The photos contain the disaster spots and work photos of the scientific research every day (Juue 15th, 2021-July 24 6th, 2021), and the questionnaire of each disaster spot (including landslide, collapse, debris flow, etc.). The disaster spots recorded every day are marked on the map, converted into KMZ format, and the distribution of disaster spots in the scientific research area is analyzed on GIS. The distribution of disaster points shows that rainfall-induced landslide, debirs flow and rockfall, flash flood disaster points are major located along along the eastern route and the intensity are dense in there. In addition, the transportation infrastructure and popultion are relative densely distributed along the earstern route, may be resulte in high comprehensively disaster risk.In the western route, there are major distributed sand disaster, also mass movement disasters such as landslde and rockfall. The above pictures, vedios, disaster point map and route map are recorded. The above data are intuitive data for researching scientific expeditions, also are the key input data and examine data. In addition, they are fundamental significance for objectively judging the types and distribution of disasters in the scientific expedition area, as well as disaster prevention and mitigation measures.
ZHANG Zhengtao
This data includes: 30m mountain flood comprehensive risk data, 30m mountain flood risk data, 30m mountain flood disaster bearing body data and 30m mountain flood vulnerability distribution data in the Himalayas. Based on the results of national investigation and evaluation of mountain flood disasters, the distribution of comprehensive risk indicators of mountain flood disasters in the study area, the distribution of mountain flood risk indicators in each administrative village, the distribution of mountain flood disaster bearing body indicators and the distribution of mountain flood vulnerability indicators are obtained, forming the comprehensive risk distribution data of mountain flood disasters in the Himalayas. This data is helpful to analyze the spatial variation characteristics and distribution law of mountain flood disaster. The zoning of mountain flood disaster risk plays a guiding role in the flood control management and deployment of flood control emergency departments.
WANG Zhonggen
This data set includes 1:1 million historical mountain flood disaster data in the Himalayas, 1:1 million mountain flood prevention and control area distribution data in the Himalayas, 1:1 million mountain flood zoning distribution data in the Himalayas, and 1:1 million key prevention and control area distribution data in the Himalayas. All data are based on the results of national mountain flood disaster investigation and evaluation, and obtain the information of historical mountain flood disaster occurrence time, location, disaster type, cause, longitude, latitude, quantity, distribution and number of victims in the study area, as well as the distribution data of mountain flood zoning, prevention and control area and key prevention and control areas in the study area, so as to form the distribution data set of historical mountain flood disaster in the Himalayas.
WANG Zhonggen
To fully implement the measures for the administration of the scientific data for the "government budget funding for formation of the scientific data shall, in accordance with the open as normal, not open for exception principle, by the competent department to organize the formulation of scientific data resources directory, the directory should be timely access to the national data sharing and data exchange platform, open to society and relevant departments to share, In the spirit of unimpeded military-civilian sharing channels for scientific data, and in accordance with the relevant requirements of relevant exchange standards and specifications, this code is now established for the second Comprehensive scientific investigation and research project on the Qinghai-Tibet Plateau. The main drafting unit of this code: Institute of Geographic Sciences and Natural Resources Research, CAS. Main draftsman of this specification: project group 9 of the second Comprehensive Scientific investigation and research Mission of qinghai-Tibet Plateau.
YANG Yaping
Log and image are unique and important primary data of field research, and also an important part of scientific data. In order to further standardize the collection, collation, warehousing and exchange of expedition logs and image data of the second Comprehensive scientific investigation and research project on the Qinghai-Tibet Plateau, and ensure the operability, organization and standardization of the warehousing of expedition logs and image data, this technical specification is formulated. This specification provides procedures and methods for the collection and collation of investigation logs and image data, including work preparation, field investigation, data collation and other requirements, in order to better serve the storage of investigation data. This specification applies to the collation and storage of log and image data of field investigations organized by the second Comprehensive scientific investigation and research project on the Qinghai-Tibet Plateau, and other relevant data formed by field investigations can also be carried out by reference to this technical specification.
YANG Yaping
Flood risk assessment data along Sichuan Tibet railway, including natural indicators, risk, vulnerability and risk assessment data. Data source: obtained from the earth big data science and Engineering website; Calculated and obtained according to DEM downloaded by USGS. Processing method: the maximum 24h precipitation with five-year return period is obtained by calculating the frequency according to the annual maximum 24h precipitation sequence in the assessment area; The river network index is obtained by cutting and processing the level 6 water network of Haihe River version in the assessment area; The risk is obtained by calculating the maximum 24h precipitation once in five years and the assignment of river network index; Vulnerability is obtained by weighting the data of population density, transportation cost and total GDP; Risk data is calculated based on risk and vulnerability weighting. Formulate digital processing operation specifications. In the process of processing, the operators are required to strictly abide by the operation specifications, and a special person is responsible for the quality review. The data integrity, logical consistency, position accuracy, attribute accuracy, edge connection accuracy and current situation all meet the requirements of relevant technical regulations and standards formulated by the State Bureau of Surveying and mapping, and the quality is excellent and reliable.
WANG Zhonggen
1) The work of automatically dividing a wide and complex geospatial area or even a complete watershed into repeatable and geomorphically consistent topographic units is still in the stage of theoretical concept, and there are great challenges in practical operation. Terrain unit is a further subdivision of topography and geomorphology, which can ensure the maximum uniformity of geomorphic features in slope unit and the maximum heterogeneity between different units. It is suitable for geomorphic or hydrological modeling, landslide detection in remote sensing images, landslide sensitivity analysis and geological disaster risk assessment. 2) Slope unit is an important type of topographic unit. Slope unit is defined as the area surrounded by watershed and catchment line. In fact, the area surrounded by watershed and catchment line is often multiple slopes or even a small watershed. Theoretically, each slope unit needs to ensure the maximum internal homogeneity and the maximum heterogeneity between different units. The slope unit is an area with obviously different topographic characteristics from the adjacent area. These topographic characteristics can be based on the characteristics of catchment or drainage boundary, slope and slope direction, such as ridge line, valley line, platform boundary, valley bottom boundary and other geomorphic boundaries. According to the high-precision digital elevation model, the slope unit with appropriate scale and quality can be drawn manually, but the manual drawing method is time-consuming and error prone. The quality of the divided slope unit depends on the subjective experience of experts, which is suitable for small-scale areas and has no wide and universal application value. Aiming at the gap in practical operation in this field, we propose an innovative modeling software system to realize the optimal division of slope units. Automatic division system of slope unit based on confluence analysis and slope direction division v1 0, written in Python programming language, runs and calculates as the grass GIS interpolation module, and realizes the automatic division of slope units in a given digital elevation data and a set of predefined parameters. 4) Based on python programming language, the code is flexible and changeable, which is suitable for scientific personnel with different professional knowledge to make a wide range of customization and personalized customization. In addition, the software can provide high-quality slope unit division results, reflect the main geomorphic characteristics of the region, and provide a based evaluation unit for fine landslide disaster evaluation and prediction. It can serve regional land use planning, disaster risk assessment and management, disaster emergency response under extreme induced events (earthquake or rainfall, etc.), and has great practical guiding significance for the selection of landslide monitoring equipment and the reasonable and effective layout and operation of early warning network. It can be popularized and applied in areas with serious landslide development.
YANG Zhongkang
1) In mountainous areas, due to the complex topographic and geological background conditions, landslides are very easy to occur triggered by external factors such as rainfall, snow melting, earthquake and human engineering activities, resulting in the loss of life and property and the destruction of the natural environment. In order to meet the safety of project site construction, the rationality of land use planning and the urgent needs of disaster mitigation, it is necessary to carry out regional landslide sensitivity evaluation. When many different evaluation results are obtained by using a variety of different methods, how to effectively combine these results to obtain the optimal prediction is a technical problem that is still not difficult to solve at present. It is still very lack in determining the optimal strategy and operation execution of the optimal method for landslide sensitivity evaluation in a certain area. 2) Using the traditional classical multivariate classification technology, through the evaluation of model results and error quantification, the optimal evaluation model is combined to quickly realize the high-quality evaluation of regional landslide sensitivity. The source code is written based on the R language software platform. The user needs to prepare a local folder separately to read and store the software operation results. The user needs to remember the folder storage path and make corresponding settings in the software source code. 3) The source code designs two different modes to display the operation results of the model. The analysis results are output in the standard format of text and graphic format and the geospatial mode that needs spatial data and is displayed in the standard geographic format. 4) it is suitable for all people interested in landslide risk assessment. The software can be used efficiently by experienced researchers in Colleges and universities, and can also be used by government personnel and public welfare organizations in the field of land and environmental planning and management to obtain landslide sensitivity classification results conveniently, quickly, correctly and reliably. It can serve regional land use planning, disaster risk assessment and management, disaster emergency response under extreme induced events (earthquake or rainfall, etc.), and has great practical guiding significance for the selection of landslide monitoring equipment and the reasonable and effective layout and operation of early warning network. It can be popularized and applied in areas with serious landslide development
YANG Zhongkang
Landslide drainage and seepage prevention is a common technology for the treatment of landslide source area in Qinghai Tibet Plateau. The existing siphon drainage technology is inefficient when applied to high altitude areas. Through improvement, a variable pipe diameter and high head siphon drainage technology is proposed to solve the deep drainage problem of landslide in high altitude and low pressure areas. 12 groups of siphon drainage tests with variable pipe diameter were carried out to verify the correctness of the theoretical velocity calculation formula. The test results show that the theoretical calculation results of siphon velocity are in good agreement with the test results, and the relative error of theoretical calculation is within 5%; Different schemes of variable pipe diameter increase the siphon flow rate by 15% - 116%. It can be seen that variable pipe diameter can significantly enhance the drainage capacity of siphons, especially for high lift siphons.
ZHENG Jun
Landslide drainage and seepage prevention is a common technology for the treatment of landslide source area in Qinghai Tibet Plateau. The calculation of the existing siphon drainage velocity formula is improved, and the correctness of the modified velocity formula is verified by experiments. The test results show that: (1) the existing siphon calculation formula is only suitable for the calculation of low lift siphon drainage velocity, and the calculation error of high lift siphon drainage velocity is large, and the maximum relative error is more than 90%; (2) The modified siphon calculation formula is suitable for siphon drainage systems with various heads. The theoretical calculation results are in good agreement with the experimental results, and the relative general error of theoretical calculation is less than 20%; (3) Therefore, it is recommended to use the proposed modified formula for the calculation of siphon drainage velocity.
ZHENG Jun
Landslide drainage and seepage prevention is a common technology for the treatment of landslide source area in Qinghai Tibet Plateau. The calculation of the existing siphon drainage velocity formula is improved, and the correctness of the modified velocity formula is verified by experiments. The test results show that: (1) the existing siphon calculation formula is only suitable for the calculation of low lift siphon drainage velocity, and the calculation error of high lift siphon drainage velocity is large, and the maximum relative error is more than 90%; (2) The modified siphon calculation formula is suitable for siphon drainage systems with various heads. The theoretical calculation results are in good agreement with the experimental results, and the relative general error of theoretical calculation is less than 20%; (3) Therefore, it is recommended to use the proposed modified formula for the calculation of siphon drainage velocity.
ZHENG Jun
1) In recent years, with the global climate change, coupled with the internal dynamic disturbance and strong tectonic uplift, mountain disasters and floods in the Qinghai Tibet Plateau occur frequently, which poses a great threat to rural settlements in mountainous areas. Village disaster vulnerability and comprehensive risk prevention ability have gradually become an important topic of rural disaster prevention and reduction. 2) This data comes from a random questionnaire survey conducted from June to September 2021 in tuomai village, Lang Town, Lang County, Nyingchi City, Bangna village, Linzhi Town, Bayi District, xuewaka village, Gu township, Bomi County, Beibeng village, Beibeng Township, Motuo County, Xueni village, zhuwagen Town, Chayu County, Ranwu village, Ranwu Town, Basu County, Qamdo city and Zhuba village, Baima Town, Basu county, And the respondents are mainly adults familiar with family conditions. 3) Based on the principles of scientificity, applicability, feasibility, typicality and specificity, the questionnaire is designed for the individual villages around the Himalayas on the Qinghai Tibet Plateau. In order to ensure the reliability and validity of the design content of the questionnaire, a pre survey was conducted before the formal survey to further modify and improve the questionnaire. Before the formal start of the questionnaire survey, the investigators were explained the contents of the questionnaire and trained in survey skills. 4) A total of 231 questionnaires were completed, including 35 in tuomai village, 24 in Bangna village, 21 in xuewaka village, 38 in Beibeng village, 16 in Xueni village, 72 in Ranwu village and 25 in Zhuba village. The effective rate of the questionnaire was 98.6%.
ZHOU Qiang, CHEN Ruishan , LIU Fenggui, LI Wanzhi , LI Shengmei , CHEN Qiong, GAO Haixin
Landslide drainage and seepage prevention is a common technology for the treatment of landslide source area in Qinghai Tibet Plateau. The existing siphon drainage technology is inefficient when applied to high altitude areas. Through improvement, a variable pipe diameter and high head siphon drainage technology is proposed to solve the deep drainage problem of landslide in high altitude and low pressure areas. 12 groups of siphon drainage tests with variable pipe diameter were carried out to verify the correctness of the theoretical velocity calculation formula. The test results show that the theoretical calculation results of siphon velocity are in good agreement with the test results, and the relative error of theoretical calculation is within 5%; Different schemes of variable pipe diameter increase the siphon flow rate by 15% - 116%. It can be seen that variable pipe diameter can significantly enhance the drainage capacity of siphons, especially for high lift siphons.
