Articles | Volume 17, issue 11
https://doi.org/10.5194/hess-17-4367-2013
© Author(s) 2013. 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-17-4367-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
06 Nov 2013
Research article |
| 06 Nov 2013
Modeling root reinforcement using a root-failure Weibull survival function
M. Schwarz
Bern University of Applied Sciences (BFH), Langgasse 85, 3052 Zollikofen, Switzerland
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Zurcherstrasse 111, 8903 Birmensdorf, Switzerland
EcorisQ, route des trois villages, 38660 Saint Hilaire du Touvet, France
F. Giadrossich
Department of Agriculture, University of Sassari, via Enrico de Nicola 1, 07100 Sassari, Italy
Nucleo Ricerca Desertificazione (NRD), viale Italia 39, 07100 Sassari, Italy
D. Cohen
Institute for Environmental Sciences, University of Geneva, Route de Drize 7, 1227 Carouge, Switzerland
Department of Geological and Atmospheric Sciences, Iowa State University, 253 Science I, Ames, IA 50011, USA
Related authors
Christoph Schaller, Luuk Dorren, Massimiliano Schwarz, Christine Moos, Arie C. Seijmonsbergen, and E. Emiel van Loon
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-76, https://doi.org/10.5194/nhess-2024-76, 2024
Revised manuscript under review for NHESS
Short summary
Short summary
We developed a machine learning-based approach to predict the potential thickness of shallow landslides to generate improved inputs for slope stability models. We selected 21 explanatory variables including metrics on terrain, geomorphology, vegetation height, and lithology and used data from two Swiss field inventories to calibrate and test the models. The best performing machine learning model consistently reduced the mean average error by least 17 % compared to previously existing models.
Feiko Bernard van Zadelhoff, Adel Albaba, Denis Cohen, Chris Phillips, Bettina Schaefli, Luuk Dorren, and Massimiliano Schwarz
Nat. Hazards Earth Syst. Sci., 22, 2611–2635, https://doi.org/10.5194/nhess-22-2611-2022, https://doi.org/10.5194/nhess-22-2611-2022, 2022
Short summary
Short summary
Shallow landslides pose a risk to people, property and infrastructure. Assessment of this hazard and the impact of protective measures can reduce losses. We developed a model (SlideforMAP) that can assess the shallow-landslide risk on a regional scale for specific rainfall events. Trees are an effective and cheap protective measure on a regional scale. Our model can assess their hazard reduction down to the individual tree level.
Luuk Dorren, Frédéric Berger, Franck Bourrier, Nicolas Eckert, Charalampos Saroglou, Massimiliano Schwarz, Markus Stoffel, Daniel Trappmann, Hans-Heini Utelli, and Christine Moos
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-32, https://doi.org/10.5194/nhess-2022-32, 2022
Publication in NHESS not foreseen
Short summary
Short summary
In the daily practice of rockfall hazard analysis, trajectory simulations are used to delimit runout zones. To do so, the expert needs to separate "realistic" from "unrealistic" simulated groups of trajectories. This is often done on the basis of reach probability values. This paper provides a basis for choosing a reach probability threshold value for delimiting the rockfall runout zone, based on recordings and simulations of recent rockfall events at 18 active rockfall sites in Europe.
Adel Albaba, Massimiliano Schwarz, Corinna Wendeler, Bernard Loup, and Luuk Dorren
Nat. Hazards Earth Syst. Sci., 19, 2339–2358, https://doi.org/10.5194/nhess-19-2339-2019, https://doi.org/10.5194/nhess-19-2339-2019, 2019
Short summary
Short summary
We present a discrete-element-based model which is adapted and used to produce hillslope debris flows. The model parameters were calibrated using field experiments, and a very good agreement was found in terms of pressure and flow velocity. Calibration results suggested that a link might exist between the model parameters and the initial conditions of the granular material. However, to better understand this link, further investigations are required by conducting detailed lab-scale experiments.
Massimiliano Schwarz, Filippo Giadrossich, Peter Lüscher, and Peter F. Germann
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-761, https://doi.org/10.5194/hess-2017-761, 2018
Preprint withdrawn
Short summary
Short summary
Vegetation strongly influences the hydrology of hillslopes that are important for the mitigation of flood risks. In this work we present a new conceptual model that aims to link the effect of tree roots combined to the preferential flow of water. We use data from field experiments, coupled to tree position and dimension for the quantification of water preferential flow patches of a vegetated hillslope, considering topography and soil profile characteristics.
Denis Cohen and Massimiliano Schwarz
Earth Surf. Dynam., 5, 451–477, https://doi.org/10.5194/esurf-5-451-2017, https://doi.org/10.5194/esurf-5-451-2017, 2017
Short summary
Short summary
Tree roots reinforce soils on slopes. A new slope stability model is presented that computes root reinforcement including the effects of root heterogeneities and dependence of root strength on tensile and compressive strain. Our results show that roots stabilize slopes that would otherwise fail under a rainfall event. Tension in roots is more effective than compression. Redistribution of forces in roots across the hillslope plays a key role in the stability of the slope during rainfall events.
