Preprints
https://doi.org/10.5194/essd-2022-346
https://doi.org/10.5194/essd-2022-346
19 Oct 2022
 | 19 Oct 2022
Status: this preprint is currently under review for the journal ESSD.

GRiMeDB: The global river database of methane concentrations and fluxes

Emily H. Stanley, Luke C. Loken, Nora J. Casson, Samantha K. Oliver, Ryan A. Sponseller, Marcus B. Wallin, Liwei Zhang, and Gerard Rocher-Ros

Abstract. Despite their small spatial extent, fluvial ecosystems play a significant role in processing and transporting carbon in aquatic networks, which results in substantial emission of methane (CH4) to the atmosphere. For this reason, considerable effort has been put into identifying patterns and drivers of CH4 concentrations in streams and rivers and estimating fluxes to the atmosphere across broad spatial scales. Yet progress toward these ends has been slow because of pronounced spatial and temporal variability of lotic CH4 concentrations and fluxes and by limited data availability across diverse habitats and physicochemical conditions. To address these challenges, we present the first comprehensive database of CH4 concentrations and fluxes for fluvial ecosystems along with broadly relevant and concurrent physical and chemical data. The Global River Methane database (GriMeDB; https://doi.org/10.6073/pasta/b7d1fba4f9a3e365c9861ac3b58b4a90) includes 24,024 records of CH4 concentration and 8,205 flux measurements from 5,037 unique sites that were extracted from publications, reports, data repositories, and other outlets published between 1973 and 2021. GriMeDB also includes 17,655 and 8,409 concurrent measurements of concentrations and 4,444 and 1,521 of fluxes for CO2 and nitrous oxide (N2O) respectively. Most observations are date-specific (i.e., not site averages) and many are supported by data for 12 physicochemical variables and 6 site variables. Site variables include codes to characterize marginal channel types (e.g., springs, ditches) and/or presence of human disturbance (e.g., point source inputs, upstream dams). Overall, observations in GRiMeDB encompass a broad range of the climatic, biological, and physical conditions that occur among world river basins, although some geographic gaps remain (e.g., arid regions, tropical regions, high latitudes and altitude systems). The global median CH4 concentration (0.20 μmol L-1) and diffusive flux (0.44 mmol m-2 d-1) in GRiMeDB are lower than estimates from past, site-averaged compilations, although ranges and standard deviations are greater from this larger and more temporally-resolved database. Available flux data are dominated by diffusive measurements despite the recognized importance of ebullitive and plant-mediated CH4 fluxes. Despite these limitations, GriMeDB provides a comprehensive and cohesive resource for examining relationships between CH4 and environmental drivers, estimating the contribution of fluvial ecosystems to CH4 emissions, and to contextualize site-based investigations.

Emily H. Stanley et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-346', Yuanzhi Yao, 13 Nov 2022
  • RC2: 'Comment on essd-2022-346', Karel Castro-Morales, 01 Feb 2023
  • RC3: 'Comment on essd-2022-346', Bridget Deemer, 02 Mar 2023

Emily H. Stanley et al.

Data sets

GRiMeDB: a comprehensive global database of methane concentrations and fluxes in fluvial ecosystems with supporting physical and chemical information ver 1. Stanley, E. H., L. C. Loken, N. J. Casson, S. K. Oliver, R. A. Sponseller, M. B. Wallin, L. Zhang, and G. Rocher-Ros https://doi.org/10.6073/pasta/b7d1fba4f9a3e365c9861ac3b58b4a90

Emily H. Stanley et al.

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Short summary
The Global Rivers Methane Database (GRiMeDB) presents CH4 concentrations and fluxes for flowing waters along with concurrent measures of CO2, N2O, and several physicochemical variables, plus information about sample locations and methods used to measure gas fluxes. GRiMeDB is intended to increase opportunities to understand variation in fluvial CH4, test hypotheses related to greenhouse gas dynamics, and reduce uncertainty in future estimates of gas emissions from world streams and rivers.