ZHENG Jun
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
This data uses a landslide hazard risk assessment model consisting of four modules: landslide hazard causative factors, landslide susceptibility model, exposed population and population casualty rate. The module of hazard-causing factors includes DEM, slope, rainfall, temperature, snow cover, GDP, and vegetation cover factors. The landslide hazard susceptibility model is a statistical analysis using a logistic regression model to obtain landslide susceptibility probability values. The population exposure module uses the landslide susceptibility values overlaid with population data. The population casualty rate module is based on the ratio of historical landslide casualties to the population exposed to landslides during the same period. Finally, by substituting the 2020 population data, the exposed population under different levels of landslide hazard susceptibility is calculated and multiplied with the historical period landslide hazard population casualty rate to assessIntegrated multi-hazard population risk in the peri-Himalayan and Asian water tower regions
WANG Ying
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
Data content: permeability and permeability stability test data of soil materials with different dry densities Data source: the test data orginated from each piezometer, osmometer, stopwatch and measuring cylinder. All instruments are submitted for inspection every year. Collection location and method: seepage Laboratory of Chinese Academy of Water Sciences. Test the dry density according to the gradation and sample preparation thickness. Collection time: August 1, 2020 to August 20, 2020 Data quality description: through the permeability and permeability stability test of piping soil material under different density and grading, the data content includes seepage flow, water head and time. The test data come from various pressure measuring tubes, osmometers, stopwatches and measuring cylinders, which were submitted for inspection every year.
XIE Dingsong
Data content: permeability and permeability stability test data of soil materials with different fine particle amounts Data source: through the seepage and seepage stability test of piping soil material under different density and grading, the data content includes seepage flow, water head and time. Collection location and method: seepage Laboratory of Chinese Academy of water sciences. Test the dry density according to the gradation and sample preparation thickness. Collection time: August 1, 2020 to August 20, 2020 Data quality description: the test data are from various pressure measuring tubes, osmometers, stopwatches and measuring cylinders, and all instruments are submitted for inspection every year.
XIE Dingsong
Data content: Damage calculation data of the Zhubalong Bridge Data source: calculation based on the established flood routing model. Collection method: comprehensive analysis through field investigation, literature retrieval and numerical model simulation. Data quality description: by constructing a two-dimensional dam break flood routing calculation model, the flood routing process after the dam break of Baige barrier lake on the "11.03" Jinsha River was simulated. Taking the Zhubalong Bridge in the lower reaches of the Jinsha River as the research object, the damage process of the bridge was explored based on the balance relationship between structural resistance and mountain flood damage force. The damage process of the Zhubalong Bridge in the process of flood routing was clarified, and the calculation formula for estimating the disaster water level of the bridge was obtained.
ZHANG Xinhua
Data content: Calculation data of bank slope scouring in the lower reaches of the Baige landslide based on flood routing model Data source: Taking the river range of 225 km downstream of Baige dam as the research object, the calculation was based on the constructed flood routing model. Collection method: visit and investigate the disaster situation on the left bank of Zhubalong section of Jinsha River. In order to compare and analyze with the actual investigation results, the 2km section from old bridge at Zhubalong in the Jinsha River to Zhubalong bridge along G318 national highway was intercepted to analyze its flood inundation and riverbed evolution process. Data quality description: Taking the 0-225km long river channel downstream of the Baige barrier lake dam site of Jinsha River as the research area, the routing process of dam break flood is simulated by using the subsection routing method. Through the measured hydrological data of hydrological stations in different river sections, the roughness coefficient of corresponding river sections is calibrated, and the flood routing process of each river section is obtained. On this basis, the 2km section from Zhubalong old bridge on Jinsha River to Zhubalong bridge on G318 national highway is intercepted, and its flood inundation and riverbed evolution process are analyzed. Taking the damaged highway and house scouring erosion from the confluence of Bachu River to Zhubalong section as an example, the analysis, calculation and verification are carried out.
ZHANG Xinhua
Data content: Calculation and numerical model of overtopping dam failure of landslide dam established based on the breach mechanism (taking the Baige landslide as an example) Data source: numerical model based on Visual Studio code platform. Collection method: Based on the basic parameters of Baige landslide dam, calculation was carried out through the established model. Data quality description: firstly, the dam-break models proposed by previous scholars were compared and analyzed, and then the input parameters required by the Baige dam-break numerical model were substituted for calculation according to the actual Baige dam break process. The breach process simulation of the Baige landslide dam was obtained, and the simulation results were compared with the actual process for verification.
ZHANG Xinhua
Data content: Basic parameter data of dam breach process under different slope conditions Data source: through literature search, classification, consolidation and compilation. Description of data quality: Based on Jiang Xiangang's physical model test on dam breach with different bed slopes, the traceability erosion process of the dam body was analyzed in order to propose a traceability erosion model and explore the influencing factors of the traceability erosion process. In addition, this job attempts to quantify the undercut rate of the breach and the change rate of the downstream slope toe at each time. In order to find the relationship between them and obtain the calculation formula of the downstream slope angle, the calculation of traceability erosion was carried out. This can provide the basis for the calculation and analysis in the later stage of the project.
ZHANG Xinhua
Data content: Basic data of the Baige landslide dam Data source: literature search, field investigation (Baige dam site), institutional investigation (Ganzi Hydrological Bureau, Chengdu survey, design and Research Institute). Collection method: use camera to take site photos during field investigation; Consult the collection materials of relevant institutions to obtain the basic data of Baige weir plug dam. Data quality description: detailed hydrological data were obtained through institutional investigation, including the data of Batang and Gangtuo hydrological stations and the changes of water level and flow in front of the dam in Ganzi Hydrological Bureau. These data will provide important theoretical basis and reference for further analysis of outburst flood in the Qinghai Tibet Plateau.
ZHANG Xinhua
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: Investigation report on the impact of the discharge flood of the "11.3" Baige landslide-damming lake on the downstream area of the Jinsha River Data source: field survey (route: from the junction of the Baqu River (also known as the Bachu River) in Batang County to the reservoir area of Liyuan reservoir). Data quality description: the disaster situation in the lower reaches of Jinsha River was analyzed from three aspects: damaged bridges, damaged towns (hydrological stations) and ancient barrier lakes. For damaged bridges, record and analyze from the aspects of longitude and latitude, flood mark elevation, bridge deck elevation, bridge type, scouring and destruction, etc were conducted; For damaged towns and hydrologic stations, record and analyze the damage on both banks of the river through visit and investigation were conducted; For the ancient barrier lake, combined with the field investigation and Google Earth map, the formation process of the ancient barrier lake was deduced; For the grading map of pebble and sediment particle size taken by the camera, the pebble particle size in the typical area is generalized into ellipse, and the generalized particle size of pebbles with different sizes was extracted. Finally, the pebble particle size grading curve can be drawn.
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
Data content: statistical analysis data of characteristic laws of large-scale landslide dams based on 1230 worldwide cases Data source: a large database containing 1230 dam cases around the world based on literature retrieval. Collection method: statistical analysis of the basic characteristics of landslide dam database through Excel, origin and other data analysis software and drawing software. Data quality description: Based on the established large-scale dam database, the distribution, inducement, service life, shape, collapse and other characteristics of dams at home and abroad were statistically analyzed. The correlation analysis of some characteristics was carried out, such as the correlation analysis of geological causes and service life of landslide dam, the correlation analysis of inducing factors and geological causes of landslide dam.
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: 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
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, 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: 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: 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: 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
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
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
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
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
Based on the concept of Height Above Nearest Drainage ( HAND ) derived from the international digital elevation model, the HAND model was used to identify the flooded area, and the spatial distribution of flood hazard level in the flood area of the study area was established. Flood hazard in the study area is divided into 1-5 grades, of which 5 represent very high risk, 4 represent high risk, 3 represent medium risk, 2 represent low risk, 1 represent very low risk.
CHEN Bo
Freezing-thawing disaster is the frost heaving and thawing settling caused by the change of thermal and mechanical stability of frozen soil, as well as the geological disasters caused by it, such as frost heaving hillock, ice cone, thermal thawing slump, thermal thawing subsidence, thawing mud flow, etc. In order to reveal the regional risk characteristics of freezing-thawing disasters around The Himalayas and in Asia's water tower region, it is very important to carry out the risk assessment of the factors causing the freezing-thawing disasters around the Himalayas and Asia's water tower region.The risk assessment of the risk factors of freezing-thawing disaster is mainly based on the climate, geography, environment and other factors of the evaluation area, and the geological conditions of the area are considered as the main factors of the risk assessment, and the risk assessment of the risk factors is graded.
ZHANG Guoming
This data set collates and collects various geological hazard points, topographic relief, landslide, elevation, land use and other influencing factors, with a resolution of 90m. The above factor layers and sample data are used to obtain the risk grade map with random forest. Data sets / atlas are mainly generated by: raw data (investigation, collection and purchase, etc.), processing data (calculation and simulation). The data source is downloaded from the open source website with an accuracy of 90m. The data is downloaded from the open source website and calculated in spider with their own random forest code. The training set is 80% and the test set is 20%. Open it with a computer that can run ArcGIS.
YANG Wentao
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 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
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
According to Ya'an Qamdo, Qamdo Nyingchi, Nyingchi Lhasa and other sections, carry out field investigation on debris flow within 10km along the new Sichuan Tibet railway line and Sichuan Tibet highway, fill in debris flow questionnaire and take photos. Based on the investigated debris flow data, the basic data are provided for the pregnant disaster background characteristics and distribution law of Sichuan Tibet traffic corridor. At the same time, the hazard modes of debris flow and the hazard modes to highway, railway and other traffic lines are investigated in detail; Furthermore, debris flow risk, vulnerability and risk assessment shall be carried out along the new Sichuan Tibet railway line at different scales such as regional scale, key sections and typical disasters, so as to provide support for the route selection of Sichuan Tibet railway.
CHEN Huayong, YANG Dongxu, LIU Jifeng, CHEN Xingzhang
The distribution data of debris flow in Sichuan Tibet transportation corridor includes two layers, one is the point layer, which mainly marks the location of debris flow gully, the other is the area layer, which is the drainage area of debris flow gully. The source of the data is the combination of remote sensing identification and ground investigation. Firstly, the remote sensing image is used to interpret the location of the debris flow gully in the region, and then the ground investigation of the debris flow gully is carried out along the Sichuan Tibet railway and Sichuan Tibet highway. The remote sensing interpretation data is verified, and finally the more reliable debris flow distribution data is obtained. The data can be used to analyze the distribution of debris flow in Sichuan Tibet transportation corridor, multi-scale debris flow risk assessment and risk assessment.
CHEN Huayong, LIU Jifeng, YANG Dongxu, CHEN Xingzhang
As a typical representative of mountainous areas in western China, Hengduan Mountain Area has become one of the areas with frequent and most serious geological disasters, which has brought great threats to rural settlements located in mountainous areas. Therefore, the vulnerability of village disasters and comprehensive risk prevention capability have gradually become an important topic of disaster prevention and disaster mitigation in rural areas. This data is from a random questionnaire survey conducted in Xiamachang Village, Meixing Town, Xiaojin County, Dashiban Village, Huiping Town, Mianning County, Sichuan Province, and Qina Village, Qina Town, Yongsheng County, Yunnan Province, from August to September, 2020. And the interviewees are mainly adults who is familiar with family situations. The design of the questionnaire is based on the principles of scientific nature, applicability, feasibility, typicality and concreteness. And Questionnaire on Disaster Risk Prevention Ability and Social Vulnerability of Villages in the Hengduan Mountain Area is designed for individual villages in the Hengduan Mountain Area. In order to ensure the reliability and validity of the questionnaire, some questionnaire was pre-investigated before the formal investigation, and there were some modification and improvement about the problem founded. Also, before the formal questionnaire survey, the investigators were given an explanation of the questionnaire and the training of the survey skills. 171 questionnaires were completed in this survey. After eliminating 20 invalid questionnaires, 151 valid questionnaires were obtained, including 50 from Xiamachang Village, 39 from Dashiban Village and 62 from Qina Village, respectively. The effective rate of questionnaires was 88.3%.
ZHOU Qiang, ZHANG Qiang, LIU Fenggui, SUN Peng, CHEN Qiong, ZHAO Fuchang, ZHI Zemin
1) Data content: ① indoor static tension video, infrared monitoring video and static tension analysis data chart of giant NPR anchor cable; ② Indoor dynamic impact video of giant NPR anchor cable; 2) Data sources: the static tension process, infrared monitoring and dynamic impact process of indoor giant NPR anchor cable were recorded, and the static tension data were imported into Origin Software for data processing and analysis; 4) Through the indoor static tension and dynamic impact tests on the giant NPR anchor cable, the supernormal mechanical properties of the giant NPR anchor cable are obtained, which can provide supporting materials for the prevention and control of slope disasters in fault zone, early warning monitoring and cross fault tunnel prevention.
