Effect of data quality on a hybrid Coulomb/STEP model for earthquake forecasting

NASA Astrophysics Data System (ADS)

Steacy, Sandy; Jimenez, Abigail; Gerstenberger, Matt; Christophersen, Annemarie

2014-05-01

Operational earthquake forecasting is rapidly becoming a 'hot topic' as civil protection authorities seek quantitative information on likely near future earthquake distributions during seismic crises. At present, most of the models in public domain are statistical and use information about past and present seismicity as well as b-value and Omori's law to forecast future rates. A limited number of researchers, however, are developing hybrid models which add spatial constraints from Coulomb stress modeling to existing statistical approaches. Steacy et al. (2013), for instance, recently tested a model that combines Coulomb stress patterns with the STEP (short-term earthquake probability) approach against seismicity observed during the 2010-2012 Canterbury earthquake sequence. They found that the new model performed at least as well as, and often better than, STEP when tested against retrospective data but that STEP was generally better in pseudo-prospective tests that involved data actually available within the first 10 days of each event of interest. They suggested that the major reason for this discrepancy was uncertainty in the slip models and, in particular, in the geometries of the faults involved in each complex major event. Here we test this hypothesis by developing a number of retrospective forecasts for the Landers earthquake using hypothetical slip distributions developed by Steacy et al. (2004) to investigate the sensitivity of Coulomb stress models to fault geometry and earthquake slip. Specifically, we consider slip models based on the NEIC location, the CMT solution, surface rupture, and published inversions and find significant variation in the relative performance of the models depending upon the input data.

Gambling scores for earthquake predictions and forecasts

NASA Astrophysics Data System (ADS)

Zhuang, Jiancang

2010-04-01

This paper presents a new method, namely the gambling score, for scoring the performance earthquake forecasts or predictions. Unlike most other scoring procedures that require a regular scheme of forecast and treat each earthquake equally, regardless their magnitude, this new scoring method compensates the risk that the forecaster has taken. Starting with a certain number of reputation points, once a forecaster makes a prediction or forecast, he is assumed to have betted some points of his reputation. The reference model, which plays the role of the house, determines how many reputation points the forecaster can gain if he succeeds, according to a fair rule, and also takes away the reputation points betted by the forecaster if he loses. This method is also extended to the continuous case of point process models, where the reputation points betted by the forecaster become a continuous mass on the space-time-magnitude range of interest. We also calculate the upper bound of the gambling score when the true model is a renewal process, the stress release model or the ETAS model and when the reference model is the Poisson model.

Measuring the effectiveness of earthquake forecasting in insurance strategies

NASA Astrophysics Data System (ADS)

Mignan, A.; Muir-Wood, R.

2009-04-01

Given the difficulty of judging whether the skill of a particular methodology of earthquake forecasts is offset by the inevitable false alarms and missed predictions, it is important to find a means to weigh the successes and failures according to a common currency. Rather than judge subjectively the relative costs and benefits of predictions, we develop a simple method to determine if the use of earthquake forecasts can increase the profitability of active financial risk management strategies employed in standard insurance procedures. Three types of risk management transactions are employed: (1) insurance underwriting, (2) reinsurance purchasing and (3) investment in CAT bonds. For each case premiums are collected based on modelled technical risk costs and losses are modelled for the portfolio in force at the time of the earthquake. A set of predetermined actions follow from the announcement of any change in earthquake hazard, so that, for each earthquake forecaster, the financial performance of an active risk management strategy can be compared with the equivalent passive strategy in which no notice is taken of earthquake forecasts. Overall performance can be tracked through time to determine which strategy gives the best long term financial performance. This will be determined by whether the skill in forecasting the location and timing of a significant earthquake (where loss is avoided) is outweighed by false predictions (when no premium is collected). This methodology is to be tested in California, where catastrophe modeling is reasonably mature and where a number of researchers issue earthquake forecasts.

Is there a basis for preferring characteristic earthquakes over a Gutenberg–Richter distribution in probabilistic earthquake forecasting?

USGS Publications Warehouse

Parsons, Thomas E.; Geist, Eric L.

2009-01-01

The idea that faults rupture in repeated, characteristic earthquakes is central to most probabilistic earthquake forecasts. The concept is elegant in its simplicity, and if the same event has repeated itself multiple times in the past, we might anticipate the next. In practice however, assembling a fault-segmented characteristic earthquake rupture model can grow into a complex task laden with unquantified uncertainty. We weigh the evidence that supports characteristic earthquakes against a potentially simpler model made from extrapolation of a Gutenberg–Richter magnitude-frequency law to individual fault zones. We find that the Gutenberg–Richter model satisfies key data constraints used for earthquake forecasting equally well as a characteristic model. Therefore, judicious use of instrumental and historical earthquake catalogs enables large-earthquake-rate calculations with quantifiable uncertainty that should get at least equal weighting in probabilistic forecasting.

Prospective testing of Coulomb short-term earthquake forecasts

NASA Astrophysics Data System (ADS)

Jackson, D. D.; Kagan, Y. Y.; Schorlemmer, D.; Zechar, J. D.; Wang, Q.; Wong, K.

2009-12-01

Earthquake induced Coulomb stresses, whether static or dynamic, suddenly change the probability of future earthquakes. Models to estimate stress and the resulting seismicity changes could help to illuminate earthquake physics and guide appropriate precautionary response. But do these models have improved forecasting power compared to empirical statistical models? The best answer lies in prospective testing in which a fully specified model, with no subsequent parameter adjustments, is evaluated against future earthquakes. The Center of Study of Earthquake Predictability (CSEP) facilitates such prospective testing of earthquake forecasts, including several short term forecasts. Formulating Coulomb stress models for formal testing involves several practical problems, mostly shared with other short-term models. First, earthquake probabilities must be calculated after each “perpetrator” earthquake but before the triggered earthquakes, or “victims”. The time interval between a perpetrator and its victims may be very short, as characterized by the Omori law for aftershocks. CSEP evaluates short term models daily, and allows daily updates of the models. However, lots can happen in a day. An alternative is to test and update models on the occurrence of each earthquake over a certain magnitude. To make such updates rapidly enough and to qualify as prospective, earthquake focal mechanisms, slip distributions, stress patterns, and earthquake probabilities would have to be made by computer without human intervention. This scheme would be more appropriate for evaluating scientific ideas, but it may be less useful for practical applications than daily updates. Second, triggered earthquakes are imperfectly recorded following larger events because their seismic waves are buried in the coda of the earlier event. To solve this problem, testing methods need to allow for “censoring” of early aftershock data, and a quantitative model for detection threshold as a function of

An Earthquake Rupture Forecast model for central Italy submitted to CSEP project

NASA Astrophysics Data System (ADS)

Pace, B.; Peruzza, L.

2009-04-01

We defined a seismogenic source model for central Italy and computed the relative forecast scenario, in order to submit the results to the CSEP (Collaboratory for the study of Earthquake Predictability, www.cseptesting.org) project. The goal of CSEP project is developing a virtual, distributed laboratory that supports a wide range of scientific prediction experiments in multiple regional or global natural laboratories, and Italy is the first region in Europe for which fully prospective testing is planned. The model we propose is essentially the Layered Seismogenic Source for Central Italy (LaSS-CI) we published in 2006 (Pace et al., 2006). It is based on three different layers of sources: the first one collects the individual faults liable to generate major earthquakes (M >5.5); the second layer is given by the instrumental seismicity analysis of the past two decades, which allows us to evaluate the background seismicity (M ~<5.0). The third layer utilizes all the instrumental earthquakes and the historical events not correlated to known structures (4.5earthquakes by Brownian passage time distribution. Beside the original model, updated earthquake rupture forecasts only for individual sources are released too, in the light of recent analyses (Peruzza et al., 2008; Zoeller et al., 2008). We computed forecasts based on the LaSS-CI model for two time-windows: 5 and 10 years. Each model to be tested defines a forecasted earthquake rate in magnitude bins of 0.1 unit steps in the range M5-9, for the periods 1st April 2009 to 1st April 2014, and 1st April 2009 to 1st April 2019. B. Pace, L. Peruzza, G. Lavecchia, and P. Boncio (2006) Layered Seismogenic Source

Applications of the gambling score in evaluating earthquake predictions and forecasts

NASA Astrophysics Data System (ADS)

Zhuang, Jiancang; Zechar, Jeremy D.; Jiang, Changsheng; Console, Rodolfo; Murru, Maura; Falcone, Giuseppe

2010-05-01

This study presents a new method, namely the gambling score, for scoring the performance earthquake forecasts or predictions. Unlike most other scoring procedures that require a regular scheme of forecast and treat each earthquake equally, regardless their magnitude, this new scoring method compensates the risk that the forecaster has taken. Starting with a certain number of reputation points, once a forecaster makes a prediction or forecast, he is assumed to have betted some points of his reputation. The reference model, which plays the role of the house, determines how many reputation points the forecaster can gain if he succeeds, according to a fair rule, and also takes away the reputation points bet by the forecaster if he loses. This method is also extended to the continuous case of point process models, where the reputation points betted by the forecaster become a continuous mass on the space-time-magnitude range of interest. For discrete predictions, we apply this method to evaluate performance of Shebalin's predictions made by using the Reverse Tracing of Precursors (RTP) algorithm and of the outputs of the predictions from the Annual Consultation Meeting on Earthquake Tendency held by China Earthquake Administration. For the continuous case, we use it to compare the probability forecasts of seismicity in the Abruzzo region before and after the L'aquila earthquake based on the ETAS model and the PPE model.

Earthquake Forecasting in Northeast India using Energy Blocked Model

NASA Astrophysics Data System (ADS)

Mohapatra, A. K.; Mohanty, D. K.

2009-12-01

In the present study, the cumulative seismic energy released by earthquakes (M ≥ 5) for a period 1897 to 2007 is analyzed for Northeast (NE) India. It is one of the most seismically active regions of the world. The occurrence of three great earthquakes like 1897 Shillong plateau earthquake (Mw= 8.7), 1934 Bihar Nepal earthquake with (Mw= 8.3) and 1950 Upper Assam earthquake (Mw= 8.7) signify the possibility of great earthquakes in future from this region. The regional seismicity map for the study region is prepared by plotting the earthquake data for the period 1897 to 2007 from the source like USGS,ISC catalogs, GCMT database, Indian Meteorological department (IMD). Based on the geology, tectonic and seismicity the study region is classified into three source zones such as Zone 1: Arakan-Yoma zone (AYZ), Zone 2: Himalayan Zone (HZ) and Zone 3: Shillong Plateau zone (SPZ). The Arakan-Yoma Range is characterized by the subduction zone, developed by the junction of the Indian Plate and the Eurasian Plate. It shows a dense clustering of earthquake events and the 1908 eastern boundary earthquake. The Himalayan tectonic zone depicts the subduction zone, and the Assam syntaxis. This zone suffered by the great earthquakes like the 1950 Assam, 1934 Bihar and the 1951 Upper Himalayan earthquakes with Mw > 8. The Shillong Plateau zone was affected by major faults like the Dauki fault and exhibits its own style of the prominent tectonic features. The seismicity and hazard potential of Shillong Plateau is distinct from the Himalayan thrust. Using energy blocked model by Tsuboi, the forecasting of major earthquakes for each source zone is estimated. As per the energy blocked model, the supply of energy for potential earthquakes in an area is remarkably uniform with respect to time and the difference between the supply energy and cumulative energy released for a span of time, is a good indicator of energy blocked and can be utilized for the forecasting of major earthquakes

Operational Earthquake Forecasting of Aftershocks for New England

NASA Astrophysics Data System (ADS)

Ebel, J.; Fadugba, O. I.

2015-12-01

Although the forecasting of mainshocks is not possible, recent research demonstrates that probabilistic forecasts of expected aftershock activity following moderate and strong earthquakes is possible. Previous work has shown that aftershock sequences in intraplate regions behave similarly to those in California, and thus the operational aftershocks forecasting methods that are currently employed in California can be adopted for use in areas of the eastern U.S. such as New England. In our application, immediately after a felt earthquake in New England, a forecast of expected aftershock activity for the next 7 days will be generated based on a generic aftershock activity model. Approximately 24 hours after the mainshock, the parameters of the aftershock model will be updated using the observed aftershock activity observed to that point in time, and a new forecast of expected aftershock activity for the next 7 days will be issued. The forecast will estimate the average number of weak, felt aftershocks and the average expected number of aftershocks based on the aftershock statistics of past New England earthquakes. The forecast also will estimate the probability that an earthquake that is stronger than the mainshock will take place during the next 7 days. The aftershock forecast will specify the expected aftershocks locations as well as the areas over which aftershocks of different magnitudes could be felt. The system will use web pages, email and text messages to distribute the aftershock forecasts. For protracted aftershock sequences, new forecasts will be issued on a regular basis, such as weekly. Initially, the distribution system of the aftershock forecasts will be limited, but later it will be expanded as experience with and confidence in the system grows.

Portals for Real-Time Earthquake Data and Forecasting: Challenge and Promise (Invited)

NASA Astrophysics Data System (ADS)

Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Feltstykket, R.; Donnellan, A.; Glasscoe, M. T.

2013-12-01

Earthquake forecasts have been computed by a variety of countries world-wide for over two decades. For the most part, forecasts have been computed for insurance, reinsurance and underwriters of catastrophe bonds. However, recent events clearly demonstrate that mitigating personal risk is becoming the responsibility of individual members of the public. Open access to a variety of web-based forecasts, tools, utilities and information is therefore required. Portals for data and forecasts present particular challenges, and require the development of both apps and the client/server architecture to deliver the basic information in real time. The basic forecast model we consider is the Natural Time Weibull (NTW) method (JBR et al., Phys. Rev. E, 86, 021106, 2012). This model uses small earthquakes (';seismicity-based models') to forecast the occurrence of large earthquakes, via data-mining algorithms combined with the ANSS earthquake catalog. This method computes large earthquake probabilities using the number of small earthquakes that have occurred in a region since the last large earthquake. Localizing these forecasts in space so that global forecasts can be computed in real time presents special algorithmic challenges, which we describe in this talk. Using 25 years of data from the ANSS California-Nevada catalog of earthquakes, we compute real-time global forecasts at a grid scale of 0.1o. We analyze and monitor the performance of these models using the standard tests, which include the Reliability/Attributes and Receiver Operating Characteristic (ROC) tests. It is clear from much of the analysis that data quality is a major limitation on the accurate computation of earthquake probabilities. We discuss the challenges of serving up these datasets over the web on web-based platforms such as those at www.quakesim.org , www.e-decider.org , and www.openhazards.com.

UCERF3: A new earthquake forecast for California's complex fault system

USGS Publications Warehouse

Field, Edward H.; ,

2015-01-01

With innovations, fresh data, and lessons learned from recent earthquakes, scientists have developed a new earthquake forecast model for California, a region under constant threat from potentially damaging events. The new model, referred to as the third Uniform California Earthquake Rupture Forecast, or "UCERF" (http://www.WGCEP.org/UCERF3), provides authoritative estimates of the magnitude, location, and likelihood of earthquake fault rupture throughout the state. Overall the results confirm previous findings, but with some significant changes because of model improvements. For example, compared to the previous forecast (Uniform California Earthquake Rupture Forecast 2), the likelihood of moderate-sized earthquakes (magnitude 6.5 to 7.5) is lower, whereas that of larger events is higher. This is because of the inclusion of multifault ruptures, where earthquakes are no longer confined to separate, individual faults, but can occasionally rupture multiple faults simultaneously. The public-safety implications of this and other model improvements depend on several factors, including site location and type of structure (for example, family dwelling compared to a long-span bridge). Building codes, earthquake insurance products, emergency plans, and other risk-mitigation efforts will be updated accordingly. This model also serves as a reminder that damaging earthquakes are inevitable for California. Fortunately, there are many simple steps residents can take to protect lives and property.

The Uniform California Earthquake Rupture Forecast, Version 2 (UCERF 2)

USGS Publications Warehouse

,

2008-01-01

California?s 35 million people live among some of the most active earthquake faults in the United States. Public safety demands credible assessments of the earthquake hazard to maintain appropriate building codes for safe construction and earthquake insurance for loss protection. Seismic hazard analysis begins with an earthquake rupture forecast?a model of probabilities that earthquakes of specified magnitudes, locations, and faulting types will occur during a specified time interval. This report describes a new earthquake rupture forecast for California developed by the 2007 Working Group on California Earthquake Probabilities (WGCEP 2007).

Simulation Based Earthquake Forecasting with RSQSim

NASA Astrophysics Data System (ADS)

Gilchrist, J. J.; Jordan, T. H.; Dieterich, J. H.; Richards-Dinger, K. B.

2016-12-01

We are developing a physics-based forecasting model for earthquake ruptures in California. We employ the 3D boundary element code RSQSim to generate synthetic catalogs with millions of events that span up to a million years. The simulations incorporate rate-state fault constitutive properties in complex, fully interacting fault systems. The Unified California Earthquake Rupture Forecast Version 3 (UCERF3) model and data sets are used for calibration of the catalogs and specification of fault geometry. Fault slip rates match the UCERF3 geologic slip rates and catalogs are tuned such that earthquake recurrence matches the UCERF3 model. Utilizing the Blue Waters Supercomputer, we produce a suite of million-year catalogs to investigate the epistemic uncertainty in the physical parameters used in the simulations. In particular, values of the rate- and state-friction parameters a and b, the initial shear and normal stress, as well as the earthquake slip speed, are varied over several simulations. In addition to testing multiple models with homogeneous values of the physical parameters, the parameters a, b, and the normal stress are varied with depth as well as in heterogeneous patterns across the faults. Cross validation of UCERF3 and RSQSim is performed within the SCEC Collaboratory for Interseismic Simulation and Modeling (CISM) to determine the affect of the uncertainties in physical parameters observed in the field and measured in the lab, on the uncertainties in probabilistic forecasting. We are particularly interested in the short-term hazards of multi-event sequences due to complex faulting and multi-fault ruptures.

A forecast experiment of earthquake activity in Japan under Collaboratory for the Study of Earthquake Predictability (CSEP)

NASA Astrophysics Data System (ADS)

Hirata, N.; Yokoi, S.; Nanjo, K. Z.; Tsuruoka, H.

2012-04-01

One major focus of the current Japanese earthquake prediction research program (2009-2013), which is now integrated with the research program for prediction of volcanic eruptions, is to move toward creating testable earthquake forecast models. For this purpose we started an experiment of forecasting earthquake activity in Japan under the framework of the Collaboratory for the Study of Earthquake Predictability (CSEP) through an international collaboration. We established the CSEP Testing Centre, an infrastructure to encourage researchers to develop testable models for Japan, and to conduct verifiable prospective tests of their model performance. We started the 1st earthquake forecast testing experiment in Japan within the CSEP framework. We use the earthquake catalogue maintained and provided by the Japan Meteorological Agency (JMA). The experiment consists of 12 categories, with 4 testing classes with different time spans (1 day, 3 months, 1 year, and 3 years) and 3 testing regions called "All Japan," "Mainland," and "Kanto." A total of 105 models were submitted, and are currently under the CSEP official suite of tests for evaluating the performance of forecasts. The experiments were completed for 92 rounds for 1-day, 6 rounds for 3-month, and 3 rounds for 1-year classes. For 1-day testing class all models passed all the CSEP's evaluation tests at more than 90% rounds. The results of the 3-month testing class also gave us new knowledge concerning statistical forecasting models. All models showed a good performance for magnitude forecasting. On the other hand, observation is hardly consistent in space distribution with most models when many earthquakes occurred at a spot. Now we prepare the 3-D forecasting experiment with a depth range of 0 to 100 km in Kanto region. The testing center is improving an evaluation system for 1-day class experiment to finish forecasting and testing results within one day. The special issue of 1st part titled Earthquake Forecast

Operational Earthquake Forecasting and Decision-Making in a Low-Probability Environment

NASA Astrophysics Data System (ADS)

Jordan, T. H.; the International Commission on Earthquake ForecastingCivil Protection

2011-12-01

Operational earthquake forecasting (OEF) is the dissemination of authoritative information about the time dependence of seismic hazards to help communities prepare for potentially destructive earthquakes. Most previous work on the public utility of OEF has anticipated that forecasts would deliver high probabilities of large earthquakes; i.e., deterministic predictions with low error rates (false alarms and failures-to-predict) would be possible. This expectation has not been realized. An alternative to deterministic prediction is probabilistic forecasting based on empirical statistical models of aftershock triggering and seismic clustering. During periods of high seismic activity, short-term earthquake forecasts can attain prospective probability gains in excess of 100 relative to long-term forecasts. The utility of such information is by no means clear, however, because even with hundredfold increases, the probabilities of large earthquakes typically remain small, rarely exceeding a few percent over forecasting intervals of days or weeks. Civil protection agencies have been understandably cautious in implementing OEF in this sort of "low-probability environment." The need to move more quickly has been underscored by recent seismic crises, such as the 2009 L'Aquila earthquake sequence, in which an anxious public was confused by informal and inaccurate earthquake predictions. After the L'Aquila earthquake, the Italian Department of Civil Protection appointed an International Commission on Earthquake Forecasting (ICEF), which I chaired, to recommend guidelines for OEF utilization. Our report (Ann. Geophys., 54, 4, 2011; doi: 10.4401/ag-5350) concludes: (a) Public sources of information on short-term probabilities should be authoritative, scientific, open, and timely, and need to convey epistemic uncertainties. (b) Earthquake probabilities should be based on operationally qualified, regularly updated forecasting systems. (c) All operational models should be evaluated

International Aftershock Forecasting: Lessons from the Gorkha Earthquake

NASA Astrophysics Data System (ADS)

Michael, A. J.; Blanpied, M. L.; Brady, S. R.; van der Elst, N.; Hardebeck, J.; Mayberry, G. C.; Page, M. T.; Smoczyk, G. M.; Wein, A. M.

2015-12-01

Following the M7.8 Gorhka, Nepal, earthquake of April 25, 2015 the USGS issued a series of aftershock forecasts. The initial impetus for these forecasts was a request from the USAID Office of US Foreign Disaster Assistance to support their Disaster Assistance Response Team (DART) which coordinated US Government disaster response, including search and rescue, with the Government of Nepal. Because of the possible utility of the forecasts to people in the region and other response teams, the USGS released these forecasts publicly through the USGS Earthquake Program web site. The initial forecast used the Reasenberg and Jones (Science, 1989) model with generic parameters developed for active deep continental regions based on the Garcia et al. (BSSA, 2012) tectonic regionalization. These were then updated to reflect a lower productivity and higher decay rate based on the observed aftershocks, although relying on teleseismic observations, with a high magnitude-of-completeness, limited the amount of data. After the 12 May M7.3 aftershock, the forecasts used an Epidemic Type Aftershock Sequence model to better characterize the multiple sources of earthquake clustering. This model provided better estimates of aftershock uncertainty. These forecast messages were crafted based on lessons learned from the Christchurch earthquake along with input from the U.S. Embassy staff in Kathmandu. Challenges included how to balance simple messaging with forecasts over a variety of time periods (week, month, and year), whether to characterize probabilities with words such as those suggested by the IPCC (IPCC, 2010), how to word the messages in a way that would translate accurately into Nepali and not alarm the public, and how to present the probabilities of unlikely but possible large and potentially damaging aftershocks, such as the M7.3 event, which had an estimated probability of only 1-in-200 for the week in which it occurred.

Operational earthquake forecasting can enhance earthquake preparedness

USGS Publications Warehouse

Jordan, T.H.; Marzocchi, W.; Michael, A.J.; Gerstenberger, M.C.

2014-01-01

We cannot yet predict large earthquakes in the short term with much reliability and skill, but the strong clustering exhibited in seismic sequences tells us that earthquake probabilities are not constant in time; they generally rise and fall over periods of days to years in correlation with nearby seismic activity. Operational earthquake forecasting (OEF) is the dissemination of authoritative information about these time‐dependent probabilities to help communities prepare for potentially destructive earthquakes. The goal of OEF is to inform the decisions that people and organizations must continually make to mitigate seismic risk and prepare for potentially destructive earthquakes on time scales from days to decades. To fulfill this role, OEF must provide a complete description of the seismic hazard—ground‐motion exceedance probabilities as well as short‐term rupture probabilities—in concert with the long‐term forecasts of probabilistic seismic‐hazard analysis (PSHA).

Forecasting Induced Seismicity Using Saltwater Disposal Data and a Hydromechanical Earthquake Nucleation Model

NASA Astrophysics Data System (ADS)

Norbeck, J. H.; Rubinstein, J. L.

2017-12-01

The earthquake activity in Oklahoma and Kansas that began in 2008 reflects the most widespread instance of induced seismicity observed to date. In this work, we demonstrate that the basement fault stressing conditions that drive seismicity rate evolution are related directly to the operational history of 958 saltwater disposal wells completed in the Arbuckle aquifer. We developed a fluid pressurization model based on the assumption that pressure changes are dominated by reservoir compressibility effects. Using injection well data, we established a detailed description of the temporal and spatial variability in stressing conditions over the 21.5-year period from January 1995 through June 2017. With this stressing history, we applied a numerical model based on rate-and-state friction theory to generate seismicity rate forecasts across a broad range of spatial scales. The model replicated the onset of seismicity, the timing of the peak seismicity rate, and the reduction in seismicity following decreased disposal activity. The behavior of the induced earthquake sequence was consistent with the prediction from rate-and-state theory that the system evolves toward a steady seismicity rate depending on the ratio between the current and background stressing rates. Seismicity rate transients occurred over characteristic timescales inversely proportional to stressing rate. We found that our hydromechanical earthquake rate model outperformed observational and empirical forecast models for one-year forecast durations over the period 2008 through 2016.

Retrospective stress-forecasting of earthquakes

NASA Astrophysics Data System (ADS)

Gao, Yuan; Crampin, Stuart

2015-04-01

Observations of changes in azimuthally varying shear-wave splitting (SWS) above swarms of small earthquakes monitor stress-induced changes to the stress-aligned vertical microcracks pervading the upper crust, lower crust, and uppermost ~400km of the mantle. (The microcracks are intergranular films of hydrolysed melt in the mantle.) Earthquakes release stress, and an appropriate amount of stress for the relevant magnitude must accumulate before each event. Iceland is on an extension of the Mid-Atlantic Ridge, where two transform zones, uniquely run onshore. These onshore transform zones provide semi-continuous swarms of small earthquakes, which are the only place worldwide where SWS can be routinely monitored. Elsewhere SWS must be monitored above temporally-active occasional swarms of small earthquakes, or in infrequent SKS and other teleseismic reflections from the mantle. Observations of changes in SWS time-delays are attributed to stress-induced changes in crack aspect-ratios allowing stress-accumulation and stress-relaxation to be identified. Monitoring SWS in SW Iceland in 1988, stress-accumulation before an impending earthquake was recognised and emails were exchanged between the University of Edinburgh (EU) and the Iceland Meteorological Office (IMO). On 10th November 1988, EU emailed IMO that a M5 earthquake could occur soon on a seismically-active fault plane where seismicity was still continuing following a M5.1 earthquake six-months earlier. Three-days later, IMO emailed EU that a M5 earthquake had just occurred on the specified fault-plane. We suggest this is a successful earthquake stress-forecast, where we refer to the procedure as stress-forecasting earthquakes as opposed to predicting or forecasting to emphasise the different formalism. Lack of funds has prevented us monitoring SWS on Iceland seismograms, however, we have identified similar characteristic behaviour of SWS time-delays above swarms of small earthquakes which have enabled us to

Application of a long-range forecasting model to earthquakes in the Japan mainland testing region

NASA Astrophysics Data System (ADS)

Rhoades, David A.

2011-03-01

The Every Earthquake a Precursor According to Scale (EEPAS) model is a long-range forecasting method which has been previously applied to a number of regions, including Japan. The Collaboratory for the Study of Earthquake Predictability (CSEP) forecasting experiment in Japan provides an opportunity to test the model at lower magnitudes than previously and to compare it with other competing models. The model sums contributions to the rate density from past earthquakes based on predictive scaling relations derived from the precursory scale increase phenomenon. Two features of the earthquake catalogue in the Japan mainland region create difficulties in applying the model, namely magnitude-dependence in the proportion of aftershocks and in the Gutenberg-Richter b-value. To accommodate these features, the model was fitted separately to earthquakes in three different target magnitude classes over the period 2000-2009. There are some substantial unexplained differences in parameters between classes, but the time and magnitude distributions of the individual earthquake contributions are such that the model is suitable for three-month testing at M ≥ 4 and for one-year testing at M ≥ 5. In retrospective analyses, the mean probability gain of the EEPAS model over a spatially smoothed seismicity model increases with magnitude. The same trend is expected in prospective testing. The Proximity to Past Earthquakes (PPE) model has been submitted to the same testing classes as the EEPAS model. Its role is that of a spatially-smoothed reference model, against which the performance of time-varying models can be compared.

Calibration and validation of earthquake catastrophe models. Case study: Impact Forecasting Earthquake Model for Algeria

NASA Astrophysics Data System (ADS)

Trendafiloski, G.; Gaspa Rebull, O.; Ewing, C.; Podlaha, A.; Magee, B.

2012-04-01

Calibration and validation are crucial steps in the production of the catastrophe models for the insurance industry in order to assure the model's reliability and to quantify its uncertainty. Calibration is needed in all components of model development including hazard and vulnerability. Validation is required to ensure that the losses calculated by the model match those observed in past events and which could happen in future. Impact Forecasting, the catastrophe modelling development centre of excellence within Aon Benfield, has recently launched its earthquake model for Algeria as a part of the earthquake model for the Maghreb region. The earthquake model went through a detailed calibration process including: (1) the seismic intensity attenuation model by use of macroseismic observations and maps from past earthquakes in Algeria; (2) calculation of the country-specific vulnerability modifiers by use of past damage observations in the country. The use of Benouar, 1994 ground motion prediction relationship was proven as the most appropriate for our model. Calculation of the regional vulnerability modifiers for the country led to 10% to 40% larger vulnerability indexes for different building types compared to average European indexes. The country specific damage models also included aggregate damage models for residential, commercial and industrial properties considering the description of the buildings stock given by World Housing Encyclopaedia and the local rebuilding cost factors equal to 10% for damage grade 1, 20% for damage grade 2, 35% for damage grade 3, 75% for damage grade 4 and 100% for damage grade 5. The damage grades comply with the European Macroseismic Scale (EMS-1998). The model was validated by use of "as-if" historical scenario simulations of three past earthquake events in Algeria M6.8 2003 Boumerdes, M7.3 1980 El-Asnam and M7.3 1856 Djidjelli earthquake. The calculated return periods of the losses for client market portfolio align with the

The Value, Protocols, and Scientific Ethics of Earthquake Forecasting

NASA Astrophysics Data System (ADS)

Jordan, Thomas H.

2013-04-01

Earthquakes are different from other common natural hazards because precursory signals diagnostic of the magnitude, location, and time of impending seismic events have not yet been found. Consequently, the short-term, localized prediction of large earthquakes at high probabilities with low error rates (false alarms and failures-to-predict) is not yet feasible. An alternative is short-term probabilistic forecasting based on empirical statistical models of seismic clustering. During periods of high seismic activity, short-term earthquake forecasts can attain prospective probability gains up to 1000 relative to long-term forecasts. The value of such information is by no means clear, however, because even with hundredfold increases, the probabilities of large earthquakes typically remain small, rarely exceeding a few percent over forecasting intervals of days or weeks. Civil protection agencies have been understandably cautious in implementing operational forecasting protocols in this sort of "low-probability environment." This paper will explore the complex interrelations among the valuation of low-probability earthquake forecasting, which must account for social intangibles; the protocols of operational forecasting, which must factor in large uncertainties; and the ethics that guide scientists as participants in the forecasting process, who must honor scientific principles without doing harm. Earthquake forecasts possess no intrinsic societal value; rather, they acquire value through their ability to influence decisions made by users seeking to mitigate seismic risk and improve community resilience to earthquake disasters. According to the recommendations of the International Commission on Earthquake Forecasting (www.annalsofgeophysics.eu/index.php/annals/article/view/5350), operational forecasting systems should appropriately separate the hazard-estimation role of scientists from the decision-making role of civil protection authorities and individuals. They should

Earthquake focal mechanism forecasting in Italy for PSHA purposes

NASA Astrophysics Data System (ADS)

Roselli, Pamela; Marzocchi, Warner; Mariucci, Maria Teresa; Montone, Paola

2018-01-01

In this paper, we put forward a procedure that aims to forecast focal mechanism of future earthquakes. One of the primary uses of such forecasts is in probabilistic seismic hazard analysis (PSHA); in fact, aiming at reducing the epistemic uncertainty, most of the newer ground motion prediction equations consider, besides the seismicity rates, the forecast of the focal mechanism of the next large earthquakes as input data. The data set used to this purpose is relative to focal mechanisms taken from the latest stress map release for Italy containing 392 well-constrained solutions of events, from 1908 to 2015, with Mw ≥ 4 and depths from 0 down to 40 km. The data set considers polarity focal mechanism solutions until to 1975 (23 events), whereas for 1976-2015, it takes into account only the Centroid Moment Tensor (CMT)-like earthquake focal solutions for data homogeneity. The forecasting model is rooted in the Total Weighted Moment Tensor concept that weighs information of past focal mechanisms evenly distributed in space, according to their distance from the spatial cells and magnitude. Specifically, for each cell of a regular 0.1° × 0.1° spatial grid, the model estimates the probability to observe a normal, reverse, or strike-slip fault plane solution for the next large earthquakes, the expected moment tensor and the related maximum horizontal stress orientation. These results will be available for the new PSHA model for Italy under development. Finally, to evaluate the reliability of the forecasts, we test them with an independent data set that consists of some of the strongest earthquakes with Mw ≥ 3.9 occurred during 2016 in different Italian tectonic provinces.

Implications of the 26 December 2004 Sumatra-Andaman earthquake on tsunami forecast and assessment models for great subduction-zone earthquakes

USGS Publications Warehouse

Geist, Eric L.; Titov, Vasily V.; Arcas, Diego; Pollitz, Fred F.; Bilek, Susan L.

