بررسی پارامترهای مؤثر بر خشک شدن دریاچه ارومیه با استفاده از فرآیند تحلیل شبکه‌ای فازی

نوع مقاله : مقاله پژوهشی

نویسندگان

آب و هواشناسی، دانشکده جغرافیا، دانشگاه تهران، ایران

چکیده
دریاچه ارومیه در شمال غربی ایران واقع‌شده و یکی از بزرگ‌ترین دریاچه‌های فوق شور دائمی جهان و بزرگ‌ترین دریاچه فوق شور خاورمیانه می‌باشد. در دو دهه اخیر در اثر تغییرات آب‌ و هوا و کاهش بارش، افزایش دما و تبخیر و بسیاری دیگر از عوامل تشدیدکننده خشک‌سالی، مصرف آب در منطقه افزایش یافته همچنین احداث سد و میان‌گذر شهید کلانتری و استفاده از آب رودهای تغذیه‌کننده دریاچه جهت مصارف کشاورزی و شهری موجب کاهش شدید آب دریاچه شد. در این تحقیق مدل مفهومی جهت بررسی میزان اثرگذاری و اثرپذیری و تعیین ضرایب اهمیت نسبی و رتبه‌بندی آن‌ها با استفاده از روش یکپارچه‌سازی دیمتل و فرآیند تحلیل شبکه‌ای فازی و ماتریس ارتباطات عوامل مؤثر جهت تعیین ضرایب وزنی به روش F.D.ANP ارائه ‌گردید تا مهم‌ترین پارامترهای موثر بر خشکی دریاچه ارومیه شناسایی شود. بررسی اولویت‌بندی زیر معیارها نشان داد تمامی زیرمعیارهایی که بعد از چهار زیر معیار مدیریتی قرارگرفته است، به‌جز افزایش دما، کاهش باران و افزایش تبخیر همگی درصورتی‌که یک برنامه مدیریتی صحیح تدوین می‌شد شرایط افت آب دریاچه رخ نمی‌داد و یا شدت بسیار کمتری داشت.

کلیدواژه‌ها

موضوعات


عنوان مقاله English

Investigating the effective parameters on the drying of Urmia lake using fuzzy network analysis process

نویسندگان English

Sahar Maleki
Homa Rostami
Hydrology and Meteorology, Faculty of Geography, University of Tehran, Iran
چکیده English

Lake Urmia is located in the northwest of Iran and is one of the largest permanent super-saline lakes in the world and the largest super-saline lake in the Middle East. In the last two decades, as a result of climate change and decrease in precipitation, increase in temperature and evaporation and many other factors that exacerbate drought, water consumption in the region has increased, as well as the construction of the Shahid Kalantari dam and bypass and the use of water from the rivers feeding the lake for agricultural purposes and A city caused a sharp decrease in the water of the lake. In this research, a conceptual model was presented to investigate the degree of influence and effectiveness and to determine the relative importance coefficients and their ranking by using the Dimetal integration method and the process of fuzzy network analysis and the matrix of effective factors to determine the weight coefficients using the F.D.ANP method, so that the most important parameters affecting To identify the dry land of Lake Urmia. The review of the sub-criteria prioritization showed that all the sub-criteria that are placed after the four management sub-criteria, except for the increase in temperature, decrease in rain and increase in evaporation, if a correct management plan was developed, the conditions of the lake's water drop would not have occurred or would have been much less severe.