TAO Zhigang
On the basis of literature and satellite image recognition, this data set has carried out a more detailed field scientific investigation on Sichuan Tibet railway, Sichuan Tibet transportation corridor and the upper reaches of Jinsha River, cataloguing and photographing the observed debris flow disaster chain, landslide disaster chain, typical fault structure points, glacial debris flow disaster chain and large-scale collapse disaster chain; Fill in the survey data form of disaster points in the field scientific examination, sort out and fill in the log files of scientific examination, and complete the distribution map of various types of disaster points. The photos are clear, the contents of the disaster questionnaire are detailed, and the scientific examination log is complete. The field survey photos and data have important reference significance for the future field survey of disaster chain and the comparative study of its future development trend.
DENG Hongyan , WANG Jiao, WANG Yufeng
Hengduan Mountain is located in the western part of Sichuan Basin, the northwestern part of Yunnan-Guizhou Plateau and the eastern part of Qinghai-Tibet Plateau. The Sichuan-Tibet Railway spans 14 large rivers and 21 snow-covered mountains over 4000 meters. The area is affected by many factors, such as complex geological structure, strong plate movement, diverse geomorphology, weathering and fragmentation of rock strata, major engineering disturbance, and climate change. As a result, earthquakes, debris flow, collapse, landslide, glacial lake outburst, mountain torrent, snow disaster and drought and other disasters in this region are highly frequent and frequent, showing obvious space-time extension, with short disaster period, high intensity and wide spread range. This data set is a collection of unmanned aerial vehicle remote sensing images and field photos of our second scientific expedition to the Qinghai-Tibet Plateau in the above areas, which is of great significance to support the strategic needs of disaster prevention and mitigation, engineering safety protection and regional development on the Qinghai-Tibet Plateau.
ZHANG Qiang, ZHOU Qiang, WU Wenhuan, ZHAO Jiaqi, YUAN Ruyue
Based on China's daily ground meteorological elements data set, national geographic basic data, demographic data, and 30M resolution DEM data, statistical yearbook data, historical disaster records, and other related data, using multi-methods like PCA, random forests to calculate hazard and vulnerability indicators, based on extreme precipitation，high temperature, flood, snow hazard, collapse and landslide hazards, to build comprehensive disaster risk index, and process them with normalization. Among them, we consider all the above disaster types in Hengduan Mountain area, and flood, snow disaster, collapse and landslide disaster in sichuan-tibet railway. The natural disasters hazard map, vulnerability map and comprehensive risk map of Hengduan Mountains (Sichuan-Tibet Railway) are included in the dataset.
ZHANG Qiang, ZHOU Qiang, WU Wenhuan, ZHAO Jiaqi, YUAN Ruyue
This data includes two standards: the data resource construction specification and the metadata specification for the scientific investigation of geological and geographical environment and disaster risk in the Qinghai Tibet Plateau. According to the opinions of the general office of the CPC Central Committee and the general office of the State Council on strengthening the development and utilization of information resources, the archives law of the people's Republic of China, the measures for the management of scientific data, and the outline for the construction of the platform for the basic conditions of science and technology, and in combination with the characteristics of the contents and achievements of task 9 scientific investigation, In order to facilitate the collection and sharing of scientific research data, realize simple and efficient management of complex project achievement data, and better protect the intellectual property rights of data resource producers, the metadata content standard framework and resource construction specification of task 9 of the second comprehensive scientific investigation on the Qinghai Tibet Plateau are formulated. In order to better serve the project itself, we should ensure the standardization and standardization of the data of each subject.
YANG Yaping
The data set includes the distribution data of mud flow terraces along the Sichuan Tibet railway and the distribution data of debris and loose particles along the Sichuan Tibet railway. The distribution data of mud flow terraces along the Sichuan Tibet railway is based on the data of Gaofen No.2 in recent years in China. The distribution map of freeze-thaw mud flow Terraces along the Sichuan Tibet railway is produced by deep learning classification method combined with manual visual interpretation and correction. The largest single mudflow terrace is 1030043 m2, which is located in Kangding City, about 12km away from Xinduqiao station of Sichuan Tibet railway. The smallest single mudflow terrace is 1102 m2, which is located in Naidong District, about 3.3km away from Jiacun station of Sichuan Tibet railway. The average area of mudflow terrace along the line is 45013 m2. Mudflow terraces along the line are mainly distributed in Kangding City, Chaya county and SANGRI county. Based on the remote sensing image data of gaofen-2 in the study area, the distribution data of clastic particles along the Sichuan Tibet railway are interpreted. The slope particles are widely developed in Litang Linzhi section of Sichuan Tibet railway. According to the flow characteristics and structural model, they are divided into active type and in-situ weathering type. At present, a total of 2308 slope granular diseases have been identified in the study area, covering an area of 1283.21km2, with an average area of 0.56km2. The minimum area in the figure above is 600m2, which is mainly distributed between 3700m and 5500m above sea level, with an average altitude of 4767.78m. About 95% of the slope particles in the study area have an area less than 2.0 × 104m2, with an average area of 55.5 square meters × 104m2, with the largest area of 9148 × 104m2； The slope granular materials are mainly distributed between the elevation of 4500-5400m, accounting for 87.9% of the total slope granular materials. The slope granular materials with the elevation of 5000-5400m account for 47.7%, with an average elevation of 4945m. The single slope granular material with the lowest elevation has an elevation of 3241m; The slope gradient of granular materials in the study area is mainly between 30-70 ° Among them, accounting for 89.5% of the total number of slope granular. The data set is used to formulate the operation specification of digital processing. In the process of processing, the operators are required to strictly abide by the operation specifications, and the special person is responsible for the quality review. The data integrity, logical consistency, position accuracy, attribute accuracy, edge connection accuracy and current situation are all in line with the requirements of relevant technical regulations and standards formulated by the State Bureau of Surveying and mapping. It provides a basis for the study of the development law of freeze-thaw mudflow and paleoclimate and the geographical distribution characteristics of granular materials on the slope of Sichuan Tibet engineering corridor.
JIANG Liming, JIANG Liming, JIANG Liming, HUANG Ronggang, WANG Huini
The main content of the data set is the survey data set of slope and pavement engineering diseases along G317 and G318 national highways, which is obtained through field survey. The survey time is from January 9 to January 19, 2020, and from August 10 to September 2, 2020. The respondents were G317 (Nagqu Ganzi) of North Sichuan Tibet line and G318 (Lhasa Xinduqiao) of South Sichuan Tibet line. The types of diseases investigated mainly include slope diseases and disasters induced by freezing and thawing (rockfall, dangerous rock mass and debris slope), pavement crack diseases, loose diseases, pit diseases, subgrade deformation diseases and salivary flow ice diseases in winter. Using the method of manual investigation, observe the damage of various diseases, and record the number (SCOPE), damage degree and location of various types of damage according to the requirements. The data set can provide a basis for a comprehensive understanding of the freeze-thaw diseases of the main highway projects in Sichuan Tibet engineering corridor and related research.
NIU Fujun
The cataloguing data and distribution map of debris flow dammed lake burst flood disaster chain, which can be observed in literature and satellite images, have been sorted out. In the data, debris flow can be divided into two types: General debris flow and glacier debris flow. The data mainly through literature investigation combined with remote sensing identification to determine the location and type of disaster chain, and then sorted into tables and generated vector data. The data were generated from the investigation literature and remote sensing visual interpretation. It is difficult to evaluate the integrity of data because it is impossible to judge the exact time of many disasters. The number of disaster points is field scientific research area code + River Basin name initial code + disaster chain type code + four digit sequence number. See Excel data file for details.
ZHOU Liqin, TANG Chenxiao
The data set records the statistical data of fire accidents in Qinghai Province from 1998 to 2010, which are divided by industry, region, affiliation and registration type. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of 13 tables Fire accident 2001.xls Fire accident 2006.xls Fire accident 2007.xls Fire accident 2008.xls Fire accident 2009.xls Fire accident 2010.xls Fire accident 1998.xls Fire accident 1999.xls Fire accident 2000.xls Fire accident 2002.xls Fire accident 2004.xls Fire accident 2006.xls Fire accident 2003.xls The data table structure is the same. For example, there are six fields in the data table of fire accidents in 2001 Field 1: Category Field 2: number of fires Field 3: number of deaths Field 4: number of injured persons Field 5: loss converted into RMB 10000 Field 6: cause of fire
Qinghai Provincial Bureau of Statistics
One belt, one road, one belt, one road, one belt, one road, is the key city to solve the extreme drought climate events in 34 key nodes (important cities, major projects, ports and industrial parks). The risk assessment of extreme drought is carried out. The research supports the green "one belt and one road" construction of the spatial route map, and serves the green "one belt and one road" construction. Design. For the risk assessment of drought disaster in each node, the hazard of disaster causing factors refers to the change characteristics and abnormal degree of the main meteorological factors causing drought disaster, such as the abnormal reduction of natural precipitation, the increase of evaporation or the abnormal high temperature. It is generally believed that the risk of drought disaster increases with the increase of the risk of disaster causing factors. Based on the spatialized satellite and reanalysis data of temperature, precipitation and soil available water content, the Palmer drought index of key node area was calculated to characterize the risk of extreme drought disaster factors in each node. One belt, one road and the other major projects should be built for the construction of the overseas parks, ports, major projects, and the scientific basis and Countermeasures for dealing with the drought disasters.
WU Hua, ZHANG Dan, CHEN Baozhang
One belt, one road, one belt, one road, one belt, one road, is the key city to solve the extreme drought climate events in 34 key nodes (important cities, major projects, ports and industrial parks). The risk assessment of extreme drought is carried out. The research supports the green "one belt and one road" construction of the spatial route map, and serves the green "one belt and one road" construction. Design. The vulnerability of drought disaster risk assessment for each node, on the one hand, depends on the sensitivity of different land cover types to drought disasters; on the other hand, it reflects the health of the ecological environment, determines the region's ability to bear and recover from drought disasters, which shows that the surface features under different land cover types are adversely affected by drought disasters The tendency to be loud. Using the 2015 land cover data of the "2018 silk road environment special project" source data, the vulnerability characteristics of different land cover types are measured by factor analysis method, and the weight of land vulnerability is assigned. The extreme drought vulnerability index with 100 m resolution of each node is obtained, which can provide reference for the construction planning, operation management and environmental problems of China's overseas parks, ports and major projects One belt, one road, one is the first and third, the other is the first and third.
WU Hua, ZHANG Dan, CHEN Baozhang
The data set is a 2015 heat wave risk data set in Dhaka, Bangladesh, with a spatial resolution of 30m and a temporal resolution of year. Heat wave risk refers to the probability or loss possibility of harmful consequences caused by the interaction between heat wave hazard (possible heat wave events in the future), heat wave exposure (total population, livelihood and assets in the area where heat wave events may occur) and heat wave vulnerability (the tendency of the disaster bearing body to suffer adverse effects when affected by heat wave events) . The risk assessment method of heat wave is "hazard-exposure-vulnerability". The data set has been proved by experts, which can provide support for regional high temperature heat wave risk assessment.
YANG Fei, YIN Cong
The data set is a 2015 heat wave hazard, exposure and vulnerability data set in Dhaka, Bangladesh, with a spatial resolution of 30m and a temporal resolution of yearly. Heat wave hazard is an index to measure the severity of heat wave event, which is expressed by surface temperature; heat wave exposure refers to the degree that human, livelihood and economy may be adversely affected, which is expressed by nighttime lighting data, and population density. The population older than 65 and younger than 5 years old constitute vulnerable groups; heat wave vulnerability is a measure of increased / reduced risk in the environment. The distance from road / hospital and ambulance station / water body, NDVI, impervious layer and slum area are used to represent the vulnerability of high temperature heat wave. The data set has been proved by experts, which can provide support for regional high temperature heat wave risk assessment.
