Aquatic systems are critical to food, security, and society. But, water data are collected by hundreds of research groups and organizations, many of which use nonstandard or inconsistent data descriptions and dissemination, and disparities across different types of water observation systems represent a major challenge for freshwater research. To address this issue, the Water Quality Portal (WQP) was developed by the U.S. Environmental Protection Agency, the U.S. Geological Survey, and the National Water Quality Monitoring Council to be a single point of access for water quality data dating back more than a century. The WQP is the largest standardized water quality data set available at the time of this writing, with more than 290 million records from more than 2.7 million sites in groundwater, inland, and coastal waters. The number of data contributors, data consumers, and third‐party application developers making use of the WQP is growing rapidly. Here we introduce the WQP, including an overview of data, the standardized data model, and data access and services; and we describe challenges and opportunities associated with using WQP data. We also demonstrate through an example the value of the WQP data by characterizing seasonal variation in lake water clarity for regions of the continental U.S. The code used to access, download, analyze, and display these WQP data as shown in the figures is included as supporting information.

Abstract. Wetlands are the largest natural source of methane (CH 4 ) emissions to the atmosphere, which vary along salinity and productivity gradients. Global change has the potential to reshape these gradients and therefore alter future contributions of wetlands to the global CH 4 budget. Our study examined CH 4 production along a natural salinity gradient in fully inundated coastal Alaska wetlands. In the laboratory, we incubated natural sediments to compare CH 4 production rates between non-tidal freshwater and tidal brackish wetlands, and quantified the abundances of methanogens and sulfate-reducing bacteria in these ecosystems. We also simulated seawater intrusion and enhanced organic matter availability, which we predicted would have contrasting effects on coastal wetland CH 4 production. Tidal brackish wetlands produced less CH 4 than non-tidal freshwater wetlands probably due to high sulfate availability and generally higher abundances of sulfate-reducing bacteria, whereas non-tidal freshwater wetlands had significantly greater methanogen abundances. Seawater addition experiments with freshwater sediments, however, did not reduce CH 4 production, perhaps because the 14-day incubation period was too short to elicit a shift in microbial communities. In contrast, increased organic matter enhanced CH 4 production in 75 % of the incubations, but this response depended on the macrophyte species added, with half of the species treatments having no significant effect. Our study suggests that CH 4 production in coastal wetlands, and therefore their overall contribution to the global CH 4 cycle, will be sensitive to increased organic matter availability and potentially seawater intrusion. To better predict future wetland contributions to the global CH 4 budget, future studies and modeling efforts should investigate how multiple global change mechanisms will interact to impact CH 4 dynamics.

<p><strong>Abstract.</strong> Wetlands are the largest natural source of methane (CH<sub>4</sub>) to the atmosphere, but their emissions vary along salinity and productivity gradients. Global change has the potential to reshape these gradients and therefore alter future contributions of wetlands to the global CH<sub>4</sub> budget. Our study examined CH<sub>4</sub> production along a natural salinity gradient in coastal Alaska wetlands. In the laboratory, we incubated natural sediments to compare CH<sub>4</sub> production rates between freshwater and intertidal wetlands, and quantified the abundances of methanogens and sulfate-reducing bacteria in these ecosystems. We also simulated sea-level rise and enhanced organic matter availability, which we predicted would have contrasting effects on coastal wetland CH<sub>4</sub> production. Intertidal wetlands produced less CH<sub>4</sub> than freshwater wetlands due to high sulfate availability and generally higher abundances of sulfate-reducing bacteria, whereas freshwater wetlands had significantly greater methanogen abundances. Simulated sea-level rise in freshwater sediments, however, did not reduce CH<sub>4</sub> production, perhaps because the 14d incubation period was too short to elicit a shift in microbial communities. In contrast, increased organic matter generally enhanced CH<sub>4</sub> production rates, but this response varied by the macrophyte species added. Our study suggests that CH<sub>4</sub> production in coastal wetlands, and therefore their overall contribution to the global CH<sub>4</sub> cycle, will be sensitive to increased organic matter availability and potentially sea-level rise. To better predict future wetland contributions to the global CH<sub>4</sub> budget, future studies and modeling efforts should investigate how multiple global change mechanisms will interact to impact CH<sub>4</sub> dynamics.</p>

Abstract. Recent debate over the scope of the U.S. Clean Water Act underscores the need to develop a robust body of scientific work that defines the connectivity between freshwater systems and people. Coupled natural and human systems (CNHS) modeling is one tool that can be used to study the complex, reciprocal linkages between human actions and ecosystem processes. Well-developed CNHS models exist at a conceptual level, but the mapping of these system representations in practice is limited in capturing these feedbacks. This article presents a paired conceptual-empirical methodology for functionally capturing feedbacks between human and natural systems in freshwater lake catchments, from human actions to the ecosystem and from the ecosystem back to human actions. We address extant challenges in CNHS modeling, which arise from differences in disciplinary approach, model structure, and spatiotemporal resolution, to connect a suite of models. In doing so, we create an integrated, multi-disciplinary tool that captures diverse processes that operate at multiple scales, including land-management decision-making, hydrologic-solute transport, aquatic nutrient cycling, and civic engagement. In this article, we build on this novel framework to advance cross-disciplinary dialogue to move CNHS lake-catchment modeling in a systematic direction and, ultimately, provide a foundation for smart decision-making and policy.