اولویت بندی امنیت هیدرولوژیکی زیرآبخیزهای حوزه آبخیز گرگانرود بر اساس شاخص‌های تغییر هیدرولوژیک (IHA)

نوع مقاله : پژوهشی

نویسندگان

1 دانشجوی مقطع دکتری، گروه مهندسی آبخیزداری، دانشکدۀ منابع طبیعی و علوم دریایی، دانشگاه تربیت مدرس، نور، ایران

2 استاد و عضو هیئت علمی گروه مهندسی آبخیزداری، دانشکدۀ منابع طبیعی و علوم دریایی، دانشگاه تربیت مدرس، نور، ایران

3 استاد گروه مهندسی عمران، محیط زیست، و ساخت و ساز و مرکز تحقیقات منابع آب، دانشگاه هاوایی، ایالات متحده آمریکا

چکیده

پژوهش حاضر با هدف اولویت بندی امنیت هیدرولوژیکی در مقیاس زیرآبخیز انجام گردیده است. برای این منظور 31 متغیر هیدرولوژیکی جریان در 16 زیرحوزه آبخیز حوزه آبخیز گرگانرود که مجهز به ایستگاه هیدرومتری بودند، با استفاده از نرم‌افزار شاخص‎‌های تغییر هیدرولوژیک (IHA) محاسبه و از آنتروپی شانون برای وزن‌دهی به آن‌ها استفاده گردید. در نهایت برای اولویت‌بندی‌ زیرآبخیزها چهار روش تصمیم‌گیری چندمعیاره (MCDM) شامل (TOPSIS) Technique for Order Preference by Similarity to an Ideal Solution، (VIKOR) VlseKriterijumska Optimizcija I Kaompromisno Resenje ، (SAW) Simple Additive Weighting و (COPRAS) COmplex PRoportional Assessment اجراء شد. نتایج نشان داد متغیر C23 (روزهای صفر جریان) و C27 (تعداد ضربان بالا) به ترتیب با مقادیر 057/0 و 006/0 بیشترین و کمترین وزن را دریافت کردند. نتایج اولویت‌بندی امنیت هیدرولوژیکی جریان نشان داد بر اساس روش‌های TOPSIS و VIKOR زیرآبخیز S11 و براساس روش‌های SAW و COPRAS زیرآبخیزهای S15 و S2 بالاترین امتیاز امنیت هیدرولوژیکی را دارند. از سوی دیگر زیرآبخیز S10 بر اساس روش‌های TOPSIS، VIKOR و COPRAS و زیر آبخیز S14 بر اساس روش SAW در اولویت آخر قرار گرفتند. ارزیابی کارایی روش‌های MCDM نشان داد روش VIKOR با کمترین شدت تغییرات، نتایج دقیق‌تری را ارائه داده است.

کلیدواژه‌ها

موضوعات


  1. [1] Flotemersch JE, Leibowitz SG, Hill RA, Stoddard JL, Thoms MC, Tharme RE. A watershed integrity

    definition and assessment approach to support strategic management of watersheds. River Research and

    Applications. 2016;32(7):1654-71.

    [2] Sadeghi S. H, Adhami M, Sheikhmohammadi M. Introduction and Applicability of Game Theory in

    Watershed CoManagement. Extension and Development of Watershed Management, 2018; 6(20): 1-8.

    [Persian]

    [3] Pal S, Debanshi S. Developing wetland landscape insecurity and hydrological security models and measuring

    their spatial linkages. Ecological Informatics. 2021; 1(66):101461.

    [4] Li S, Liu H. Spatio-temporal pattern evolution of coupling coordination between urbanization and ecological

    resilience in arid region: A case of Ningxia Hui Autonomous Region. Arid Land Geography. 2022; 45(4).

    [5] Salvati L, Bajocco S. Land sensitivity to desertification across Italy: past, present, and future. Applied

    geography. 2011 1;31(1):223-31.

    [6] Carpenter S, Walker B, Anderies JM, Abel N. From metaphor to measurement: resilience of what to what?.

    Ecosystems. 2001; 4(8): 65-81.

    [7] Khosravi G, Sadodin A, Ownegh M, Bahremand A, Mostafavi H. Classification and identification of changes

    in river flow regime using the Indicators of Hydrologic Alteration (IHA) Case study: (The Khormarud River-

    Tilabad Watershed- Golestan Province). Iranian Journal of Ecohydrology, 2019; 6(3): 651-671. [Persian]

    [8] Kundzewicz ZW, Matczak PI. Hydrological extremes and security. Proceedings of the International

    Association of Hydrological Sciences. 2015; 10(366): 44-53.

    [9] Gandri L, Bana S. Conservation Strategy Analysis in Upstream Watershead: Case Study in Cimandiri

    Watershead. Jurnal Ecosolum. 2021; 16(1):33-48.

    [10] Lee CS. Multi-objective game-theory models for conflict analysis in reservoir watershed management.

    Chemosphere. 2012; 87(6): 8-13.

