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Handling Large Decision Variables in Multi-Objective Groundwater Optimization Problems: Aquifer Parameter-Based Clustering Approach

Author

Listed:
  • Shreyansh Mishra

    (Indian Institute of Technology (Banaras Hindu University))

  • Lilian Bosc

    (Ecole des Mines de Saint-Étienne)

  • Shishir Gaur

    (Indian Institute of Technology (Banaras Hindu University))

  • Mariem Kacem

    (Centrale Lyon-ENISE, Univ Lyon, Tribology and Systems Dynamics Lab. (CNRS UMR 5513 LTDS)
    Centrale Pékin, Beihang University)

  • Anurag Ohri

    (Indian Institute of Technology (Banaras Hindu University))

Abstract

Number of decision variables (DVs) significantly impacts the convergence of multi-objective groundwater simulation-optimization problems (MO-GSOPs). Previous studies of reducing DV by decomposition methods based on the proximity between the pumping wells have yet to assess its implication on the Pareto fronts. This study introduces a novel approach to clustering known as aquifer parameter-based clustering. This work aims to decrease the number of wells involved in MO-GSOPs via clustering based on essential aquifer properties that govern groundwater flow, including initial head, recharge, top elevation of the aquifer layer, and hydraulic conductivity. The simulation-optimization model solves the objectives of maximizing pumping discharge and river-aquifer (R-A) exchanges. The resulting Pareto fronts are compared in terms of convergence and diversity. The analysis reveals that initial head-based clustering exhibits superior performance, leading to a significant increase in hypervolume (46%) and a decrease in the inverted generational distance (22%) compared to distance-based DV clustering. Comparison between results shows that aquifer parameter-based clustering has superior optimal results overall than traditional clustering based upon Euclidian distance. Furthermore, the discharge variation resulting from the parameter-based clustering is examined at the commune level. Notably, Chazey Sur Ain, located near the river, experiences a substantial increase in discharge (12659.13 m3/d), while communes situated near the study area’s boundary, namely Douvres and Jujurieux, observe marginal discharge increases (500 m3/d and 130.33 m3/d, respectively).

Suggested Citation

  • Shreyansh Mishra & Lilian Bosc & Shishir Gaur & Mariem Kacem & Anurag Ohri, 2023. "Handling Large Decision Variables in Multi-Objective Groundwater Optimization Problems: Aquifer Parameter-Based Clustering Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(11), pages 4553-4568, September.
    • Handle: RePEc:spr:waterr:v:37:y:2023:i:11:d:10.1007_s11269-023-03580-3
    DOI: 10.1007/s11269-023-03580-3
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    References listed on IDEAS

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    1. Ali Al-Maktoumi & Mohammad Mahdi Rajabi & Slim Zekri & Chefi Triki, 2021. "A Probabilistic Multiperiod Simulation–Optimization Approach for Dynamic Coastal Aquifer Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(11), pages 3447-3462, September.
    2. Pedro Beça & António C. Rodrigues & João P. Nunes & Paulo Diogo & Babar Mujtaba, 2023. "Optimizing Reservoir Water Management in a Changing Climate," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(9), pages 3423-3437, July.
    3. Mayank Bajpai & Shreyansh Mishra & Shishir Gaur & Anurag Ohri & Hervé Piégay & Didier Graillot, 2022. "Optimization of Groundwater Pumping and River-Aquifer Exchanges for Management of Water Resources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(6), pages 1863-1878, April.
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