针对黄土高原极端天气情景下“天上水—地表水—地下水”转化过程及其致灾机理不明的科学问题，本数据建立宁夏固原西吉小岔组同震滑坡、甘肃庆阳火巷沟高填方人工黄土边坡与甘肃天水罗玉沟蒸渗科学试验三处观测站，分别布设气象八要素监测、温度–水分–倾斜联合传感、正负孔隙水压力传感及激光位移式/FDR感应式地表径流监测，并实现观测数据的实时采集、传输与展示。
数据内容涵盖庆阳火巷沟监测站点自2023年7月16日开始观测，观测时间长达27个月、西吉小岔组滑坡站点自2023年7月16日至2024年10月31日，观测时间长达15个月和天水罗玉沟滑坡监测站点自2024年10月22日开始观测，观测时间达12个月的高频连续观测记录，其中庆阳火巷沟监测站点观测数据量达239196条、西吉小岔组滑坡站点观测数据量达136,512条以及天水罗玉沟滑坡监测站点观测数据量达101670条，数据包含大气降雨、温度、湿度、大气压、太阳辐射等8个气象指标、基质吸力与孔隙水压力以及地表径流与斜坡倾斜变形数据。\n
相较于传统单一物理量监测，该数据集具备“站点—要素—平台”一体化与多物理场耦合特征，特别是通过研制螺纹式粗砂表面探头解决了砂质/粉质黄土负孔压难以精确获取的难题，数据不仅揭示了入渗影响深度与时滞规律，还可直接用于黄土区水文—陆气耦合模型参数化、灾害动力学模拟校验及区域滑坡预警阈值的精细化研究 。
", "ds_source": "数据来源于兰州大学联合陕西省地质调查院建设的黄土体灾变效应科学观测站实测数据集。该观测网络由宁夏固原西吉小岔组同震滑坡、甘肃庆阳火巷沟高填方人工黄土边坡及甘肃天水罗玉沟蒸渗科学试验场三处典型黄土台塬与地貌分区站点组成。各站点均布设了气象八要素监测、温度–水分–倾斜联合传感、正负孔隙水压力传感及激光位移式/FDR感应式地表径流监测。在西吉小岔组滑坡体，后缘与前缘分别布设气象、地表径流与多深度正/负孔压传感，联合温度—水分—倾斜监测，以刻画干旱区浅层地下水—滑坡体对极端气候的响应；在庆阳火巷沟高填方边坡，除既有气象与位移外，新增地下水与地表径流监测，面向工程填方体的雨热响应规律与稳定性评估，且针对粉质/砂质黄土使用了改良的螺纹式粗砂表面探头以提升基质吸力监测精度；天水罗玉沟人工黄土边坡依托蒸渗科学试验系统，构建“一体化蒸散—入渗—地表/地下径流”联合观测，直接服务水平衡闭合与水文模型校验。项目构建了智慧管理平台，实现实时采集—存储—传输—展示—共享—分享功能。
", "ds_process_way": "（1）布设气象八要素、温度–水分–倾斜联合传感及激光/FDR地表径流监测设备，构建“站点—要素—平台”一体化观测体系，将多物理场参数的采样频率统一设定为10分钟/样，利用智慧管理平台实现数据的实时采集、传输、存储与可视化展示。（2）通过监测数据，分析庆阳火巷沟高填方黄土边坡、西吉小岔组滑坡同震历史黄土滑坡和天水罗玉沟黄土边坡滑坡多物理场参数变化规律。（3）选择典型时段开展了两组黄土高原不同地貌单元监测站点多物理场参数对比分析，并采用皮尔森相关性系数分析气象指标与不同深度孔隙水压力的相关性。（4）选取降雨频繁月份的多物理参数进行随时间变化的规律分析。（5）通过构建响应效率指数REI与降雨强度拟合模型对监测周期内的多物理参数进行降雨的响应分析。（6）通过分析异常数据对监测周期内的多物理参数进行气候变化的异常规律分析并开展了Granger因果检验。（7）通过分析庆阳站监测数据对多物理参数进行了对干汛两期的变化规律分析。
", "ds_quality": "（1）观测站位于庆阳市火巷沟，为了更好去理解黄土高原不同地貌单元、不同土性、不同成灾体对极端天气的孕灾响应规律，本项目建设了甘肃庆阳火巷沟黄土填方边坡观测站，在原有气象和地表位移观测的基础上，增加了地下水和地表径流的观测；为了解决地表径流精准观测的难题，采用FDR水分感应的地表径流观测；同时，针对砂质/粉质黄土负孔压难以精确获取的问题，已研制螺纹式粗砂表面探头，并将基质吸力量程由100kPa提升至150kPa，以提高不同土性条件下的观测精度与稳定性。根据实际观测采集的数据进行图表绘制与多参数分析。（2）观测站位于宁夏西吉小岔组，为了探究在干旱区黄土边坡水分和浅层地下水位对黄土高原极端气候变化的响应规律，本项目建设在滑坡后缘布设了气象站、激光地表径流仪、孔隙水压力的组合观测体系；在滑坡前缘布设了温度-水分-倾斜联合观测仪和孔隙水压力的组合观测体系。气象站包括大气降雨、温度、湿度、大气压、太阳辐射等8个气象指标，保证了可以提供现场实时的观测数据，还可以为后期大气-植被-土壤相互作用模型验证提供气象输入数据。根据实际观测采集的数据进行图表绘制与多参数分析。（3）观测站位于天水市黄河水土保持治理监督局罗玉沟试验场，结合罗玉沟大型黄土边坡蒸渗试验系统，本研究在观测台前站布设了气象站，在边坡后缘布设了温度-水分-倾斜联合观测仪和激光地表径流仪的组合观测体系；其中不同深度的温度、水分及边坡倾斜变化，多个气象指标观测，结合蒸渗试验系统水文循环中的蒸散发、入渗、地表径流和地下径流形成大气-植被-土壤相互作用的水平衡体系，为水平衡模型以及水文模型的开发和验证提供数据基础。根据实际观测采集的数据进行图表绘制与多参数分析。
", "ds_acq_start_time": "2023-07-16 00:00:00", "ds_acq_end_time": "2024-10-31 00:00:00", "ds_acq_place": "宁夏西吉小岔组、甘肃庆阳火巷沟和甘肃天水罗玉沟", "ds_acq_lon_east": null, "ds_acq_lat_south": null, "ds_acq_lon_west": null, "ds_acq_lat_north": null, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 98315001, "ds_files_count": 0, "ds_format": "*.xlsx，*.csv", "ds_space_res": "", "ds_time_res": "秒", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "4513d00e-8104-434a-931d-810f21f21da7.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": "", "organization_id": "bf138922-7121-438c-8d1b-19d5f751c907", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967592", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "140", "410.30" ], "quality_level": 0, "publish_time": "2026-05-21 11:16:22", "last_updated": "2026-05-21 11:16:22", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.loess.db7336.2026", "i18n": { "en": { "title": "2023–2025 Multi-physics Observation Dataset of Loess Slopes at Huoxiangou in Qingyang, the Xiaocha Formation in Xiji, and Luoyugou in Tianshui, Gansu", "ds_format": "*.xlsx，*.csv", "ds_source": "The data were obtained from the in-situ dataset of the Scientific Observation Station for Loess Catastrophic Effects, jointly established by Lanzhou University and the Shaanxi Institute of Geological Survey. This network comprises three stations representing typical loess tableland and geomorphic zones: the Xiaocha Group co-seismic landslide in Xiji (Ningxia), the Huoxianggou high-fill artificial loess slope in Qingyang (Gansu), and the Luoyugou scientific experimental site for