Spatial transferability of the physically based model TRIGRS using parameter ensembles
The development of better, more reliable and more efficient susceptibility assessments for shallow landslides is becoming increasingly important. Physically based models are well‐suited for this, due to their high predictive capability. However, their demands for large, high‐resolution and detailed...
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Veröffentlicht in: | Earth surface processes and landforms 2024-03, Vol.49 (4), p.1330-1347 |
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description | The development of better, more reliable and more efficient susceptibility assessments for shallow landslides is becoming increasingly important. Physically based models are well‐suited for this, due to their high predictive capability. However, their demands for large, high‐resolution and detailed input datasets make them very time‐consuming and costly methods. This study investigates if a spatially transferable model calibration can be created with the use of parameter ensembles and with this alleviate the time‐consuming calibration process of these methods. To investigate this, the study compares the calibration of the model TRIGRS in two different study areas. The first study area was taken from a previous study where the dynamic physically based model TRIGRS was calibrated for the Laternser valley in Vorarlberg, Austria. The calibrated parameter ensemble and its performance from this previous study are compared with a calibrated parameter ensemble of the model TRIGRS for the Passeier valley in South Tyrol, Italy. The comparison showed very similar model performance and large similarities in the calibrated geotechnical parameter values of the best model runs in both study areas. There is a subset of calibrated geotechnical parameter values that can be used successfully in both study areas and potentially other study areas with similar lithological characteristics. For the hydraulic parameters, the study did not find a transferable parameter subset. These parameters seem to be more sensitive to different soil types. Additionally, the results of the study also showed the importance of the inclusion of detailed information on the timing of landslide initiation in the calibration of the model.
Calibrations of the physically based slope stability model TRIGRS were derived and compared for two study areas in the Eastern Alps. The comparison shows high similarities in the calibrated values of the geotechnical parameters, but differences in the hydraulic parameters. A subset of the geotechnical parameters exists that is applicable for modelling slope stability in study areas where lodgement till soils are important factors for the occurrence of shallow landslides. |
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Calibrations of the physically based slope stability model TRIGRS were derived and compared for two study areas in the Eastern Alps. The comparison shows high similarities in the calibrated values of the geotechnical parameters, but differences in the hydraulic parameters. A subset of the geotechnical parameters exists that is applicable for modelling slope stability in study areas where lodgement till soils are important factors for the occurrence of shallow landslides.</description><identifier>ISSN: 0197-9337</identifier><identifier>EISSN: 1096-9837</identifier><identifier>DOI: 10.1002/esp.5770</identifier><language>eng</language><publisher>Bognor Regis: Wiley Subscription Services, Inc</publisher><subject>Calibration ; HPC ; Landslides ; Lithology ; Mathematical models ; Parameter sensitivity ; Parameters ; shallow landslides ; Soil types ; South Tyrol ; spatial transferability ; TRIGRS ; Valleys</subject><ispartof>Earth surface processes and landforms, 2024-03, Vol.49 (4), p.1330-1347</ispartof><rights>2024 The Authors. published by John Wiley & Sons Ltd.</rights><rights>2024. This article is published under http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a3500-f4c933e34ca20f5d20f48f7db0d33ecbfa6d803b42ec57aea51af8285196c30e3</citedby><cites>FETCH-LOGICAL-a3500-f4c933e34ca20f5d20f48f7db0d33ecbfa6d803b42ec57aea51af8285196c30e3</cites><orcidid>0000-0002-9530-3076 ; 0009-0003-0221-036X ; 0000-0001-5947-9181</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fesp.5770$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fesp.5770$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids></links><search><creatorcontrib>de Vugt, Lotte</creatorcontrib><creatorcontrib>Zieher, Thomas</creatorcontrib><creatorcontrib>Schneider‐Muntau, Barbara</creatorcontrib><creatorcontrib>Moreno, Mateo</creatorcontrib><creatorcontrib>Steger, Stefan</creatorcontrib><creatorcontrib>Rutzinger, Martin</creatorcontrib><title>Spatial transferability of the physically based model TRIGRS using parameter ensembles</title><title>Earth surface processes and landforms</title><description>The development of better, more reliable and more efficient susceptibility assessments for shallow landslides is becoming increasingly important. Physically based models are well‐suited for this, due to their high predictive capability. However, their demands for large, high‐resolution and detailed input datasets make them very time‐consuming and costly methods. This study investigates if a spatially transferable model calibration can be created with the use of parameter ensembles and with this alleviate the time‐consuming calibration process of these methods. To investigate this, the study compares the calibration of the model TRIGRS in two different study areas. The first study area was taken from a previous study where the dynamic physically based model TRIGRS was calibrated for the Laternser valley in Vorarlberg, Austria. The calibrated parameter ensemble and its performance from this previous study are compared with a calibrated parameter ensemble of the model TRIGRS for the Passeier valley in South Tyrol, Italy. The comparison showed very similar model performance and large similarities in the calibrated geotechnical parameter values of the best model runs in both study areas. There is a subset of calibrated geotechnical parameter values that can be used successfully in both study areas and potentially other study areas with similar lithological characteristics. For the hydraulic parameters, the study did not find a transferable parameter subset. These parameters seem to be more sensitive to different soil types. Additionally, the results of the study also showed the importance of the inclusion of detailed information on the timing of landslide initiation in the calibration of the model.
