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Simulation-Optimization for Conjunctive Water Resources Management and Optimal Crop Planning in Kushabhadra-Bhargavi River Delta of Eastern India

Author

Listed:
  • Madan K. Jha

    (Agricultural & Food Engineering Department, Indian Institute of Technology Kharagpur, Kharagpur-721 302, India)

  • Richard C. Peralta

    (Civil and Environmental Engineering, Utah State University, Logan, UT 84322-4110, USA)

  • Sasmita Sahoo

    (Agricultural & Food Engineering Department, Indian Institute of Technology Kharagpur, Kharagpur-721 302, India)

Abstract

Water resources sustainability is a worldwide concern because of climate variability, growing population, and excessive groundwater exploitation in order to meet freshwater demand. Addressing these conflicting challenges sometimes can be aided by using both simulation and mathematical optimization tools. This study combines a groundwater-flow simulation model and two optimization models to develop optimal reconnaissance-level water management strategies. For a given set of hydrologic and management constraints, both of the optimization models are applied to part of the Mahanadi River basin groundwater system, which is an important source of water supply in Odisha State, India. The first optimization model employs a calibrated groundwater simulation model (MODFLOW-2005, the U.S. Geological Survey modular ground-water model) within the Simulation-Optimization MOdeling System (SOMOS) module number 1 (SOMO1) to estimate maximum permissible groundwater extraction, subject to suitable constraints that protect the aquifer from seawater intrusion. The second optimization model uses linear programming optimization to: (a) optimize conjunctive allocation of surface water and groundwater and (b) to determine a cropping pattern that maximizes net annual returns from crop yields, without causing seawater intrusion. Together, the optimization models consider the weather seasons, and the suitability and variability of existing cultivable land, crops, and the hydrogeologic system better than the models that do not employ the distributed maximum groundwater pumping rates that will not induce seawater intrusion. The optimization outcomes suggest that minimizing agricultural rice cultivation (especially during the non-monsoon season) and increasing crop diversification would improve farmers’ livelihoods and aid sustainable use of water resources.

Suggested Citation

  • Madan K. Jha & Richard C. Peralta & Sasmita Sahoo, 2020. "Simulation-Optimization for Conjunctive Water Resources Management and Optimal Crop Planning in Kushabhadra-Bhargavi River Delta of Eastern India," IJERPH, MDPI, vol. 17(10), pages 1-20, May.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:10:p:3521-:d:359577
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    References listed on IDEAS

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    1. Fateme Heydari & Bahram Saghafian & Majid Delavar, 2016. "Coupled Quantity-Quality Simulation-Optimization Model for Conjunctive Surface-Groundwater Use," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4381-4397, September.
    2. T. Fowe & I. Nouiri & B. Ibrahim & H. Karambiri & J. Paturel, 2015. "OPTIWAM: An Intelligent Tool for Optimizing Irrigation Water Management in Coupled Reservoir–Groundwater Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3841-3861, August.
    3. Nicolaos Theodossiou, 2004. "Application of Non-Linear Simulation and Optimisation Models in Groundwater Aquifer Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 18(2), pages 125-141, April.
    4. Arianna Renau-Pruñonosa & Ignacio Morell & David Pulido-Velazquez, 2016. "A Methodology to Analyse and Assess Pumping Management Strategies in Coastal Aquifers to Avoid Degradation Due to Seawater Intrusion Problems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4823-4837, October.
    5. Wu, Xin & Zheng, Yi & Wu, Bin & Tian, Yong & Han, Feng & Zheng, Chunmiao, 2016. "Optimizing conjunctive use of surface water and groundwater for irrigation to address human-nature water conflicts: A surrogate modeling approach," Agricultural Water Management, Elsevier, vol. 163(C), pages 380-392.
    6. Garg, N.K. & Dadhich, Sushmita M., 2014. "Integrated non-linear model for optimal cropping pattern and irrigation scheduling under deficit irrigation," Agricultural Water Management, Elsevier, vol. 140(C), pages 1-13.
    7. Jiang, Yao & Xu, Xu & Huang, Quanzhong & Huo, Zailin & Huang, Guanhua, 2016. "Optimizing regional irrigation water use by integrating a two-level optimization model and an agro-hydrological model," Agricultural Water Management, Elsevier, vol. 178(C), pages 76-88.
    8. Kathleen Miller & Valerie Belton, 2014. "Water resource management and climate change adaptation: a holistic and multiple criteria perspective," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 19(3), pages 289-308, March.
    9. Vasileios Christelis & Aristotelis Mantoglou, 2016. "Pumping Optimization of Coastal Aquifers Assisted by Adaptive Metamodelling Methods and Radial Basis Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(15), pages 5845-5859, December.
    10. D.-A. An-Vo & S. Mushtaq & T. Nguyen-Ky & J. Bundschuh & T. Tran-Cong & T. Maraseni & K. Reardon-Smith, 2015. "Nonlinear Optimisation Using Production Functions to Estimate Economic Benefit of Conjunctive Water Use for Multicrop Production," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2153-2170, May.
    11. Slim Zekri & Chefi Triki & Ali Al-Maktoumi & Mohammad Bazargan-Lari, 2015. "An Optimization-Simulation Approach for Groundwater Abstraction under Recharge Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3681-3695, August.
    12. R. González Perea & E. Camacho Poyato & P. Montesinos & J. A. Rodríguez Díaz, 2016. "Optimization of Irrigation Scheduling Using Soil Water Balance and Genetic Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(8), pages 2815-2830, June.
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