macrosheds:
an open watershed data platform
MacroSheds is an open access platform integrating watershed data from all the entities that collect and house it, making it easy for anyone to the hydrology, water quality, and biogeochemistry of rivers in the US and beyond.
MacroSheds is funded by the National Science Foundation and is co-investigated with the Bernhardt Lab at Duke University.
harmonizing watershed science
Watershed ecosystem science is complex, and developing theories around identified idiosyncrasies is further complicated by the lack of data unification across platforms.
Macrosheds aims to massively increase the access, use, and analysis of watershed ecosystem data by merging all US watershed ecosystem studies into a standardized and searchable common data platform. We’re also building high-powered data infrastructure and visualization tools to make accessing this data as easy as possible.
Streamlining access to hydrology, biogeochemistry, and climate data across hundreds of sites will helps scientists answer major questions about how watersheds function and respond to change.
Macrosheds provides:
A centralized data infrastructure that harmonizes formats across watershed studies
Tools to analyze, visualize, and compare watershed variables at local to continental scales
A publicly accessible Shiny web app to explore nutrient retention, erosion, hydrologic sensitivity, and more
big questions, big data
MacroSheds is currently being used to investigate and visualize big questions like:
What types of watersheds are best at retaining nutrients?
Which watersheds are recovering more quickly from acid rain or pollution events?
Which watersheds have the highest erosion rates and why?
How do flow patterns differ in sensitivity to floods and droughts?
The platform enables cross-site watershed comparisons to explore answers at scale.
training the next wave of watershed researchers
MacroSheds is more than just a research tool. Through macro-scale watershed training camps, we’re mentoring early-career scientists in data-intensive research, coding, and cross-site synthesis.
By emphasizing open science, reproducibility, and collaboration, we’re building capacity in the watershed and ecosystem science community.