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River corridors integrate the active channels, geomorphic floodplain and riparian areas, and hyporheic zone while receiving inputs from the uplands and groundwater and exchanging mass and energy with the atmosphere. Here, we trace the development of the contemporary understanding of river corridors from the perspectives of geomorphology, hydrology, ecology, and biogeochemistry. We then summarize contemporary models of the river corridor along multiple axes including dimensions of space and time, disturbance regimes, connectivity, hydrochemical exchange flows, and legacy effects of humans. We explore how river corridor science can be advanced with a critical zone framework by moving beyond a primary focus on discharge-based controls toward multi-factor models that identify dominant processes and thresholds that make predictions that serve society. We then identify opportunities to investigate relationships between large-scale spatial gradients and local-scale processes, embrace that riverine processes are temporally variable and interacting, acknowledge that river corridor processes and services do not respect disciplinary boundaries and increasingly need integrated multidisciplinary investigations, and explicitly integrate humans and their management actions as part of the river corridor. We intend our review to stimulate cross-disciplinary research while recognizing that river corridors occupy a unique position on the Earth's surface.

 

Access to and extensive use of fluorometric analyses is limited, despite its extensive utility in environmental transport and fate. Wide-spread application of fluorescent tracers has been limited by the prohibitive costs of research-grade equipment and logistical constraints of sampling, due to the need for high spatial resolutions and access to remote locations over long timescales. Recently, low-cost alternatives to research-grade equipment have been found to produce comparable data at a small fraction of the price for commercial equipment. Here, we prototyped and benchmarked performance of a variety of fluorometer components against commercial units, including performance as a function of tracer concentration, turbidity, and temperature, all of which are known to impact fluorometer performance. While component performance was found to be comparable to the commercial units tested, the best configuration tested obtained a functional resolution of 0.1 ppb, a working concentration range of 0.1 to >300 ppb, and a cost of USD 59.13. 

The Clean Water Act (CWA) is the primary federal mechanism by which the physical, chemical, and biological integrity of streams, lakes, and wetlands are protected in the United States. The CWA has evolved considerably since its initial passage in 1948, including explicit expansions and contractions of jurisdictional scope through a series of legislative actions, court decisions, and agency rules. Here, we provide a practical summary of the CWA's evolution, detailing the major updates or revisions and their circumstances. Additionally, we identify the jurisdictional scope of the law for rivers and streams, lakes, and wetlands based on the language used and implementation by the agencies during the same time period. While the rulemaking process commonly uses language that will be abstract to many hydrologists, understanding the on‐the‐ground implications, quantifying regulatory (un)certainties, and assessing the magnitude of changes through time is important to understanding the implications of environmental regulation development, litigation, and enforcement. Thus, we translate the enforcement norms and definitions into quantitative estimates for Clean Water Act scope in the Wabash River Basin (Illinois, Indiana, and Ohio, USA) as a demonstration of the spatial consequences of changing regulatory language.

This article is categorized under:

Engineering Water > Planning Water

Human Water > Water Governance

Water and Life > Conservation, Management, and Awareness

 

Midwestern cities require forecasts of surface nitrate loads to bring additional treatment processes online or activate alternative water supplies. Concurrently, networks of nitrate monitoring stations are being deployed in river basins, co‐locating water quality observations with established stream gauges. However, tools to evaluate the future value of expanded networks to improve water quality forecasts remains challenging. Here, we construct a synthetic data set of stream discharge and nitrate for the Wabash River Basin—one of the United States’ most nutrient polluted basins—using the established Agro‐IBIS and THMB models. Synthetic data enables rapid, unbiased and low‐cost assessment of potential sensor placements to support management objectives, such as near‐term forecasting. Using the synthetic data, we established baseline 1‐day forecasts for surface water nitrate at 12 cities in the basin using support vector machine regression (SVMR; RMSE 0.48–3.3 ppm). Next, we used the SVMRs to evaluate the improvement in forecast performance associated with deployment of additional nitrate sensors. We identified the optimal sensor placement to improve forecasts at each city, and the relative value of sensors at each candidate location. Finally, we assessed the co‐benefit realized by other cities when a sensor is deployed to optimize a forecast at one city, finding significant positive externalities in all cases. Ultimately, our study explores the potential for machine learning to make near‐term predictions and critically evaluate the improvement realized by expanding a monitoring network. While we use nitrate pollution in the Wabash River Basin as a case study, this approach could be readily applied to any problem where the future value of sensors and network design are being evaluated.