Soil moisture is one of the core variables in the water cycle. Although its variation is very small, for a precipitation process, soil moisture directly determines the transformation of precipitation into evaporation, runoff and groundwater, which is very important to finely simulate spatial-temporal dynamics of various variables in hydrological process and to accurately estimate water inflow in the upper reaches of Heihe River. This dataset includes soil moisture and temperature data observed by 40 nodes from July 2013 to December 2017. Each node in Babao River Basin has soil moisture observation at depth of 4cm and 20cm; some nodes also include observations at depth of 10 cm. The data observation frequency is 1 hour. The dataset can provide ground -based observations for hydrological simulation, data assimilation and remote sensing verification.
File name: the soil moisture data is stored in text format, and the name of the file is "WATERNET- xx.csv ” , where "xx" represents the node number, and the file contains all the observation data of the node.
Data reading mode: all the CSV files in the data set can be directly opened by text programs (such as Notepad).
JIN Rui, KANG Jian. Hourly soil moisture dataset observed by eco-hydrological sensor network in the upper reaches of Heihe River (2013-2017). National Tibetan Plateau Data Center, 2021. doi: 10.11888/Hydro.tpdc.271137. (Download the reference： RIS | Bibtex )
Related Literatures:1. Jin, R., Li, X., Yan, B., Li, X., Luo, W., Ma, M., Guo, J., Kang, J., Zhu, Z., & Zhao, S. (2014). A nested ecohydrological wireless sensor network for capturing the surface heterogeneity in the midstream areas of the heihe river basin, China. IEEE Geoscience and Remote Sensing Letters, 11(11), 2015-2019. DOI:10.1109/LGRS.2014.2319085.( View Details | Bibtex)
2. Kang, J., Jin, R., Li, X., Ma, C., Qin, J., & Zhang, Y. (2017). High spatio-temporal resolution mapping of soil moisture by integrating wireless sensor network observations and modis apparent thermal inertia in the babao river basin, China. Remote Sensing of Environment. 191, 232-245, 10.1016/j.rse.2017.01.027.( View Details | Bibtex)
3. Ge, Y., Wang, J., Heuvelink, G., Jin, R., Li, X., & Wang, J. (2015). Sampling design optimization of a wireless sensor network for monitoring ecohydrological processes in the babao river basin, China. International Journal of Geographical Information Science, 29, 92-110. DOI: 10.1080/13658816.2014.948446.( View Details | Bibtex)
Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.
Key Theory and Methods for Validation of Land Surface Remote Sensing Products (No:41531174)
Downloading Microwave Remote Sensing Products of Soil Moisture based on Area-to-Area Regression Kriging (No:41701419)
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| East: 101.16 | West: 100.10 |
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| South: 37.72 | North: 38.32 |
