Articles | Volume 20, issue 11
https://doi.org/10.5194/hess-20-4585-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-20-4585-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
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
CORRESPONDING AUTHOR
University of Calabria Dipartimento di Ingegneria Informatica,
Modellistica, Elettronica e Sistemistica Ponte Pietro Bucci, Cubo 41/b,
87036 Rende, Italy
Giovanna Capparelli
University of Calabria Dipartimento di Ingegneria Informatica,
Modellistica, Elettronica e Sistemistica Ponte Pietro Bucci, Cubo 41/b,
87036 Rende, Italy
Pasquale Versace
University of Calabria Dipartimento di Ingegneria Informatica,
Modellistica, Elettronica e Sistemistica Ponte Pietro Bucci, Cubo 41/b,
87036 Rende, Italy
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This study documents a state-of-the-art estimation of the water budget (rainfall, evapotranspiration, discharge, and soil and groundwater storage) components for the Upper Blue Nile river. The budget uses various JGrass-NewAGE components, satellite data and all ground measurements available. The analysis shows that precipitation of the basin is 1360 ± 230 mm per year. Evapotranspiration accounts for 56 %, runoff is 33 %, and storage varies from minus 10 % to plus 17 % of the annual water budget.
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Landslides are a threat not only to people but also to important infrastructure, like highways. Nowadays there are several monitoring systems that are able to detect slope displacements in order to give prompt alarms. On the other hand, such instruments produce a huge amount of information, which is often not totally used and which can also represent an issue for data storage and transmission. In this paper we explain how we dealt with the large quantity of data provided by one of these tools.
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Pedro Henrique Lima Alencar, José Carlos de Araújo, and Adunias dos Santos Teixeira
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Fabien Cochand, Daniel Käser, Philippe Grosvernier, Daniel Hunkeler, and Philip Brunner
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Felipe Hernández and Xu Liang
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Anna Botto, Enrica Belluco, and Matteo Camporese
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Peter Metcalfe, Keith Beven, Barry Hankin, and Rob Lamb
Hydrol. Earth Syst. Sci., 22, 2589–2605, https://doi.org/10.5194/hess-22-2589-2018, https://doi.org/10.5194/hess-22-2589-2018, 2018
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Flooding is a significant hazard and extreme events in recent years have focused attention on effective means of reducing its risk. An approach known as natural flood management (NFM) seeks to increase flood resilience by a range of measures that work with natural processes. The paper develops a modelling approach to assess one type NFM of intervention – distributed additional hillslope storage features – and demonstrates that more strategic placement is required than has hitherto been applied.
Abraham Endalamaw, W. Robert Bolton, Jessica M. Young-Robertson, Don Morton, Larry Hinzman, and Bart Nijssen
Hydrol. Earth Syst. Sci., 21, 4663–4680, https://doi.org/10.5194/hess-21-4663-2017, https://doi.org/10.5194/hess-21-4663-2017, 2017
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This study applies plot-scale and hill-slope knowledge to a process-based mesoscale model to improve the skill of distributed hydrological models to simulate the spatially and basin-integrated hydrological processes of complex ecosystems in the sub-arctic boreal forest. We developed a sub-grid parameterization method to parameterize the surface heterogeneity of interior Alaskan discontinuous permafrost watersheds.
Antonio Hayas, Tom Vanwalleghem, Ana Laguna, Adolfo Peña, and Juan V. Giráldez
Hydrol. Earth Syst. Sci., 21, 235–249, https://doi.org/10.5194/hess-21-235-2017, https://doi.org/10.5194/hess-21-235-2017, 2017
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Gully erosion is one of the most important erosion processes. In this study, we provide new data on gully dynamics over long timescales with an unprecedented temporal resolution. We apply a new Monte Carlo based method for calculating gully volumes based on orthophotos and, especially, for constraining uncertainties of these estimations. Our results show that gully erosion rates are highly variable from year to year and significantly higher than other erosion processes.