2007-01-01

Results from different tsunami forecasting and hazard assessment models are compared with observed tsunami wave heights from the 26 December 2004 Indian Ocean tsunami. Forecast models are based on initial earthquake information and are used to estimate tsunami wave heights during propagation. An empirical forecast relationship based only on seismic moment provides a close estimate to the observed mean regional and maximum local tsunami runup heights for the 2004 Indian Ocean tsunami but underestimates mean regional tsunami heights at azimuths in line with the tsunami beaming pattern (e.g., Sri Lanka, Thailand). Standard forecast models developed from subfault discretization of earthquake rupture, in which deep- ocean sea level observations are used to constrain slip, are also tested. Forecast models of this type use tsunami time-series measurements at points in the deep ocean. As a proxy for the 2004 Indian Ocean tsunami, a transect of deep-ocean tsunami amplitudes recorded by satellite altimetry is used to constrain slip along four subfaults of the M >9 Sumatra–Andaman earthquake. This proxy model performs well in comparison to observed tsunami wave heights, travel times, and inundation patterns at Banda Aceh. Hypothetical tsunami hazard assessments models based on end- member estimates for average slip and rupture length (Mw 9.0–9.3) are compared with tsunami observations. Using average slip (low end member) and rupture length (high end member) (Mw 9.14) consistent with many seismic, geodetic, and tsunami inversions adequately estimates tsunami runup in most regions, except the extreme runup in the western Aceh province. The high slip that occurred in the southern part of the rupture zone linked to runup in this location is a larger fluctuation than expected from standard stochastic slip models. In addition, excess moment release (∼9%) deduced from geodetic studies in comparison to seismic moment estimates may generate additional tsunami energy, if the

Earthquake forecasts for the CSEP Japan experiment based on the RI algorithm

NASA Astrophysics Data System (ADS)

Nanjo, K. Z.

2011-03-01

An earthquake forecast testing experiment for Japan, the first of its kind, is underway within the framework of the Collaboratory for the Study of Earthquake Predictability (CSEP) under a controlled environment. Here we give an overview of the earthquake forecast models, based on the RI algorithm, which we have submitted to the CSEP Japan experiment. Models have been submitted to a total of 9 categories, corresponding to 3 testing classes (3 years, 1 year, and 3 months) and 3 testing regions. The RI algorithm is originally a binary forecast system based on the working assumption that large earthquakes are more likely to occur in the future at locations of higher seismicity in the past. It is based on simple counts of the number of past earthquakes, which is called the Relative Intensity (RI) of seismicity. To improve its forecast performance, we first expand the RI algorithm by introducing spatial smoothing. We then convert the RI representation from a binary system to a CSEP-testable model that produces forecasts for the number of earthquakes of predefined magnitudes. We use information on past seismicity to tune the parameters. The final submittal consists of 36 executable computer codes: 4 variants corresponding to different smoothing parameters for each of the 9 categories. They will help to elucidate which categories and which smoothing parameters are the most meaningful for the RI hypothesis. The main purpose of our participation in the experiment is to better understand the significance of the relative intensity of seismicity for earthquake forecastability in Japan.

Statistical physics approach to earthquake occurrence and forecasting

NASA Astrophysics Data System (ADS)

de Arcangelis, Lucilla; Godano, Cataldo; Grasso, Jean Robert; Lippiello, Eugenio

2016-04-01

There is striking evidence that the dynamics of the Earth crust is controlled by a wide variety of mutually dependent mechanisms acting at different spatial and temporal scales. The interplay of these mechanisms produces instabilities in the stress field, leading to abrupt energy releases, i.e., earthquakes. As a consequence, the evolution towards instability before a single event is very difficult to monitor. On the other hand, collective behavior in stress transfer and relaxation within the Earth crust leads to emergent properties described by stable phenomenological laws for a population of many earthquakes in size, time and space domains. This observation has stimulated a statistical mechanics approach to earthquake occurrence, applying ideas and methods as scaling laws, universality, fractal dimension, renormalization group, to characterize the physics of earthquakes. In this review we first present a description of the phenomenological laws of earthquake occurrence which represent the frame of reference for a variety of statistical mechanical models, ranging from the spring-block to more complex fault models. Next, we discuss the problem of seismic forecasting in the general framework of stochastic processes, where seismic occurrence can be described as a branching process implementing space-time-energy correlations between earthquakes. In this context we show how correlations originate from dynamical scaling relations between time and energy, able to account for universality and provide a unifying description for the phenomenological power laws. Then we discuss how branching models can be implemented to forecast the temporal evolution of the earthquake occurrence probability and allow to discriminate among different physical mechanisms responsible for earthquake triggering. In particular, the forecasting problem will be presented in a rigorous mathematical framework, discussing the relevance of the processes acting at different temporal scales for different

Earthquake forecasting during the complex Amatrice-Norcia seismic sequence.

PubMed

Marzocchi, Warner; Taroni, Matteo; Falcone, Giuseppe

2017-09-01

Earthquake forecasting is the ultimate challenge for seismologists, because it condenses the scientific knowledge about the earthquake occurrence process, and it is an essential component of any sound risk mitigation planning. It is commonly assumed that, in the short term, trustworthy earthquake forecasts are possible only for typical aftershock sequences, where the largest shock is followed by many smaller earthquakes that decay with time according to the Omori power law. We show that the current Italian operational earthquake forecasting system issued statistically reliable and skillful space-time-magnitude forecasts of the largest earthquakes during the complex 2016-2017 Amatrice-Norcia sequence, which is characterized by several bursts of seismicity and a significant deviation from the Omori law. This capability to deliver statistically reliable forecasts is an essential component of any program to assist public decision-makers and citizens in the challenging risk management of complex seismic sequences.

Earthquake forecasting during the complex Amatrice-Norcia seismic sequence

PubMed Central

Marzocchi, Warner; Taroni, Matteo; Falcone, Giuseppe

2017-01-01

Earthquake forecasting is the ultimate challenge for seismologists, because it condenses the scientific knowledge about the earthquake occurrence process, and it is an essential component of any sound risk mitigation planning. It is commonly assumed that, in the short term, trustworthy earthquake forecasts are possible only for typical aftershock sequences, where the largest shock is followed by many smaller earthquakes that decay with time according to the Omori power law. We show that the current Italian operational earthquake forecasting system issued statistically reliable and skillful space-time-magnitude forecasts of the largest earthquakes during the complex 2016–2017 Amatrice-Norcia sequence, which is characterized by several bursts of seismicity and a significant deviation from the Omori law. This capability to deliver statistically reliable forecasts is an essential component of any program to assist public decision-makers and citizens in the challenging risk management of complex seismic sequences. PMID:28924610

Retrospective Evaluation of the Long-Term CSEP-Italy Earthquake Forecasts

NASA Astrophysics Data System (ADS)

Werner, M. J.; Zechar, J. D.; Marzocchi, W.; Wiemer, S.

2010-12-01

On 1 August 2009, the global Collaboratory for the Study of Earthquake Predictability (CSEP) launched a prospective and comparative earthquake predictability experiment in Italy. The goal of the CSEP-Italy experiment is to test earthquake occurrence hypotheses that have been formalized as probabilistic earthquake forecasts over temporal scales that range from days to years. In the first round of forecast submissions, members of the CSEP-Italy Working Group presented eighteen five-year and ten-year earthquake forecasts to the European CSEP Testing Center at ETH Zurich. We considered the twelve time-independent earthquake forecasts among this set and evaluated them with respect to past seismicity data from two Italian earthquake catalogs. Here, we present the results of tests that measure the consistency of the forecasts with the past observations. Besides being an evaluation of the submitted time-independent forecasts, this exercise provided insight into a number of important issues in predictability experiments with regard to the specification of the forecasts, the performance of the tests, and the trade-off between the robustness of results and experiment duration.

Likelihood testing of seismicity-based rate forecasts of induced earthquakes in Oklahoma and Kansas

USGS Publications Warehouse

Moschetti, Morgan P.; Hoover, Susan M.; Mueller, Charles

2016-01-01

Likelihood testing of induced earthquakes in Oklahoma and Kansas has identified the parameters that optimize the forecasting ability of smoothed seismicity models and quantified the recent temporal stability of the spatial seismicity patterns. Use of the most recent 1-year period of earthquake data and use of 10–20-km smoothing distances produced the greatest likelihood. The likelihood that the locations of January–June 2015 earthquakes were consistent with optimized forecasts decayed with increasing elapsed time between the catalogs used for model development and testing. Likelihood tests with two additional sets of earthquakes from 2014 exhibit a strong sensitivity of the rate of decay to the smoothing distance. Marked reductions in likelihood are caused by the nonstationarity of the induced earthquake locations. Our results indicate a multiple-fold benefit from smoothed seismicity models in developing short-term earthquake rate forecasts for induced earthquakes in Oklahoma and Kansas, relative to the use of seismic source zones.

Report of the International Commission on Earthquake Forecasting for Civil Protection (Invited)

NASA Astrophysics Data System (ADS)

Jordan, T. H.

2009-12-01

The destructive L’Aquila earthquake of 6 April 2009 (Mw 6.3) illustrates the challenges of operational earthquake forecasting. The earthquake ruptured a mapped normal fault in a region identified by long-term forecasting models as one of the most seismically dangerous in Italy; it was the strongest of a rich sequence that started several months earlier and included a M3.9 foreshock less than five hours prior to the mainshock. According to widely circulated news reports, the earthquake had been predicted by a local resident using unpublished radon-based techniques, provoking a public controversy prior to the event that intensified in its wake. Several weeks after the earthquake, the Italian Department of Civil Protection appointed an international commission with the mandate to report on the current state of knowledge of prediction and forecasting and guidelines for operational utilization. The commission included geoscientists from China, France, Germany, Greece, Italy, Japan, Russia, United Kingdom, and United States with experience in earthquake forecasting and prediction. This presentation by the chair of the commission will report on its findings and recommendations.

A synoptic view of the Third Uniform California Earthquake Rupture Forecast (UCERF3)

USGS Publications Warehouse

Field, Edward; Jordan, Thomas H.; Page, Morgan T.; Milner, Kevin R.; Shaw, Bruce E.; Dawson, Timothy E.; Biasi, Glenn; Parsons, Thomas E.; Hardebeck, Jeanne L.; Michael, Andrew J.; Weldon, Ray; Powers, Peter; Johnson, Kaj M.; Zeng, Yuehua; Bird, Peter; Felzer, Karen; van der Elst, Nicholas; Madden, Christopher; Arrowsmith, Ramon; Werner, Maximillan J.; Thatcher, Wayne R.

2017-01-01

Probabilistic forecasting of earthquake‐producing fault ruptures informs all major decisions aimed at reducing seismic risk and improving earthquake resilience. Earthquake forecasting models rely on two scales of hazard evolution: long‐term (decades to centuries) probabilities of fault rupture, constrained by stress renewal statistics, and short‐term (hours to years) probabilities of distributed seismicity, constrained by earthquake‐clustering statistics. Comprehensive datasets on both hazard scales have been integrated into the Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3). UCERF3 is the first model to provide self‐consistent rupture probabilities over forecasting intervals from less than an hour to more than a century, and it is the first capable of evaluating the short‐term hazards that result from multievent sequences of complex faulting. This article gives an overview of UCERF3, illustrates the short‐term probabilities with aftershock scenarios, and draws some valuable scientific conclusions from the modeling results. In particular, seismic, geologic, and geodetic data, when combined in the UCERF3 framework, reject two types of fault‐based models: long‐term forecasts constrained to have local Gutenberg–Richter scaling, and short‐term forecasts that lack stress relaxation by elastic rebound.

Application of Second-Moment Source Analysis to Three Problems in Earthquake Forecasting

NASA Astrophysics Data System (ADS)

Donovan, J.; Jordan, T. H.

2011-12-01

Though earthquake forecasting models have often represented seismic sources as space-time points (usually hypocenters), a more complete hazard analysis requires the consideration of finite-source effects, such as rupture extent, orientation, directivity, and stress drop. The most compact source representation that includes these effects is the finite moment tensor (FMT), which approximates the degree-two polynomial moments of the stress glut by its projection onto the seismic (degree-zero) moment tensor. This projection yields a scalar space-time source function whose degree-one moments define the centroid moment tensor (CMT) and whose degree-two moments define the FMT. We apply this finite-source parameterization to three forecasting problems. The first is the question of hypocenter bias: can we reject the null hypothesis that the conditional probability of hypocenter location is uniformly distributed over the rupture area? This hypothesis is currently used to specify rupture sets in the "extended" earthquake forecasts that drive simulation-based hazard models, such as CyberShake. Following McGuire et al. (2002), we test the hypothesis using the distribution of FMT directivity ratios calculated from a global data set of source slip inversions. The second is the question of source identification: given an observed FMT (and its errors), can we identify it with an FMT in the complete rupture set that represents an extended fault-based rupture forecast? Solving this problem will facilitate operational earthquake forecasting, which requires the rapid updating of earthquake triggering and clustering models. Our proposed method uses the second-order uncertainties as a norm on the FMT parameter space to identify the closest member of the hypothetical rupture set and to test whether this closest member is an adequate representation of the observed event. Finally, we address the aftershock excitation problem: given a mainshock, what is the spatial distribution of aftershock

Earthquake likelihood model testing

USGS Publications Warehouse

Schorlemmer, D.; Gerstenberger, M.C.; Wiemer, S.; Jackson, D.D.; Rhoades, D.A.

2007-01-01

INTRODUCTIONThe Regional Earthquake Likelihood Models (RELM) project aims to produce and evaluate alternate models of earthquake potential (probability per unit volume, magnitude, and time) for California. Based on differing assumptions, these models are produced to test the validity of their assumptions and to explore which models should be incorporated in seismic hazard and risk evaluation. Tests based on physical and geological criteria are useful but we focus on statistical methods using future earthquake catalog data only. We envision two evaluations: a test of consistency with observed data and a comparison of all pairs of models for relative consistency. Both tests are based on the likelihood method, and both are fully prospective (i.e., the models are not adjusted to fit the test data). To be tested, each model must assign a probability to any possible event within a specified region of space, time, and magnitude. For our tests the models must use a common format: earthquake rates in specified “bins” with location, magnitude, time, and focal mechanism limits.Seismology cannot yet deterministically predict individual earthquakes; however, it should seek the best possible models for forecasting earthquake occurrence. This paper describes the statistical rules of an experiment to examine and test earthquake forecasts. The primary purposes of the tests described below are to evaluate physical models for earthquakes, assure that source models used in seismic hazard and risk studies are consistent with earthquake data, and provide quantitative measures by which models can be assigned weights in a consensus model or be judged as suitable for particular regions.In this paper we develop a statistical method for testing earthquake likelihood models. A companion paper (Schorlemmer and Gerstenberger 2007, this issue) discusses the actual implementation of these tests in the framework of the RELM initiative.Statistical testing of hypotheses is a common task and a

From Tornadoes to Earthquakes: Forecast Verification for Binary Events Applied to the 1999 Chi-Chi, Taiwan, Earthquake

NASA Astrophysics Data System (ADS)

Chen, C.; Rundle, J. B.; Holliday, J. R.; Nanjo, K.; Turcotte, D. L.; Li, S.; Tiampo, K. F.

2005-12-01

Forecast verification procedures for statistical events with binary outcomes typically rely on the use of contingency tables and Relative Operating Characteristic (ROC) diagrams. Originally developed for the statistical evaluation of tornado forecasts on a county-by-county basis, these methods can be adapted to the evaluation of competing earthquake forecasts. Here we apply these methods retrospectively to two forecasts for the m = 7.3 1999 Chi-Chi, Taiwan, earthquake. These forecasts are based on a method, Pattern Informatics (PI), that locates likely sites for future large earthquakes based on large change in activity of the smallest earthquakes. A competing null hypothesis, Relative Intensity (RI), is based on the idea that future large earthquake locations are correlated with sites having the greatest frequency of small earthquakes. We show that for Taiwan, the PI forecast method is superior to the RI forecast null hypothesis. Inspection of the two maps indicates that their forecast locations are indeed quite different. Our results confirm an earlier result suggesting that the earthquake preparation process for events such as the Chi-Chi earthquake involves anomalous changes in activation or quiescence, and that signatures of these processes can be detected in precursory seismicity data. Furthermore, we find that our methods can accurately forecast the locations of aftershocks from precursory seismicity changes alone, implying that the main shock together with its aftershocks represent a single manifestation of the formation of a high-stress region nucleating prior to the main shock.

Earthquake Forecasting Methodology Catalogue - A collection and comparison of the state-of-the-art in earthquake forecasting and prediction methodologies

NASA Astrophysics Data System (ADS)

Schaefer, Andreas; Daniell, James; Wenzel, Friedemann

2015-04-01

Earthquake forecasting and prediction has been one of the key struggles of modern geosciences for the last few decades. A large number of approaches for various time periods have been developed for different locations around the world. A categorization and review of more than 20 of new and old methods was undertaken to develop a state-of-the-art catalogue in forecasting algorithms and methodologies. The different methods have been categorised into time-independent, time-dependent and hybrid methods, from which the last group represents methods where additional data than just historical earthquake statistics have been used. It is necessary to categorize in such a way between pure statistical approaches where historical earthquake data represents the only direct data source and also between algorithms which incorporate further information e.g. spatial data of fault distributions or which incorporate physical models like static triggering to indicate future earthquakes. Furthermore, the location of application has been taken into account to identify methods which can be applied e.g. in active tectonic regions like California or in less active continental regions. In general, most of the methods cover well-known high-seismicity regions like Italy, Japan or California. Many more elements have been reviewed, including the application of established theories and methods e.g. for the determination of the completeness magnitude or whether the modified Omori law was used or not. Target temporal scales are identified as well as the publication history. All these different aspects have been reviewed and catalogued to provide an easy-to-use tool for the development of earthquake forecasting algorithms and to get an overview in the state-of-the-art.

A new scoring method for evaluating the performance of earthquake forecasts and predictions

NASA Astrophysics Data System (ADS)

Zhuang, J.

2009-12-01

This study presents a new method, namely the gambling score, for scoring the performance of earthquake forecasts or predictions. Unlike most other scoring procedures that require a regular scheme of forecast and treat each earthquake equally, regardless their magnitude, this new scoring method compensates the risk that the forecaster has taken. A fair scoring scheme should reward the success in a way that is compatible with the risk taken. Suppose that we have the reference model, usually the Poisson model for usual cases or Omori-Utsu formula for the case of forecasting aftershocks, which gives probability p0 that at least 1 event occurs in a given space-time-magnitude window. The forecaster, similar to a gambler, who starts with a certain number of reputation points, bets 1 reputation point on ``Yes'' or ``No'' according to his forecast, or bets nothing if he performs a NA-prediction. If the forecaster bets 1 reputation point of his reputations on ``Yes" and loses, the number of his reputation points is reduced by 1; if his forecasts is successful, he should be rewarded (1-p0)/p0 reputation points. The quantity (1-p0)/p0 is the return (reward/bet) ratio for bets on ``Yes''. In this way, if the reference model is correct, the expected return that he gains from this bet is 0. This rule also applies to probability forecasts. Suppose that p is the occurrence probability of an earthquake given by the forecaster. We can regard the forecaster as splitting 1 reputation point by betting p on ``Yes'' and 1-p on ``No''. In this way, the forecaster's expected pay-off based on the reference model is still 0. From the viewpoints of both the reference model and the forecaster, the rule for rewarding and punishment is fair. This method is also extended to the continuous case of point process models, where the reputation points bet by the forecaster become a continuous mass on the space-time-magnitude range of interest. We also calculate the upper bound of the gambling score when

Prospectively Evaluating the Collaboratory for the Study of Earthquake Predictability: An Evaluation of the UCERF2 and Updated Five-Year RELM Forecasts

NASA Astrophysics Data System (ADS)

Strader, Anne; Schneider, Max; Schorlemmer, Danijel; Liukis, Maria

2016-04-01

The Collaboratory for the Study of Earthquake Predictability (CSEP) was developed to rigorously test earthquake forecasts retrospectively and prospectively through reproducible, completely transparent experiments within a controlled environment (Zechar et al., 2010). During 2006-2011, thirteen five-year time-invariant prospective earthquake mainshock forecasts developed by the Regional Earthquake Likelihood Models (RELM) working group were evaluated through the CSEP testing center (Schorlemmer and Gerstenberger, 2007). The number, spatial, and magnitude components of the forecasts were compared to the respective observed seismicity components using a set of consistency tests (Schorlemmer et al., 2007, Zechar et al., 2010). In the initial experiment, all but three forecast models passed every test at the 95% significance level, with all forecasts displaying consistent log-likelihoods (L-test) and magnitude distributions (M-test) with the observed seismicity. In the ten-year RELM experiment update, we reevaluate these earthquake forecasts over an eight-year period from 2008-2016, to determine the consistency of previous likelihood testing results over longer time intervals. Additionally, we test the Uniform California Earthquake Rupture Forecast (UCERF2), developed by the U.S. Geological Survey (USGS), and the earthquake rate model developed by the California Geological Survey (CGS) and the USGS for the National Seismic Hazard Mapping Program (NSHMP) against the RELM forecasts. Both the UCERF2 and NSHMP forecasts pass all consistency tests, though the Helmstetter et al. (2007) and Shen et al. (2007) models exhibit greater information gain per earthquake according to the T- and W- tests (Rhoades et al., 2011). Though all but three RELM forecasts pass the spatial likelihood test (S-test), multiple forecasts fail the M-test due to overprediction of the number of earthquakes during the target period. Though there is no significant difference between the UCERF2 and NSHMP

Earthquake cycles and physical modeling of the process leading up to a large earthquake

NASA Astrophysics Data System (ADS)

Ohnaka, Mitiyasu

2004-08-01

A thorough discussion is made on what the rational constitutive law for earthquake ruptures ought to be from the standpoint of the physics of rock friction and fracture on the basis of solid facts observed in the laboratory. From this standpoint, it is concluded that the constitutive law should be a slip-dependent law with parameters that may depend on slip rate or time. With the long-term goal of establishing a rational methodology of forecasting large earthquakes, the entire process of one cycle for a typical, large earthquake is modeled, and a comprehensive scenario that unifies individual models for intermediate-and short-term (immediate) forecasts is presented within the framework based on the slip-dependent constitutive law and the earthquake cycle model. The earthquake cycle includes the phase of accumulation of elastic strain energy with tectonic loading (phase II), and the phase of rupture nucleation at the critical stage where an adequate amount of the elastic strain energy has been stored (phase III). Phase II plays a critical role in physical modeling of intermediate-term forecasting, and phase III in physical modeling of short-term (immediate) forecasting. The seismogenic layer and individual faults therein are inhomogeneous, and some of the physical quantities inherent in earthquake ruptures exhibit scale-dependence. It is therefore critically important to incorporate the properties of inhomogeneity and physical scaling, in order to construct realistic, unified scenarios with predictive capability. The scenario presented may be significant and useful as a necessary first step for establishing the methodology for forecasting large earthquakes.

Forecasting of future earthquakes in the northeast region of India considering energy released concept

NASA Astrophysics Data System (ADS)

Zarola, Amit; Sil, Arjun

2018-04-01

This study presents the forecasting of time and magnitude size of the next earthquake in the northeast India, using four probability distribution models (Gamma, Lognormal, Weibull and Log-logistic) considering updated earthquake catalog of magnitude Mw ≥ 6.0 that occurred from year 1737-2015 in the study area. On the basis of past seismicity of the region, two types of conditional probabilities have been estimated using their best fit model and respective model parameters. The first conditional probability is the probability of seismic energy (e × 1020 ergs), which is expected to release in the future earthquake, exceeding a certain level of seismic energy (E × 1020 ergs). And the second conditional probability is the probability of seismic energy (a × 1020 ergs/year), which is expected to release per year, exceeding a certain level of seismic energy per year (A × 1020 ergs/year). The logarithm likelihood functions (ln L) were also estimated for all four probability distribution models. A higher value of ln L suggests a better model and a lower value shows a worse model. The time of the future earthquake is forecasted by dividing the total seismic energy expected to release in the future earthquake with the total seismic energy expected to release per year. The epicentre of recently occurred 4 January 2016 Manipur earthquake (M 6.7), 13 April 2016 Myanmar earthquake (M 6.9) and the 24 August 2016 Myanmar earthquake (M 6.8) are located in zone Z.12, zone Z.16 and zone Z.15, respectively and that are the identified seismic source zones in the study area which show that the proposed techniques and models yield good forecasting accuracy.

Lessons of L'Aquila for Operational Earthquake Forecasting

NASA Astrophysics Data System (ADS)

Jordan, T. H.

2012-12-01

The L'Aquila earthquake of 6 Apr 2009 (magnitude 6.3) killed 309 people and left tens of thousands homeless. The mainshock was preceded by a vigorous seismic sequence that prompted informal earthquake predictions and evacuations. In an attempt to calm the population, the Italian Department of Civil Protection (DPC) convened its Commission on the Forecasting and Prevention of Major Risk (MRC) in L'Aquila on 31 March 2009 and issued statements about the hazard that were widely received as an "anti-alarm"; i.e., a deterministic prediction that there would not be a major earthquake. On October 23, 2012, a court in L'Aquila convicted the vice-director of DPC and six scientists and engineers who attended the MRC meeting on charges of criminal manslaughter, and it sentenced each to six years in prison. A few weeks after the L'Aquila disaster, the Italian government convened an International Commission on Earthquake Forecasting for Civil Protection (ICEF) with the mandate to assess the status of short-term forecasting methods and to recommend how they should be used in civil protection. The ICEF, which I chaired, issued its findings and recommendations on 2 Oct 2009 and published its final report, "Operational Earthquake Forecasting: Status of Knowledge and Guidelines for Implementation," in Aug 2011 (www.annalsofgeophysics.eu/index.php/annals/article/view/5350). As defined by the Commission, operational earthquake forecasting (OEF) involves two key activities: the continual updating of authoritative information about the future occurrence of potentially damaging earthquakes, and the officially sanctioned dissemination of this information to enhance earthquake preparedness in threatened communities. Among the main lessons of L'Aquila is the need to separate the role of science advisors, whose job is to provide objective information about natural hazards, from that of civil decision-makers who must weigh the benefits of protective actions against the costs of false alarms

Earthquake number forecasts testing

NASA Astrophysics Data System (ADS)

Kagan, Yan Y.

2017-10-01

We study the distributions of earthquake numbers in two global earthquake catalogues: Global Centroid-Moment Tensor and Preliminary Determinations of Epicenters. The properties of these distributions are especially required to develop the number test for our forecasts of future seismic activity rate, tested by the Collaboratory for Study of Earthquake Predictability (CSEP). A common assumption, as used in the CSEP tests, is that the numbers are described by the Poisson distribution. It is clear, however, that the Poisson assumption for the earthquake number distribution is incorrect, especially for the catalogues with a lower magnitude threshold. In contrast to the one-parameter Poisson distribution so widely used to describe earthquake occurrences, the negative-binomial distribution (NBD) has two parameters. The second parameter can be used to characterize the clustering or overdispersion of a process. We also introduce and study a more complex three-parameter beta negative-binomial distribution. We investigate the dependence of parameters for both Poisson and NBD distributions on the catalogue magnitude threshold and on temporal subdivision of catalogue duration. First, we study whether the Poisson law can be statistically rejected for various catalogue subdivisions. We find that for most cases of interest, the Poisson distribution can be shown to be rejected statistically at a high significance level in favour of the NBD. Thereafter, we investigate whether these distributions fit the observed distributions of seismicity. For this purpose, we study upper statistical moments of earthquake numbers (skewness and kurtosis) and compare them to the theoretical values for both distributions. Empirical values for the skewness and the kurtosis increase for the smaller magnitude threshold and increase with even greater intensity for small temporal subdivision of catalogues. The Poisson distribution for large rate values approaches the Gaussian law, therefore its skewness

Chapter B. The Loma Prieta, California, Earthquake of October 17, 1989 - Forecasts

USGS Publications Warehouse

Harris, Ruth A.

1998-01-01

The magnitude (Mw) 6.9 Loma Prieta earthquake struck the San Francisco Bay region of central California at 5:04 p.m. P.d.t. on October 17, 1989, killing 62 people and generating billions of dollars in property damage. Scientists were not surprised by the occurrence of a destructive earthquake in this region and had, in fact, been attempting to forecast the location of the next large earthquake in the San Francisco Bay region for decades. This paper summarizes more than 20 scientifically based forecasts made before the 1989 Loma Prieta earthquake for a large earthquake that might occur in the Loma Prieta area. The forecasts geographically closest to the actual earthquake primarily consisted of right-lateral strike-slip motion on the San Andreas Fault northwest of San Juan Bautista. Several of the forecasts did encompass the magnitude of the actual earthquake, and at least one approximately encompassed the along-strike rupture length. The 1989 Loma Prieta earthquake differed from most of the forecasted events in two ways: (1) it occurred with considerable dip-slip in addition to strike-slip motion, and (2) it was much deeper than expected.

2017 One‐year seismic‐hazard forecast for the central and eastern United States from induced and natural earthquakes

USGS Publications Warehouse

Petersen, Mark D.; Mueller, Charles; Moschetti, Morgan P.; Hoover, Susan M.; Shumway, Allison; McNamara, Daniel E.; Williams, Robert; Llenos, Andrea L.; Ellsworth, William L.; Rubinstein, Justin L.; McGarr, Arthur F.; Rukstales, Kenneth S.

2017-01-01

We produce a one‐year 2017 seismic‐hazard forecast for the central and eastern United States from induced and natural earthquakes that updates the 2016 one‐year forecast; this map is intended to provide information to the public and to facilitate the development of induced seismicity forecasting models, methods, and data. The 2017 hazard model applies the same methodology and input logic tree as the 2016 forecast, but with an updated earthquake catalog. We also evaluate the 2016 seismic‐hazard forecast to improve future assessments. The 2016 forecast indicated high seismic hazard (greater than 1% probability of potentially damaging ground shaking in one year) in five focus areas: Oklahoma–Kansas, the Raton basin (Colorado/New Mexico border), north Texas, north Arkansas, and the New Madrid Seismic Zone. During 2016, several damaging induced earthquakes occurred in Oklahoma within the highest hazard region of the 2016 forecast; all of the 21 moment magnitude (M) ≥4 and 3 M≥5 earthquakes occurred within the highest hazard area in the 2016 forecast. Outside the Oklahoma–Kansas focus area, two earthquakes with M≥4 occurred near Trinidad, Colorado (in the Raton basin focus area), but no earthquakes with M≥2.7 were observed in the north Texas or north Arkansas focus areas. Several observations of damaging ground‐shaking levels were also recorded in the highest hazard region of Oklahoma. The 2017 forecasted seismic rates are lower in regions of induced activity due to lower rates of earthquakes in 2016 compared with 2015, which may be related to decreased wastewater injection caused by regulatory actions or by a decrease in unconventional oil and gas production. Nevertheless, the 2017 forecasted hazard is still significantly elevated in Oklahoma compared to the hazard calculated from seismicity before 2009.

Earthquake and failure forecasting in real-time: A Forecasting Model Testing Centre

NASA Astrophysics Data System (ADS)

Filgueira, Rosa; Atkinson, Malcolm; Bell, Andrew; Main, Ian; Boon, Steven; Meredith, Philip

2013-04-01

Across Europe there are a large number of rock deformation laboratories, each of which runs many experiments. Similarly there are a large number of theoretical rock physicists who develop constitutive and computational models both for rock deformation and changes in geophysical properties. Here we consider how to open up opportunities for sharing experimental data in a way that is integrated with multiple hypothesis testing. We present a prototype for a new forecasting model testing centre based on e-infrastructures for capturing and sharing data and models to accelerate the Rock Physicist (RP) research. This proposal is triggered by our work on data assimilation in the NERC EFFORT (Earthquake and Failure Forecasting in Real Time) project, using data provided by the NERC CREEP 2 experimental project as a test case. EFFORT is a multi-disciplinary collaboration between Geoscientists, Rock Physicists and Computer Scientist. Brittle failure of the crust is likely to play a key role in controlling the timing of a range of geophysical hazards, such as volcanic eruptions, yet the predictability of brittle failure is unknown. Our aim is to provide a facility for developing and testing models to forecast brittle failure in experimental and natural data. Model testing is performed in real-time, verifiably prospective mode, in order to avoid selection biases that are possible in retrospective analyses. The project will ultimately quantify the predictability of brittle failure, and how this predictability scales from simple, controlled laboratory conditions to the complex, uncontrolled real world. Experimental data are collected from controlled laboratory experiments which includes data from the UCL Laboratory and from Creep2 project which will undertake experiments in a deep-sea laboratory. We illustrate the properties of the prototype testing centre by streaming and analysing realistically noisy synthetic data, as an aid to generating and improving testing methodologies in

Hydromechanical Earthquake Nucleation Model Forecasts Onset, Peak, and Falling Rates of Induced Seismicity in Oklahoma and Kansas

NASA Astrophysics Data System (ADS)

Norbeck, J. H.; Rubinstein, J. L.

2018-04-01

The earthquake activity in Oklahoma and Kansas that began in 2008 reflects the most widespread instance of induced seismicity observed to date. We develop a reservoir model to calculate the hydrologic conditions associated with the activity of 902 saltwater disposal wells injecting into the Arbuckle aquifer. Estimates of basement fault stressing conditions inform a rate-and-state friction earthquake nucleation model to forecast the seismic response to injection. Our model replicates many salient features of the induced earthquake sequence, including the onset of seismicity, the timing of the peak seismicity rate, and the reduction in seismicity following decreased disposal activity. We present evidence for variable time lags between changes in injection and seismicity rates, consistent with the prediction from rate-and-state theory that seismicity rate transients occur over timescales inversely proportional to stressing rate. Given the efficacy of the hydromechanical model, as confirmed through a likelihood statistical test, the results of this study support broader integration of earthquake physics within seismic hazard analysis.

First Results of the Regional Earthquake Likelihood Models Experiment

USGS Publications Warehouse

Schorlemmer, D.; Zechar, J.D.; Werner, M.J.; Field, E.H.; Jackson, D.D.; Jordan, T.H.

2010-01-01

The ability to successfully predict the future behavior of a system is a strong indication that the system is well understood. Certainly many details of the earthquake system remain obscure, but several hypotheses related to earthquake occurrence and seismic hazard have been proffered, and predicting earthquake behavior is a worthy goal and demanded by society. Along these lines, one of the primary objectives of the Regional Earthquake Likelihood Models (RELM) working group was to formalize earthquake occurrence hypotheses in the form of prospective earthquake rate forecasts in California. RELM members, working in small research groups, developed more than a dozen 5-year forecasts; they also outlined a performance evaluation method and provided a conceptual description of a Testing Center in which to perform predictability experiments. Subsequently, researchers working within the Collaboratory for the Study of Earthquake Predictability (CSEP) have begun implementing Testing Centers in different locations worldwide, and the RELM predictability experiment-a truly prospective earthquake prediction effort-is underway within the U. S. branch of CSEP. The experiment, designed to compare time-invariant 5-year earthquake rate forecasts, is now approximately halfway to its completion. In this paper, we describe the models under evaluation and present, for the first time, preliminary results of this unique experiment. While these results are preliminary-the forecasts were meant for an application of 5 years-we find interesting results: most of the models are consistent with the observation and one model forecasts the distribution of earthquakes best. We discuss the observed sample of target earthquakes in the context of historical seismicity within the testing region, highlight potential pitfalls of the current tests, and suggest plans for future revisions to experiments such as this one. ?? 2010 The Author(s).

First Results of the Regional Earthquake Likelihood Models Experiment

NASA Astrophysics Data System (ADS)

Schorlemmer, Danijel; Zechar, J. Douglas; Werner, Maximilian J.; Field, Edward H.; Jackson, David D.; Jordan, Thomas H.

