Performance Benchmarking Tsunami Models for NTHMP’s Inundation Mapping Activities
Abstract The coastal states and territories of the United States (US) are vulnerable to devastating tsunamis from near-field or far-field coseismic and underwater/subaerial landslide sources. Following the catastrophic 2004 Indian Ocean tsunami, the National Tsunami Hazard Mitigation Program (NTHMP)...
Ausführliche Beschreibung
Autor*in: |
Horrillo, Juan [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
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2014 |
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Anmerkung: |
© Springer Basel 2014 |
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Übergeordnetes Werk: |
Enthalten in: Pure and applied geophysics - Basel : Birkhäuser, 1939, 172(2014), 3-4 vom: 25. Juli, Seite 869-884 |
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Übergeordnetes Werk: |
volume:172 ; year:2014 ; number:3-4 ; day:25 ; month:07 ; pages:869-884 |
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DOI / URN: |
10.1007/s00024-014-0891-y |
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Katalog-ID: |
SPR000237841 |
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520 | |a Abstract The coastal states and territories of the United States (US) are vulnerable to devastating tsunamis from near-field or far-field coseismic and underwater/subaerial landslide sources. Following the catastrophic 2004 Indian Ocean tsunami, the National Tsunami Hazard Mitigation Program (NTHMP) accelerated the development of public safety products for the mitigation of these hazards. In response to this initiative, US coastal states and territories speeded up the process of developing/enhancing/adopting tsunami models that can be used for developing inundation maps and evacuation plans. One of NTHMP’s requirements is that all operational and inundation-based numerical (O&I) models used for such purposes be properly validated against established standards to ensure the reliability of tsunami inundation maps as well as to achieve a basic level of consistency between parallel efforts. The validation of several O&I models was considered during a workshop held in 2011 at Texas A&M University (Galveston). This validation was performed based on the existing standard (OAR-PMEL-135), which provides a list of benchmark problems (BPs) covering various tsunami processes that models must meet to be deemed acceptable. Here, we summarize key approaches followed, results, and conclusions of the workshop. Eight distinct tsunami models were validated and cross-compared by using a subset of the BPs listed in the OAR-PMEL-135 standard. Of the several BPs available, only two based on laboratory experiments are detailed here for sake of brevity; since they are considered as sufficiently comprehensive. Average relative errors associated with expected parameters values such as maximum surface amplitude/runup are estimated. The level of agreement with the reference data, reasons for discrepancies between model results, and some of the limitations are discussed. In general, dispersive models were found to perform better than nondispersive models, but differences were relatively small, in part because the BPs mostly featured long waves, such as solitary waves. The largest error found (e.g., the laboratory experiment case of a solitary wave on a simple beach) was 10 % for non-breaking wave conditions and 12 % for breaking conditions; these errors are equal or smaller than the thresholds (10 % and 20 %, respectively) defined by the OAR-PMEL-135 for predicting the surface profile; hence, all models examined here are deemed acceptable for inundation mapping purposes. | ||
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650 | 4 | |a models comparison |7 (dpeaa)DE-He213 | |
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650 | 4 | |a hydrostatic models |7 (dpeaa)DE-He213 | |
650 | 4 | |a NTHMP |7 (dpeaa)DE-He213 | |
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700 | 1 | |a Nicolsky, Dmitry |4 aut | |
700 | 1 | |a Roeber, Volker |4 aut | |
700 | 1 | |a Zhang, Joseph |4 aut | |
