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Abstract: Evapotranspiration (ET) is a central process in the terrestrial hydrological cycle and energy balance. Water use efficiency (WUE) reflects the coupling between the carbon and water cycles. Both ET and WUE have been widely used in the research related to ecology, agriculture, hydrology, and climatology. The eddy covariance (EC) method is regarded as the only standard method for directly measuring exchanges of material and energy between the biosphere and atmosphere, as well as the most important method for observing gross primary productivity (GPP) and ET at an ecosystem scale. By synthesizing eddy-covariance carbon and water flux data in China, using both ChinaFLUX observations and the published literature, we have constructed a dataset recording the actual evapotranspiration and water use efficiency of typical terrestrial ecosystems in China. The dataset contains 143 records of annual actual ET and 96 records of annual mean water use efficiency for 45 ecosystems across China during 2000 – 2010. This dataset can provide data support for analyses on the terrestrial carbon and water cycles, ecosystem management and evaluation, global change, and other related research.
Keywords: actual evapotranspiration; water use efficiency; eddy covariance; terrestrial ecosystem; China; ChinaFLUX
|Title||A dataset of actual evapotranspiration and water use efficiency of typical terrestrial ecosystems in China (2000 – 2010)|
|Data corresponding author||Yu Guirui (firstname.lastname@example.org)|
|Data authors||Zheng Han, Yu Guirui, Zhu Xianjin, Wang Qiufeng, Zhang Leiming, Chen Zhi, Sun Xiaomin, He Honglin, Su Wen, Wang Yanfen, Han Shijie, Zhou Guoyi, Zhao Xinquan, Wang Huimin, Ouyang Zhu, Zhang Xianzhou, Zhang Yangjian, Shi Peili, Li Yingnian, Zhao Liang, Zhang Yiping, Yan Junhua, Wang Anzhi, Zhang Junhui, Hao Yanbin, Zhao Fenghua, Zhang Fawei, Zhou Guangsheng, Lin Guanghui, Chen Shiping, Liu Shaomin, Zhao Bin, Jia Gensuo, Zhang Xudong, Zhang Yucui, Gu Song, Liu Wenzhao, Li Yan, Wang Wenjie, Yang Dawen, Zhang Jinsong, Zhang Zhiqiang, Zhao Zhonghui, Zhou Shiqiao, Guo Haiqiang, Shen Yanjun, Xu Ziwei, Huang Hui, Meng Ping|
|Time range||2000 – 2010|
|Geographical scope||Typical terrestrial ecosystems in China|
|Data volume||143 entries for actual evapotranspiration and 96 entries for water use efficiency|
|Data service system||<http://www.cnern.org.cn/data/meta?id=40573>;|
|Sources of funding||National Natural Science Foundation of China (31700414, 31500390), National Key Research and Development Program of China (2016YFA0600104), Strategic Priority Research Program of the Chinese Academy of Sciences (XDA19020302), Science and Technology Service Network Initiative of the Chinese Academy of Sciences (KFJ-SW-STS-169).|
|Dataset composition||The dataset consists of one data file with four sections in total: (1) basic information for each ecosystem, including ecosystem code, ecosystem name, province, latitude, longitude, altitude, ecosystem type, vegetation type, dominant species, mean annual temperature, and mean annual precipitation; (2) annual actual evapotranspiration data for the observational periods of each ecosystem; (3) annual mean water use efficiency data for the observational periods of each ecosystem; (4) references.|
Evapotranspiration (ET) is a central process in the terrestrial hydrological cycle and energy balance, and is closely coupled with the carbon cycle of terrestrial ecosystems.1-2 As an important indicator linking an ecosystem’s coupled carbon and water cycles, water use efficiency (WUE) is generally defined as the ratio of gross primary productivity (GPP) over evapotranspiration (ET) at the ecosystem scale,3-4 which is meaningful for understanding ecosystem-atmosphere interactions and water resource management. Therefore, data on the actual ET and WUE of terrestrial ecosystems is crucial for research into terrestrial carbon-water cycles, ecosystem management, ecosystem service assessment, global change, and other related research fields under the background of global climate change.5-6
A number of in situ observational methods for ascertaining GPP and ET have been widely applied at different spatial and temporal scales. Of these the eddy covariance (EC) method can measure the vegetation-atmosphere carbon and water fluxes at the ecosystem scale on a continuous and long-term basis with almost no empirical hypothesis.7-9 The GPP and ET data obtained from EC method have been widely accepted by micrometeorologists and ecologists. FLUXNET and several regional networks (e.g., AmeriFlux, ChinaFLUX) have been operating9 using EC as the main observation method, which makes it possible to explore the spatial-temporal variations in the regional actual ET and WUE based on the measurements of these networks.