2010-08-01

The ability to successfully predict the future behavior of a system is a strong indication that the system is well understood. Certainly many details of the earthquake system remain obscure, but several hypotheses related to earthquake occurrence and seismic hazard have been proffered, and predicting earthquake behavior is a worthy goal and demanded by society. Along these lines, one of the primary objectives of the Regional Earthquake Likelihood Models (RELM) working group was to formalize earthquake occurrence hypotheses in the form of prospective earthquake rate forecasts in California. RELM members, working in small research groups, developed more than a dozen 5-year forecasts; they also outlined a performance evaluation method and provided a conceptual description of a Testing Center in which to perform predictability experiments. Subsequently, researchers working within the Collaboratory for the Study of Earthquake Predictability (CSEP) have begun implementing Testing Centers in different locations worldwide, and the RELM predictability experiment—a truly prospective earthquake prediction effort—is underway within the U.S. branch of CSEP. The experiment, designed to compare time-invariant 5-year earthquake rate forecasts, is now approximately halfway to its completion. In this paper, we describe the models under evaluation and present, for the first time, preliminary results of this unique experiment. While these results are preliminary—the forecasts were meant for an application of 5 years—we find interesting results: most of the models are consistent with the observation and one model forecasts the distribution of earthquakes best. We discuss the observed sample of target earthquakes in the context of historical seismicity within the testing region, highlight potential pitfalls of the current tests, and suggest plans for future revisions to experiments such as this one.

Time-varying loss forecast for an earthquake scenario in Basel, Switzerland

NASA Astrophysics Data System (ADS)

Herrmann, Marcus; Zechar, Jeremy D.; Wiemer, Stefan

2014-05-01

When an unexpected earthquake occurs, people suddenly want advice on how to cope with the situation. The 2009 L'Aquila quake highlighted the significance of public communication and pushed the usage of scientific methods to drive alternative risk mitigation strategies. For instance, van Stiphout et al. (2010) suggested a new approach for objective evacuation decisions on short-term: probabilistic risk forecasting combined with cost-benefit analysis. In the present work, we apply this approach to an earthquake sequence that simulated a repeat of the 1356 Basel earthquake, one of the most damaging events in Central Europe. A recent development to benefit society in case of an earthquake are probabilistic forecasts of the aftershock occurrence. But seismic risk delivers a more direct expression of the socio-economic impact. To forecast the seismic risk on short-term, we translate aftershock probabilities to time-varying seismic hazard and combine this with time-invariant loss estimation. Compared with van Stiphout et al. (2010), we use an advanced aftershock forecasting model and detailed settlement data to allow us spatial forecasts and settlement-specific decision-making. We quantify the risk forecast probabilistically in terms of human loss. For instance one minute after the M6.6 mainshock, the probability for an individual to die within the next 24 hours is 41 000 times higher than the long-term average; but the absolute value remains at minor 0.04 %. The final cost-benefit analysis adds value beyond a pure statistical approach: it provides objective statements that may justify evacuations. To deliver supportive information in a simple form, we propose a warning approach in terms of alarm levels. Our results do not justify evacuations prior to the M6.6 mainshock, but in certain districts afterwards. The ability to forecast the short-term seismic risk at any time-and with sufficient data anywhere-is the first step of personal decision-making and raising risk

Retrospective validation of renewal-based, medium-term earthquake forecasts

NASA Astrophysics Data System (ADS)

Rotondi, R.

2013-10-01

In this paper, some methods for scoring the performances of an earthquake forecasting probability model are applied retrospectively for different goals. The time-dependent occurrence probabilities of a renewal process are tested against earthquakes of Mw ≥ 5.3 recorded in Italy according to decades of the past century. An aim was to check the capability of the model to reproduce the data by which the model was calibrated. The scoring procedures used can be distinguished on the basis of the requirement (or absence) of a reference model and of probability thresholds. Overall, a rank-based score, information gain, gambling scores, indices used in binary predictions and their loss functions are considered. The definition of various probability thresholds as percentages of the hazard functions allows proposals of the values associated with the best forecasting performance as alarm level in procedures for seismic risk mitigation. Some improvements are then made to the input data concerning the completeness of the historical catalogue and the consistency of the composite seismogenic sources with the hypotheses of the probability model. Another purpose of this study was thus to obtain hints on what is the most influential factor and on the suitability of adopting the consequent changes of the data sets. This is achieved by repeating the estimation procedure of the occurrence probabilities and the retrospective validation of the forecasts obtained under the new assumptions. According to the rank-based score, the completeness appears to be the most influential factor, while there are no clear indications of the usefulness of the decomposition of some composite sources, although in some cases, it has led to improvements of the forecast.

Near-Field Tsunami Models with Rapid Earthquake Source Inversions from Land and Ocean-Based Observations: The Potential for Forecast and Warning

NASA Astrophysics Data System (ADS)

Melgar, D.; Bock, Y.; Crowell, B. W.; Haase, J. S.

2013-12-01

Computation of predicted tsunami wave heights and runup in the regions adjacent to large earthquakes immediately after rupture initiation remains a challenging problem. Limitations of traditional seismological instrumentation in the near field which cannot be objectively employed for real-time inversions and the non-unique source inversion results are a major concern for tsunami modelers. Employing near-field seismic, GPS and wave gauge data from the Mw 9.0 2011 Tohoku-oki earthquake, we test the capacity of static finite fault slip models obtained from newly developed algorithms to produce reliable tsunami forecasts. First we demonstrate the ability of seismogeodetic source models determined from combined land-based GPS and strong motion seismometers to forecast near-source tsunamis in ~3 minutes after earthquake origin time (OT). We show that these models, based on land-borne sensors only tend to underestimate the tsunami but are good enough to provide a realistic first warning. We then demonstrate that rapid ingestion of offshore shallow water (100 - 1000 m) wave gauge data significantly improves the model forecasts and possible warnings. We ingest data from 2 near-source ocean-bottom pressure sensors and 6 GPS buoys into the earthquake source inversion process. Tsunami Green functions (tGFs) are generated using the GeoClaw package, a benchmarked finite volume code with adaptive mesh refinement. These tGFs are used for a joint inversion with the land-based data and substantially improve the earthquake source and tsunami forecast. Model skill is assessed by detailed comparisons of the simulation output to 2000+ tsunami runup survey measurements collected after the event. We update the source model and tsunami forecast and warning at 10 min intervals. We show that by 20 min after OT the tsunami is well-predicted with a high variance reduction to the survey data and by ~30 minutes a model that can be considered final, since little changed is observed afterwards, is

Statistical Earthquake Focal Mechanism Forecasts

NASA Astrophysics Data System (ADS)

Kagan, Y. Y.; Jackson, D. D.

2013-12-01

The new whole Earth focal mechanism forecast, based on the GCMT catalog, has been created. In the present forecast, the sum of normalized seismic moment tensors within 1000 km radius is calculated and the P- and T-axes for the focal mechanism are evaluated on the basis of the sum. Simultaneously we calculate an average rotation angle between the forecasted mechanism and all the surrounding mechanisms. This average angle shows tectonic complexity of a region and indicates the accuracy of the prediction. The method was originally proposed by Kagan and Jackson (1994, JGR). Recent interest by CSEP and GEM has motivated some improvements, particularly to extend the previous forecast to polar and near-polar regions. The major problem in extending the forecast is the focal mechanism calculation on a spherical surface. In the previous forecast as our average focal mechanism was computed, it was assumed that longitude lines are approximately parallel within 1000 km radius. This is largely accurate in the equatorial and near-equatorial areas. However, when one approaches the 75 degree latitude, the longitude lines are no longer parallel: the bearing (azimuthal) difference at points separated by 1000 km reach about 35 degrees. In most situations a forecast point where we calculate an average focal mechanism is surrounded by earthquakes, so a bias should not be strong due to the difference effect cancellation. But if we move into polar regions, the bearing difference could approach 180 degrees. In a modified program focal mechanisms have been projected on a plane tangent to a sphere at a forecast point. New longitude axes which are parallel in the tangent plane are corrected for the bearing difference. A comparison with the old 75S-75N forecast shows that in equatorial regions the forecasted focal mechanisms are almost the same, and the difference in the forecasted focal mechanisms rotation angle is close to zero. However, though the forecasted focal mechanisms are similar

Uniform California earthquake rupture forecast, version 2 (UCERF 2)

USGS Publications Warehouse

Field, E.H.; Dawson, T.E.; Felzer, K.R.; Frankel, A.D.; Gupta, V.; Jordan, T.H.; Parsons, T.; Petersen, M.D.; Stein, R.S.; Weldon, R.J.; Wills, C.J.

2009-01-01

The 2007 Working Group on California Earthquake Probabilities (WGCEP, 2007) presents the Uniform California Earthquake Rupture Forecast, Version 2 (UCERF 2). This model comprises a time-independent (Poisson-process) earthquake rate model, developed jointly with the National Seismic Hazard Mapping Program and a time-dependent earthquake-probability model, based on recent earthquake rates and stress-renewal statistics conditioned on the date of last event. The models were developed from updated statewide earthquake catalogs and fault deformation databases using a uniform methodology across all regions and implemented in the modular, extensible Open Seismic Hazard Analysis framework. The rate model satisfies integrating measures of deformation across the plate-boundary zone and is consistent with historical seismicity data. An overprediction of earthquake rates found at intermediate magnitudes (6.5 ??? M ???7.0) in previous models has been reduced to within the 95% confidence bounds of the historical earthquake catalog. A logic tree with 480 branches represents the epistemic uncertainties of the full time-dependent model. The mean UCERF 2 time-dependent probability of one or more M ???6.7 earthquakes in the California region during the next 30 yr is 99.7%; this probability decreases to 46% for M ???7.5 and to 4.5% for M ???8.0. These probabilities do not include the Cascadia subduction zone, largely north of California, for which the estimated 30 yr, M ???8.0 time-dependent probability is 10%. The M ???6.7 probabilities on major strike-slip faults are consistent with the WGCEP (2003) study in the San Francisco Bay Area and the WGCEP (1995) study in southern California, except for significantly lower estimates along the San Jacinto and Elsinore faults, owing to provisions for larger multisegment ruptures. Important model limitations are discussed.

Assessing a 3D smoothed seismicity model of induced earthquakes

NASA Astrophysics Data System (ADS)

Zechar, Jeremy; Király, Eszter; Gischig, Valentin; Wiemer, Stefan

2016-04-01

As more energy exploration and extraction efforts cause earthquakes, it becomes increasingly important to control induced seismicity. Risk management schemes must be improved and should ultimately be based on near-real-time forecasting systems. With this goal in mind, we propose a test bench to evaluate models of induced seismicity based on metrics developed by the CSEP community. To illustrate the test bench, we consider a model based on the so-called seismogenic index and a rate decay; to produce three-dimensional forecasts, we smooth past earthquakes in space and time. We explore four variants of this model using the Basel 2006 and Soultz-sous-Forêts 2004 datasets to make short-term forecasts, test their consistency, and rank the model variants. Our results suggest that such a smoothed seismicity model is useful for forecasting induced seismicity within three days, and giving more weight to recent events improves forecast performance. Moreover, the location of the largest induced earthquake is forecast well by this model. Despite the good spatial performance, the model does not estimate the seismicity rate well: it frequently overestimates during stimulation and during the early post-stimulation period, and it systematically underestimates around shut-in. In this presentation, we also describe a robust estimate of information gain, a modification that can also benefit forecast experiments involving tectonic earthquakes.

Evaluation of annual, global seismicity forecasts, including ensemble models

NASA Astrophysics Data System (ADS)

Taroni, Matteo; Zechar, Jeremy; Marzocchi, Warner

2013-04-01

In 2009, the Collaboratory for the Study of the Earthquake Predictability (CSEP) initiated a prototype global earthquake forecast experiment. Three models participated in this experiment for 2009, 2010 and 2011—each model forecast the number of earthquakes above magnitude 6 in 1x1 degree cells that span the globe. Here we use likelihood-based metrics to evaluate the consistency of the forecasts with the observed seismicity. We compare model performance with statistical tests and a new method based on the peer-to-peer gambling score. The results of the comparisons are used to build ensemble models that are a weighted combination of the individual models. Notably, in these experiments the ensemble model always performs significantly better than the single best-performing model. Our results indicate the following: i) time-varying forecasts, if not updated after each major shock, may not provide significant advantages with respect to time-invariant models in 1-year forecast experiments; ii) the spatial distribution seems to be the most important feature to characterize the different forecasting performances of the models; iii) the interpretation of consistency tests may be misleading because some good models may be rejected while trivial models may pass consistency tests; iv) a proper ensemble modeling seems to be a valuable procedure to get the best performing model for practical purposes.

Earthquake recurrence models fail when earthquakes fail to reset the stress field

USGS Publications Warehouse

Tormann, Thessa; Wiemer, Stefan; Hardebeck, Jeanne L.

2012-01-01

Parkfield's regularly occurring M6 mainshocks, about every 25 years, have over two decades stoked seismologists' hopes to successfully predict an earthquake of significant size. However, with the longest known inter-event time of 38 years, the latest M6 in the series (28 Sep 2004) did not conform to any of the applied forecast models, questioning once more the predictability of earthquakes in general. Our study investigates the spatial pattern of b-values along the Parkfield segment through the seismic cycle and documents a stably stressed structure. The forecasted rate of M6 earthquakes based on Parkfield's microseismicity b-values corresponds well to observed rates. We interpret the observed b-value stability in terms of the evolution of the stress field in that area: the M6 Parkfield earthquakes do not fully unload the stress on the fault, explaining why time recurrent models fail. We present the 1989 M6.9 Loma Prieta earthquake as counter example, which did release a significant portion of the stress along its fault segment and yields a substantial change in b-values.

Optimizing Tsunami Forecast Model Accuracy

NASA Astrophysics Data System (ADS)

Whitmore, P.; Nyland, D. L.; Huang, P. Y.

2015-12-01

Recent tsunamis provide a means to determine the accuracy that can be expected of real-time tsunami forecast models. Forecast accuracy using two different tsunami forecast models are compared for seven events since 2006 based on both real-time application and optimized, after-the-fact "forecasts". Lessons learned by comparing the forecast accuracy determined during an event to modified applications of the models after-the-fact provide improved methods for real-time forecasting for future events. Variables such as source definition, data assimilation, and model scaling factors are examined to optimize forecast accuracy. Forecast accuracy is also compared for direct forward modeling based on earthquake source parameters versus accuracy obtained by assimilating sea level data into the forecast model. Results show that including assimilated sea level data into the models increases accuracy by approximately 15% for the events examined.

Time-dependent earthquake forecasting: Method and application to the Italian region

NASA Astrophysics Data System (ADS)

Chan, C.; Sorensen, M. B.; Grünthal, G.; Hakimhashemi, A.; Heidbach, O.; Stromeyer, D.; Bosse, C.

2009-12-01

We develop a new approach for time-dependent earthquake forecasting and apply it to the Italian region. In our approach, the seismicity density is represented by a bandwidth function as a smoothing Kernel in the neighboring region of earthquakes. To consider the fault-interaction-based forecasting, we calculate the Coulomb stress change imparted by each earthquake in the study area. From this, the change of seismicity rate as a function of time can be estimated by the concept of rate-and-state stress transfer. We apply our approach to the region of Italy and earthquakes that occurred before 2003 to generate the seismicity density. To validate our approach, we compare our estimated seismicity density with the distribution of earthquakes with M≥3.8 after 2004. A positive correlation is found and all of the examined earthquakes locate in the area of the highest 66 percentile of seismicity density in the study region. Furthermore, the seismicity density corresponding to the epicenter of the 2009 April 6, Mw = 6.3, L’Aquila earthquake is in the area of the highest 5 percentile. For the time-dependent seismicity rate change, we estimate the rate-and-state stress transfer imparted by the M≥5.0 earthquakes occurred in the past 50 years. It suggests that the seismicity rate has increased at the locations of 65% of the examined earthquakes. Applying this approach to the L’Aquila sequence by considering seven M≥5.0 aftershocks as well as the main shock, not only spatial but also temporal forecasting of the aftershock distribution is significant.

Rate/state Coulomb stress transfer model for the CSEP Japan seismicity forecast

NASA Astrophysics Data System (ADS)

Toda, Shinji; Enescu, Bogdan

2011-03-01

Numerous studies retrospectively found that seismicity rate jumps (drops) by coseismic Coulomb stress increase (decrease). The Collaboratory for the Study of Earthquake Prediction (CSEP) instead provides us an opportunity for prospective testing of the Coulomb hypothesis. Here we adapt our stress transfer model incorporating rate and state dependent friction law to the CSEP Japan seismicity forecast. We demonstrate how to compute the forecast rates of large shocks in 2009 using the large earthquakes during the past 120 years. The time dependent impact of the coseismic stress perturbations explains qualitatively well the occurrence of the recent moderate size shocks. Such ability is partly similar to that of statistical earthquake clustering models. However, our model differs from them as follows: the off-fault aftershock zones can be simulated using finite fault sources; the regional areal patterns of triggered seismicity are modified by the dominant mechanisms of the potential sources; the imparted stresses due to large earthquakes produce stress shadows that lead to a reduction of the forecasted number of earthquakes. Although the model relies on several unknown parameters, it is the first physics based model submitted to the CSEP Japan test center and has the potential to be tuned for short-term earthquake forecasts.

Short-term earthquake forecasting based on an epidemic clustering model

NASA Astrophysics Data System (ADS)

Console, Rodolfo; Murru, Maura; Falcone, Giuseppe

2016-04-01

The application of rigorous statistical tools, with the aim of verifying any prediction method, requires a univocal definition of the hypothesis, or the model, characterizing the concerned anomaly or precursor, so as it can be objectively recognized in any circumstance and by any observer. This is mandatory to build up on the old-fashion approach consisting only of the retrospective anecdotic study of past cases. A rigorous definition of an earthquake forecasting hypothesis should lead to the objective identification of particular sub-volumes (usually named alarm volumes) of the total time-space volume within which the probability of occurrence of strong earthquakes is higher than the usual. The test of a similar hypothesis needs the observation of a sufficient number of past cases upon which a statistical analysis is possible. This analysis should be aimed to determine the rate at which the precursor has been followed (success rate) or not followed (false alarm rate) by the target seismic event, or the rate at which a target event has been preceded (alarm rate) or not preceded (failure rate) by the precursor. The binary table obtained from this kind of analysis leads to the definition of the parameters of the model that achieve the maximum number of successes and the minimum number of false alarms for a specific class of precursors. The mathematical tools suitable for this purpose may include the definition of Probability Gain or the R-Score, as well as the application of popular plots such as the Molchan error-diagram and the ROC diagram. Another tool for evaluating the validity of a forecasting method is the concept of the likelihood ratio (also named performance factor) of occurrence and non-occurrence of seismic events under different hypotheses. Whatever is the method chosen for building up a new hypothesis, usually based on retrospective data, the final assessment of its validity should be carried out by a test on a new and independent set of observations

2018 one‐year seismic hazard forecast for the central and eastern United States from induced and natural earthquakes

USGS Publications Warehouse

Petersen, Mark D.; Mueller, Charles; Moschetti, Morgan P.; Hoover, Susan M.; Rukstales, Kenneth S.; McNamara, Daniel E.; Williams, Robert A.; Shumway, Allison; Powers, Peter; Earle, Paul; Llenos, Andrea L.; Michael, Andrew J.; Rubinstein, Justin L.; Norbeck, Jack; Cochran, Elizabeth S.

2018-01-01

This article describes the U.S. Geological Survey (USGS) 2018 one‐year probabilistic seismic hazard forecast for the central and eastern United States from induced and natural earthquakes. For consistency, the updated 2018 forecast is developed using the same probabilistic seismicity‐based methodology as applied in the two previous forecasts. Rates of earthquakes across the United States M≥3.0">M≥3.0 grew rapidly between 2008 and 2015 but have steadily declined over the past 3 years, especially in areas of Oklahoma and southern Kansas where fluid injection has decreased. The seismicity pattern in 2017 was complex with earthquakes more spatially dispersed than in the previous years. Some areas of west‐central Oklahoma experienced increased activity rates where industrial activity increased. Earthquake rates in Oklahoma (429 earthquakes of M≥3">M≥3 and 4 M≥4">M≥4), Raton basin (Colorado/New Mexico border, six earthquakes M≥3">M≥3), and the New Madrid seismic zone (11 earthquakes M≥3">M≥3) continue to be higher than historical levels. Almost all of these earthquakes occurred within the highest hazard regions of the 2017 forecast. Even though rates declined over the past 3 years, the short‐term hazard for damaging ground shaking across much of Oklahoma remains at high levels due to continuing high rates of smaller earthquakes that are still hundreds of times higher than at any time in the state’s history. Fine details and variability between the 2016–2018 forecasts are obscured by significant uncertainties in the input model. These short‐term hazard levels are similar to active regions in California. During 2017, M≥3">M≥3 earthquakes also occurred in or near Ohio, West Virginia, Missouri, Kentucky, Tennessee, Arkansas, Illinois, Oklahoma, Kansas, Colorado, New Mexico, Utah, and Wyoming.

Spatial organization of foreshocks as a tool to forecast large earthquakes.

PubMed

Lippiello, E; Marzocchi, W; de Arcangelis, L; Godano, C

2012-01-01

An increase in the number of smaller magnitude events, retrospectively named foreshocks, is often observed before large earthquakes. We show that the linear density probability of earthquakes occurring before and after small or intermediate mainshocks displays a symmetrical behavior, indicating that the size of the area fractured during the mainshock is encoded in the foreshock spatial organization. This observation can be used to discriminate spatial clustering due to foreshocks from the one induced by aftershocks and is implemented in an alarm-based model to forecast m > 6 earthquakes. A retrospective study of the last 19 years Southern California catalog shows that the daily occurrence probability presents isolated peaks closely located in time and space to the epicenters of five of the six m > 6 earthquakes. We find daily probabilities as high as 25% (in cells of size 0.04 × 0.04deg(2)), with significant probability gains with respect to standard models.

Spatial organization of foreshocks as a tool to forecast large earthquakes

PubMed Central

Lippiello, E.; Marzocchi, W.; de Arcangelis, L.; Godano, C.

2012-01-01

An increase in the number of smaller magnitude events, retrospectively named foreshocks, is often observed before large earthquakes. We show that the linear density probability of earthquakes occurring before and after small or intermediate mainshocks displays a symmetrical behavior, indicating that the size of the area fractured during the mainshock is encoded in the foreshock spatial organization. This observation can be used to discriminate spatial clustering due to foreshocks from the one induced by aftershocks and is implemented in an alarm-based model to forecast m > 6 earthquakes. A retrospective study of the last 19 years Southern California catalog shows that the daily occurrence probability presents isolated peaks closely located in time and space to the epicenters of five of the six m > 6 earthquakes. We find daily probabilities as high as 25% (in cells of size 0.04 × 0.04deg2), with significant probability gains with respect to standard models. PMID:23152938

Earthquake Forecasting Through Semi-periodicity Analysis of Labeled Point Processes

NASA Astrophysics Data System (ADS)

Quinteros Cartaya, C. B. M.; Nava Pichardo, F. A.; Glowacka, E.; Gomez-Trevino, E.

2015-12-01

Large earthquakes have semi-periodic behavior as result of critically self-organized processes of stress accumulation and release in some seismogenic region. Thus, large earthquakes in a region constitute semi-periodic sequences with recurrence times varying slightly from periodicity. Nava et al., 2013 and Quinteros et al., 2013 realized that not all earthquakes in a given region need belong to the same sequence, since there can be more than one process of stress accumulation and release in it; they also proposed a method to identify semi-periodic sequences through analytic Fourier analysis. This work presents improvements on the above-mentioned method: the influence of earthquake size on the spectral analysis, and its importance in semi-periodic events identification, which means that earthquake occurrence times are treated as a labeled point process; the estimation of appropriate upper limit uncertainties to use in forecasts; and the use of Bayesian analysis to evaluate the forecast performance. This improved method is applied to specific regions: the southwestern coast of Mexico, the northeastern Japan Arc, the San Andreas Fault zone at Parkfield, and northeastern Venezuela.

2016 one-year seismic hazard forecast for the Central and Eastern United States from induced and natural earthquakes

USGS Publications Warehouse

Petersen, Mark D.; Mueller, Charles S.; Moschetti, Morgan P.; Hoover, Susan M.; Llenos, Andrea L.; Ellsworth, William L.; Michael, Andrew J.; Rubinstein, Justin L.; McGarr, Arthur F.; Rukstales, Kenneth S.

2016-03-28

The U.S. Geological Survey (USGS) has produced a 1-year seismic hazard forecast for 2016 for the Central and Eastern United States (CEUS) that includes contributions from both induced and natural earthquakes. The model assumes that earthquake rates calculated from several different time windows will remain relatively stationary and can be used to forecast earthquake hazard and damage intensity for the year 2016. This assessment is the first step in developing an operational earthquake forecast for the CEUS, and the analysis could be revised with updated seismicity and model parameters. Consensus input models consider alternative earthquake catalog durations, smoothing parameters, maximum magnitudes, and ground motion estimates, and represent uncertainties in earthquake occurrence and diversity of opinion in the science community. Ground shaking seismic hazard for 1-percent probability of exceedance in 1 year reaches 0.6 g (as a fraction of standard gravity [g]) in northern Oklahoma and southern Kansas, and about 0.2 g in the Raton Basin of Colorado and New Mexico, in central Arkansas, and in north-central Texas near Dallas. Near some areas of active induced earthquakes, hazard is higher than in the 2014 USGS National Seismic Hazard Model (NHSM) by more than a factor of 3; the 2014 NHSM did not consider induced earthquakes. In some areas, previously observed induced earthquakes have stopped, so the seismic hazard reverts back to the 2014 NSHM. Increased seismic activity, whether defined as induced or natural, produces high hazard. Conversion of ground shaking to seismic intensity indicates that some places in Oklahoma, Kansas, Colorado, New Mexico, Texas, and Arkansas may experience damage if the induced seismicity continues unabated. The chance of having Modified Mercalli Intensity (MMI) VI or greater (damaging earthquake shaking) is 5–12 percent per year in north-central Oklahoma and southern Kansas, similar to the chance of damage caused by natural earthquakes

An earthquake rate forecast for Europe based on smoothed seismicity and smoothed fault contribution

NASA Astrophysics Data System (ADS)

Hiemer, Stefan; Woessner, Jochen; Basili, Roberto; Wiemer, Stefan

2013-04-01

The main objective of project SHARE (Seismic Hazard Harmonization in Europe) is to develop a community-based seismic hazard model for the Euro-Mediterranean region. The logic tree of earthquake rupture forecasts comprises several methodologies including smoothed seismicity approaches. Smoothed seismicity thus represents an alternative concept to express the degree of spatial stationarity of seismicity and provides results that are more objective, reproducible, and testable. Nonetheless, the smoothed-seismicity approach suffers from the common drawback of being generally based on earthquake catalogs alone, i.e. the wealth of knowledge from geology is completely ignored. We present a model that applies the kernel-smoothing method to both past earthquake locations and slip rates on mapped crustal faults and subductions. The result is mainly driven by the data, being independent of subjective delineation of seismic source zones. The core parts of our model are two distinct location probability densities: The first is computed by smoothing past seismicity (using variable kernel smoothing to account for varying data density). The second is obtained by smoothing fault moment rate contributions. The fault moment rates are calculated by summing the moment rate of each fault patch on a fully parameterized and discretized fault as available from the SHARE fault database. We assume that the regional frequency-magnitude distribution of the entire study area is well known and estimate the a- and b-value of a truncated Gutenberg-Richter magnitude distribution based on a maximum likelihood approach that considers the spatial and temporal completeness history of the seismic catalog. The two location probability densities are linearly weighted as a function of magnitude assuming that (1) the occurrence of past seismicity is a good proxy to forecast occurrence of future seismicity and (2) future large-magnitude events occur more likely in the vicinity of known faults. Consequently

Discussion of New Approaches to Medium-Short-Term Earthquake Forecast in Practice of The Earthquake Prediction in Yunnan

NASA Astrophysics Data System (ADS)

Hong, F.

2017-12-01

After retrospection of years of practice of the earthquake prediction in Yunnan area, it is widely considered that the fixed-point earthquake precursory anomalies mainly reflect the field information. The increase of amplitude and number of precursory anomalies could help to determine the original time of earthquakes, however it is difficult to obtain the spatial relevance between earthquakes and precursory anomalies, thus we can hardly predict the spatial locations of earthquakes using precursory anomalies. The past practices have shown that the seismic activities are superior to the precursory anomalies in predicting earthquakes locations, resulting from the increased seismicity were observed before 80% M=6.0 earthquakes in Yunnan area. While the mobile geomagnetic anomalies are turned out to be helpful in predicting earthquakes locations in recent year, for instance, the forecasted earthquakes occurring time and area derived form the 1-year-scale geomagnetic anomalies before the M6.5 Ludian earthquake in 2014 are shorter and smaller than which derived from the seismicity enhancement region. According to the past works, the author believes that the medium-short-term earthquake forecast level, as well as objective understanding of the seismogenic mechanisms, could be substantially improved by the densely laying observation array and capturing the dynamic process of physical property changes in the enhancement region of medium to small earthquakes.

Future WGCEP Models and the Need for Earthquake Simulators

NASA Astrophysics Data System (ADS)

Field, E. H.

2008-12-01

The 2008 Working Group on California Earthquake Probabilities (WGCEP) recently released the Uniform California Earthquake Rupture Forecast version 2 (UCERF 2), developed jointly by the USGS, CGS, and SCEC with significant support from the California Earthquake Authority. Although this model embodies several significant improvements over previous WGCEPs, the following are some of the significant shortcomings that we hope to resolve in a future UCERF3: 1) assumptions of fault segmentation and the lack of fault-to-fault ruptures; 2) the lack of an internally consistent methodology for computing time-dependent, elastic-rebound-motivated renewal probabilities; 3) the lack of earthquake clustering/triggering effects; and 4) unwarranted model complexity. It is believed by some that physics-based earthquake simulators will be key to resolving these issues, either as exploratory tools to help guide the present statistical approaches, or as a means to forecast earthquakes directly (although significant challenges remain with respect to the latter).

Earthquake and tsunami forecasts: Relation of slow slip events to subsequent earthquake rupture

PubMed Central

Dixon, Timothy H.; Jiang, Yan; Malservisi, Rocco; McCaffrey, Robert; Voss, Nicholas; Protti, Marino; Gonzalez, Victor

2014-01-01

The 5 September 2012 Mw 7.6 earthquake on the Costa Rica subduction plate boundary followed a 62-y interseismic period. High-precision GPS recorded numerous slow slip events (SSEs) in the decade leading up to the earthquake, both up-dip and down-dip of seismic rupture. Deeper SSEs were larger than shallower ones and, if characteristic of the interseismic period, release most locking down-dip of the earthquake, limiting down-dip rupture and earthquake magnitude. Shallower SSEs were smaller, accounting for some but not all interseismic locking. One SSE occurred several months before the earthquake, but changes in Mohr–Coulomb failure stress were probably too small to trigger the earthquake. Because many SSEs have occurred without subsequent rupture, their individual predictive value is limited, but taken together they released a significant amount of accumulated interseismic strain before the earthquake, effectively defining the area of subsequent seismic rupture (rupture did not occur where slow slip was common). Because earthquake magnitude depends on rupture area, this has important implications for earthquake hazard assessment. Specifically, if this behavior is representative of future earthquake cycles and other subduction zones, it implies that monitoring SSEs, including shallow up-dip events that lie offshore, could lead to accurate forecasts of earthquake magnitude and tsunami potential. PMID:25404327

Earthquake and tsunami forecasts: relation of slow slip events to subsequent earthquake rupture.

PubMed

Dixon, Timothy H; Jiang, Yan; Malservisi, Rocco; McCaffrey, Robert; Voss, Nicholas; Protti, Marino; Gonzalez, Victor

2014-12-02

The 5 September 2012 M(w) 7.6 earthquake on the Costa Rica subduction plate boundary followed a 62-y interseismic period. High-precision GPS recorded numerous slow slip events (SSEs) in the decade leading up to the earthquake, both up-dip and down-dip of seismic rupture. Deeper SSEs were larger than shallower ones and, if characteristic of the interseismic period, release most locking down-dip of the earthquake, limiting down-dip rupture and earthquake magnitude. Shallower SSEs were smaller, accounting for some but not all interseismic locking. One SSE occurred several months before the earthquake, but changes in Mohr-Coulomb failure stress were probably too small to trigger the earthquake. Because many SSEs have occurred without subsequent rupture, their individual predictive value is limited, but taken together they released a significant amount of accumulated interseismic strain before the earthquake, effectively defining the area of subsequent seismic rupture (rupture did not occur where slow slip was common). Because earthquake magnitude depends on rupture area, this has important implications for earthquake hazard assessment. Specifically, if this behavior is representative of future earthquake cycles and other subduction zones, it implies that monitoring SSEs, including shallow up-dip events that lie offshore, could lead to accurate forecasts of earthquake magnitude and tsunami potential.

The Virtual Quake earthquake simulator: a simulation-based forecast of the El Mayor-Cucapah region and evidence of predictability in simulated earthquake sequences

NASA Astrophysics Data System (ADS)

Yoder, Mark R.; Schultz, Kasey W.; Heien, Eric M.; Rundle, John B.; Turcotte, Donald L.; Parker, Jay W.; Donnellan, Andrea

2015-12-01

In this manuscript, we introduce a framework for developing earthquake forecasts using Virtual Quake (VQ), the generalized successor to the perhaps better known Virtual California (VC) earthquake simulator. We discuss the basic merits and mechanics of the simulator, and we present several statistics of interest for earthquake forecasting. We also show that, though the system as a whole (in aggregate) behaves quite randomly, (simulated) earthquake sequences limited to specific fault sections exhibit measurable predictability in the form of increasing seismicity precursory to large m > 7 earthquakes. In order to quantify this, we develop an alert-based forecasting metric, and show that it exhibits significant information gain compared to random forecasts. We also discuss the long-standing question of activation versus quiescent type earthquake triggering. We show that VQ exhibits both behaviours separately for independent fault sections; some fault sections exhibit activation type triggering, while others are better characterized by quiescent type triggering. We discuss these aspects of VQ specifically with respect to faults in the Salton Basin and near the El Mayor-Cucapah region in southern California, USA and northern Baja California Norte, Mexico.