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10.1007/s00024-014-0891-y doi (DE-627)SPR000237841 (SPR)s00024-014-0891-y-e DE-627 ger DE-627 rakwb eng Horrillo, Juan verfasserin aut Performance Benchmarking Tsunami Models for NTHMP’s Inundation Mapping Activities 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Basel 2014 Abstract The coastal states and territories of the United States (US) are vulnerable to devastating tsunamis from near-field or far-field coseismic and underwater/subaerial landslide sources. Following the catastrophic 2004 Indian Ocean tsunami, the National Tsunami Hazard Mitigation Program (NTHMP) accelerated the development of public safety products for the mitigation of these hazards. In response to this initiative, US coastal states and territories speeded up the process of developing/enhancing/adopting tsunami models that can be used for developing inundation maps and evacuation plans. One of NTHMP’s requirements is that all operational and inundation-based numerical (O&I) models used for such purposes be properly validated against established standards to ensure the reliability of tsunami inundation maps as well as to achieve a basic level of consistency between parallel efforts. The validation of several O&I models was considered during a workshop held in 2011 at Texas A&M University (Galveston). This validation was performed based on the existing standard (OAR-PMEL-135), which provides a list of benchmark problems (BPs) covering various tsunami processes that models must meet to be deemed acceptable. Here, we summarize key approaches followed, results, and conclusions of the workshop. Eight distinct tsunami models were validated and cross-compared by using a subset of the BPs listed in the OAR-PMEL-135 standard. Of the several BPs available, only two based on laboratory experiments are detailed here for sake of brevity; since they are considered as sufficiently comprehensive. Average relative errors associated with expected parameters values such as maximum surface amplitude/runup are estimated. The level of agreement with the reference data, reasons for discrepancies between model results, and some of the limitations are discussed. In general, dispersive models were found to perform better than nondispersive models, but differences were relatively small, in part because the BPs mostly featured long waves, such as solitary waves. The largest error found (e.g., the laboratory experiment case of a solitary wave on a simple beach) was 10 % for non-breaking wave conditions and 12 % for breaking conditions; these errors are equal or smaller than the thresholds (10 % and 20 %, respectively) defined by the OAR-PMEL-135 for predicting the surface profile; hence, all models examined here are deemed acceptable for inundation mapping purposes. Tsunami (dpeaa)DE-He213 tsunami numerical models (dpeaa)DE-He213 models comparison (dpeaa)DE-He213 models validation (dpeaa)DE-He213 dispersive models (dpeaa)DE-He213 nonhydrostatic models (dpeaa)DE-He213 hydrostatic models (dpeaa)DE-He213 NTHMP (dpeaa)DE-He213 Grilli, Stéphan T. aut Nicolsky, Dmitry aut Roeber, Volker aut Zhang, Joseph aut Enthalten in Pure and applied geophysics Basel : Birkhäuser, 1939 172(2014), 3-4 vom: 25. Juli, Seite 869-884 (DE-627)265506743 (DE-600)1464028-4 1420-9136 nnns volume:172 year:2014 number:3-4 day:25 month:07 pages:869-884 https://dx.doi.org/10.1007/s00024-014-0891-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 172 2014 3-4 25 07 869-884 |
spelling |
10.1007/s00024-014-0891-y doi (DE-627)SPR000237841 (SPR)s00024-014-0891-y-e DE-627 ger DE-627 rakwb eng Horrillo, Juan verfasserin aut Performance Benchmarking Tsunami Models for NTHMP’s Inundation Mapping Activities 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Basel 2014 Abstract The coastal states and territories of the United States (US) are vulnerable to devastating tsunamis from near-field or far-field coseismic and underwater/subaerial landslide sources. Following the catastrophic 2004 Indian Ocean tsunami, the National Tsunami Hazard Mitigation Program (NTHMP) accelerated the development of public safety products for the mitigation of these hazards. In response to this initiative, US coastal states and territories speeded up the process of developing/enhancing/adopting tsunami models that can be used for developing inundation maps and evacuation plans. One of NTHMP’s requirements is that all operational and inundation-based numerical (O&I) models used for such purposes be properly validated against established standards to ensure the reliability of tsunami inundation maps as well as to achieve a basic level of consistency between parallel efforts. The validation of several O&I models was considered during a workshop held in 2011 at Texas A&M University (Galveston). This validation was performed based on the existing standard (OAR-PMEL-135), which provides a list of benchmark problems (BPs) covering various tsunami processes that models must meet to be deemed acceptable. Here, we summarize key approaches followed, results, and conclusions of the workshop. Eight distinct tsunami models were validated and