13 citations as recorded by crossref.

1. Evaluation of Greenhouse Gas-Flux-Determination Models and Calculation in Southeast Arkansas Cotton Production C. Seuferling et al. https://doi.org/10.3390/agriengineering7070213
2. Hydrodynamic reconstruction regulates carbon emissions in water diversion rivers S. Liu et al. https://doi.org/10.1016/j.jhydrol.2026.135527
3. Contrasting effects of biochar and compost on greenhouse gas emissions and the global warming potential of semi-arid cropping systems P. Madhuwanthi et al. https://doi.org/10.1038/s41598-026-42554-4
4. Summer drought enhances diurnal amplitude of CO2 in two German rivers of different size P. Leng et al. https://doi.org/10.1016/j.watres.2024.122870
5. Quantifying temporal dynamics of greenhouse gas emissions in lake mesocosms: Deployment of a low‐cost measurement system T. Bucak et al. https://doi.org/10.1002/lom3.70060
6. Natural abundance sediment δ15N as a proxy for long-term gross N-turnover processes, GHG emissions, and denitrification hotspots within fluvial ecosystems R. Mwanake et al. https://doi.org/10.1016/j.envadv.2026.100685
7. Diel Variability of CO2 and CH4 from Inland Waters: Patterns, Drivers, and Implications L. Li et al. https://doi.org/10.3390/w18030415
8. Research of characteristics of spatial and temporal variations of CH 4 emission at the water-gas interface of the Inner Mongolia section of the Yellow River and its influencing factors H. Bao et al. https://doi.org/10.1080/02705060.2025.2460813
9. Temporal dynamics of CO2 emissions from dry reservoir sediments M. Koschorreck et al. https://doi.org/10.1007/s11368-026-04293-x
10. Divergent Effects of Agriculture on River Methane and Carbon Dioxide Concentrations and Emissions: Insights from Multiple Techniques Y. Li et al. https://doi.org/10.1021/acsestwater.4c01274
11. Wastewater-effluent discharge and incomplete denitrification drive riverine CO2, CH4 and N2O emissions I. Peterse et al. https://doi.org/10.1016/j.scitotenv.2024.175797
12. From data to insights: Upscaling riverine GHG fluxes in Germany with machine learning R. Mwanake et al. https://doi.org/10.1016/j.scitotenv.2024.177984
13. Emission of CO 2 and CH 4 from urban rivers: a review H. Qin et al. https://doi.org/10.1080/11956860.2026.2652665