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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 20, issue 11
Hydrol. Earth Syst. Sci., 20, 4585–4603, 2016
https://doi.org/10.5194/hess-20-4585-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 20, 4585–4603, 2016
https://doi.org/10.5194/hess-20-4585-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 15 Nov 2016

Research article | 15 Nov 2016

Evaluating performance of simplified physically based models for shallow landslide susceptibility

Giuseppe Formetta, Giovanna Capparelli, and Pasquale Versace Giuseppe Formetta et al.
  • University of Calabria Dipartimento di Ingegneria Informatica, Modellistica, Elettronica e Sistemistica Ponte Pietro Bucci, Cubo 41/b, 87036 Rende, Italy

Abstract. Rainfall-induced shallow landslides can lead to loss of life and significant damage to private and public properties, transportation systems, etc. Predicting locations that might be susceptible to shallow landslides is a complex task and involves many disciplines: hydrology, geotechnical science, geology, hydrogeology, geomorphology, and statistics. Two main approaches are commonly used: statistical or physically based models. Reliable model applications involve automatic parameter calibration, objective quantification of the quality of susceptibility maps, and model sensitivity analyses. This paper presents a methodology to systemically and objectively calibrate, verify, and compare different models and model performance indicators in order to identify and select the models whose behavior is the most reliable for particular case studies.

The procedure was implemented in a package of models for landslide susceptibility analysis and integrated in the NewAge-JGrass hydrological model. The package includes three simplified physically based models for landslide susceptibility analysis (M1, M2, and M3) and a component for model verification. It computes eight goodness-of-fit indices by comparing pixel-by-pixel model results and measurement data. The integration of the package in NewAge-JGrass uses other components, such as geographic information system tools, to manage input–output processes, and automatic calibration algorithms to estimate model parameters.

The system was applied for a case study in Calabria (Italy) along the Salerno–Reggio Calabria highway, between Cosenza and Altilia. The area is extensively subject to rainfall-induced shallow landslides mainly because of its complex geology and climatology. The analysis was carried out considering all the combinations of the eight optimized indices and the three models. Parameter calibration, verification, and model performance assessment were performed by a comparison with a detailed landslide inventory map for the area. The results showed that the index distance to perfect classification in the receiver operating characteristic plane (D2PC) coupled with the model M3 is the best modeling solution for our test case.

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This paper focuses on performance evaluation of simplified, physically based landslide susceptibility models. It presents a new methodology to systemically and objectively calibrate, verify, and compare different models and models performances indicators in order to individuate and select the models whose behavior is more reliable for a certain case study. The procedure was implemented in a package for landslide susceptibility analysis and integrated the open-source hydrological model NewAge.
This paper focuses on performance evaluation of simplified, physically based landslide...
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