cross-compared by using a subset of the BPs listed in the OAR-PMEL-135 standard. Of the several BPs available, only two based on laboratory experiments are detailed here for sake of brevity; since they are considered as sufficiently comprehensive. Average relative errors associated with expected parameters values such as maximum surface amplitude/runup are estimated. The level of agreement with the reference data, reasons for discrepancies between model results, and some of the limitations are discussed. In general, dispersive models were found to perform better than nondispersive models, but differences were relatively small, in part because the BPs mostly featured long waves, such as solitary waves. The largest error found (e.g., the laboratory experiment case of a solitary wave on a simple beach) was 10 % for non-breaking wave conditions and 12 % for breaking conditions; these errors are equal or smaller than the thresholds (10 % and 20 %, respectively) defined by the OAR-PMEL-135 for predicting the surface profile; hence, all models examined here are deemed acceptable for inundation mapping purposes. Tsunami (dpeaa)DE-He213 tsunami numerical models (dpeaa)DE-He213 models comparison (dpeaa)DE-He213 models validation (dpeaa)DE-He213 dispersive models (dpeaa)DE-He213 nonhydrostatic models (dpeaa)DE-He213 hydrostatic models (dpeaa)DE-He213 NTHMP (dpeaa)DE-He213 Grilli, Stéphan T. aut Nicolsky, Dmitry aut Roeber, Volker aut Zhang, Joseph aut Enthalten in Pure and applied geophysics Basel : Birkhäuser, 1939 172(2014), 3-4 vom: 25. Juli, Seite 869-884 (DE-627)265506743 (DE-600)1464028-4 1420-9136 nnns volume:172 year:2014 number:3-4 day:25 month:07 pages:869-884 https://dx.doi.org/10.1007/s00024-014-0891-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 172 2014 3-4 25 07 869-884 |
allfields_unstemmed |
10.1007/s00024-014-0891-y doi (DE-627)SPR000237841 (SPR)s00024-014-0891-y-e DE-627 ger DE-627 rakwb eng Horrillo, Juan verfasserin aut Performance Benchmarking Tsunami Models for NTHMP’s Inundation Mapping Activities 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Basel 2014 Abstract The coastal states and territories of the United States (US) are vulnerable to devastating tsunamis from near-field or far-field coseismic and underwater/subaerial landslide sources. Following the catastrophic 2004 Indian Ocean tsunami, the National Tsunami Hazard Mitigation Program (NTHMP) accelerated the development of public safety products for the mitigation of these hazards. In response to this initiative, US coastal states and territories speeded up the process of developing/enhancing/adopting tsunami models that can be used for developing inundation maps and evacuation plans. One of NTHMP’s requirements is that all operational and inundation-based numerical (O&I) models used for such purposes be properly validated against established standards to ensure the reliability of tsunami inundation maps as well as to achieve a basic level of consistency between parallel efforts. The validation of several O&I models was considered during a workshop held in 2011 at Texas A&M University (Galveston). This validation was performed based on the existing standard (OAR-PMEL-135), which provides a list of benchmark problems (BPs) covering various tsunami processes that models must meet to be deemed acceptable. Here, we summarize key approaches followed, results, and conclusions of the workshop. Eight distinct tsunami models were validated and cross-compared by using a subset of the BPs listed in the OAR-PMEL-135 standard. Of the several BPs available, only two based on laboratory experiments are detailed here for sake of brevity; since they are considered as sufficiently comprehensive. Average relative errors associated with expected parameters values such as maximum surface amplitude/runup are estimated. The level of agreement with the reference data, reasons for discrepancies between model results, and some of the limitations are discussed. In general, dispersive models were found to perform better than nondispersive models, but differences were relatively small, in part because the BPs mostly featured long waves, such as solitary waves. The largest error found (e.g., the laboratory experiment case of a solitary wave on a simple beach) was 10 % for non-breaking wave conditions and 12 % for breaking conditions; these errors are equal or smaller than the thresholds (10 % and 20 %, respectively) defined by the OAR-PMEL-135 for predicting the surface profile; hence, all models examined here are deemed acceptable for inundation mapping purposes. Tsunami (dpeaa)DE-He213 tsunami numerical models (dpeaa)DE-He213 models comparison (dpeaa)DE-He213 models validation (dpeaa)DE-He213 dispersive models (dpeaa)DE-He213 nonhydrostatic models (dpeaa)DE-He213 hydrostatic models (dpeaa)DE-He213 NTHMP (dpeaa)DE-He213 Grilli, Stéphan T. aut Nicolsky, Dmitry aut Roeber, Volker aut Zhang, Joseph aut Enthalten in Pure and applied geophysics Basel : Birkhäuser, 1939 172(2014), 3-4 vom: 25. Juli, Seite 869-884 (DE-627)265506743 (DE-600)1464028-4 1420-9136 nnns volume:172 year:2014 number:3-4 day:25 month:07 pages:869-884 https://dx.doi.org/10.1007/s00024-014-0891-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 172 2014 3-4 25 07 869-884 |
