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Representing Local Dynamics of Water Resource Systems through a Data-Driven Emulation Approach

Author

Listed:
  • Shahin Zandmoghaddam

    (Concordia University)

  • Ali Nazemi

    (Concordia University)

  • Elmira Hassanzadeh

    (Polytechnique Montreal)

  • Shadi Hatami

    (Concordia University)

Abstract

Water resource systems are under enormous pressures globally. To diagnose and quantify potential vulnerabilities, effective modeling tools are required to represent the interactions between water availability, water demands and their natural and anthropogenic drivers across a range of spatial and temporal scales. Despite significant progresses, system models often undergo various level of simplifications. For instance, several variables are represented within models as prescribed values; and therefore, their links with their natural and anthropogenic drives are not represented. Here we propose a data-driven emulation approach to represent the local dynamics of water resource systems through advising a set of interconnected functional mappings that not only learn and replicate input-output relationships of an existing model, but also link the prescribed variables to their corresponding natural and anthropogenic drivers. To demonstrate the practical utility of the suggested methodology, we consider representing the local dynamics at the Oldman Reservoir, which is a critical infrastructure for effective regional water resource management in southern Alberta, Canada. Using a rigorous setup/falsification procedure, we develop a set of alternative emulators to describe the local dynamics of irrigation demand and withdrawals along with reservoir release and evaporation. The non-falsified emulators are then used to address the impact of changing climate on the local irrigation deficit. Our analysis shows that local irrigation deficit is more sensitive to changes in local temperature than those of local precipitation. In addition, the rate of change in irrigation deficit is much more significant under a unit degree of warming than a unit degree of cooling. Such local understandings are not attainable by the existing operational model.

Suggested Citation

  • Shahin Zandmoghaddam & Ali Nazemi & Elmira Hassanzadeh & Shadi Hatami, 2019. "Representing Local Dynamics of Water Resource Systems through a Data-Driven Emulation Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(10), pages 3579-3594, August.
  • Handle: RePEc:spr:waterr:v:33:y:2019:i:10:d:10.1007_s11269-019-02319-3
    DOI: 10.1007/s11269-019-02319-3
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    References listed on IDEAS

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    1. Mohammad S. Khorshidi & Mohammad Reza Nikoo & Mojtaba Sadegh & Banafsheh Nematollahi, 2019. "A Multi-Objective Risk-Based Game Theoretic Approach to Reservoir Operation Policy in Potential Future Drought Condition," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(6), pages 1999-2014, April.
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    3. Mahmood Mahmoodian & Juan Pablo Carbajal & Vasilis Bellos & Ulrich Leopold & Georges Schutz & Francois Clemens, 2018. "A Hybrid Surrogate Modelling Strategy for Simplification of Detailed Urban Drainage Simulators," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(15), pages 5241-5256, December.
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    6. Mojtaba Sadegh & Reza Kerachian, 2011. "Water Resources Allocation Using Solution Concepts of Fuzzy Cooperative Games: Fuzzy Least Core and Fuzzy Weak Least Core," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(10), pages 2543-2573, August.
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    Cited by:

    1. Amirali Amir Jabbari & Ali Nazemi, 2019. "Alterations in Canadian Hydropower Production Potential Due to Continuation of Historical Trends in Climate Variables," Resources, MDPI, vol. 8(4), pages 1-29, September.
    2. Xiaobin Zhang & Ligang Ma & Yihang Zhu & Weidong Lou & Baoliang Xie & Li Sheng & Hao Hu & Kefeng Zheng & Qing Gu, 2022. "Temporal Stability Analysis for the Evaluation of Spatial and Temporal Patterns of Surface Water Quality," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1413-1429, March.

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