Carlotta Scudeler, Luke Pangle, Damiano Pasetto, Guo-Yue Niu, Till Volkmann, Claudio Paniconi, Mario Putti, and Peter Troch
Hydrol. Earth Syst. Sci., 20, 4061–4078, https://doi.org/10.5194/hess-20-4061-2016, https://doi.org/10.5194/hess-20-4061-2016, 2016
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Very few studies have applied a physically based hydrological model with integrated and distributed multivariate observation data of both flow and transport phenomena. In this study we address this challenge for a hillslope-scale unsaturated zone isotope tracer experiment. The results show how model complexity evolves as the number and detail of simulated responses increases. Possible gaps in process representation for simulating solute transport phenomena in very dry soils are discussed.
Bruno Cheviron and Roger Moussa
Hydrol. Earth Syst. Sci., 20, 3799–3830, https://doi.org/10.5194/hess-20-3799-2016, https://doi.org/10.5194/hess-20-3799-2016, 2016
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This review paper investigates the determinants of modelling choices for numerous applications of 1-D free-surface flow and morphodynamics in hydrology and hydraulics. Each case study has a signature composed of given contexts (spatiotemporal scales, flow typology, and phenomenology) and chosen concepts (refinement and subscales of the flow model). This review proposes a normative procedure possibly enriched by the community for a larger, comprehensive and updated image of modelling strategies.
F. Todisco, L. Brocca, L. F. Termite, and W. Wagner
Hydrol. Earth Syst. Sci., 19, 3845–3856, https://doi.org/10.5194/hess-19-3845-2015, https://doi.org/10.5194/hess-19-3845-2015, 2015
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We developed a new formulation of USLE, named Soil Moisture for Erosion (SM4E), that directly incorporates soil moisture information. SM4E is applied here by using modeled data and satellite observations obtained from the Advanced SCATterometer (ASCAT). SM4E is found to outperform USLE and USLE-MM models in silty–clay soil in central Italy. Through satellite data, there is the potential of applying SM4E for large-scale monitoring and quantification of the soil erosion process.
W. Shao, T. A. Bogaard, M. Bakker, and R. Greco
Hydrol. Earth Syst. Sci., 19, 2197–2212, https://doi.org/10.5194/hess-19-2197-2015, https://doi.org/10.5194/hess-19-2197-2015, 2015
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The effect of preferential flow on the stability of landslides is studied through numerical simulation of two types of rainfall events on a hypothetical hillslope. A model is developed that consists of two parts. The first part is a model for combined saturated/unsaturated subsurface flow and is used to compute the spatial and temporal water pressure response to rainfall. Preferential flow is simulated with a dual-permeability continuum model consisting of a matrix/preferential flow domain.
O. Fovet, L. Ruiz, M. Hrachowitz, M. Faucheux, and C. Gascuel-Odoux
Hydrol. Earth Syst. Sci., 19, 105–123, https://doi.org/10.5194/hess-19-105-2015, https://doi.org/10.5194/hess-19-105-2015, 2015
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We studied the annual hysteretic patterns observed between stream flow and water storage in the saturated and unsaturated zones of a hillslope and a riparian zone. We described these signatures using a hysteresis index and then used this to assess conceptual hydrological models. This led us to identify four hydrological periods and a clearly distinct behaviour between riparian and hillslope groundwaters and to provide new information about the model performances.
D. J. Peres and A. Cancelliere
Hydrol. Earth Syst. Sci., 18, 4913–4931, https://doi.org/10.5194/hess-18-4913-2014, https://doi.org/10.5194/hess-18-4913-2014, 2014
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A Monte Carlo approach, combining rainfall-stochastic models and hydrological and slope stability physically based models, is used to derive rainfall thresholds of landslide triggering. The uncertainty in threshold assessment related to variability of rainfall intensity within events and to past rainfall (antecedent rainfall) is analyzed and measured via ROC-based indexes, with a specific focus dedicated to the widely used power-law rainfall intensity-duration (I-D) thresholds.
