Decision-ready cdom: development of a national scale water quality dataset from remotely sensed dissolved organic matterproject period: 1 1 25-12 31 26AWARD purpose:dissolved organic matter (DOM)…

This Cooperative Agreement award, provided by the U.S. Geological Survey (USGS) under the USGS Research and Data Collection program (CFDA 15.808), will fund the development of a national-scale dataset of dissolved organic matter (DOM) concentrations in U.S. inland waters from 1984 to 2024. The $337,987 award to the University of Colorado will support the following key products and activities:

1. The release of a publicly available, nationally consistent DOM dataset derived from remote sensing data and in-situ observations.
2. The development and publication of statistical and machine learning models to predict DOM concentrations at a national scale.
3. At least one journal article documenting the models and synthesizing results to inform future water quality monitoring programs and water resource management.

The project aims to address the gap in observational data on DOM, which plays a critical role in water quality, by leveraging remote sensing and modeling approaches. The resulting dataset and research outputs are intended to benefit USGS water monitoring programs, water resource decision-makers, and the broader aquatic science community.

Activities

To address this GAP, propose to provide remote sensing-derived estimates of DOM concentration for selected lakes and rivers across the continental US from 1984-2024. Notably, this work will build upon existing efforts at the U.S. Geological survey next generation water observing system where matched in situ DOM concentrations will be paired with surface reflectance values from landsat 5, 7, 8, and 9 as well as sentinel 2. Will hire a postdoctoral researcher who will be responsible for building predictive models based on the knownobservations of DOM in lakes and rivers.deliverables and expected outcomes products will include (1) a data release of internally consistent national-scale DOM data, (2) publication of statistical and machine learning models predicting DOM concentrations at a national scale, and (3) at least one journal article documenting models and synthesizing results to inform future water quality observation programs and water resource management. Intended beneficiaries include USGS water monitoring programs, water resource decision makers, and the broader aquatic science community.

Intended beneficiaries

A major motivation for this work is the publication of novel datasets for exploration and application by the broader scientific and water resource practitioner communities. The dataset will be published in the environmental data initiative repository, a USGS-approved data platform. All coding workflows will be made public on USGS gitlab repositories. Next generation water observing system leadership and program decision making will be informedby interim project activity summaries, presentations, and the final products. Anticipate the results of this project to inform future national scale water quality monitoring strategies. Finally, since the data will be publicly available, there are many interesting scientific questions that can be probed regarding the spatiotemporal variability of dissolved organic carbon in US inland waters.subrecipient activitiesthe PI at the subrecipient university will serve as a faculty mentor for the postdoctoral researcher on this project.