Paths to research-driven decision making in the realms of environment and water

Abstract

Now more than ever it is critical for researchers and decision makers to work together to improve how we manage and preserve the planet's natural resources. Water managers in the western U.S., as in many regions of the world, are facing unprecedented challenges including increasing water demands and diminishing or unpredictable supplies. The transfer of knowledge (KT) and technology (TT) between researchers and entities that manage natural resources can help address these issues. However, numerous barriers impede the advancement of such transfer, particularly between organizations that do not operate in a profit-oriented context and for which best practices for university-industry collaborative engagement may not be sufficient. Frameworks designed around environmental KT - such as the recently-developed Research-Integration-Utilization (RIU) model - can be leveraged to address these barriers. Here, we examine two examples in which NASA Earth science satellite data and remote-sensing technology are used to improve the management of water availability and quality. Despite differences in scope and outcomes, both of these case studies adopt KT and TT best practices and can be further understood through the lens of the RIU model. We show how these insights could be adopted by NASA through a conceptual framework that charts individual- and organizational-level integration milestones alongside technical milestones. Environmental organizations can learn from this approach and adapt it to fit their own institutional needs, integrating KT/TT models and best practices while recognizing and leveraging existing institutional logics that suit their organization's unique history, technical capability and priorities.

Fig. 1.

Measurements of snow depth collected on May 4–5, 2020 for the San Joaquin River Basin upstream of Millerton Lake. ASO measured the entire snowpack within the 4500 km² watershed area and recorded snow depth at a spatial resolution of 3 × 3 m and SWE at a resolution of 50 × 50 m (not shown) within 72 h of the survey. The 3D inset highlights the spatial complexity in snow depth in the Ritter Range vicinity, where darker blue reflects deeper snowpack. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 2.

Conceptual representation of the (CyAN) Sentinel-3 satellite coverage for early detection and monitoring of cyanobacterial events across the U.S. The spatial resolution of the data is 300 × 300 m pixels. Operational delivery of cyanobacteria data is available for daily and weekly composites as demonstrated here for the 7-day weekly composite June 23 to June 27, 2020. The figure shows a zoom in of Lake Okeechobee in Florida; blue and green represent low concentrations of cyanobacteria biomass while warm yellow and orange represent higher concentrations. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3.

The NASA R2O–O2R framework, consisting of six iterative, linked processes that research and operational organizations co-develop. The framework builds on NASA’s ARL scale by folding in relationship-building requirements as well as technical milestones. Coupled together, these technical and social processes form the foundational elements needed to successfully transition Earth science from research to operations while also providing an explicit pathway for operational knowledge to inform research directions and practices.