YANG Fei, YIN Cong
The data set records the comparison of natural and man-made disaster losses in Qinghai Province from 2011 to 2018. The data is collected from the Department of natural resources of Qinghai Province. The data set contains 12 data tables, which are: comparison of natural and man-made disasters in 2011, natural and man-made disasters in 2012, natural and man-made disasters in 2013, and natural and man-made disasters in 2014 The structure of the data table is the same, including two fields: Field 1: disaster causes Field 2: Proportion It is classified according to human factors and natural factors
Department of Natural Resources of Qinghai Province
The data set records the main distribution of sudden geological disasters in Qinghai Province from 2011 to 2018. The data are collected from the Department of ecological environment of Qinghai Province. The data set contains seven tables, which are: the main distribution of sudden geological disasters in 2011, 2012, 2014, 2015 and 2016 Distribution statistics table, 2017 Qinghai Province sudden geological disasters distribution table, 2018 Qinghai Province sudden geological disasters distribution table, the data table structure is the same. Each data table has five fields, such as the statistical table of the main distribution of sudden geological disasters in Qinghai Province in 2016 Field 1: county (city) Field 2: landslide Field 3: collapse Field 4: debris flow Field 5: loess collapsibility
Department of Ecology and Environment of Qinghai Province
The data set records the comparison of direct economic losses caused by geological disasters in Qinghai Province from 2011 to 2018. The data is collected from the Department of ecological environment of Qinghai Province, and the data set contains 8 data tables, which are: direct economic losses caused by sudden geological disasters in 2011, direct economic losses caused by sudden geological disasters in 2012, comparison chart of direct economic losses caused by sudden geological disasters in 2013 and comparison chart of direct economic losses caused by geological disasters in 2014 The statistical table of direct economic losses caused by sudden geological disasters in Qinghai Province in 2015, the statistical table of direct economic losses caused by sudden geological disasters in Qinghai Province in 2016, the comparison of direct economic losses caused by sudden geological disasters in Qinghai Province in 2017, and the comparison chart of direct economic losses caused by sudden geological disasters in Qinghai Province in 2018 have the same data table structure. Each data table has two fields, such as the comparison chart of direct economic losses caused by sudden geological disasters in Qinghai Province in 2013 Field 1: disaster type Field 2: direct economic loss
Department of Ecology and Environment of Qinghai Province
The data set records the frequency statistics of typical geological disasters in Qinghai Province from 2011 to 2016. The data is collected from the Department of ecological environment of Qinghai Province. The data set contains six data tables, which are: the frequency of sudden geological disasters in 2011, 2012, 2013, 2014 and 2015 Statistical table, 2016 Qinghai Province sudden geological disasters frequency statistical table, data table structure is the same. There are two fields in each data table, such as the occurrence frequency of sudden geological disasters in 2011: Field 1: Location Field 2: frequency ratio
Department of Ecology and Environment of Qinghai Province
The data set records the typical geological disasters in Qinghai Province from 2011 to 2018. The data set includes 10 data tables, which are: typical geological disasters in 2011, 2012, 2013, 2013, distribution, 2014, etc The data structure of typical geological disasters in 2018 is the same. Each data table has five fields, such as the typical geological disasters in 2011: Field 1: Location Field 2: disaster type Field 3: time of occurrence Field 4: scale Field 5: hazards and losses
ZHAO Hu
The data set records the Geological Environment Bulletin of Qinghai Province from 2011 to 2019. The data set contains 9 PDF data files, which are collected from the Department of natural resources of Qinghai Province. Qinghai provincial government order No. 72 "geological environment protection, social and environmental protection for the people of Qinghai Province" is the basis for the comprehensive protection of the geological environment, According to the geological environment survey and monitoring data, the provincial natural resources department publishes the annual Geological Environment Bulletin and publishes the annual geological environment status of our province to the public. The main contents of the Geological Environment Bulletin of Qinghai province include: the distribution characteristics, causes, harm degree and prevention and control of geological disasters in the whole province; the development and utilization of groundwater resources and dynamic changes, groundwater pollution; the protection and restoration of mine geological environment. The Geological Environment Bulletin of Qinghai Province is jointly compiled by the geological exploration management office of Qinghai Provincial Department of natural resources and the geological environment monitoring station of Qinghai Province.
Department of Natural Resources of Qinghai Province
There are 428 large and medium-sized landslides in the Bangladesh China India Myanmar economic corridor. The number of landslides in Myanmar is the largest, reaching 304, accounting for 71% of the total landslides, followed by China and India. The number of landslides is 71 and 52, accounting for 17% and 12% of the total landslides, respectively. There is only one landslide in Bangladesh. According to the material composition of landslide, it can be divided into rock landslide and soil landslide. There are 343 rock landslides in this area, accounting for 80% of the total number of landslides, and 85 soil landslides, accounting for 20% of the total number of landslides. Rock landslides are mainly distributed in the north of China, India and Myanmar, while soil landslides are mainly distributed in the middle and south of Myanmar. A total of 1569 debris flows were interpreted in the Bangladesh China India Myanmar corridor, including 574 gully debris flows and 995 slope debris flows. In the eastern part of the study area, debris flows are mainly distributed on both sides of Lancang River, Nujiang River, Mojiang River and Honghe River, and they are distributed in the north-south direction along these rivers. In the central part of the study area, debris flows are distributed in the ruokai mountain area. Compared with the gully type debris flow, the scale and harm of slope debris flow are much smaller. In this study, the correlation analysis of debris flow is mainly aimed at the gully type debris flow.
ZOU Qiang
The China Mongolia Russia economic corridor starts from China in the East, passes through Mongolia in the west to Russia, and crosses the Mongolian Plateau, West Siberian plain and Eastern European Plain. There are great differences in natural environment and complex geological conditions in the region. Driven by regional differences in structure, earthquake, meteorology, hydrology and ecology, landslides are widely distributed in China Mongolia Russia economic corridor. Based on remote sensing images, the landslide and debris flow disasters in China Mongolia Russia economic corridor are interpreted. Statistics show that there are 396 landslide disasters in China Mongolia Russia economic corridor, and the landslide disaster area is between 0.0006km2 ~ 8.57km2. The watershed area within 100km on both sides of the railway line, with a total area of 1.43 × 106km2, has identified 1336 debris flow gullies in the China Mongolia Russia economic corridor.
ZOU Qiang
One belt, one road, one belt, one road, one belt, one road, is the key city to solve the extreme drought climate events. 34 key nodes (important cities, major projects, ports and industrial parks) are selected to carry out extreme drought risk assessment. Construction. The data one belt, one road area, and 34 extreme nodes in the "one area" area were evaluated by the extreme drought risk assessment index system. The time resolution and spatial resolution were 300 months. In order to facilitate the analysis of extreme drought risk index, the slope of the linear regression equation of monthly drought risk index at each pixel scale from 2014 to 2015 is calculated, which is used to represent the temporal variation characteristics of extreme drought (greater than 0 means drought aggravation, less than 0 means drought alleviation). At the same time, it can also reflect the spatial difference of extreme drought on the regional scale because it calculates the temporal change rate of each pixel.
WU Hua, ZHANG Dan, CHEN Baozhang
Gwadar deepwater port is located in the south of Gwadar city in the southwest of Balochistan province, Pakistan. It is 460km away from Karachi in the East and 120km away from the Pakistan Iran border in the West. It is adjacent to the Arabian Sea in the Indian Ocean in the South and the Strait of Hormuz and the Red Sea in the West. It is a port with a strategic position far away from Muscat, the capital of Oman. This data set is an extreme drought risk assessment data set. From the four aspects of extreme drought risk, exposure, vulnerability, and stability, the Palmer drought index, elevation, water system, land use, population density, GDP density, inter field water capacity, and other data are used to comprehensively assess the extreme drought risk of the region. The spatial resolution of the data is 30 meters and the time is 2015.
WU Hua
This data set is based on the spatial distribution data set of extreme precipitation disaster risk (2019) and vulnerability spatial distribution data set (2019) in Yangon deep water port area, combined with GDP and population distribution data of Yangon deep water port area, and through the definition of "risk = exposure × vulnerability × risk", the risk of extreme precipitation disaster in Yangon deepwater port area is calculated. The data set can provide a reference for the local disaster prevention and reduction work. By analyzing the distribution and causes of high risk, we can put forward engineering measures or non engineering measures to achieve the purpose of disaster reduction and prevention, and reduce the loss of people's lives and property caused by extreme precipitation disasters.
LI Yi
The area of the data set is the central urban area of Yangon deep water port. The data set is based on the spatial distribution data set of extreme precipitation disaster vulnerability (2019) and refers to its evaluation index system. When evaluating the vulnerability of extreme precipitation disaster in Yangon deepwater port area, the disaster reduction ability and sensitivity index are considered. The disaster reduction ability is negatively correlated with vulnerability, and the sensitivity is positively correlated with vulnerability. Disaster reduction capacity considers the density of impervious surface, road network and emergency rescue facilities; sensitivity considers the local land cover types, including farmland, urban and road crisscross. When extreme precipitation disaster occurs, high vulnerability areas will suffer more serious losses, and the reconstruction is more difficult.
GE Yong, LI Qiangzi, LI Yi
The evaluation area of the data set is the central urban area of Yangon deepwater port. The data set is based on the extreme precipitation disaster risk spatial distribution data set (2019) and its evaluation index system. The data set considers both precipitation risk and terrain risk. Among them, precipitation risk index includes extreme precipitation intensity index and extreme precipitation frequency index, both of which are obtained from GPM precipitation data. Terrain risk mainly considers elevation index. Finally, the risk assessment results of extreme precipitation disaster are obtained. The probability and intensity of extreme precipitation disaster in high risk area are higher than those in low risk area.
GE Yong, LI Qiangzi, LI Yi
One belt, one road, one belt, one road, one belt, one road, is the key city to solve the extreme drought climate events. 34 key nodes (important cities, major projects, ports and industrial parks) are selected to carry out extreme drought risk assessment. Construction. In one belt, one road area is divided into 34 zones with 1km resolution. The data are based on the linear regression slope of 2011-2015 years' multi period drought risk as the "extreme drought state change". The scientific basis for the drought disaster in China's overseas parks, ports, major construction projects, operation management, environmental problems, and prevention and control is provided. One belt, one road, the third pole area, is to promote and ensure the smooth implementation of the regional development strategy.
WU Hua, ZHANG Dan, CHEN Baozhang
On the basis of the global tropical cyclone track dataset, the global disaster events and losses dataset, the global tide level observation dataset and DEM data, coastline distribution data, land cover information, population and other related data of Hambantota, indicators related to the disaster danger of storm surge in each unit are extracted and calculated using ten meters grid as evaluation unit. Based on statistical method, the tide level of every 20 years, 50 years and 100 years is estimated. The comprehensive index of storm surge disaster danger is constructed, and the danger index of storm surge is obtained by using the weighted method, which can be used to evaluate the danger level of storm surge in each assessment unit. The data set includes 20-year, 50-year and 100-year hazard assessment results of the port area of Hambantota.
One belt, one road level, is set up. The data set is based on the 100 meter risk assessment data set and the 100m level vulnerability assessment dataset. The risk assessment data set of 34 nodes and 100 meters in the key area of the whole area is calculated based on the international definition of risk, risk (R) = hazard (H) * vulnerability (V). The data set assessed one belt, one road, the extreme precipitation risk under extreme precipitation events, and provided the basis for local government departments' decision-making. At the same time, it could make early warning before the flood disaster, so that we could gain valuable time to take measures to prevent and reduce disasters and reduce the loss of lives and property of people caused by floods.
GE Yong, LI Qiangzi, LI Yi
Based on the global surface water data (wod) from 1984 to 2018, the extreme precipitation frequency index and extreme precipitation intensity index were selected. Combined with the spatial analysis method in ArcGIS, the risk level of flood disaster in 34 key nodes under extreme precipitation conditions was constructed and evaluated. One belt, one road, 34 key nodes, is evaluated for the risk of flooding in the key areas of the "one belt" Road area under extreme precipitation events, which provides a basis for local government departments to make decisions and early warning before floods occur, so that we can gain valuable time for disaster prevention and mitigation measures to reduce the lives of the people brought by floods. Loss of property.
GE Yong, LI Qiangzi, LI Yi
One belt, one road, 34 key nodes, is used to assess the risk of flooding in the key areas of the "one belt" Road area under extreme precipitation events. It provides a basis for local government departments to make decisions and early warning before the flood. Thus, we can gain valuable time to take measures to prevent and reduce disasters and reduce the lives of the people. Loss of property. The data set takes one belt, one road, 34 key nodes, and the ratio of cultivated land to land, the proportion of urban land, the proportion of interlaced zone, the density of road network and the impervious surface. Based on the spatial analysis method in ArcGIS, the weights of each index are assigned. The vulnerability of 34 key nodes under extreme precipitation conditions is evaluated, and the vulnerability is determined by natural breakpoint method. Sex is divided into five levels, which represent no vulnerability, low vulnerability, medium vulnerability, high vulnerability and extremely high vulnerability.
GE Yong, LI Qiangzi, LI Yi
The historical storm surge events data of the 34 key areas along One Belt One Road were first collected from Internet and then re-processed. First, a Web crawler was coded by python language. Using several key words about storm surge, web pages were then collected by Google and Baidu search engine. Last, important information about the storm surge events (e.g., place, time, affected area, affected population, count of death) were extracted from web pages. This data can be used for risk assessment of storm surge in the 34 key areas along One Belt One Road.
GE Yong, LING Feng
The historical extreme precipitation events data of the 34 key areas along One Belt One Road were first collected from Internet and then re-processed. First, a Web crawler was coded by python language. Using several key words about extreme precipitation, web pages were then collected by Google and Baidu search engine. Last, important information about the extreme precipitation events (e.g., place, time, affected area, affected population, count of death) were extracted from web pages. This data can be used for risk assessment of extreme precipitation in the 34 key areas along One Belt One Road.
