Sensitivity analysis and calibration of a dynamic physically based slope stability model
Physically based modelling of slope stability on a catchment scale is still a challenging task. When applying a physically based model on such a scale (1 : 10 000 to 1 : 50 000), parameters with a high impact on the model result should be calibrated to account for (i) the spatial variability of...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2017-06-01
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| Series: | Natural Hazards and Earth System Sciences |
| Online Access: | https://www.nat-hazards-earth-syst-sci.net/17/971/2017/nhess-17-971-2017.pdf |
| _version_ | 1811194227863846912 |
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| author | T. Zieher T. Zieher M. Rutzinger B. Schneider-Muntau F. Perzl D. Leidinger H. Formayer C. Geitner |
| author_facet | T. Zieher T. Zieher M. Rutzinger B. Schneider-Muntau F. Perzl D. Leidinger H. Formayer C. Geitner |
| author_sort | T. Zieher |
| collection | DOAJ |
| description | Physically based modelling of slope stability on a catchment scale
is still a challenging task. When applying a physically based model on such a
scale (1 : 10 000 to 1 : 50 000), parameters with a high impact on the
model result should be calibrated to account for (i) the spatial variability
of parameter values, (ii) shortcomings of the selected model,
(iii) uncertainties of laboratory tests and field measurements or (iv)
parameters that cannot be derived experimentally or measured in the field (e.g.
calibration constants). While systematic parameter calibration is a common
task in hydrological modelling, this is rarely done using physically based
slope stability models. In the present study a dynamic, physically based,
coupled hydrological–geomechanical slope stability model is calibrated based
on a limited number of laboratory tests and a detailed multitemporal shallow
landslide inventory covering two landslide-triggering rainfall events in the
Laternser valley, Vorarlberg (Austria). Sensitive parameters are identified
based on a local one-at-a-time sensitivity analysis. These parameters
(hydraulic conductivity, specific storage, angle of internal friction for
effective stress, cohesion for effective stress) are systematically sampled
and calibrated for a landslide-triggering rainfall event in August 2005. The
identified model ensemble, including 25 <q>behavioural model runs</q> with the
highest portion of correctly predicted landslides and non-landslides, is then
validated with another landslide-triggering rainfall event in May 1999. The
identified model ensemble correctly predicts the location and the supposed
triggering timing of 73.0 % of the observed landslides triggered in
August 2005 and 91.5 % of the observed landslides triggered in May 1999.
Results of the model ensemble driven with raised precipitation input reveal a
slight increase in areas potentially affected by slope failure. At the same
time, the peak run-off increases more markedly, suggesting that precipitation
intensities during the investigated landslide-triggering rainfall events were
already close to or above the soil's infiltration capacity. |
| first_indexed | 2024-04-12T00:22:24Z |
| format | Article |
| id | doaj.art-9f8e20b831c14a269b2145cbe05ca36d |
| institution | Directory Open Access Journal |
| issn | 1561-8633 1684-9981 |
| language | English |
| last_indexed | 2024-04-12T00:22:24Z |
| publishDate | 2017-06-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Natural Hazards and Earth System Sciences |
| spelling | doaj.art-9f8e20b831c14a269b2145cbe05ca36d2022-12-22T03:55:40ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812017-06-011797199210.5194/nhess-17-971-2017Sensitivity analysis and calibration of a dynamic physically based slope stability modelT. Zieher0T. Zieher1M. Rutzinger2B. Schneider-Muntau3F. Perzl4D. Leidinger5H. Formayer6C. Geitner7Institute of Geography, University of Innsbruck, Innrain 52f, 6020 Innsbruck, AustriaInstitute for Interdisciplinary Mountain Research, Austrian Academy of Sciences, Technikerstraße 21a, 6020 Innsbruck, AustriaInstitute for Interdisciplinary Mountain Research, Austrian Academy of Sciences, Technikerstraße 21a, 6020 Innsbruck, AustriaUnit of Geotechnical and Tunnel Engineering, Institute of Infrastructure, University of Innsbruck, Technikerstraße 13, 6020 Innsbruck, AustriaAustrian Research and Training Centre for Forests, Natural Hazards and Landscape, Rennweg 1, 6020 Innsbruck, AustriaInstitute of Meteorology, University of Natural Resources and Life Sciences Vienna, Peter Jordan Straße 82, 1190 Vienna, AustriaInstitute of Meteorology, University of Natural Resources and Life Sciences Vienna, Peter Jordan Straße 82, 1190 Vienna, AustriaInstitute of Geography, University of Innsbruck, Innrain 52f, 6020 Innsbruck, AustriaPhysically based modelling of slope stability on a catchment scale is still a challenging task. When applying a physically based model on such a scale (1 : 10 000 to 1 : 50 000), parameters with a high impact on the model result should be calibrated to account for (i) the spatial variability of parameter values, (ii) shortcomings of the selected model, (iii) uncertainties of laboratory tests and field measurements or (iv) parameters that cannot be derived experimentally or measured in the field (e.g. calibration constants). While systematic parameter calibration is a common task in hydrological modelling, this is rarely done using physically based slope stability models. In the present study a dynamic, physically based, coupled hydrological–geomechanical slope stability model is calibrated based on a limited number of laboratory tests and a detailed multitemporal shallow landslide inventory covering two landslide-triggering rainfall events in the Laternser valley, Vorarlberg (Austria). Sensitive parameters are identified based on a local one-at-a-time sensitivity analysis. These parameters (hydraulic conductivity, specific storage, angle of internal friction for effective stress, cohesion for effective stress) are systematically sampled and calibrated for a landslide-triggering rainfall event in August 2005. The identified model ensemble, including 25 <q>behavioural model runs</q> with the highest portion of correctly predicted landslides and non-landslides, is then validated with another landslide-triggering rainfall event in May 1999. The identified model ensemble correctly predicts the location and the supposed triggering timing of 73.0 % of the observed landslides triggered in August 2005 and 91.5 % of the observed landslides triggered in May 1999. Results of the model ensemble driven with raised precipitation input reveal a slight increase in areas potentially affected by slope failure. At the same time, the peak run-off increases more markedly, suggesting that precipitation intensities during the investigated landslide-triggering rainfall events were already close to or above the soil's infiltration capacity.https://www.nat-hazards-earth-syst-sci.net/17/971/2017/nhess-17-971-2017.pdf |
| spellingShingle | T. Zieher T. Zieher M. Rutzinger B. Schneider-Muntau F. Perzl D. Leidinger H. Formayer C. Geitner Sensitivity analysis and calibration of a dynamic physically based slope stability model Natural Hazards and Earth System Sciences |
| title | Sensitivity analysis and calibration of a dynamic physically based slope stability model |
| title_full | Sensitivity analysis and calibration of a dynamic physically based slope stability model |
| title_fullStr | Sensitivity analysis and calibration of a dynamic physically based slope stability model |
| title_full_unstemmed | Sensitivity analysis and calibration of a dynamic physically based slope stability model |
| title_short | Sensitivity analysis and calibration of a dynamic physically based slope stability model |
| title_sort | sensitivity analysis and calibration of a dynamic physically based slope stability model |
| url | https://www.nat-hazards-earth-syst-sci.net/17/971/2017/nhess-17-971-2017.pdf |
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