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10.1007/s00024-014-0891-y doi (DE-627)SPR000237841 (SPR)s00024-014-0891-y-e DE-627 ger DE-627 rakwb eng Horrillo, Juan verfasserin aut Performance Benchmarking Tsunami Models for NTHMP’s Inundation Mapping Activities 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Basel 2014 Abstract The coastal states and territories of the United States (US) are vulnerable to devastating tsunamis from near-field or far-field coseismic and underwater/subaerial landslide sources. Following the catastrophic 2004 Indian Ocean tsunami, the National Tsunami Hazard Mitigation Program (NTHMP) accelerated the development of public safety products for the mitigation of these hazards. In response to this initiative, US coastal states and territories speeded up the process of developing/enhancing/adopting tsunami models that can be used for developing inundation maps and evacuation plans. One of NTHMP’s requirements is that all operational and inundation-based numerical (O&I) models used for such purposes be properly validated against established standards to ensure the reliability of tsunami inundation maps as well as to achieve a basic level of consistency between parallel efforts. The validation of several O&I models was considered during a workshop held in 2011 at Texas A&M University (Galveston). This validation was performed based on the existing standard (OAR-PMEL-135), which provides a list of benchmark problems (BPs) covering various tsunami processes that models must meet to be deemed acceptable. Here, we summarize key approaches followed, results, and conclusions of the workshop. Eight distinct tsunami models were validated and cross-compared by using a subset of the BPs listed in the OAR-PMEL-135 standard. Of the several BPs available, only two based on laboratory experiments are detailed here for sake of brevity; since they are considered as sufficiently comprehensive. Average relative errors associated with expected parameters values such as maximum surface amplitude/runup are estimated. The level of agreement with the reference data, reasons for discrepancies between model results, and some of the limitations are discussed. In general, dispersive models were found to perform better than nondispersive models, but differences were relatively small, in part because the BPs mostly featured long waves, such as solitary waves. The largest error found (e.g., the laboratory experiment case of a solitary wave on a simple beach) was 10 % for non-breaking wave conditions and 12 % for breaking conditions; these errors are equal or smaller than the thresholds (10 % and 20 %, respectively) defined by the OAR-PMEL-135 for predicting the surface profile; hence, all models examined here are deemed acceptable for inundation mapping purposes. Tsunami (dpeaa)DE-He213 tsunami numerical models (dpeaa)DE-He213 models comparison (dpeaa)DE-He213 models validation (dpeaa)DE-He213 dispersive models (dpeaa)DE-He213 nonhydrostatic models (dpeaa)DE-He213 hydrostatic models (dpeaa)DE-He213 NTHMP (dpeaa)DE-He213 Grilli, Stéphan T. aut Nicolsky, Dmitry aut Roeber, Volker aut Zhang, Joseph aut Enthalten in Pure and applied geophysics Basel : Birkhäuser, 1939 172(2014), 3-4 vom: 25. Juli, Seite 869-884 (DE-627)265506743 (DE-600)1464028-4 1420-9136 nnns volume:172 year:2014 number:3-4 day:25 month:07 pages:869-884 https://dx.doi.org/10.1007/s00024-014-0891-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 172 2014 3-4 25 07 869-884 |
allfieldsSound |