کلیدواژه‌ها English

Lake Urmia
climate
fuzzy network analysis process
drought
environmental management
Ahmadian, M.&Asghari, S. (2013). The Environmental consequences of reduced water levels in the Lake Urmia and its survival, Journal of Territory, (40): 81-96. (in persian) 
Alavipanah, K., Khodaei, K. &Biglou, J. (2005). Study of satellite data efficacy on water quality in the Urmia lake causeway, Physical Geography Research Quarterly, (53): 57-69.(in persian)
Alden, M., Mortsch, L.&Scheraga, J. (2003). Climate Change and Water Quality in the Great Lakes Region: Risks, Opportunities, and Responses. A Report prepared for the Great Lakes Water Quality Board of the International Joint Commission.
Bates, B., Kundzewicz, Z. W., Wu, S., &Palutikof, J. (2008). Climate change and water. Intergovernmental Panel on Climate Change (IPCC).
Chang, D.Y. (1996). Theory and Methodology Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, (95): 649-655.
Chang, D.Y., Zhu, k.j.& Jing, Y. (1999). A discussion on Extent Analysis Method and applications of fuzzy AHP. European Journal of Operational Research,(116): 450-456.
Chen, J.F., Hsieh, H.N.&Do, Q.H. (2015). Evaluating teaching performance based on fuzzy AHP andcomprehensive evaluation approach. Applied Soft Computing(28): 100–108.
Cil, I.&Turkan, Y.S. (2013). An ANP-based assessment model for lean enterprise transformation. International Journal of Advanced Manufacturing Technology, (64):1113–1130.
Eimanifar, A. &Mohebbi, F. (2007). Urmia Lake (Northwest Iran)a brief review,Saline SystemsBioMed Central Ltd, (3:5): 1-8.
Faezeh, A., Azizi, Gh.,Karimi. M.&Nazif, S.(2014). Assessment of climate change`s portion on declining water level in Urmia lake, Thesis of M.A. in Climatology, Faculty of Geography, University of Tehran.
Fathian, F., Morid, S.&Arshad, S.(2013). Trend Assessment of Land Use Changes Using Remote Sensing Technique and its Relationship with Streamflows Trend (Case Study: The East Sub-Basins of Urmia Lake), Journal of Water and Soil,(27):642-655.
Gogus, O.&Boucher, T.O.(1998). Strong transitivity and weak monotonicity in fuzzy pairwise comparisons. Fuzzy Sets and Systems, (94):1-133.
Golabian, H., 2010. Urumia Lake: Hydro-Ecological Stabilization and Permanence Macro-engineering Seawater in Unique Environments. Berlin, Springer-Verlag. 365-397.
Hassanzadeh,E.,Zarghami,M.&Hassanzadeh, Y.(2012). Determining the main factors in declining the urmia lake level by using system Dynamics Modelling,Journal of water Resource Management, 26(1):129-145.
Hoseinpour, M., FakheriFard, A.&Naghili,R. (2010). Death of Urmia Lake, a Silent Disaster Investigating of causes, results and solutions of Urmia Lake drying, The 1st International Applied Geological Congress, Department of Geology, Islamic Azad University - Mashad Branch, Iran, 26-28.
Jeng, D.J.F.&Tzeng, G.H., (2012). Social influence on the use of Clinical Decision Support Systems: Revisiting the Unified Theory of Acceptance and Use of Technology by the fuzzy DEMATEL technique. Computers & Industrial Engineering,(62): 819–828.
Kadioglu, M., Sen, Z. &Batur, M.(1997). The great test soda-water Lake in the world and how it is influenced by climatic change, Ann Geophysical,Springer Verlag,(15): 1489-1497.
Kahraman, C., Ertay, T., &Büyüközkan, G. (2006). A fuzzy optimization model for QFD planning process using analytic network approach. European Journal of Operational Research,(171): 390–411.
Kebede, S., Y, Travi, T. Alemayehu & Marc V. (2006). Water balance of Lake Tana and its sensitivity to fluctuations in rainfall, Blue Nile basin, Ethiopia. Journal of Hydrology, (316): 233-247.
Koushki, R.(2013). Assessing the portions of each parameter on decline of the Lake’s water level in different years, Lake Urmia Conference, Berlin Centre for Caspian Region Studies (BC CARE).
Leung, L.C.&Cao, D., (2000). On consistency and ranking of alternatives in fuzzy AHP. Europen Journal of Operational Reasearch, 124(1)
Lin, C.J.& Wu, W.W.(2008). A causal analytical method for group decision making under fuzzy environment. Expert Systems with Applications,(34): 205-213.
Nasiri, K.K., Modiri, M.&Hashemzadeh, G.(2015). Assessment Model for Implementing a Lean Transformation in Enterprise Based on the Fuzzy Anp, Fuzzy Dematel and Fuzzy Vikor, journal of modiriat-e-farda, 42 (13): 129-156.(in persian)
Nazmfar, H., Fathi, M.&Khaligi, M.(2014). Effects of water level fluctuations in Lake Urmia in Iran on the bio-ecology of the North West using telemetry data, Geography and Environmental Planning, 26(3): 193-208.(in persian)
Opricovic, S.&Tzeng, G. H. (2003). Defuzzification within a multicriteria decision model. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 11(5): 635–652.
Reza, K., &Vassilis, S. M.(1998). Delphi hierarchy process (DHP): A methodology for priority setting derived from the Delphi method and analytical hierarchy process,European Journal of Operational Research, (697): 947–914.
Saaty, T. L. (1996). Decision making with dependence and feedback: The analytic network process. Pittsburgh: RWS Publications.
Saaty, T.L. (2002). Decision making, scaling, and number crunching, Journal of Decision Sciences,(20): 404-409.
Shariatmadari1, A.,Abbaspour, M.,Abedi, Z.,Vafaeenejad, A.& Tabatabai, R. (2015).Assessment of the environmental condition of Lake Urmia by combining DPSIR framework and productivity model (Ishikawa), Journal of Biodiversity and Environmental Sciences (JBES), Vol. 6 (6): 596-600.
Sima, S., and Tajrishy, M. (2014). Developing water quality maps of a hyper-saline lake using spatial interpolation methods, Sharif University of Technology, ScientiaIranica, Transactions A: Civil Engineering, 22(1): 30-46.
United Nations Environment Program (UNEP).(2012). the drying of Iran's Lake Urmia and its environmental consequences.Report.
Wang, Y., Jung, K.A., Yeo, G.T.& Chou, C.C. (2014). Selecting a cruise port of call location using the fuzzy-AHP method: A case study in East Asia. Tourism Management,(42): 262-270.
Yüksel, I.&Dağdeviren, M., (2010). Using the fuzzy analytic network process (ANP) for Balanced Scorecard (BSC): A case study for a manufacturing firm. Expert Systems with Applications, (37): 1270–1278.
Zarghami, M. (2011). Effective watershed management; Case study ofUrmia Lake, Iran, Lake and Reservoir Management,(27):87–94.