Torrential rainfall-triggered shallow landslide characteristics and susceptibility assessment using ensemble data-driven models in the Dongjiang Reservoir Watershed, China-Reference-Cited by-同舟云学术

Torrential rainfall-triggered shallow landslide characteristics and susceptibility assessment using ensemble data-driven models in the Dongjiang Reservoir Watershed, China

Published:2019-06 Issue:2 Volume:97 Page:579-609
ISSN:0921-030X
Container-title:Natural Hazards
language:en
Short-container-title:Nat Hazards

Author:

Dou Jie^ORCID,Yunus Ali P.,Xu Yueren,Zhu Zhongfan,Chen Chi-Wen,Sahana Mehebub,Khosravi Khabat,Yang Yong,Pham Binh Thai

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Water Science and Technology

Link

http://link.springer.com/content/pdf/10.1007/s11069-019-03659-4.pdf

Reference60 articles.

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2. Arnone E, Francipane A, Noto LV et al (2014) Strategies investigation in using artificial neural network for landslide susceptibility mapping: application to a Sicilian catchment. J Hydroinform. https://doi.org/10.2166/hydro.2013.191

3. Arnone E, Francipane A, Scarbaci A et al (2016) Effect of raster resolution and polygon-conversion algorithm on landslide susceptibility mapping. Environ Model Softw. https://doi.org/10.1016/j.envsoft.2016.07.016

4. Asano Y, Uchida T, Ohte N (2003) Hydrologic and geochemical influences on the dissolved silica concentration in natural water in a steep headwater catchment. Geochim Cosmochim Acta . https://doi.org/10.1016/S0016-7037(02)01342-X

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