Technological advances and resource constraints present scientists and engineers with renewed challenges in the design of methods to conduct water quality monitoring, and these decisions ultimately determine the degree of project success. Many professionals are exploring alternative lower-cost options because of cost constraints, and research and development is largely focused on in situ sensors that produce high temporal resolution data. While some guidance is available, contemporary information is needed to balance water quality monitoring decisions with financial and personnel constraints, while meeting data quality needs. This manuscript focuses on monitoring constituents, such as sediment, nutrients, and pathogens, at the field scale and in small watersheds. Specifically, the impacts on the costs and data quality of alternatives related to site selection, discharge measurement, and constituent concentration measurement, are explored. The present analysis showed that avoiding sites requiring extensive berm construction and the installation of electric power to reach distant sites greatly reduces the initial costs with little impact on data quality; however, other decisions directly impact data quality. For example, proper discharge measurement, high-frequency sampling, frequent site and equipment maintenance, and the purchase of backup power and monitoring equipment can be costly, but are important for high quality data collection. In contrast, other decisions such as the equipment type (mechanical samplers, electronic samplers, or in situ sensors) and whether to analyze discrete or composite samples greatly affect the costs, but have minimal impact on data quality. These decisions, therefore, can be based on other considerations (e.g., project goals, intended data uses, funding agency specifications, and agency protocols). We hope this guidance helps practitioners better design and implement water quality monitoring to satisfy resource constraints and data quality needs.

Long‐term research is essential for guiding the development of agroecosystems to meet escalating production demands in a manner that is environmentally sound and socially acceptable. Research must integrate biophysical and socioeconomic factors to provide geographically scalable knowledge that involves stakeholders across the research‐education‐extension‐policy spectrum. In response to this need, the Long‐Term Agroecosystem Research (LTAR) network developed a “Common Experiment,” which seeks to develop and disseminate multi‐region, science‐based information to enable implementation of visionary agricultural innovations while simultaneously promoting food security, well‐being, environmental quality, and climate adaptation and mitigation. The core design of the Common Experiment contrasts prevailing and alternative/aspirational production systems, with the latter including novel innovations hypothesized to advance sustainable intensification in locally appropriate ways. Treatments in the Common Experiment represent a diversity of production systems under cropland, grazing land, and integrated crop/grazing land management. Where possible, treatments are evaluated at multiple spatial scales (e.g., from plot to enterprise) and are designed to evolve over the course of the experiment with stakeholder input. A common assessment framework guides data collection for the experiment and is complemented by metric‐specific protocols and an emerging data management infrastructure. Currently, there are large differences among sites in the application of the experimental framework and degree of stakeholder engagement; differences largely grounded in pragmatic issues related to land access, site expertise, and resource availability. The full potential of the LTAR Common Experiment may be realized with strategic investments in network capacity.

Agricultural systems evolve from the interactions of climate, crops, soils, management practices (e.g., tillage, cover crops, nutrient management), and economic risks and rewards. Alternatives to the corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] (C–S) cropping systems that dominate in the US Midwest may provide more sustainable use of resources, reduce the documented environmental impacts of current C–S systems, and improve production efficiency and ecosystem services. Innovative management practices are needed to offer producers options to increase farm resilience to variable weather conditions and offset negative environmental impacts. In response to this need, the Upper Mississippi River Basin Long‐Term Agroecosystem Research network site at Ames, IA, established a cropland experiment in 2016 to investigate an alternative crop management system that includes reduced tillage, cover crops, and right source, right rate, right time, and right place (4R) nitrogen (N) management. The experimental site is located on the Iowa State University Kelley Research Farm in Boone County, IA. Crop, soil, air, and tile drainage water measurements are made throughout the year using published methods for each agronomic and environmental metric. Our goal is to provide quantitative information to farmers, consultants, agribusiness partners, and state and federal agencies to help guide decisions on the effective use of alternative management practices. Future changes in experimental treatments will adopt a knowledge co‐production approach whereby researchers and stakeholders will work collaboratively to identify problems, implement research protocols, and interpret results.