مدیریت تلفیقی منابع آبی در محدوده حوضه آبریز دشت یزد-اردکان با تاکید بر پایداری زیست‎محیطی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری / آبخیزداری دانشکده منابع طبیعی دانشگاه یزد و مربی دانشکده کشاورزی دانشگاه پیام نور

2 دانشیار / گروه مرتع و آبخیزداری دانشکده منابع طبیعی دانشگاه یزد

3 استاد/ دانشگاه شهید باهنر کرمان، دانشکده ریاضی و کامپیوتر، بخش ریاضی کاربردی

چکیده

با توجه به محدودیت منابع آبی، افزایش روزافزون نیاز به این منابع در همه زمینه‎ها و نیز تاثیر تغییرات اقلیمی بر منابع آبی، مدیریت بهینه منابع آبی و استفاده کارآمد از آن‎ها امری ضروری است. لازمه دست‎یابی به مدیریت بهینه، استفاده از تکنیک‎های مناسب بهینه‎سازی می‎باشد. در تحقیق حاضر که در محدوده حوضه آبریز دشت یزد-اردکان انجام گرفت، تکنیک‎های مختلف بهینه‎سازی شامل الگوریتم ژنتیک و الگوریتم ژنتیک چندهدفه مبتنی بر جواب غیر پست (NSGAП)، مورد استفاده قرار گرفتند. منابع آبی آبخوان زیرزمینی و آب انتقالی به‎صورت تلفیقی در نظر گرفته شد. اهداف مورد نظر عبارت بودند از حداکثر نمودن سود اقتصادی حاصل از برداشت آّب با توجه به جنبه‎های کیفی پایداری آبخوان، حداقل نمودن عدم تامین نیاز کاربران و تعادل بخشی آبخوان. به منظور دسترسی به مقدار آب قابل برداشت آبخوان زیرزمینی از مدل مادفلو برای شبیه‎سازی آبخوان استفاده شد و بیلان آبی در گام‎های زمانی ماهانه به‎دست آمد. نتایج نشان داد الگوریتم ژنتیک NSGAП، توانایی بیشتری در تخصیص بهینه منابع آبی منطقه دارد. در ضمن چنان‎چه به‎جای استفاده از ذخیره قابل برداشت هر ماه، از مجموع ذخایر قابل برداشت سالانه سفره، استفاده شود، نتایج بهتری به‎دست می‎آید.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Conjunctive Water Resources Management with Emphasis on Environmental Sustainability in Yazd-Ardakan Basin

نویسندگان [English]

  • F. Barzegari Banadkooki 1
  • H. Malekinezhad 2
  • M.M. Hosseini 3
1 Ph.D. Candidate of Watershed Management, Department of Watershed and Rangeland Engineering, Faculty of Natural Resources, Yazd University and Faculty Member, Department of Agriculture, Payamnoor University, Yazd, Iran
2 Associate Professor, Faculty of Natural Resources, Yazd University, Yazd, Iran.
3 Professor, Department of Applied Mathematics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran.
چکیده [English]

Due to some factors such as limitations in water resources, increasing needs in these resources in all aspects and also the impact of climate changes on these resources, the optimal management of water resources and efficient use of them is an essential task. To achieve this optimal management, appropriate optimization techniques can be utilized. In this paper, a multi objective model is developed for conjunctive use of ground water and transitive water in Yazd-Ardakan basin. To attain this, optimization approaches including Genetic algorithm (GA) based on penalty function and non-dominated sorting genetic algorithm (NSGA II), were used. Three objective functions were developed including, maximizing economic income obtained from water resources considering qualitative aspects the aquifer sustainability, minimizing failure in water supply and balancing aquifer storage. 3-D analysis Mod flow model served to simulate ground water aquifer. The monthly water budget was extracted using 3-D analysis Mod flow model. The findings indicated that NSGA II is prior to GA in optimizing water allocation model. On the other hand, using annual renewable ground water storage, considered in water allocation, instead of using monthly renewable ground water storage resulted in better allocation model performance.

کلیدواژه‌ها [English]

  • optimization
  • Genetic algorithm
  • Water Resources Management
  • Mod Flow
  • Environmental Sustainability
Asadi R, Malekinezhad H, Fatahi A (2015) Optimization of land use based on water resources by using linear programming (Case study: Yazd city). Journal of Water Management in Arid Lands 1(2): 11-26 (In Persian)

Azaiez MN (2002) A model for conjunctive use of ground and surface water with opportunity costs. European Journal of Operational Research 143:611-624

Barlow PM, Ahlfeld DP, Dickerman DC (2003) Conjunctive-management models for sustained yield of stream-aquifer systems. Journal of Water Resources Planning and Management 129(1):35-48

Buras N (1963) Conjunctive operation of dams and aquifers. Journal of the Hydraulics Division 89(6):111-132

Chang LC, Ho CC, Chen YW (2009) Applying multi objective genetic algorithm to analyze the conflict among different water use sectors during drought period. Journal of Water Resources Plan Management 136 (5):539–546

Coe Jack J (1990) Conjunctive use-advantages, constraints, and examples. Journal of Irrigation and Drainage Engineering 116(3):427-443

Dale Larry L, Vicuna S, Dracup JA (2008) The conjunctive use of reservoirs and aquifers: Tradeoffs in electricity generation and water supply.” Proceedings of the World Environmental and Water Resources Congress, Honolulu, Hawaii