Calibrations of the physically based slope stability model TRIGRS were derived and compared for two study areas in the Eastern Alps. The comparison shows high similarities in the calibrated values of the geotechnical parameters, but differences in the hydraulic parameters. A subset of the geotechnical parameters exists that is applicable for modelling slope stability in study areas where lodgement till soils are important factors for the occurrence of shallow landslides.</description><subject>Calibration</subject><subject>HPC</subject><subject>Landslides</subject><subject>Lithology</subject><subject>Mathematical models</subject><subject>Parameter sensitivity</subject><subject>Parameters</subject><subject>shallow landslides</subject><subject>Soil types</subject><subject>South Tyrol</subject><subject>spatial transferability</subject><subject>TRIGRS</subject><subject>Valleys</subject><issn>0197-9337</issn><issn>1096-9837</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><recordid>eNp10E1Lw0AQBuBFFKxV8CcsePGSOpvN1x6laC0UlLZ6XSbJrE3ZfLibIvn3ptarlxkYHmaGl7FbATMBED6Q72ZxmsIZmwhQSaAymZ6zCQiVBkrK9JJdeb8HECLK1IR9bDrsK7S8d9h4Qw7zylb9wFvD-x3xbjf4qkBrB56jp5LXbUmWb9fLxXrDD75qPnmHDmvqyXFqPNW5JX_NLgxaTzd_fcren5-285dg9bpYzh9XAcoYIDBRMf5EMiowBBOXY4kyk5Y5lOO4yA0mZQYyj0Iq4hQJY4EmC7NYqKSQQHLK7k57O9d-Hcj3et8eXDOe1KGKo0SqKAxHdX9ShWu9d2R056oa3aAF6GNqekxNH1MbaXCi35Wl4V-nnzZvv_4HfrNuwg</recordid><startdate>20240330</startdate><enddate>20240330</enddate><creator>de Vugt, Lotte</creator><creator>Zieher, Thomas</creator><creator>Schneider‐Muntau, Barbara</creator><creator>Moreno, Mateo</creator><creator>Steger, Stefan</creator><creator>Rutzinger, Martin</creator><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0002-9530-3076</orcidid><orcidid>https://orcid.org/0009-0003-0221-036X</orcidid><orcidid>https://orcid.org/0000-0001-5947-9181</orcidid></search><sort><creationdate>20240330</creationdate><title>Spatial transferability of the physically based model TRIGRS using parameter ensembles</title><author>de Vugt, Lotte ; Zieher, Thomas ; Schneider‐Muntau, Barbara ; Moreno, Mateo ; Steger, Stefan ; Rutzinger, Martin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a3500-f4c933e34ca20f5d20f48f7db0d33ecbfa6d803b42ec57aea51af8285196c30e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Calibration</topic><topic>HPC</topic><topic>Landslides</topic><topic>Lithology</topic><topic>Mathematical models</topic><topic>Parameter sensitivity</topic><topic>Parameters</topic><topic>shallow landslides</topic><topic>Soil types</topic><topic>South Tyrol</topic><topic>spatial transferability</topic><topic>TRIGRS</topic><topic>Valleys</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>de Vugt, Lotte</creatorcontrib><creatorcontrib>Zieher, Thomas</creatorcontrib><creatorcontrib>Schneider‐Muntau, Barbara</creatorcontrib><creatorcontrib>Moreno, Mateo</creatorcontrib><creatorcontrib>Steger, Stefan</creatorcontrib><creatorcontrib>Rutzinger, Martin</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Earth surface processes and landforms</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>de Vugt, Lotte</au><au>Zieher, Thomas</au><au>Schneider‐Muntau, Barbara</au><au>Moreno, Mateo</au><au>Steger, Stefan</au><au>Rutzinger, Martin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatial transferability of the physically based model TRIGRS using parameter ensembles</atitle><jtitle>Earth surface processes and landforms</jtitle><date>2024-03-30</date><risdate>2024</risdate><volume>49</volume><issue>4</issue><spage>1330</spage><epage>1347</epage><pages>1330-1347</pages><issn>0197-9337</issn><eissn>1096-9837</eissn><abstract>The development of better, more reliable and more efficient susceptibility assessments for shallow landslides is becoming increasingly important. Physically based models are well‐suited for this, due to their high predictive capability. However, their demands for large, high‐resolution and detailed input datasets make them very time‐consuming and costly methods. This study investigates if a spatially transferable model calibration can be created with the use of parameter ensembles and with this alleviate the time‐consuming calibration process of these methods. To investigate this, the study compares the calibration of the model TRIGRS in two different study areas. The first study area was taken from a previous study where the dynamic physically based model TRIGRS was calibrated for the Laternser valley in Vorarlberg, Austria. The calibrated parameter ensemble and its performance from this previous study are compared with a calibrated parameter ensemble of the model TRIGRS for the Passeier valley in South Tyrol, Italy. The comparison showed very similar model performance and large similarities in the calibrated geotechnical parameter values of the best model runs in both study areas. There is a subset of calibrated geotechnical parameter values that can be used successfully in both study areas and potentially other study areas with similar lithological characteristics. For the hydraulic parameters, the study did not find a transferable parameter subset. These parameters seem to be more sensitive to different soil types. Additionally, the results of the study also showed the importance of the inclusion of detailed information on the timing of landslide initiation in the calibration of the model.
Calibrations of the physically based slope stability model TRIGRS were derived and compared for two study areas in the Eastern Alps. The comparison shows high similarities in the calibrated values of the geotechnical parameters, but differences in the hydraulic parameters. A subset of the geotechnical parameters exists that is applicable for modelling slope stability in study areas where lodgement till soils are important factors for the occurrence of shallow landslides.</abstract><cop>Bognor Regis</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/esp.5770</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0002-9530-3076</orcidid><orcidid>https://orcid.org/0009-0003-0221-036X</orcidid><orcidid>https://orcid.org/0000-0001-5947-9181</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Calibration HPC Landslides Lithology Mathematical models Parameter sensitivity Parameters shallow landslides Soil types South Tyrol spatial transferability TRIGRS Valleys |
title | Spatial transferability of the physically based model TRIGRS using parameter ensembles |
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