Skip to main content

Advertisement

Log in

Multi-Objective Optimization of Integrated Surface and Groundwater Resources Under the Clean Development Mechanism

  • Published:
Water Resources Management Aims and scope Submit manuscript

Abstract

Acquiring sustainable water resources for water-based development of countries is the experts҆ concern in this field, who seek to follow the clean development mechanism (CDM) regulations and overcome water crisis through integrated water resources management (IWRM). The Great Karun River basin is one of the major basins in the Middle East. This basin, containing six of the largest reservoir dams with a cumulative power plant capacity of more than 10,500 MW generates about 93% of hydropower of Iran. The water balance of the aquifer in the study area was simulated using MODFLOW model while water resources and surface water reserves were simulated by the water evaluation and planning (WEAP) model. A separate simulation was performed with each of two models and the results of two models were coupled using a link file. The multi-objective function optimization process including the maximized supply of demands and hydropower and the minimized aquifer drawdown was completed using non-dominated sorting genetic algorithm (NSGA-II). All effective system components, such as inter-basin water transfer, integrated use of water resources, variation of irrigation network efficiencies, and the effect of water shortage were studied and analyzed under the targeted scenarios. Finally, the best scenario, which was capable to supply the future needs until time horizon of 2040 was planned for the basin considering minimization of aquifer drawdown and optimal generation of hydropower resulting in a maximum decrease in emission of greenhouse gases.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data Availability

The total data and materials are available for applicants if needed.

References

  • Amponsah NY, Troldborg M, Kington B, Aalders I, Hough RL (2014) Greenhouse gas emissions from renewable energy sources: A review of lifecycle considerations. Renewable and Sustainable Energy Rev 39:461–475

    Article  Google Scholar 

  • Anderson MP, Woessner WW, Hunt R (2015) Applied Groundwater Modeling. Academic Press, Cambridge, MA, Simulation of Flow and Advective Transport

    Google Scholar 

  • Anugrah P, Setiawan AA, Budiarto R, Sihana S (2015) Evaluating micro hydro power generation system under climate change scenario in Bayang Catchment, Kabupaten Pesisir Selatan, West Sumatra. Energy Procedia 65:257–263

    Article  Google Scholar 

  • Assaf H, Saadeh M (2008) Assessing water quality management options in the Upper Litani Basin, Lebanon, using an integrated GIS-based decision support system. Environ Modell Software 23(10–11):1327–1337

    Article  Google Scholar 

  • World Nuclear Association (2011) Comparison of Lifecycle Greenhouse Gas Emissions of Various Electricity Generation Sources. www.world-nuclear.org

  • Bharati L, Rodgers C, Erdenberger T, Plotnikova M, Shumilov S, Vlek P, Martin N (2008) Integration of economic and hydrologic models: exploring conjunctive irrigation water use strategies in the Volta Basin. Agric Water Manage 95(8):925–936

    Article  Google Scholar 

  • Bear J, Cheng AHD (2010) Modeling groundwater flow and contaminant transport (Vol. 23). Springer Science & Business Media

  • Chang LC, Chang FJ (2009) Multi-objective evolutionary algorithm for operating parallel reservoir system. J Hydro 377(1–2):12–20

    Article  Google Scholar 

  • Chenini I, Mammou AB (2010) Groundwater recharge study in arid region: an approach using GIS techniques and numerical modeling. Comput Geosci 36(6):801–817

    Article  Google Scholar 

  • Coello CAC (1999) A comprehensive survey of evolutionary-based multiobjective optimization techniques. Knowl Inf Syst 1(3):269–308

    Article  Google Scholar 

  • Cohen G (1978) Optimization by decomposition and coordination: A unified approach. IEEE Trans Autom Control 23(2):222–232

    Article  Google Scholar 

  • Copenhagen Accord (2009) Report of the Conference of the Parties on its fifteenth session, held in Copenhagen from 7 to 19 December 2009. United Nations Framework Convention on Climate Change

  • Dalir F, Shafiepour Motlagh M, Ashrafi K (2017) A well to wire LCA model development and sensitivity analysis for carbon footprint of combined cycle power plants in Iranian electricity network. Int J Green Energy 14(5):499–508

    Article  Google Scholar 

  • Deb K, Pratap A, Agarwal S, Meyarivan TAMT (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197

    Article  Google Scholar 

  • Droogers P, Butterfield R, Dyszynski J (2009) Climate change and hydropower, impact and adaptation costs: case study Kenya. FutureWater Report, 85

  • Ercan MB, Goodall JL (2016) Design and implementation of a general software library for using NSGA-II with SWAT for multi-objective model calibration. Environ Modell Software 84:112–120

    Article  Google Scholar 

  • Fu G, Butler D, Khu ST (2008) Multiple objective optimal control of integrated urban wastewater systems. Environ Modell Software 23(2):225–234

    Article  Google Scholar 

  • Gambolati G, Pini G, Verri G (1989) Simulation of regional subsurface flow by finite element models. Adv Water Resour 12(2):59–65

