Westdc Logo

HiWATER: The Multi-Scale Observation Experiment on Evapotranspiration over heterogeneous land surfaces (MUSOEXE) Dataset - flux observation matrix (an eddy covariance system at Zhangye wetland Station) Chinese Version


This dataset contains the flux measurements from the Zhangye wetland station eddy covariance system (EC) in the flux observation matrix from 25 June to 26 September, 2012. The site (100.44640° E, 38.97514° N) was located in a wetland surface, which is near Zhangye city, Gansu Province. The elevation is 1460.00 m. The EC was installed at a height of 5.2 m; the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (Gill&Li7500A) was 0.25 m.

Raw data acquired at 10 Hz were processed using the Eddypro post-processing software (Li-Cor Company, http://www.licor.com/env/products/ eddy_covariance/software.html), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, angle of attack correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. Moreover, the observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC), which was proposed by Foken and Wichura [1996]: class 1 (level 0: Δst<30 and ITC<30), class 2 (level 1: Δst<100 and ITC<100), and class 3 (level 2: Δst>100 and ITC>100), representing high-, medium-, and low-quality data, respectively. In addition to the above processing steps, the half-hourly flux data were screened in a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data before or after 1 h of precipitation were rejected; (3) incomplete 30 min data were rejected when the missing data constituted more than 3% of the 30 min raw record; and (4) data were rejected at night when the friction velocity (u*) was less than 0.1 m/s. There were 48 records per day; the missing data were replaced with -6999. Moreover, suspicious data were marked in red.

The released data contained the following variables: data/time, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m^3), CO2 mass density (CO2, mg/m^3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m^2), latent heat flux (LE, W/m^2), carbon dioxide flux (Fc, mg/ (m^2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xlsx format.

For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.


CitationsHelp

  1. Liu SM, Xu ZW, Song LS, Zhao QY, Ge Y, Xu TR, Ma YF, Zhu ZL, Jia ZZ, Zhang F. Upscaling evapotranspiration measurements from multi-site to the satellite pixel scale over heterogeneous land surfaces. Agricultural and Forest Meteorology, 2016, 230-231, 97-113. doi:10.1016/j.agrformet.2016.04.008.DetailDownload
  2. Xu ZW, Liu SM, Li X, Shi SJ, Wang JM, Zhu ZL, Xu TR, Wang WZ, Ma MG. Intercomparison of surface energy flux measurement systems used during the HiWATER-MUSOEXE. Journal of Geophysical Research, 2013,118, 13140-13157, doi:10.1002/2013JD020260.DetailDownload

Related Publications (Recommended by Author)

