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Multi-objective Optimization Tool for Integrated Groundwater Management

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Abstract

Integrated water resources management requires demands from agriculture, industry, and domestic users be met with the available supply with full considerations to water quality, cost and the environment. Thus, optimal allocation of available water resources is the challenge faced by water managers and policy makers to meet demands. With this in mind, a new tool called ALL_WATER_gw was developed for groundwater management within the framework of the WEAP-MODFLOW Decision Support System. It takes into account satisfaction of demand, minimization of water cost and maximal drawdown, as well as meeting water salinity restrictions. A Multi-Objective Genetic Algorithm (MOGA) and the PARETO optimality approaches were used to handle the formulated problem. Sensitivity analysis based on a pilot study showed that the MOGA parameters have strong impacts on the efficiency and the robustness of the developed tool. The results also demonstrated the tool’s capabilities to identify optimal solutions and support groundwater management decisions.

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References

  • Ayvaz TM (2009) Application of harmony search algorithm to the solution of groundwater management models. Adv Water Resour 32:916–924

    Article  Google Scholar 

  • Back T, Fogel DB, Michalewicz T (2000) Evolutionary computation 1: basic algorithms and operators. Institute of Physics Publishing, United Kingdom

    Book  Google Scholar 

  • Bates BC, Kundzewicz ZW, Wu S, Palutikof JP (eds) (2008) Climate change and water. Technical paper of the intergovernmental panel on climate change. IPCC Secretariat, Geneva, 210 pp

    Google Scholar 

  • Chang LC (2008) Guiding rational reservoir flood operation using penalty-type genetic algorithm. J Hydrol 354:65–74

    Article  Google Scholar 

  • Coelho AC, Labadie JW, Fontane DG (2012) Multicriteria decision support system for regionalization of integrated water resources management. Water Resour Manag 26:1325–1346

    Article  Google Scholar 

  • Deb K, Agrawal S, Pratap A, Meyarivan T (2000) A fast Non-dominated genetic algorithm for multi-objective optimisation : NSGA-II. KanGAL report No. 200001. Indian Institute of Technology, Kanpur

    Google Scholar 

  • Droubi A, Al-Sibai M, Abdallah A, Zahra S, Obeissi M, Wolfer J, Huber M, Hennings V, Schelkes KA (2008) Decision support system (DSS) for water resources management, −design and results from a pilot study in Syria. In: Zereini F, Hötzl H (Eds.): Climatic changes and water resources in the middle east and north africa. Springer, p 199–225

  • Esquivel S, Leiva HA, Gallard RH (1999) Multiplicity in genetic algorithms to face multicriteria optimization. In: Congress on evolutionary computation. IEEE Service Centre, Washington

    Google Scholar 

  • Fonseca CR, Esteller MV, Díaz-Delgado C (2013) Territorial approach to increased energy consumption of water extraction from depletion of a highlands Mexican aquifer. J Environ Manag 128(2013):920–930

    Article  Google Scholar 

  • Fu G (2008) A fuzzy optimization method for multicriteria decision making: an application to reservoir flood control operation. Expert Syst Appl 34:145–149

    Article  Google Scholar 

  • Gholami V, Yousefi Z, Rostami HZ (2010) Modeling of ground water salinity on the Caspian southern coasts. Water Resour Manag 24:1415–1424

    Article  Google Scholar 

  • Giupponi C (2007) Decision support systems for implementing the european water framework directive: the MULINO approach. Environ Model Softw 22:248–258

    Article  Google Scholar 

  • Goldberg DE (1991) Genetic algorithms. Addison-Wesley

  • GWP - Global Water Partnership (2000) TAC background papers No. 4. Integrated Water Resources Management, GWP, Denmark

    Google Scholar 

  • Haddad 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 Manag 27:1981–2000. doi:10.1007/s11269-013-0266-7

    Article  Google Scholar 

  • Harbaugh AW (2005) MODFLOW-2005, the U.S. geological survey modular

  • IPCC (2013) Summary for policymakers. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge and New York

    Google Scholar 

  • Khare D, Jat MK, Deva SV (2007) Assessment of water resources allocation options: conjunctive use planning in a link canal command. Resour Conserv Recycl 51:487–506

    Article  Google Scholar 

  • Knowles J, Corne D (1999) The pareto archived evolution strategy: a new baseline algorithm for pareto multiobjective optimisation. Proceedings of the 1999 congress on evolutionary computation (CEC'99). Volume 1, 98–105

  • Koutsoyiannis D, Karavokiros G, Efstratiadis A, Mamassis N, Koukouvinos A, Christofides A (2003) A decision support system for the management of the water resource system of Athens. Phys Chem Earth, Parts A B C 28:599–609

    Article  Google Scholar 

  • Leiva HA, Esquivel SC, Gallard RH (2000) Miltiplicity and local search in, evolutionary algorithms to build the pareto front. Proceedings of the XX international conf. of the chilean computer science society (SCCC’00). 0-7695-0810-1/00. IEEE Service Centre

