This dataset is based on historical glacial lake disaster data, using Landsat, Sentinel, Planet and other high-resolution remote sensing satellite images. Based on the characteristics of glacial lake area, lake sedimentation, breaches, residual dam bodies, flood erosion and accumulation, the authenticity and reliability of historical glacial lake disaster data in the study area are verified. Using remote sensing technology and platforms to extract relevant parameters such as glacial lake area, water volume, dam body, and impact range, and to revise or supplement event data to improve the historical glacial lake disaster database in the research area. Since 2010, there have been a total of 19 incidents of collapse in the China Pakistan Economic Corridor. The dataset of glacial lake outburst floods provides basic data for disaster prevention and mitigation, glacial lake outburst flood evaluation, and glacial lake hydrological research in the China Pakistan Economic Corridor region.
Dataset Name: GLOFsCPECSInce2010.Shp
Attribute information:
IDs: Encoding of Ice Lake
Name: The name of the collapsed glacial lake
Longitude: Longitude of the center point of the glacial lake (°)
Latitude: Latitude of the center point of the glacial lake (°)
Elevation: Average elevation of glacial lake (m)
Dam: Types of dam bodies in glacial lakes
Date_of_outburst: Ice Lake Collapse Date
Loss_damage: GLOF's damage to downstream carriers
Reference: Reference materials
Area_foot_outburst: Area before glacial lake outburst (km2)
Recent'area: Recent glacial lake area (km2)
| collect time | 2010/01/01 - 2022/12/31 |
|---|---|
| collect place | The high mountain and high-altitude areas in the northern part of the China Pakistan Economic Corridor, along the Kashgar to Takote section of the China Pakistan Highway, all flow into the river basin |
| altitude | 240.0m - 8560.0m |
| data size | 37.2 KiB |
| data format | shp |
| Coordinate system |
1. Landsat land satellite imagery data: from the website of the United States Geological Survey( https://www.usgs.gov/ )Geospatial Data Cloud( http://www.gscloud.cn/ )Download.
2. Sentinel-2 satellite imagery data: from the European Space Agency( https://dataspace.copernicus.eu/ )Download.
3. DEM data: SRTM DEM data with a spatial resolution of 1 ", download link: http://imagico.de/map/demsearch.php .
4. Historical Ice Lake Disaster Data of China Pakistan Economic Corridor
Nie, Y. et al., 2023. Glacial lake outburst floods threaten Asia's infrastructure. Sci. Bull., 68: 1361-1365.
Zheng, G., 2021. Numerous unreported glacial lake outburst floods in the Third Pole revealed by high-resolution satellite data and geomorphological evidence. Sci. Bull., 66:1270-1273.
Veh, G., 2019. Unchanged frequency of moraine-dammed glacial lake outburst floods in the Himalaya. Nat. Clim. chang., 5(9): 379-3838.
1. Collection and screening of historical disaster data: Collect GLOF events in the China Pakistan Economic Corridor from various channels and screen for events that have occurred since 2010.
2. Verification of disaster events: False color synthesis of Landsat and Sentinel-2 satellite images, based on Landsat, Sentinel and other high-resolution remote sensing satellite images, using characteristics such as glacial lake area, lake sedimentation, breaches, residual dam bodies, flood erosion and accumulation, to verify the reliability of the collected GLOF events.
3. Parameter extraction: Using remote sensing technology and platforms to extract relevant parameters such as glacial lake area, water volume, dam body, and impact range, correcting or supplementing event data, and improving the historical glacial lake disaster database in the research area
4. Interaction inspection and quality control: Further verify the reliability of events through interaction inspection.
The glacial lake outburst flood event has undergone strict quality control, and each event has corresponding evidence, with a reliability of over 95%.
| # | number | name | type |
| 1 | 2022YFF0711704-05 | National key R & D plan | |
| 2 | 4217012226 | National Natural Science Foundation of China | |
| 3 | 2022YFF0711704-04 | National key R & D plan | |
| 4 | 2022YFF0711703 | Permafrost Variable Rapid Change Intelligent Discovery and Evolution Perception Data Engineering | National key R & D plan |
This work is licensed under a
Creative
Commons Attribution 4.0 International License.
| # | title | file size |
|---|---|---|
| 1 | _ncdc_meta_.json | 7.8 KiB |
| 2 | 冰湖溃决洪水 |
©Copyright 2005-. Northwest Institute of Eco-Environment and Resources, CAS.
Donggang West Road 320, Lanzhou, Gansu, China (730000)