10.1007/s00024-014-0891-y doi (DE-627)SPR000237841 (SPR)s00024-014-0891-y-e DE-627 ger DE-627 rakwb eng Horrillo, Juan verfasserin aut Performance Benchmarking Tsunami Models for NTHMP’s Inundation Mapping Activities 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer Basel 2014 Abstract The coastal states and territories of the United States (US) are vulnerable to devastating tsunamis from near-field or far-field coseismic and underwater/subaerial landslide sources. Following the catastrophic 2004 Indian Ocean tsunami, the National Tsunami Hazard Mitigation Program (NTHMP) accelerated the development of public safety products for the mitigation of these hazards. In response to this initiative, US coastal states and territories speeded up the process of developing/enhancing/adopting tsunami models that can be used for developing inundation maps and evacuation plans. One of NTHMP’s requirements is that all operational and inundation-based numerical (O&I) models used for such purposes be properly validated against established standards to ensure the reliability of tsunami inundation maps as well as to achieve a basic level of consistency between parallel efforts. The validation of several O&I models was considered during a workshop held in 2011 at Texas A&M University (Galveston). This validation was performed based on the existing standard (OAR-PMEL-135), which provides a list of benchmark problems (BPs) covering various tsunami processes that models must meet to be deemed acceptable. Here, we summarize key approaches followed, results, and conclusions of the workshop. Eight distinct tsunami models were validated and cross-compared by using a subset of the BPs listed in the OAR-PMEL-135 standard. Of the several BPs available, only two based on laboratory experiments are detailed here for sake of brevity; since they are considered as sufficiently comprehensive. Average relative errors associated with expected parameters values such as maximum surface amplitude/runup are estimated. The level of agreement with the reference data, reasons for discrepancies between model results, and some of the limitations are discussed. In general, dispersive models were found to perform better than nondispersive models, but differences were relatively small, in part because the BPs mostly featured long waves, such as solitary waves. The largest error found (e.g., the laboratory experiment case of a solitary wave on a simple beach) was 10 % for non-breaking wave conditions and 12 % for breaking conditions; these errors are equal or smaller than the thresholds (10 % and 20 %, respectively) defined by the OAR-PMEL-135 for predicting the surface profile; hence, all models examined here are deemed acceptable for inundation mapping purposes. Tsunami (dpeaa)DE-He213 tsunami numerical models (dpeaa)DE-He213 models comparison (dpeaa)DE-He213 models validation (dpeaa)DE-He213 dispersive models (dpeaa)DE-He213 nonhydrostatic models (dpeaa)DE-He213 hydrostatic models (dpeaa)DE-He213 NTHMP (dpeaa)DE-He213 Grilli, Stéphan T. aut Nicolsky, Dmitry aut Roeber, Volker aut Zhang, Joseph aut Enthalten in Pure and applied geophysics Basel : Birkhäuser, 1939 172(2014), 3-4 vom: 25. Juli, Seite 869-884 (DE-627)265506743 (DE-600)1464028-4 1420-9136 nnns volume:172 year:2014 number:3-4 day:25 month:07 pages:869-884 https://dx.doi.org/10.1007/s00024-014-0891-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_381 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 172 2014 3-4 25 07 869-884 |
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Enthalten in Pure and applied geophysics 172(2014), 3-4 vom: 25. Juli, Seite 869-884 volume:172 year:2014 number:3-4 day:25 month:07 pages:869-884 |
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Enthalten in Pure and applied geophysics 172(2014), 3-4 vom: 25. Juli, Seite 869-884 volume:172 year:2014 number:3-4 day:25 month:07 pages:869-884 |
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Horrillo, Juan @@aut@@ Grilli, Stéphan T. @@aut@@ Nicolsky, Dmitry @@aut@@ Roeber, Volker @@aut@@ Zhang, Joseph @@aut@@ |
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This validation was performed based on the existing standard (OAR-PMEL-135), which provides a list of benchmark problems (BPs) covering various tsunami processes that models must meet to be deemed acceptable. Here, we summarize key approaches followed, results, and conclusions of the workshop. Eight distinct tsunami models were validated and cross-compared by using a subset of the BPs listed in the OAR-PMEL-135 standard. Of the several BPs available, only two based on laboratory experiments are detailed here for sake of brevity; since they are considered as sufficiently comprehensive. Average relative errors associated with expected parameters values such as maximum surface amplitude/runup are estimated. The level of agreement with the reference data, reasons for discrepancies between model results, and some of the limitations are discussed. 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Horrillo, Juan |