Christoph Schaller, Luuk Dorren, Massimiliano Schwarz, Christine Moos, Arie C. Seijmonsbergen, and E. Emiel van Loon
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2024-76, https://doi.org/10.5194/nhess-2024-76, 2024
Revised manuscript under review for NHESS
Short summary
Short summary
We developed a machine learning-based approach to predict the potential thickness of shallow landslides to generate improved inputs for slope stability models. We selected 21 explanatory variables including metrics on terrain, geomorphology, vegetation height, and lithology and used data from two Swiss field inventories to calibrate and test the models. The best performing machine learning model consistently reduced the mean average error by least 17 % compared to previously existing models.
Feiko Bernard van Zadelhoff, Adel Albaba, Denis Cohen, Chris Phillips, Bettina Schaefli, Luuk Dorren, and Massimiliano Schwarz
Nat. Hazards Earth Syst. Sci., 22, 2611–2635, https://doi.org/10.5194/nhess-22-2611-2022, https://doi.org/10.5194/nhess-22-2611-2022, 2022
Short summary
Short summary
Shallow landslides pose a risk to people, property and infrastructure. Assessment of this hazard and the impact of protective measures can reduce losses. We developed a model (SlideforMAP) that can assess the shallow-landslide risk on a regional scale for specific rainfall events. Trees are an effective and cheap protective measure on a regional scale. Our model can assess their hazard reduction down to the individual tree level.
Luuk Dorren, Frédéric Berger, Franck Bourrier, Nicolas Eckert, Charalampos Saroglou, Massimiliano Schwarz, Markus Stoffel, Daniel Trappmann, Hans-Heini Utelli, and Christine Moos
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-32, https://doi.org/10.5194/nhess-2022-32, 2022
Publication in NHESS not foreseen
Short summary
Short summary
In the daily practice of rockfall hazard analysis, trajectory simulations are used to delimit runout zones. To do so, the expert needs to separate "realistic" from "unrealistic" simulated groups of trajectories. This is often done on the basis of reach probability values. This paper provides a basis for choosing a reach probability threshold value for delimiting the rockfall runout zone, based on recordings and simulations of recent rockfall events at 18 active rockfall sites in Europe.
Thomas Bueche, Marko Wenk, Benjamin Poschlod, Filippo Giadrossich, Mario Pirastru, and Mark Vetter
Geosci. Model Dev., 13, 565–580, https://doi.org/10.5194/gmd-13-565-2020, https://doi.org/10.5194/gmd-13-565-2020, 2020
Short summary
Short summary
The R-based graphical user interface glmGUI provides tools for pre- and postprocessing of General Lake Model (GLM) simulations. This includes an autocalibration, parameter sensitivity analysis, and several plot options. The model parameters can be analyzed and calibrated for the simulation output variables water temperature and lake level. The toolbox is tested for two sites (lake Ammersee, Germany, and lake Baratz, Italy).
Adel Albaba, Massimiliano Schwarz, Corinna Wendeler, Bernard Loup, and Luuk Dorren
Nat. Hazards Earth Syst. Sci., 19, 2339–2358, https://doi.org/10.5194/nhess-19-2339-2019, https://doi.org/10.5194/nhess-19-2339-2019, 2019
Short summary
Short summary
We present a discrete-element-based model which is adapted and used to produce hillslope debris flows. The model parameters were calibrated using field experiments, and a very good agreement was found in terms of pressure and flow velocity. Calibration results suggested that a link might exist between the model parameters and the initial conditions of the granular material. However, to better understand this link, further investigations are required by conducting detailed lab-scale experiments.
Massimiliano Schwarz, Filippo Giadrossich, Peter Lüscher, and Peter F. Germann
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-761, https://doi.org/10.5194/hess-2017-761, 2018
Preprint withdrawn
Short summary
Short summary
Vegetation strongly influences the hydrology of hillslopes that are important for the mitigation of flood risks. In this work we present a new conceptual model that aims to link the effect of tree roots combined to the preferential flow of water. We use data from field experiments, coupled to tree position and dimension for the quantification of water preferential flow patches of a vegetated hillslope, considering topography and soil profile characteristics.
Denis Cohen and Massimiliano Schwarz
Earth Surf. Dynam., 5, 451–477, https://doi.org/10.5194/esurf-5-451-2017, https://doi.org/10.5194/esurf-5-451-2017, 2017
Short summary
Short summary
Tree roots reinforce soils on slopes. A new slope stability model is presented that computes root reinforcement including the effects of root heterogeneities and dependence of root strength on tensile and compressive strain. Our results show that roots stabilize slopes that would otherwise fail under a rainfall event. Tension in roots is more effective than compression. Redistribution of forces in roots across the hillslope plays a key role in the stability of the slope during rainfall events.
