%0 Dataset
%T 2023–2025 Multi-physics Observation Dataset of Loess Slopes at Huoxiangou in Qingyang, the Xiaocha Formation in Xiji, and Luoyugou in Tianshui, Gansu
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/4513d00e-8104-434a-931d-810f21f21da7
%W NCDC
%R 10.12072/ncdc.loess.db7336.2026
%A ZHANG Fanyu
%K Loess Plateau;Extreme rainfall;Multi-physics monitoring;Pore water pressure;Lysimeter test;Smart management platform
%X To address the scientific problem of unclear transformation processes and disaster-causing mechanisms of the “atmospheric water–surface water–groundwater” system under extreme weather conditions on the Loess Plateau, this dataset establishes three observational stations: the Xiaochazu co-seismic landslide site in Xiji, Guyuan, Ningxia; the high-fill artificial loess slope at Huoxiangou in Qingyang, Gansu; and the Luoyugou evaporation–infiltration experimental site in Tianshui, Gansu. At these sites, we deploy monitoring of the eight standard meteorological elements, integrated temperature–moisture–tilt sensors, positive and negative pore-water pressure sensors, and laser displacement / FDR-based surface runoff monitoring, thereby realizing real-time acquisition, transmission, and visualization of the observation data.The dataset includes high-frequency, continuous observation records from: the Huoxiangou station in Qingyang, monitored from 16 July 2023 for a duration of 27 months; the Xiaochazu landslide station in Xiji, monitored from 16 July 2023 to 31 October 2024 for a duration of 15 months; and the Luoyugou landslide monitoring station in Tianshui, monitored from 22 October 2024 for a duration of 12 months. The total number of records reaches 239,196 for the Huoxiangou station, 136,512 for the Xiaochazu landslide station, and 101,670 for the Luoyugou station. The data cover eight meteorological indicators including precipitation, temperature, humidity, atmospheric pressure, and solar radiation, as well as matric suction and pore-water pressure, surface runoff, and slope tilt deformation.Compared with traditional single-parameter monitoring, this dataset features an integrated “site–element–platform” framework and a coupled multi-physical-field design. In particular, by developing a threaded coarse-sand surface probe, it overcomes the difficulty of accurately measuring negative pore-water pressure in sandy/silty loess. The data not only reveal the depth of infil