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Horrillo, Juan misc Tsunami misc tsunami numerical models misc models comparison misc models validation misc dispersive models misc nonhydrostatic models misc hydrostatic models misc NTHMP Performance Benchmarking Tsunami Models for NTHMP’s Inundation Mapping Activities |
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Performance Benchmarking Tsunami Models for NTHMP’s Inundation Mapping Activities Tsunami (dpeaa)DE-He213 tsunami numerical models (dpeaa)DE-He213 models comparison (dpeaa)DE-He213 models validation (dpeaa)DE-He213 dispersive models (dpeaa)DE-He213 nonhydrostatic models (dpeaa)DE-He213 hydrostatic models (dpeaa)DE-He213 NTHMP (dpeaa)DE-He213 |
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Horrillo, Juan Grilli, Stéphan T. Nicolsky, Dmitry Roeber, Volker Zhang, Joseph |
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performance benchmarking tsunami models for nthmp’s inundation mapping activities |
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Performance Benchmarking Tsunami Models for NTHMP’s Inundation Mapping Activities |
abstract |
Abstract The coastal states and territories of the United States (US) are vulnerable to devastating tsunamis from near-field or far-field coseismic and underwater/subaerial landslide sources. Following the catastrophic 2004 Indian Ocean tsunami, the National Tsunami Hazard Mitigation Program (NTHMP) accelerated the development of public safety products for the mitigation of these hazards. In response to this initiative, US coastal states and territories speeded up the process of developing/enhancing/adopting tsunami models that can be used for developing inundation maps and evacuation plans. One of NTHMP’s requirements is that all operational and inundation-based numerical (O&I) models used for such purposes be properly validated against established standards to ensure the reliability of tsunami inundation maps as well as to achieve a basic level of consistency between parallel efforts. The validation of several O&I models was considered during a workshop held in 2011 at Texas A&M University (Galveston). This validation was performed based on the existing standard (OAR-PMEL-135), which provides a list of benchmark problems (BPs) covering various tsunami processes that models must meet to be deemed acceptable. Here, we summarize key approaches followed, results, and conclusions of the workshop. Eight distinct tsunami models were validated and cross-compared by using a subset of the BPs listed in the OAR-PMEL-135 standard. Of the several BPs available, only two based on laboratory experiments are detailed here for sake of brevity; since they are considered as sufficiently comprehensive. Average relative errors associated with expected parameters values such as maximum surface amplitude/runup are estimated. The level of agreement with the reference data, reasons for discrepancies between model results, and some of the limitations are discussed. In general, dispersive models were found to perform better than nondispersive models, but differences were relatively small, in part because the BPs mostly featured long waves, such as solitary waves. The largest error found (e.g., the laboratory experiment case of a solitary wave on a simple beach) was 10 % for non-breaking wave conditions and 12 % for breaking conditions; these errors are equal or smaller than the thresholds (10 % and 20 %, respectively) defined by the OAR-PMEL-135 for predicting the surface profile; hence, all models examined here are deemed acceptable for inundation mapping purposes. © Springer Basel 2014 |
abstractGer |
Abstract The coastal states and territories of the United States (US) are vulnerable to devastating tsunamis from near-field or far-field coseismic and underwater/subaerial landslide sources. Following the catastrophic 2004 Indian Ocean tsunami, the National Tsunami Hazard Mitigation Program (NTHMP) accelerated the development of public safety products for the mitigation of these hazards. In response to this initiative, US coastal states and territories speeded up the process of developing/enhancing/adopting tsunami models that can be used for developing inundation maps and evacuation plans. One of NTHMP’s requirements is that all operational and inundation-based numerical (O&I) models used for such purposes be properly validated against established standards to ensure the reliability of tsunami inundation maps as well as to achieve a basic level of consistency between parallel efforts. The validation of several O&I models was considered during a workshop held in 2011 at Texas A&M University (Galveston). This validation was performed based