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Integrated Modelling Systems

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Hydrological Processes Modelling and Data Analysis

Part of the book series: Water Science and Technology Library ((WSTL,volume 127))

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Abstract

The present chapter attempted to briefly overview integrated modelling systems and their applications for hydrologic sciences. Integrated modelling systems provide non-invasive ways of utilising the synergetic effect of two models. In conventional hydrologic research, integrated modelling focused on considering the surface and groundwater interactions (e.g., MIKE SHE) for accurate water balance estimation. However, in modern hydrology, integrated modelling is more inclined towards combining data-driven and process-based hydrologic modelling. In this aspect, ‘big data’ can further strengthen the credibility of the hybrid model by providing the opportunity to validate them on extensive, diverse data. The chapter also attempted to highlight the emerging techniques like explainable machine ML and physics-constraint ML that are useful in interpreting the black-box ML models and making the process opaque. Incorporation of these techniques can leverage the strengths of hybrid models.

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Authors and Affiliations

  1. Department of Biological and Agricultural Engineering and Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, TX, USA

    Vijay P. Singh

  2. Agricultural and Food Engineering Department, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India

    Rajendra Singh

  3. School of Engineering, University of Guelph, Guelph, ON, Canada

    Pranesh Kumar Paul

  4. Centre for Cryosphere and Climate Change Studies, National Institute of Hydrology, Roorkee, Uttarakhand, India

    Deepak Singh Bisht

  5. Department of Food, Agricultural and Biological Engineering, The Ohio State University, Columbus, OH, USA

    Srishti Gaur

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  1. Vijay P. Singh
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  5. Srishti Gaur
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Correspondence to Rajendra Singh .

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Singh, V.P., Singh, R., Paul, P.K., Bisht, D.S., Gaur, S. (2024). Integrated Modelling Systems. In: Hydrological Processes Modelling and Data Analysis. Water Science and Technology Library, vol 127. Springer, Singapore. https://doi.org/10.1007/978-981-97-1316-5_7

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