Digital Heihe

HiWATER: Dataset of hydrometeorological observation network (an observation system of meteorological elements gradient of Daman Superstation, 2016)

This data set contains the data of meteorological element gradient observation system of dashman superstation in the middle reaches of heihe hydrometeorological observation network from January 1, 2016 to December 31, 2016.The station is located in the farmland of daman irrigation district of zhangye city, gansu province.The longitude and latitude of the observation point are 100.3722e, 38.8555n and 1556m above sea level.The wind speed/direction, air temperature and relative humidity sensors are located at 3m, 5m, 10m, 15m, 20m, 30m and 40m respectively, with a total of 7 layers, facing due north.The barometer is installed at 2m;The tilting bucket rain gauge was installed at about 8m on the west side of the tower, with a height of 2.5m;The four-component radiometer is installed at 12m, facing due south;Two infrared thermometers are installed at 12m, facing due south and the probe facing vertically downward.Soil heat flow plate (self-calibration formal) (3 pieces) were buried in the ground 6cm in turn, 2m away from the tower body due south, two of which (Gs_2 and Gs_3) were buried between the trees, and one (Gs_1) was buried under the plants.The mean soil temperature sensor TCAV is buried 2cm and 4cm underground, facing due south and 2m away from the tower body.The soil temperature probe is buried at 0cm of the surface and 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm underground, 2m to the south of the meteorological tower.The soil water sensor is buried 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm underground, 2m to the south of the meteorological tower.The photosynthetic effective radiometer is installed at 12m with the probe facing vertically upward.Four other photosynthetically active radiometers were installed above and inside the canopy, 12m above the canopy (one probe vertically up and one probe vertically down), and 0.3m above the canopy (one probe vertically up and one probe vertically down), facing due south.

The observation items are: wind speed (WS_3m, WS_5m, WS_10m, WS_15m, WS_20m, WS_30m, WS_40m) (unit: m/s), wind direction (WD_3m, WD_5m, WD_10m, WD_15m, WD_20m, WD_30m, WD_40m) (unit:Air temperature and humidity (Ta_3m, Ta_5m, Ta_10m, Ta_15m, Ta_20m, Ta_30m, Ta_40m and RH_3m, RH_5m, RH_10m, RH_15m, RH_20m, RH_30m, RH_40m) (unit: Celsius, percentage), air pressure (Press) (unit: hpa), precipitation (Rain) (unit: mm), four-component radiation (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit:Watts/m2), surface radiant temperature (IRT_1, IRT_2) (unit: Celsius), average soil temperature (TCAV) (unit: Celsius), soil heat flux (Gs_1, Gs_2, Gs_3) (unit: watts/m2), soil moisture (Ms_2cm, Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_80cm, Ms_120cm, Ms_160cm) (unit:Soil temperature (Ts_0cm, Ts_2cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm)Mmol/m s) and the upward and downward photosynthetic effective radiation (PAR_D_up, PAR_D_down) under the canopy (in mmol/m s).

Processing and quality control of observed data :(1) ensure 144 pieces of data every day (every 10min), and mark by -6999 in case of data missing;The sensor in the soil part was adjusted and the data could not be used;(2) excluding the time with duplicate records;(3) data that obviously exceeds the physical significance or the range of the instrument is deleted;(4) the part marked with red letter in the data is the data in question;(5) date and time have the same format, and date and time are in the same column.For example, the time is: 2016-6-10-10:30;(6) the naming rule is: AWS+ site name.

For information of hydrometeorological network or station, please refer to Liu et al. (2018), and for observation data processing, please refer to Liu et al. (2011).

Data Citations
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Related Literatures:

1. Liu, S.M., Li, X., Xu, Z.W., Che, T., Xiao, Q., Ma, M.G., Liu, Q.H., Jin, R., Guo, J.W., Wang, L.X., Wang, W.Z., Qi, Y., Li, H.Y., Xu, T.R., Ran, Y.H., Hu, X.L., Shi, S.J., Zhu, Z.L., Tan, J.L., Zhang, Y., & Ren, Z.G. (2018). The Heihe Integrated Observatory Network: A Basin-Scale Land Surface Processes Observatory in China. Vadose Zone Journal, 17(1), 180072. doi:10.2136/vzj2018.04.0072.(View Details |Download )