D. Windhorst, P. Kraft, E. Timbe, H.-G. Frede, and L. Breuer
Hydrol. Earth Syst. Sci., 18, 4113–4127, https://doi.org/10.5194/hess-18-4113-2014, https://doi.org/10.5194/hess-18-4113-2014, 2014
G. Capparelli and P. Versace
Hydrol. Earth Syst. Sci., 18, 3225–3237, https://doi.org/10.5194/hess-18-3225-2014, https://doi.org/10.5194/hess-18-3225-2014, 2014
D. Penna, M. Borga, G. T. Aronica, G. Brigandì, and P. Tarolli
Hydrol. Earth Syst. Sci., 18, 2127–2139, https://doi.org/10.5194/hess-18-2127-2014, https://doi.org/10.5194/hess-18-2127-2014, 2014
G.-Y. Niu, D. Pasetto, C. Scudeler, C. Paniconi, M. Putti, P. A. Troch, S. B. DeLong, K. Dontsova, L. Pangle, D. D. Breshears, J. Chorover, T. E. Huxman, J. Pelletier, S. R. Saleska, and X. Zeng
Hydrol. Earth Syst. Sci., 18, 1873–1883, https://doi.org/10.5194/hess-18-1873-2014, https://doi.org/10.5194/hess-18-1873-2014, 2014
J. Tao and A. P. Barros
Hydrol. Earth Syst. Sci., 18, 367–388, https://doi.org/10.5194/hess-18-367-2014, https://doi.org/10.5194/hess-18-367-2014, 2014
J. Wienhöfer and E. Zehe
Hydrol. Earth Syst. Sci., 18, 121–138, https://doi.org/10.5194/hess-18-121-2014, https://doi.org/10.5194/hess-18-121-2014, 2014
A. Richard, S. Galle, M. Descloitres, J.-M. Cohard, J.-P. Vandervaere, L. Séguis, and C. Peugeot
Hydrol. Earth Syst. Sci., 17, 5079–5096, https://doi.org/10.5194/hess-17-5079-2013, https://doi.org/10.5194/hess-17-5079-2013, 2013
S. R. Lutz, H. J. van Meerveld, M. J. Waterloo, H. P. Broers, and B. M. van Breukelen
Hydrol. Earth Syst. Sci., 17, 4505–4524, https://doi.org/10.5194/hess-17-4505-2013, https://doi.org/10.5194/hess-17-4505-2013, 2013
Makoto Tani
Hydrol. Earth Syst. Sci., 17, 4453–4470, https://doi.org/10.5194/hess-17-4453-2013, https://doi.org/10.5194/hess-17-4453-2013, 2013
M. N. Papa, V. Medina, F. Ciervo, and A. Bateman
Hydrol. Earth Syst. Sci., 17, 4095–4107, https://doi.org/10.5194/hess-17-4095-2013, https://doi.org/10.5194/hess-17-4095-2013, 2013
P. Fiener, K. Auerswald, F. Winter, and M. Disse
Hydrol. Earth Syst. Sci., 17, 4121–4132, https://doi.org/10.5194/hess-17-4121-2013, https://doi.org/10.5194/hess-17-4121-2013, 2013
R. Greco, L. Comegna, E. Damiano, A. Guida, L. Olivares, and L. Picarelli
Hydrol. Earth Syst. Sci., 17, 4001–4013, https://doi.org/10.5194/hess-17-4001-2013, https://doi.org/10.5194/hess-17-4001-2013, 2013
C. Lepore, E. Arnone, L. V. Noto, G. Sivandran, and R. L. Bras
Hydrol. Earth Syst. Sci., 17, 3371–3387, https://doi.org/10.5194/hess-17-3371-2013, https://doi.org/10.5194/hess-17-3371-2013, 2013
J. E. van der Spek, T. A. Bogaard, and M. Bakker
Hydrol. Earth Syst. Sci., 17, 2171–2183, https://doi.org/10.5194/hess-17-2171-2013, https://doi.org/10.5194/hess-17-2171-2013, 2013
A. M. Ireson and A. P. Butler
Hydrol. Earth Syst. Sci., 17, 2083–2096, https://doi.org/10.5194/hess-17-2083-2013, https://doi.org/10.5194/hess-17-2083-2013, 2013
A. M. J. Coenders-Gerrits, L. Hopp, H. H. G. Savenije, and L. Pfister
Hydrol. Earth Syst. Sci., 17, 1749–1763, https://doi.org/10.5194/hess-17-1749-2013, https://doi.org/10.5194/hess-17-1749-2013, 2013
G. Martelloni, S. Segoni, D. Lagomarsino, R. Fanti, and F. Catani