GE Yong, LING Feng
On the basis of the global tropical cyclone track dataset, the global disaster events and losses dataset, the global tide level observation dataset and DEM data, coastline distribution data, land cover information, population and other related data of the Belt and Road, indicators related to the disaster risk and vulnerability of storm surge in each unit are extracted and calculated using10 meter grid as evaluation unit, such as historical intensity of tide level frequency of storm historic arrival, historical loss, population density, land cover type, etc. The comprehensive index of storm surge disaster risk is constructed, and the risk index of storm surge is obtained by using the weighted method. Finally, the storm surge risk index is normalized to 0-1, which can be used to evaluate the risk level of storm surge in each assessment unit. The data set includes 20-year, 50-year, and 100-year corresponding risks.
On the basis of the global tropical cyclone track dataset, the global disaster events and losses dataset, the global tide level observation dataset and DEM data, coastline distribution data, land cover information, population and other related data of the Belt and Road, indicators related to the vulnerability of storm surge in each unit are extracted and calculated using 100 meter grid as evaluation unit, such as population density, land cover type, etc. The comprehensive index of storm surge vulnerability is constructed, and the vulnerability index of storm surge is obtained by using the weighted method. Finally, the storm surge vulnerability index is normalized to 0-1, which can be used to evaluate the vulnerability level of storm surge in each assessment unit.
This data set contains the statistical information of natural disasters in Qinghai Tibet Plateau in the past 50 years (1950-2002), including drought, snow disaster, frost disaster, hail, flood, wind disaster, lightning disaster, cold wave and strong cooling, low temperature and freezing damage, gale sandstorm, insect disaster, rodent damage and other meteorological disasters. Qinghai and Tibet are the main parts of the Qinghai Tibet Plateau. The Qinghai Tibet Plateau is one of the Centers for the formation and evolution of biological species in China. It is also a sensitive area and fragile zone for the international scientific and technological circles to study climate and ecological environment changes. Its complex terrain conditions, high altitude and severe climate conditions determine that the ecological environment is very fragile, It has become the most frequent area of natural disasters in China. The data were extracted from "China Meteorological Disaster Canon · Qinghai volume" and "China Meteorological Disaster Canon · Tibet Volume", which were manually input, summarized and proofread.
Statistical Bureau Statistical Bureau
The accuracy of tropical cyclone (tropical storm) track forecasting improved by nearly 50% for lead times of 24–72 h since 1990s. Over the same period forecasting of tropical cyclone intensity showed only limited improvement. Given the limited prediction skill of models of tropical cyclone intensity based on environmental properties, there have been a wealth of studies of the role of internal dynamical processes of tropical cyclones, which are largely linked to precipitation properties and convective processes. The release of latent heat by convection in the inner core of a tropical cyclone is considered crucial to tropical cyclone intensification. 16-year satellite-based precipitation, and clouds top infrared brightness temperature were used to explore the relationship between precipitation, convective cloud, and tropical cyclone intensity change. The 6-hourly TC centers were linearly interpolated to give the hourly and half hourly tropical cyclone center positions, to match the temporal resolution of the precipitation and clouds top infrared brightness temperature. More precipitation is found as storms intensify, while tropical cyclone 24 h future intensity change is closely connected with very deep convective clouds with IR BT < 208 K. Intensifying tropical cyclones follow the occurrence of colder clouds with IR BT < 208 K with greater areal extents. As an indicator of very deep convective clouds, IR BT < 208 K is suggested to be a good predictor of tropical cyclone intensity change（Ruan&Wu，2018，GRL）. The properties of the satellite-based precipitation, and clouds top infrared brightness temperature are therefore suggested to be important measurements to study tropical cyclone intensity, intensity change and their underlying mechanisms. The high resolution of the satellite-based precipitation (3h), and cloud top infrared brightness temperature (half hour) datasets also makes them possible to be used to study tropical cyclone variability associated with diurnal cycle.
WU Qiaoyan
Land surface temperature (LST) is a key variable for high temperature and drought monitoring and climate and ecological environment research. Due to the sparse distribution of ground observation stations, thermal infrared remote sensing technology has become an important means of quickly obtaining ground temperature over large areas. However, there are many missing and low-quality values in satellite-based LST data because clouds cover more than 60% of the global surface every day. This article presents a unique LST dataset with a monthly temporal resolution for China from 2003 to 2017 that makes full use of the advantages of MODIS data and meteorological station data to overcome the defects of cloud influence via a reconstruction model. We specifically describe the reconstruction model, which uses a combination of MODIS daily data, monthly data and meteorological station data to reconstruct the LST in areas with cloud coverage and for grid cells with elevated LST error, and the data performance is then further improved by establishing a regression analysis model. The validation indicates that the new LST dataset is highly consistent with in situ observations. For the six natural subregions with different climatic conditions in China, verification using ground observation data shows that the root mean square error (RMSE) ranges from 1.24 to 1.58 K, the mean absolute error (MAE) varies from 1.23 to 1.37 K and the Pearson coefficient (R2) ranges from 0.93 to 0.99. The new dataset adequately captures the spatiotemporal variations in LST at annual, seasonal and monthly scales. From 2003 to 2017, the overall annual mean LST in China showed a weak increase. Moreover, the positive trend was remarkably unevenly distributed across China. The most significant warming occurred in the central and western areas of the Inner Mongolia Plateau in the Northwest Region, and the average annual temperature change is greater than 0.1K (R>0:71, P<0:05), and a strong negative trend was observed in some parts of the Northeast Region and South China Region. Seasonally, there was significant warming in western China in winter, which was most pronounced in December. The reconstructed dataset exhibits significant improvements and can be used for the spatiotemporal evaluation of LST in high-temperature and drought-monitoring studies. More detail please refer to Zhao et al (2020). doi.org/10.5281/zenodo.3528024
MAO Kebiao
The Land Surface Temperature in China dataset contains land surface temperature data for China (about 9.6 million square kilometers of land) during the period of 2003-2017, in Celsius, in monthly temporal and 5600 m spatial resolution. It is produced by combing MODIS daily data(MOD11C1 and MYD11C1), monthly data(MOD11C3 and MYD11C3) and meteorological station data to reconstruct real LST under cloud coverage in monthly LST images, and then a regression analysis model is constructed to further improve accuracy in six natural subregions with different climatic conditions.
MAO Kebiao
This data set is a collection of statistics on major geological disasters in the Himalayas, the study area starts in Zada County, Guer County of The Ali region in the west, the east side is bounded by the Yalu-Zanbu River, the northern boundary is the Yalu-Zanbu River break, south to the vast Himalayan region of the national boundary. The Himalayas are located in the southwest of China, the southwest of the Qinghai-Tibet Plateau, the world's largest, highest and youngest mountain range, the world's highest peak Mount Qomolangma is located here. Here the geological structure is complex, seismic activity is frequent, the new tectonic movement is strong, the internal and external dynamic geological action is very active, is one of the most serious geological disasters in China. The original data of the data set is digitized from the report of the Remote Sensing Survey of Major Geological Disasters in the Himalayas, and the total number of disaster statistics is more than 540, including three types of disasters: landslides, mudslides and glacial final lake collapses. This data set provides basic data for the study of disaster reduction and prevention in the Himalayas region of Tibet, and is of reference value for research in related fields.
TONG Liqiang
The pan third pole historical extreme precipitation data set includes 2000-2018 extreme precipitation identification data. One belt, one road, was used to assess the rainfall in the important area along the GPM IMERG Final Run (GPM) daily rainfall. The extreme precipitation threshold of 34 important nodes was evaluated by percentile method. The daily precipitation period was identified by the calculated threshold, and the surface inundation area was produced on the basis of extreme precipitation. The data range mainly includes 34 key nodes of Pan third pole (Vientiane, Alexandria, Yangon, Calcutta, Warsaw, Karachi, yekajerinburg, Chittagong, Djibouti, etc.) The data set can provide the basis for local government decision-making, so as to correctly identify extreme precipitation and reduce the loss of life and property caused by extreme precipitation.
HE Yufeng
Water scarcity，food crises and ecological deterioration caused by drought disasters are a direct threat to food security and socio-economic development. Improvement of drought disaster risk assessment and emergency management is now urgently required. This article describes major scientific and technological progress in the field of drought disaster risk assessment. Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. The percentage of precipitation anomaly is the percentage of the precipitation between a certain period of time and the average climate precipitation of the same period divided by the average climate precipitation of the same period.Based on the daily rainfall data of GPM IMERG Final Run(GPM), this data set calculates the precipitation of the corresponding region, adopts the evaluation index of precipitation anomaly percentage grade, and analyzes the distribution characteristics of drought of different grades. The data area is 34 key nodes of the pan-third pole (Abbas, Astana, Colombo, Gwadar, Mamba, Tehran, Vientiane, etc.).
WU Hua
We compiled the Seismotectonic Map of Western Asia using the ArcGIS platform through data collecting and digitization. The seismotectonic map of Western Asia covers Iran and its surrounding countries and regions. Based on the “Major active faults of Iran” map, the seismotectonic map is replenished with massive published data and depicts the location and nature of the seisogenic faults or active faults and the epicenter of earthquakes with M ≥ 5 from 1960 to 2019. The map can not only be used in the research of active faults and seismic risks in Western Asia, but also will be applied to the seismic safety evaluation for infrastructure construction.
LIU Zhicheng
The Pan-Third Polar region has strong seismic activity, which is driven by the subduction and collision of the Indian plate, the Arab plate and the Eurasian plate. 18806 earthquakes with Magnitude 5 or larger have occurred in Pan-Third Polar region (north latitude 0-56 degrees and east longitude 43-139 degrees) since 1960. Among them, 4 earthquakes with Magnitude 8 or larger, 187 earthquakes with Magnitude 7.0-7.9， 1625 earthquakes with Magnitude 6.0-6.9 and 16990 earthquakes with Magnitude 5.0-5.9 have occurred. Earthquakes occurred mainly in the foothills of the India-Myanmar Mountains, the Himalaya Mountains, the Sulaiman Mountains, where the India Plate collided with the Eurasian plate, and the Zagros Mountains where the Arab plate collided with the Eurasian plate.
WANG Ji
We compiled the Seismic Zonation Map of Western Asia using the ArcGIS platform through data collecting and digitization. The Seismic Zonation map of Western Asia covers Iran and its surrounding countries and regions. Based on the “Major active faults of Iran” map, the map is replenished with massive published data and depicts the location and nature of the seisogenic faults or active faults and the epicenter of earthquakes with M ≥ 5 from 1960 to 2019. The zonation map shows the mean values of peak ground acceleration (PGA) with 10% probability of being exceeded in 50 years. The two maps can not only be used in the research of active faults and seismic risks in Western Asia, but also will be applied to the seismic safety evaluation for infrastructure construction.
LIU Zhicheng
A gridded ocean temperature dataset with complete global ocean coverage is a highly valuable resource for the understanding of climate change and climate variability. The Institute of Atmospheric Physics (IAP) provides a new objective analysis of historical ocean subsurface temperature since 1990 for the upper 2000m through several innovative steps. The first was to use an updated set of past observations that had been newly corrected for biases (e.g., in XBTs). The XBT bias was corrected by CH14 scheme, which is recommended by the XBT community. The second was to use co-variability between values at different places in the ocean and background information from a number of climate models that included a comprehensive ocean model. The third was to extend the influence of each observation over larger areas, recognizing the relative homogeneity of the vast open expanses of the southern oceans. Then the observations were also used to provide finer scale detail. Finally, the new analysis was carefully evaluated by using the knowledge of recent well-observed ocean states, but subsampled using the sparse distribution of observations in the more distant past to show that the method produces unbiased historical reconstruction. The ocean wind data set is constructed using RSS Version-7 microwave radiometer wind speed data. The input microwave data are processed by Remote Sensing Systems with funding from the NASA MEaSUREs Program and from the NASA Earth Science Physical Oceanography Program. This wind speed product is intended for climate study as the input data have been carefully intercalibrated and consistently processed. Each netCDF file contains: 1) monthly means of wind speed, grid size 360x180xnumber of all months since Jan 1988(increases over time) 2) a 12-month set of climatology wind speed, grid size 360x180, the climatology is an average calculated over the 20-year period 1988-2007 3) monthly anomalies of wind speed derived by subtracting the above climatology maps from the monthly means, grid size 360x180x#months since Jan 1988 (increases over time) 4) a wind speed trend map, grid size 360x180, the trend is calculated from 1988-01-01 to the latest complete calendar year 5) a time-latitude plot (a minimum of 10% of latitude cells is required for valid data), grid size 180x#months since Jan 1988 (increases over time).
GE Yong, LI Qiangzi, DONG Wen
The extreme drought damage historical events data of the 34 key areas along One Belt One Road were collected from Internet. First, a Web crawler was coded by python language. Using several key words about extreme drought damage, web pages were then collected by Google and Baidu search engine. Last, important information about the extreme drought events (e.g., place, time, affected area, affected population, count of death) were extracted from web pages. This data can be used for risk assessment of extreme drought in the 34 key areas along One Belt One Road.