2. Liu, S.M., Xu, Z.W., Wang, W.Z., Bai, J., Jia, Z., Zhu, M., & Wang, J.M. (2011). A comparison of eddy-covariance and large aperture scintillometer measurements with respect to the energy balance closure problem. Hydrology and Earth System Sciences, 15(4), 1291-1306.(View Details |Download )

Cite as:

Liu, S., Li, X., Che, T., Xu, Z., Ren, Z., Tan, J. (2017). < b>HiWATER: Dataset of hydrometeorological observation network (an observation system of meteorological elements gradient of Daman Superstation, 2016)</b>2017. doi: 10.3972/hiwater.455.2017.db. (Download the reference： RIS | Bibtex )

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

References literature

1.Zhou, J., Li, M.S., Liu, S.M., Jia, Z.Z., &Ma, Y.F. (2015). 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, 7, 7126-7156. (View Details )

2.Li, X., Liu, S.M., Xiao, Q., Ma, M.G., Jin, R., Che, T., Wang, W.Z., Hu, X.L., Xu, Z.W., Wen, J.G., Wang, L.X. (2017). A multiscale dataset for understanding complex eco-hydrological processes in a heterogeneous oasis system. Scientific Data, 4, 170083. doi:10.1038/sdata.2017.83. (View Details |Download)

3.Su, P.X., Yan, Q.D., Xie, T.T., Zhou,Z.J., & Gao, S. (2012). Associated growth of C3 and C4 desert plants helps the C3 species at the cost of the C4 species. Acta Physiologiae Plantarum, 34(6), 2057-2068. (View Details )

4.Song, L.S., Kustas WP, Liu, S.M., Colaizzi PD, Nieto H, Xu, Z.W., Ma, Y.F., Li, M.S., Xu, T.R., Agam, N., Tolk, J., & Evett, S. (2016). Applications of a thermal-based two-source energy balance model using Priestley-Taylor approach for surface temperature partitioning under advective conditions. Journal of Hydrology, doi:10.1016/j.jhydrol.2016.06.034. (View Details )

5.Xu, T.R., Bateni, S.M., & Liang, S.L. (2015). Estimating turbulent heat fluxes with a weak-constraint data assimilation scheme: A case study (HiWATER-MUSOEXE). IEEE Geoscience and Remote Sensing Letters, 12(1), 68-72. (View Details )

6.Song, L.S., Liu, S.M., Kustas, W.P., Zhou, J., Xu, Z.W., Xia, T., & Li, M.S. (2016). Application of remote sensing-based two-source energy balance model for mapping field surface fluxes with composite and component surface temperatures. Agricultural and Forest Meteorology, 230-231, 8-19. (View Details |Download)

7.Zhang, L., Sun, R., Xu, Z.W., Qiao, C., &Jiang, G.Q. (2015). Diurnal and Seasonal Variations in Carbon Dioxide Exchange in Ecosystems in the Zhangye Oasis Area, Northwest China. PLOS ONE, 10(6). (View Details )

8.Bai, J., Jia, L., Liu, S., Xu, Z., Hu, G., Zhu, M., &Song, L. (2015). Characterizing the Footprint of Eddy Covariance System and Large Aperture Scintillometer Measurements to Validate Satellite-Based Surface Fluxes. IEEE Geoscience and Remote Sensing Letters, 12(5), 943-947. (View Details |Download)

9.Xu, Z.W., Liu, S.M., Li, X., Shi, S.J., Wang, J.M., Zhu, Z.L., Xu, T.R., Wang, W.Z., &Ma, M.G. (2013). Intercomparison of surface energy flux measurement systems used during the HiWATER-MUSOEXE. Journal of Geophysical Research, 118, 13140-13157. (View Details |Download)

10.Song, L.S., Liu, S.M., William Kustas, P., Zhou, J., &Ma, Y.F. (2015). Using the Surface Temperature-Albedo Space to Separate Regional Soil and Vegetation Temperatures from ASTER Data. Remote Sensing, 7(5), 5828-5848. (View Details |Download)

11.Zhang, Q., Sun, R., Jiang, G.Q., Xu, Z.W., & Liu, S.M. (2016). Carbon and energy flux from a Phragmites australis wetland in Zhangye oasis-desert area, China. Agricultural and Forest Meteorology, 230-231, 45-57. (View Details )