Uniform California earthquake rupture forecast, version 3 (UCERF3): the time-independent model

USGS Publications Warehouse

Field, Edward H.; Biasi, Glenn P.; Bird, Peter; Dawson, Timothy E.; Felzer, Karen R.; Jackson, David D.; Johnson, Kaj M.; Jordan, Thomas H.; Madden, Christopher; Michael, Andrew J.; Milner, Kevin R.; Page, Morgan T.; Parsons, Thomas; Powers, Peter M.; Shaw, Bruce E.; Thatcher, Wayne R.; Weldon, Ray J.; Zeng, Yuehua; ,

2013-01-01

In this report we present the time-independent component of the Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3), which provides authoritative estimates of the magnitude, location, and time-averaged frequency of potentially damaging earthquakes in California. The primary achievements have been to relax fault segmentation assumptions and to include multifault ruptures, both limitations of the previous model (UCERF2). The rates of all earthquakes are solved for simultaneously, and from a broader range of data, using a system-level "grand inversion" that is both conceptually simple and extensible. The inverse problem is large and underdetermined, so a range of models is sampled using an efficient simulated annealing algorithm. The approach is more derivative than prescriptive (for example, magnitude-frequency distributions are no longer assumed), so new analysis tools were developed for exploring solutions. Epistemic uncertainties were also accounted for using 1,440 alternative logic tree branches, necessitating access to supercomputers. The most influential uncertainties include alternative deformation models (fault slip rates), a new smoothed seismicity algorithm, alternative values for the total rate of M≥5 events, and different scaling relationships, virtually all of which are new. As a notable first, three deformation models are based on kinematically consistent inversions of geodetic and geologic data, also providing slip-rate constraints on faults previously excluded because of lack of geologic data. The grand inversion constitutes a system-level framework for testing hypotheses and balancing the influence of different experts. For example, we demonstrate serious challenges with the Gutenberg-Richter hypothesis for individual faults. UCERF3 is still an approximation of the system, however, and the range of models is limited (for example, constrained to stay close to UCERF2). Nevertheless, UCERF3 removes the apparent UCERF2 overprediction of

Multicomponent ensemble models to forecast induced seismicity

NASA Astrophysics Data System (ADS)

Király-Proag, E.; Gischig, V.; Zechar, J. D.; Wiemer, S.

2018-01-01

In recent years, human-induced seismicity has become a more and more relevant topic due to its economic and social implications. Several models and approaches have been developed to explain underlying physical processes or forecast induced seismicity. They range from simple statistical models to coupled numerical models incorporating complex physics. We advocate the need for forecast testing as currently the best method for ascertaining if models are capable to reasonably accounting for key physical governing processes—or not. Moreover, operational forecast models are of great interest to help on-site decision-making in projects entailing induced earthquakes. We previously introduced a standardized framework following the guidelines of the Collaboratory for the Study of Earthquake Predictability, the Induced Seismicity Test Bench, to test, validate, and rank induced seismicity models. In this study, we describe how to construct multicomponent ensemble models based on Bayesian weightings that deliver more accurate forecasts than individual models in the case of Basel 2006 and Soultz-sous-Forêts 2004 enhanced geothermal stimulation projects. For this, we examine five calibrated variants of two significantly different model groups: (1) Shapiro and Smoothed Seismicity based on the seismogenic index, simple modified Omori-law-type seismicity decay, and temporally weighted smoothed seismicity; (2) Hydraulics and Seismicity based on numerically modelled pore pressure evolution that triggers seismicity using the Mohr-Coulomb failure criterion. We also demonstrate how the individual and ensemble models would perform as part of an operational Adaptive Traffic Light System. Investigating seismicity forecasts based on a range of potential injection scenarios, we use forecast periods of different durations to compute the occurrence probabilities of seismic events M ≥ 3. We show that in the case of the Basel 2006 geothermal stimulation the models forecast hazardous levels

Operational Earthquake Forecasting and Earthquake Early Warning: The Challenges of Introducing Scientific Innovations for Public Safety

NASA Astrophysics Data System (ADS)

Goltz, J. D.

2016-12-01

Although variants of both earthquake early warning and short-term operational earthquake forecasting systems have been implemented or are now being implemented in some regions and nations, they have been slow to gain acceptance within the disciplines that produced them as well as among those for whom they were intended to assist. To accelerate the development and implementation of these technologies will require the cooperation and collaboration of multiple disciplines, some inside and others outside of academia. Seismologists, social scientists, emergency managers, elected officials and key opinion leaders from the media and public must be the participants in this process. Representatives of these groups come from both inside and outside of academia and represent very different organizational cultures, backgrounds and expectations for these systems, sometimes leading to serious disagreements and impediments to further development and implementation. This presentation will focus on examples of the emergence of earthquake early warning and operational earthquake forecasting systems in California, Japan and other regions and document the challenges confronted in the ongoing effort to improve seismic safety.

Testing hypotheses of earthquake occurrence

NASA Astrophysics Data System (ADS)

Kagan, Y. Y.; Jackson, D. D.; Schorlemmer, D.; Gerstenberger, M.

2003-12-01

We present a relatively straightforward likelihood method for testing those earthquake hypotheses that can be stated as vectors of earthquake rate density in defined bins of area, magnitude, and time. We illustrate the method as it will be applied to the Regional Earthquake Likelihood Models (RELM) project of the Southern California Earthquake Center (SCEC). Several earthquake forecast models are being developed as part of this project, and additional contributed forecasts are welcome. Various models are based on fault geometry and slip rates, seismicity, geodetic strain, and stress interactions. We would test models in pairs, requiring that both forecasts in a pair be defined over the same set of bins. Thus we offer a standard "menu" of bins and ground rules to encourage standardization. One menu category includes five-year forecasts of magnitude 5.0 and larger. Forecasts would be in the form of a vector of yearly earthquake rates on a 0.05 degree grid at the beginning of the test. Focal mechanism forecasts, when available, would be also be archived and used in the tests. The five-year forecast category may be appropriate for testing hypotheses of stress shadows from large earthquakes. Interim progress will be evaluated yearly, but final conclusions would be made on the basis of cumulative five-year performance. The second category includes forecasts of earthquakes above magnitude 4.0 on a 0.05 degree grid, evaluated and renewed daily. Final evaluation would be based on cumulative performance over five years. Other types of forecasts with different magnitude, space, and time sampling are welcome and will be tested against other models with shared characteristics. All earthquakes would be counted, and no attempt made to separate foreshocks, main shocks, and aftershocks. Earthquakes would be considered as point sources located at the hypocenter. For each pair of forecasts, we plan to compute alpha, the probability that the first would be wrongly rejected in favor of

A smoothed stochastic earthquake rate model considering seismicity and fault moment release for Europe

NASA Astrophysics Data System (ADS)

Hiemer, S.; Woessner, J.; Basili, R.; Danciu, L.; Giardini, D.; Wiemer, S.

2014-08-01

We present a time-independent gridded earthquake rate forecast for the European region including Turkey. The spatial component of our model is based on kernel density estimation techniques, which we applied to both past earthquake locations and fault moment release on mapped crustal faults and subduction zone interfaces with assigned slip rates. Our forecast relies on the assumption that the locations of past seismicity is a good guide to future seismicity, and that future large-magnitude events occur more likely in the vicinity of known faults. We show that the optimal weighted sum of the corresponding two spatial densities depends on the magnitude range considered. The kernel bandwidths and density weighting function are optimized using retrospective likelihood-based forecast experiments. We computed earthquake activity rates (a- and b-value) of the truncated Gutenberg-Richter distribution separately for crustal and subduction seismicity based on a maximum likelihood approach that considers the spatial and temporal completeness history of the catalogue. The final annual rate of our forecast is purely driven by the maximum likelihood fit of activity rates to the catalogue data, whereas its spatial component incorporates contributions from both earthquake and fault moment-rate densities. Our model constitutes one branch of the earthquake source model logic tree of the 2013 European seismic hazard model released by the EU-FP7 project `Seismic HAzard haRmonization in Europe' (SHARE) and contributes to the assessment of epistemic uncertainties in earthquake activity rates. We performed retrospective and pseudo-prospective likelihood consistency tests to underline the reliability of our model and SHARE's area source model (ASM) using the testing algorithms applied in the collaboratory for the study of earthquake predictability (CSEP). We comparatively tested our model's forecasting skill against the ASM and find a statistically significant better performance for

Japanese earthquake predictability experiment with multiple runs before and after the 2011 Tohoku-oki earthquake

NASA Astrophysics Data System (ADS)

Hirata, N.; Tsuruoka, H.; Yokoi, S.

2011-12-01

The current Japanese national earthquake prediction program emphasizes the importance of modeling as well as monitoring for a sound scientific development of earthquake prediction research. One major focus of the current program is to move toward creating testable earthquake forecast models. For this purpose, in 2009 we joined the Collaboratory for the Study of Earthquake Predictability (CSEP) and installed, through an international collaboration, the CSEP Testing Centre, an infrastructure to encourage researchers to develop testable models for Japan. We started Japanese earthquake predictability experiment on November 1, 2009. The experiment consists of 12 categories, with 4 testing classes with different time spans (1 day, 3 months, 1 year and 3 years) and 3 testing regions called 'All Japan,' 'Mainland,' and 'Kanto.' A total of 160 models, as of August 2013, were submitted, and are currently under the CSEP official suite of tests for evaluating the performance of forecasts. We will present results of prospective forecast and testing for periods before and after the 2011 Tohoku-oki earthquake. Because a seismic activity has changed dramatically since the 2011 event, performances of models have been affected very much. In addition, as there is the problem of authorized catalogue related to the completeness magnitude, most models did not pass the CSEP consistency tests. Also, we will discuss the retrospective earthquake forecast experiments for aftershocks of the 2011 Tohoku-oki earthquake. Our aim is to describe what has turned out to be the first occasion for setting up a research environment for rigorous earthquake forecasting in Japan.

Japanese earthquake predictability experiment with multiple runs before and after the 2011 Tohoku-oki earthquake

NASA Astrophysics Data System (ADS)

Hirata, N.; Tsuruoka, H.; Yokoi, S.

2013-12-01

The current Japanese national earthquake prediction program emphasizes the importance of modeling as well as monitoring for a sound scientific development of earthquake prediction research. One major focus of the current program is to move toward creating testable earthquake forecast models. For this purpose, in 2009 we joined the Collaboratory for the Study of Earthquake Predictability (CSEP) and installed, through an international collaboration, the CSEP Testing Centre, an infrastructure to encourage researchers to develop testable models for Japan. We started Japanese earthquake predictability experiment on November 1, 2009. The experiment consists of 12 categories, with 4 testing classes with different time spans (1 day, 3 months, 1 year and 3 years) and 3 testing regions called 'All Japan,' 'Mainland,' and 'Kanto.' A total of 160 models, as of August 2013, were submitted, and are currently under the CSEP official suite of tests for evaluating the performance of forecasts. We will present results of prospective forecast and testing for periods before and after the 2011 Tohoku-oki earthquake. Because a seismic activity has changed dramatically since the 2011 event, performances of models have been affected very much. In addition, as there is the problem of authorized catalogue related to the completeness magnitude, most models did not pass the CSEP consistency tests. Also, we will discuss the retrospective earthquake forecast experiments for aftershocks of the 2011 Tohoku-oki earthquake. Our aim is to describe what has turned out to be the first occasion for setting up a research environment for rigorous earthquake forecasting in Japan.

Modeling fast and slow earthquakes at various scales

PubMed Central

IDE, Satoshi

2014-01-01

Earthquake sources represent dynamic rupture within rocky materials at depth and often can be modeled as propagating shear slip controlled by friction laws. These laws provide boundary conditions on fault planes embedded in elastic media. Recent developments in observation networks, laboratory experiments, and methods of data analysis have expanded our knowledge of the physics of earthquakes. Newly discovered slow earthquakes are qualitatively different phenomena from ordinary fast earthquakes and provide independent information on slow deformation at depth. Many numerical simulations have been carried out to model both fast and slow earthquakes, but problems remain, especially with scaling laws. Some mechanisms are required to explain the power-law nature of earthquake rupture and the lack of characteristic length. Conceptual models that include a hierarchical structure over a wide range of scales would be helpful for characterizing diverse behavior in different seismic regions and for improving probabilistic forecasts of earthquakes. PMID:25311138

Modeling fast and slow earthquakes at various scales.

PubMed

Ide, Satoshi

2014-01-01

Earthquake sources represent dynamic rupture within rocky materials at depth and often can be modeled as propagating shear slip controlled by friction laws. These laws provide boundary conditions on fault planes embedded in elastic media. Recent developments in observation networks, laboratory experiments, and methods of data analysis have expanded our knowledge of the physics of earthquakes. Newly discovered slow earthquakes are qualitatively different phenomena from ordinary fast earthquakes and provide independent information on slow deformation at depth. Many numerical simulations have been carried out to model both fast and slow earthquakes, but problems remain, especially with scaling laws. Some mechanisms are required to explain the power-law nature of earthquake rupture and the lack of characteristic length. Conceptual models that include a hierarchical structure over a wide range of scales would be helpful for characterizing diverse behavior in different seismic regions and for improving probabilistic forecasts of earthquakes.

Data sensitivity in a hybrid STEP/Coulomb model for aftershock forecasting

NASA Astrophysics Data System (ADS)

Steacy, S.; Jimenez Lloret, A.; Gerstenberger, M.

2014-12-01

Operational earthquake forecasting is rapidly becoming a 'hot topic' as civil protection authorities seek quantitative information on likely near future earthquake distributions during seismic crises. At present, most of the models in public domain are statistical and use information about past and present seismicity as well as b-value and Omori's law to forecast future rates. A limited number of researchers, however, are developing hybrid models which add spatial constraints from Coulomb stress modeling to existing statistical approaches. Steacy et al. (2013), for instance, recently tested a model that combines Coulomb stress patterns with the STEP (short-term earthquake probability) approach against seismicity observed during the 2010-2012 Canterbury earthquake sequence. They found that the new model performed at least as well as, and often better than, STEP when tested against retrospective data but that STEP was generally better in pseudo-prospective tests that involved data actually available within the first 10 days of each event of interest. They suggested that the major reason for this discrepancy was uncertainty in the slip models and, in particular, in the geometries of the faults involved in each complex major event. Here we test this hypothesis by developing a number of retrospective forecasts for the Landers earthquake using hypothetical slip distributions developed by Steacy et al. (2004) to investigate the sensitivity of Coulomb stress models to fault geometry and earthquake slip, and we also examine how the choice of receiver plane geometry affects the results. We find that the results are strongly sensitive to the slip models and moderately sensitive to the choice of receiver orientation. We further find that comparison of the stress fields (resulting from the slip models) with the location of events in the learning period provides advance information on whether or not a particular hybrid model will perform better than STEP.

A long-term earthquake rate model for the central and eastern United States from smoothed seismicity

USGS Publications Warehouse

Moschetti, Morgan P.

2015-01-01

I present a long-term earthquake rate model for the central and eastern United States from adaptive smoothed seismicity. By employing pseudoprospective likelihood testing (L-test), I examined the effects of fixed and adaptive smoothing methods and the effects of catalog duration and composition on the ability of the models to forecast the spatial distribution of recent earthquakes. To stabilize the adaptive smoothing method for regions of low seismicity, I introduced minor modifications to the way that the adaptive smoothing distances are calculated. Across all smoothed seismicity models, the use of adaptive smoothing and the use of earthquakes from the recent part of the catalog optimizes the likelihood for tests with M≥2.7 and M≥4.0 earthquake catalogs. The smoothed seismicity models optimized by likelihood testing with M≥2.7 catalogs also produce the highest likelihood values for M≥4.0 likelihood testing, thus substantiating the hypothesis that the locations of moderate-size earthquakes can be forecast by the locations of smaller earthquakes. The likelihood test does not, however, maximize the fraction of earthquakes that are better forecast than a seismicity rate model with uniform rates in all cells. In this regard, fixed smoothing models perform better than adaptive smoothing models. The preferred model of this study is the adaptive smoothed seismicity model, based on its ability to maximize the joint likelihood of predicting the locations of recent small-to-moderate-size earthquakes across eastern North America. The preferred rate model delineates 12 regions where the annual rate of M≥5 earthquakes exceeds 2×10−3. Although these seismic regions have been previously recognized, the preferred forecasts are more spatially concentrated than the rates from fixed smoothed seismicity models, with rate increases of up to a factor of 10 near clusters of high seismic activity.

Scientific and non-scientific challenges for Operational Earthquake Forecasting

NASA Astrophysics Data System (ADS)

Marzocchi, W.

2015-12-01

Tracking the time evolution of seismic hazard in time windows shorter than the usual 50-years of long-term hazard models may offer additional opportunities to reduce the seismic risk. This is the target of operational earthquake forecasting (OEF). During the OEF development in Italy we identify several challenges that range from pure science to the more practical interface of science with society. From a scientific point of view, although earthquake clustering is the clearest empirical evidence about earthquake occurrence, and OEF clustering models are the most (successfully) tested hazard models in seismology, we note that some seismologists are still reluctant to accept their scientific reliability. After exploring the motivations of these scientific doubts, we also look into an issue that is often overlooked in this discussion, i.e., in any kind of hazard analysis, we do not use a model because it is the true one, but because it is the better than anything else we can think of. The non-scientific aspects are mostly related to the fact that OEF usually provides weekly probabilities of large eartquakes smaller than 1%. These probabilities are considered by some seismologists too small to be of interest or useful. However, in a recent collaboration with engineers we show that such earthquake probabilities may lead to intolerable individual risk of death. Interestingly, this debate calls for a better definition of the still fuzzy boundaries among the different expertise required for the whole risk mitigation process. The last and probably more pressing challenge is related to the communication to the public. In fact, a wrong message could be useless or even counterproductive. Here we show some progresses that we have made in this field working with communication experts in Italy.

Numerical Modeling and Forecasting of Strong Sumatra Earthquakes

NASA Astrophysics Data System (ADS)

Xing, H. L.; Yin, C.

2007-12-01

ESyS-Crustal, a finite element based computational model and software has been developed and applied to simulate the complex nonlinear interacting fault systems with the goal to accurately predict earthquakes and tsunami generation. With the available tectonic setting and GPS data around the Sumatra region, the simulation results using the developed software have clearly indicated that the shallow part of the subduction zone in the Sumatra region between latitude 6S and 2N has been locked for a long time, and remained locked even after the Northern part of the zone underwent a major slip event resulting into the infamous Boxing Day tsunami. Two strong earthquakes that occurred in the distant past in this region (between 6S and 1S) in 1797 (M8.2) and 1833 (M9.0) respectively are indicative of the high potential for very large destructive earthquakes to occur in this region with relatively long periods of quiescence in between. The results have been presented in the 5th ACES International Workshop in 2006 before the recent 2007 Sumatra earthquakes occurred which exactly fell into the predicted zone (see the following web site for ACES2006 and detailed presentation file through workshop agenda). The preliminary simulation results obtained so far have shown that there seem to be a few obvious events around the previously locked zone before it is totally ruptured, but apparently no indication of a giant earthquake similar to the 2004 M9 event in the near future which is believed to happen by several earthquake scientists. Further detailed simulations will be carried out and presented in the meeting.

Comparing Foreshock Characteristics and Foreshock Forecasting in Observed and Simulated Earthquake Catalogs

NASA Astrophysics Data System (ADS)

Ogata, Y.

2014-12-01

In our previous papers (Ogata et al., 1995, 1996, 2012; GJI), we characterized foreshock activity in Japan, and then presented a model that forecasts the probability that one or more earthquakes form a foreshock sequence; then we tested prospectively foreshock probabilities in the JMA catalog. In this talk, I compare the empirical results with results for synthetic catalogs in order to clarify whether or not these results are consistent with the description of the seismicity by a superposition of background activity and epidemic-type aftershock sequences (ETAS models). This question is important, because it is still controversially discussed whether the nucleation process of large earthquakes is driven by seismically cascading (ETAS-type) or by aseismic accelerating processes. To explore the foreshock characteristics, I firstly applied the same clustering algorithms to real and synthetic catalogs and analyzed the temporal, spatial and magnitude distributions of the selected foreshocks, to find significant differences particularly in the temporal acceleration and magnitude dependence. Finally, I calculated forecast scores based on a single-link cluster algorithm which could be appropriate for real-time applications. I find that the JMA catalog yields higher scores than all synthetic catalogs and that the ETAS models having the same magnitude sequence as the original catalog performs significantly better (more close to the reality) than ETAS-models with randomly picked magnitudes.

Aftershock Forecasting: Recent Developments and Lessons from the 2016 M5.8 Pawnee, Oklahoma, Earthquake

NASA Astrophysics Data System (ADS)

Michael, A. J.; Field, E. H.; Hardebeck, J.; Llenos, A. L.; Milner, K. R.; Page, M. T.; Perry, S. C.; van der Elst, N.; Wein, A. M.

2016-12-01

After the Mw 5.8 Pawnee, Oklahoma, earthquake of September 3, 2016 the USGS issued a series of aftershock forecasts for the next month and year. These forecasts were aimed at the emergency response community, those making decisions about well operations in the affected region, and the general public. The forecasts were generated manually using methods planned for automatically released Operational Aftershock Forecasts. The underlying method is from Reasenberg and Jones (Science, 1989) with improvements recently published in Page et al. (BSSA, 2016), implemented in a JAVA Graphical User Interface and presented in a template that is under development. The methodological improvements include initial models based on the tectonic regime as defined by Garcia et al. (BSSA, 2012) and the inclusion of both uncertainty in the clustering parameters and natural random variability. We did not utilize the time-dependent magnitude of completeness model from Page et al. because it applies only to teleseismic events recorded by NEIC. The parameters for Garcia's Generic Active Continental Region underestimated the modified-Omori decay parameter and underestimated the aftershock rate by a factor of 2. And the sequence following the Mw 5.7 Prague, Oklahoma, earthquake of November 6, 2011 was about 3 to 4 times more productive than the Pawnee sequence. The high productivity for these potentially induced sequences is consistent with an increase in productivity in Oklahoma since 2009 (Llenos and Michael, BSSA, 2013) and makes a general tectonic model inapplicable to sequences in this region. Soon after the mainshock occurred, the forecasts relied on the sequence specific parameters. After one month, the Omori decay parameter p is less than one, implying a very long-lived sequence. However, the decay parameter is known to be biased low at early times due to secondary aftershock triggering, and the p-value determined early in the sequence may be inaccurate for long-term forecasting.

The potential uses of operational earthquake forecasting

USGS Publications Warehouse

Field, Edward; Jordan, Thomas; Jones, Lucille M.; Michael, Andrew; Blanpied, Michael L.

2016-01-01

This article reports on a workshop held to explore the potential uses of operational earthquake forecasting (OEF). We discuss the current status of OEF in the United States and elsewhere, the types of products that could be generated, the various potential users and uses of OEF, and the need for carefully crafted communication protocols. Although operationalization challenges remain, there was clear consensus among the stakeholders at the workshop that OEF could be useful.

Regional Earthquake Likelihood Models: A realm on shaky grounds?

NASA Astrophysics Data System (ADS)

Kossobokov, V.

2005-12-01

Seismology is juvenile and its appropriate statistical tools to-date may have a "medievil flavor" for those who hurry up to apply a fuzzy language of a highly developed probability theory. To become "quantitatively probabilistic" earthquake forecasts/predictions must be defined with a scientific accuracy. Following the most popular objectivists' viewpoint on probability, we cannot claim "probabilities" adequate without a long series of "yes/no" forecast/prediction outcomes. Without "antiquated binary language" of "yes/no" certainty we cannot judge an outcome ("success/failure"), and, therefore, quantify objectively a forecast/prediction method performance. Likelihood scoring is one of the delicate tools of Statistics, which could be worthless or even misleading when inappropriate probability models are used. This is a basic loophole for a misuse of likelihood as well as other statistical methods on practice. The flaw could be avoided by an accurate verification of generic probability models on the empirical data. It is not an easy task in the frames of the Regional Earthquake Likelihood Models (RELM) methodology, which neither defines the forecast precision nor allows a means to judge the ultimate success or failure in specific cases. Hopefully, the RELM group realizes the problem and its members do their best to close the hole with an adequate, data supported choice. Regretfully, this is not the case with the erroneous choice of Gerstenberger et al., who started the public web site with forecasts of expected ground shaking for `tomorrow' (Nature 435, 19 May 2005). Gerstenberger et al. have inverted the critical evidence of their study, i.e., the 15 years of recent seismic record accumulated just in one figure, which suggests rejecting with confidence above 97% "the generic California clustering model" used in automatic calculations. As a result, since the date of publication in Nature the United States Geological Survey website delivers to the public, emergency

Time‐dependent renewal‐model probabilities when date of last earthquake is unknown

USGS Publications Warehouse

Field, Edward H.; Jordan, Thomas H.

2015-01-01

We derive time-dependent, renewal-model earthquake probabilities for the case in which the date of the last event is completely unknown, and compare these with the time-independent Poisson probabilities that are customarily used as an approximation in this situation. For typical parameter values, the renewal-model probabilities exceed Poisson results by more than 10% when the forecast duration exceeds ~20% of the mean recurrence interval. We also derive probabilities for the case in which the last event is further constrained to have occurred before historical record keeping began (the historic open interval), which can only serve to increase earthquake probabilities for typically applied renewal models.We conclude that accounting for the historic open interval can improve long-term earthquake rupture forecasts for California and elsewhere.

Risk Management in Earthquakes, Financial Markets, and the Game of 21: The role of Forecasting, Nowcasting, and Timecasting

NASA Astrophysics Data System (ADS)

Rundle, J. B.

2017-12-01

Earthquakes and financial markets share surprising similarities [1]. For example, the well-known VIX index, which by definition is the implied volatility of the Standard and Poors 500 index, behaves in very similar quantitative fashion to time series for earthquake rates. Both display sudden increases at the time of an earthquake or an announcement of the US Federal Reserve Open Market Committee [2], and both decay as an inverse power of time. Both can be regarded as examples of first order phase transitions [1], and display fractal and scaling behavior associated with critical transitions, such as power-law magnitude-frequency relations in the tails of the distributions. Early quantitative investors such as Edward Thorpe and John Kelly invented novel methods to mitigate or manage risk in games of chance such as blackjack, and in markets using hedging techniques that are still in widespread use today. The basic idea is the concept of proportional betting, where the gambler/investor bets a fraction of the bankroll whose size is determined by the "edge" or inside knowledge of the real (and changing) odds. For earthquake systems, the "edge" over nature can only exist in the form of a forecast (probability of a future earthquake); a nowcast (knowledge of the current state of an earthquake fault system); or a timecast (statistical estimate of the waiting time until the next major earthquake). In our terminology, a forecast is a model, while the nowcast and timecast are analysis methods using observed data only (no model). We also focus on defined geographic areas rather than on faults, thereby eliminating the need to consider specific fault data or fault interactions. Data used are online earthquake catalogs, generally since 1980. Forecasts are based on the Weibull (1952) probability law, and only a handful of parameters are needed. These methods allow the development of real time hazard and risk estimation using cloud-based technologies, and permit the application of

Physics-based and statistical earthquake forecasting in a continental rift zone: the case study of Corinth Gulf (Greece)

NASA Astrophysics Data System (ADS)

Segou, Margarita

2016-01-01

I perform a retrospective forecast experiment in the most rapid extensive continental rift worldwide, the western Corinth Gulf (wCG, Greece), aiming to predict shallow seismicity (depth <15 km) with magnitude M ≥ 3.0 for the time period between 1995 and 2013. I compare two short-term earthquake clustering models, based on epidemic-type aftershock sequence (ETAS) statistics, four physics-based (CRS) models, combining static stress change estimations and the rate-and-state laboratory law and one hybrid model. For the latter models, I incorporate the stress changes imparted from 31 earthquakes with magnitude M ≥ 4.5 at the extended area of wCG. Special attention is given on the 3-D representation of active faults, acting as potential receiver planes for the estimation of static stress changes. I use reference seismicity between 1990 and 1995, corresponding to the learning phase of physics-based models, and I evaluate the forecasts for six months following the 1995 M = 6.4 Aigio earthquake using log-likelihood performance metrics. For the ETAS realizations, I use seismic events with magnitude M ≥ 2.5 within daily update intervals to enhance their predictive power. For assessing the role of background seismicity, I implement a stochastic reconstruction (aka declustering) aiming to answer whether M > 4.5 earthquakes correspond to spontaneous events and identify, if possible, different triggering characteristics between aftershock sequences and swarm-type seismicity periods. I find that: (1) ETAS models outperform CRS models in most time intervals achieving very low rejection ratio RN = 6 per cent, when I test their efficiency to forecast the total number of events inside the study area, (2) the best rejection ratio for CRS models reaches RN = 17 per cent, when I use varying target depths and receiver plane geometry, (3) 75 per cent of the 1995 Aigio aftershocks that occurred within the first month can be explained by static stress changes, (4) highly variable

Recent Achievements of the Collaboratory for the Study of Earthquake Predictability

NASA Astrophysics Data System (ADS)

Jordan, T. H.; Liukis, M.; Werner, M. J.; Schorlemmer, D.; Yu, J.; Maechling, P. J.; Jackson, D. D.; Rhoades, D. A.; Zechar, J. D.; Marzocchi, W.

2016-12-01

The Collaboratory for the Study of Earthquake Predictability (CSEP) supports a global program to conduct prospective earthquake forecasting experiments. CSEP testing centers are now operational in California, New Zealand, Japan, China, and Europe with 442 models under evaluation. The California testing center, started by SCEC, Sept 1, 2007, currently hosts 30-minute, 1-day, 3-month, 1-year and 5-year forecasts, both alarm-based and probabilistic, for California, the Western Pacific, and worldwide. Our tests are now based on the hypocentral locations and magnitudes of cataloged earthquakes, but we plan to test focal mechanisms, seismic hazard models, ground motion forecasts, and finite rupture forecasts as well. We have increased computational efficiency for high-resolution global experiments, such as the evaluation of the Global Earthquake Activity Rate (GEAR) model, introduced Bayesian ensemble models, and implemented support for non-Poissonian simulation-based forecasts models. We are currently developing formats and procedures to evaluate externally hosted forecasts and predictions. CSEP supports the USGS program in operational earthquake forecasting and a DHS project to register and test external forecast procedures from experts outside seismology. We found that earthquakes as small as magnitude 2.5 provide important information on subsequent earthquakes larger than magnitude 5. A retrospective experiment for the 2010-2012 Canterbury earthquake sequence showed that some physics-based and hybrid models outperform catalog-based (e.g., ETAS) models. This experiment also demonstrates the ability of the CSEP infrastructure to support retrospective forecast testing. Current CSEP development activities include adoption of the Comprehensive Earthquake Catalog (ComCat) as an authorized data source, retrospective testing of simulation-based forecasts, and support for additive ensemble methods. We describe the open-source CSEP software that is available to researchers as

Statistical tests of simple earthquake cycle models

NASA Astrophysics Data System (ADS)

DeVries, Phoebe M. R.; Evans, Eileen L.

2016-12-01

A central goal of observing and modeling the earthquake cycle is to forecast when a particular fault may generate an earthquake: a fault late in its earthquake cycle may be more likely to generate an earthquake than a fault early in its earthquake cycle. Models that can explain geodetic observations throughout the entire earthquake cycle may be required to gain a more complete understanding of relevant physics and phenomenology. Previous efforts to develop unified earthquake models for strike-slip faults have largely focused on explaining both preseismic and postseismic geodetic observations available across a few faults in California, Turkey, and Tibet. An alternative approach leverages the global distribution of geodetic and geologic slip rate estimates on strike-slip faults worldwide. Here we use the Kolmogorov-Smirnov test for similarity of distributions to infer, in a statistically rigorous manner, viscoelastic earthquake cycle models that are inconsistent with 15 sets of observations across major strike-slip faults. We reject a large subset of two-layer models incorporating Burgers rheologies at a significance level of α = 0.05 (those with long-term Maxwell viscosities ηM < 4.0 × 1019 Pa s and ηM > 4.6 × 1020 Pa s) but cannot reject models on the basis of transient Kelvin viscosity ηK. Finally, we examine the implications of these results for the predicted earthquake cycle timing of the 15 faults considered and compare these predictions to the geologic and historical record.

Earthquake Potential Models for China

NASA Astrophysics Data System (ADS)

Rong, Y.; Jackson, D. D.

2002-12-01

We present three earthquake potential estimates for magnitude 5.4 and larger earthquakes for China. The potential is expressed as the rate density (probability per unit area, magnitude and time). The three methods employ smoothed seismicity-, geologic slip rate-, and geodetic strain rate data. We tested all three estimates, and the published Global Seismic Hazard Assessment Project (GSHAP) model, against earthquake data. We constructed a special earthquake catalog which combines previous catalogs covering different times. We used the special catalog to construct our smoothed seismicity model and to evaluate all models retrospectively. All our models employ a modified Gutenberg-Richter magnitude distribution with three parameters: a multiplicative ``a-value," the slope or ``b-value," and a ``corner magnitude" marking a strong decrease of earthquake rate with magnitude. We assumed the b-value to be constant for the whole study area and estimated the other parameters from regional or local geophysical data. The smoothed seismicity method assumes that the rate density is proportional to the magnitude of past earthquakes and approximately as the reciprocal of the epicentral distance out to a few hundred kilometers. We derived the upper magnitude limit from the special catalog and estimated local a-values from smoothed seismicity. Earthquakes since January 1, 2000 are quite compatible with the model. For the geologic forecast we adopted the seismic source zones (based on geological, geodetic and seismicity data) of the GSHAP model. For each zone, we estimated a corner magnitude by applying the Wells and Coppersmith [1994] relationship to the longest fault in the zone, and we determined the a-value from fault slip rates and an assumed locking depth. The geological model fits the earthquake data better than the GSHAP model. We also applied the Wells and Coppersmith relationship to individual faults, but the results conflicted with the earthquake record. For our geodetic

Prospective earthquake forecasts at the Himalayan Front after the 25 April 2015 M 7.8 Gorkha Mainshock

USGS Publications Warehouse

Segou, Margaret; Parsons, Thomas E.

2016-01-01

When a major earthquake strikes, the resulting devastation can be compounded or even exceeded by the subsequent cascade of triggered seismicity. As the Nepalese recover from the 25 April 2015 shock, knowledge of what comes next is essential. We calculate the redistribution of crustal stresses and implied earthquake probabilities for different periods, from daily to 30 years into the future. An initial forecast was completed before an M 7.3 earthquake struck on 12 May 2015 that enables a preliminary assessment; postforecast seismicity has so far occurred within a zone of fivefold probability gain. Evaluation of the forecast performance, using two months of seismic data, reveals that stress‐based approaches present improved skill in higher‐magnitude triggered seismicity. Our results suggest that considering the total stress field, rather than only the coseismic one, improves the spatial performance of the model based on the estimation of a wide range of potential triggered faults following a mainshock.

Combining Multiple Rupture Models in Real-Time for Earthquake Early Warning

NASA Astrophysics Data System (ADS)

Minson, S. E.; Wu, S.; Beck, J. L.; Heaton, T. H.