GE Yong, LING Feng
Data from EM-DAT. EM-DAT is a global database on natural and technological disasters, containing essential core data on the occurrence and effects of more than 21,000 disasters in the world, from 1900 to present. EM-DAT is maintained by the Centre for Research on the Epidemiology of Disasters (CRED) at the School of Public Health of the Université catholique de Louvain located in Brussels, Belgium.The main objective of the database is to serve the purposes of humanitarian action at national and international levels. The initiative aims to rationalise decision making for disaster preparedness, as well as provide an objective base for vulnerability assessment and priority setting.The database is made up of information from various sources, including UN agencies, non-governmental organizations, insurance companies, research institutes and press agencies. Priority is given to data from UN agencies, governments, and the International Federation of Red Cross and Red Crescent Societies. This prioritization is not only a reflection of the quality or value of the data, it also reflects the fact that most reporting sources do not cover all disasters or have political limitations that could affect the figures. The entries are constantly reviewed for inconsistencies, redundancy, and incompleteness. CRED consolidates and updates data on a daily basis. A further check is made at monthly intervals, and revisions are made at the end of each calendar year.
GE Yong, LI Qiangzi, DONG Wen
On the basis of the global tropical cyclone track dataset, the global disaster events and losses dataset, the global tide level observation dataset and DEM data, coastline distribution data, land cover information, population and other related data of the Belt and Road, indicators related to the disaster risk and vulnerability of storm surge in each unit are extracted and calculated using100 meter grid as evaluation unit, such as historical intensity of tide level frequency of storm historic arrival, historical loss, population density, land cover type, etc. The comprehensive index of storm surge disaster risk is constructed, and the risk index of storm surge is obtained by using the weighted method. Finally, the storm surge risk index is normalized to 0-1, which can be used to evaluate the risk level of storm surge in each assessment unit.At the same time, the data set includes the corresponding risk index, exposure index and vulnerability assessment results.The key nodes data set only contains 11 nodes which have risks ((Chittagong port, Bangladesh; Kyaukpyu Port, Myanmar; Kolkata, India; Yangon Port, Myanmar; Karachi, Pakistan; Dhaka, Bangladesh; Mumbai, India; Hambantota Port, Sri Lanka; Bangkok, Thailand; China-Myanmar Oil and Gas Pipeline; Jakarta-Bandung High-speed Railway).
On the basis of the global tropical cyclone track dataset, the global disaster events and losses dataset, the global tide level observation dataset and DEM data, coastline distribution data, land cover information, population and other related data of the Belt and Road, indicators related to the vulnerability of storm surge in each unit are extracted and calculated using 100 meter grid as evaluation unit, such as population density, land cover type, etc. The comprehensive index of storm surge vulnerability is constructed, and the vulnerability index of storm surge is obtained by using the weighted method. Finally, the storm surge vulnerability index is normalized to 0-1, which can be used to evaluate the vulnerability level of storm surge in each assessment unit. The key nodes data set only contains 11 nodes which have risks (Chittagong port, Bangladesh; Kyaukpyu Port, Myanmar; Kolkata, India; Yangon Port, Myanmar; Karachi, Pakistan; Dhaka, Bangladesh; Mumbai, India; Hambantota Port, Sri Lanka; Bangkok, Thailand; China-Myanmar Oil and Gas Pipeline; Jakarta-Bandung High-speed Railway).
DONG Wen
Water scarcity，food crises and ecological deterioration caused by drought disasters are a direct threat to food security and socio-economic development. Improvement of drought disaster risk assessment and emergency management is now urgently required. This article describes major scientific and technological progress in the field of drought disaster risk assessment. Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. Soil relative humidity index is one of the indicators to characterize soil drought and can directly reflect the status of crops' available water.
GE Yong, WU Hua
The UHSLC offers tide gauge data with two levels of quality-control (QC). Fast Delivery (FD) data are released within 1-2 months of data collection and receive only basic QC focused on large level shifts and obvious outliers. The GLOSS/CLIVAR (formerly known as the WOCE) "fast" sea level data is distributed as hourly, daily, and monthly values. This project is supported by the NOAA Climate and Global Change program, and is one of the activities of the University of Hawaii Sea Level Center. Each file is given a name "h###.dat" where "h" denotes hourly sea level data and "###" denotes the station number. A file exists for every station with hourly data. The UHSLC datasets are GLOSS data streams (read more here). There are many tide gauge records in the UHSLC database, but the backbone is the GLOSS Core Network (GCN) – a global set of ~300 tide gauge stations that serve as the foundation of the global in situ sea level network. The network is designed to provide evenly distributed sampling of global coastal sea level variation at a variety of time-scales.
DONG Wen, University of hawaii sealevel center （UHSLC）
On the basis of the global tropical cyclone track dataset, the global disaster events and losses dataset, the global tide level observation dataset and DEM data, coastline distribution data, land cover information, population and other related data of 34 key nodes, indicators related to the disaster danger of storm surge in each unit are extracted and calculated using handred meters grid as evaluation unit, such as historical intensity of tide level frequency of storm historic arrival, historical loss, distance of offshore line, etc. The comprehensive index of storm surge disaster danger is constructed, and the danger index of storm surge is obtained by using the weighted method. Finally, the storm surge danger index is normalized to 0-1, which can be used to evaluate the danger level of storm surge in each assessment unit. The key nodes data set only contains 11 nodes which have risks.
GE Yong, LI Qiangzi, DONG Wen
Data set of surface inundation caused by historical extreme precipitation evaluated the surface inundation range of One Belt And One Road key areas under extreme precipitation, providing a basis and reference for the decision-making of local government departments, so as to give early warning before the occurrence of extreme precipitation and reduce the loss of life and property caused by extreme precipitation.This data set to the extreme precipitation threshold set "and" the extreme precipitation recognition "as the foundation, to confirm the extreme precipitation time node and the area, and then to NASA's web site to download the submerged range products corresponding to the time and region, combining ArcGIS spatial analysis was used to connect the above data, build the data sets of historical extreme precipitation caused surface submerged range for 34 key nodes. The data mainly includes 34 key nodes (Vientiane, China-Myanmar oil and gas pipeline, China-Laos Thai-Cambodia railway, Alexandria, Yangon, Kwantan, Kolkata, Warsaw, Karachi, Yekaterinburg, Yekaterinburg and other regions).
WU Hua
Water scarcity，food crises and ecological deterioration caused by drought disasters are a direct threat to food security and socio-economic development. Improvement of drought disaster risk assessment and emergency management is now urgently required. This article describes major scientific and technological progress in the field of drought disaster risk assessment. Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. Soil relative moisture index is one of the indicators that characterize soil drought. It is the ratio of soil relative humidity to field water holding capacity, which can directly reflect the availability of water for crops.The soil moisture data is obtained from the SMAP remote sensing soil moisture data product through the downscaling method, and the field water holding capacity data comes from the Hamonized World Soil Database (HWSD). For detailed calculation formulas and methods, please refer to: "National Standard for Agricultural Drought Grades of China" No.: GB/T 32136-2015. The data covers 34 key node areas along the Belt and Road.
WU Hua
Water scarcity，food crises and ecological deterioration caused by drought disasters are a direct threat to food security and socio-economic development. Improvement of drought disaster risk assessment and emergency management is now urgently required. This article describes major scientific and technological progress in the field of drought disaster risk assessment. Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. The relative humidity index is the difference between the amount of precipitation in a certain period of time and the potential evapotranspiration over the same period divided by the potential evapotranspiration.
GE Yong, WU Hua
Apparent temperature refers to the degree of heat and cold that the human body feels, which is affected by temperature, wind speed and humidity. The spatial scope of the data covers 34 key nodes in the pan-third pole region (Vientiane, Yangon, Kolkata, Warsaw, Karachi, Yekaterinburg, Chittagong, Tashkent, etc.). The spatial resolution is 100m, and the temporal resolution is year. Processing process: Based on the monitoring data of the meteorological station, calculate the apperant temperature based on the Humidex index, and then use the temperature correction method based on elevation correction to obtain 1km gridded data of the entire area, and downscale it to 100m. The heat wave risk dataset mainly uses intensity as the evaluation index. The spatial range and spatial resolution are consistent with the somatosensory temperature data set, and the temporal resolution is years. The criterion for judging the heat wave is: the weather process in which the somatosensory temperature exceeds 29℃ for three consecutive days is judged to be a high-temperature heat wave.
YANG Fei, WU Xilin, YIN Cong
Water scarcity，food crises and ecological deterioration caused by drought disasters are a direct threat to food security and socio-economic development. Improvement of drought disaster risk assessment and emergency management is now urgently required. This article describes major scientific and technological progress in the field of drought disaster risk assessment. Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. The relative moisture index is the difference between the precipitation in a certain period of time and the potential evapotranspiration in the same period and then divided by the potential evapotranspiration in the same period.The precipitation data comes from the downscaling of the TRMM/GPM satellite precipitation data, and the potential evapotranspiration is estimated using the Thornthwaite method. For detailed algorithm, please refer to "National Standard for Meteorological Drought of China" (GB/T 20481-2017). The data only covers 34 key node areas along the Belt and Road.
WU Hua
The basic data source of this dataset is from the website of the National Oceanic and Atmospheric Administration (NOAA). NOAA satellites are meteorological observation satellites. Provide meteorological environment information including temperature, precipitation, dew point, wind speed, etc. This dataset mainly covers key nodes in the pan-third pole Southeast Asia and Middle East regions. The main steps of data processing are as follows: First, according to the definition of high temperature heat waves in China's national standard "GB / T 29457-2012", based on basic meteorological data, determine the occurrence of high temperature heat waves, and then statistically obtain the frequency of high temperature heat waves. The time and occurrence intensity are collated to obtain the historical high temperature heat wave disaster event data set. This data set is helpful for clarifying the occurrence of extreme high temperature disasters in each study area, and provides reference materials and a strong basis for judging the intensity of high temperature heat waves in each area.
GE Yong, LIU Qingsheng
Global Tropical cyclone (TC) best track data already exist as individual storm tracks at other agencies. The intent of the IBTrACS project is to overcome data availability issues. This was achieved by working directly with all the Regional Specialized Meteorological Centers and other international centers and individuals to create a global best track dataset, merging storm information from multiple centers into one product and archiving the data for public use. The World Meteorological Organization Tropical Cyclone Programme has endorsed IBTrACS as an official archiving and distribution resource for tropical cyclone best track data. The IBTrACS project: contains the most complete global set of historical tropical cyclones available, combines information from numerous tropical cyclone datasets, simplifies inter-agency comparisons by providing storm data from multiple sources in one place, provides data in popular formats to facilitate analysis and checks the quality of storm inventories, positions, pressures, and wind speeds, passing the information on to the user. The primary intent of IBTrACS is to support scientific research efforts.
GE Yong, LI Qiangzi, DONG Wen
Under the background of global warming, the frequency and intensity of drought are increasing. The lack of water resources, food crisis and ecological deterioration (such as desertification) caused by drought disasters directly threaten the national food security and social and economic development. The technical level of drought disaster risk assessment and emergency management needs to be improved. One belt, one road area has one belt, one road area is fragile, agricultural land is concentrated and drought is frequent. Monitoring the drought level and its temporal and spatial changes in large areas by using remote sensing satellites is of great scientific and practical significance for scientifically grasping the drought pattern, regional differentiation characteristics and its impact on agricultural land in the "one belt and one road" area. The percentage of precipitation anomaly reflects the deviation degree between the precipitation of a certain period and the average state of the same period, expressed as a percentage. Based on the daily rainfall data of GPM imerg final run (GPM), the precipitation of corresponding area is calculated. The distribution characteristics of drought of different grades are analyzed by using the grade evaluation index of precipitation anomaly percentage. The spatial resolution is 200m. The data area is 34 key nodes of Pan third pole (Abbas, Astana, Colombo, Gwadar, Mengba, Teheran, Vientiane, etc.).
WU Hua
This data set collects the wave tide level data of the southern sea area of Sri Lanka from September 2013 to October 2014. Sri Lanka is located in the core node of the "maritime Silk Road", which is the necessary node of our oil transportation lifeline. The wave observation data of this sea area is of great significance to understand the wave characteristics of this sea area and ensure the navigation safety of cargo ships and sea convoys. The data is obtained by the pressure sensor deployed on the seabed, and the data reliability is ensured by the quality control segments such as the removal of abnormal values. This data is of great significance to the analysis of marine disaster assessment, ship passing safety assessment and the study of wave characteristics in the sea area.
LUO Yao
1) The data includes the soil erosion modulus of 22 watersheds with a resolution of 2.5 m in the year of 2019 in the Xinjiang Uygur Autonomous Region. 2）Based on the surface layer of rainfall erosivity R, soil erodibility K, slope length factor LS, vegetation coverage FVC, and rotation sampling survey unit, the Chinese soil erosion model (CSLE) was used to calculate soil erosin modulus in 22 watersheds respectively. Through spatial data processing (including chart linking and transformation, vector-grid conversion, and resampling), R, K, LS factors were calculated from the regional thematic map of rainfall erosivity, soil erodibility, and DEM. By half-month FVC, NPV, half-month rainfall erosivity data, we calculated the value of B factors in each sampling watershed. The value of E factor was calculated based on the remote sensing interpretation result and engineering measure factor table. The value of tillage factor T was obtained from tillage zoning map and tillage measure table. And then the soil erosion modulus in each sampling watershed was calculated by the equation: A=R•K•LS•B•E•T. The selection of 22 watersheds was based on the layout of sampling survey in pan-third polar region. 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 modulus is of great significance for studying the present situation of soil erosion in Pan third polar region, and it is also crucial for the implementation of the development policy of the Silk Road Economic Belt and the 21st-Century Maritime Silk Road.
