iNAIADS: iNtegration, Artificial Intelligence Analytical Data Services for Rivers and Watersheds

This project uses a novel data synthesis,

synthesis

The process of combining a number of things into a coherent whole to form a theory or system.

Source: National Library of Medicine Source

analysis, and machine learning

machine learning (ML)

Machine Learning (ML) refers to the field and practice of using algorithms that are able to “learn” by extracting patterns from a large body of data.

Source: Center of Excellence Source

framework to determine how climate-driven disturbances like floods, droughts and heat waves will change water quality over time. We are studying impacted locations across river corridors

river corridor

A river (or stream) corridor includes the width of the channel in which water flows and is typically expanded to account for the extensive influence of the watercourse into the surrounding landscape.

Source: FEMA- River Corridor and watershed management Source

and basins of the United States, including the Colorado, Pacific Northwest and mid-Atlantic basins. Our objective is to determine whether and how watersheds

watershed

An area of land that channels rainfall and snowmelt to creeks, streams, and rivers, and eventually flows to the lowest point in a basin.

Source: USGS Source

with different characteristics are resistant and resilient to these disturbances, resulting in better predictions of water quality in future changing climates.