Digital Heihe

HiWATER: Dataset of hydrometeorological observation network (an observation system of meteorological elements gradient of A'rou superstation, 2015)

This data set contains the data of meteorological element gradient observation system of alou superstation, upstream of heihe hydrometeorological observation network, from January 1, 2015 to December 31, 2015.The station is located in caoban village, aru township, qilian county, qinghai province.The longitude and latitude of the observation point are 100.4643e, 38.0473n and 3033m above sea level.The air temperature, relative humidity and wind speed sensors are located at 1m, 2m, 5m, 10m, 15m and 25m respectively, with a total of six layers facing due north.The wind direction sensor is located at 10m, facing due north;The barometer is installed at 2m;The tilting bucket rain gauge is installed on the observation tower 40m of super aru station;The four-component radiometer is installed at 5m, facing due south;Two infrared thermometers are installed at 5m, facing due south, and the probe facing vertically downward.The photosynthetic effective radiometer is installed at 5m, facing due south, and the probe facing vertically upward.Part of the soil sensor is buried at 2m in the south direction of the tower body, and the soil heat flow plate (self-correcting formal) (3 pieces) are all buried at 6cm underground.The mean soil temperature sensor TCAV is buried 2cm and 4cm underground.The soil temperature probe is buried at the surface of 0cm and underground of 2cm, 4cm, 6cm, 10cm, 15cm, 20cm, 30cm, 40cm, 60cm, 80cm, 120cm, 160cm, 200cm, 240cm, 280cm and 320cm, among which the 4cm and 10cm layers have three repeats.The soil water sensor is buried underground 2cm, 4cm, 6cm, 10cm, 15cm, 20cm, 30cm, 40cm, 60cm, 80cm, 120cm, 160cm, 200cm, 240cm, 280cm and 320cm respectively, among which the 4cm and 10cm layers have three duplexes.

The observations included the following: air temperature and humidity (Ta_1 m, Ta_2 m, Ta_5 m, Ta_10 m, Ta_15 m and Ta_25 m; RH_1 m, RH_2 m, RH_5 m, RH_10 m, RH_15 m and RH_25 m) (℃ and %, respectively), wind speed (Ws_1 m, Ws_2 m, Ws_5 m, Ws_10 m, Ws_15 m and Ws_25 m) (m/s), wind direction (WD_2 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m2), infrared temperature (IRT_1 and IRT_2) (℃), photosynthetically active radiation (PAR) (μmol/(s m-2)), average soil temperature (TCAV, ℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm_1, Ts_4 cm_2, Ts_4 cm_3, Ts_6 cm, Ts_10 cm_1, Ts_10 cm_2, Ts_10 cm_3, Ts_15 cm, Ts_20 cm, Ts_30 cm, Ts_40 cm, Ts_60 cm, Ts_80 cm, Ts_120 cm, Ts_160 cm, Ts_200 cm, Ts_240 cm, Ts_280 cm and Ts_320 cm) (℃), and soil moisture (Ms_2 cm, Ms_4 cm_1, Ms_4 cm_2, Ms_4 cm_3, Ms_6 cm, Ms_10 cm_1, Ms_10 cm_2, Ms_10 cm_3, Ms_15 cm, Ms_20 cm, Ms_30 cm, Ms_40 cm, Ms_60 cm, Ms_80 cm, Ms_120 cm, Ms_160 cm, Ms_200 cm, Ms_240 cm, Ms_280 cm and Ms_320 cm) (%, volumetric water content).

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;Soil temperature and humidity, soil heat flux between September 9, 2015 to September 19, 2015 and September 30, 2015 to October 20, 2015 due to power supply problems, data missing;(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: June 10, 2015, 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).

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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. Che, T., Li, X., Liu, S., Li, H., Xu, Z., Tan, J., Zhang, Y., Ren, Z., Xiao, L., Deng, J., Jin, R., Ma, M., Wang, J., & Yang, X. (2019). Integrated hydrometeorological, snow and frozen-ground observations in the alpine region of the Heihe River Basin, China. Earth System Science Data, 11, 1483-1499(View Details |Download )

3. 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., Zhang, Y., Tan, J. (2016). < b>HiWATER: Dataset of hydrometeorological observation network (an observation system of meteorological elements gradient of A'rou superstation, 2015)</b>2016. doi: 10.3972/hiwater.308.2016.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.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 )

3.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 )

4.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 )

5.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)

6.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 )

7.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)

8.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)

9.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)

10.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 )

11.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)

12.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)

13.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)

14.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 )

15.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)

16.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 )

17.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)

18.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 )

19.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 )

20.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)

21.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 )

22.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 )

23.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)

24.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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