Geoscientists now live in a world rich with digital data and methods, and their computational research cannot be fully captured in traditional publications. The Geoscience Paper of the Future (GPF) presents an approach to fully document, share, and cite all their research products including data, software, and computational provenance. This article proposes best practices for GPF authors to make data, software, and methods openly accessible, citable, and well documented. The publication of digital objects empowers scientists to manage their research products as valuable scientific assets in an open and transparent way that enables broader access by other scientists, students, decision makers, and the public. Improving documentation and dissemination of research will accelerate the pace of scientific discovery by improving the ability of others to build upon published work.

Quantifying distributed lateral groundwater contributions to surface water (GW-SW discharges) is a key aspect of tracking nonpoint-source pollution (NPSP) within a watershed. In this study, we characterized distributed GW-SW discharges and associated salt loading using elevated GW specific conductance (SC) as a tracer along a 38 km reach of the Lower Merced River in Central California. High resolution longitudinal surveys for multiple flows (1.3-150 m(3) s(-1)) revealed river SC gradients that mainly decreased with increasing flow, suggesting a dilution effect and/or reduced GW-SW discharges due to hydraulic gradient reductions. However, exceptions occurred (gradients increasing with increasing flow), pointing to complex spatiotemporal influences on GW-SW dynamics. The surveys revealed detailed variability in salinity gradients, from which we estimated distributed GW-SW discharge and salt loading using a simple mixing model. Modeled cumulative GW discharges for two surveys unaffected by ungauged SW discharges were comparable in magnitude to differential gauging-based discharge estimates and prior GW-SW studies along the same river reach. Ungauged lateral inlets and sparse GW data limited the study, and argue for enhancing monitoring efforts. Our approach provides a rapid and economical method for characterizing NPSP for gaining rivers in the context of integrated watershed modeling and management.

Abstract. Scientific metadata containing semantic descriptions of scientific data is expensive to capture and is typically not used across entire data analytic processes. We present an approach where semantic metadata is generated as scientific data is being prepared, and then subsequently used to configure models and to customize them to the data. The metadata captured includes sensor descriptions, data characteristics, data types, and process documentation. This metadata is then used in a workflow system to select analytic models dynamically and to set up model parameters automatically. In addition, all aspects of data processing are documented, and the system is able to generate extensive provenance records for new data products based on the metadata. As a result, the system can dynamically select analytic models based on the metadata properties of the data it is processing, generating more accurate results. We show results in analyzing stream metabolism for watershed ecosystem management.

Land use and climate are two determinant factors of water yield within a watershed. Understanding the effects of these two variables is key for the decision-making process within watersheds. Hydrologic modeling can be used for this purpose and the integration of future climate scenarios to calibrated models widens the spectrum of analysis. Such types of studies have been carried out in many areas of the world, including the Amazon Basin of South America. However, there is a lack of understanding on the effect of land use/land cover and climate change on Andean watersheds of this continent. Our study focused on the evaluation of water yield under different land use and climate scenarios using the semi-distributed hydrological model known as the Soil and Water Assessment Tool (SWAT) model. We worked on the Tona watershed (Colombia, South America), the most important source of water for a metropolitan population. Our results compared water yield estimates for historical conditions (1987–2002) with those of future combined scenarios for land use and climate for the 2006–2050 period. The modeling effort produced global estimates of water yield (average annual values) and, at the subwatershed level, identified strategic areas on which the protection and conservation activities of water managers can be focused.

Delineating pollutant reactive transport pathways that connect local land use patterns to surface water is an important goal. This work illustrates high‐resolution river mapping of salinity or specific conductance (SC) and nitrate ( NO3−) as a potential part of achieving this goal. We observed longitudinal river SC and nitrate distributions using high‐resolution synoptic in situ sensing along the lower Merced River (38 river km) in Central California (USA) from 2010 to 2012. We calibrated a distributed groundwater‐surface water (GW‐SW) discharge model for a conservative solute using 13 synoptic SC sampling events at flows ranging from 1.3 to 31.6 m3 s−1. Nitrogen loads ranged from 0.3 to 1.6 kg N d−1 and were greater following an extended high flow period during a wet winter. Applying the distributed GW‐SW discharge estimates to a simplistic reactive nitrate transport model, the model reproduced observed river nitrate distribution well (RRMSE = 5–21%), with dimensionless watershed‐averaged nitrate removal (kt) ranging from 0 to 0.43. Estimates were uncertain due to GW nitrate data variability, but the resulting range was consistent with prior removal estimates. At the segment scale, estimated GW‐SW nitrate loading ranged from 0 to 17 g NO3− s−1 km−1. Local loading peaked near the middle of the study reach, a location that coincides with a shallow clay lens and with confined animal feed operations in close proximity to the river. Overall, the results demonstrate the potential for high‐resolution synoptic monitoring to support GW‐SW modeling efforts aimed at understanding and managing nonpoint source pollution.