2015-12-01

The ShakeAlert earthquake early warning system for the west coast of the United States is designed to combine information from multiple independent earthquake analysis algorithms in order to provide the public with robust predictions of shaking intensity at each user's location before they are affected by strong shaking. The current contributing analyses come from algorithms that determine the origin time, epicenter, and magnitude of an earthquake (On-site, ElarmS, and Virtual Seismologist). A second generation of algorithms will provide seismic line source information (FinDer), as well as geodetically-constrained slip models (BEFORES, GPSlip, G-larmS, G-FAST). These new algorithms will provide more information about the spatial extent of the earthquake rupture and thus improve the quality of the resulting shaking forecasts.Each of the contributing algorithms exploits different features of the observed seismic and geodetic data, and thus each algorithm may perform differently for different data availability and earthquake source characteristics. Thus the ShakeAlert system requires a central mediator, called the Central Decision Module (CDM). The CDM acts to combine disparate earthquake source information into one unified shaking forecast. Here we will present a new design for the CDM that uses a Bayesian framework to combine earthquake reports from multiple analysis algorithms and compares them to observed shaking information in order to both assess the relative plausibility of each earthquake report and to create an improved unified shaking forecast complete with appropriate uncertainties. We will describe how these probabilistic shaking forecasts can be used to provide each user with a personalized decision-making tool that can help decide whether or not to take a protective action (such as opening fire house doors or stopping trains) based on that user's distance to the earthquake, vulnerability to shaking, false alarm tolerance, and time required to act.

Pattern Informatics Approach to Earthquake Forecasting in 3D

NASA Astrophysics Data System (ADS)

Toya, Y.; Tiampo, K. F.; Rundle, J. B.; Chen, C.; Li, H.; Klein, W.

2009-05-01

Natural seismicity is correlated across multiple spatial and temporal scales, but correlations in seismicity prior to a large earthquake are locally subtle (e.g. seismic quiescence) and often prominent in broad scale (e.g., seismic activation), resulting in local and regional seismicity patterns, e.g. a Mogi's donut. Recognizing that patterns in seismicity rate are reflecting the regional dynamics of the directly unobservable crustal stresses, the Pattern Informatics (PI) approach was introduced by Tiampo et al. in 2002 [Europhys. Lett., 60 (3), 481-487,] Rundle et al., 2002 [PNAS 99, suppl. 1, 2514-2521.] In this study, we expand the PI approach to forecasting earthquakes into the third, or vertical dimension, and illustrate its further improvement in the forecasting performance through case studies of both natural and synthetic data. The PI characterizes rapidly evolving spatio-temporal seismicity patterns as angular drifts of a unit state vector in a high dimensional correlation space, and systematically identifies anomalous shifts in seismic activity with respect to the regional background. 3D PI analysis is particularly advantageous over 2D analysis in resolving vertically overlapped seismicity anomalies in a highly complex tectonic environment. Case studies will help to illustrate some important properties of the PI forecasting tool. [Submitted to: Concurrency and Computation: Practice and Experience, Wiley, Special Issue: ACES2008.

Spatial Distribution of the Coefficient of Variation and Bayesian Forecast for the Paleo-Earthquakes in Japan

NASA Astrophysics Data System (ADS)

Nomura, Shunichi; Ogata, Yosihiko

2016-04-01

We propose a Bayesian method of probability forecasting for recurrent earthquakes of inland active faults in Japan. Renewal processes with the Brownian Passage Time (BPT) distribution are applied for over a half of active faults in Japan by the Headquarters for Earthquake Research Promotion (HERP) of Japan. Long-term forecast with the BPT distribution needs two parameters; the mean and coefficient of variation (COV) for recurrence intervals. The HERP applies a common COV parameter for all of these faults because most of them have very few specified paleoseismic events, which is not enough to estimate reliable COV values for respective faults. However, different COV estimates are proposed for the same paleoseismic catalog by some related works. It can make critical difference in forecast to apply different COV estimates and so COV should be carefully selected for individual faults. Recurrence intervals on a fault are, on the average, determined by the long-term slip rate caused by the tectonic motion but fluctuated by nearby seismicities which influence surrounding stress field. The COVs of recurrence intervals depend on such stress perturbation and so have spatial trends due to the heterogeneity of tectonic motion and seismicity. Thus we introduce a spatial structure on its COV parameter by Bayesian modeling with a Gaussian process prior. The COVs on active faults are correlated and take similar values for closely located faults. It is found that the spatial trends in the estimated COV values coincide with the density of active faults in Japan. We also show Bayesian forecasts by the proposed model using Markov chain Monte Carlo method. Our forecasts are different from HERP's forecast especially on the active faults where HERP's forecasts are very high or low.

Statistical tests of simple earthquake cycle models

USGS Publications Warehouse

Devries, Phoebe M. R.; Evans, Eileen

2016-01-01

A central goal of observing and modeling the earthquake cycle is to forecast when a particular fault may generate an earthquake: a fault late in its earthquake cycle may be more likely to generate an earthquake than a fault early in its earthquake cycle. Models that can explain geodetic observations throughout the entire earthquake cycle may be required to gain a more complete understanding of relevant physics and phenomenology. Previous efforts to develop unified earthquake models for strike-slip faults have largely focused on explaining both preseismic and postseismic geodetic observations available across a few faults in California, Turkey, and Tibet. An alternative approach leverages the global distribution of geodetic and geologic slip rate estimates on strike-slip faults worldwide. Here we use the Kolmogorov-Smirnov test for similarity of distributions to infer, in a statistically rigorous manner, viscoelastic earthquake cycle models that are inconsistent with 15 sets of observations across major strike-slip faults. We reject a large subset of two-layer models incorporating Burgers rheologies at a significance level of α = 0.05 (those with long-term Maxwell viscosities ηM <~ 4.0 × 1019 Pa s and ηM >~ 4.6 × 1020 Pa s) but cannot reject models on the basis of transient Kelvin viscosity ηK. Finally, we examine the implications of these results for the predicted earthquake cycle timing of the 15 faults considered and compare these predictions to the geologic and historical record.

Forecast model for great earthquakes at the Nankai Trough subduction zone

USGS Publications Warehouse

Stuart, W.D.

1988-01-01

An earthquake instability model is formulated for recurring great earthquakes at the Nankai Trough subduction zone in southwest Japan. The model is quasistatic, two-dimensional, and has a displacement and velocity dependent constitutive law applied at the fault plane. A constant rate of fault slip at depth represents forcing due to relative motion of the Philippine Sea and Eurasian plates. The model simulates fault slip and stress for all parts of repeated earthquake cycles, including post-, inter-, pre- and coseismic stages. Calculated ground uplift is in agreement with most of the main features of elevation changes observed before and after the M=8.1 1946 Nankaido earthquake. In model simulations, accelerating fault slip has two time-scales. The first time-scale is several years long and is interpreted as an intermediate-term precursor. The second time-scale is a few days long and is interpreted as a short-term precursor. Accelerating fault slip on both time-scales causes anomalous elevation changes of the ground surface over the fault plane of 100 mm or less within 50 km of the fault trace. ?? 1988 Birkha??user Verlag.

Earthquake Rate Models for Evolving Induced Seismicity Hazard in the Central and Eastern US

NASA Astrophysics Data System (ADS)

Llenos, A. L.; Ellsworth, W. L.; Michael, A. J.

2015-12-01

Injection-induced earthquake rates can vary rapidly in space and time, which presents significant challenges to traditional probabilistic seismic hazard assessment methodologies that are based on a time-independent model of mainshock occurrence. To help society cope with rapidly evolving seismicity, the USGS is developing one-year hazard models for areas of induced seismicity in the central and eastern US to forecast the shaking due to all earthquakes, including aftershocks which are generally omitted from hazards assessments (Petersen et al., 2015). However, the spatial and temporal variability of the earthquake rates make them difficult to forecast even on time-scales as short as one year. An initial approach is to use the previous year's seismicity rate to forecast the next year's seismicity rate. However, in places such as northern Oklahoma the rates vary so rapidly over time that a simple linear extrapolation does not accurately forecast the future, even when the variability in the rates is modeled with simulations based on an Epidemic-Type Aftershock Sequence (ETAS) model (Ogata, JASA, 1988) to account for earthquake clustering. Instead of relying on a fixed time period for rate estimation, we explore another way to determine when the earthquake rate should be updated. This approach could also objectively identify new areas where the induced seismicity hazard model should be applied. We will estimate the background seismicity rate by optimizing a single set of ETAS aftershock triggering parameters across the most active induced seismicity zones -- Oklahoma, Guy-Greenbrier, the Raton Basin, and the Azle-Dallas-Fort Worth area -- with individual background rate parameters in each zone. The full seismicity rate, with uncertainties, can then be estimated using ETAS simulations and changes in rate can be detected by applying change point analysis in ETAS transformed time with methods already developed for Poisson processes.

Combining multiple earthquake models in real time for earthquake early warning

USGS Publications Warehouse

Minson, Sarah E.; Wu, Stephen; Beck, James L; Heaton, Thomas H.

2017-01-01

The ultimate goal of earthquake early warning (EEW) is to provide local shaking information to users before the strong shaking from an earthquake reaches their location. This is accomplished by operating one or more real‐time analyses that attempt to predict shaking intensity, often by estimating the earthquake’s location and magnitude and then predicting the ground motion from that point source. Other EEW algorithms use finite rupture models or may directly estimate ground motion without first solving for an earthquake source. EEW performance could be improved if the information from these diverse and independent prediction models could be combined into one unified, ground‐motion prediction. In this article, we set the forecast shaking at each location as the common ground to combine all these predictions and introduce a Bayesian approach to creating better ground‐motion predictions. We also describe how this methodology could be used to build a new generation of EEW systems that provide optimal decisions customized for each user based on the user’s individual false‐alarm tolerance and the time necessary for that user to react.

E-DECIDER: Using Earth Science Data and Modeling Tools to Develop Decision Support for Earthquake Disaster Response

NASA Astrophysics Data System (ADS)

Glasscoe, Margaret T.; Wang, Jun; Pierce, Marlon E.; Yoder, Mark R.; Parker, Jay W.; Burl, Michael C.; Stough, Timothy M.; Granat, Robert A.; Donnellan, Andrea; Rundle, John B.; Ma, Yu; Bawden, Gerald W.; Yuen, Karen

2015-08-01

Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) is a NASA-funded project developing new capabilities for decision making utilizing remote sensing data and modeling software to provide decision support for earthquake disaster management and response. E-DECIDER incorporates the earthquake forecasting methodology and geophysical modeling tools developed through NASA's QuakeSim project. Remote sensing and geodetic data, in conjunction with modeling and forecasting tools allows us to provide both long-term planning information for disaster management decision makers as well as short-term information following earthquake events (i.e. identifying areas where the greatest deformation and damage has occurred and emergency services may need to be focused). This in turn is delivered through standards-compliant web services for desktop and hand-held devices.

Update of the USGS 2016 One-year Seismic Hazard Forecast for the Central and Eastern United States From Induced and Natural Earthquakes

NASA Astrophysics Data System (ADS)

Petersen, M. D.; Mueller, C. S.; Moschetti, M. P.; Hoover, S. M.; Llenos, A. L.; Ellsworth, W. L.; Michael, A. J.; Rubinstein, J. L.; McGarr, A.; Rukstales, K. S.

2016-12-01

The U.S. Geological Survey released a 2016 one-year forecast for seismic hazard in the central and eastern U.S., which included the influence from both induced and natural earthquakes. This forecast was primarily based on 2015 declustered seismicity rates but also included longer-term rates, 10- and 20- km smoothing distances, earthquakes between Mw 4.7 and maximum magnitudes of 6.0 or 7.1, and 9 alternative ground motion models. Results indicate that areas in Oklahoma, Kansas, Colorado, New Mexico, Arkansas, Texas, and the New Madrid Seismic Zone have a significant chance for damaging ground shaking levels in 2016 (greater than 1% chance of exceeding 0.12 PGA and MMI VI). We evaluate this one-year forecast by considering the earthquakes and ground shaking levels that occurred during the first half of 2016 (earthquakes not included in the forecast). During this period the full catalog records hundreds of events with M ≥ 3.0, but the declustered catalog eliminates most of these dependent earthquakes and results in much lower numbers of earthquakes. The declustered catalog based on USGS COMCAT indicates a M 5.1 earthquake occurred in the zone of highest hazard on the map. Two additional earthquakes of M ≥ 4.0 occurred in Oklahoma, and about 82 earthquakes of M ≥ 3.0 occurred with 77 in Oklahoma and Kansas, 4 in Raton Basin Colorado/New Mexico, and 1 near Cogdell Texas. In addition, 72 earthquakes occurred outside the zones of induced seismicity with more than half in New Madrid and eastern Tennessee. The catalog rates in the first half of 2016 and the corresponding seismic hazard were generally lower than in 2015. For example, the zones for Irving, Venus, and Fashing, Texas; Sun City, Kansas; and north-central Arkansas did not experience any earthquakes with M≥ 2.7 during this period. The full catalog rates were lower by about 30% in Raton Basin and the Oklahoma-Kansas zones but the declustered catalog rates did not drop as much. This decrease in earthquake

Short-Term Forecasting of Taiwanese Earthquakes Using a Universal Model of Fusion-Fission Processes

PubMed Central

Cheong, Siew Ann; Tan, Teck Liang; Chen, Chien-Chih; Chang, Wu-Lung; Liu, Zheng; Chew, Lock Yue; Sloot, Peter M. A.; Johnson, Neil F.

2014-01-01

Predicting how large an earthquake can be, where and when it will strike remains an elusive goal in spite of the ever-increasing volume of data collected by earth scientists. In this paper, we introduce a universal model of fusion-fission processes that can be used to predict earthquakes starting from catalog data. We show how the equilibrium dynamics of this model very naturally explains the Gutenberg-Richter law. Using the high-resolution earthquake catalog of Taiwan between Jan 1994 and Feb 2009, we illustrate how out-of-equilibrium spatio-temporal signatures in the time interval between earthquakes and the integrated energy released by earthquakes can be used to reliably determine the times, magnitudes, and locations of large earthquakes, as well as the maximum numbers of large aftershocks that would follow. PMID:24406467

Rapid tsunami models and earthquake source parameters: Far-field and local applications

USGS Publications Warehouse

Geist, E.L.

2005-01-01

Rapid tsunami models have recently been developed to forecast far-field tsunami amplitudes from initial earthquake information (magnitude and hypocenter). Earthquake source parameters that directly affect tsunami generation as used in rapid tsunami models are examined, with particular attention to local versus far-field application of those models. First, validity of the assumption that the focal mechanism and type of faulting for tsunamigenic earthquakes is similar in a given region can be evaluated by measuring the seismic consistency of past events. Second, the assumption that slip occurs uniformly over an area of rupture will most often underestimate the amplitude and leading-wave steepness of the local tsunami. Third, sometimes large magnitude earthquakes will exhibit a high degree of spatial heterogeneity such that tsunami sources will be composed of distinct sub-events that can cause constructive and destructive interference in the wavefield away from the source. Using a stochastic source model, it is demonstrated that local tsunami amplitudes vary by as much as a factor of two or more, depending on the local bathymetry. If other earthquake source parameters such as focal depth or shear modulus are varied in addition to the slip distribution patterns, even greater uncertainty in local tsunami amplitude is expected for earthquakes of similar magnitude. Because of the short amount of time available to issue local warnings and because of the high degree of uncertainty associated with local, model-based forecasts as suggested by this study, direct wave height observations and a strong public education and preparedness program are critical for those regions near suspected tsunami sources.

Earthquake forecasting studies using radon time series data in Taiwan

NASA Astrophysics Data System (ADS)

Walia, Vivek; Kumar, Arvind; Fu, Ching-Chou; Lin, Shih-Jung; Chou, Kuang-Wu; Wen, Kuo-Liang; Chen, Cheng-Hong

2017-04-01

For few decades, growing number of studies have shown usefulness of data in the field of seismogeochemistry interpreted as geochemical precursory signals for impending earthquakes and radon is idendified to be as one of the most reliable geochemical precursor. Radon is recognized as short-term precursor and is being monitored in many countries. This study is aimed at developing an effective earthquake forecasting system by inspecting long term radon time series data. The data is obtained from a network of radon monitoring stations eastblished along different faults of Taiwan. The continuous time series radon data for earthquake studies have been recorded and some significant variations associated with strong earthquakes have been observed. The data is also examined to evaluate earthquake precursory signals against environmental factors. An automated real-time database operating system has been developed recently to improve the data processing for earthquake precursory studies. In addition, the study is aimed at the appraisal and filtrations of these environmental parameters, in order to create a real-time database that helps our earthquake precursory study. In recent years, automatic operating real-time database has been developed using R, an open source programming language, to carry out statistical computation on the data. To integrate our data with our working procedure, we use the popular and famous open source web application solution, AMP (Apache, MySQL, and PHP), creating a website that could effectively show and help us manage the real-time database.

Eruption Forecasting in Alaska: A Retrospective and Test of the Distal VT Model

NASA Astrophysics Data System (ADS)

Prejean, S. G.; Pesicek, J. D.; Wellik, J.; Cameron, C.; White, R. A.; McCausland, W. A.; Buurman, H.

2015-12-01

United States volcano observatories have successfully forecast most significant US eruptions in the past decade. However, eruptions of some volcanoes remain stubbornly difficult to forecast effectively using seismic data alone. The Alaska Volcano Observatory (AVO) has responded to 28 eruptions from 10 volcanoes since 2005. Eruptions that were not forecast include those of frequently active volcanoes with basaltic-andesite magmas, like Pavlof, Veniaminof, and Okmok volcanoes. In this study we quantify the success rate of eruption forecasting in Alaska and explore common characteristics of eruptions not forecast. In an effort to improve future forecasts, we re-examine seismic data from eruptions and known intrusive episodes in Alaska to test the effectiveness of the distal VT model commonly employed by the USGS-USAID Volcano Disaster Assistance Program (VDAP). In the distal VT model, anomalous brittle failure or volcano-tectonic (VT) earthquake swarms in the shallow crust surrounding the volcano occur as a secondary response to crustal strain induced by magma intrusion. Because the Aleutian volcanic arc is among the most seismically active regions on Earth, distinguishing distal VT earthquake swarms for eruption forecasting purposes from tectonic seismicity unrelated to volcanic processes poses a distinct challenge. In this study, we use a modified beta-statistic to identify pre-eruptive distal VT swarms and establish their statistical significance with respect to long-term background seismicity. This analysis allows us to explore the general applicability of the distal VT model and quantify the likelihood of encountering false positives in eruption forecasting using this model alone.

Long‐term time‐dependent probabilities for the third Uniform California Earthquake Rupture Forecast (UCERF3)

USGS Publications Warehouse

Field, Edward; Biasi, Glenn P.; Bird, Peter; Dawson, Timothy E.; Felzer, Karen R.; Jackson, David A.; Johnson, Kaj M.; Jordan, Thomas H.; Madden, Christopher; Michael, Andrew J.; Milner, Kevin; Page, Morgan T.; Parsons, Thomas E.; Powers, Peter; Shaw, Bruce E.; Thatcher, Wayne R.; Weldon, Ray J.; Zeng, Yuehua

2015-01-01

The 2014 Working Group on California Earthquake Probabilities (WGCEP 2014) presents time-dependent earthquake probabilities for the third Uniform California Earthquake Rupture Forecast (UCERF3). Building on the UCERF3 time-independent model, published previously, renewal models are utilized to represent elastic-rebound-implied probabilities. A new methodology has been developed that solves applicability issues in the previous approach for un-segmented models. The new methodology also supports magnitude-dependent aperiodicity and accounts for the historic open interval on faults that lack a date-of-last-event constraint. Epistemic uncertainties are represented with a logic tree, producing 5,760 different forecasts. Results for a variety of evaluation metrics are presented, including logic-tree sensitivity analyses and comparisons to the previous model (UCERF2). For 30-year M≥6.7 probabilities, the most significant changes from UCERF2 are a threefold increase on the Calaveras fault and a threefold decrease on the San Jacinto fault. Such changes are due mostly to differences in the time-independent models (e.g., fault slip rates), with relaxation of segmentation and inclusion of multi-fault ruptures being particularly influential. In fact, some UCERF2 faults were simply too long to produce M 6.7 sized events given the segmentation assumptions in that study. Probability model differences are also influential, with the implied gains (relative to a Poisson model) being generally higher in UCERF3. Accounting for the historic open interval is one reason. Another is an effective 27% increase in the total elastic-rebound-model weight. The exact factors influencing differences between UCERF2 and UCERF3, as well as the relative importance of logic-tree branches, vary throughout the region, and depend on the evaluation metric of interest. For example, M≥6.7 probabilities may not be a good proxy for other hazard or loss measures. This sensitivity, coupled with the

Short-term volcano-tectonic earthquake forecasts based on a moving mean recurrence time algorithm: the El Hierro seismo-volcanic crisis experience

NASA Astrophysics Data System (ADS)

García, Alicia; De la Cruz-Reyna, Servando; Marrero, José M.; Ortiz, Ramón

2016-05-01

Under certain conditions, volcano-tectonic (VT) earthquakes may pose significant hazards to people living in or near active volcanic regions, especially on volcanic islands; however, hazard arising from VT activity caused by localized volcanic sources is rarely addressed in the literature. The evolution of VT earthquakes resulting from a magmatic intrusion shows some orderly behaviour that may allow the occurrence and magnitude of major events to be forecast. Thus governmental decision makers can be supplied with warnings of the increased probability of larger-magnitude earthquakes on the short-term timescale. We present here a methodology for forecasting the occurrence of large-magnitude VT events during volcanic crises; it is based on a mean recurrence time (MRT) algorithm that translates the Gutenberg-Richter distribution parameter fluctuations into time windows of increased probability of a major VT earthquake. The MRT forecasting algorithm was developed after observing a repetitive pattern in the seismic swarm episodes occurring between July and November 2011 at El Hierro (Canary Islands). From then on, this methodology has been applied to the consecutive seismic crises registered at El Hierro, achieving a high success rate in the real-time forecasting, within 10-day time windows, of volcano-tectonic earthquakes.

Computing and Visualizing the Complex Dynamics of Earthquake Fault Systems: Towards Ensemble Earthquake Forecasting

NASA Astrophysics Data System (ADS)

Rundle, J.; Rundle, P.; Donnellan, A.; Li, P.

2003-12-01

We consider the problem of the complex dynamics of earthquake fault systems, and whether numerical simulations can be used to define an ensemble forecasting technology similar to that used in weather and climate research. To effectively carry out such a program, we need 1) a topological realistic model to simulate the fault system; 2) data sets to constrain the model parameters through a systematic program of data assimilation; 3) a computational technology making use of modern paradigms of high performance and parallel computing systems; and 4) software to visualize and analyze the results. In particular, we focus attention of a new version of our code Virtual California (version 2001) in which we model all of the major strike slip faults extending throughout California, from the Mexico-California border to the Mendocino Triple Junction. We use the historic data set of earthquakes larger than magnitude M > 6 to define the frictional properties of all 654 fault segments (degrees of freedom) in the model. Previous versions of Virtual California had used only 215 fault segments to model the strike slip faults in southern California. To compute the dynamics and the associated surface deformation, we use message passing as implemented in the MPICH standard distribution on a small Beowulf cluster consisting of 10 cpus. We are also planning to run the code on significantly larger machines so that we can begin to examine much finer spatial scales of resolution, and to assess scaling properties of the code. We present results of simulations both as static images and as mpeg movies, so that the dynamical aspects of the computation can be assessed by the viewer. We also compute a variety of statistics from the simulations, including magnitude-frequency relations, and compare these with data from real fault systems.

Development of Physics and Control of Multiple Forcing Mechanisms for the Alaska Tsunami Forecast Model

NASA Astrophysics Data System (ADS)

Bahng, B.; Whitmore, P.; Macpherson, K. A.; Knight, W. R.

2016-12-01

The Alaska Tsunami Forecast Model (ATFM) is a numerical model used to forecast propagation and inundation of tsunamis generated by earthquakes or other mechanisms in either the Pacific Ocean, Atlantic Ocean or Gulf of Mexico. At the U.S. National Tsunami Warning Center (NTWC), the use of the model has been mainly for tsunami pre-computation due to earthquakes. That is, results for hundreds of hypothetical events are computed before alerts, and are accessed and calibrated with observations during tsunamis to immediately produce forecasts. The model has also been used for tsunami hindcasting due to submarine landslides and due to atmospheric pressure jumps, but in a very case-specific and somewhat limited manner. ATFM uses the non-linear, depth-averaged, shallow-water equations of motion with multiply nested grids in two-way communications between domains of each parent-child pair as waves approach coastal waters. The shallow-water wave physics is readily applicable to all of the above tsunamis as well as to tides. Recently, the model has been expanded to include multiple forcing mechanisms in a systematic fashion, and to enhance the model physics for non-earthquake events.ATFM is now able to handle multiple source mechanisms, either individually or jointly, which include earthquake, submarine landslide, meteo-tsunami and tidal forcing. As for earthquakes, the source can be a single unit source or multiple, interacting source blocks. Horizontal slip contribution can be added to the sea-floor displacement. The model now includes submarine landslide physics, modeling the source either as a rigid slump, or as a viscous fluid. Additional shallow-water physics have been implemented for the viscous submarine landslides. With rigid slumping, any trajectory can be followed. As for meteo-tsunami, the forcing mechanism is capable of following any trajectory shape. Wind stress physics has also been implemented for the meteo-tsunami case, if required. As an example of multiple

Statistical analysis of earthquakes after the 1999 MW 7.7 Chi-Chi, Taiwan, earthquake based on a modified Reasenberg-Jones model

NASA Astrophysics Data System (ADS)

Chen, Yuh-Ing; Huang, Chi-Shen; Liu, Jann-Yenq

2015-12-01

We investigated the temporal-spatial hazard of the earthquakes after the 1999 September 21 MW = 7.7 Chi-Chi shock in a continental region of Taiwan. The Reasenberg-Jones (RJ) model (Reasenberg and Jones, 1989, 1994) that combines the frequency-magnitude distribution (Gutenberg and Richter, 1944) and time-decaying occurrence rate (Utsu et al., 1995) is conventionally employed for assessing the earthquake hazard after a large shock. However, it is found that the b values in the frequency-magnitude distribution of the earthquakes in the study region dramatically decreased from background values after the Chi-Chi shock, and then gradually increased up. The observation of a time-dependent frequency-magnitude distribution motivated us to propose a modified RJ model (MRJ) to assess the earthquake hazard. To see how the models perform on assessing short-term earthquake hazard, the RJ and MRJ models were separately used to sequentially forecast earthquakes in the study region. To depict the potential rupture area for future earthquakes, we further constructed relative hazard (RH) maps based on the two models. The Receiver Operating Characteristics (ROC) curves (Swets, 1988) finally demonstrated that the RH map based on the MRJ model was, in general, superior to the one based on the original RJ model for exploring the spatial hazard of earthquakes in a short time after the Chi-Chi shock.

CSEP-Japan: The Japanese node of the collaboratory for the study of earthquake predictability

NASA Astrophysics Data System (ADS)

Yokoi, S.; Tsuruoka, H.; Nanjo, K.; Hirata, N.

2011-12-01

Collaboratory for the Study of Earthquake Predictability (CSEP) is a global project of earthquake predictability research. The final goal of this project is to have a look for the intrinsic predictability of the earthquake rupture process through forecast testing experiments. The Earthquake Research Institute, the University of Tokyo joined the CSEP and started the Japanese testing center called as CSEP-Japan. This testing center constitutes an open access to researchers contributing earthquake forecast models for applied to Japan. A total of 91 earthquake forecast models were submitted on the prospective experiment starting from 1 November 2009. The models are separated into 4 testing classes (1 day, 3 months, 1 year and 3 years) and 3 testing regions covering an area of Japan including sea area, Japanese mainland and Kanto district. We evaluate the performance of the models in the official suite of tests defined by the CSEP. The experiments of 1-day, 3-month, 1-year and 3-year forecasting classes were implemented for 92 rounds, 4 rounds, 1round and 0 round (now in progress), respectively. The results of the 3-month class gave us new knowledge concerning statistical forecasting models. All models showed a good performance for magnitude forecasting. On the other hand, observation is hardly consistent in space-distribution with most models in some cases where many earthquakes occurred at the same spot. Throughout the experiment, it has been clarified that some properties of the CSEP's evaluation tests such as the L-test show strong correlation with the N-test. We are now processing to own (cyber-) infrastructure to support the forecast experiment as follows. (1) Japanese seismicity has changed since the 2011 Tohoku earthquake. The 3rd call for forecasting models was announced in order to promote model improvement for forecasting earthquakes after this earthquake. So, we provide Japanese seismicity catalog maintained by JMA for modelers to study how seismicity

Spatial Evaluation and Verification of Earthquake Simulators

NASA Astrophysics Data System (ADS)

Wilson, John Max; Yoder, Mark R.; Rundle, John B.; Turcotte, Donald L.; Schultz, Kasey W.

2017-06-01

In this paper, we address the problem of verifying earthquake simulators with observed data. Earthquake simulators are a class of computational simulations which attempt to mirror the topological complexity of fault systems on which earthquakes occur. In addition, the physics of friction and elastic interactions between fault elements are included in these simulations. Simulation parameters are adjusted so that natural earthquake sequences are matched in their scaling properties. Physically based earthquake simulators can generate many thousands of years of simulated seismicity, allowing for a robust capture of the statistical properties of large, damaging earthquakes that have long recurrence time scales. Verification of simulations against current observed earthquake seismicity is necessary, and following past simulator and forecast model verification methods, we approach the challenges in spatial forecast verification to simulators; namely, that simulator outputs are confined to the modeled faults, while observed earthquake epicenters often occur off of known faults. We present two methods for addressing this discrepancy: a simplistic approach whereby observed earthquakes are shifted to the nearest fault element and a smoothing method based on the power laws of the epidemic-type aftershock (ETAS) model, which distributes the seismicity of each simulated earthquake over the entire test region at a decaying rate with epicentral distance. To test these methods, a receiver operating characteristic plot was produced by comparing the rate maps to observed m>6.0 earthquakes in California since 1980. We found that the nearest-neighbor mapping produced poor forecasts, while the ETAS power-law method produced rate maps that agreed reasonably well with observations.

Forecasting the Rupture Directivity of Large Earthquakes: Centroid Bias of the Conditional Hypocenter Distribution

NASA Astrophysics Data System (ADS)

Donovan, J.; Jordan, T. H.

2012-12-01

Forecasting the rupture directivity of large earthquakes is an important problem in probabilistic seismic hazard analysis (PSHA), because directivity is known to strongly influence ground motions. We describe how rupture directivity can be forecast in terms of the "conditional hypocenter distribution" or CHD, defined to be the probability distribution of a hypocenter given the spatial distribution of moment release (fault slip). The simplest CHD is a uniform distribution, in which the hypocenter probability density equals the moment-release probability density. For rupture models in which the rupture velocity and rise time depend only on the local slip, the CHD completely specifies the distribution of the directivity parameter D, defined in terms of the degree-two polynomial moments of the source space-time function. This parameter, which is zero for a bilateral rupture and unity for a unilateral rupture, can be estimated from finite-source models or by the direct inversion of seismograms (McGuire et al., 2002). We compile D-values from published studies of 65 large earthquakes and show that these data are statistically inconsistent with the uniform CHD advocated by McGuire et al. (2002). Instead, the data indicate a "centroid biased" CHD, in which the expected distance between the hypocenter and the hypocentroid is less than that of a uniform CHD. In other words, the observed directivities appear to be closer to bilateral than predicted by this simple model. We discuss the implications of these results for rupture dynamics and fault-zone heterogeneities. We also explore their PSHA implications by modifying the CyberShake simulation-based hazard model for the Los Angeles region, which assumed a uniform CHD (Graves et al., 2011).

Forecasting the evolution of seismicity in southern California: Animations built on earthquake stress transfer

USGS Publications Warehouse

Toda, S.; Stein, R.S.; Richards-Dinger, K.; Bozkurt, S.B.

2005-01-01

We develop a forecast model to reproduce the distibution of main shocks, aftershocks and surrounding seismicity observed during 1986-200 in a 300 ?? 310 km area centered on the 1992 M = 7.3 Landers earthquake. To parse the catalog into frames with equal numbers of aftershocks, we animate seismicity in log time increments that lengthen after each main shock; this reveals aftershock zone migration, expansion, and densification. We implement a rate/state algorithm that incorporates the static stress transferred by each M ??? 6 shock and then evolves. Coulomb stress changes amplify the background seismicity, so small stress changes produce large changes in seismicity rate in areas of high background seismicity. Similarly, seismicity rate declines in the stress shadows are evident only in areas with previously high seismicity rates. Thus a key constituent of the model is the background seismicity rate, which we smooth from 1981 to 1986 seismicity. The mean correlation coefficient between observed and predicted M ??? 1.4 shocks (the minimum magnitude of completeness) is 0.52 for 1986-2003 and 0.63 for 1992-2003; a control standard aftershock model yields 0.54 and 0.52 for the same periods. Four M ??? 6.0 shocks struck during the test period; three are located at sites where the expected seismicity rate falls above the 92 percentile, and one is located above the 75 percentile. The model thus reproduces much, but certainly not all, of the observed spatial and temporal seismicity, from which we infer that the decaying effect of stress transferred by successive main shocks influences seismicity for decades. Finally, we offer a M ??? 5 earthquake forecast for 2005-2015, assigning probabilities to 324 10 ?? 10 km cells.

Evaluation of W Phase CMT Based PTWC Real-Time Tsunami Forecast Model Using DART Observations: Events of the Last Decade

NASA Astrophysics Data System (ADS)

Wang, D.; Becker, N. C.; Weinstein, S.; Duputel, Z.; Rivera, L. A.; Hayes, G. P.; Hirshorn, B. F.; Bouchard, R. H.; Mungov, G.

2017-12-01

The Pacific Tsunami Warning Center (PTWC) began forecasting tsunamis in real-time using source parameters derived from real-time Centroid Moment Tensor (CMT) solutions in 2009. Both the USGS and PTWC typically obtain W-Phase CMT solutions for large earthquakes less than 30 minutes after earthquake origin time. Within seconds, and often before waves reach the nearest deep ocean bottom pressure sensor (DARTs), PTWC then generates a regional tsunami propagation forecast using its linear shallow water model. The model is initialized by the sea surface deformation that mimics the seafloor deformation based on Okada's (1985) dislocation model of a rectangular fault with a uniform slip. The fault length and width are empirical functions of the seismic moment. How well did this simple model perform? The DART records provide a very valuable dataset for model validation. We examine tsunami events of the last decade with earthquake magnitudes ranging from 6.5 to 9.0 including some deep events for which tsunamis were not expected. Most of the forecast results were obtained during the events. We also include events from before the implementation of the WCMT method at USGS and PTWC, 2006-2009. For these events, WCMTs were computed retrospectively (Duputel et al. 2012). We also re-ran the model with a larger domain for some events to include far-field DARTs that recorded a tsunami with identical source parameters used during the events. We conclude that our model results, in terms of maximum wave amplitude, are mostly within a factor of two of the observed at DART stations, with an average error of less than 40% for most events, including the 2010 Maule and the 2011 Tohoku tsunamis. However, the simple fault model with a uniform slip is too simplistic for the Tohoku tsunami. We note model results are sensitive to centroid location and depth, especially if the earthquake is close to land or inland. For the 2016 M7.8 New Zealand earthquake the initial forecast underestimated the

Volcanic Eruption Forecasts From Accelerating Rates of Drumbeat Long-Period Earthquakes

NASA Astrophysics Data System (ADS)

Bell, Andrew F.; Naylor, Mark; Hernandez, Stephen; Main, Ian G.; Gaunt, H. Elizabeth; Mothes, Patricia; Ruiz, Mario

2018-02-01

Accelerating rates of quasiperiodic "drumbeat" long-period earthquakes (LPs) are commonly reported before eruptions at andesite and dacite volcanoes, and promise insights into the nature of fundamental preeruptive processes and improved eruption forecasts. Here we apply a new Bayesian Markov chain Monte Carlo gamma point process methodology to investigate an exceptionally well-developed sequence of drumbeat LPs preceding a recent large vulcanian explosion at Tungurahua volcano, Ecuador. For more than 24 hr, LP rates increased according to the inverse power law trend predicted by material failure theory, and with a retrospectively forecast failure time that agrees with the eruption onset within error. LPs resulted from repeated activation of a single characteristic source driven by accelerating loading, rather than a distributed failure process, showing that similar precursory trends can emerge from quite different underlying physics. Nevertheless, such sequences have clear potential for improving forecasts of eruptions at Tungurahua and analogous volcanoes.