China has utilized the EC method to measure carbon and water fluxes of typical ecosystems since the establishment of the Chinese terrestrial ecosystem flux observation and research network (ChinaFLUX) in 2002,10 filling an observational gap in the Asian monsoon region. Abundant carbon and water flux observations have been collected, which provide an important opportunity to construct a dataset of the actual ET and WUE of typical terrestrial ecosystems in China. Based on the long-term observation of ChinaFLUX sites and published data from other flux sites in China, we synthesized the eddy-covariance flux data in China and constructed a dataset of the actual ET and WUE of typical terrestrial ecosystems in China during 2000-2010. This can be used to provide data support for analyses on terrestrial carbon and water cycles, ecosystem management and evaluation, global change, and other related research at regional and even global scales.
By synthesizing ChinaFLUX observations and published data from other sites in China during 2000-2010, we obtained eddy-covariance carbon and water flux data from 45 typical ecosystems in China (Figure 1 shows the location information. Table 1 shows the basic information), and using these constructed an actual ET sub-dataset and a WUE sub-dataset. The actual ET sub-dataset contains 143 entries from 45 ecosystems, covering 14 forests, 12 grasslands, 11 croplands, 6 wetlands and 2 desert ecosystems. The WUE sub-dataset contains 96 entries from 34 ecosystems, covering 12 forests, 10 grasslands, 4 croplands, 6 wetlands and 2 desert ecosystems.
|Ecosystem Code||Ecosystem Name||Latitude (°N)||Longitude (°E)||Elevation (m)||Ecosystem Type|
|HB1||Haibei alpine meadow||37.6||101.3||3250||Grassland|
|HB2||Haibei shrubland meadow||37.66||101.33||3293||Grassland|
|XFS||Xilinhot Stipa krylovii steppe||44.13||116.33||1030||Grassland|
|Xi1||Xilinhot fenced steppe||43.55||116.68||1250||Grassland|
|Xi2||Xilinhot degraded steppe||43.55||116.67||1250||Grassland|
|XSBN1||Xishuangbanna rain forest||21.93||101.27||750||Forest|
|XSBN2||Xishuangbanna rubber plantation||21.93||101.27||750||Forest|
2.1 Data observation and process of ChinaFLUX
The ChinaFLUX program was launched in 2002, relying on the existing Chinese Ecosystem Research Network (CERN). ChinaFLUX fills an important regional gap and increases the number of ecosystem types in FLUXNET.10-11 The measurement system of ChinaFLUX sites is uniformly composed of an EC system and a meteorological measurement system. The Open-Path Eddy Covariance (OPEC) system is used to measure carbon and water fluxes at ChinaFLUX sites. The OPEC system is composed of an open-path fast response infrared CO2/H2O analyzer (Li-7500, Li-Cor Inc., Lincoln, Nebraska, USA), a three-dimensional sonic anemometer (CSAT3, Campbell Scientific Inc., Logan, Utah, USA), and a data logger (CR5000, Campbell Scientific Inc., Logan, Utah, USA). All signals are sampled with a frequency of 10 Hz and then calculated and recorded at 30 min intervals. Standard meteorological variables are measured synchronously and recorded with a data logger (CR10X and CR23X, Campbell Scientific Inc., Logan, Utah, USA) at 30 min intervals, including solar radiation, net radiation, photosynthetically active radiation, air temperature, air humidity, wind speed, wind direction, precipitation, soil temperature, soil moisture, soil heat flux, etc.
