sanitation Foundation Water Quality Index (NSF-WQI) and water quality parameter changes. Journal of Health and Environ 4:439-450 (In persian)
Sobol IM (2001) Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Mathematics and Computers in Simulation 55:271-280
Sohrabi N, Alizade A, Hasoonizade H , Hosseinzade S (2015) Qualitative zoning of the Surgical River based on the NSFWQI index and using the GIS. Journal of Wetland Ecobiology 22:31-40
Song X, Zhan C, Xia J, Zhang Y (2014) Methodology and application of parameter uncertainty quantification in watershed hydrological models. China Water Power Press, Beijing, China, 432p
Song X, Zhang J, Zhan C, Xuan Y, Ye M, Xu C (2015) Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications. Journal of hydrology 523:739-757
Tian W (2013) A review of sensitivity analysis methods in building energy analysis. Renewable and Sustainable Energy Reviews 20:411-419
Zeng X, Wang D, Wu J (2012) Sensitivity analysis of the probability distribution of groundwater level series based on information entropy. Stochastic Environmental Research and Risk Assessment 26:345-356
Zhan C-S, Song X-M, Xia J, Tong C (2013) An efficient integrated approach for global sensitivity analysis of hydrological model parameters. Environmental Modelling and Software 41:39-52