Operational foreshock forecasting: Fifteen years after

NASA Astrophysics Data System (ADS)

Ogata, Y.

2010-12-01

We are concerned with operational forecasting of the probability that events are foreshocks of a forthcoming earthquake that is significantly larger (mainshock). Specifically, we define foreshocks as the preshocks substantially smaller than the mainshock by a magnitude gap of 0.5 or larger. The probability gain of foreshock forecast is extremely high compare to long-term forecast by renewal processes or various alarm-based intermediate-term forecasts because of a large event’s low occurrence rate in a short period and a narrow target region. Thus, it is desired to establish operational foreshock probability forecasting as seismologists have done for aftershocks. When a series of earthquakes occurs in a region, we attempt to discriminate foreshocks from a swarm or mainshock-aftershock sequence. Namely, after real time identification of an earthquake cluster using methods such as the single-link algorithm, the probability is calculated by applying statistical features that discriminate foreshocks from other types of clusters, by considering the events' stronger proximity in time and space and tendency towards chronologically increasing magnitudes. These features were modeled for probability forecasting and the coefficients of the model were estimated in Ogata et al. (1996) for the JMA hypocenter data (M≧4, 1926-1993). Currently, fifteen years has passed since the publication of the above-stated work so that we are able to present the performance and validation of the forecasts (1994-2009) by using the same model. Taking isolated events into consideration, the probability of the first events in a potential cluster being a foreshock vary in a range between 0+% and 10+% depending on their locations. This conditional forecasting performs significantly better than the unconditional (average) foreshock probability of 3.7% throughout Japan region. Furthermore, when we have the additional events in a cluster, the forecast probabilities range more widely from nearly 0% to

Forecast experiment: do temporal and spatial b value variations along the Calaveras fault portend M ≥ 4.0 earthquakes?

USGS Publications Warehouse

Parsons, Tom

2007-01-01

The power law distribution of earthquake magnitudes and frequencies is a fundamental scaling relationship used for forecasting. However, can its slope (b value) be used on individual faults as a stress indicator? Some have concluded that b values drop just before large shocks. Others suggested that temporally stable low b value zones identify future large-earthquake locations. This study assesses the frequency of b value anomalies portending M ≥ 4.0 shocks versus how often they do not. I investigated M ≥ 4.0 Calaveras fault earthquakes because there have been 25 over the 37-year duration of the instrumental catalog on the most active southern half of the fault. With that relatively large sample, I conducted retrospective time and space earthquake forecasts. I calculated temporal b value changes in 5-km-radius cylindrical volumes of crust that were significant at 90% confidence, but these changes were poor forecasters of M ≥ 4.0 earthquakes. M ≥ 4.0 events were as likely to happen at times of high b values as they were at low ones. However, I could not rule out a hypothesis that spatial b value anomalies portend M ≥ 4.0 events; of 20 M ≥ 4 shocks that could be studied, 6 to 8 (depending on calculation method) occurred where b values were significantly less than the spatial mean, 1 to 2 happened above the mean, and 10 to 13 occurred within 90% confidence intervals of the mean and were thus inconclusive. Thus spatial b value variation might be a useful forecast tool, but resolution is poor, even on seismically active faults.

Fractals and Forecasting in Earthquakes and Finance

NASA Astrophysics Data System (ADS)

Rundle, J. B.; Holliday, J. R.; Turcotte, D. L.

2011-12-01

It is now recognized that Benoit Mandelbrot's fractals play a critical role in describing a vast range of physical and social phenomena. Here we focus on two systems, earthquakes and finance. Since 1942, earthquakes have been characterized by the Gutenberg-Richter magnitude-frequency relation, which in more recent times is often written as a moment-frequency power law. A similar relation can be shown to hold for financial markets. Moreover, a recent New York Times article, titled "A Richter Scale for the Markets" [1] summarized the emerging viewpoint that stock market crashes can be described with similar ideas as large and great earthquakes. The idea that stock market crashes can be related in any way to earthquake phenomena has its roots in Mandelbrot's 1963 work on speculative prices in commodities markets such as cotton [2]. He pointed out that Gaussian statistics did not account for the excessive number of booms and busts that characterize such markets. Here we show that both earthquakes and financial crashes can both be described by a common Landau-Ginzburg-type free energy model, involving the presence of a classical limit of stability, or spinodal. These metastable systems are characterized by fractal statistics near the spinodal. For earthquakes, the independent ("order") parameter is the slip deficit along a fault, whereas for the financial markets, it is financial leverage in place. For financial markets, asset values play the role of a free energy. In both systems, a common set of techniques can be used to compute the probabilities of future earthquakes or crashes. In the case of financial models, the probabilities are closely related to implied volatility, an important component of Black-Scholes models for stock valuations. [2] B. Mandelbrot, The variation of certain speculative prices, J. Business, 36, 294 (1963)

Development, testing, and applications of site-specific tsunami inundation models for real-time forecasting

NASA Astrophysics Data System (ADS)

Tang, L.; Titov, V. V.; Chamberlin, C. D.

2009-12-01

The study describes the development, testing and applications of site-specific tsunami inundation models (forecast models) for use in NOAA's tsunami forecast and warning system. The model development process includes sensitivity studies of tsunami wave characteristics in the nearshore and inundation, for a range of model grid setups, resolutions and parameters. To demonstrate the process, four forecast models in Hawaii, at Hilo, Kahului, Honolulu, and Nawiliwili are described. The models were validated with fourteen historical tsunamis and compared with numerical results from reference inundation models of higher resolution. The accuracy of the modeled maximum wave height is greater than 80% when the observation is greater than 0.5 m; when the observation is below 0.5 m the error is less than 0.3 m. The error of the modeled arrival time of the first peak is within 3% of the travel time. The developed forecast models were further applied to hazard assessment from simulated magnitude 7.5, 8.2, 8.7 and 9.3 tsunamis based on subduction zone earthquakes in the Pacific. The tsunami hazard assessment study indicates that use of a seismic magnitude alone for a tsunami source assessment is inadequate to achieve such accuracy for tsunami amplitude forecasts. The forecast models apply local bathymetric and topographic information, and utilize dynamic boundary conditions from the tsunami source function database, to provide site- and event-specific coastal predictions. Only by combining a Deep-ocean Assessment and Reporting of Tsunami-constrained tsunami magnitude with site-specific high-resolution models can the forecasts completely cover the evolution of earthquake-generated tsunami waves: generation, deep ocean propagation, and coastal inundation. Wavelet analysis of the tsunami waves suggests the coastal tsunami frequency responses at different sites are dominated by the local bathymetry, yet they can be partially related to the locations of the tsunami sources. The study

Earthquake precursors: activation or quiescence?

NASA Astrophysics Data System (ADS)

Rundle, John B.; Holliday, James R.; Yoder, Mark; Sachs, Michael K.; Donnellan, Andrea; Turcotte, Donald L.; Tiampo, Kristy F.; Klein, William; Kellogg, Louise H.

2011-10-01

We discuss the long-standing question of whether the probability for large earthquake occurrence (magnitudes m > 6.0) is highest during time periods of smaller event activation, or highest during time periods of smaller event quiescence. The physics of the activation model are based on an idea from the theory of nucleation, that a small magnitude earthquake has a finite probability of growing into a large earthquake. The physics of the quiescence model is based on the idea that the occurrence of smaller earthquakes (here considered as magnitudes m > 3.5) may be due to a mechanism such as critical slowing down, in which fluctuations in systems with long-range interactions tend to be suppressed prior to large nucleation events. To illuminate this question, we construct two end-member forecast models illustrating, respectively, activation and quiescence. The activation model assumes only that activation can occur, either via aftershock nucleation or triggering, but expresses no choice as to which mechanism is preferred. Both of these models are in fact a means of filtering the seismicity time-series to compute probabilities. Using 25 yr of data from the California-Nevada catalogue of earthquakes, we show that of the two models, activation and quiescence, the latter appears to be the better model, as judged by backtesting (by a slight but not significant margin). We then examine simulation data from a topologically realistic earthquake model for California seismicity, Virtual California. This model includes not only earthquakes produced from increases in stress on the fault system, but also background and off-fault seismicity produced by a BASS-ETAS driving mechanism. Applying the activation and quiescence forecast models to the simulated data, we come to the opposite conclusion. Here, the activation forecast model is preferred to the quiescence model, presumably due to the fact that the BASS component of the model is essentially a model for activated seismicity. These

GPS Technologies as a Tool to Detect the Pre-Earthquake Signals Associated with Strong Earthquakes

NASA Astrophysics Data System (ADS)

Pulinets, S. A.; Krankowski, A.; Hernandez-Pajares, M.; Liu, J. Y. G.; Hattori, K.; Davidenko, D.; Ouzounov, D.

2015-12-01

The existence of ionospheric anomalies before earthquakes is now widely accepted. These phenomena started to be considered by GPS community to mitigate the GPS signal degradation over the territories of the earthquake preparation. The question is still open if they could be useful for seismology and for short-term earthquake forecast. More than decade of intensive studies proved that ionospheric anomalies registered before earthquakes are initiated by processes in the boundary layer of atmosphere over earthquake preparation zone and are induced in the ionosphere by electromagnetic coupling through the Global Electric Circuit. Multiparameter approach based on the Lithosphere-Atmosphere-Ionosphere Coupling model demonstrated that earthquake forecast is possible only if we consider the final stage of earthquake preparation in the multidimensional space where every dimension is one from many precursors in ensemble, and they are synergistically connected. We demonstrate approaches developed in different countries (Russia, Taiwan, Japan, Spain, and Poland) within the framework of the ISSI and ESA projects) to identify the ionospheric precursors. They are also useful to determine the all three parameters necessary for the earthquake forecast: impending earthquake epicenter position, expectation time and magnitude. These parameters are calculated using different technologies of GPS signal processing: time series, correlation, spectral analysis, ionospheric tomography, wave propagation, etc. Obtained results from different teams demonstrate the high level of statistical significance and physical justification what gives us reason to suggest these methodologies for practical validation.

Jumping over the hurdles to effectively communicate the Operational Earthquake Forecast

NASA Astrophysics Data System (ADS)

McBride, S.; Wein, A. M.; Becker, J.; Potter, S.; Tilley, E. N.; Gerstenberger, M.; Orchiston, C.; Johnston, D. M.

2016-12-01

Probabilities, uncertainties, statistics, science, and threats are notoriously difficult topics to communicate with members of the public. The Operational Earthquake Forecast (OEF) is designed to provide an understanding of potential numbers and sizes of earthquakes and the communication of it must address all of those challenges. Furthermore, there are other barriers to effective communication of the OEF. These barriers include the erosion of trust in scientists and experts, oversaturation of messages, fear and threat messages magnified by the sensalisation of the media, fractured media environments and online echo chambers. Given the complexities and challenges of the OEF, how can we overcome barriers to effective communication? Crisis and risk communication research can inform the development of communication strategies to increase the public understanding and use of the OEF, when applied to the opportunities and challenges of practice. We explore ongoing research regarding how the OEF can be more effectively communicated - including the channels, tools and message composition to engage with a variety of publics. We also draw on past experience and a study of OEF communication during the Canterbury Earthquake Sequence (CES). We demonstrate how research and experience has guided OEF communications during subsequent events in New Zealand, including the M5.7 Valentine's Day earthquake in 2016 (CES), M6.0 Wilberforce earthquake in 2015, and the Cook Strait/Lake Grassmere earthquakes in 2013. We identify the successes and lessons learned of the practical communication of the OEF. Finally, we present future projects and directions in the communication of OEF, informed by both practice and research.

Recent Achievements of the Collaboratory for the Study of Earthquake Predictability

NASA Astrophysics Data System (ADS)

Jackson, D. D.; Liukis, M.; Werner, M. J.; Schorlemmer, D.; Yu, J.; Maechling, P. J.; Zechar, J. D.; Jordan, T. H.

2015-12-01

Maria Liukis, SCEC, USC; Maximilian Werner, University of Bristol; Danijel Schorlemmer, GFZ Potsdam; John Yu, SCEC, USC; Philip Maechling, SCEC, USC; Jeremy Zechar, Swiss Seismological Service, ETH; Thomas H. Jordan, SCEC, USC, and the CSEP Working Group The Collaboratory for the Study of Earthquake Predictability (CSEP) supports a global program to conduct prospective earthquake forecasting experiments. CSEP testing centers are now operational in California, New Zealand, Japan, China, and Europe with 435 models under evaluation. The California testing center, operated by SCEC, has been operational since Sept 1, 2007, and currently hosts 30-minute, 1-day, 3-month, 1-year and 5-year forecasts, both alarm-based and probabilistic, for California, the Western Pacific, and worldwide. We have reduced testing latency, implemented prototype evaluation of M8 forecasts, and are currently developing formats and procedures to evaluate externally-hosted forecasts and predictions. These efforts are related to CSEP support of the USGS program in operational earthquake forecasting and a DHS project to register and test external forecast procedures from experts outside seismology. A retrospective experiment for the 2010-2012 Canterbury earthquake sequence has been completed, and the results indicate that some physics-based and hybrid models outperform purely statistical (e.g., ETAS) models. The experiment also demonstrates the power of the CSEP cyberinfrastructure for retrospective testing. Our current development includes evaluation strategies that increase computational efficiency for high-resolution global experiments, such as the evaluation of the Global Earthquake Activity Rate (GEAR) model. We describe the open-source CSEP software that is available to researchers as they develop their forecast models (http://northridge.usc.edu/trac/csep/wiki/MiniCSEP). We also discuss applications of CSEP infrastructure to geodetic transient detection and how CSEP procedures are being

Ergodicity and Phase Transitions and Their Implications for Earthquake Forecasting.

NASA Astrophysics Data System (ADS)

Klein, W.

2017-12-01

Forecasting earthquakes or even predicting the statistical distribution of events on a given fault is extremely difficult. One reason for this difficulty is the large number of fault characteristics that can affect the distribution and timing of events. The range of stress transfer, the level of noise, and the nature of the friction force all influence the type of the events and the values of these parameters can vary from fault to fault and also vary with time. In addition, the geometrical structure of the faults and the correlation of events on different faults plays an important role in determining the event size and their distribution. Another reason for the difficulty is that the important fault characteristics are not easily measured. The noise level, fault structure, stress transfer range, and the nature of the friction force are extremely difficult, if not impossible to ascertain. Given this lack of information, one of the most useful approaches to understanding the effect of fault characteristics and the way they interact is to develop and investigate models of faults and fault systems.In this talk I will present results obtained from a series of models of varying abstraction and compare them with data from actual faults. We are able to provide a physical basis for several observed phenomena such as the earthquake cycle, thefact that some faults display Gutenburg-Richter scaling and others do not, and that some faults exhibit quasi-periodic characteristic events and others do not. I will also discuss some surprising results such as the fact that some faults are in thermodynamic equilibrium depending on the stress transfer range and the noise level. An example of an important conclusion that can be drawn from this work is that the statistical distribution of earthquake events can vary from fault to fault and that an indication of an impending large event such as accelerating moment release may be relevant on some faults but not on others.

From Data-Sharing to Model-Sharing: SCEC and the Development of Earthquake System Science (Invited)

NASA Astrophysics Data System (ADS)

Jordan, T. H.

2009-12-01

Earthquake system science seeks to construct system-level models of earthquake phenomena and use them to predict emergent seismic behavior—an ambitious enterprise that requires high degree of interdisciplinary, multi-institutional collaboration. This presentation will explore model-sharing structures that have been successful in promoting earthquake system science within the Southern California Earthquake Center (SCEC). These include disciplinary working groups to aggregate data into community models; numerical-simulation working groups to investigate system-specific phenomena (process modeling) and further improve the data models (inverse modeling); and interdisciplinary working groups to synthesize predictive system-level models. SCEC has developed a cyberinfrastructure, called the Community Modeling Environment, that can distribute the community models; manage large suites of numerical simulations; vertically integrate the hardware, software, and wetware needed for system-level modeling; and promote the interactions among working groups needed for model validation and refinement. Various socio-scientific structures contribute to successful model-sharing. Two of the most important are “communities of trust” and collaborations between government and academic scientists on mission-oriented objectives. The latter include improvements of earthquake forecasts and seismic hazard models and the use of earthquake scenarios in promoting public awareness and disaster management.

The EM Earthquake Precursor

NASA Astrophysics Data System (ADS)

Jones, K. B., II; Saxton, P. T.

2013-12-01

Many attempts have been made to determine a sound forecasting method regarding earthquakes and warn the public in turn. Presently, the animal kingdom leads the precursor list alluding to a transmission related source. By applying the animal-based model to an electromagnetic (EM) wave model, various hypotheses were formed, but the most interesting one required the use of a magnetometer with a differing design and geometry. To date, numerous, high-end magnetometers have been in use in close proximity to fault zones for potential earthquake forecasting; however, something is still amiss. The problem still resides with what exactly is forecastable and the investigating direction of EM. After the 1989 Loma Prieta Earthquake, American earthquake investigators predetermined magnetometer use and a minimum earthquake magnitude necessary for EM detection. This action was set in motion, due to the extensive damage incurred and public outrage concerning earthquake forecasting; however, the magnetometers employed, grounded or buried, are completely subject to static and electric fields and have yet to correlate to an identifiable precursor. Secondly, there is neither a networked array for finding any epicentral locations, nor have there been any attempts to find even one. This methodology needs dismissal, because it is overly complicated, subject to continuous change, and provides no response time. As for the minimum magnitude threshold, which was set at M5, this is simply higher than what modern technological advances have gained. Detection can now be achieved at approximately M1, which greatly improves forecasting chances. A propagating precursor has now been detected in both the field and laboratory. Field antenna testing conducted outside the NE Texas town of Timpson in February, 2013, detected three strong EM sources along with numerous weaker signals. The antenna had mobility, and observations were noted for recurrence, duration, and frequency response. Next, two

Analysis of the Seismicity Preceding Large Earthquakes

NASA Astrophysics Data System (ADS)

Stallone, A.; Marzocchi, W.

2016-12-01

The most common earthquake forecasting models assume that the magnitude of the next earthquake is independent from the past. This feature is probably one of the most severe limitations of the capability to forecast large earthquakes.In this work, we investigate empirically on this specific aspect, exploring whether spatial-temporal variations in seismicity encode some information on the magnitude of the future earthquakes. For this purpose, and to verify the universality of the findings, we consider seismic catalogs covering quite different space-time-magnitude windows, such as the Alto Tiberina Near Fault Observatory (TABOO) catalogue, and the California and Japanese seismic catalog. Our method is inspired by the statistical methodology proposed by Zaliapin (2013) to distinguish triggered and background earthquakes, using the nearest-neighbor clustering analysis in a two-dimension plan defined by rescaled time and space. In particular, we generalize the metric based on the nearest-neighbor to a metric based on the k-nearest-neighbors clustering analysis that allows us to consider the overall space-time-magnitude distribution of k-earthquakes (k-foreshocks) which anticipate one target event (the mainshock); then we analyze the statistical properties of the clusters identified in this rescaled space. In essence, the main goal of this study is to verify if different classes of mainshock magnitudes are characterized by distinctive k-foreshocks distribution. The final step is to show how the findings of this work may (or not) improve the skill of existing earthquake forecasting models.

Rapid Tsunami Inundation Forecast from Near-field or Far-field Earthquakes using Pre-computed Tsunami Database: Pelabuhan Ratu, Indonesia

NASA Astrophysics Data System (ADS)

Gusman, A. R.; Setiyono, U.; Satake, K.; Fujii, Y.

2017-12-01

We built pre-computed tsunami inundation database in Pelabuhan Ratu, one of tsunami-prone areas on the southern coast of Java, Indonesia. The tsunami database can be employed for a rapid estimation of tsunami inundation during an event. The pre-computed tsunami waveforms and inundations are from a total of 340 scenarios ranging from 7.5 to 9.2 in moment magnitude scale (Mw), including simple fault models of 208 thrust faults and 44 tsunami earthquakes on the plate interface, as well as 44 normal faults and 44 reverse faults in the outer-rise region. Using our tsunami inundation forecasting algorithm (NearTIF), we could rapidly estimate the tsunami inundation in Pelabuhan Ratu for three different hypothetical earthquakes. The first hypothetical earthquake is a megathrust earthquake type (Mw 9.0) offshore Sumatra which is about 600 km from Pelabuhan Ratu to represent a worst-case event in the far-field. The second hypothetical earthquake (Mw 8.5) is based on a slip deficit rate estimation from geodetic measurements and represents a most likely large event near Pelabuhan Ratu. The third hypothetical earthquake is a tsunami earthquake type (Mw 8.1) which often occur south off Java. We compared the tsunami inundation maps produced by the NearTIF algorithm with results of direct forward inundation modeling for the hypothetical earthquakes. The tsunami inundation maps produced from both methods are similar for the three cases. However, the tsunami inundation map from the inundation database can be obtained in much shorter time (1 min) than the one from a forward inundation modeling (40 min). These indicate that the NearTIF algorithm based on pre-computed inundation database is reliable and useful for tsunami warning purposes. This study also demonstrates that the NearTIF algorithm can work well even though the earthquake source is located outside the area of fault model database because it uses a time shifting procedure for the best-fit scenario searching.

Stress-based aftershock forecasts made within 24h post mainshock: Expected north San Francisco Bay area seismicity changes after the 2014M=6.0 West Napa earthquake

USGS Publications Warehouse

Parsons, Thomas E.; Segou, Margaret; Sevilgen, Volkan; Milner, Kevin; Field, Edward; Toda, Shinji; Stein, Ross S.

2014-01-01

We calculate stress changes resulting from the M= 6.0 West Napa earthquake on north San Francisco Bay area faults. The earthquake ruptured within a series of long faults that pose significant hazard to the Bay area, and we are thus concerned with potential increases in the probability of a large earthquake through stress transfer. We conduct this exercise as a prospective test because the skill of stress-based aftershock forecasting methodology is inconclusive. We apply three methods: (1) generalized mapping of regional Coulomb stress change, (2) stress changes resolved on Uniform California Earthquake Rupture Forecast faults, and (3) a mapped rate/state aftershock forecast. All calculations were completed within 24 h after the main shock and were made without benefit of known aftershocks, which will be used to evaluative the prospective forecast. All methods suggest that we should expect heightened seismicity on parts of the southern Rodgers Creek, northern Hayward, and Green Valley faults.

Stress-based aftershock forecasts made within 24 h postmain shock: Expected north San Francisco Bay area seismicity changes after the 2014 M = 6.0 West Napa earthquake

NASA Astrophysics Data System (ADS)

Parsons, Tom; Segou, Margaret; Sevilgen, Volkan; Milner, Kevin; Field, Edward; Toda, Shinji; Stein, Ross S.

2014-12-01

We calculate stress changes resulting from the M = 6.0 West Napa earthquake on north San Francisco Bay area faults. The earthquake ruptured within a series of long faults that pose significant hazard to the Bay area, and we are thus concerned with potential increases in the probability of a large earthquake through stress transfer. We conduct this exercise as a prospective test because the skill of stress-based aftershock forecasting methodology is inconclusive. We apply three methods: (1) generalized mapping of regional Coulomb stress change, (2) stress changes resolved on Uniform California Earthquake Rupture Forecast faults, and (3) a mapped rate/state aftershock forecast. All calculations were completed within 24 h after the main shock and were made without benefit of known aftershocks, which will be used to evaluative the prospective forecast. All methods suggest that we should expect heightened seismicity on parts of the southern Rodgers Creek, northern Hayward, and Green Valley faults.

Nonlinear time series modeling and forecasting the seismic data of the Hindu Kush region

NASA Astrophysics Data System (ADS)

Khan, Muhammad Yousaf; Mittnik, Stefan

2018-01-01

In this study, we extended the application of linear and nonlinear time models in the field of earthquake seismology and examined the out-of-sample forecast accuracy of linear Autoregressive (AR), Autoregressive Conditional Duration (ACD), Self-Exciting Threshold Autoregressive (SETAR), Threshold Autoregressive (TAR), Logistic Smooth Transition Autoregressive (LSTAR), Additive Autoregressive (AAR), and Artificial Neural Network (ANN) models for seismic data of the Hindu Kush region. We also extended the previous studies by using Vector Autoregressive (VAR) and Threshold Vector Autoregressive (TVAR) models and compared their forecasting accuracy with linear AR model. Unlike previous studies that typically consider the threshold model specifications by using internal threshold variable, we specified these models with external transition variables and compared their out-of-sample forecasting performance with the linear benchmark AR model. The modeling results show that time series models used in the present study are capable of capturing the dynamic structure present in the seismic data. The point forecast results indicate that the AR model generally outperforms the nonlinear models. However, in some cases, threshold models with external threshold variables specification produce more accurate forecasts, indicating that specification of threshold time series models is of crucial importance. For raw seismic data, the ACD model does not show an improved out-of-sample forecasting performance over the linear AR model. The results indicate that the AR model is the best forecasting device to model and forecast the raw seismic data of the Hindu Kush region.

Forecasting in Complex Systems

NASA Astrophysics Data System (ADS)

Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Turcotte, D. L.; Donnellan, A.

2014-12-01

Complex nonlinear systems are typically characterized by many degrees of freedom, as well as interactions between the elements. Interesting examples can be found in the areas of earthquakes and finance. In these two systems, fat tails play an important role in the statistical dynamics. For earthquake systems, the Gutenberg-Richter magnitude-frequency is applicable, whereas for daily returns for the securities in the financial markets are known to be characterized by leptokurtotic statistics in which the tails are power law. Very large fluctuations are present in both systems. In earthquake systems, one has the example of great earthquakes such as the M9.1, March 11, 2011 Tohoku event. In financial systems, one has the example of the market crash of October 19, 1987. Both were largely unexpected events that severely impacted the earth and financial systems systemically. Other examples include the M9.3 Andaman earthquake of December 26, 2004, and the Great Recession which began with the fall of Lehman Brothers investment bank on September 12, 2013. Forecasting the occurrence of these damaging events has great societal importance. In recent years, national funding agencies in a variety of countries have emphasized the importance of societal relevance in research, and in particular, the goal of improved forecasting technology. Previous work has shown that both earthquakes and financial crashes can be described by a common Landau-Ginzburg-type free energy model. These metastable systems are characterized by fat tail statistics near the classical spinodal. Correlations in these systems can grow and recede, but do not imply causation, a common source of misunderstanding. In both systems, a common set of techniques can be used to compute the probabilities of future earthquakes or crashes. In this talk, we describe the basic phenomenology of these systems and emphasize their similarities and differences. We also consider the problem of forecast validation and verification

ViscoSim Earthquake Simulator

USGS Publications Warehouse

Pollitz, Fred

2012-01-01

Synthetic seismicity simulations have been explored by the Southern California Earthquake Center (SCEC) Earthquake Simulators Group in order to guide long‐term forecasting efforts related to the Unified California Earthquake Rupture Forecast (Tullis et al., 2012a). In this study I describe the viscoelastic earthquake simulator (ViscoSim) of Pollitz, 2009. Recapitulating to a large extent material previously presented by Pollitz (2009, 2011) I describe its implementation of synthetic ruptures and how it differs from other simulators being used by the group.

M ≥ 7.0 earthquake recurrence on the San Andreas fault from a stress renewal model

USGS Publications Warehouse

Parsons, Thomas E.

2006-01-01

 Forecasting M ≥ 7.0 San Andreas fault earthquakes requires an assessment of their expected frequency. I used a three-dimensional finite element model of California to calculate volumetric static stress drops from scenario M ≥ 7.0 earthquakes on three San Andreas fault sections. The ratio of stress drop to tectonic stressing rate derived from geodetic displacements yielded recovery times at points throughout the model volume. Under a renewal model, stress recovery times on ruptured fault planes can be a proxy for earthquake recurrence. I show curves of magnitude versus stress recovery time for three San Andreas fault sections. When stress recovery times were converted to expected M ≥ 7.0 earthquake frequencies, they fit Gutenberg-Richter relationships well matched to observed regional rates of M ≤ 6.0 earthquakes. Thus a stress-balanced model permits large earthquake Gutenberg-Richter behavior on an individual fault segment, though it does not require it. Modeled slip magnitudes and their expected frequencies were consistent with those observed at the Wrightwood paleoseismic site if strict time predictability does not apply to the San Andreas fault.

The Virtual Quake Earthquake Simulator: Earthquake Probability Statistics for the El Mayor-Cucapah Region and Evidence of Predictability in Simulated Earthquake Sequences

NASA Astrophysics Data System (ADS)

Schultz, K.; Yoder, M. R.; Heien, E. M.; Rundle, J. B.; Turcotte, D. L.; Parker, J. W.; Donnellan, A.

2015-12-01

We introduce a framework for developing earthquake forecasts using Virtual Quake (VQ), the generalized successor to the perhaps better known Virtual California (VC) earthquake simulator. We discuss the basic merits and mechanics of the simulator, and we present several statistics of interest for earthquake forecasting. We also show that, though the system as a whole (in aggregate) behaves quite randomly, (simulated) earthquake sequences limited to specific fault sections exhibit measurable predictability in the form of increasing seismicity precursory to large m > 7 earthquakes. In order to quantify this, we develop an alert based forecasting metric similar to those presented in Keilis-Borok (2002); Molchan (1997), and show that it exhibits significant information gain compared to random forecasts. We also discuss the long standing question of activation vs quiescent type earthquake triggering. We show that VQ exhibits both behaviors separately for independent fault sections; some fault sections exhibit activation type triggering, while others are better characterized by quiescent type triggering. We discuss these aspects of VQ specifically with respect to faults in the Salton Basin and near the El Mayor-Cucapah region in southern California USA and northern Baja California Norte, Mexico.

Physics-based forecasting of induced seismicity at Groningen gas field, the Netherlands

NASA Astrophysics Data System (ADS)

Dempsey, David; Suckale, Jenny

2017-08-01

Earthquakes induced by natural gas extraction from the Groningen reservoir, the Netherlands, put local communities at risk. Responsible operation of a reservoir whose gas reserves are of strategic importance to the country requires understanding of the link between extraction and earthquakes. We synthesize observations and a model for Groningen seismicity to produce forecasts for felt seismicity (M > 2.5) in the period February 2017 to 2024. Our model accounts for poroelastic earthquake triggering and rupture on the 325 largest reservoir faults, using an ensemble approach to model unknown heterogeneity and replicate earthquake statistics. We calculate probability distributions for key model parameters using a Bayesian method that incorporates the earthquake observations with a nonhomogeneous Poisson process. Our analysis indicates that the Groningen reservoir was not critically stressed prior to the start of production. Epistemic uncertainty and aleatoric uncertainty are incorporated into forecasts for three different future extraction scenarios. The largest expected earthquake was similar for all scenarios, with a 5% likelihood of exceeding M 4.0.

Analysis of the seismicity preceding large earthquakes

NASA Astrophysics Data System (ADS)

Stallone, Angela; Marzocchi, Warner

2017-04-01

The most common earthquake forecasting models assume that the magnitude of the next earthquake is independent from the past. This feature is probably one of the most severe limitations of the capability to forecast large earthquakes. In this work, we investigate empirically on this specific aspect, exploring whether variations in seismicity in the space-time-magnitude domain encode some information on the size of the future earthquakes. For this purpose, and to verify the stability of the findings, we consider seismic catalogs covering quite different space-time-magnitude windows, such as the Alto Tiberina Near Fault Observatory (TABOO) catalogue, the California and Japanese seismic catalog. Our method is inspired by the statistical methodology proposed by Baiesi & Paczuski (2004) and elaborated by Zaliapin et al. (2008) to distinguish between triggered and background earthquakes, based on a pairwise nearest-neighbor metric defined by properly rescaled temporal and spatial distances. We generalize the method to a metric based on the k-nearest-neighbors that allows us to consider the overall space-time-magnitude distribution of k-earthquakes, which are the strongly correlated ancestors of a target event. Finally, we analyze the statistical properties of the clusters composed by the target event and its k-nearest-neighbors. In essence, the main goal of this study is to verify if different classes of target event magnitudes are characterized by distinctive "k-foreshocks" distributions. The final step is to show how the findings of this work may (or not) improve the skill of existing earthquake forecasting models.

Lessons Learned about Best Practices for Communicating Earthquake Forecasting and Early Warning to Non-Scientific Publics

NASA Astrophysics Data System (ADS)

Sellnow, D. D.; Sellnow, T. L.

2017-12-01

Earthquake scientists are without doubt experts in understanding earthquake probabilities, magnitudes, and intensities, as well as the potential consequences of them to community infrastructures and inhabitants. One critical challenge these scientific experts face, however, rests with communicating what they know to the people they want to help. Helping scientists translate scientific information to non-scientists is something Drs. Tim and Deanna Sellnow have been committed to for decades. As such, they have compiled a host of data-driven best practices for communicating effectively to non-scientific publics about earthquake forecasting, probabilities, and warnings. In this session, they will summarize what they have learned as it may help earthquake scientists, emergency managers, and other key spokespersons share these important messages to disparate publics in ways that result in positive outcomes, the most important of which is saving lives.

Forecasting induced seismicity rate and Mmax using calibrated numerical models

NASA Astrophysics Data System (ADS)

Dempsey, D.; Suckale, J.