  1. Li X, Liu SM, Xiao Q, Ma MG, Jin R, Che T, Wang WZ, Hu XL, Xu ZW, Wen JG, Wang LX. A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system. Scientific Data, 2017, 4: 170083. doi:10.1038/sdata.2017.83.Detail Download
  2. Li X, Cheng GD, Liu SM, Xiao Q, Ma MG, Jin R, Che T, Liu QH, Wang WZ, Qi Y, Wen JG, Li HY, Zhu GF, Guo JW, Ran YH, Wang SG, Zhu ZL, Zhou J, Hu XL, Xu ZW. Heihe Watershed Allied Telemetry Experimental Research (HiWATER): Scientific objectives and experimental design. Bulletin of the American Meteorological Society, 2013, 94(8): 1145-1160, 10.1175/BAMS-D-12-00154.1.Detail Download
  3. Xu ZW, Ma YF, Liu SM, Shi SJ, Wang JM. Assessment of the energy balance closure under advective conditions and its impact using remote sensing data. Journal of Applied Meteorology and Climatology, 2017, 56: 127-140, doi: 10.1175/JAMC-D-16-0096.1.Detail Download
  4. Liu SM, Xu ZW, Wang WZ, Bai J, Jia Z, Zhu M, Wang JM. A comparison of eddy-covariance and large aperture scintillometer measurements with respect to the energy balance closure problem. Hydrology and Earth System Sciences, 2011, 15(4): 1291-1306. doi:10.5194/hess-15-1291-2011.Detail Download
  5. Liu SM, Xu ZW, Zhu ZL, Jia ZZ, Zhu MJ. Measurements of evapotranspiration from eddy-covariance systems and large aperture scintillometers in the Hai River Basin, China. Journal of Hydrology, 2013, 487, 24-38.Detail Download
  6. Wang JM, Zhuang JX, Wang WZ, Liu SM, Xu ZW. Assessment of uncertainties in eddy covariance flux measurement based on intensive flux matrix of HiWATER-MUSOEXE. IEEE Geoscience and Remote Sensing Letters, 2015, 12 (2), 259-263. doi:10.1109/LGRS.2014.2334703Detail Download
  7. Song LS, Liu SM, Zhang X, Zhou J, Li MS. Estimating and Validating Soil Evaporation and Crop Transpiration During the HiWATER-MUSOEXE. IEEE Geoscience and Remote Sensing Letters, 2015, 12 (2), 334-338. doi:10.1109/LGRS.2014.2339360Detail Download
  8. Ma YF, Liu SM, Zhang F, Zhou J, Jia ZZ. Estimations of regional surface energy fluxes over heterogeneous oasis-desert surfaces in the middle reaches of the Heihe River during HiWATER-MUSOEXE. IEEE Geoscience and Remote Sensing Letters, 2015, 12(3), 671-675. doi:10.1109/LGRS.2014.2356652Detail Download
  9. Xu TR, Bateni S.M., Liang SL. Estimating turbulent heat fluxes with a weak-constraint data assimilation scheme: A case study (HiWATER-MUSOEXE). IEEE Geoscience and Remote Sensing Letters, 2015, 12 (1), 68-72.doi:10.1109/LGRS.2014.2326180Detail Download
  10. Ge Y, Liang YZ, Wang JH, Zhao QY, Liu SM. Upscaling sensible heat fluxes with area-to-area regression kriging.  IEEE Geoscience and Remote Sensing Letters, 2015, 12(3), 656-660.doi:10.1109/LGRS.2014.2355871Detail Download
  11. Gao SG, Zhu ZL, Liu SM, Jin R, Yang GC, Tan L. Estimating spatial distribution of soil moisture based on Bayesian maximum entropy method with auxiliary data from remote sensing. International Journal of Applied Earth Observation and Geoinformation, 2014, 32, 54-66. doi:10.1016/j.jag.2014.03.003Detail Download
  12. Bai, J., Jia, L., Liu, S., Xu, Z., Hu, G., Zhu, M., Song, L.. Characterizing the Footprint of Eddy Covariance System and Large Aperture Scintillometer Measurements to Validate Satellite-Based Surface Fluxes. IEEE Geoscience and Remote Sensing Letters, 2015, 12(5), 943-947. doi:10.1109/LGRS.2014.2368580Detail Download
  13. Xu TR, Liu SM, Xu ZW, Liang SL, Xu L. A dual-pass data assimilation scheme for estimating surface fluxes with FY3A-VIRR land surface temperature. Sci. China Earth Sci., 2015, 58(2), 211-230, doi: 10.1007/s11430-014-4964-7.Detail Download
  14. Hu MG, Wang JH, Ge Y, Liu MX, Liu SM, Xu ZW, Xu TR. Scaling Flux Tower Observations of Sensible Heat Flux Using Weighted Area-to-Area Regression Kriging. Atmosphere 2015, 6, 1032-1044.Detail Download
  15. Xu T, Liu S, Xu L, Chen Y, Jia Z, Xu Z, Nielson J. Temporal Upscaling and Reconstruction of Thermal Remotely Sensed Instantaneous Evapotranspiration. Remote Sensing. 2015, 7(3):3400-3425. doi:10.3390/rs70303400Detail Download
  16. Song LS, Liu SM, William Kustas P, Zhou J, Ma YF. Using the Surface Temperature-Albedo Space to Separate Regional Soil and Vegetation Temperatures from ASTER Data. Remote Sensing, 2015, 7(5):5828-5848. doi:10.3390/rs70505828Detail Download
  17. Zhou J, Li MS, Liu SM, Jia ZZ, Ma YF. Validation and performance evaluations of methods for estimating land surface temperatures from ASTER data in the middle reach of the Heihe River Basin, Northwest China. Remote Sensing, 2015, 7, 7126-7156.Detail Download
  18. Li Y, Sun R, Liu SM. Vegetation Physiological Parameters Setting in the Simple Biosphere Model 2 (SiB2) for alpine meadows in upper reaches of Heihe River. SCIENCE CHINA, 2014,doi:10.1007/s11430-014-4909-1Detail Download
  19. Zhang L, Sun R, Xu ZW, Qiao C, Jiang GQ. Diurnal and Seasonal Variations in Carbon Dioxide Exchange in Ecosystems in the Zhangye Oasis Area, Northwest China. PLoS ONE, 2015, 10(3). doi:10.1371/journal.pone.0120660Detail Download

General introduction of HiWATER

  1. Li X, Cheng GD, Liu SM, Xiao Q, Ma MG, Jin R, Che T, Liu QH, Wang WZ, Qi Y, Wen JG, Li HY, Zhu GF, Guo JW, Ran YH, Wang SG, Zhu ZL, Zhou J, Hu XL, Xu ZW. Heihe Watershed Allied Telemetry Experimental Research (HiWATER): Scientific objectives and experimental design. Bulletin of the American Meteorological Society, 2013, 94(8): 1145-1160, 10.1175/BAMS-D-12-00154.1.Detail | Download

Limitations

The dataset is generated from the "Heihe Watershed Allied Telemetry Experimental Research (HiWATER)". User must have a clear statement in the article of the original data source and cite the dataset and papers in the Citation section.

Fund

  • National Natural Science Foundation of China (No. 91125002)

Online Resources



InformationFile list

  • File Format: *.xlsx
  • Size: 0.57 MB
  • Downloaded: 89
  • Viewed: 7806
  • Temporal Range: 2012-06-25 to 2012-09-26

Google Maps


Contacts


  • Last update: 2016-07-05
  • Download Metadata: Adobe PDF OpenOffice odt Word doc XML
  • Versions: 4