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Improved data gap-filling schemes for estimation of net ecosystem exchange in typical East-Asian croplands

Improved data gap-filling schemes for estimation of net ecosystem exchange in typical East-Asian croplands
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摘要 The estimation of carbon exchange between ecosystems and the atmosphere suffers unavoidable data gaps in eddy-covariance technique, especially for short-living and fast-growing croplands. In this study we developed a modified gap-filling scheme introducing a leaf area index factor as the vegetation status information based on the conventional light response function for two East-Asian cropland sites (rice and potatoes). This scheme’s performance is comparable to the conventional time window scheme, but has the advantage when the gaps are large compared to the total length of the time series. To investigate how the time binning approach performs for fast-growing croplands, we tested different widths of the time window, showing that a four-day window for the potato field and an eight-day time window for the rice field perform the best. The insufficiency of the conventional temperature binning approach was explained as well as the influence of vapor pressure deficit. We found that vapor pressure deficit plays a minor role in both the potato and the rice fields under Asian monsoon weather conditions with the exception of the early pre-monsoon growing stage of the potatoes. Consequently, we recommend using the conventional time-window scheme together with our new leaf-light response function to fill data gaps of net ecosystem exchange in fast-growing croplands. The estimation of carbon exchange between ecosystems and the atmosphere suffers unavoidable data gaps in eddy-covariance technique, especially for short-living and fast-growing croplands. In this study we developed a modified gap-filling scheme introducing a leaf area index factor as the vegetation status information based on the conventional light response function for two East-Asian cropland sites (rice and potatoes). This scheme’s performance is comparable to the conventional time window scheme, but has the advantage when the gaps are large compared to the total length of the time series. To investigate how the time binning approach performs for fast-growing croplands, we tested different widths of the time window, showing that a four-day window for the potato field and an eight-day time window for the rice field perform the best. The insufficiency of the conventional temperature binning approach was explained as well as the influence of vapor pressure deficit. We found that vapor pressure deficit plays a minor role in both the potato and the rice fields under Asian monsoon weather conditions with the exception of the early pre-monsoon growing stage of the potatoes. Consequently, we recommend using the conventional time-window scheme together with our new leaf-light response function to fill data gaps of net ecosystem exchange in fast-growing croplands.
出处 《Science China Earth Sciences》 SCIE EI CAS CSCD 2016年第8期1652-1664,共13页 中国科学(地球科学英文版)
基金 funding provided by University of Innsbruck part of the International Research Training Group TERRECO (Grant No. GRK 1565/1) funded by the Deutsche Forschungsge-meinschaft (DFG) at the University of Bayreuth, Germany and the Korean Research Foundation (KRF) at Kangwon National University, Chuncheon, South Korea
关键词 EDDY-COVARIANCE GAP-FILLING Net ecosystem exchange LAI Eddy-covariance Gap-filling Net ecosystem exchange LAI
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