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Advocates of enhanced quality for published scientific results are increasingly voicing the need for further transparency of data and software for scientific reproducibility. However, such advanced digital scholarship can appear perplexing to geoscientists that are seduced by the concept of open science yet wonder about the exact mechanics and implications of the associated efforts. This special issue of Earth and Space Science entitled “Geoscience Papers of the Future” includes a review of existing best practices for digital scholarship and bundles a set of example articles that share their digital research products and reflect on the process of opening their scientific approach in a common quest for reproducible science. This article is protected by copyright. All rights reserved.

Integrated modeling of coupled surface-subsurface flow and ensuing role in diverse Earth system processes is of current research interest to characterize nonlinear rainfall-runoff response and also to understand land surface energy balances, biogeochemical processes, geomorphological dynamics, etc. A growing number of complex models have been developed for water-related research, and many of these are made available to the Earth science community. However, relatively few resources have been made accessible to the potentially large group of Earth science and engineering users. New users have to invest an extraordinary effort to study the models. To provide a stimulating experience focusing on the learning curve of integrated modeling of coupled surface-subsurface flow, we describe use cases of an open source model, the Penn State Integrated Hydrologic Model, PIHM. New users were guided through data processing and model application by reproducing a numerical benchmark problem and a real-world watershed simulation. Specifically, we document the PIHM application and its computational workflow to enable intuitive understanding of coupled surface-subsurface flow processes. In addition, we describe the user experience as important evidence of the significance of reusability. The interaction shows that documentation of data, software, and computational workflow in research papers is a promising method to foster open scientific collaboration and reuse. This study demonstrates how open science practice in research papers would promote the utility of open source software. Addressing such open science practice in publications would promote the utility of journal papers. Further, popularization of such practice will require coordination among research communities, funding agencies, and journals.