2016-12-01

At Groningen, The Netherlands, several decades of induced seismicity from gas extraction has culminated in a M 3.6 event (mid 2012). From a public safety and commercial perspective, it is desirable to anticipate future seismicity outcomes at Groningen. One way to quantify earthquake risk is Probabilistic Seismic Hazard Analysis (PSHA), which requires an estimate of the future seismicity rate and its magnitude frequency distribution (MFD). This approach is effective at quantifying risk from tectonic events because the seismicity rate, once measured, is almost constant over timescales of interest. In contrast, rates of induced seismicity vary significantly over building lifetimes, largely in response to changes in injection or extraction. Thus, the key to extending PSHA to induced earthquakes is to estimate future changes of the seismicity rate in response to some proposed operating schedule. Numerical models can describe the physical link between fluid pressure, effective stress change, and the earthquake process (triggering and propagation). However, models with predictive potential of individual earthquakes face the difficulty of characterizing specific heterogeneity - stress, strength, roughness, etc. - at locations of interest. Modeling catalogs of earthquakes provides a means of averaging over this uncertainty, focusing instead on the collective features of the seismicity, e.g., its rate and MFD. The model we use incorporates fluid pressure and stress changes to describe nucleation and crack-like propagation of earthquakes on stochastically characterized 1D faults. This enables simulation of synthetic catalogs of induced seismicity from which the seismicity rate, location and MFD are extracted. A probability distribution for Mmax - the largest event in some specified time window - is also computed. Because the model captures the physics linking seismicity to changes in the reservoir, earthquake observations and operating information can be used to calibrate a

Evaluation of induced seismicity forecast models in the Induced Seismicity Test Bench

NASA Astrophysics Data System (ADS)

Király, Eszter; Gischig, Valentin; Zechar, Jeremy; Doetsch, Joseph; Karvounis, Dimitrios; Wiemer, Stefan

2016-04-01

Induced earthquakes often accompany fluid injection, and the seismic hazard they pose threatens various underground engineering projects. Models to monitor and control induced seismic hazard with traffic light systems should be probabilistic, forward-looking, and updated as new data arrive. Here, we propose an Induced Seismicity Test Bench to test and rank such models. We apply the test bench to data from the Basel 2006 and Soultz-sous-Forêts 2004 geothermal stimulation projects, and we assess forecasts from two models that incorporate a different mix of physical understanding and stochastic representation of the induced sequences: Shapiro in Space (SiS) and Hydraulics and Seismics (HySei). SiS is based on three pillars: the seismicity rate is computed with help of the seismogenic index and a simple exponential decay of the seismicity; the magnitude distribution follows the Gutenberg-Richter relation; and seismicity is distributed in space based on smoothing seismicity during the learning period with 3D Gaussian kernels. The HySei model describes seismicity triggered by pressure diffusion with irreversible permeability enhancement. Our results show that neither model is fully superior to the other. HySei forecasts the seismicity rate well, but is only mediocre at forecasting the spatial distribution. On the other hand, SiS forecasts the spatial distribution well but not the seismicity rate. The shut-in phase is a difficult moment for both models in both reservoirs: the models tend to underpredict the seismicity rate around, and shortly after, shut-in. Ensemble models that combine HySei's rate forecast with SiS's spatial forecast outperform each individual model.

Identified EM Earthquake Precursors

NASA Astrophysics Data System (ADS)

Jones, Kenneth, II; Saxton, Patrick

2014-05-01

Many attempts have been made to determine a sound forecasting method regarding earthquakes and warn the public in turn. Presently, the animal kingdom leads the precursor list alluding to a transmission related source. By applying the animal-based model to an electromagnetic (EM) wave model, various hypotheses were formed, but the most interesting one required the use of a magnetometer with a differing design and geometry. To date, numerous, high-end magnetometers have been in use in close proximity to fault zones for potential earthquake forecasting; however, something is still amiss. The problem still resides with what exactly is forecastable and the investigating direction of EM. After a number of custom rock experiments, two hypotheses were formed which could answer the EM wave model. The first hypothesis concerned a sufficient and continuous electron movement either by surface or penetrative flow, and the second regarded a novel approach to radio transmission. Electron flow along fracture surfaces was determined to be inadequate in creating strong EM fields, because rock has a very high electrical resistance making it a high quality insulator. Penetrative flow could not be corroborated as well, because it was discovered that rock was absorbing and confining electrons to a very thin skin depth. Radio wave transmission and detection worked with every single test administered. This hypothesis was reviewed for propagating, long-wave generation with sufficient amplitude, and the capability of penetrating solid rock. Additionally, fracture spaces, either air or ion-filled, can facilitate this concept from great depths and allow for surficial detection. A few propagating precursor signals have been detected in the field occurring with associated phases using custom-built loop antennae. Field testing was conducted in Southern California from 2006-2011, and outside the NE Texas town of Timpson in February, 2013. The antennae have mobility and observations were noted for

Simulation of the Burridge-Knopoff model of earthquakes with variable range stress transfer.

PubMed

Xia, Junchao; Gould, Harvey; Klein, W; Rundle, J B

2005-12-09

Simple models of earthquake faults are important for understanding the mechanisms for their observed behavior, such as Gutenberg-Richter scaling and the relation between large and small events, which is the basis for various forecasting methods. Although cellular automaton models have been studied extensively in the long-range stress transfer limit, this limit has not been studied for the Burridge-Knopoff model, which includes more realistic friction forces and inertia. We find that the latter model with long-range stress transfer exhibits qualitatively different behavior than both the long-range cellular automaton models and the usual Burridge-Knopoff model with nearest-neighbor springs, depending on the nature of the velocity-weakening friction force. These results have important implications for our understanding of earthquakes and other driven dissipative systems.

A parimutuel gambling perspective to compare probabilistic seismicity forecasts

NASA Astrophysics Data System (ADS)

Zechar, J. Douglas; Zhuang, Jiancang

2014-10-01

Using analogies to gaming, we consider the problem of comparing multiple probabilistic seismicity forecasts. To measure relative model performance, we suggest a parimutuel gambling perspective which addresses shortcomings of other methods such as likelihood ratio, information gain and Molchan diagrams. We describe two variants of the parimutuel approach for a set of forecasts: head-to-head, in which forecasts are compared in pairs, and round table, in which all forecasts are compared simultaneously. For illustration, we compare the 5-yr forecasts of the Regional Earthquake Likelihood Models experiment for M4.95+ seismicity in California.

A Simple Model for the Earthquake Cycle Combining Self-Organized Criticality with Critical Point Behavior

NASA Astrophysics Data System (ADS)

Newman, W. I.; Turcotte, D. L.

2002-12-01

We have studied a hybrid model combining the forest-fire model with the site-percolation model in order to better understand the earthquake cycle. We consider a square array of sites. At each time step, a "tree" is dropped on a randomly chosen site and is planted if the site is unoccupied. When a cluster of "trees" spans the site (a percolating cluster), all the trees in the cluster are removed ("burned") in a "fire." The removal of the cluster is analogous to a characteristic earthquake and planting "trees" is analogous to increasing the regional stress. The clusters are analogous to the metastable regions of a fault over which an earthquake rupture can propagate once triggered. We find that the frequency-area statistics of the metastable regions are power-law with a negative exponent of two (as in the forest-fire model). This is analogous to the Gutenberg-Richter distribution of seismicity. This "self-organized critical behavior" can be explained in terms of an inverse cascade of clusters. Individual trees move from small to larger clusters until they are destroyed. This inverse cascade of clusters is self-similar and the power-law distribution of cluster sizes has been shown to have an exponent of two. We have quantified the forecasting of the spanning fires using error diagrams. The assumption that "fires" (earthquakes) are quasi-periodic has moderate predictability. The density of trees gives an improved degree of predictability, while the size of the largest cluster of trees provides a substantial improvement in forecasting a "fire."

Development of Parallel Code for the Alaska Tsunami Forecast Model

NASA Astrophysics Data System (ADS)

Bahng, B.; Knight, W. R.; Whitmore, P.

2014-12-01

The Alaska Tsunami Forecast Model (ATFM) is a numerical model used to forecast propagation and inundation of tsunamis generated by earthquakes and other means in both the Pacific and Atlantic Oceans. At the U.S. National Tsunami Warning Center (NTWC), the model is mainly used in a pre-computed fashion. That is, results for hundreds of hypothetical events are computed before alerts, and are accessed and calibrated with observations during tsunamis to immediately produce forecasts. ATFM uses the non-linear, depth-averaged, shallow-water equations of motion with multiply nested grids in two-way communications between domains of each parent-child pair as waves get closer to coastal waters. Even with the pre-computation the task becomes non-trivial as sub-grid resolution gets finer. Currently, the finest resolution Digital Elevation Models (DEM) used by ATFM are 1/3 arc-seconds. With a serial code, large or multiple areas of very high resolution can produce run-times that are unrealistic even in a pre-computed approach. One way to increase the model performance is code parallelization used in conjunction with a multi-processor computing environment. NTWC developers have undertaken an ATFM code-parallelization effort to streamline the creation of the pre-computed database of results with the long term aim of tsunami forecasts from source to high resolution shoreline grids in real time. Parallelization will also permit timely regeneration of the forecast model database with new DEMs; and, will make possible future inclusion of new physics such as the non-hydrostatic treatment of tsunami propagation. The purpose of our presentation is to elaborate on the parallelization approach and to show the compute speed increase on various multi-processor systems.

Modeling Extra-Long Tsunami Propagation: Assessing Data, Model Accuracy and Forecast Implications

NASA Astrophysics Data System (ADS)

Titov, V. V.; Moore, C. W.; Rabinovich, A.

2017-12-01

Detecting and modeling tsunamis propagating tens of thousands of kilometers from the source is a formidable scientific challenge and seemingly satisfies only scientific curiosity. However, results of such analyses produce a valuable insight into the tsunami propagation dynamics, model accuracy and would provide important implications for tsunami forecast. The Mw = 9.3 megathrust earthquake of December 26, 2004 off the coast of Sumatra generated a tsunami that devastated Indian Ocean coastlines and spread into the Pacific and Atlantic oceans. The tsunami was recorded by a great number of coastal tide gauges, including those located in 15-25 thousand kilometers from the source area. To date, it is still the farthest instrumentally detected tsunami. The data from these instruments throughout the world oceans enabled to estimate various statistical parameters and energy decay of this event. High-resolution records of this tsunami from DARTs 32401 (offshore of northern Chile), 46405 and NeMO (both offshore of the US West Coast), combined with the mainland tide gauge measurements enabled us to examine far-field characteristics of the 2004 in the Pacific Ocean and to compare the results of global numerical simulations with the observations. Despite their small heights (less than 2 cm at deep-ocean locations), the records demonstrated consistent spatial and temporal structure. The numerical model described well the frequency content, amplitudes and general structure of the observed waves at deep-ocean and coastal gages. We present analysis of the measurements and comparison with model data to discuss implication for tsunami forecast accuracy. Model study for such extreme distances from the tsunami source and at extra-long times after the event is an attempt to find accuracy bounds for tsunami models and accuracy limitations of model use for forecast. We discuss results in application to tsunami model forecast and tsunami modeling in general.

On the adaptive daily forecasting of seismic aftershock hazard

NASA Astrophysics Data System (ADS)

Ebrahimian, Hossein; Jalayer, Fatemeh; Asprone, Domenico; Lombardi, Anna Maria; Marzocchi, Warner; Prota, Andrea; Manfredi, Gaetano

2013-04-01

Post-earthquake ground motion hazard assessment is a fundamental initial step towards time-dependent seismic risk assessment for buildings in a post main-shock environment. Therefore, operative forecasting of seismic aftershock hazard forms a viable support basis for decision-making regarding search and rescue, inspection, repair, and re-occupation in a post main-shock environment. Arguably, an adaptive procedure for integrating the aftershock occurrence rate together with suitable ground motion prediction relations is key to Probabilistic Seismic Aftershock Hazard Assessment (PSAHA). In the short-term, the seismic hazard may vary significantly (Jordan et al., 2011), particularly after the occurrence of a high magnitude earthquake. Hence, PSAHA requires a reliable model that is able to track the time evolution of the earthquake occurrence rates together with suitable ground motion prediction relations. This work focuses on providing adaptive daily forecasts of the mean daily rate of exceeding various spectral acceleration values (the aftershock hazard). Two well-established earthquake occurrence models suitable for daily seismicity forecasts associated with the evolution of an aftershock sequence, namely, the modified Omori's aftershock model and the Epidemic Type Aftershock Sequence (ETAS) are adopted. The parameters of the modified Omori model are updated on a daily basis using Bayesian updating and based on the data provided by the ongoing aftershock sequence based on the methodology originally proposed by Jalayer et al. (2011). The Bayesian updating is used also to provide sequence-based parameter estimates for a given ground motion prediction model, i.e. the aftershock events in an ongoing sequence are exploited in order to update in an adaptive manner the parameters of an existing ground motion prediction model. As a numerical example, the mean daily rates of exceeding specific spectral acceleration values are estimated adaptively for the L'Aquila 2009

Monitoring and Modeling: The Future of Volcanic Eruption Forecasting

NASA Astrophysics Data System (ADS)

Poland, M. P.; Pritchard, M. E.; Anderson, K. R.; Furtney, M.; Carn, S. A.

2016-12-01

Eruption forecasting typically uses monitoring data from geology, gas geochemistry, geodesy, and seismology, to assess the likelihood of future eruptive activity. Occasionally, months to years of warning are possible from specific indicators (e.g., deep LP earthquakes, elevated CO2 emissions, and aseismic deformation) or a buildup in one or more monitoring parameters. More often, observable changes in unrest occur immediately before eruption, as magma is rising toward the surface. In some cases, little or no detectable unrest precedes eruptive activity. Eruption forecasts are usually based on the experience of volcanologists studying the activity, but two developing fields offer a potential leap beyond this practice. First, remote sensing data, which can track thermal, gas, and ash emissions, as well as surface deformation, are increasingly available, allowing statistically significant research into the characteristics of unrest. For example, analysis of hundreds of volcanoes indicates that deformation is a more common pre-eruptive phenomenon than thermal anomalies, and that most episodes of satellite-detected unrest are not immediately followed by eruption. Such robust datasets inform the second development—probabilistic models of eruption potential, especially those that are based on physical-chemical models of the dynamics of magma accumulation and ascent. Both developments are essential for refining forecasts and reducing false positives. For example, many caldera systems have not erupted but are characterized by unrest that, in another context, would elicit strong concern from volcanologists. More observations of this behavior and better understanding of the underlying physics of unrest will improve forecasts of such activity. While still many years from implementation as a forecasting tool, probabilistic physio-chemical models incorporating satellite data offer a complement to expert assessments that, together, can form a powerful forecasting approach.

Earthquake hazard assessment in the Zagros Orogenic Belt of Iran using a fuzzy rule-based model

NASA Astrophysics Data System (ADS)

Farahi Ghasre Aboonasr, Sedigheh; Zamani, Ahmad; Razavipour, Fatemeh; Boostani, Reza

2017-08-01

Producing accurate seismic hazard map and predicting hazardous areas is necessary for risk mitigation strategies. In this paper, a fuzzy logic inference system is utilized to estimate the earthquake potential and seismic zoning of Zagros Orogenic Belt. In addition to the interpretability, fuzzy predictors can capture both nonlinearity and chaotic behavior of data, where the number of data is limited. In this paper, earthquake pattern in the Zagros has been assessed for the intervals of 10 and 50 years using fuzzy rule-based model. The Molchan statistical procedure has been used to show that our forecasting model is reliable. The earthquake hazard maps for this area reveal some remarkable features that cannot be observed on the conventional maps. Regarding our achievements, some areas in the southern (Bandar Abbas), southwestern (Bandar Kangan) and western (Kermanshah) parts of Iran display high earthquake severity even though they are geographically far apart.

Spatial Distribution of the Coefficient of Variation for the Paleo-Earthquakes in Japan

NASA Astrophysics Data System (ADS)

Nomura, S.; Ogata, Y.

2015-12-01

Renewal processes, point prccesses in which intervals between consecutive events are independently and identically distributed, are frequently used to describe this repeating earthquake mechanism and forecast the next earthquakes. However, one of the difficulties in applying recurrent earthquake models is the scarcity of the historical data. Most studied fault segments have few, or only one observed earthquake that often have poorly constrained historic and/or radiocarbon ages. The maximum likelihood estimate from such a small data set can have a large bias and error, which tends to yield high probability for the next event in a very short time span when the recurrence intervals have similar lengths. On the other hand, recurrence intervals at a fault depend on the long-term slip rate caused by the tectonic motion in average. In addition, recurrence times are also fluctuated by nearby earthquakes or fault activities which encourage or discourage surrounding seismicity. These factors have spatial trends due to the heterogeneity of tectonic motion and seismicity. Thus, this paper introduces a spatial structure on the key parameters of renewal processes for recurrent earthquakes and estimates it by using spatial statistics. Spatial variation of mean and variance parameters of recurrence times are estimated in Bayesian framework and the next earthquakes are forecasted by Bayesian predictive distributions. The proposal model is applied for recurrent earthquake catalog in Japan and its result is compared with the current forecast adopted by the Earthquake Research Committee of Japan.

Sensitivity of Coulomb stress changes to slip models of source faults: A case study for the 2011 Mw 9.0 Tohoku-oki earthquake

NASA Astrophysics Data System (ADS)

Wang, J.; Xu, C.; Furlong, K.; Zhong, B.; Xiao, Z.; Yi, L.; Chen, T.

2017-12-01

Although Coulomb stress changes induced by earthquake events have been used to quantify stress transfers and to retrospectively explain stress triggering among earthquake sequences, realistic reliable prospective earthquake forecasting remains scarce. To generate a robust Coulomb stress map for earthquake forecasting, uncertainties in Coulomb stress changes associated with the source fault, receiver fault and friction coefficient and Skempton's coefficient need to be exhaustively considered. In this paper, we specifically explore the uncertainty in slip models of the source fault of the 2011 Mw 9.0 Tohoku-oki earthquake as a case study. This earthquake was chosen because of its wealth of finite-fault slip models. Based on the wealth of those slip models, we compute the coseismic Coulomb stress changes induced by this mainshock. Our results indicate that nearby Coulomb stress changes for each slip model can be quite different, both for the Coulomb stress map at a given depth and on the Pacific subducting slab. The triggering rates for three months of aftershocks of the mainshock, with and without considering the uncertainty in slip models, differ significantly, decreasing from 70% to 18%. Reliable Coulomb stress changes in the three seismogenic zones of Nanki, Tonankai and Tokai are insignificant, approximately only 0.04 bar. By contrast, the portions of the Pacific subducting slab at a depth of 80 km and beneath Tokyo received a positive Coulomb stress change of approximately 0.2 bar. The standard errors of the seismicity rate and earthquake probability based on the Coulomb rate-and-state model (CRS) decay much faster with elapsed time in stress triggering zones than in stress shadows, meaning that the uncertainties in Coulomb stress changes in stress triggering zones would not drastically affect assessments of the seismicity rate and earthquake probability based on the CRS in the intermediate to long term.

The 1985 central chile earthquake: a repeat of previous great earthquakes in the region?

PubMed

Comte, D; Eisenberg, A; Lorca, E; Pardo, M; Ponce, L; Saragoni, R; Singh, S K; Suárez, G

1986-07-25

A great earthquake (surface-wave magnitude, 7.8) occurred along the coast of central Chile on 3 March 1985, causing heavy damage to coastal towns. Intense foreshock activity near the epicenter of the main shock occurred for 11 days before the earthquake. The aftershocks of the 1985 earthquake define a rupture area of 170 by 110 square kilometers. The earthquake was forecast on the basis of the nearly constant repeat time (83 +/- 9 years) of great earthquakes in this region. An analysis of previous earthquakes suggests that the rupture lengths of great shocks in the region vary by a factor of about 3. The nearly constant repeat time and variable rupture lengths cannot be reconciled with time- or slip-predictable models of earthquake recurrence. The great earthquakes in the region seem to involve a variable rupture mode and yet, for unknown reasons, remain periodic. Historical data suggest that the region south of the 1985 rupture zone should now be considered a gap of high seismic potential that may rupture in a great earthquake in the next few tens of years.

Modelling and forecasting 3D-hypocentre seismicity in the Kanto region

NASA Astrophysics Data System (ADS)

Guo, Yicun; Zhuang, Jiancang; Hirata, Naoshi

2018-04-01

This study analyses the seismicity in the Kanto region by fitting the 2D-epicentre and 3D-hypocentre ETAS models to the JMA catalogue for events above magnitude M4.0. In the 3D ETAS model, the focal depth is assumed to follow the beta distribution. Compared with results from the 2D-epicentre ETAS model, the 3D ETAS model greatly improves the data fitting. In addition, the stochastic reconstruction method is used when validating the results of the 3D ETAS model, with results indicating that the shallow events are more productive and their aftershocks decay slightly faster in the time and epicentre dimensions. We also study the changes of seismicity patterns before and after the 2011 Tohoku earthquake. The direct aftershocks of events from the post-Tohoku period are more diffusive in time and epicentre but more concentrated in depth. The seismicity rate increases significantly following the Tohoku earthquake, especially along the interface of the subducting Pacific plate. The curve of cumulative background probabilities for events above M4.0 implies that the background rate decays back to the pre-Tohoku level in about 5 years after the Tohoku earthquake. However, the occurrence rates of smaller events (from M2.0 to M4.0) indicate that the adjustments of local stress field continue at finer scales. Finally, we verify that the 3D model can reproduce the focal depths better than the 2D model and improve the forecasting performance.

Forecasting volcanic eruptions and other material failure phenomena: An evaluation of the failure forecast method

NASA Astrophysics Data System (ADS)

Bell, Andrew F.; Naylor, Mark; Heap, Michael J.; Main, Ian G.

2011-08-01

Power-law accelerations in the mean rate of strain, earthquakes and other precursors have been widely reported prior to material failure phenomena, including volcanic eruptions, landslides and laboratory deformation experiments, as predicted by several theoretical models. The Failure Forecast Method (FFM), which linearizes the power-law trend, has been routinely used to forecast the failure time in retrospective analyses; however, its performance has never been formally evaluated. Here we use synthetic and real data, recorded in laboratory brittle creep experiments and at volcanoes, to show that the assumptions of the FFM are inconsistent with the error structure of the data, leading to biased and imprecise forecasts. We show that a Generalized Linear Model method provides higher-quality forecasts that converge more accurately to the eventual failure time, accounting for the appropriate error distributions. This approach should be employed in place of the FFM to provide reliable quantitative forecasts and estimate their associated uncertainties.

Retrospective forecast of ETAS model with daily parameters estimate

NASA Astrophysics Data System (ADS)

Falcone, Giuseppe; Murru, Maura; Console, Rodolfo; Marzocchi, Warner; Zhuang, Jiancang

2016-04-01

We present a retrospective ETAS (Epidemic Type of Aftershock Sequence) model based on the daily updating of free parameters during the background, the learning and the test phase of a seismic sequence. The idea was born after the 2011 Tohoku-Oki earthquake. The CSEP (Collaboratory for the Study of Earthquake Predictability) Center in Japan provided an appropriate testing benchmark for the five 1-day submitted models. Of all the models, only one was able to successfully predict the number of events that really happened. This result was verified using both the real time and the revised catalogs. The main cause of the failure was in the underestimation of the forecasted events, due to model parameters maintained fixed during the test. Moreover, the absence in the learning catalog of an event similar to the magnitude of the mainshock (M9.0), which drastically changed the seismicity in the area, made the learning parameters not suitable to describe the real seismicity. As an example of this methodological development we show the evolution of the model parameters during the last two strong seismic sequences in Italy: the 2009 L'Aquila and the 2012 Reggio Emilia episodes. The achievement of the model with daily updated parameters is compared with that of same model where the parameters remain fixed during the test time.

Probing failure susceptibilities of earthquake faults using small-quake tidal correlations.

PubMed

Brinkman, Braden A W; LeBlanc, Michael; Ben-Zion, Yehuda; Uhl, Jonathan T; Dahmen, Karin A

2015-01-27

Mitigating the devastating economic and humanitarian impact of large earthquakes requires signals for forecasting seismic events. Daily tide stresses were previously thought to be insufficient for use as such a signal. Recently, however, they have been found to correlate significantly with small earthquakes, just before large earthquakes occur. Here we present a simple earthquake model to investigate whether correlations between daily tidal stresses and small earthquakes provide information about the likelihood of impending large earthquakes. The model predicts that intervals of significant correlations between small earthquakes and ongoing low-amplitude periodic stresses indicate increased fault susceptibility to large earthquake generation. The results agree with the recent observations of large earthquakes preceded by time periods of significant correlations between smaller events and daily tide stresses. We anticipate that incorporating experimentally determined parameters and fault-specific details into the model may provide new tools for extracting improved probabilities of impending large earthquakes.

The Loma Prieta, California, Earthquake of October 17, 1989: Earthquake Occurrence

USGS Publications Warehouse

Coordinated by Bakun, William H.; Prescott, William H.

1993-01-01

Professional Paper 1550 seeks to understand the M6.9 Loma Prieta earthquake itself. It examines how the fault that generated the earthquake ruptured, searches for and evaluates precursors that may have indicated an earthquake was coming, reviews forecasts of the earthquake, and describes the geology of the earthquake area and the crustal forces that affect this geology. Some significant findings were: * Slip during the earthquake occurred on 35 km of fault at depths ranging from 7 to 20 km. Maximum slip was approximately 2.3 m. The earthquake may not have released all of the strain stored in rocks next to the fault and indicates a potential for another damaging earthquake in the Santa Cruz Mountains in the near future may still exist. * The earthquake involved a large amount of uplift on a dipping fault plane. Pre-earthquake conventional wisdom was that large earthquakes in the Bay area occurred as horizontal displacements on predominantly vertical faults. * The fault segment that ruptured approximately coincided with a fault segment identified in 1988 as having a 30% probability of generating a M7 earthquake in the next 30 years. This was one of more than 20 relevant earthquake forecasts made in the 83 years before the earthquake. * Calculations show that the Loma Prieta earthquake changed stresses on nearby faults in the Bay area. In particular, the earthquake reduced stresses on the Hayward Fault which decreased the frequency of small earthquakes on it. * Geological and geophysical mapping indicate that, although the San Andreas Fault can be mapped as a through going fault in the epicentral region, the southwest dipping Loma Prieta rupture surface is a separate fault strand and one of several along this part of the San Andreas that may be capable of generating earthquakes.

A Bayesian Assessment of Seismic Semi-Periodicity Forecasts

NASA Astrophysics Data System (ADS)

Nava, F.; Quinteros, C.; Glowacka, E.; Frez, J.

2016-01-01

Among the schemes for earthquake forecasting, the search for semi-periodicity during large earthquakes in a given seismogenic region plays an important role. When considering earthquake forecasts based on semi-periodic sequence identification, the Bayesian formalism is a useful tool for: (1) assessing how well a given earthquake satisfies a previously made forecast; (2) re-evaluating the semi-periodic sequence probability; and (3) testing other prior estimations of the sequence probability. A comparison of Bayesian estimates with updated estimates of semi-periodic sequences that incorporate new data not used in the original estimates shows extremely good agreement, indicating that: (1) the probability that a semi-periodic sequence is not due to chance is an appropriate estimate for the prior sequence probability estimate; and (2) the Bayesian formalism does a very good job of estimating corrected semi-periodicity probabilities, using slightly less data than that used for updated estimates. The Bayesian approach is exemplified explicitly by its application to the Parkfield semi-periodic forecast, and results are given for its application to other forecasts in Japan and Venezuela.

On some methods for assessing earthquake predictions

NASA Astrophysics Data System (ADS)

Molchan, G.; Romashkova, L.; Peresan, A.

2017-09-01

A regional approach to the problem of assessing earthquake predictions inevitably faces a deficit of data. We point out some basic limits of assessment methods reported in the literature, considering the practical case of the performance of the CN pattern recognition method in the prediction of large Italian earthquakes. Along with the classical hypothesis testing, a new game approach, the so-called parimutuel gambling (PG) method, is examined. The PG, originally proposed for the evaluation of the probabilistic earthquake forecast, has been recently adapted for the case of 'alarm-based' CN prediction. The PG approach is a non-standard method; therefore it deserves careful examination and theoretical analysis. We show that the PG alarm-based version leads to an almost complete loss of information about predicted earthquakes (even for a large sample). As a result, any conclusions based on the alarm-based PG approach are not to be trusted. We also show that the original probabilistic PG approach does not necessarily identifies the genuine forecast correctly among competing seismicity rate models, even when applied to extensive data.

A prototype operational earthquake loss model for California based on UCERF3-ETAS – A first look at valuation

USGS Publications Warehouse

Field, Edward; Porter, Keith; Milner, Kevn

2017-01-01

We present a prototype operational loss model based on UCERF3-ETAS, which is the third Uniform California Earthquake Rupture Forecast with an Epidemic Type Aftershock Sequence (ETAS) component. As such, UCERF3-ETAS represents the first earthquake forecast to relax fault segmentation assumptions and to include multi-fault ruptures, elastic-rebound, and spatiotemporal clustering, all of which seem important for generating realistic and useful aftershock statistics. UCERF3-ETAS is nevertheless an approximation of the system, however, so usefulness will vary and potential value needs to be ascertained in the context of each application. We examine this question with respect to statewide loss estimates, exemplifying how risk can be elevated by orders of magnitude due to triggered events following various scenario earthquakes. Two important considerations are the probability gains, relative to loss likelihoods in the absence of main shocks, and the rapid decay of gains with time. Significant uncertainties and model limitations remain, so we hope this paper will inspire similar analyses with respect to other risk metrics to help ascertain whether operationalization of UCERF3-ETAS would be worth the considerable resources required.

Earthquake outlook for the San Francisco Bay region 2014–2043

USGS Publications Warehouse

Aagaard, Brad T.; Blair, James Luke; Boatwright, John; Garcia, Susan H.; Harris, Ruth A.; Michael, Andrew J.; Schwartz, David P.; DiLeo, Jeanne S.; Jacques, Kate; Donlin, Carolyn

2016-06-13

Using information from recent earthquakes, improved mapping of active faults, and a new model for estimating earthquake probabilities, the 2014 Working Group on California Earthquake Probabilities updated the 30-year earthquake forecast for California. They concluded that there is a 72 percent probability (or likelihood) of at least one earthquake of magnitude 6.7 or greater striking somewhere in the San Francisco Bay region before 2043. Earthquakes this large are capable of causing widespread damage; therefore, communities in the region should take simple steps to help reduce injuries, damage, and disruption, as well as accelerate recovery from these earthquakes.

From integrated observation of pre-earthquake signals towards physical-based forecasting: A prospective test experiment

NASA Astrophysics Data System (ADS)

Ouzounov, D.; Pulinets, S. A.; Tramutoli, V.; Lee, L.; Liu, J. G.; Hattori, K.; Kafatos, M.

2013-12-01

We are conducting an integrated study involving multi-parameter observations over different seismo- tectonics regions in our investigation of phenomena preceding major earthquakes. Our approach is based on a systematic analysis of several selected parameters namely: gas discharge; thermal infrared radiation; ionospheric electron concentration; and atmospheric temperature and humidity, which we suppose are associated with earthquake preparation phase. We intended to test in prospective mode the set of geophysical measurements for different regions of active earthquakes and volcanoes. In 2012-13 we established a collaborative framework with the leading projects PRE-EARTHQUAKE (EU) and iSTEP3 (Taiwan) for coordinate measurements and prospective validation over seven test regions: Southern California (USA), Eastern Honshu (Japan), Italy, Turkey, Greece, Taiwan (ROC), Kamchatka and Sakhalin (Russia). The current experiment provided a 'stress test' opportunity to validate the physical based approach in teal -time over regions of high seismicity. Our initial results are: (1) Prospective tests have shown the presence in real time of anomalies in the atmosphere before most of the significant (M>5.5) earthquakes in all regions; (2) False positive rate alarm is different for each region and varying between 50% (Italy, Kamchatka and California) to 25% (Taiwan and Japan) with a significant reduction of false positives when at least two parameters are contemporary used; (3) One of most complex problem, which is still open, was the systematic collection and real-time integration of pre-earthquake observations. Our findings suggest that the physical based short-term forecast is feasible and more tests are needed. We discus the physical concept we used, the future integration of data observations and related developments.

A Brownian model for recurrent earthquakes

USGS Publications Warehouse

Matthews, M.V.; Ellsworth, W.L.; Reasenberg, P.A.

2002-01-01

We construct a probability model for rupture times on a recurrent earthquake source. Adding Brownian perturbations to steady tectonic loading produces a stochastic load-state process. Rupture is assumed to occur when this process reaches a critical-failure threshold. An earthquake relaxes the load state to a characteristic ground level and begins a new failure cycle. The load-state process is a Brownian relaxation oscillator. Intervals between events have a Brownian passage-time distribution that may serve as a temporal model for time-dependent, long-term seismic forecasting. This distribution has the following noteworthy properties: (1) the probability of immediate rerupture is zero; (2) the hazard rate increases steadily from zero at t = 0 to a finite maximum near the mean recurrence time and then decreases asymptotically to a quasi-stationary level, in which the conditional probability of an event becomes time independent; and (3) the quasi-stationary failure rate is greater than, equal to, or less than the mean failure rate because the coefficient of variation is less than, equal to, or greater than 1/???2 ??? 0.707. In addition, the model provides expressions for the hazard rate and probability of rupture on faults for which only a bound can be placed on the time of the last rupture. The Brownian relaxation oscillator provides a connection between observable event times and a formal state variable that reflects the macromechanics of stress and strain accumulation. Analysis of this process reveals that the quasi-stationary distance to failure has a gamma distribution, and residual life has a related exponential distribution. It also enables calculation of "interaction" effects due to external perturbations to the state, such as stress-transfer effects from earthquakes outside the target source. The influence of interaction effects on recurrence times is transient and strongly dependent on when in the loading cycle step pertubations occur. Transient effects may

Probability estimates of seismic event occurrence compared to health hazards - Forecasting Taipei's Earthquakes

NASA Astrophysics Data System (ADS)

Fung, D. C. N.; Wang, J. P.; Chang, S. H.; Chang, S. C.

2014-12-01

Using a revised statistical model built on past seismic probability models, the probability of different magnitude earthquakes occurring within variable timespans can be estimated. The revised model is based on Poisson distribution and includes the use of best-estimate values of the probability distribution of different magnitude earthquakes recurring from a fault from literature sources. Our study aims to apply this model to the Taipei metropolitan area with a population of 7 million, which lies in the Taipei Basin and is bounded by two normal faults: the Sanchaio and Taipei faults. The Sanchaio fault is suggested to be responsible for previous large magnitude earthquakes, such as the 1694 magnitude 7 earthquake in northwestern Taipei (Cheng et. al., 2010). Based on a magnitude 7 earthquake return period of 543 years, the model predicts the occurrence of a magnitude 7 earthquake within 20 years at 1.81%, within 79 years at 6.77% and within 300 years at 21.22%. These estimates increase significantly when considering a magnitude 6 earthquake; the chance of one occurring within the next 20 years is estimated to be 3.61%, 79 years at 13.54% and 300 years at 42.45%. The 79 year period represents the average lifespan of the Taiwan population. In contrast, based on data from 2013, the probability of Taiwan residents experiencing heart disease or malignant neoplasm is 11.5% and 29%. The inference of this study is that the calculated risk that the Taipei population is at from a potentially damaging magnitude 6 or greater earthquake occurring within their lifetime is just as great as of suffering from a heart attack or other health ailments.