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Hydrol. Earth Syst. Sci., 22, 2759–2773, https://doi.org/10.5194/hess-22-2759-2018, https://doi.org/10.5194/hess-22-2759-2018, 2018
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Guillaume Le Bihan, Olivier Payrastre, Eric Gaume, David Moncoulon, and Frédéric Pons
Hydrol. Earth Syst. Sci., 21, 5911–5928, https://doi.org/10.5194/hess-21-5911-2017, https://doi.org/10.5194/hess-21-5911-2017, 2017
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Ashley Wright, Jeffrey P. Walker, David E. Robertson, and Valentijn R. N. Pauwels
Hydrol. Earth Syst. Sci., 21, 3827–3838, https://doi.org/10.5194/hess-21-3827-2017, https://doi.org/10.5194/hess-21-3827-2017, 2017
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The accurate reduction of hydrologic model input data is an impediment towards understanding input uncertainty and model structural errors. This paper compares the ability of two transforms to reduce rainfall input data. The resultant transforms are compressed to varying extents and reconstructed before being evaluated with standard simulation performance summary metrics and descriptive statistics. It is concluded the discrete wavelet transform is most capable of preserving rainfall time series.
Ricardo Zubieta, Augusto Getirana, Jhan Carlo Espinoza, Waldo Lavado-Casimiro, and Luis Aragon
Hydrol. Earth Syst. Sci., 21, 3543–3555, https://doi.org/10.5194/hess-21-3543-2017, https://doi.org/10.5194/hess-21-3543-2017, 2017
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This paper indicates that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, in comparison to observed rainfall (by 11.1 % and 15.7 %, respectively). Statistical analysis indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets for estimating observed streamflows in Andean–Amazonian regions (Ucayali Basin, southern regions of the Amazon Basin of Peru and Ecuador).
Anna Botto, Daniele Ganora, Pierluigi Claps, and Francesco Laio
Hydrol. Earth Syst. Sci., 21, 3353–3358, https://doi.org/10.5194/hess-21-3353-2017, https://doi.org/10.5194/hess-21-3353-2017, 2017
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The paper provides an easy-to-use implementation of the UNCODE framework, which allows one to estimate the design flood value by directly accounting for sample uncertainty. Other than a design tool, this methodology is also a practical way to quantify the value of data in the design process.
Amin Elshorbagy, Raja Bharath, Anchit Lakhanpal, Serena Ceola, Alberto Montanari, and Karl-Erich Lindenschmidt
Hydrol. Earth Syst. Sci., 21, 2219–2232, https://doi.org/10.5194/hess-21-2219-2017, https://doi.org/10.5194/hess-21-2219-2017, 2017
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Flood mapping is one of Canada's major national interests. This work presents a simple and effective method for large-scale flood hazard and risk mapping, applied in this study to Canada. Readily available data, such as remote sensing night-light data, topography, and stream network were used to create the maps.
D. C. Verdon-Kidd and A. S. Kiem
Hydrol. Earth Syst. Sci., 19, 4735–4746, https://doi.org/10.5194/hess-19-4735-2015, https://doi.org/10.5194/hess-19-4735-2015, 2015
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Rainfall intensity-frequency-duration (IFD) relationships are required for the design and planning of water supply and management systems around the world. Currently IFD information is based on the "stationary climate assumption". However, this paper provides evidence of regime shifts in annual maxima rainfall time series using 96 daily rainfall stations and 66 sub-daily rainfall stations across Australia. Importantly, current IFD relationships may under- or overestimate the design rainfall.
P. A. Marker, N. Foged, X. He, A. V. Christiansen, J. C. Refsgaard, E. Auken, and P. Bauer-Gottwein
Hydrol. Earth Syst. Sci., 19, 3875–3890, https://doi.org/10.5194/hess-19-3875-2015, https://doi.org/10.5194/hess-19-3875-2015, 2015
H. Vernieuwe, S. Vandenberghe, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 19, 2685–2699, https://doi.org/10.5194/hess-19-2685-2015, https://doi.org/10.5194/hess-19-2685-2015, 2015
H. Vuollekoski, M. Vogt, V. A. Sinclair, J. Duplissy, H. Järvinen, E.-M. Kyrö, R. Makkonen, T. Petäjä, N. L. Prisle, P. Räisänen, M. Sipilä, J. Ylhäisi, and M. Kulmala
Hydrol. Earth Syst. Sci., 19, 601–613, https://doi.org/10.5194/hess-19-601-2015, https://doi.org/10.5194/hess-19-601-2015, 2015
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The global potential for collecting usable water from dew on an
artificial collector sheet was investigated by utilising 34 years of
meteorological reanalysis data as input to a dew formation model. Continental dew formation was found to be frequent and common, but daily yields were
mostly below 0.1mm.
D. E. Mora, L. Campozano, F. Cisneros, G. Wyseure, and P. Willems
Hydrol. Earth Syst. Sci., 18, 631–648, https://doi.org/10.5194/hess-18-631-2014, https://doi.org/10.5194/hess-18-631-2014, 2014
M. T. Pham, W. J. Vanhaute, S. Vandenberghe, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 17, 5167–5183, https://doi.org/10.5194/hess-17-5167-2013, https://doi.org/10.5194/hess-17-5167-2013, 2013
G. Di Baldassarre, A. Viglione, G. Carr, L. Kuil, J. L. Salinas, and G. Blöschl
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