YANG Qinke
The China-Pakistan Economic Corridor, north from Kashgar of China and south to the Gwadar seaport of Pakistan, with a total length of 000 km, is the key to linking the north and south Silk Road. Due to the complex geology, landform, climate, hydrology conditions, landslides and debris flows are very active in this area. Through the combination of field investigation and image interpretation, the symbols of typical landslide and debris flow images were established. Based on interactive interpretation and field investigation verification, the spatial distribution of landslides and debris flows within the scope of CPEC was identified, which provides important data support for risk analysis of landslide and debris flow disasters in CPEC and disaster prevention and reduction.
ZOU Qiang
This dataset mainly includes the spatial distribution of global SPEI in 1218 in 2018, the global drought intensity in 2018, and the anomalies of precipitation, land surface temperature, 0-10 cm soil moisture and the past 10 years (2009-2018); The flat index method, the maximum value synthesis method and the trend analysis method calculate the global drought intensity and the main meteorological factor anomaly data for 2018. The data time scale is 2018-01-01 to 2018-12-31, and the spatial resolution is 0.5 degree. The data can provide a scientific reference for the analysis of global drought distribution and drought assessment in 2018.
TIAN Feng, WU Jianjun, ZHOU Hongmin
The data set analyzes the spatial and temporal distribution, impact and loss of typical global flood disasters from 2018 to 2019. In 2018, there were 109 flood disasters in the world, with a death toll of 1995. The total number of people affected was 12.62 million. The direct economic loss was about 4.5 billion US dollars, which was at a low level in the past 30 years. The number of global flood incidents in 2018 was higher in the first half of the year than in the second half of the year, and the frequency of occurrence was higher from May to July. Therefore, based on three typical disaster events such as the hurricane flood in Florence in the United States in 2018, the flooding of the Niger River in Nigeria in 2018, and the Shouguang flood in Shandong Province in 2018, the disaster background, hazard factors, and disaster situation were analyzed. .
JIANG Zijie, JIANG Weiguo, WU Jianjun, ZHOU Hongmin
The global typhoon path data set contains the data of 29 typhoon path points in the Northwest Pacific in 2018, including time, longitude and latitude, central air pressure, wind speed and wind force, future direction, future speed, wind force level and other indicators; the data comes from the typhoon network of the Central Meteorological Station (http://typhone.nmc.cn/web.html), using Python to grab the typhoon path data published on the web page, In addition, the captured Excel data table is sorted into ShapeFile form, and each path point is given wind power level according to the wind power rating standard of typhoon; It can be applied to the analysis of the characteristics and influence of the movement of typhoon path points, wind speed and wind force.
CHEN Yiting, YANG Hua, WU Jianjun, ZHOU Hongmin
This data set contains 2018 global forest fire case data for the whole year and 2019, including the forest fire in California in November 2018, the forest fire in Attica, Greece in July 2018, and the forest fire in Shanxi Province in March 2019. Case data. Specific data include: fire intensity data of the monitoring range and data of vegetation index changes before and after the disaster. The data set is mainly used to describe the occurrence, development, impact and recovery of major global forest fire events in the first half of 2018-2019. The data mainly comes from NASA official website and EM-DAT database, it was processed by statistical and spatial analysis methods using EXCEL and ArcGIS tools. The data source is reliable, the processing method is scientific and rigorous, and it can be effectively applied to global (forest fire) disaster case analysis research.
YANG Yuqing, GONG Adu, WU Jianjun, ZHOU Hongmin
This data set is used to analyze the global activity level of strong earthquakes (Mw 5) in the past 30 years, and to present it spatially. It can be used to obtain the distribution areas of strong earthquakes with high frequency and activity level in recent years. By comparing the distribution of strong earthquakes in 2018 with that in 1989-2018, the distribution characteristics of global strong earthquakes in 2018 are obtained. The original data of strong earthquakes are from USGS, and the local density is calculated as frequency information. The magnitudes of all earthquake cases are interpolated globally, and then the frequency and magnitude are multiplied as the activity level of strong earthquakes. The data set is in TIff format with a spatial resolution of about 80 km. The data set can provide a reference for the analysis of strong earthquake activity level on the global scale, and is helpful for the analysis of global earthquake risk and the construction of earthquake prevention and disaster reduction system.
Chen Jin, Tang Hong, WU Jianjun, ZHOU Hongmin
The data includes the path data of tropical cyclone "iday" in the southern hemisphere in March 2019, and the data of flood affected area in southern Africa caused by it. It is an important data source supplement for major global tropical cyclone disasters in 2019. The track data of the tropical cyclone is collected from the monitoring data of the National Satellite Meteorological Center, and the longitude and latitude coordinates are obtained by using ArcGIS software; the flooded range data of the southern Africa flood is extracted by the Institute of remote sensing of the Chinese Academy of Sciences Based on the high-resolution three satellite image. The data can be used for the path analysis, affected situation analysis and disaster damage assessment of tropical cyclone "Yidai".
CHEN Yiting, YANG Hua, WU Jianjun, ZHOU Hongmin
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
1) The dataset includes the raster data of soil erosion intensity in Pan-Third Pole 65 countries.2) The data of soil erosion intensity are obtained by using the Chinese soil loss equation (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 are calculated by 250 m soil grid data; engineering measure factors are calculated based on vegetation cover, land use and rainfall erosivity ratio; tillage measure factors haven't been considered yet, and the default value is 1; 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 implementation of the development policy of the Silk Road Economic Belt and the 21st-Century Maritime Silk Road.
ZHANG Wenbo
1) The data includes the soil erosion modulus of 18 watersheds with a resolution of 5 m in the year of 2017 in Thailand. 2) Based on the surface layer of rainfall erosivity R, soil erodibility K, slope length factor LS, vegetation coverage FVC, and rotation sampling survey unit, the Chinese soil erosion model (CSLE) was used to calculate soil erosin modulus in 18 watersheds of Thailand respectively. Through spatial data processing (including chart linking and transformation, vector-grid conversion, and resampling), R, K, LS factors were calculated from the regional thematic map of rainfall erosivity, soil erodibility, and DEM. By half-month FVC, NPV, half-month rainfall erosivity data, we calculated the value of B factors in each sampling watershed. The value of E factor was calculated based on the remote sensing interpretation result and engineering measure factor table. The value of tillage factor T was obtained from tillage zoning map and tillage measure table. And then the soil erosion modulus in each sampling watershed was calculated by the equation: A=R•K•LS•B•E•T. The selection of 18 watersheds was based on the layout of sampling survey in pan-third polar region. 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 region and better implementation of the development policy of the Silk Road Economic Belt and the 21st-Century Maritime Silk Road.
YANG Qinke
1)The data content includes three stages of soil erosion intensity in Qinghai-Tibet Plateau in 1992, 2005 and 2015, and the grid resolution is 300m. 2) China soil erosion prediction model (CSLE) was used to calculate the soil erosion amount of more than 4,000 investigation units on the Qinghai-Tibet Plateau. Soil erosion was interpolated according to land use on Qinghai-Tibet Plateau. According to the soil erosion classification standard, the soil erosion intensity map of Qinghai-Tibet Plateau was obtained. 3) By comparing the differences of three-stage soil erosion intensity data, it conforms to the actual change law and the data quality is good. 4) The data of soil erosion intensity are of great significance to the study of soil erosion in the Qinghai-Tibet Plateau and the sustainable development of local ecosystems. In the attribute table, "Value" represents the erosion intensity level, from 1 to 6, the value represents slight, mild, moderate, intense, extremely intense and severe. "BL" represents the percentage of echa erosion intensity in the total area.
ZHANG Wenbo
"Disaster data for countries along the belt and road, mainly from the global disaster database.The records information of disaster database are from the United Nations, government and non-governmental organizations, research institutions and the media. It's documented in detail such as the country where the disaster occurred, the type of disaster, the date of the disaster, the number of deaths and the estimated economic losses. This study extracts the natural disaster records of the countries along the One Belt And One Road line one by one from the database, and finally forms the disaster database of 9 major disasters of the 65 countries. The natural disaster records collected can be roughly divided into nine categories, including: floods, landslides, extreme temperatures, storms, droughts, forest fires, earthquakes, mass movements and volcanic activities. From 1900 to 2018, a total of 5,479 disaster records were recorded in countries along the One Belt And One Road. From 2000 to 2015, there were 2,673 disaster records. On this basis, the natural disasters of the countries along the belt and road are investigated from four aspects, including disaster frequency, death toll, disaster-affected population and economic loss assessment. Overall, since 1900, a total of 5479 natural disasters have occurred in countries along the One Belt And One Road, resulting in about 19 million deaths and economic losses of about 950 billion us dollars. Among them, the most frequent occurrence is flood and storm; the biggest economic losses are floods and earthquakes; the most affected people are flood and drought; drought and flooding are the leading causes of death
YIN Jun
This data set contains information on natural disasters in Qinghai over nearly 50 years, including the times, places and the consequences of natural disasters such as droughts, floods, hail, continuous rain, snow disasters, cold waves and strong temperature drops, low temperature freezing injuries, gales and sandstorms, pest plagues, rats, and geological disasters. Qinghai Province is located in the northeastern part of the Tibetan Plateau and has a total area of 720,000 square kilometers. Numerous rivers, glaciers and lakes lie in the province. Because two mother rivers of the Chinese nation, the Yangtze River and the Yellow River, and the famous international river—the Lancang River—originated here, it is known as the "Chinese Water Tower"; there are 335,000 square meters of available grasslands in the province, and the natural pasture area ranks fourth in the country after those of Inner Mongolia, Tibet and Xinjiang. There are various types of grasslands, abundant grassland resources, and 113 families, 564 genera and 2100 species of vascular plants, which grow and develop under the unique climatic condition of the Tibetan Plateau and strongly represent the characteristics of the plateau ecological environment. As the main part of the Tibetan Plateau, Qinghai Province is one of the centers of the formation and evolution of biological species in China. It is also a sensitive area and fragile zone for the study of climate and ecological environment in the international field of sciences and technology. The terrain and land-forms in Qinghai are complex, with interlaced mountains, valleys and basins, widely distributed snow and glaciers, the Gobi and other deserts and grassland. Complex terrain conditions, high altitudes and harsh climatic conditions make Qinghai a province with frequent meteorological disasters. The main meteorological disasters include droughts, floods, hail, continuous rain, snow disasters, cold waves and strong temperature drops, low temperature freezing injuries, gales and sandstorms. The data are extracted from the Qinghai Volume of Chinese Meteorological Disaster Dictionary, with manual entry, summarizing and proofreading.
Qinghai Provincial Bureau of Statistics
1) The data is the layout of sample survey units in 65 countries of Pan-Third Polar region and western China. 2)Sample survey units were set in the pan-third pole region (70 °N-10 °S, 180 °E-180 ° W) . No samplings points were selected in the region with latitude >70 °. In the region wiht latitude of 60 ° -70 ° , sample survey units were selected in cells of 0.5 ° latitude ×1 ° Longitude (about 55km×55km-55km×38km). In the area with latitude of 40°-60°, sample survey units were selected in cells of 0.5 ° latitude×0.75 ° longitude (about 55km×63km-55km×42km). In the area with latitude <40°, sample survey units were selected in cells of 0.5 ° latitude × 0.5 ° longitude. In the Qinghai-Tibet Plateau, sample survey units were selected in cells of 0.25 ° latitude × 0.25 ° longitude. Thesample survey units deployed in the first national water conservancy survey for soil and water conservation were used in current project in five provinces including Xinjiang, Qinghai, Gansu, Sichuan and Yunnan in western China. The total number of sample survey units is 29,651, of which, 4052 are in the Qinghai-Tibet Plateau, 8771 in the western China, and 16,828 in countries outside of China. 3) The selected sample survey units is well distributed and the data quality is good.4) the layout map of sample survey units is of great significance for the study of soil erosion in Pan third polar region, and it is also crucial for the implementation of the development policy of the area along the Silk Road Economic Belt and the 21st-Century Maritime Silk Road.
WEI Xin
1) The data includes the soil erosion modulus of 11 watersheds with a resolution of 5 m in the year of 2017 in Tibet. 2）Based on the surface layer of rainfall erosivity R, soil erodibility K, slope length factor LS, vegetation coverage FVC, and rotation sampling survey unit, the Chinese soil erosion model (CSLE) was used to calculate soil erosin modulus in 11 watersheds respectively. Through spatial data processing (including chart linking and transformation, vector-grid conversion, and resampling), R, K, LS factors were calculated from the regional thematic map of rainfall erosivity, soil erodibility, and DEM. By half-month FVC, NPV, half-month rainfall erosivity data, we calculated the value of B factors in each sampling watershed. The value of E factor was calculated based on the remote sensing interpretation results and engineering measure factor table. The value of tillage factor T was obtained from tillage zoning map and tillage measure table. And then the soil erosion modulus in each sampling watershed was calculated by the equation: A=R•K•LS•B•E•T. The selection of 11 watersheds was based on the layout of sampling survey in pan-third polar region. 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 modulus is of great significance for studying the present situation of soil erosion in Pan third polar region, and it is also crucial for the implementation of the development policy of the Silk Road Economic Belt and the 21st-Century Maritime Silk Road.