Hydrol. Earth Syst. Sci., 17, 1229–1240, https://doi.org/10.5194/hess-17-1229-2013, https://doi.org/10.5194/hess-17-1229-2013, 2013
C. D. Guzman, S. A. Tilahun, A. D. Zegeye, and T. S. Steenhuis
Hydrol. Earth Syst. Sci., 17, 1067–1077, https://doi.org/10.5194/hess-17-1067-2013, https://doi.org/10.5194/hess-17-1067-2013, 2013
D. M. Krzeminska, T. A. Bogaard, J.-P. Malet, and L. P. H. van Beek
Hydrol. Earth Syst. Sci., 17, 947–959, https://doi.org/10.5194/hess-17-947-2013, https://doi.org/10.5194/hess-17-947-2013, 2013
A. Peñuela, M. Javaux, and C. L. Bielders
Hydrol. Earth Syst. Sci., 17, 87–101, https://doi.org/10.5194/hess-17-87-2013, https://doi.org/10.5194/hess-17-87-2013, 2013
A. Rodhe
Hydrol. Earth Syst. Sci., 16, 3075–3082, https://doi.org/10.5194/hess-16-3075-2012, https://doi.org/10.5194/hess-16-3075-2012, 2012
G. Y. Gao, B. J. Fu, Y. H. Lü, Y. Liu, S. Wang, and J. Zhou
Hydrol. Earth Syst. Sci., 16, 2347–2364, https://doi.org/10.5194/hess-16-2347-2012, https://doi.org/10.5194/hess-16-2347-2012, 2012
C. E. Ballard, N. McIntyre, and H. S. Wheater
Hydrol. Earth Syst. Sci., 16, 2299–2310, https://doi.org/10.5194/hess-16-2299-2012, https://doi.org/10.5194/hess-16-2299-2012, 2012
D. M. Krzeminska, T. A. Bogaard, Th. W. J. van Asch, and L. P. H. van Beek
Hydrol. Earth Syst. Sci., 16, 1561–1576, https://doi.org/10.5194/hess-16-1561-2012, https://doi.org/10.5194/hess-16-1561-2012, 2012
T. Maurer, A. Schneider, and H. H. Gerke
Hydrol. Earth Syst. Sci., 15, 3617–3638, https://doi.org/10.5194/hess-15-3617-2011, https://doi.org/10.5194/hess-15-3617-2011, 2011
J. Klaus and E. Zehe
Hydrol. Earth Syst. Sci., 15, 2127–2144, https://doi.org/10.5194/hess-15-2127-2011, https://doi.org/10.5194/hess-15-2127-2011, 2011
M. C. Westhoff, T. A. Bogaard, and H. H. G. Savenije
Hydrol. Earth Syst. Sci., 15, 1945–1957, https://doi.org/10.5194/hess-15-1945-2011, https://doi.org/10.5194/hess-15-1945-2011, 2011
J. Minet, E. Laloy, S. Lambot, and M. Vanclooster
Hydrol. Earth Syst. Sci., 15, 1323–1338, https://doi.org/10.5194/hess-15-1323-2011, https://doi.org/10.5194/hess-15-1323-2011, 2011
T. Sabzevari, A. Talebi, R. Ardakanian, and A. Shamsai
Hydrol. Earth Syst. Sci., 14, 891–900, https://doi.org/10.5194/hess-14-891-2010, https://doi.org/10.5194/hess-14-891-2010, 2010
Y. Zhang, S. K. Carey, W. L. Quinton, J. R. Janowicz, J. W. Pomeroy, and G. N. Flerchinger
Hydrol. Earth Syst. Sci., 14, 729–750, https://doi.org/10.5194/hess-14-729-2010, https://doi.org/10.5194/hess-14-729-2010, 2010
Cited articles
Abera W., Antonello, A., Franceschi, S., Formetta, G., and Rigon, R.: The uDig Spatial Toolbox for hydro-geomorphic analysis, Geomorphology, 4, 1–19, available at: http://www.geomorphology.org.uk/sites/default/files/geom_tech_chapters/2.4.1_GISToolbox.pdf (last access: 12 November 2016), 2014.
Beguería, S.: Validation and evaluation of predictive models in hazard assessment and risk management, Nat. Hazards, 37, 315–329, 2006.
Bennett, N. D., Croke, B. F., Guariso, G., Guillaume, J. H., Hamilton, S. H., Jakeman, A. J., Marsili-Libelli, S., Newham, L. T., Norton, J. P., Perrin, C., and Pierce, S. A.: Characterising performance of environmental models, Environ. Modell. Softw., 40, 1–20, 2013.
