Collaborative groundwater modeling: Open-source, cloud-based, applied science at a small-island water utility scale

Christopher K. Shuler, Katrina E. Mariner
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引用次数: 5

Abstract

Recent advancements 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 advancements. 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 climatic 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
协同地下水建模:开放源码,基于云的,应用科学在一个小岛屿的水公用事业规模
云计算和社交网络的最新进展正在影响我们专业沟通、协同工作和处理数据科学任务的方式。在这里,我们展示了地下水建模领域如何从这些进步中受益。我们提出了一个案例研究,详细介绍了由美属萨摩亚电力局和夏威夷大学水资源研究中心的参与者共同开发的垂直集成协作建模框架。该框架的组成部分包括直接收集和分析气候和河流数据,开发水预算模型,以及启动动态地下水建模过程。该框架是完全开源的,并使用基于python的工具(由Jupyter notebook和云计算服务(如GitHub)编译)应用最新可用的数据科学基础设施。这些资源允许将多个计算组件无缝集成到一个动态的基于云的工作流中,利益相关者、资源管理人员或任何有互联网连接的人都可以立即访问该工作流
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