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.

File naming and required software

Usage: Based on GIS platform, import with SuperMap, ArcGIS and other software

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Cite as:

Wang, Z. (2022). Flood risk assessment data along Sichuan Tibet Railway (2015). A Big Earth Data Platform for Three Poles, DOI: 10.11888/HumanNat.tpdc.272398. CSTR: 18406.11.HumanNat.tpdc.272398. (Download the reference： RIS | Bibtex )

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

Support Program

Second Tibetan Plateau Scientific Expedition Program

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License： This work is licensed under an Attribution 4.0 International (CC BY 4.0)