evapotranspiration and infiltration in Tianshui (Gansu). Each station is equipped with 8-element meteorological monitoring, combined temperature-moisture-tilt sensors, positive/negative pore water pressure sensors, and laser displacement or FDR inductive surface runoff monitoring. Specifically, at the Xiji landslide, meteorological, runoff, and multi-depth pore pressure sensors were deployed at the trailing and leading edges to characterize the response of shallow groundwater and the landslide body to extreme arid climates; at the Qingyang high-fill slope, groundwater and runoff monitoring were added to evaluate the hydrothermal response and stability of the engineered fill, utilizing improved threaded coarse-sand surface probes to enhance matric suction measurement in silty/sandy loess; and at the Tianshui site, an integrated “evapotranspiration-infiltration-surface/subsurface runoff” observation system was constructed to directly serve water balance closure analysis and hydrological model verification. Furthermore, a smart management platform was established to enable real-time data acquisition, storage, transmission, visualization, sharing, and dissemination.", "ds_quality": "
（1）The monitoring station is located in Huoxianggou, Qingyang City. To better understand how different geomorphic units, soil types, and failure bodies on the Loess Plateau respond to extreme weather in terms of hazard formation, this project has built the Huoxianggou Loess Fill Slope Monitoring Station in Qingyang, Gansu Province. On the basis of existing meteorological and surface displacement monitoring, groundwater and surface runoff observations have been added. To solve the problem of accurately monitoring surface runoff, an FDR (Frequency Domain Reflectometry) soil-moisture–based surface runoff monitoring method is adopted. Meanwhile, to address the difficulty of accurately obtaining negative pore water pressure in sandy/silty loess, a threaded coarse-sand surface probe has been developed, and the suction measurement range of the tensiometer has been increased from 100 kPa to 150 kPa, thereby improving the accuracy and stability of observations under different soil conditions. Charts are plotted and multi-parameter analyses are carried out based on the actual monitoring data.（2）The monitoring station is located in Xiaochazu, Xiji County, Ningxia. To investigate how soil moisture and shallow groundwater levels in loess slopes in arid regions respond to extreme climate change on the Loess Plateau, this project has established a combined monitoring system at the rear edge of a landslide, consisting of a weather station, a laser surface runoff meter, and pore water pressure observation. At the leading edge of the landslide, a combined system of temperature–moisture–tilt joint sensors and pore water pressure monitoring has been installed. The weather station records eight meteorological variables, including precipitation, air temperature, humidity, atmospheric pressure, and solar radiation, providing real-time on-site observation data and serving as meteorological input for subsequent validation of atmosphere–vegetation–soil interaction models. Charts are plotted and multi-parameter analyses are carried out based on the actual monitoring data.（3）The monitoring station is located at the Luoyugou Experimental Site of the Yellow River Soil and Water Conservation Supervision Bureau in Tianshui City. In combination with the large-scale loess slope evapotranspiration–infiltration experimental system at Luoyugou, this study has installed a weather station at the front of the observation platform, and at the rear edge of the slope has arranged a combined monitoring system of temperature–moisture–tilt joint sensors and a laser surface runoff meter. The temperature and moisture at different depths, slope tilt variations, and multiple meteorological indicators are observed and, together with evapotranspiration, infiltration, surface runoff, and subsurface runoff in the hydrological cycle of the evapotranspiration–infiltration system, form a water-balance framework for atmosphere–vegetation–soil interactions. This provides a data basis for the development and validation of water-balance models and hydrological models. Charts are plotted and multi-parameter analyses are carried out based on the actual monitoring data.", "ds_ref_way": "", "ds_abstract": "
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.\r\n
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.\r\n
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 infiltration influence and associated time-lag patterns, but can also be directly used for parameterization of hydro–land–atmosphere coupled models in loess regions, for calibration and validation of disaster dynamics simulations, and for refined studies on regional landslide early-warning thresholds.", "ds_time_res": "", "ds_acq_place": "Ningxia Xiji Xiaocha Formation, Gansu Qingyang Huoxianggou, and Gansu Tianshui Luoyugou", "ds_space_res": "", "ds_projection": "", "ds_process_way": "
（1）Meteorological eight-element sensors, integrated temperature–moisture–inclination joint sensing equipment, and laser/FDR surface runoff monitoring devices were deployed to establish an integrated “station–element–platform” observation system. The sampling frequency of all multi-physical-field parameters was uniformly set to one sample per 10 minutes. A smart management platform was used to realize real-time data acquisition, transmission, storage, and visualization.（2）Based on the monitoring data, the variation patterns of multi-physical-field parameters were analyzed for the high-fill loess slope at Huoxiangou in Qingyang, the coseismic historical loess landslide of the Xiaochazu Formation in Xiji, and the Luoyugou loess slope landslide in Tianshui.（3）Two groups of typical time periods were selected to conduct comparative analyses of multi-physical-field parameters from monitoring stations in different geomorphic units of the Loess Plateau. Pearson correlation coefficients were applied to analyze the correlations between meteorological indicators and pore-water pressures at different depths.（4）Multi-physical parameters during months with frequent rainfall were selected to analyze their temporal variation patterns.（5）A rainfall response analysis of multi-physical parameters during the monitoring period was conducted by constructing a response efficiency index (REI) and fitting it with rainfall intensity.（6）An abnormal-pattern analysis of multi-physical parameters under climate change during the monitoring period was carried out by identifying anomalous data, followed by Granger causality testing.（7）Through analysis of monitoring data from the Qingyang station, the variation patterns of multi-physical parameters during the dry and wet seasons were examined.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "recommendation_value": 0, "license_type": "https://creativecommons.org/licenses/by/4.0/", "doi_reg_from": "reg_local", "cstr_reg_from": "reg_local", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "黄土高原", "极端降雨", "多物理场监测", "孔隙水压力", "蒸渗试验", "智慧管理平台" ], "ds_subject_tags": [ "物理学", "工程地质学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国", "甘肃", "宁夏" ], "ds_time_tags": [ 2023, 2024 ], "ds_contributors": [ { "true_name": "张帆宇", "email": "Zhangfy@lzu.edu.cn", "work_for": "兰州大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "张帆宇", "email": "Zhangfy@lzu.edu.cn", "work_for": "兰州大学", "country": "中国" } ], "ds_managers": [ { "true_name": "张帆宇", "email": "Zhangfy@lzu.edu.cn", "work_for": "兰州大学", "country": "中国" } ], "category": "灾害" }