Deb K, Agrawal S, Pratap A, Meyarivan T (2000) A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In Parallel problem solving from nature PPSN VI (849-858). Springer Berlin Heidelberg

Dogrul EC, Kadir TN, Brush C F, Chung FI (2016) Linking groundwater simulation and reservoir system analysis models: The case for California’s Central Valley. Environmental Modeling and Software77:168-182

Emch PG, Yeh WG (1998) Management model for conjunctive use of coastal surface water and groundwater. Journal of Water Resources Planning and Management 124(3):129-139

Goldberg DE (1989) Genetic algorithms in search, optimization and machine learning. Addison-Wesley, Reading Menlo Park: Addison-wesley

Gracheva I, Karimov A, Turral H, Miryusupov F (2009) An assessment of the potential and impacts of winter water banking in the Sokh aquifer. Central Asia. Hydrogeology Journal.17 (6):1471-1482

Holland JH (1975) Adaptation in natural and artificial systems,” University of Michigan Press Annarbor, Cam-bridge Mass

Hamshari Newspaper (2014) Factory resistance from connection to industrial state refinery (In Persian)

Jyrkama MI, Sykes JF, Normani SD (2002) Recharge estimation for transient ground water modeling. Journal of Groundwater, 40:638–648

Karamouz M, Kerachian R, Zahraie B (2004) Monthly water resources and irrigation planning: Case study of conjunctive use of surface and ground water resources. Journal of Irrigation and Drainage Engineering 130 (5):391-402

Karimi A, Nikoo MR, Kerachian R, and Mokhtarpour A (2014) Long-term conjunctive use of surface and ground water resources at basin scale considering water quality constraints (Case study: Zayandehrud watershed), Iranian Journal of Water Research, 14(8):97-108 (In Persian)

Kim NW, Chung IM, Won YS, Arnold JG (2008) Development and application of the integrated SWAT–MODFLOW model. Journal of  Hydrology 356:1–16

Kim Y, Chung ES (2013) Assessing climate change vulnerability with group multi criteria decision making approaches. Journal of Climatic change121 (2):301–315

Latif M (1991) Conjunctive water use to control water logging and stalinization. Journal of Water Resources Planning and Management, 117(6):611-628

Moghaddasi M, Morid S, Araghinejad Sh (2009) Optimization of water allocation during water scarcity condition using non-linear programming, genetic algorithm and particle swarm optimization (Case study). Iran-Water Resources Research 4(3):1-13. (In Persian)

Mohammad Rezapour Tabari M, Maknoon R., Ebadi E (2009) Multi-objective optimal model for conjunctive use management using SGAs and NSGA-II models. Journal of Water and Wastewater 69: 2-12 (In Persian)

Mohammad Rezapour Tabari M, Maknoon R., Ebadi E (2012) Development structure for optimal long-term planning in conjunctive use. Journal of Water and Wastewater 4:56-69 (In Persian)

Parsapour-Moghaddam P, Abed-Elmdoust A, and Kerachian R (2015). A Heuristic evolutionary game theoretic methodology for conjunctive use of surface and ground water resources. Journal of  Water Resources Management, 29(11):3905-3918

Pulido-Velázquez M, Andreu J, and Sahuquillo A (2006) Economic optimization of conjunctive use of surface water and groundwater at the basin scale. Journal of Water Resources Planning and Management 132 (6):454-467

Regulwar DG, Anand Raj P (2008)Development of 3-D optimal surface for operation policies of a multireservoir in fuzzy environment using genetic algorithm for river basin development and management. Journal of Water Resources Planning and Management. 22:595–610

Saber Chenari K, Abghari H, Erfanian M, Gholizadeh S (2013) Short-term model of optimization operation of water resources using particle swarm optimization and compared with genetic algorithm. Journal of Watershed Management Research (Pajouhesh & Sazandegi) 97:63-72. (In Persian)

Scherberg J, Baker T, Selker J, Henry R (2014) Design of managed aquifer recharge for agricultural and ecological water supply assessed through numerical modeling. Journal of Water Resources Management28 (14):4971-4984

Scibek J, Allen DM (2006) Modeled impacts of predicted climate change on recharge and groundwater levels. Water Resources Research 42(11):1-18

Shourian M, Mousavi SJ, Tahershamsi A (2008) Basin-wide water resources planning by integrating PSO algorithm and MODSIM. Journal of Water Resources Management 22 (10):1347–1366

Statistical Center of Iran, statistical yearbook from 2001-2011.(In Persian)

Valerio A, Rajaram H, Zagona E (2010) Incorporating groundwater-surface water interaction into river management models. Groundwater 48 (5):661-673.

Wang H, Gao JE, Zhang MJ, Li XH, Zhang SL, Jia LZ (2015) Effects of rainfall intensity on groundwater recharge based on simulated rainfall experiments and a groundwater flow model. Catena 127:80-91

Xuan W, Quan C, and Shuyi L (2012) An optimal water allocation model based on water resources security assessment and its application in Zhangjiakou Region, Northern China. Resources, Conservation and Recycling, 69:57-65

Yazd Regional Water Organization (2015). Statistics and information.(In Persian)

Zhang H, Hiscock KM (2010) Modeling the impact of forest cover on groundwater resources: A case study of the Sherwood Sandstone aquifer in the East Midlands, UK. Journal of Hydrology 392:136–149