Borga, M., Dalla Fontana, G., and Cazorzi, F.: Analysis of topographic and climatic control on rainfall-triggered shallow landsliding using a quasi-dynamic wetness index, J. Hydrol., 268, 56–71, 2002.
Brabb, E. E.: Innovative approaches to landslide hazard and risk mapping, Proceedings of the 4th International Symposium on Landslides, 16–21 September, Toronto, Ontario, Canada, Canadian Geotechnical Society, Toronto, Ontario, Canada, 1, 307–324, 1984.
Brenning, A.: Spatial prediction models for landslide hazards: review, comparison and evaluation, Nat. Hazards Earth Syst. Sci., 5, 853–862, https://doi.org/10.5194/nhess-5-853-2005, 2005.
Capparelli, G. and Versace, P.: FLaIR and SUSHI: two mathematical models for early warning of landslides induced by rainfall, Landslides, 8, 67–79, 2011.
Capparelli, G., Iaquinta, P., Iovine, G. G. R., Terranova, O. G., and Versace, P.: Modelling the rainfall-induced mobilization of a large slope movement in northern Calabria, Nat. Hazards, 61, 247–256, 2012.
Carrara, A. and Merenda, L.: Landslide inventory in Northern Calabria, Southern Italy, Geol. Soc. Am. Bull., 87, 1153–1162, 1976.
Casadei, M., Dietrich, W. E., and Miller, N. L.: Testing a model for predicting the timing and location of shallow landslide initiation in soil mantled landscapes, Earth Surf. Process. Landf., 28, 925–950, 2003.
Cascini, L., Bonnard, C., Corominas, J., Jibson, R., and Montero-Olarte, J.: Landslide hazard and risk zoning for urban planning and development, Landslide Risk Management, Taylor and Francis, London, 199–235, 2005.
Catani, F., Casagli, N., Ermini, L., Righini, G., and Menduni, G.: Landslide hazard and risk mapping at catchment scale in the Arno River basin, Landslides, 2, 329–342, 2005.
Chung, C.-J. F., Fabbri, A. G., and van Westen, C. J.: Multivariate regression analysis for landslide hazard zonation, edited by: Carrara, A. and Guzzetti, F., Geographical Information Systems in assessing natural hazards, Kluwer Academic Publishers, Dordrecht, 5, 107–134, 1995.
Colella, A., De Boer, P. L., and Nio, S. D.: Sedimentology of a marine intermontane Pleistocene Gilbert-type fan-delta complex in the Crati Basin, Calabria, southern Italy, Sedimentology, 34, 721–736, 1987.
Conforti, M., Aucelli, P. P. C., Robustelli, G., and Scarciglia, F.: Geomorphology and GIS analysis for mapping gully erosion susceptibility in the Turbolo Stream catchment (Northern Calabria, Italy), Nat. Hazards, 56, 881–898, 2011.
Conforti, M., Pascale, S., Robustelli, G., and Sdao, F.: Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo River catchment (northern Calabria, Italy), Catena, 113, 236–250, 2014.
Corominas, J., Van Westen, C., Frattini, P., Cascini, L., Malet, J. P., Fotopoulou, S., Catani, F., Van Den Eeckhaut, M., Mavrouli, O., Agliardi, F., and Pitilakis, K.: Recommendations for the quantitative analysis of landslide risk, Bull. Eng. Geol. Environ., 73, 209–263, 2014.
David, O., Ascough II, J. C., Lloyd, W., Green, T. R., Rojas, K. W., Leavesley, G. H., and Ahuja, L. R.: A software engineering perspective on environmental modeling framework design: The Object Modeling System, Environ. Modell. Softw., 39, 201–213, 2013.
Dietrich, W. E., Bellugi, D., and Real De Asua, R.: Validation of the Shallow Landslide Model, SHALSTAB, for Forest Management, in: Land Use and Watersheds: Human Influence on Hydrology and Geomorphology in Urban and Forest Areas, edited by: Wigmosta, M. S. and Burges, S. J., American Geophysical Union, Washington, D. C., 1, 195–227, https://doi.org/10.1029/WS002p0195, 2001.
