Ecosystem metabolism is a measure of energy flow in terrestrial and aquatic environments that quantifies a balance between the rate of biomass production by photosynthesizing plants and the rate of biomass oxidation by respiring plants and animals to maintain and build living biomass. It is therefore a fundamental measure of ecosystem function that quantifies the balance between the rate of production, maintenance, and decay of organic matter. It also provides an understanding of energy flow to higher trophic levels that supports food webs with secondary and tertiary productivity. Furthermore, metabolism helps explain when aquatic ecosystems undergo out-of-balance behaviors such as hypoxia. Recent advances in sensor technology and modeling capabilities have enabled estimation of aquatic system metabolism and gas exchange over long time periods in rivers, streams, ponds, and wetlands where oxygen sensors have been deployed. For convenience, metabolism can be measured by tracking the rate of oxygen production and consumption in the aquatic system. Over time, the measurements of dissolved oxygen concentration can be analyzed to estimate both gross primary productivity (GPP) and ecosystem respiration (ER). GPP is defined as positive, adding oxygen and organic carbon to the system, and ER is defined as negative, subtracting oxygen by consuming organic carbon to fuel work. The sum of GPP and ER is the net ecosystem productivity, a net measure of whether oxygen and organic carbon are building up or being depleted in the system. In order to use the oxygen balance method to quantify GPP and ER in shallow waters it is also necessary to quantify the rate of gas exchange with the atmosphere by accounting for physical effects of surface renewal as well as the dissolved oxygen difference compared to the saturated concentration for a given temperature and atmospheric pressure. Here we present RiverMET for estimating river metabolism with provided workflows that streamline data preparation, run a metabolism model, assess the model performance, and flag and censor final output data. We tested RiverMET by calculating gross primary productivity (GPP), ecosystem respiration (ER) and the air-water gas exchange rate constant (K600) across seventeen (17) river sites in the Illinois River basin (ILRB) using water quality data and hydrologic data from National Water Information System (NWIS, https://waterdata.usgs.gov/nwis, data accessed September 2021) and pressure data from National Oceanic and Atmospheric Administration (NOAA, https://www.ncei.noaa.gov/maps/lcd/, data accessed September 2021). The workflows are specifically tailored to use streamMetabolizer (version 0.12.0; https://github.com/USGS-R/streamMetabolizer), a model for one-station calculations of stream metabolism that calculates daily average areal rates of GPP and ER, and the daily average volumetric air-water gas exchange rate constant, K600. We advise potential users of RiverMET to review core publications for the streamMetabolizer model to ensure best practices that produce the most useful results. We encourage feedback about our workflows, although issues regarding the streamMetabolizer model itself should be referred to the model authors. The zipped (.zip) folder "RiverMET_Outputs.zip" contains two (2) folders entitled "Outputs_from_script-2" and "Outputs_from_script-5". The folder "Outputs_from_script-2" contains four (4) folders. Each of the folders contains the prepared model input files for each unique USGS station as produced by running R script "2_Prepare-Model-InputFiles.R" from the provided "RiverMET_Scripts.zip" folder as described in the "RiverMET_readMe.txt" file. The resultant streamMetabolizer input files (.csv) are created for each unique USGS study station and stored within four (4) sub-folders titled according to the applied water depth estimation approaches with a common naming convention "bayesInput_[date]depth-[estimation_approach][site_no].csv". The script includes four (4) methods to calculate water depth.

a. field measurements (‘depth-fieldmeas’) b. hydraulic geometry coefficients (‘depth-hgc’) c. field measurements from a replacement site (‘depth-repfieldmeas’, closest geographical NWIS site with available data) d. field measurements without “poor” rating filtering (‘depth-poorfieldmeas’) The format is standardized across each of the .csv files within all subfolders and are described in detail in the Entity and Attribute section of this metadata file. Before executing streamMetabolizer model (version 0.12.0), all input data was validated by comparing with the raw downloaded data. The folder "Outputs_from_script-5" contains two (2) subfolders entitled "outputs-A" and "outputs-B". The "outputs-A" folder contains twenty-one (21) .csv files with a common naming convention in the format "flagged_GPP_ER_K600_[date]depth-[estimation_approach][site_no].csv". The "outputs-B" folder contains twenty-one (21) .csv files with a common naming convention in the format "censored_GPP_ER_K600_[date]depth-[estimation_approach][site_no].csv". The format is standardized across each of the .csv files within both subfolders and are described in detail in the Entity and Attribute section of this metadata file.