    [11] Skardi MJ, Afshar A, Solis SS. Simulation-optimization model for non-point source pollution management in

    watersheds: Application of cooperative game theory. KSCE Journal of Civil Engineering. 2013; 17(6): 32-40.

    [12] Mir MA, Ghazvinei PT, Sulaiman NM, Basri NE, Saheri S, Mahmood NZ, Jahan A, Begum RA,

    Aghamohammadi NJ. Application of TOPSIS and VIKOR improved versions in a multi criteria decision

    analysis to develop an optimized municipal solid waste management model. Journal of Environmental

    Management. 2016; 15(166): 109-15.

    [13] Akbari M, Meshram SG, Krishna RS, Pradhan B, Shadeed S, Khedher KM, Sepehri M, Ildoromi AR,

    Alimerzaei F, Darabi F. Identification of the groundwater potential recharge zones using MCDM models: full

    consistency method (FUCOM), best worst method (BWM) and analytic hierarchy process (AHP). Water

    Resources Management. 2021; 35(47): 27-45.

    [14] Chang CL, Hsu CH. Multi-criteria analysis via the VIKOR method for prioritizing land-use restraint

    strategies in the Tseng-Wen reservoir watershed. Journal of Environmental Management. 2009; 90(11): 26-30.

    [15] Chang CL, Lin YT. Using the VIKOR method to evaluate the design of a water quality monitoring network

    in a watershed. International Journal of Environmental Science and Technology. 2014; 2(11):10-30.

    [16] Dong J, Huo H, Liu D, Li R. Evaluating the comprehensive performance of demand response for commercial

    customers by applying combination weighting techniques and fuzzy VIKOR approach. Sustainability. 2017;

    9(8):1332.

    [17] Malekian A, Azarnivand A. Application of integrated Shannon’s entropy and VIKOR techniques in

    prioritization of flood risk in the Shemshak watershed, Iran. Water Resources Management. 2016; 30(1): 9-25.

    [18] Meshram SG, Singh VP, Kahya E, Alvandi E, Meshram C, Sharma SK. The feasibility of multi-criteria

    decision-making approach for prioritization of sensitive area at risk of water erosion. Water Resources

    Management. 2020; 34(15): 65-85.

    [19] Meshram SG, Adhami M, Kisi O, Meshram C, Duc PA, Khedher KM. Identification of critical watershed for

    soil conservation using Game Theory-based approaches. Water Resources Management. 2021; 35(10): 5-20.

    [20] Meshram SG, Singh VP, Kahya E, Sepehri M, Meshram C, Hasan MA, Islam S, Duc PA. Assessing erosion

    prone areas in a watershed using interval rough-analytical hierarchy process (IR-AHP) and fuzzy logic (FL).

    Stochastic Environmental Research and Risk Assessment. 2022; 36(2):1-6.

    [21] Mulliner E, Malys N, Maliene V. Comparative analysis of MCDM methods for the assessment of sustainable

    housing affordability. Omega. 2016; 59: 46-56.

    [22] Nguyen NM, Bahramloo R, Sadeghian J, Sepehri M, Nazaripouya H, Nguyen Dinh V, Ghahramani A, Talebi

    A, Elkhrachy I, Pande CB, Meshram SG. Ranking sub-watersheds for flood hazard mapping: A multi-criteria

    decision-making approach. Water. 2023; 15(11):2128.

    [23] Jalali A, Nagesh Kumar D, Srinivasa Raju K. Prioritization of sub-catchments of a river basin using DEM

    and fuzzy VIKOR. Indian Academy of Science. 2018; 1(1):1-11.

    [24] Salehi A, Izadikhah M. A novel method to extend SAW for decision-making problems with interval data.

    Decision Science Letters. 2014; 3(2):22-36.

    [25] Shih HS, Shyur HJ, Lee ES. An extension of TOPSIS for group decision making. Mathematical and

    Computer Modelling. 2007; 45(7-8): 1-13.

    [26] Yu X, Zhang S, Liao X, Qi X. ELECTRE methods in prioritized MCDM environment. Information Sciences.

    2018; 424: 1-16.

    [27] Mahmoodi E, Azari M, Dastorani MT. Comparison of different objective weighting methods in a multi­

    criteria model for watershed prioritization for flood risk assessment using morphometric analysis. Journal of

    Flood Risk Management. 2023; 16(2):e12894.

    [28] Nasiri Khiavi A, Vafakhah M, Sadeghi SH. Flood-based critical sub-watershed mapping: comparative

    application of multi-criteria decision-making methods and hydrological modeling approach. Stochastic

    Environmental Research and Risk Assessment. 2023; 37(7): 57-75.

    [29] Nasiri Khiavi A, Mostafazadeh R, Ghanbari Talouki F. Using game theory algorithm to identify critical

    watersheds based on environmental flow components and hydrological indicators. Environment, Development

    and Sustainability. 2024; 9:1-24.

    [30] Sahraei R, Kanani Sadat Y, Homayouni S, Safari A, Oubennaceur K, Chokmani K. A novel hybrid GIS­

    based multi criteria decision making approach for flood susceptibility analysis in large ungauged watersheds.