Duan, Q., Sorooshian, S., and Gupta, V.: Effective and efficient global optimization for conceptual rainfall-runoff models, Water Resour. Res., 28, 1015–1031, 1992.
Fabbricatore, D., Robustelli, G., and Muto, F.: Facies analysis and depositional architecture of shelf-type deltas in the Crati Basin (Calabrian Arc, south Italy), Boll. Soc. Geol. It., 133, 131–148 2014.
Formetta, G., Mantilla, R., Franceschi, S., Antonello, A., and Rigon, R.: The JGrass-NewAge system for forecasting and managing the hydrological budgets at the basin scale: models of flow generation and propagation/routing, Geosci. Model Dev., 4, 943–955, https://doi.org/10.5194/gmd-4-943-2011, 2011.
Formetta, G., Antonello, A., Franceschi, S., David, O., and Rigon, R.: Hydrological modelling with components: A GIS-based open-source framework, Environ. Modell. Softw., 55, 190–200, 2014a.
Formetta, G., Capparelli, G., Rigon, R., and Versace, P.: Physically based landslide susceptibility models with different degree of complexity: calibration and verification. International Environmental Modelling and Software Society (iEMSs), 7th Intl. Congress on Env. Modelling and Software, San Diego, CA, 15–19 June, USA, edited by: Ames, D. P., Quinn, N. W. T., and Rizzoli, A. E., http://www.iemss.org/sites/iemss2014/papers/iemss2014_submission_157.pdf (last access: 12 November 2015), 2014b.
Formetta, G., Capparelli, G., and Versace, P.: Modelling rainfall induced shallow landslides in the Landslide Early Warning Integrated System project, Slopes and Geohazards, 1747–1752, available at: http://www.icevirtuallibrary.com/doi/abs/10.1680/ecsmge.60678.vol4.260 (last access: 12 November 2015), 2015.
Formetta, G., Simoni, S., Godt, J. W., Lu, N., and Rigon, R.: Geomorphological control on variably saturated hillslope hydrology and slope instability, Water Resour. Res., 52, 4590–4607, 2016.
Frattini, P., Crosta, G., and Carrara, A.: Techniques for evaluating the performance of landslide susceptibility models, Eng. Geol., 111, 62–72, 2010.
Glade, T. and Crozier, M. J.: A review of scale dependency in landslide hazard and risk analysis, Landsl. Hazard Risk, 3, 75–138, 2005.
Goodenough, D. J., Rossmann, K., and Lusted, L. B.: Radiographic applications of receiver operating characteristic (ROC) analysis, Radiology, 110, 89–95, 1974.
Grahm, J.: Methods of slope stability analysis, in: Slope instability, edited by: Brunsden, D. and Prior, D. B., Wiley, New York, 171–215, 1984.
Guzzetti, F., Carrara, A., Cardinali, M., and Reichenbach, P.: Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy, Geomorphology, 31, 181–216, 1999.
Guzzetti, F., Reichenbach, P., Ardizzone, F., Cardinali, M., and Galli, M.: Estimating the quality of landslide susceptibility models, Geomorphology, 81, 166–184, 2006.
Hay, L. E., Leavesley, G. H., Clark, M. P., Markstrom, S. L., Viger, R. J., and Umemoto, M.: Step-Wise, Multiple-Objective Calibration of a Hydrologic Model for a Snowmelt-Dominated Basin, J. Am. Water Resour. Assoc., 42, 877–890, 2006.
Huang, J.-C., Kao, S.-J., Hsu, M.-L., and Liu, Y.-A.: Influence of Specific Contributing Area algorithms on slope failure prediction in landslide modeling, Nat. Hazards Earth Syst. Sci., 7, 781–792, https://doi.org/10.5194/nhess-7-781-2007, 2007.
Iovine, G., Petrucci, O., Rizzo, V., nad Tansi, C.: The March 7th 2005 Cavallerizzo (Cerzeto) landslide in Calabria – Southern Italy. Engineering geology for tomorrow's cities – the 10th IAEG congress, Nottingham (UK), The Geological Society of London, Paper number 785, 2006.