1) The data includes the soil erosion modulus of 11 watersheds with a resolution of 30 m in the year of 2017 in Qinhai. 2）Based on the surface layer of rainfall erosivity R, soil erodibility K, slope length factor LS, vegetation coverage FVC, and rotation sampling survey unit, the Chinese soil erosion model (CSLE) was used to calculate soil erosin modulus in 11 watersheds respectively. Through spatial data processing (including chart linking and transformation, vector-grid conversion, and resampling), R, K, LS factors were calculated from the regional thematic map of rainfall erosivity, soil erodibility, and DEM. By half-month FVC, NPV, half-month rainfall erosivity data, we calculated the value of B factors in each sampling watershed. The value of E factor was calculated based on the remote sensing interpretation result and engineering measure factor table. The value of tillage factor T was obtained from tillage zoning map and tillage measure table. And then the soil erosion modulus in each sampling watershed was calculated by the equation: A=R•K•LS•B•E•T. The selection of 11 watersheds was based on the layout of sampling survey in pan-third polar region. 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 modulus is of great significance for studying the present situation of soil erosion in Pan third polar region, and it is also crucial for the implementation of the development policy of the Silk Road Economic Belt and the 21st-Century Maritime Silk Road.
ZHANG Wenbo
The Pan-Third Polar region has strong seismic activity, which is driven by the subduction and collision of the Indian plate, the Arab plate and the Eurasian plate. 3809 earthquakes with Magnitude 6 or larger have occurred in Pan-Third Polar region (north latitude 0-56 degrees and east longitude 43-139 degrees) since 1960. Among them, 59 earthquakes with Magnitude 8 or larger, 689 earthquakes with Magnitude 7.0-7.9 and 3061 earthquakes with Magnitude 6.0-6.9 have occurred. Earthquakes occurred mainly in the foothills of the India-Myanmar Mountains, the Himalaya Mountains, the Sulaiman Mountains, where the India Plate collided with the Eurasian plate, and the Zagros Mountains where the Arab plate collided with the Eurasian plate.
WANG Ji
The sand drift potential data sets of Central Asia in 2017 is in tif format. It covers five countries in Central Asia, including Uzbekistan, Tajikistan, Kyrgyzstan, Kazakhstan and Turkmenistan. The sand drift potential is absolutely drift potential, that is, the sum of the flux in all directions, regardless of the direction of the potential. The data was obtained by GLDAS global three-hour assimilation data extraction calculation. The temporal resolution is month, the spatial resolution is 0.25°, and the time range is 2017. This data set can be used as an important reference data for sand storm disaster assessment.
GAO Xin
Slope data of economic corridors in Silk Road can reflect the degree of steepness of the surface units of the six major economic corridors, the unit is degree (°). The spatial resolution of the data is 0.016 degrees, which is about 1.8km. The longitude range is 12.09°E-180°, and the latitude range is 10.99°S-90°N. The source is derived from the Global Relief Model built by the National Oceanic and Atmospheric Administration of the United States (NOAA). The range is cut by the border of the Silk Road. This data is one of the basic data necessary to assess the risks of natural disasters (including debris flows, landslides, flash floods, etc.) in the six economic corridors. The application frequency will be high and the prospects will be broad.
ZOU Qiang
The data set describes the hypocentre parameters of shallow-focus earthquakes that occurred in the Himalayan-Tibetan Plateau area from 1990 to 2014. Accurate seismic focal depth and focal mechanism solutions can provide an elementary scientific basis for deep Earth deformation and seismogenic structure research. The seismic waveform data are from the IRIS website (http://ds.iris.edu/wilber3/find_event). Teleseismic waveform fitting is used in processing data. The focal depth error is ±3 km. Earthquake number: earthquake number ID for different areas in chronological order Origin Time: mm/dd/yyyy (month/day/year), hh:mm (hour/minute) Earthquake location: longitude, latitude, depth Earthquake magnitude: moment magnitude (Mw) Focal mechanism solution: trend / inclination / inclination angle (strike / dip / slip) Error: the least squares method is used to determine the variance between the theoretical waveform and the observed waveform (misfit) Moho Depth: Moho
BAI Ling
The data set describes the hypocentre parameters of intermediate- and deep-focus earthquakes in the Pamir-Hindu Kush region from 1964 to 2011. The earthquake relocation results clarified the complex deformation characteristics of underground structures in the deep subduction area in the Pamir-Xindu Kush region. The seismic waveform data are from the IRIS website (http://ds.iris.edu/wilber3/find_event), and the arrival time data are from the ISC website (http://www.isc.ac.uk/) and the CEDC website (http:// Data.earthquake.cn/data/index.jsp?id=11number=9). Seismic location was determined using the teleseismic waveform fitting and the multi-scale double-difference (Multi-DD) method developed in this study. The errors in latitude and longitude data are approximately ±7 km and ±7 km, respectively. Origin Time: yyyy (year), mm (month), dd (day), hh (hour), mm (minute), ss.ss (second) Earthquake Magnitude: Magnitude (from the ISC seismic catalogue) Earthquake Location: Latitude, Longitude, Depth Hypocentre determination method: Hypocentres marked with an "F" were determined by the waveform fitting method
BAI Ling
The research project on the function and mechanism of sand-fixing afforestation of waste lignin from straw pulp and paper making belongs to the national natural science foundation of China "environment and ecological science in western China" major research program, led by wang hanjie, a researcher of the institute of aviation meteorology and chemical protection, air force equipment research institute. The project ran from January 2004 to December 2006 Remittance data of the project: 1. 2005-08-10 - sand lake - jinsha wan test site image (JPG) 2.2006 field picture of fixed sand test (JPG) 3. Meteorological data of ningxia jinshawan meteorological station (TXT text) Observation data including dry bulb temperature, wet bulb temperature, 0, 5, 10, 15, 20cm ground temperature, evaporation and air temperature were observed at 8:00,14:00 and 20:00 on August 13, 2005 4. Growth data of jinshawan community in ningxia (TXT text) The data of crown diameter and height of four samples are included. 5. Soil water data of jinshawan, ningxia (excel) Soil moisture data of 16 samples at depths of 20CM and 12CM in clear water control area and lignin spraying area by 2 hours in the daytime on August 19, 2005. 6. Soil water data of shahu lake in ningxia (excel) On August 10,11, 2005, soil moisture data of various depths of 10CM,12CM and 20CM were obtained 7. Plant growth data of sand fixation community in shahu, ningxia (excel) Plant growth statistics of 5 sample plots: species name,x,y, base, crown, height, number of plants.
WANG Hanjie
This data is digitized from the `` Map of Desertification Types of Naiman Banner, Kulun Banner, and Horqin Left-wing Rear Banner '' on the drawing.The specific information of this map is as follows: * Chief Editor: Zhu Zhenda * Deputy editors: Liu Shu and Qiu Xingmin * Edit: Feng Yukun * Mapping: Feng Yudi, Zhao Yanhua, Wang Jianhua * Double photo: Li Weimin * Field trip: Zhu Zhenda, Qiu Xingmin, Liu Shu, Shen Jingqi, Feng Yudi, Wang Yimou, Yang Youlin, Yang Taiyun, Wen Zixiang, Liu Yangxuan * Mapping unit: Prepared by Desert Research Office, Chinese Academy of Sciences * Publisher: No * Scale: 1: 300000 * Publication time: No * Legend: undulating undulating sandy loess plain, non-desertified land, grassland, saline-alkali land, woods and shrubs, arable land, mountains, sand dunes File format and naming The data is stored in ESRI Shapefile format, including the following layers: Naiman Banner, Kubian Banner, Kezuohou Banner Desertification Type Map, River, Road, Lake, Railway, Well Spring, Residential Area Data attributes Desertification Grade Vegetation Background Desertified land under development Saline-alkali land Heavily desertified land Woods and shrubs Mountain Strongly developed desertified land Potentially desertified land Lake Non-desertified land Undulating sandy loess plain 2. Projection information: Angular Unit: Degree (0.017453292519943295) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_Beijing_1954 Spheroid: Krasovsky_1940 Semimajor Axis: 6378245.000000000000000000 Semiminor Axis: 6356863.018773047300000000 Inverse Flattening: 298.300000000000010000
WANG Jianhua, ZHU Zhenda
The data is digitized from a drawing, the map of developmental degree of desertification in Daqinggou, Keerqin (HORQIN) Steppe (1981). The specific information of this map is as follows: * Chief Editor: Zhu Zhenda * Editor: Feng Yusun * Drawer: Feng Yusun, Yao Fafen, Wang Jianhua, Zhao Yanhua, Li Weimin * Mapping unit: Prepared by Desert Research Office, Chinese Academy of Sciences * Publisher: No * Scale: 1: 50000 * Publication time: No * Legend: Gully Dense Forest, Sparse Woods, Brush, Artificial Woodland, Nursery and Vegetable Garden, Grass Land, Dry Farmland (Dry Farmland), Rejected Farmland, Marsh Land, Shifting Snad-Dunes, Semi-Shifting Sand-Dunes, Semi-Fixed Sand-Dunes ), Fixed Sand-Dunes, Water Area, Rice, Residential, Highway 1. File format and naming The data is stored in ESRI Shapefile format, including the following layers: Desertification map of Daqinggou area in Horqin steppe, rivers, swamps, roads, lakes, residential areas 2. Data desertification attribute fields: Type of desertification (Shape), Grassland (Grassland), Woodland (Woodland), Woodland Density (W_density), Farmland (Farmland) 3. Projection information: Angular Unit: Degree (0.017453292519943295) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_Beijing_1954 Spheroid: Krasovsky_1940 Semimajor Axis: 6378245.000000000000000000 Semiminor Axis: 6356863.018773047300000000 Inverse Flattening: 298.300000000000010000
WANG Jianhua, ZHU Zhenda, YAO Fafen, FENG Yusun
The data is digitized from a drawing, the map of developmental degree of desertification in Daqinggou, Keerqin (HORQIN) Steppe (1975). The specific information of this map is as follows: * Chief Editor: Zhu Zhenda * Editor: Feng Yusun * Drawer: Feng Yusun, Yao Fafen, Wang Jianhua, Zhao Yanhua, Li Weimin * Mapping unit: Prepared by Desert Research Office, Chinese Academy of Sciences * Publisher: No * Scale: 1: 50000 * Publication time: No * Legend: Gully Dense Forest, Sparse Woods, Brush, Artificial Woodland, Nursery and Vegetable Garden, Grass Land, Dry Farmland (Dry Farmland), Rejected Farmland, Marsh Land, Shifting Snad-Dunes, Semi-Shifting Sand-Dunes, Semi-Fixed Sand-Dunes ), Fixed Sand-Dunes, Water Area, Rice, Residential, Highway 1. File format and naming The data is stored in ESRI Shapefile format, including the following layers: Desertification map of Daqinggou area in Horqin steppe, rivers, swamps, roads, lakes, residential areas 2. Data desertification attribute fields: Type of desertification (Shape), Grassland (Grassland), Woodland (Woodland), Woodland Density (W_density), Farmland (Farmland) 3. Projection information: Angular Unit: Degree (0.017453292519943295) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_Beijing_1954 Spheroid: Krasovsky_1940 Semimajor Axis: 6378245.000000000000000000 Semiminor Axis: 6356863.018773047300000000 Inverse Flattening: 298.300000000000010000
WANG Jianhua, ZHU Zhenda, FENG Yusun, YAO Fafen
The dataset contains all individual glacial storage (unit: km3) over the Qinghai-Tibetan Plateau in 1970s and 2000s. It is sourced from the resultant data of the paper entitled "Consolidating the Randolph Glacier Inventory and the Glacier Inventory of China over the Qinghai-Tibetan Plateau and Investigating Glacier Changes Since the mid-20th Century". The first draft of this paper has been completed and is planned to be submitted to Earth System Science Data journal. The baseline glacier inventories in 1970s and 2000s are the Randolph Glacier Inventory 4.0 dataset, and the Glacier Inventory of China, respectively. Based on the individual glacial boundaries extracted from the above-mentioned two datasets, the grid-based bedrock elevation dataset (https://www.ngdc.noaa.gov/mgg/global/global.html, DOI: 10.7289/v5c8276m), and the glacier surface elevation obtained by a slope-dependent method, the individual glacier volumes in 1970s and 2000s are then calculated. In addition, the calculated results of individual glacier volumes in this study have been compared and verified with the existent results of several glacier volumes, relevant remote sensing datasets, and the global glacier thickness dataset based on the average of multiple glacier model outputs (https://www.research-collection.ethz.ch/handle/20.500.11850/315707, doi:10.3929/ethz-b-000315707), and the errors in the calculations have also been quantified. The established dataset in this study is expected to provide the data basis for the future regional water resources estimation and glacier ablation-involved researches. Moreover, the acquisition of the data also provides a new idea for the future glacier storage estimation.
WANG Jianhua, ZHU Zhenda, FENG Yusun, YAO Fafen
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