The routine processing procedures recommended by ChinaFLUX were applied to process the raw 30 min eddy flux data (Figure 2), including coordinate rotation, Webb-Pearman-Leuning (WPL) correction, storage term calculation, outlier filter and gap filling10. The coordinate rotation was used to make the average vertical wind speed zero and to force the horizontal wind to the mean wind direction.7,12-13 WPL correction was used to adjust the effects of density change on CO2 and H2O fluxes.7,14 The storage flux below the EC height was calculated for the forest ecosystems.15-16 Spurious data were removed from the data series if the instrument performance and experimental conditions were abnormal, using flux threshold, precipitation events, standard deviation, and low turbulence flux as the criteria. The gaps in the flux data series were filled using the following methods. Short data gaps (<2 h) in the carbon and water flux data were filled with linear interpolation, and longer gaps in the water flux data were filled using a look-up table method. The non-linear regression method was applied for the longer gaps in the carbon flux data,17 so that daytime gaps were filled using a rectangular hyperbola function between carbon flux and photosynthetically active radiation, and the nighttime gaps were filled using the exponential relationship between ecosystem respiration (Re) and temperature.
Fig.2 Flow chart showing the data processing of carbon and water fluxes in ChinaFLUX
Notes: NEE = net ecosystem exchange, GPP = gross primary productivity, ET = evapotranspiration, WUE = water use efficiency. 'wpl' indicates data after WPL correction, and 's' as storage term corresponding to NEE or ET.
In order to obtain the ecosystem GPP data, the net ecosystem exchange (NEE, i.e., carbon flux) data measured using the eddy covariance method was separated into GPP and Re using a non-linear regression method18. First, the nighttime NEE measurements were used to determine the coefficients in the Re equation, which were the same in the gap-filling regression equation, and then the daytime and nighttime Re data were calculated. Second, GPP data was estimated as the sum of daytime NEE and daytime Re for the same time period.
Based on the data collection and processing methods of ChinaFLUX above, we obtained the complete time series of 30 min GPP and ET (i.e., water flux) data from eight ecosystems. The 30 min GPP and ET data were collected to obtain annual GPP and ET data for a given ecosystem, and the ratio of annual GPP to annual ET was regarded as the annual mean WUE value for the corresponding year.
2.2 Collection of published flux data in China
In addition to the ChinaFLUX observations, we also collected published carbon and water flux data of other sites in China from the literature. We adopted the following methods to screen these data. First, GPP and ET data were uniformly measured using the EC method, and subsequently passed through a series of processing procedures performed by individual site researchers, including coordinate rotation, WPL correction, outlier filter and gap filling. Second, annual mean WUE value for a given ecosystem was calculated only when the annual GPP and ET were both available for the same year. Third, only sites with at least one year of continuous flux measurements were selected, and the actual observational period was recorded. For example, the observational period for the ecosystems of DLC and DLG is from December 2005 to November 2006.
The units of the GPP and ET data were uniformly transformed into g C m-2 yr-1 and kg H2O m-2 yr-1 (i.e., mm yr-1), respectively, and thus the WUE data had a unit of g C kg-1 H2O. We also collected the basic information for each ecosystem, including geographical factors (i.e., latitude, longitude and elevation), vegetation type, the dominant species, the mean annual air temperature, and the mean annual precipitation.
This dataset is composed of four Excel sheets as showed in Table 2:
(1) The ‘Ecosystem basic information’ sheet contains information on ecosystem code, ecosystem name, latitude, longitude, elevation, ecosystem type, vegetation type, dominant species, references, etc. Among them, the ecosystem was coded based on the initial letters of the ecosystem name; for instance, CBS is the acronym for Chang Bai Shan. The code representing ecosystem management measure or ecosystem type has been applied to distinguish between ecosystems with the same acronym. For instance, DLC and DLG represent the cropland and grassland ecosystem in Duolun, respectively. The vegetation type for each ecosystem was determined according to the relevant literature and vegetation map of China19. ‘√’ indicates that actual ET or WUE data is available for the given ecosystem in this dataset. The reference corresponds to the reference with the same number in the ‘Reference’ sheet.
