Wetland ecosystems play a crucial role in mitigating global climate change, and long-term, continuous eddy covariance monitoring of carbon and water fluxes is essential for better conserving and utilizing the service functions of wetland ecosystems. However, due to the scarcity of relevant monitoring data, there are relatively few studies focusing on changes in carbon and water fluxes in wetland ecosystems. Therefore, there is an urgent need for high-quality monitoring datasets to provide support. The Coastal Wetland Ecological Experimental Station of the Yellow River Delta, Chinese Academy of Sciences (hereinafter referred to as the Yellow River Delta Station) has been continuously monitoring the reed wetland ecosystem based on eddy covariance technology since 2010, and has accumulated years of observation data on carbon and water fluxes. This dataset is based on the monitoring work already conducted by the Yellow River Delta Station, summarizing and organizing the eddy covariance observation data of carbon and water fluxes at the station from 2011 to 2018, and forming data products with four temporal resolutions: half-hourly, daily, monthly, and inter-annual scales.
This dataset provides reliable data support for accurately assessing the carbon and water fluxes of the wetland ecosystem in the Yellow River Delta and their dynamic changes at various temporal scales.
The processing method for this data product follows the standardized eddy data processing workflow of the Yellow River Delta Station, mainly divided into four steps: data pre-processing, data quality control, data post-processing, and the formation of flux data products.
The 10 Hz raw high-frequency data measured by the eddy covariance observation equipment is stored on the data storage card within the data collector. Personnel responsible for maintenance collect the raw data at least twice a month, and perform checks and backups to ensure the continuity of the monitoring data. Additionally, instrument engineers conduct annual field calibrations at the observation sites to maximize the accuracy and reliability of the carbon and water flux data within the observation sites.
After data pre-processing and quality control, the proportion of valid carbon and water flux data for most years remains around 60%, and the data quality is good.
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CSTR:31253.11.sciencedb.j00001.00867
10.57760/sciencedb.j00001.00867