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.

云计算和社交网络的最新进展正在影响我们进行专业沟通，协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展中受益。我们将提供一个案例研究，详细介绍由美国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的协作建模框架。框架的组成部分包括直接收集和分析气候和流量数据，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，并使用通过Jupyter Notebooks和GitHub等云计算服务编译的基于Python的工具来应用新可用的数据科学基础架构。这些资源允许将多个计算组件无缝集成到基于动态云的工作流程中，利益相关者，资源经理或任何具有Internet连接的人员都可以立即访问。