A new hybrid Coulomb/statistical model for forecasting aftershock rates

Sandy Steacy, Matt Gerstenberger, Charles Williams, David Rhoades, Annemarie Christophersen

    Research output: Contribution to journalArticle

    22 Citations (Scopus)

    Abstract

    Forecasting the spatial and temporal distribution of aftershocks is of great importance to earthquake scientists, civil protection authorities and the general public as these events cause disproportionate damage and consternation relative to their size. At present, there are two main approaches to such forecasts—purely statistical methods based on observations of the initial portions of aftershock sequences and a physics-based approach based on Coulomb stress changes caused by the main shock. Here we develop a new method which combines the spatial constraints from the Coulomb model with the statistical power of the STEP (short-term earthquake probability) approach. We test this pseudo prospectively and retrospectively on the Canterbury sequence against the STEP model and a Coulomb rate–state method, using data from the first 10 d following each main event to forecast the rate of M ≥ 4 events in the following 100 d. We find that in retrospective tests the new model outperforms STEP for two events in the sequence but this is not the case for pseudo-prospective tests. Further, the Coulomb rate–state approach never performs better than STEP. Our results suggest that incorporating the physical constraints from Coulomb stress changes can increase the forecasting power of statistical models and clearly show the importance of good data quality if prospective forecasts are to be implemented in practice.
    LanguageEnglish
    Pages1-6
    JournalGeophysical Journal International
    DOIs
    Publication statusPublished - 11 Nov 2013

    Fingerprint

    aftershock
    forecasting
    Earthquakes
    earthquakes
    earthquake
    stress change
    temporal distribution
    data quality
    Statistical methods
    spatial distribution
    physics
    Physics
    shock
    rate
    Statistical Models
    damage
    causes
    method
    forecast
    test

    Keywords

    • Earthquake interaction
    • forecasting
    • and prediction
    • probabilistic forecasting
    • statistical seismology

    Cite this

    Steacy, S., Gerstenberger, M., Williams, C., Rhoades, D., & Christophersen, A. (2013). A new hybrid Coulomb/statistical model for forecasting aftershock rates. Geophysical Journal International, 1-6. https://doi.org/10.1093/gji/ggt404
    Steacy, Sandy ; Gerstenberger, Matt ; Williams, Charles ; Rhoades, David ; Christophersen, Annemarie. / A new hybrid Coulomb/statistical model for forecasting aftershock rates. In: Geophysical Journal International. 2013 ; pp. 1-6.
    @article{50323351c393497289d67de7d20d0a41,
    title = "A new hybrid Coulomb/statistical model for forecasting aftershock rates",
    abstract = "Forecasting the spatial and temporal distribution of aftershocks is of great importance to earthquake scientists, civil protection authorities and the general public as these events cause disproportionate damage and consternation relative to their size. At present, there are two main approaches to such forecasts—purely statistical methods based on observations of the initial portions of aftershock sequences and a physics-based approach based on Coulomb stress changes caused by the main shock. Here we develop a new method which combines the spatial constraints from the Coulomb model with the statistical power of the STEP (short-term earthquake probability) approach. We test this pseudo prospectively and retrospectively on the Canterbury sequence against the STEP model and a Coulomb rate–state method, using data from the first 10 d following each main event to forecast the rate of M ≥ 4 events in the following 100 d. We find that in retrospective tests the new model outperforms STEP for two events in the sequence but this is not the case for pseudo-prospective tests. Further, the Coulomb rate–state approach never performs better than STEP. Our results suggest that incorporating the physical constraints from Coulomb stress changes can increase the forecasting power of statistical models and clearly show the importance of good data quality if prospective forecasts are to be implemented in practice.",
    keywords = "Earthquake interaction, forecasting, and prediction, probabilistic forecasting, statistical seismology",
    author = "Sandy Steacy and Matt Gerstenberger and Charles Williams and David Rhoades and Annemarie Christophersen",
    year = "2013",
    month = "11",
    day = "11",
    doi = "10.1093/gji/ggt404",
    language = "English",
    pages = "1--6",
    journal = "Geophysical Journal International",
    issn = "0956-540X",

    }

    Steacy, S, Gerstenberger, M, Williams, C, Rhoades, D & Christophersen, A 2013, 'A new hybrid Coulomb/statistical model for forecasting aftershock rates', Geophysical Journal International, pp. 1-6. https://doi.org/10.1093/gji/ggt404

    A new hybrid Coulomb/statistical model for forecasting aftershock rates. / Steacy, Sandy; Gerstenberger, Matt; Williams, Charles; Rhoades, David; Christophersen, Annemarie.

    In: Geophysical Journal International, 11.11.2013, p. 1-6.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - A new hybrid Coulomb/statistical model for forecasting aftershock rates

    AU - Steacy, Sandy

    AU - Gerstenberger, Matt

    AU - Williams, Charles

    AU - Rhoades, David

    AU - Christophersen, Annemarie

    PY - 2013/11/11

    Y1 - 2013/11/11

    N2 - Forecasting the spatial and temporal distribution of aftershocks is of great importance to earthquake scientists, civil protection authorities and the general public as these events cause disproportionate damage and consternation relative to their size. At present, there are two main approaches to such forecasts—purely statistical methods based on observations of the initial portions of aftershock sequences and a physics-based approach based on Coulomb stress changes caused by the main shock. Here we develop a new method which combines the spatial constraints from the Coulomb model with the statistical power of the STEP (short-term earthquake probability) approach. We test this pseudo prospectively and retrospectively on the Canterbury sequence against the STEP model and a Coulomb rate–state method, using data from the first 10 d following each main event to forecast the rate of M ≥ 4 events in the following 100 d. We find that in retrospective tests the new model outperforms STEP for two events in the sequence but this is not the case for pseudo-prospective tests. Further, the Coulomb rate–state approach never performs better than STEP. Our results suggest that incorporating the physical constraints from Coulomb stress changes can increase the forecasting power of statistical models and clearly show the importance of good data quality if prospective forecasts are to be implemented in practice.

    AB - Forecasting the spatial and temporal distribution of aftershocks is of great importance to earthquake scientists, civil protection authorities and the general public as these events cause disproportionate damage and consternation relative to their size. At present, there are two main approaches to such forecasts—purely statistical methods based on observations of the initial portions of aftershock sequences and a physics-based approach based on Coulomb stress changes caused by the main shock. Here we develop a new method which combines the spatial constraints from the Coulomb model with the statistical power of the STEP (short-term earthquake probability) approach. We test this pseudo prospectively and retrospectively on the Canterbury sequence against the STEP model and a Coulomb rate–state method, using data from the first 10 d following each main event to forecast the rate of M ≥ 4 events in the following 100 d. We find that in retrospective tests the new model outperforms STEP for two events in the sequence but this is not the case for pseudo-prospective tests. Further, the Coulomb rate–state approach never performs better than STEP. Our results suggest that incorporating the physical constraints from Coulomb stress changes can increase the forecasting power of statistical models and clearly show the importance of good data quality if prospective forecasts are to be implemented in practice.

    KW - Earthquake interaction

    KW - forecasting

    KW - and prediction

    KW - probabilistic forecasting

    KW - statistical seismology

    U2 - 10.1093/gji/ggt404

    DO - 10.1093/gji/ggt404

    M3 - Article

    SP - 1

    EP - 6

    JO - Geophysical Journal International

    T2 - Geophysical Journal International

    JF - Geophysical Journal International

    SN - 0956-540X

    ER -