    Journal of Flood Risk Management. 2023; 16(2):e12879.

    [31] Sarkar P, Sarma US, Gayen SK. Prioritization of sub-watersheds of Teesta River according to soil erosion

    susceptibility using multi-criteria decision-making in Sikkim and West Bengal. Arabian Journal of

    Geosciences. 2023;16(6):398.

    [32] Sepehri M, Linh NT, Pouya HN, Bahramloo R, Sadeghian J, Ghermezcheshme B, Talebi A, Peyrovan H,

    Thanh PN. Developing a new multi-criteria decision-making for flood prioritization of sub-watersheds using

    concept of D numbers. Acta Geophysica. 2023; 12:1-3.

    [33] Nie RX, Tian ZP, Wang JQ, Zhang HY, Wang TL. Water security sustainability evaluation: Applying a

    multistage decision support framework in industrial region. Journal of Cleaner Production. 2018; 20(196):70-

    81.

    [34] Tu Y, Wang H, Zhou X, Shen W, Lev B. Comprehensive evaluation of security, equity, and efficiency on

    regional water resources coordination using a hybrid multi-criteria decision-making method with different

    hesitant fuzzy linguistic term sets. Journal of Cleaner Production. 2021; 310: 27-44.

    [35] Yu H, Gu X, Liu G, Fan X, Zhao Q, Zhang Q. Construction of regional ecological security patterns based on

    multi-criteria decision making and circuit theory. Remote Sensing. 2022; 14(3):527.

    [36] Khazaei Fizabad A, Pourreza Bilondi M. Identifying areas with underground water potential using multi-

    criteria decision-making models, AHP and ANP (case study: Naiband-Tabas Plain). Iranian Journal of

    Irrigation & Drainage, 2024; 17(5): 917-929. [Persian]

    [37] Nasiri Khiavi Ali, Mostafazadeh Raoof, Esmali Ouri Abazar, Ghafarzadeh Omid, Golshan Mohammad.

    Alteration of hydrologic flow indicators in Ardabil Balikhlouchai River under combined effects of change in

    climatic variables and Yamchi Dam construction using Range of Variability Approach. Watershed Engineering

    and Management. 2020;11(4 ):851-865. [Persian]

    [38] Daechini F, Vafakhah M, Moosavi V, Silabi MZ. Performance assessment of five water balance models for

    runoff simulation in the Gorganrood watershed. JWSS-Journal of Water and Soil Science 2022; 26 (2) :263-

    1. [Persian]

    [39] Chen YD, Yang T, Xu CY, Zhang Q, Chen X, Hao ZC. Hydrologic alteration along the Middle and Upper

    East River (Dongjiang) basin, South China: a visually enhanced mining on the results of RVA method.

    Stochastic Environmental Research and Risk Assessment. 2010; 24(1): 9-18.

    [40] Hanifinia A, Nazarnejad H, Najafi S, Kornejady A. K. Landslide Hazard Mapping Using AHP and Shannon

    Entropy Models in Cherikabad of Urmia Watershed. Applied Soil Research, 2022; 10(3): 130-144. [Persian]

    [41] Yufeng S, Fengxiang J. Landslide stability analysis based on generalized information entropy. In2009

    International Conference on Environmental Science and Information Application Technology 2009; 4(2): 83-85.

    [42] Chen SJ, Hwang CL. Fuzzy multiple attribute decision making methods. InFuzzy multiple attribute decision

    making: Methods and applications. Berlin, Heidelberg: Springer Berlin Heidelberg. 1992.

    [43] Opricovic S. Multicriteria optimization of civil engineering systems. Faculty of Civil Engineering, Belgrade.

    1998; 2(1):5-21.

    [44] Widianta MM, Rizaldi T, Setyohadi DP, Riskiawan HY. Comparison of multi-criteria decision support

    methods (AHP, TOPSIS, SAW & PROMENTHEE) for employee placement. Journal of Physics: Conference

    Series 2018; 1: 953.

    [45] Vytautas B, Marija B, Vytautas P. Assessment of neglected areas in Vilnius city using MCDM and COPRAS

    methods. Procedia Engineering. 2015; 122: 29-38.

    [46] Setayeshi Nasaz H, Asghari Saraskanrood S, Mostafazadeh R, Madadi A. Investigating changes in the

    hydrological flow regime and the environmental flow component of EFCs in Khiauchai River in a 30-year

    period. Hydrogeomorphology, 2023; 10(37): 43-25. [Persian]

    [47] Tajbakhsh Fakhrabadi S. M, Chezgi J. Effect of morphometric factors in prioritizing flooding of sub-

    watersheds in the north of Birjand Plain. Water and Soil Management and Modelling, 2022; 3(3): 240-255. [Persian]

دوره 11، شماره 2
تیر 1403
صفحه 193-206
  • تاریخ دریافت: 21 فروردین 1403
  • تاریخ بازنگری: 07 خرداد 1403
  • تاریخ پذیرش: 15 خرداد 1403
  • تاریخ اولین انتشار: 01 مرداد 1403
  • تاریخ انتشار: 01 مرداد 1403