(2) The ‘Actual evapotranspiration data’ contains annual actual ET values during observational period for each ecosystem. For example, the annual actual ET of CBS site in the year of 2003 is 520.56 mm.
(3) The ‘Water use efficiency data’ sheet contains annual mean WUE values during the observational period for each ecosystem. For example, the annual mean WUE of the CBS site in the year of 2003 is 2.62 g C kg-1 H2O.
(4) The ‘Reference’ sheet contains the detailed reference for the ‘Reference’ item in the ‘Ecosystem basic information’ sheet.
|Data Item||Data Type||Sample|
|Ecosystem basic information|
|Mean annual temperature (℃)||Number||3.6|
|Mean annual precipitation (mm yr1)||Number||695.3|
|Actual evapotranspiration data||Character||√|
|Water use efficiency data||Character||√|
|Actual evapotranspiration data|
|Annual actual ET (mm yr1)||Number||520.56|
|Water use efficiency data|
|Annual mean WUE (g C kg-1 H2O)||Number||2.62|
|Reference||Character||ZHANG et al. (2006)|
ChinaFLUX has established a series of strict measures to guarantee the quality of flux data and the operation of long-term network observations. First, the observation equipment, elements and methods are uniform and have been standardized at different sites. Second, multi-level data verification was established to guarantee the data quality. The ChinaFLUX sites turn over raw high frequency flux observations to the Synthesis Research Center of CERN after elementary examinations each year. The Synthesis Research Center of CERN then conducts further verification and assessment on the equipment performance and data quality, and exports the 30 min flux data with uniform formats. Finally, the routine processing procedures of ChinaFLUX were applied to the 30 min flux data (Figure 2) to ensure the reliability and consistency of the flux data from different ChinaFLUX sites.
For the quality control and assessment on the published data from other sites in China, the following methods were adopted to screen the published data: (1) The carbon and water flux data were uniformly measured using the EC method, and subsequently passed a series of data processing procedures performed by individual site researchers; (2) Only sites with at least one year of continuous flux measurements were selected; (3) Only peer-reviewed literature was used to guarantee the credibility of published data. At the same time, self-examination and expert review were utilized to further ensure the accuracy and reliability of the GPP and ET data from the literature.
The dataset can be used for research into terrestrial carbon and water cycles, ecosystem management and evaluation, global change, and other related research, and also provides ground-based observations for model verification. Readers can also conduct multi-site comparison studies by selecting sites from typical regions or ecosystem types.
It should be noted that the data processing techniques and methods for eddy flux data have not been universally recognized due to diverse land surfaces, vegetation characteristics, and climatic conditions. A researcher’s preferences (e.g., for parameter setting) could affect the calculation results even with the same data processing procedures. In this dataset, the carbon and water fluxes of ChinaFLUX sites were calculated with the routine processing procedures recommended by ChinaFLUX, which may differ from the calculations by the researchers from a given site. The GPP and ET data from the literature were calculated by different researchers using independent data quality control and data processing procedures. Thus, the differences in processing carbon and water fluxes may result in deviations in the actual evapotranspiration and water use efficiency data to some extent. The readers can refer to our published papers5-6 when having problems in using this dataset.
The dataset is available in the data resources service website of CERN (http://www.cnern.org.cn). After logged in, click ‘data for papers’ icon on the home page or select ‘paper data’ in the data resources section and then the reader can download data. The dataset is also available in the website of Science Data Bank online (http://www.sciencedb.cn/dataSet/handle/610).
We acknowledge CERN, ChinaFLUX, and all eddy-covariance flux sites involved in this dataset for contributing data and other support. We thank Professor He Nianpeng for suggestions about how to improve this paper.
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Zheng H, Yu G, Zhu X et al. A dataset of actual evapotranspiration and water use efficiency of typical terrestrial ecosystems in China (2000 – 2010). China Scientific Data 4(2019). DOI: 10.11922/csdata.2018.0034.zh