    Article  Google Scholar 

  • Hadded R, Nouiri I, Alshihabi O, Maßmann J, Huber M, Laghouane A, Yahiaoui H, Tarhouni J (2013) A decision support system to manage the groundwater of the zeuss koutine aquifer using the WEAP-MODFLOW framework. Water Resour Manage 27(7):1981–2000

    Article  Google Scholar 

  • International Hydropower Association (IHA) (2016) International Hydropower Association Sustainability Guidelines. International Hydropower Association, London

    Google Scholar 

  • Jiao R, Zeng S, Li C, Yang S, Ong YS (2020) Handling constrained many-objective optimization problems via problem transformation. IEEE Trans Cybern

  • Jones BA, Ripberger J, Jenkins-Smith H, Silva C (2017) Estimating willingness to pay for greenhouse gas emission reductions provided by hydropower using the contingent valuation method. Energy Policy 111:362–370

    Article  Google Scholar 

  • Ma Q, Abily M, Du M, Gourbesville P, Fouché O (2020) Integrated Groundwater Resources Management: Spatially-Nested Modelling Approach for Water Cycle Simulation. Water Resour Manage 34(4):1319–1333

    Article  Google Scholar 

  • Maier HR, Razavi S, Kapelan Z, Matott LS, Kasprzyk J, Tolson BA (2019) Introductory overview: Optimization using evolutionary algorithms and other metaheuristics. Environ Modell Software 114:195–213

    Article  Google Scholar 

  • Mansoor U, Kessentini M, Langer P, Wimmer M, Bechikh S, Deb K (2015) MOMM: Multi-objective model merging. J Syst Software 103:423–439

    Article  Google Scholar 

  • Mugatsia EA (2010) Simulation and scenario analysis of water resources management in Perkerra catchment using WEAP model. Dissertation, university of Moi

  • Naghdi S, Bozorg-Haddad O, Khorsandi M, Chu X (2021) Multi-objective optimization for allocation of surface water and groundwater resources. Sci Total Environ 776:146026

    Article  Google Scholar 

  • Poblete D, Vicuña S, Meza F, Bustos E (2012) Water resources modeling under Climate Change scenarios of Maule River Basin (Chile) with two main water intensive and competing sectors: Agriculture and Hydropower Generation. In IWA World Congress on Water, Climate and Energy

  • Raadal HL, Gagnon L, Modahl IS, Hanssen OJ (2011) Life cycle greenhouse gas (GHG) emissions from the generation of wind and hydro power. Renewable Sustainable Energy Rev 15(7):3417–3422

    Article  Google Scholar 

  • Sieber J, Swartz C, Huber-Lee AH (2005) Water evaluation and planning system (WEAP): User guide. Stockholm Environment Institute, Boston

    Google Scholar 

  • Song J, Yang Y, Sun X, Lin J, Wu M, Wu J, Wu J (2020) Basin-scale multi-objective simulation-optimization modeling for conjunctive use of surface water and groundwater in northwest China. Hydrol Earth Syst Sci 24(5):2323–2341

    Article  Google Scholar 

  • Tang L, Liu J, Rong A, Yang Z (2002) Modelling and a genetic algorithm solution for the slab stack shuffling problem when implementing steel rolling schedules. Int J Prod Res 40(7):1583–1595

    Article  Google Scholar 

  • Weisser D (2007) A guide to life-cycle greenhouse gas (GHG) emissions from electric supply technologies. Energy 32(9):1543–1559

    Article  Google Scholar 

  • Young G, Shah B, Kimaite F (2008) UN Water Report. Status report on integrated water resources management and water efficiency plans

  • Zucker MB, Remson I, Janet E, Aguado E (1973) Hydrologic studies using the Boussinesq equation with recharge term. Water Resour Res 9(3):586–592

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank the Khuzestan Water and Power Authority (KWPA) and the management of the Office of Applied Research for financial support for this research. Also, the authors would like to thank the deputy of Basic Studies of KWPA for providing the data.

Funding

Partial financial support was received from Khuzestan Water and Power Authority (KWPA).

Author information

Authors and Affiliations

Authors

Contributions

All authors with names Hamidreza Majedi, Hossein Fathian, Alireza Nikbakht-Shahbazi, Narges Zohrabi and Fatemeh Hassani have contributed to this article.

Corresponding author

Correspondence to Hossein Fathian.

Ethics declarations

Ethical Approval

The authors approve principles of ethical and professional conduct.

Consent to Participate

The authors consent to participate in the preparation of this article.

Consent to Publish

The authors consent to publish this article in journal of Water Resources Management.

Competing Interests

All authors have the same interest in this article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Majedi, H., Fathian, H., Nikbakht-Shahbazi, A. et al. Multi-Objective Optimization of Integrated Surface and Groundwater Resources Under the Clean Development Mechanism. Water Resour Manage 35, 2685–2704 (2021). https://doi.org/10.1007/s11269-021-02860-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11269-021-02860-0

Keywords

Navigation