Interevent Variability in Ground-Motion Prediction Models: The Role of the Source Parameter Selection Article Swipe
Dino Bindi
,
Adrien Oth
,
Stefano Parolai
,
Matteo Picozzi
,
Daniele Spallarossa
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1785/0120250098
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1785/0120250098
We investigate the dependence of interevent residuals on the choice of source parameters used in ground-motion prediction models calibrated for peak ground acceleration, peak ground velocity, and peak ground displacement. Using a dataset of 877,566 recordings from 1586 earthquakes with magnitudes ranging from 1 to 6.5 in central-southern Italy, we perform multiple mixed-effects regressions, exploring different approaches for the source scaling component. We compare the interevent standard deviation of models based on various source parameters, including moment magnitude, local magnitude, radiated energy, source spectral value at 3 Hz, moment magnitude with stress drop, and moment magnitude with apparent stress. Our results show that combining moment magnitude with either stress drop or apparent stress yields the lowest variability across all peak parameters, as expected. In addition, using local magnitude effectively captures the stress-drop-related component of variability. For the analyzed magnitude range, the source spectral amplitude at 3 Hz performs similarly to local magnitude in this regard, without saturating for large magnitudes. These findings suggest that source parameter choices complementary or alternative to moment magnitude can help reduce interevent variability. However, the suitability of models based on parameters other than moment magnitude depends on the specific application.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1785/0120250098
- https://pubs.geoscienceworld.org/ssa/bssa/article-pdf/doi/10.1785/0120250098/7332377/bssa-2025098.1.pdf
- OA Status
- hybrid
- References
- 61
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4413744140
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4413744140Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1785/0120250098Digital Object Identifier
- Title
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Interevent Variability in Ground-Motion Prediction Models: The Role of the Source Parameter SelectionWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-08-27Full publication date if available
- Authors
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Dino Bindi, Adrien Oth, Stefano Parolai, Matteo Picozzi, Daniele SpallarossaList of authors in order
- Landing page
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https://doi.org/10.1785/0120250098Publisher landing page
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https://pubs.geoscienceworld.org/ssa/bssa/article-pdf/doi/10.1785/0120250098/7332377/bssa-2025098.1.pdfDirect link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://pubs.geoscienceworld.org/ssa/bssa/article-pdf/doi/10.1785/0120250098/7332377/bssa-2025098.1.pdfDirect OA link when available
- Concepts
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Selection (genetic algorithm), Ground motion, Geology, Environmental science, Mathematics, Geodesy, Computer science, Seismology, Artificial intelligenceTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W3179226937, https://openalex.org/W2626957249, https://openalex.org/W2102889840, https://openalex.org/W2157264936, https://openalex.org/W2339012508, https://openalex.org/W2332202223, https://openalex.org/W3003590472, https://openalex.org/W2122059558, https://openalex.org/W3045856389, https://openalex.org/W2802917784, https://openalex.org/W4403850811, https://openalex.org/W3113014468, https://openalex.org/W2278590165, https://openalex.org/W2263834384, https://openalex.org/W1994553199, https://openalex.org/W2148943622, https://openalex.org/W1927664617, https://openalex.org/W6921410930, https://openalex.org/W2593083022, https://openalex.org/W3080679805, https://openalex.org/W6903573648, https://openalex.org/W6923691062, https://openalex.org/W2105658614, https://openalex.org/W3005764919, https://openalex.org/W2106641143, https://openalex.org/W6922507753, https://openalex.org/W6958983793, https://openalex.org/W6960345870, https://openalex.org/W2499574849, https://openalex.org/W6959712758, https://openalex.org/W4365516908, https://openalex.org/W2143591903, https://openalex.org/W4408342767, https://openalex.org/W2015948680, https://openalex.org/W2795620676, https://openalex.org/W4403943261, https://openalex.org/W3091953864, https://openalex.org/W2900550994, https://openalex.org/W2807347144, https://openalex.org/W2988235490, https://openalex.org/W4399223476, https://openalex.org/W6921633356, https://openalex.org/W1956217412, https://openalex.org/W6940279807, https://openalex.org/W4367557075, https://openalex.org/W2900159430, https://openalex.org/W2114785396, https://openalex.org/W2076411043, https://openalex.org/W6939974137, https://openalex.org/W6921365956, https://openalex.org/W2032941099, https://openalex.org/W6906190292, https://openalex.org/W2972175553, https://openalex.org/W1994018849, https://openalex.org/W21702993, https://openalex.org/W3138122495, https://openalex.org/W4299687266, https://openalex.org/W2096105657, https://openalex.org/W51647267, https://openalex.org/W2101987062, https://openalex.org/W4411392672 |
| referenced_works_count | 61 |
| abstract_inverted_index.1 | 44 |
| abstract_inverted_index.3 | 87, 146 |
| abstract_inverted_index.a | 32 |
| abstract_inverted_index.Hz | 147 |
