Content: Flow variation data of fine material dam break Data source: the test data are from the dam-breach model test of China Institute of Water Resources and Hydropower Research Collection location and method: China Institute of Water Resources and Hydropower Research. Collect and monitor various data through physical model test. Data quality description: the purpose of this test was to simulate the permeable piping dam break of the dam body, monitor the whole process of the break, and analyze the occurrence and development process of the break. The dam break mode of this test was the dam body permeable piping dam break. The initial piping position was located in the middle of the left side of the dam body. When piping occurs, the water storage height in the model reservoir was 4.6m and the water surface was 0.4m from the dam crest. The dam break process can be divided into seven stages.
XIE Dingsong
The data set uses the multi disaster risk assessment model for livestock in the Qinghai Tibet Plateau (Ye et al. 2019) to simulate the livestock deaths caused by the comprehensive superposition impact of multiple disasters on livestock, such as winter snow disaster, strong wind, low temperature, high altitude hypoxia and summer drought, and evaluate the expected annual deaths. The data can provide information on the death risk of multi disaster livestock around the Himalayas and the Asian water tower area. The data comes from China Meteorological science data sharing service system cn05 1. National Qinghai Tibet Plateau data center, Qinghai Tibet Plateau multi-source remote sensing synthetic 1km snow cover data set (1995-2018), mod13q1.006 vegetation index data, SRTM 1 arc second global elevation data.
YE Tao
The evaluation area of the data set is the Qinghai Tibet Plateau. The data set is based on the spatial distribution data set of geological hazard risk, earthquake risk, flood risk and freeze-thaw risk, with weights of 0.25, 0.4, 0.15 and 0.05 respectively. The disaster risk is divided into five levels, representing extremely low, low, medium, high and extremely high risk levels respectively. Finally, the risk evaluation results of multiple disasters in the Qinghai Tibet Plateau are obtained. Using the investigation data and public data, the multi disaster risk data of the Qinghai Tibet Plateau are obtained by weighted analysis of each single disaster risk data in ArcGIS.
LIU Lianyou
1) Data content: this data set is the landslide disaster data of Sanjiang Basin in the southeast of Qinghai Tibet Plateau; 2) Data source and processing method: this data set was independently interpreted by Dai Fuchu of Beijing University of technology using Google Earth; This data file is finally formed by remote sensing interpretation - on-site verification - re interpretation - re verification and other methods after 7 systematic interpretation. More than 5000 landslides have been verified on site with high accuracy; 4) This data has broad application prospects for hydropower resources development, traffic engineering construction and geological disaster evaluation in the three river basins in the southeast of Qinghai Tibet Plateau.
DAI Fuchu
Data content: spatial distribution, development mechanism and point database of river-blocking landslide in the Three Rivers region Collection scheme: First carry out Google Earth remote sensing interpretation, then carry out field verification and improve the interpretation signs in combination with field verification. Then carry out detailed interpretation, and collect the scale and geomorphic data including landslide source area, movement area and accumulation area. Then study and analyze the typical cases of river-blocking landslide, This reveals the engineering geological classification and genetic mechanism of river-blocking landslide in the Three Rivers rigion. Collection location: Sanjiang area of Qinghai Tibet Plateau and Sichuan University Collection time: October 1, 2018 to October 31, 2021
DENG Jianhui , ZHAO Siyuan
Data content: Monitoring of seepage infiltration line and analysis of seepage infiltration degree of dam break Data source: the data collection place is Sichuan. The experimental analysis was mainly completed in Sichuan University and Chengdu Ruyi Instrument Co., Ltd. The instruments used included high-speed camera, wave altimeter, electronic pressure measuring tube, pressure sensor, mechanical timer, etc. The collection time is 2021. Acquisition method: according to the indoor test, observe the evolution process of seepage development in the process of dam break of weir plug dam through electronic piezometer, pressure sensor and high-speed camera. Data quality description: carry out the stability model test of dam with different structures, and carry out the indoor test. According to the grading requirements of 14 working conditions, pile the dam body on the bottom plate of the water tank, and arrange multiple cameras to observe. During the process of clean water flowing into the water tank to wash the dam until the end of dam break, observe the coordinates of the infiltration process, and record the change process of the infiltration coordinates with time.
NIU Zhipan
Data content: monitoring of water level and flow velocity of dam break, and analysis of Froude number and flow process Data source: the data collection place is Sichuan. The experimental analysis was mainly completed in Sichuan University and Chengdu Ruyi Instrument Co., Ltd. The instruments used include high-speed camera, wave altimeter, electronic pressure measuring tube, pressure sensor, mechanical timer, etc. The collection time is 2021. Acquisition method: observe the process of field large-scale dam burst test through multiple high-speed cameras, wave altimeters, total head pressure sensors, mechanical timers and other instruments. Data quality description: relevant sensors were arranged in the field test, and real-time process dynamic observation was carried out. A total of 6 large-scale test conditions were observed, including water level and flow rate observation at 400 points. Then, Froude number and flow process were calculated and analyzed through flow rate and water level.
NIU Zhipan
Data content: Taking Baige landslide in 2018 as an example, this data simulated the down-hill migration and accumulation process of debris flow on the slope Data source: this numerical simulation data was collected and recorded by computer software (using open source code ESYS-Particle). Data quality description: the data were mainly images and video GIF files, which were processed by video editing and image processing software. Data application results: Taking the latest Dujiang landslide as an example, the simulation of the downward migration and accumulation process of debris flow along the slope will provide a theoretical basis for the evaluation of landslide disaster effect from the development of similar strata and slope structure.
XU Nuwen
Data content: this data used the open source code ESYS-Particle to simulate the interaction between debris flow and slit dam Data source: this numerical simulation data was collected and recorded by computer software (using open source code ESYS-Particle). Data quality description: the data were mainly images and video GIF files, which were processed by video editing and image processing software. Data application: four basic interaction stages of debris flow impacting slit dam were revealed: initial impact stage, uplift stage, accumulation stage and deposition stage. The interception efficiency of slit dam with different relative column spacing to particles of different shapes was analyzed.
XU Nuwen
Data content: Taking Baige landslide in 2018 as an example, the numerical simulation of typical river-blocking landslide was carried out Data source: the numerical simulation data were collected and recorded by computer software (massflow developed by Mountain Institute of Chinese Academy of Sciences). Data quality description: the data were mainly image JPG and video GIF files, which were processed by video editing and image processing software. Data application results: Taking the latest river blocking landslide as a case, the numerical simulation of typical river-blocking landslide will provide a theoretical basis for the evaluation of the disaster effect of river blocking landslide in the deep valley area developed from similar strata and slope structure.
XU Nuwen
1) The data content includes: high-speed friction test data of rock mass structural plane in the sliding source area of typical high-speed remote landslide, physical simulation test data of high-speed remote landslide fragmentation, high-speed ring shear test data of sliding belt in the circulation area of typical landslide, fine particle migration and reverse order physical simulation test data in the accumulation area of landslide, high-speed remote landslide numerical simulation system and evaluation data. 2) Data source and processing method: test data collection. 3) Data quality description: good - General. 4) Data application achievements and prospects: it can be used to study the initiation, movement and accumulation mechanism of high-speed and long-distance rock landslide in Qinghai Tibet Plateau, and simulate the whole process of landslide movement.
WEN Baoping
Data content: Storage capacity curve of the Hongshiyan, yibadao and xiaogangjian impoundment and flow hydrograph data of breach Data source: through literature search, classification, consolidation and compilation. Data quality description: through literature retrieval, data of four typical barrier lakes were compiled, including Hongshiyan barrier lake in Ludian, Yunnan, xiaogangjian (upper) barrier lake in Mianzhu County, Deyang City, Sichuan, and yibadao barrier lake in Mianzhu County, Deyang City, Sichuan. The basic parameters compiled here include: dam crest elevation, dam height, dam width and other basic parameters, as well as discharge channel parameters, dam grading, storage capacity curve, breach discharge hydrograph and other parameters, which were summarized and analyzed. It can provide a reference for the parameters of barrier lakes in the Qinghai Tibet Plateau.
ZHANG Xinhua
Data content: A large database of 1230 worldwide dam cases Data source: through literature search, classification, consolidation and compilation. Data quality description: classify and sort out the historical cases of weir plug dam from two aspects: qualitative description and quantitative description. The qualitative description includes the country, the name of the dam, the formation time, the type of landslide, the inducing factors, the type of dam body, the mechanism of collapse, etc; Quantitative description includes landslide volume, dam volume, dam height, dam length, dam width, barrier lake length, barrier lake volume, barrier dam life, breach depth, breach top width, breach bottom width, breach time, peak flow, casualties, etc.
ZHANG Xinhua
Data content: empirical formula calculation data of final bottom elevation of dam breach Data source: a large database containing 1230 dam cases around the world based on literature retrieval. Collection method: processing and fitting through Excel data processing software. Data quality description: in order to solve the problem of assigning the final bottom elevation of the dam breach, based on the collected data of dam height and breach depth in the dam database, combined with the classification method of overtopping breach dam body erosion proposed by briaud in 2008, the dams were divided into three types: high, medium and low erosion degrees. Then the dam height and breach depth of the dam plug dam with different erosion degrees were regressed, The empirical formula for the depths of dam breaches with different erosion degrees were also fitted, and then the final bottom elevations of dam breaches were determined.
ZHANG Xinhua
This data combines the direct economic loss risk assessment results of earthquake and geological disasters. According to the obtained loss assessment results, the study area is divided into nine categories according to the risk level, which are seismic geological low-risk area, geological medium seismic low-risk area, seismic medium geological low-risk area, seismic geological medium risk area, geological high epicenter risk area and seismic high quality low-risk area, Geological high seismic low risk area, seismic high quality low risk area and seismic geological high risk area. The data results of this multi disaster direct economic loss risk assessment provide a basis for the spatial distribution of direct economic losses in the Asian water tower area and the surrounding areas of the Himalayas in the future.
