Articles | Volume 23, issue 10
https://doi.org/10.5194/hess-23-4199-2019
https://doi.org/10.5194/hess-23-4199-2019
Research article
 | 
18 Oct 2019
Research article |  | 18 Oct 2019

Assessment of simulated soil moisture from WRF Noah, Noah-MP, and CLM land surface schemes for landslide hazard application

Lu Zhuo, Qiang Dai, Dawei Han, Ningsheng Chen, and Binru Zhao

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Cited articles

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Battistini, A., Segoni, S., Manzo, G., Catani, F., and Casagli, N. J. A. G.: Web data mining for automatic inventory of geohazards at national scale, Appl. Geogr., 43, 147–158, 2013. 
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Berti, M., Martina, M., Franceschini, S., Pignone, S., Simoni, A., and Pizziolo, M.: Probabilistic rainfall thresholds for landslide occurrence using a Bayesian approach, J. Geophys. Res.-Ea. Surf., 117, F04006, https://doi.org/10.1029/2012JF002367, 2012. 
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Short summary
This study assesses the usability of WRF model-simulated soil moisture for landslide monitoring in northern Italy. In particular, three advanced land surface model schemes (Noah, Noah-MP, and CLM4) are used to provide multi-layer soil moisture data. The results have shown Noah-MP can provide the best landslide monitoring performance. It is also demonstrated that a single soil moisture sensor located in plain area has a high correlation with a significant proportion of the study area.