on the existing standard (OAR-PMEL-135), which provides a list of benchmark problems (BPs) covering various tsunami processes that models must meet to be deemed acceptable. Here, we summarize key approaches followed, results, and conclusions of the workshop. Eight distinct tsunami models were validated and cross-compared by using a subset of the BPs listed in the OAR-PMEL-135 standard. Of the several BPs available, only two based on laboratory experiments are detailed here for sake of brevity; since they are considered as sufficiently comprehensive. Average relative errors associated with expected parameters values such as maximum surface amplitude/runup are estimated. The level of agreement with the reference data, reasons for discrepancies between model results, and some of the limitations are discussed. In general, dispersive models were found to perform better than nondispersive models, but differences were relatively small, in part because the BPs mostly featured long waves, such as solitary waves. The largest error found (e.g., the laboratory experiment case of a solitary wave on a simple beach) was 10 % for non-breaking wave conditions and 12 % for breaking conditions; these errors are equal or smaller than the thresholds (10 % and 20 %, respectively) defined by the OAR-PMEL-135 for predicting the surface profile; hence, all models examined here are deemed acceptable for inundation mapping purposes. © Springer Basel 2014 |
abstract_unstemmed |
Abstract The coastal states and territories of the United States (US) are vulnerable to devastating tsunamis from near-field or far-field coseismic and underwater/subaerial landslide sources. Following the catastrophic 2004 Indian Ocean tsunami, the National Tsunami Hazard Mitigation Program (NTHMP) accelerated the development of public safety products for the mitigation of these hazards. In response to this initiative, US coastal states and territories speeded up the process of developing/enhancing/adopting tsunami models that can be used for developing inundation maps and evacuation plans. One of NTHMP’s requirements is that all operational and inundation-based numerical (O&I) models used for such purposes be properly validated against established standards to ensure the reliability of tsunami inundation maps as well as to achieve a basic level of consistency between parallel efforts. The validation of several O&I models was considered during a workshop held in 2011 at Texas A&M University (Galveston). This validation was performed based on the existing standard (OAR-PMEL-135), which provides a list of benchmark problems (BPs) covering various tsunami processes that models must meet to be deemed acceptable. Here, we summarize key approaches followed, results, and conclusions of the workshop. Eight distinct tsunami models were validated and cross-compared by using a subset of the BPs listed in the OAR-PMEL-135 standard. Of the several BPs available, only two based on laboratory experiments are detailed here for sake of brevity; since they are considered as sufficiently comprehensive. Average relative errors associated with expected parameters values such as maximum surface amplitude/runup are estimated. The level of agreement with the reference data, reasons for discrepancies between model results, and some of the limitations are discussed. In general, dispersive models were found to perform better than nondispersive models, but differences were relatively small, in part because the BPs mostly featured long waves, such as solitary waves. The largest error found (e.g., the laboratory experiment case of a solitary wave on a simple beach) was 10 % for non-breaking wave conditions and 12 % for breaking conditions; these errors are equal or smaller than the thresholds (10 % and 20 %, respectively) defined by the OAR-PMEL-135 for predicting the surface profile; hence, all models examined here are deemed acceptable for inundation mapping purposes. © Springer Basel 2014 |
collection_details |
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container_issue |
3-4 |
title_short |
Performance Benchmarking Tsunami Models for NTHMP’s Inundation Mapping Activities |
url |
https://dx.doi.org/10.1007/s00024-014-0891-y |
remote_bool |
true |
author2 |
Grilli, Stéphan T. Nicolsky, Dmitry Roeber, Volker Zhang, Joseph |
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Grilli, Stéphan T. Nicolsky, Dmitry Roeber, Volker Zhang, Joseph |
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doi_str |
10.1007/s00024-014-0891-y |
up_date |
2024-07-03T14:50:52.792Z |
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|
score |
7.398304 |