12.Liu, S.M., Xu, Z.W., Song, L.S., Zhao, Q.Y., Ge, Y., Xu, T.R., Ma, Y.F., Zhu, Z.L., Jia, Z.Z., &Zhang, F. (2016). Upscaling evapotranspiration measurements from multi-site to the satellite pixel scale over heterogeneous land surfaces. Agricultural and Forest Meteorology, 230-231, 97-113. (View Details |Download)

13.Xu, Z.W., Ma, Y.F., Liu, S.M., Shi, S.J., &Wang, J.M. (2017). Assessment of the energy balance closure under advective conditions and its impact using remote sensing data. Journal of Applied Meteorology and Climatology, 56, 127-140. (View Details |Download)

14.Li Xin, Liu Shaomin, Ma Mingguo, Xiao Qing, Liu Qinhuo, Jin Rui, Che Tao. HiWATER: An Integrated Remote Sensing Experiment on Hydrological and Ecological Processes in the Heihe River Basin. Advances in Earth Science, 2012, 27(5): 481-498. (View Details |Download)

15.Wang, J.M., Zhuang, J.X., Wang, W.Z., Liu, S.M., &Xu, Z.W. (2015). Assessment of uncertainties in eddy covariance flux measurement based on intensive flux matrix of HiWATER-MUSOEXE. IEEE Geoscience and Remote Sensing Letters, 12(2), 259-263. (View Details )

16.Song, L.S., Liu, S.M., Zhang, X., Zhou, J., & Li, M.S. (2015). Estimating and Validating Soil Evaporation and Crop Transpiration During the HiWATER-MUSOEXE. IEEE Geoscience and Remote Sensing Letters, 12(2), 334-338. (View Details |Download)

17.Ge, Y., Liang, Y.Z., Wang, J.H., Zhao, Q.Y., &Liu, S.M. (2015). Upscaling sensible heat fluxes with area-to-area regression kriging. IEEE Geoscience and Remote Sensing Letters, 12(3), 656-660. (View Details )

18.Hu, M.G., Wang, J.H., Ge, Y., Liu, M.X., Liu, S.M., Xu, Z.W., &Xu, T.R. (2015). Scaling Flux Tower Observations of Sensible Heat Flux Using Weighted Area-to-Area Regression Kriging. Atmosphere, 6(8), 1032-1044. (View Details |Download)

19.Gao, S.G., Zhu, Z.L., Liu, S.M., Jin, R., Yang, G.C., Tan, L. (2014). 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, 32, 54-66. doi:10.1016/j.jag.2014.03.003. (View Details )

20.Ma, Y.F., Liu, S.M., Zhang, F., Zhou, J., & Jia, Z.Z. (2015). 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, 12(3), 671-675. doi:10.1109/LGRS.2014.2356652. (View Details )

21.Xu, T., Liu, S., Xu, L., Chen ,Y., Jia, Z., Xu, Z., &Nielson, J. (2015). Temporal Upscaling and Reconstruction of Thermal Remotely Sensed Instantaneous Evapotranspiration. Remote Sensing, 7(3), 3400-3425. (View Details |Download)

22.Liu, S.M., Xu, Z.W., Zhu, Z.L., Jia, Z.Z., &Zhu, M.J. (2013). Measurements of evapotranspiration from eddy-covariance systems and large aperture scintillometers in the Hai River Basin, China. Journal of Hydrology, 487, 24-38. (View Details )

23.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. (View Details )

24.Li, Y., Sun, R., &Liu, S.M. (2015). Vegetation Physiological Parameters Setting in the Simple Biosphere Model 2 (SiB2) for alpine meadows in upper reaches of Heihe River. Science China Earth Sciences, 58(5), 755-769. (View Details |Download)

25.Wang, Binbin, Ma, Yaoming, Chen, Xuelong, Ma, Weiqiang, Su, Zhongbo, Menenti, Massimo. Observation and simulation of lake-air heat and water transfer processes in a high-altitude shallow lake on the Tibetan Plateau. Journal of Geophysical Research: Atmospheres, 2015, 120(24):2015JD023863. doi:10.1002/2015JD023863 (View Details )

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