Environmental Modelling & Software, Volume 135

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Elsevier BV
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Socio-technical scales in socio-environmental modeling: Managing a system-of-systems modeling approach
Takuya Iwanaga | Hsiao‐Hsuan Wang | Serena H. Hamilton | Volker Grimm | Tomasz E. Koralewski | Alejandro Salado | Sondoss Elsawah | Saman Razavi | Yang Jian | Pierre D. Glynn | Jennifer Badham | Alexey Voinov | Min Chen | William E. Grant | Tarla Rai Peterson | Karin Frank | Gary W. Shenk | C. Michael Barton | Anthony J. Jakeman | John C. Little

System-of-systems approaches for integrated assessments have become prevalent in recent years. Such approaches integrate a variety of models from different disciplines and modeling paradigms to represent a socio-environmental (or social-ecological) system aiming to holistically inform policy and decision-making processes. Central to the system-of-systems approaches is the representation of systems in a multi-tier framework with nested scales. Current modeling paradigms, however, have disciplinary-specific lineage, leading to inconsistencies in the conceptualization and integration of socio-environmental systems. In this paper, a multidisciplinary team of researchers, from engineering, natural and social sciences, have come together to detail socio-technical practices and challenges that arise in the consideration of scale throughout the socio-environmental modeling process. We identify key paths forward, focused on explicit consideration of scale and uncertainty, strengthening interdisciplinary communication, and improvement of the documentation process. We call for a grand vision (and commensurate funding) for holistic system-of-systems research that engages researchers, stakeholders, and policy makers in a multi-tiered process for the co-creation of knowledge and solutions to major socio-environmental problems.

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Toward open and reproducible environmental modeling by integrating online data repositories, computational environments, and model Application Programming Interfaces
Young-Don Choi | Jonathan L. Goodall | Jeffrey M. Sadler | Anthony M. Castronova | Andrew Bennett | Zhiyu Li | Bart Nijssen | Shaowen Wang | Martyn P. Clark | Daniel P. Ames | Jeffery S. Horsburgh | Yi Hong | C. Bandaragoda | M. Seul | Richard Hooper | David G. Tarboton

Cyberinfrastructure needs to be advanced to enable open and reproducible environmental modeling research. Recent efforts toward this goal have focused on advancing online repositories for data and model sharing, online computational environments along with containerization technology and notebooks for capturing reproducible computational studies, and Application Programming Interfaces (APIs) for simulation models to foster intuitive programmatic control. The objective of this research is to show how these efforts can be integrated to support reproducible environmental modeling. We present first the high-level concept and general approach for integrating these three components. We then present one possible implementation that integrates HydroShare (an online repository), CUAHSI JupyterHub and CyberGIS-Jupyter for Water (computational environments), and pySUMMA (a model API) to support open and reproducible hydrologic modeling. We apply the example implementation for a hydrologic modeling use case to demonstrate how the approach can advance reproducible environmental modeling through the seamless integration of cyberinfrastructure services. • New approaches are needed to support open and reproducible environmental modeling. • Efforts should focus on integrating existing cyberinfrastructure to build new systems. • Our focus is on integrating repositories, computational environments, and model APIs. • An example implementation is shown using HydroShare, JupyterHub, and pySUMMA. • We demonstrate how the approach fosters reproducibility using a modeling case study.