Iovine, G. G. R., Lollino, P., Gariano, S. L., and Terranova, O. G.: Coupling limit equilibrium analyses and real-time monitoring to refine a landslide surveillance system in Calabria (southern Italy), Nat. Hazards Earth Syst. Sci., 10, 2341–2354, https://doi.org/10.5194/nhess-10-2341-2010, 2010.
Jolliffe, I. T. and Stephenson, D. B. (Eds.): Forecast verification: a practitioner's guide in atmospheric science, University of Exeter, UK, John Wiley & Sons, 292 pp., 2012.
Kennedy, J. and Eberhart, R.: Particle swarm optimization. Neural Networks, Proceedings, IEEE International Conference, Vol. 4. Perth, WA, IEEE, 1942–1948, 1995.
Lanzafame, G. and Tortorici, L.: La tettonica recente del Fiume Crati (Calabria), Geogr. Fis. Din. Quat., 4, 11–21, 1984.
Lee, S., Choi, J., and Min, K.: Landslide susceptibility analysis and verification using the Bayesian probability model, Environ. Geol., 43, 120–131, 2002.
Lu, N. and Godt, J.: Infinite slope stability under steady unsaturated seepage conditions, Water Resour. Res., 44, W11404, https://doi.org/10.1029/2008WR006976, 2008.
Lu, N. and Godt, J. W.: Hillslope hydrology and stability, Cambridge University Press, 458 pp., 2013.
Milledge, D. G., Bellugi, D., McKean, J. A., Densmore, A. L., and Dietrich, W. E.: A multidimensional stability model for predicting shallow landslide size and shape across landscapes, J. Geophys. Res.-Earth, 119, 2481–2504, 2014.
Montgomery, D. R. and Dietrich, W. E.: A physically based model for the topographic control on shallow landsliding, Water Resour. Res., 30, 1153–1171, 1994.
Murdoch, D. J. and Chow, E. D.: A graphical display of large correlation matrices, Am. Stat., 50, 178–180, 1996.
Naranjo, J. L., van Westen, C. J., and Soeters, R.: Evaluating the use of training areas in bivariate statistical landslide hazard analysis: a case study in Colombia, ITC Journal, 3, 292–300, 1994.
Park, N. W.: Application of Dempster-Shafer theory of evidence to GIS-based landslide susceptibility analysis, Environ. Earth Sci., 62, 367–376, 2011.
Park, H. J., Lee, J. H., and Woo, I.: Assessment of rainfall-induced shallow landslide susceptibility using a GIS-based probabilistic approach, Eng. Geol., 161, 1–15, 2013.
Pepe, M. S.: The Statistical Evaluation of Medical Tests for Classification and Prediction, Oxford University Press, New York, 320 pp., 2003.
Pradhan, B.: An assessment of the use of an advanced neural network model with five different training strategies for the preparation of landslide susceptibility maps, J. Data Sci., 9, 65–81, 2011.
Pradhan, B.: A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS, Comp. Geosci., 51, 350–365, 2013.
Provost, F. and Fawcett, T.: Robust classification for imprecise environments, Mach. Learn., 42, 203–231, 2001.
Rosso, R., Rulli, M. C., and Vannucchi, G.: A physically based model for the hydrologic control on shallow landsliding, Water Resour. Res., 42, W06410, https://doi.org/10.1029/2005WR004369, 2006.
Sidle, R. C. and Ochiai, H.: Landslides: processes, prediction, and land use, Vol. 18, Washington D.C., USA, American Geophysical Union, 312 pp., 2006.
Simoni, S., Zanotti, F., Bertoldi, G., and Rigon, R.: Modeling the probability of occurrence of shallow landslides and channelized debris flows using GEOtop-FS, Hydrol. Process., 22, 532–545, 2008.
Vezzani L.: I terreni plio-pleistocenici del basso Crati (Cosenza), Atti dell'Accademia Gioenia di Scienze Naturali di Catania, 6, 28–84, 1968.
Vrugt, J. A., ter Braak, C. J. F., Clark, M. P., Hyman, J. M., and Robinson, B. A.: Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation, Water Resour. Res., 44, W00B09, https://doi.org/10.1029/2007WR006720, 2008.
Young, J. and Colella, A.: Calcarenous nannofossils from the Crati Basin, in: Fan Deltas-Excursion Guidebook, edited by: Colella A., Università della Calabria, Cosenza, Italy, 79–96, 1988.
Short summary
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...
