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Water Resources Research

An ontology for component-based models of water resource systems

Authors

  • Mostafa Elag,

    1. Department of Civil and Environmental Engineering, University of South Carolina, Columbia, South Carolina, USA
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  • Jonathan L. Goodall

    Corresponding author
    1. Department of Civil and Environmental Engineering, University of South Carolina, Columbia, South Carolina, USA
    • Corresponding author: J. L. Goodall, Department of Civil and Environmental Engineering, University of South Carolina, Columbia, SC 29208, USA. (goodall@cec.sc.edu)

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Abstract

[1] Component-based modeling is an approach for simulating water resource systems where a model is composed of a set of components, each with a defined modeling objective, interlinked through data exchanges. Component-based modeling frameworks are used within the hydrologic, atmospheric, and earth surface dynamics modeling communities. While these efforts have been advancing, it has become clear that the water resources modeling community in particular, and arguably the larger earth science modeling community as well, faces a challenge of fully and precisely defining the metadata for model components. The lack of a unified framework for model component metadata limits interoperability between modeling communities and the reuse of models across modeling frameworks due to ambiguity about the model and its capabilities. To address this need, we propose an ontology for water resources model components that describes core concepts and relationships using the Web Ontology Language (OWL). The ontology that we present, which is termed the Water Resources Component (WRC) ontology, is meant to serve as a starting point that can be refined over time through engagement by the larger community until a robust knowledge framework for water resource model components is achieved. This paper presents the methodology used to arrive at the WRC ontology, the WRC ontology itself, and examples of how the ontology can aid in component-based water resources modeling by (i) assisting in identifying relevant models, (ii) encouraging proper model coupling, and (iii) facilitating interoperability across earth science modeling frameworks.

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