{"title":"Multitemporal landslide inventory and susceptibility map for the Arun River Basin, Nepal","authors":"Pukar Amatya, Robert Emberson, Dalia Kirschbaum","doi":"10.1002/gdj3.240","DOIUrl":null,"url":null,"abstract":"<p>The transboundary Arun River Basin (ARB) spreads across Nepal and Tibet. Nearly 95% of the basin lies in Tibet through which the Pumqu River flows, forming the Arun River once it enters Nepal. The ARB has five large hydropower projects undergoing construction or planned for the future. Rainfall and earthquake-induced landslides, landslide-dammed lakes and landslide-induced glacial lake outburst floods pose major risks to smooth operation of these projects. To safeguard upcoming hydropower projects, areas susceptible to landslides in the ARB must be identified. We used high-resolution satellite imagery and open-source tools to generate a multitemporal landslide inventory for the basin. The rigorously quality-controlled inventory represents a yearly record of landslides from 2011 to 2020. A data-driven approach was used to map areas susceptible to landslides within the ARB. The multitemporal landslide inventory combined with other readily available Earth observation-based variables was used to create a landslide susceptibility map. The susceptibility analysis provides a valuable initial estimate of where landslides are likely to initiate. These landslide products could form the basis of more comprehensive local studies to inform hydropower project development.</p>","PeriodicalId":54351,"journal":{"name":"Geoscience Data Journal","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gdj3.240","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoscience Data Journal","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/gdj3.240","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The transboundary Arun River Basin (ARB) spreads across Nepal and Tibet. Nearly 95% of the basin lies in Tibet through which the Pumqu River flows, forming the Arun River once it enters Nepal. The ARB has five large hydropower projects undergoing construction or planned for the future. Rainfall and earthquake-induced landslides, landslide-dammed lakes and landslide-induced glacial lake outburst floods pose major risks to smooth operation of these projects. To safeguard upcoming hydropower projects, areas susceptible to landslides in the ARB must be identified. We used high-resolution satellite imagery and open-source tools to generate a multitemporal landslide inventory for the basin. The rigorously quality-controlled inventory represents a yearly record of landslides from 2011 to 2020. A data-driven approach was used to map areas susceptible to landslides within the ARB. The multitemporal landslide inventory combined with other readily available Earth observation-based variables was used to create a landslide susceptibility map. The susceptibility analysis provides a valuable initial estimate of where landslides are likely to initiate. These landslide products could form the basis of more comprehensive local studies to inform hydropower project development.
Geoscience Data JournalGEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
审稿时长
4 weeks
期刊介绍:
Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered.
An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices.
Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.