  • Letcher RA, Croke BFW, Jakeman AJ (2007) Integrated assessment modelling for water resource allocation and management: a generalised conceptual framework. Environ Model Softw 22:733–742

    Article  Google Scholar 

  • Li YP, Huang GH, Nie SL, Liu L (2007) Inexact multistage stochastic integer programming for water resources management under uncertainty. J Environ Manag 88:93–107

    Article  Google Scholar 

  • Lis J, Eiben AE (1997) Multi-sexual genetic algorithm for multiobjective optimization. 4thInternational conf. on evolutionary computation (ICEC’97). Indiapolis, USA, p 59–64

  • Liu S, Gikas P, Papageorgiou LG (2010) An optimisation-based approach for integrated water resources management. Comput Aided Chem Eng 28:1075–1080

    Article  Google Scholar 

  • Maßmann J, Wolfer J, Huber M, Schelkes K, Hennings V, Droubi A, Al-Sibai M (2012) WEAP-MODFLOW as a decision support system (DSS) for integrated water resources management: Design of the coupled model and results from a pilot study in Syria. In: Maloszewski P, Witczak S, Malina G (eds.): Groundwater quality sustainability. IAH selected papers. CRC Press

  • Mongelli G, Monni S, Oggiano G, Paternoster M, Sinisi R (2013) Tracing groundwater salinization processes in coastal aquifers: a hydrogeochemical and isotopic approach in the Na-Cl brackish waters of northwestern Sardinia. Italy Hydrol Earth Syst Sci 17:2917–2928

    Article  Google Scholar 

  • Moradi-Jalal M, Haddad OB, Karney BW, Marin MA (2007) Reservoir operation in assigning optimal multi-crop irrigation areas. Agric Water Manag 90:149–159

    Article  Google Scholar 

  • Mysiak J, Giupponi C, Rosato P (2005) Towards the development of a decision support system for water resource management. Environ Model Softw 20:203–214

    Article  Google Scholar 

  • Nouiri I (2011) ALL_WATER_gw user guide, 37 p

  • Nouiri I (2014) Multi-objective tool to optimize the water resources management using genetic algorithm and the pareto optimality concept. Water Resour Manag 28:2885–290

    Article  Google Scholar 

  • Pahl-Wostl C (2007) The implications of complexity for integrated resources management. Environ Model Softw 22:561–569

    Article  Google Scholar 

  • Prato T, Herath G (2007) Multiple-criteria decision analysis for integrated catchment management. Ecol Econ 63:627–632

    Article  Google Scholar 

  • Rees HG, Holmes MGR, Fry MJ, Young AR, Pitson DG, Kansakar SR (2006) An integrated water resource management tool for the Himalayan region. Environ Model Softw 21:1001–1012

    Article  Google Scholar 

  • Sedki A, Ouazar D (2011) Simulation-optimization modeling for sustainable groundwater development: a Moroccan coastal aquifer case study. Water Resour Manag 25(11):2855–2875

    Article  Google Scholar 

  • SEI (2008) WEAP tutorial, 228 p

  • Singh A (2014) Optimization modelling for seawater intrusion management. J Hydrol 508(16):43–52

    Article  Google Scholar 

  • Van Cauwenbergh N, Pinte D, Tilmant A, Frances I, Pulido-Bosch A et al (2008) Multi-objective, multiple participant decision support for water management in the Andarax catchment. Almeria Environ Geol 54:479–489

    Article  Google Scholar 

  • Vasan A, Raju KS (2008) Comparative analysis of simulated annealing, simulated quenching and genetic algorithms for optimal reservoir operation. Appl Soft Comput J. doi:10.1016/j.asoc.2007.09.002

    Google Scholar 

  • Zitzler E, Thiele L (1998) Multiobjective optimization using evolutionary algorithms – A comparative case study. Proceeding of parallel problem solving nature v. Amsterdam. 292–301

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Acknowledgments

The first author would like to thank the German Federal Institute for Geosciences and Natural Resources (BGR) and the Arab Center for the Studies of Arid Zones and Dry Lands (ACSAD), for their support in building the first version of the ALL_WATER_gw software.

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Authors and Affiliations

  1. Laboratory of Water Sciences and Technologies, National Institute of Agronomy of Tunisia, 43, Avenue Charles Nicolle, 1082, Tunis, Mahrajène, Tunisia

    Issam Nouiri & Jamila Tarhouni

  2. Agricultural and Biosystems Engineering Department, The University of Arizona, Tucson, AZ, 85721, USA

    Muluneh Yitayew

  3. Federal Institute for Geosciences and Natural Resources (BGR), Hannover, Germany

    Jobst Maßmann

Authors
  1. Issam Nouiri
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  2. Muluneh Yitayew
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  3. Jobst Maßmann
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  4. Jamila Tarhouni
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Correspondence to Issam Nouiri.

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Nouiri, I., Yitayew, M., Maßmann, J. et al. Multi-objective Optimization Tool for Integrated Groundwater Management. Water Resour Manage 29, 5353–5375 (2015). https://doi.org/10.1007/s11269-015-1122-8

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  • DOI: https://doi.org/10.1007/s11269-015-1122-8

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