Articles | Volume 25, issue 6
Research article
16 Jun 2021
Research article |  | 16 Jun 2021

Satellite rainfall products outperform ground observations for landslide prediction in India

Maria Teresa Brunetti, Massimo Melillo, Stefano Luigi Gariano, Luca Ciabatta, Luca Brocca, Giriraj Amarnath, and Silvia Peruccacci


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-42', Anonymous Referee #1, 13 Feb 2021
    • AC1: 'Reply on RC1', Maria Teresa Brunetti, 18 Feb 2021
    • AC2: 'Reply on RC1', Maria Teresa Brunetti, 04 Mar 2021
  • RC2: 'Comment on hess-2021-42', Ben Mirus, 29 Mar 2021
    • AC3: 'Reply on RC2', Maria Teresa Brunetti, 07 Apr 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Publish subject to revisions (further review by editor and referees) (19 Apr 2021) by Roberto Greco
AR by Maria Teresa Brunetti on behalf of the Authors (20 Apr 2021)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (03 May 2021) by Roberto Greco
RR by Anonymous Referee #1 (19 May 2021)
ED: Publish as is (25 May 2021) by Roberto Greco
AR by Maria Teresa Brunetti on behalf of the Authors (25 May 2021)
Short summary
Satellite and rain gauge data are tested to predict landslides in India, where the annual toll of human lives and loss of property urgently demands the implementation of strategies to prevent geo-hydrological instability. For this purpose, we calculated empirical rainfall thresholds for landslide initiation. The validation of thresholds showed that satellite-based rainfall data perform better than ground-based data, and the best performance is obtained with an hourly temporal resolution.