| abstract_inverted_index.In | 124 |
| abstract_inverted_index.We | 1, 63 |
| abstract_inverted_index.as | 122 |
| abstract_inverted_index.at | 86, 145 |
| abstract_inverted_index.in | 15, 47, 153 |
| abstract_inverted_index.of | 5, 11, 34, 69, 134, 182 |
| abstract_inverted_index.on | 8, 72, 185, 192 |
| abstract_inverted_index.or | 111, 169 |
| abstract_inverted_index.to | 45, 150, 171 |
| abstract_inverted_index.we | 50 |
| abstract_inverted_index.6.5 | 46 |
| abstract_inverted_index.For | 136 |
| abstract_inverted_index.Hz, | 88 |
| abstract_inverted_index.Our | 100 |
| abstract_inverted_index.all | 119 |
| abstract_inverted_index.and | 27, 94 |
| abstract_inverted_index.can | 174 |
| abstract_inverted_index.for | 20, 58, 158 |
| abstract_inverted_index.the | 3, 9, 59, 65, 115, 131, 137, 141, 180, 193 |
| abstract_inverted_index.1586 | 38 |
| abstract_inverted_index.drop | 110 |
| abstract_inverted_index.from | 37, 43 |
| abstract_inverted_index.help | 175 |
| abstract_inverted_index.peak | 21, 24, 28, 120 |
| abstract_inverted_index.show | 102 |
| abstract_inverted_index.than | 188 |
| abstract_inverted_index.that | 103, 164 |
| abstract_inverted_index.this | 154 |
| abstract_inverted_index.used | 14 |
| abstract_inverted_index.with | 40, 91, 97, 107 |
| abstract_inverted_index.These | 161 |
| abstract_inverted_index.Using | 31 |
| abstract_inverted_index.based | 71, 184 |
| abstract_inverted_index.drop, | 93 |
| abstract_inverted_index.large | 159 |
| abstract_inverted_index.local | 79, 127, 151 |
| abstract_inverted_index.other | 187 |
| abstract_inverted_index.using | 126 |
| abstract_inverted_index.value | 85 |
| abstract_inverted_index.Italy, | 49 |
| abstract_inverted_index.across | 118 |
| abstract_inverted_index.choice | 10 |
| abstract_inverted_index.either | 108 |
| abstract_inverted_index.ground | 22, 25, 29 |
| abstract_inverted_index.lowest | 116 |
| abstract_inverted_index.models | 18, 70, 183 |
| abstract_inverted_index.moment | 77, 89, 95, 105, 172, 189 |
| abstract_inverted_index.range, | 140 |
| abstract_inverted_index.reduce | 176 |
| abstract_inverted_index.source | 12, 60, 74, 83, 142, 165 |
| abstract_inverted_index.stress | 92, 109, 113 |
| abstract_inverted_index.yields | 114 |
| abstract_inverted_index.877,566 | 35 |
| abstract_inverted_index.choices | 167 |
| abstract_inverted_index.compare | 64 |
| abstract_inverted_index.dataset | 33 |
| abstract_inverted_index.depends | 191 |
| abstract_inverted_index.energy, | 82 |
| abstract_inverted_index.perform | 51 |
| abstract_inverted_index.ranging | 42 |
| abstract_inverted_index.regard, | 155 |
| abstract_inverted_index.results | 101 |
| abstract_inverted_index.scaling | 61 |
| abstract_inverted_index.stress. | 99 |
| abstract_inverted_index.suggest | 163 |
| abstract_inverted_index.various | 73 |
| abstract_inverted_index.without | 156 |
| abstract_inverted_index.ABSTRACT | 0 |
| abstract_inverted_index.However, | 179 |
| abstract_inverted_index.analyzed | 138 |
| abstract_inverted_index.apparent | 98, 112 |
| abstract_inverted_index.captures | 130 |
| abstract_inverted_index.findings | 162 |
| abstract_inverted_index.multiple | 52 |
| abstract_inverted_index.performs | 148 |
| abstract_inverted_index.radiated | 81 |
| abstract_inverted_index.specific | 194 |
| abstract_inverted_index.spectral | 84, 143 |
| abstract_inverted_index.standard | 67 |
| abstract_inverted_index.addition, | 125 |
| abstract_inverted_index.amplitude | 144 |
| abstract_inverted_index.combining | 104 |
| abstract_inverted_index.component | 133 |
| abstract_inverted_index.deviation | 68 |
| abstract_inverted_index.different | 56 |
| abstract_inverted_index.expected. | 123 |
| abstract_inverted_index.exploring | 55 |
| abstract_inverted_index.including | 76 |
| abstract_inverted_index.magnitude | 90, 96, 106, 128, 139, 152, 173, 190 |
| abstract_inverted_index.parameter | 166 |
| abstract_inverted_index.residuals | 7 |
| abstract_inverted_index.similarly | 149 |
| abstract_inverted_index.velocity, | 26 |
| abstract_inverted_index.approaches | 57 |
| abstract_inverted_index.calibrated | 19 |
| abstract_inverted_index.component. | 62 |
| abstract_inverted_index.dependence | 4 |
| abstract_inverted_index.interevent | 6, 66, 177 |
| abstract_inverted_index.magnitude, | 78, 80 |
| abstract_inverted_index.magnitudes | 41 |
| abstract_inverted_index.parameters | 13, 186 |
| abstract_inverted_index.prediction | 17 |
| abstract_inverted_index.recordings | 36 |
| abstract_inverted_index.saturating | 157 |
| abstract_inverted_index.alternative | 170 |
| abstract_inverted_index.earthquakes | 39 |
| abstract_inverted_index.effectively | 129 |
| abstract_inverted_index.investigate | 2 |
| abstract_inverted_index.magnitudes. | 160 |
| abstract_inverted_index.parameters, | 75, 121 |
| abstract_inverted_index.suitability | 181 |
| abstract_inverted_index.variability | 117 |
| abstract_inverted_index.application. | 195 |
| abstract_inverted_index.regressions, | 54 |
| abstract_inverted_index.variability. | 135, 178 |
| abstract_inverted_index.acceleration, | 23 |
| abstract_inverted_index.complementary | 168 |
| abstract_inverted_index.displacement. | 30 |
| abstract_inverted_index.ground-motion | 16 |
| abstract_inverted_index.mixed-effects | 53 |
| abstract_inverted_index.central-southern | 48 |
| abstract_inverted_index.stress-drop-related | 132 |
| cited_by_percentile_year | |
| countries_distinct_count | 3 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile.value | 0.38907063 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |