Dr. Todd Steissberg (ERDC-EL) delivered a presentation titled “Integrating Water Resources Infrastructure with Upland Management to Advance Nature-Based Solutions for Water Quantity and Quality” at the International Soil and Water Assessment Tool (SWAT) Conference, June 28, 2023. This presentation gave an overview of the project, the goals of the EWN program, the watershed-scale problems that need to be addressed, and the methods and models the project team is developing. Maintaining water quality while effectively managing water resources is a formidable task, primarily due to the presence of extreme conditions and contaminants throughout the system. Precipitation, flow, temperature, and runoff that carries heavy loads of nutrients and other pollutants make it challenging to meet water quality objectives. Moreover, the complexity of the water system introduces multiple drivers and control points that need to be considered. Water quantity and quality are influenced at various stages as it traverses the watershed. Source areas in the uplands, including precipitation, snowmelt, agricultural sources, and springs, contribute to the water flow. Runoff, both on the surface and through sub-surface pathways, transports the water across the landscape. It eventually flows into and through stream networks, impacting the quality of water in rivers. Additionally, water may accumulate in reservoirs or other water infrastructure, further influencing its quantity and quality. To address these challenges, this project is developing methods and linked models that will enable strategic design and implementation of Natural and Nature-Based Features (NNBF) that are in harmony with ecohydrological processes to meet EWN objectives. Our core goals are to evaluate the viability of our approach through comprehensive national data analysis and active engagement with stakeholders, and to craft advanced modeling and data science tools. These tools aim to define best practices and aid USACE in pinpointing and assessing NNBF opportunities within its managed systems. This endeavor seeks to bridge significant knowledge voids about these systems’ operations, unearthing innovative strategies for optimized landscape management. By emulating expansive natural processes, we will deliver a system-wide EWN approach, harnessing cutting-edge modeling and data science methodologies.