Collaborative groundwater modeling: Open-source, cloud-based, applied science at a small-island water utility scale. (May 2020)

• Record Type: Journal Article
• Authors: Shuler, Christopher K.; Mariner, Katrina E.
• Is Part Of: Environmental modelling & software. Volume 127(2020)
• Publication Date: 2020-05
• Subjects: Groundwater modeling -- Hydrologic monitoring network -- American Samoa -- Jupyter Notebooks -- GitHub -- Python; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2020.104693
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Recent advances in cloud-computing and social-networking are influencing how we communicate professionally, work collaboratively, and approach data-science tasks. Here we show how the groundwater modeling field is well positioned to benefit from these advances. We present a case study detailing a vertically-integrated, collaborative modeling framework jointly developed by participants at the American Samoa Power Authority and at the University of Hawaii Water Resources Research Center. The framework components include direct collection and analysis of climate and streamflow data, development of a water budget model, and initiation of a dynamic groundwater modeling process. The framework is entirely open-source and applies newly available data-science infrastructure using Python-based tools compiled with Jupyter Notebooks and cloud computing services such as GitHub. These resources allow for seamless integration of multiple computational components into a dynamic cloud-based workflow that is immediately accessible to stakeholders, resource managers, or anyone with an internet connection. Highlights: Used cloud-based methods to collaborate with remote stakeholders in American Samoa. Applied open-source tools to develop a collaborative hydrologic modeling framework. Used seamless framework to integrate multiple data collection and modeling components. Components included monitoring network, water budget model, and groundwater model.