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    <identifier>10.11922/sciencedb.939</identifier>
    <datestamp>2020-01-14T18:17:07Z</datestamp>
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  <dc:date>2020-01-14</dc:date>
  <dc:title>Daily fluxes dataset of the typical irrigated agro-ecosystem in the North China Plain: A Case Study of Luancheng Station (2007 &amp;ndash; 2013)</dc:title>
  <dc:identifier>doi:10.11922/sciencedb.939</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>Based on micrometeorology; the Eddy Covariance System (EC) has become one of the standard observation methods for the exchange of CO2 and water heat flux between terrestrial ecosystems and the atmosphere. The dataset includes all the fluxes data accumulated in Luancheng Agro-ecosystem Experimental Station of the Chinese Academy of Sciences from the EC System; which spans from October 2007 to September 2013 and covers 6 consecutive crop growth years. And the fluxes consist of evapotranspiration (ET); precipitation (P); net radiation (Rn); sensible heat Flux (Hs) and net ecosystem exchange of CO2 (NEE). The observation object is winter wheat-summer maize rotation cropping system. It can represent the general crop growth system in the North China Plain (NCP). The network observation; quality control and storage process of this dataset strictly abide by ChinaFLUX data management technology system to make sure the reliability. The EC flux data provide important support for the study of crop field water balance and typical cropping system adjustment in the North China Plain; the mechanism of ecosystem carbon-water coupling cycles and crop growth model simulation.</dc:description>
  <dc:subject>Luancheng;  eddy covariance system;  irrigated agro-ecosystem;  water-heat-carbon daily fluxes;  winter wheat-summer maize cropping system</dc:subject>
  <dc:creator>张玉翠</dc:creator>
  <dc:creator>姜寒冰</dc:creator>
  <dc:creator>张传伟</dc:creator>
  <dc:creator>沈彦俊</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.11922/csdata.2020.0002.zh</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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