Satellite rainfall products outperform ground  observations for landslide prediction in India

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

doi:https://doi.org/10.5194/hess-25-3267-2021

Articles | Volume 25, issue 6

https://doi.org/10.5194/hess-25-3267-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-25-3267-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

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

Data sets

SM2RAIN-ASCAT (2007-June 2020): global daily satellite rainfall from ASCAT soil moisture L. Brocca, P. Filippucci, S. Hahn, L. Ciabatta, C. Massari, S. Camici, L. Schüller, B. Bojkov, and W. Wagner https://doi.org/10.5281/zenodo.3972958

Model code and software

CTRL–T (Calculation of Thresholds for Rainfall-induced Landslides – Tool) M. Melillo, M. T. Brunetti, S. Peruccacci, S. L. Gariano, and F. Guzzetti https://doi.org/10.5281/zenodo.4533719

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.