WU Jidong
This data includes the seismic data of the Qinghai Tibet Plateau, the Asian water tower region and the Himalayas region from 1971 to 2021, The main attributes include earthquake occurrence time (UTC), longitude, latitude, earthquake depth, magnitude, magnitude type and occurrence area. It is divided into shp files and tabular data, which can be more convenient for relevant personnel to use. This data can help relevant personnel understand the earthquake distribution on the Qinghai Tibet Plateau and interpret the relationship between earthquake occurrence location and relevant structural zones. This data is derived from https://earthquake.usgs.gov/data/pager/ , download by selecting the initial target area and time, export by using ArcGIS tools, filter and make according to the edited files of the scientific research area of the Qinghai Tibet Plateau.
LIU Jifu
1) The data content includes three stages of soil erosion intensity in Qinghai-Tibet Plateau in 1992, 2005 and 2015m the grid resolution is 300m.2) The data of soil erosion intensity are obtained by using the Chinese soil erosion prediction model (CSLE). The formula of soil erosion prediction model includes rainfall erosivity factor, soil erodibility factor, slope length factor, slope factor, vegetation cover and biological measure factor, engineering measure factor and tillage measure factor. Rainfall erodibility factors are calculated from the daily rainfall data by the US Climate Prdiction Center (CPC); soil erodibility factors, engineering measures factors and tillage measures factors are obtained from the first water conservancy census data; slope length factors and slope factors are obtained by resampling after calculating 30 m elevation data; vegetation coverage and biological measures factors are obtained by combining fractional vegetation cover with land use data and rainfall erodibility proportionometer. The fractional vegetation cover is calculated by MODIS vegetation index products through pixel dichotomy. 3) Compared with the data of soil erosion intensity in the same region in the same year, there is no significant difference and the data quality is good.4) the data of soil erosion intensity is of great significance for studying the present situation of soil erosion in Pan third polar 65 countries and better carrying out the development policy of the area along the way.
ZHANG Wenbo
The Slope Length and Stepness Factor (LS) dataset of Pan-third pole 20 country is calculated based on the free accessed 1 arc second resolution SRTM digital elevation data (Shuttle Radar Topography Mission, SRTM; the website is http://srtm.csi.cgiar.org）. After the pre-processing such as pseudo edge removal, filtering and noise removal, the LS factor with 7.5 arc second resolution was calculated with the LS factor algorithm in CSLE model and the LS calculation tool (LS_tool) developed in this project. The LS factor data of Pan-third pole 20 countries is the fundamental data for soil erosion rate calculation based on CSLE, and it also the fuandatmental data for analyzing the erosion topographic characteristics of Pan third pole 20 countries (such as macro distribution and micro pattern of elevation, slope and slope) . The dataset if of great importance for the analysis of geomorphic characteristics and geological disaster characteristics in this area.
YANG Qinke
1)The datase includes a 30-year (1986-2015) average rainfall erosivity raster data for 20 countries in key regions, with a spatial resolution of 300 meters. 2）The 0.5°×0.5° grid daily rainfall data generated by the Climate Prediction Center (CPC) based on global site data was used to calculate the rainfall erosivity R factor of 20 countries in key regions. 3）The daily rainfall data of 2358 weather stations nationwide from China Meteorological Administration from 1986 to 2015 was used to calculate the R value, and the R value calculated by establishing the CPC data source was rechecked and verified. It is found that the R value calculated by the CPC data system was low, and then it was revised, and the final data obtained was of good quality. 4）Rainfall erosivity R factor can be used as the driving factor of the CSLE model, and the data is of great significance for the simulation of soil erosion in 20 countries in key regions and the analysis of its spatial pattern.
ZHANG Wenbo
1)The dataset includes the grid data of vegetation coverage and biological measure factor B of 20 countries in key regions, with a spatial resolution of 300 meters. 2）The basic data source is the MODIS MOD13Q1 product from 2014 to 2016 with a spatial resolution of 250 m. Based on this, a 24-half month average vegetation coverage raster data during a 3 year period was calculated, and then the soil loss ratio was calculated according to the land type. The, the 24- half months rainfall erosivity was further weighted and averaged to obtain a grid map of vegetation coverage and biological measures B factor. 3）MOD13Q1 remote sensing vegetation data was processed by cloud removal. The calculated B factor was statistically analyzed by landuse types and rationality analyzed. The final data quality is good. 4）The factor B of vegetation coverage and biological measures reflects the impact of surface land use/vegetation coverage on soil erosion, and is of great significance for soil erosion simulation and spatial pattern analysis in 20 key regions.
ZHANG Wenbo
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