Earthquake precursors: spatial-temporal gravity changes before the great earthquakes in the Sichuan-Yunnan area

NASA Astrophysics Data System (ADS)

Zhu, Yi-Qing; Liang, Wei-Feng; Zhang, Song

2018-01-01

Using multiple-scale mobile gravity data in the Sichuan-Yunnan area, we systematically analyzed the relationships between spatial-temporal gravity changes and the 2014 Ludian, Yunnan Province Ms6.5 earthquake and the 2014 Kangding Ms6.3, 2013 Lushan Ms7.0, and 2008 Wenchuan Ms8.0 earthquakes in Sichuan Province. Our main results are as follows. (1) Before the occurrence of large earthquakes, gravity anomalies occur in a large area around the epicenters. The directions of gravity change gradient belts usually agree roughly with the directions of the main fault zones of the study area. Such gravity changes might reflect the increase of crustal stress, as well as the significant active tectonic movements and surface deformations along fault zones, during the period of gestation of great earthquakes. (2) Continuous significant changes of the multiple-scale gravity fields, as well as greater gravity changes with larger time scales, can be regarded as medium-range precursors of large earthquakes. The subsequent large earthquakes always occur in the area where the gravity changes greatly. (3) The spatial-temporal gravity changes are very useful in determining the epicenter of coming large earthquakes. The large gravity networks are useful to determine the general areas of coming large earthquakes. However, the local gravity networks with high spatial-temporal resolution are suitable for determining the location of epicenters. Therefore, denser gravity observation networks are necessary for better forecasts of the epicenters of large earthquakes. (4) Using gravity changes from mobile observation data, we made medium-range forecasts of the Kangding, Ludian, Lushan, and Wenchuan earthquakes, with especially successful forecasts of the location of their epicenters. Based on the above discussions, we emphasize that medium-/long-term potential for large earthquakes might exist nowadays in some areas with significant gravity anomalies in the study region. Thus, the monitoring

Optimal Scaling of Aftershock Zones using Ground Motion Forecasts

NASA Astrophysics Data System (ADS)

Wilson, John Max; Yoder, Mark R.; Rundle, John B.

2018-02-01

The spatial distribution of aftershocks following major earthquakes has received significant attention due to the shaking hazard these events pose for structures and populations in the affected region. Forecasting the spatial distribution of aftershock events is an important part of the estimation of future seismic hazard. A simple spatial shape for the zone of activity has often been assumed in the form of an ellipse having semimajor axis to semiminor axis ratio of 2.0. However, since an important application of these calculations is the estimation of ground shaking hazard, an effective criterion for forecasting future aftershock impacts is to use ground motion prediction equations (GMPEs) in addition to the more usual approach of using epicentral or hypocentral locations. Based on these ideas, we present an aftershock model that uses self-similarity and scaling relations to constrain parameters as an option for such hazard assessment. We fit the spatial aspect ratio to previous earthquake sequences in the studied regions, and demonstrate the effect of the fitting on the likelihood of post-disaster ground motion forecasts for eighteen recent large earthquakes. We find that the forecasts in most geographic regions studied benefit from this optimization technique, while some are better suited to the use of the a priori aspect ratio.

Nowcasting Earthquakes and Tsunamis

NASA Astrophysics Data System (ADS)

Rundle, J. B.; Turcotte, D. L.

2017-12-01

The term "nowcasting" refers to the estimation of the current uncertain state of a dynamical system, whereas "forecasting" is a calculation of probabilities of future state(s). Nowcasting is a term that originated in economics and finance, referring to the process of determining the uncertain state of the economy or market indicators such as GDP at the current time by indirect means. We have applied this idea to seismically active regions, where the goal is to determine the current state of a system of faults, and its current level of progress through the earthquake cycle (http://onlinelibrary.wiley.com/doi/10.1002/2016EA000185/full). Advantages of our nowcasting method over forecasting models include: 1) Nowcasting is simply data analysis and does not involve a model having parameters that must be fit to data; 2) We use only earthquake catalog data which generally has known errors and characteristics; and 3) We use area-based analysis rather than fault-based analysis, meaning that the methods work equally well on land and in subduction zones. To use the nowcast method to estimate how far the fault system has progressed through the "cycle" of large recurring earthquakes, we use the global catalog of earthquakes, using "small" earthquakes to determine the level of hazard from "large" earthquakes in the region. We select a "small" region in which the nowcast is to be made, and compute the statistics of a much larger region around the small region. The statistics of the large region are then applied to the small region. For an application, we can define a small region around major global cities, for example a "small" circle of radius 150 km and a depth of 100 km, as well as a "large" earthquake magnitude, for example M6.0. The region of influence of such earthquakes is roughly 150 km radius x 100 km depth, which is the reason these values were selected. We can then compute and rank the seismic risk of the world's major cities in terms of their relative seismic risk

The nature of earthquake prediction

USGS Publications Warehouse

Lindh, A.G.

1991-01-01

Earthquake prediction is inherently statistical. Although some people continue to think of earthquake prediction as the specification of the time, place, and magnitude of a future earthquake, it has been clear for at least a decade that this is an unrealistic and unreasonable definition. the reality is that earthquake prediction starts from the long-term forecasts of place and magnitude, with very approximate time constraints, and progresses, at least in principle, to a gradual narrowing of the time window as data and understanding permit. Primitive long-term forecasts are clearly possible at this time on a few well-characterized fault systems. Tightly focuses monitoring experiments aimed at short-term prediction are already underway in Parkfield, California, and in the Tokai region in Japan; only time will tell how much progress will be possible. 

Real-time forecasting and predictability of catastrophic failure events: from rock failure to volcanoes and earthquakes

NASA Astrophysics Data System (ADS)

Main, I. G.; Bell, A. F.; Naylor, M.; Atkinson, M.; Filguera, R.; Meredith, P. G.; Brantut, N.

2012-12-01

Accurate prediction of catastrophic brittle failure in rocks and in the Earth presents a significant challenge on theoretical and practical grounds. The governing equations are not known precisely, but are known to produce highly non-linear behavior similar to those of near-critical dynamical systems, with a large and irreducible stochastic component due to material heterogeneity. In a laboratory setting mechanical, hydraulic and rock physical properties are known to change in systematic ways prior to catastrophic failure, often with significant non-Gaussian fluctuations about the mean signal at a given time, for example in the rate of remotely-sensed acoustic emissions. The effectiveness of such signals in real-time forecasting has never been tested before in a controlled laboratory setting, and previous work has often been qualitative in nature, and subject to retrospective selection bias, though it has often been invoked as a basis in forecasting natural hazard events such as volcanoes and earthquakes. Here we describe a collaborative experiment in real-time data assimilation to explore the limits of predictability of rock failure in a best-case scenario. Data are streamed from a remote rock deformation laboratory to a user-friendly portal, where several proposed physical/stochastic models can be analysed in parallel in real time, using a variety of statistical fitting techniques, including least squares regression, maximum likelihood fitting, Markov-chain Monte-Carlo and Bayesian analysis. The results are posted and regularly updated on the web site prior to catastrophic failure, to ensure a true and and verifiable prospective test of forecasting power. Preliminary tests on synthetic data with known non-Gaussian statistics shows how forecasting power is likely to evolve in the live experiments. In general the predicted failure time does converge on the real failure time, illustrating the bias associated with the 'benefit of hindsight' in retrospective analyses

Long-range dependence in earthquake-moment release and implications for earthquake occurrence probability.

PubMed

Barani, Simone; Mascandola, Claudia; Riccomagno, Eva; Spallarossa, Daniele; Albarello, Dario; Ferretti, Gabriele; Scafidi, Davide; Augliera, Paolo; Massa, Marco

2018-03-28

Since the beginning of the 1980s, when Mandelbrot observed that earthquakes occur on 'fractal' self-similar sets, many studies have investigated the dynamical mechanisms that lead to self-similarities in the earthquake process. Interpreting seismicity as a self-similar process is undoubtedly convenient to bypass the physical complexities related to the actual process. Self-similar processes are indeed invariant under suitable scaling of space and time. In this study, we show that long-range dependence is an inherent feature of the seismic process, and is universal. Examination of series of cumulative seismic moment both in Italy and worldwide through Hurst's rescaled range analysis shows that seismicity is a memory process with a Hurst exponent H ≈ 0.87. We observe that H is substantially space- and time-invariant, except in cases of catalog incompleteness. This has implications for earthquake forecasting. Hence, we have developed a probability model for earthquake occurrence that allows for long-range dependence in the seismic process. Unlike the Poisson model, dependent events are allowed. This model can be easily transferred to other disciplines that deal with self-similar processes.

Real-time forecasting of the April 11, 2012 Sumatra tsunami

USGS Publications Warehouse

Wang, Dailin; Becker, Nathan C.; Walsh, David; Fryer, Gerard J.; Weinstein, Stuart A.; McCreery, Charles S.; ,

2012-01-01

The April 11, 2012, magnitude 8.6 earthquake off the northern coast of Sumatra generated a tsunami that was recorded at sea-level stations as far as 4800 km from the epicenter and at four ocean bottom pressure sensors (DARTs) in the Indian Ocean. The governments of India, Indonesia, Sri Lanka, Thailand, and Maldives issued tsunami warnings for their coastlines. The United States' Pacific Tsunami Warning Center (PTWC) issued an Indian Ocean-wide Tsunami Watch Bulletin in its role as an Interim Service Provider for the region. Using an experimental real-time tsunami forecast model (RIFT), PTWC produced a series of tsunami forecasts during the event that were based on rapidly derived earthquake parameters, including initial location and Mwp magnitude estimates and the W-phase centroid moment tensor solutions (W-phase CMTs) obtained at PTWC and at the U. S. Geological Survey (USGS). We discuss the real-time forecast methodology and how successive, real-time tsunami forecasts using the latest W-phase CMT solutions improved the accuracy of the forecast.

Real-time Mainshock Forecast by Statistical Discrimination of Foreshock Clusters

NASA Astrophysics Data System (ADS)

Nomura, S.; Ogata, Y.

2016-12-01

Foreshock discremination is one of the most effective ways for short-time forecast of large main shocks. Though many large earthquakes accompany their foreshocks, discreminating them from enormous small earthquakes is difficult and only probabilistic evaluation from their spatio-temporal features and magnitude evolution may be available. Logistic regression is the statistical learning method best suited to such binary pattern recognition problems where estimates of a-posteriori probability of class membership are required. Statistical learning methods can keep learning discreminating features from updating catalog and give probabilistic recognition of forecast in real time. We estimated a non-linear function of foreshock proportion by smooth spline bases and evaluate the possibility of foreshocks by the logit function. In this study, we classified foreshocks from earthquake catalog by the Japan Meteorological Agency by single-link clustering methods and learned spatial and temporal features of foreshocks by the probability density ratio estimation. We use the epicentral locations, time spans and difference in magnitudes for learning and forecasting. Magnitudes of main shocks are also predicted our method by incorporating b-values into our method. We discuss the spatial pattern of foreshocks from the classifier composed by our model. We also implement a back test to validate predictive performance of the model by this catalog.

A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale

NASA Astrophysics Data System (ADS)

Zhang, Shaojie; Zhao, Luqiang; Delgado-Tellez, Ricardo; Bao, Hongjun

2018-03-01

Conventional outputs of physics-based landslide forecasting models are presented as deterministic warnings by calculating the safety factor (Fs) of potentially dangerous slopes. However, these models are highly dependent on variables such as cohesion force and internal friction angle which are affected by a high degree of uncertainty especially at a regional scale, resulting in unacceptable uncertainties of Fs. Under such circumstances, the outputs of physical models are more suitable if presented in the form of landslide probability values. In order to develop such models, a method to link the uncertainty of soil parameter values with landslide probability is devised. This paper proposes the use of Monte Carlo methods to quantitatively express uncertainty by assigning random values to physical variables inside a defined interval. The inequality Fs < 1 is tested for each pixel in n simulations which are integrated in a unique parameter. This parameter links the landslide probability to the uncertainties of soil mechanical parameters and is used to create a physics-based probabilistic forecasting model for rainfall-induced shallow landslides. The prediction ability of this model was tested in a case study, in which simulated forecasting of landslide disasters associated with heavy rainfalls on 9 July 2013 in the Wenchuan earthquake region of Sichuan province, China, was performed. The proposed model successfully forecasted landslides in 159 of the 176 disaster points registered by the geo-environmental monitoring station of Sichuan province. Such testing results indicate that the new model can be operated in a highly efficient way and show more reliable results, attributable to its high prediction accuracy. Accordingly, the new model can be potentially packaged into a forecasting system for shallow landslides providing technological support for the mitigation of these disasters at regional scale.

Fixed recurrence and slip models better predict earthquake behavior than the time- and slip-predictable models: 2. Laboratory earthquakes

NASA Astrophysics Data System (ADS)

Rubinstein, Justin L.; Ellsworth, William L.; Beeler, Nicholas M.; Kilgore, Brian D.; Lockner, David A.; Savage, Heather M.

2012-02-01

The behavior of individual stick-slip events observed in three different laboratory experimental configurations is better explained by a "memoryless" earthquake model with fixed inter-event time or fixed slip than it is by the time- and slip-predictable models for earthquake occurrence. We make similar findings in the companion manuscript for the behavior of natural repeating earthquakes. Taken together, these results allow us to conclude that the predictions of a characteristic earthquake model that assumes either fixed slip or fixed recurrence interval should be preferred to the predictions of the time- and slip-predictable models for all earthquakes. Given that the fixed slip and recurrence models are the preferred models for all of the experiments we examine, we infer that in an event-to-event sense the elastic rebound model underlying the time- and slip-predictable models does not explain earthquake behavior. This does not indicate that the elastic rebound model should be rejected in a long-term-sense, but it should be rejected for short-term predictions. The time- and slip-predictable models likely offer worse predictions of earthquake behavior because they rely on assumptions that are too simple to explain the behavior of earthquakes. Specifically, the time-predictable model assumes a constant failure threshold and the slip-predictable model assumes that there is a constant minimum stress. There is experimental and field evidence that these assumptions are not valid for all earthquakes.

Rapid modeling of complex multi-fault ruptures with simplistic models from real-time GPS: Perspectives from the 2016 Mw 7.8 Kaikoura earthquake

NASA Astrophysics Data System (ADS)

Crowell, B.; Melgar, D.

2017-12-01

The 2016 Mw 7.8 Kaikoura earthquake is one of the most complex earthquakes in recent history, rupturing across at least 10 disparate faults with varying faulting styles, and exhibiting intricate surface deformation patterns. The complexity of this event has motivated the need for multidisciplinary geophysical studies to get at the underlying source physics to better inform earthquake hazards models in the future. However, events like Kaikoura beg the question of how well (or how poorly) such earthquakes can be modeled automatically in real-time and still satisfy the general public and emergency managers. To investigate this question, we perform a retrospective real-time GPS analysis of the Kaikoura earthquake with the G-FAST early warning module. We first perform simple point source models of the earthquake using peak ground displacement scaling and a coseismic offset based centroid moment tensor (CMT) inversion. We predict ground motions based on these point sources as well as simple finite faults determined from source scaling studies, and validate against true recordings of peak ground acceleration and velocity. Secondly, we perform a slip inversion based upon the CMT fault orientations and forward model near-field tsunami maximum expected wave heights to compare against available tide gauge records. We find remarkably good agreement between recorded and predicted ground motions when using a simple fault plane, with the majority of disagreement in ground motions being attributable to local site effects, not earthquake source complexity. Similarly, the near-field tsunami maximum amplitude predictions match tide gauge records well. We conclude that even though our models for the Kaikoura earthquake are devoid of rich source complexities, the CMT driven finite fault is a good enough "average" source and provides useful constraints for rapid forecasting of ground motion and near-field tsunami amplitudes.

Earthquakes Magnitude Predication Using Artificial Neural Network in Northern Red Sea Area

NASA Astrophysics Data System (ADS)

Alarifi, A. S.; Alarifi, N. S.

2009-12-01

Earthquakes are natural hazards that do not happen very often, however they may cause huge losses in life and property. Early preparation for these hazards is a key factor to reduce their damage and consequence. Since early ages, people tried to predicate earthquakes using simple observations such as strange or a typical animal behavior. In this paper, we study data collected from existing earthquake catalogue to give better forecasting for future earthquakes. The 16000 events cover a time span of 1970 to 2009, the magnitude range from greater than 0 to less than 7.2 while the depth range from greater than 0 to less than 100km. We propose a new artificial intelligent predication system based on artificial neural network, which can be used to predicate the magnitude of future earthquakes in northern Red Sea area including the Sinai Peninsula, the Gulf of Aqaba, and the Gulf of Suez. We propose a feed forward new neural network model with multi-hidden layers to predicate earthquakes occurrences and magnitudes in northern Red Sea area. Although there are similar model that have been published before in different areas, to our best knowledge this is the first neural network model to predicate earthquake in northern Red Sea area. Furthermore, we present other forecasting methods such as moving average over different interval, normally distributed random predicator, and uniformly distributed random predicator. In addition, we present different statistical methods and data fitting such as linear, quadratic, and cubic regression. We present a details performance analyses of the proposed methods for different evaluation metrics. The results show that neural network model provides higher forecast accuracy than other proposed methods. The results show that neural network achieves an average absolute error of 2.6% while an average absolute error of 3.8%, 7.3% and 6.17% for moving average, linear regression and cubic regression, respectively. In this work, we show an analysis

Introduction to the special issue on the 2004 Parkfield earthquake and the Parkfield earthquake prediction experiment

USGS Publications Warehouse

Harris, R.A.; Arrowsmith, J.R.

2006-01-01

The 28 September 2004 M 6.0 Parkfield earthquake, a long-anticipated event on the San Andreas fault, is the world's best recorded earthquake to date, with state-of-the-art data obtained from geologic, geodetic, seismic, magnetic, and electrical field networks. This has allowed the preearthquake and postearthquake states of the San Andreas fault in this region to be analyzed in detail. Analyses of these data provide views into the San Andreas fault that show a complex geologic history, fault geometry, rheology, and response of the nearby region to the earthquake-induced ground movement. Although aspects of San Andreas fault zone behavior in the Parkfield region can be modeled simply over geological time frames, the Parkfield Earthquake Prediction Experiment and the 2004 Parkfield earthquake indicate that predicting the fine details of future earthquakes is still a challenge. Instead of a deterministic approach, forecasting future damaging behavior, such as that caused by strong ground motions, will likely continue to require probabilistic methods. However, the Parkfield Earthquake Prediction Experiment and the 2004 Parkfield earthquake have provided ample data to understand most of what did occur in 2004, culminating in significant scientific advances.

M≥7 Earthquake rupture forecast and time-dependent probability for the Sea of Marmara region, Turkey

USGS Publications Warehouse

Murru, Maura; Akinci, Aybige; Falcone, Guiseppe; Pucci, Stefano; Console, Rodolfo; Parsons, Thomas E.

2016-01-01

We forecast time-independent and time-dependent earthquake ruptures in the Marmara region of Turkey for the next 30 years using a new fault-segmentation model. We also augment time-dependent Brownian Passage Time (BPT) probability with static Coulomb stress changes (ΔCFF) from interacting faults. We calculate Mw > 6.5 probability from 26 individual fault sources in the Marmara region. We also consider a multisegment rupture model that allows higher-magnitude ruptures over some segments of the Northern branch of the North Anatolian Fault Zone (NNAF) beneath the Marmara Sea. A total of 10 different Mw=7.0 to Mw=8.0 multisegment ruptures are combined with the other regional faults at rates that balance the overall moment accumulation. We use Gaussian random distributions to treat parameter uncertainties (e.g., aperiodicity, maximum expected magnitude, slip rate, and consequently mean recurrence time) of the statistical distributions associated with each fault source. We then estimate uncertainties of the 30-year probability values for the next characteristic event obtained from three different models (Poisson, BPT, and BPT+ΔCFF) using a Monte Carlo procedure. The Gerede fault segment located at the eastern end of the Marmara region shows the highest 30-yr probability, with a Poisson value of 29%, and a time-dependent interaction probability of 48%. We find an aggregated 30-yr Poisson probability of M >7.3 earthquakes at Istanbul of 35%, which increases to 47% if time dependence and stress transfer are considered. We calculate a 2-fold probability gain (ratio time-dependent to time-independent) on the southern strands of the North Anatolian Fault Zone.

Significance of stress transfer in time-dependent earthquake probability calculations

USGS Publications Warehouse

Parsons, T.

2005-01-01

A sudden change in stress is seen to modify earthquake rates, but should it also revise earthquake probability? Data used to derive input parameters permits an array of forecasts; so how large a static stress change is require to cause a statistically significant earthquake probability change? To answer that question, effects of parameter and philosophical choices are examined through all phases of sample calculations, Drawing at random from distributions of recurrence-aperiodicity pairs identifies many that recreate long paleoseismic and historic earthquake catalogs. Probability density funtions built from the recurrence-aperiodicity pairs give the range of possible earthquake forecasts under a point process renewal model. Consequences of choices made in stress transfer calculations, such as different slip models, fault rake, dip, and friction are, tracked. For interactions among large faults, calculated peak stress changes may be localized, with most of the receiving fault area changed less than the mean. Thus, to avoid overstating probability change on segments, stress change values should be drawn from a distribution reflecting the spatial pattern rather than using the segment mean. Disparity resulting from interaction probability methodology is also examined. For a fault with a well-understood earthquake history, a minimum stress change to stressing rate ratio of 10:1 to 20:1 is required to significantly skew probabilities with >80-85% confidence. That ratio must be closer to 50:1 to exceed 90-95% confidence levels. Thus revision to earthquake probability is achievable when a perturbing event is very close to the fault in question or the tectonic stressing rate is low.

Tsunami Forecast Progress Five Years After Indonesian Disaster

NASA Astrophysics Data System (ADS)

Titov, Vasily V.; Bernard, Eddie N.; Weinstein, Stuart A.; Kanoglu, Utku; Synolakis, Costas E.

2010-05-01

Almost five years after the 26 December 2004 Indian Ocean tragedy, tsunami warnings are finally benefiting from decades of research toward effective model-based forecasts. Since the 2004 tsunami, two seminal advances have been (i) deep-ocean tsunami measurements with tsunameters and (ii) their use in accurately forecasting tsunamis after the tsunami has been generated. Using direct measurements of deep-ocean tsunami heights, assimilated into numerical models for specific locations, greatly improves the real-time forecast accuracy over earthquake-derived magnitude estimates of tsunami impact. Since 2003, this method has been used to forecast tsunamis at specific harbors for different events in the Pacific and Indian Oceans. Recent tsunamis illustrated how this technology is being adopted in global tsunami warning operations. The U.S. forecasting system was used by both research and operations to evaluate the tsunami hazard. Tests demonstrated the effectiveness of operational tsunami forecasting using real-time deep-ocean data assimilated into forecast models. Several examples also showed potential of distributed forecast tools. With IOC and USAID funding, NOAA researchers at PMEL developed the Community Model Interface for Tsunami (ComMIT) tool and distributed it through extensive capacity-building sessions in the Indian Ocean. Over hundred scientists have been trained in tsunami inundation mapping, leading to the first generation of inundation models for many Indian Ocean shorelines. These same inundation models can also be used for real-time tsunami forecasts as was demonstrated during several events. Contact Information Vasily V. Titov, Seattle, Washington, USA, 98115

Evaluating spatial and temporal relationships between an earthquake cluster near Entiat, central Washington, and the large December 1872 Entiat earthquake

USGS Publications Warehouse

Brocher, Thomas M.; Blakely, Richard J.; Sherrod, Brian

2017-01-01

We investigate spatial and temporal relations between an ongoing and prolific seismicity cluster in central Washington, near Entiat, and the 14 December 1872 Entiat earthquake, the largest historic crustal earthquake in Washington. A fault scarp produced by the 1872 earthquake lies within the Entiat cluster; the locations and areas of both the cluster and the estimated 1872 rupture surface are comparable. Seismic intensities and the 1–2 m of coseismic displacement suggest a magnitude range between 6.5 and 7.0 for the 1872 earthquake. Aftershock forecast models for (1) the first several hours following the 1872 earthquake, (2) the largest felt earthquakes from 1900 to 1974, and (3) the seismicity within the Entiat cluster from 1976 through 2016 are also consistent with this magnitude range. Based on this aftershock modeling, most of the current seismicity in the Entiat cluster could represent aftershocks of the 1872 earthquake. Other earthquakes, especially those with long recurrence intervals, have long‐lived aftershock sequences, including the Mw">MwMw 7.5 1891 Nobi earthquake in Japan, with aftershocks continuing 100 yrs after the mainshock. Although we do not rule out ongoing tectonic deformation in this region, a long‐lived aftershock sequence can account for these observations.

Large earthquake rates from geologic, geodetic, and seismological perspectives

NASA Astrophysics Data System (ADS)

Jackson, D. D.

2017-12-01

Earthquake rate and recurrence information comes primarily from geology, geodesy, and seismology. Geology gives the longest temporal perspective, but it reveals only surface deformation, relatable to earthquakes only with many assumptions. Geodesy is also limited to surface observations, but it detects evidence of the processes leading to earthquakes, again subject to important assumptions. Seismology reveals actual earthquakes, but its history is too short to capture important properties of very large ones. Unfortunately, the ranges of these observation types barely overlap, so that integrating them into a consistent picture adequate to infer future prospects requires a great deal of trust. Perhaps the most important boundary is the temporal one at the beginning of the instrumental seismic era, about a century ago. We have virtually no seismological or geodetic information on large earthquakes before then, and little geological information after. Virtually all-modern forecasts of large earthquakes assume some form of equivalence between tectonic- and seismic moment rates as functions of location, time, and magnitude threshold. That assumption links geology, geodesy, and seismology, but it invokes a host of other assumptions and incurs very significant uncertainties. Questions include temporal behavior of seismic and tectonic moment rates; shape of the earthquake magnitude distribution; upper magnitude limit; scaling between rupture length, width, and displacement; depth dependence of stress coupling; value of crustal rigidity; and relation between faults at depth and their surface fault traces, to name just a few. In this report I'll estimate the quantitative implications for estimating large earthquake rate. Global studies like the GEAR1 project suggest that surface deformation from geology and geodesy best show the geography of very large, rare earthquakes in the long term, while seismological observations of small earthquakes best forecasts moderate earthquakes

Parallelization of the Coupled Earthquake Model

NASA Technical Reports Server (NTRS)

Block, Gary; Li, P. Peggy; Song, Yuhe T.

2007-01-01

This Web-based tsunami simulation system allows users to remotely run a model on JPL s supercomputers for a given undersea earthquake. At the time of this reporting, predicting tsunamis on the Internet has never happened before. This new code directly couples the earthquake model and the ocean model on parallel computers and improves simulation speed. Seismometers can only detect information from earthquakes; they cannot detect whether or not a tsunami may occur as a result of the earthquake. When earthquake-tsunami models are coupled with the improved computational speed of modern, high-performance computers and constrained by remotely sensed data, they are able to provide early warnings for those coastal regions at risk. The software is capable of testing NASA s satellite observations of tsunamis. It has been successfully tested for several historical tsunamis, has passed all alpha and beta testing, and is well documented for users.

Evaluation of statistical models for forecast errors from the HBV model

NASA Astrophysics Data System (ADS)

Engeland, Kolbjørn; Renard, Benjamin; Steinsland, Ingelin; Kolberg, Sjur

2010-04-01

SummaryThree statistical models for the forecast errors for inflow into the Langvatn reservoir in Northern Norway have been constructed and tested according to the agreement between (i) the forecast distribution and the observations and (ii) median values of the forecast distribution and the observations. For the first model observed and forecasted inflows were transformed by the Box-Cox transformation before a first order auto-regressive model was constructed for the forecast errors. The parameters were conditioned on weather classes. In the second model the Normal Quantile Transformation (NQT) was applied on observed and forecasted inflows before a similar first order auto-regressive model was constructed for the forecast errors. For the third model positive and negative errors were modeled separately. The errors were first NQT-transformed before conditioning the mean error values on climate, forecasted inflow and yesterday's error. To test the three models we applied three criterions: we wanted (a) the forecast distribution to be reliable; (b) the forecast intervals to be narrow; (c) the median values of the forecast distribution to be close to the observed values. Models 1 and 2 gave almost identical results. The median values improved the forecast with Nash-Sutcliffe R eff increasing from 0.77 for the original forecast to 0.87 for the corrected forecasts. Models 1 and 2 over-estimated the forecast intervals but gave the narrowest intervals. Their main drawback was that the distributions are less reliable than Model 3. For Model 3 the median values did not fit well since the auto-correlation was not accounted for. Since Model 3 did not benefit from the potential variance reduction that lies in bias estimation and removal it gave on average wider forecasts intervals than the two other models. At the same time Model 3 on average slightly under-estimated the forecast intervals, probably explained by the use of average measures to evaluate the fit.

Fixed recurrence and slip models better predict earthquake behavior than the time- and slip-predictable models 1: repeating earthquakes

USGS Publications Warehouse

Rubinstein, Justin L.; Ellsworth, William L.; Chen, Kate Huihsuan; Uchida, Naoki

2012-01-01

The behavior of individual events in repeating earthquake sequences in California, Taiwan and Japan is better predicted by a model with fixed inter-event time or fixed slip than it is by the time- and slip-predictable models for earthquake occurrence. Given that repeating earthquakes are highly regular in both inter-event time and seismic moment, the time- and slip-predictable models seem ideally suited to explain their behavior. Taken together with evidence from the companion manuscript that shows similar results for laboratory experiments we conclude that the short-term predictions of the time- and slip-predictable models should be rejected in favor of earthquake models that assume either fixed slip or fixed recurrence interval. This implies that the elastic rebound model underlying the time- and slip-predictable models offers no additional value in describing earthquake behavior in an event-to-event sense, but its value in a long-term sense cannot be determined. These models likely fail because they rely on assumptions that oversimplify the earthquake cycle. We note that the time and slip of these events is predicted quite well by fixed slip and fixed recurrence models, so in some sense they are time- and slip-predictable. While fixed recurrence and slip models better predict repeating earthquake behavior than the time- and slip-predictable models, we observe a correlation between slip and the preceding recurrence time for many repeating earthquake sequences in Parkfield, California. This correlation is not found in other regions, and the sequences with the correlative slip-predictable behavior are not distinguishable from nearby earthquake sequences that do not exhibit this behavior.

E-DECIDER Decision Support Gateway For Earthquake Disaster Response

NASA Astrophysics Data System (ADS)

Glasscoe, M. T.; Stough, T. M.; Parker, J. W.; Burl, M. C.; Donnellan, A.; Blom, R. G.; Pierce, M. E.; Wang, J.; Ma, Y.; Rundle, J. B.; Yoder, M. R.

2013-12-01

Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) is a NASA-funded project developing capabilities for decision-making utilizing remote sensing data and modeling software in order to provide decision support for earthquake disaster management and response. E-DECIDER incorporates earthquake forecasting methodology and geophysical modeling tools developed through NASA's QuakeSim project in order to produce standards-compliant map data products to aid in decision-making following an earthquake. Remote sensing and geodetic data, in conjunction with modeling and forecasting tools, help provide both long-term planning information for disaster management decision makers as well as short-term information following earthquake events (i.e. identifying areas where the greatest deformation and damage has occurred and emergency services may need to be focused). E-DECIDER utilizes a service-based GIS model for its cyber-infrastructure in order to produce standards-compliant products for different user types with multiple service protocols (such as KML, WMS, WFS, and WCS). The goal is to make complex GIS processing and domain-specific analysis tools more accessible to general users through software services as well as provide system sustainability through infrastructure services. The system comprises several components, which include: a GeoServer for thematic mapping and data distribution, a geospatial database for storage and spatial analysis, web service APIs, including simple-to-use REST APIs for complex GIS functionalities, and geoprocessing tools including python scripts to produce standards-compliant data products. These are then served to the E-DECIDER decision support gateway (http://e-decider.org), the E-DECIDER mobile interface, and to the Department of Homeland Security decision support middleware UICDS (Unified Incident Command and Decision Support). The E-DECIDER decision support gateway features a web interface that

Stochastic Model of Seasonal Runoff Forecasts

NASA Astrophysics Data System (ADS)

Krzysztofowicz, Roman; Watada, Leslie M.

1986-03-01

Each year the National Weather Service and the Soil Conservation Service issue a monthly sequence of five (or six) categorical forecasts of the seasonal snowmelt runoff volume. To describe uncertainties in these forecasts for the purposes of optimal decision making, a stochastic model is formulated. It is a discrete-time, finite, continuous-space, nonstationary Markov process. Posterior densities of the actual runoff conditional upon a forecast, and transition densities of forecasts are obtained from a Bayesian information processor. Parametric densities are derived for the process with a normal prior density of the runoff and a linear model of the forecast error. The structure of the model and the estimation procedure are motivated by analyses of forecast records from five stations in the Snake River basin, from the period 1971-1983. The advantages of supplementing the current forecasting scheme with a Bayesian analysis are discussed.

Demand forecast model based on CRM

NASA Astrophysics Data System (ADS)

Cai, Yuancui; Chen, Lichao

2006-11-01

With interiorizing day by day management thought that regarding customer as the centre, forecasting customer demand becomes more and more important. In the demand forecast of customer relationship management, the traditional forecast methods have very great limitation because much uncertainty of the demand, these all require new modeling to meet the demands of development. In this paper, the notion is that forecasting the demand according to characteristics of the potential customer, then modeling by it. The model first depicts customer adopting uniform multiple indexes. Secondly, the model acquires characteristic customers on the basis of data warehouse and the technology of data mining. The last, there get the most similar characteristic customer by their comparing and forecast the demands of new customer by the most similar characteristic customer.

Sufficient Forecasting Using Factor Models

PubMed Central

Fan, Jianqing; Xue, Lingzhou; Yao, Jiawei

2017-01-01

We consider forecasting a single time series when there is a large number of predictors and a possible nonlinear effect. The dimensionality was first reduced via a high-dimensional (approximate) factor model implemented by the principal component analysis. Using the extracted factors, we develop a novel forecasting method called the sufficient forecasting, which provides a set of sufficient predictive indices, inferred from high-dimensional predictors, to deliver additional predictive power. The projected principal component analysis will be employed to enhance the accuracy of inferred factors when a semi-parametric (approximate) factor model is assumed. Our method is also applicable to cross-sectional sufficient regression using extracted factors. The connection between the sufficient forecasting and the deep learning architecture is explicitly stated. The sufficient forecasting correctly estimates projection indices of the underlying factors even in the presence of a nonparametric forecasting function. The proposed method extends the sufficient dimension reduction to high-dimensional regimes by condensing the cross-sectional information through factor models. We derive asymptotic properties for the estimate of the central subspace spanned by these projection directions as well as the estimates of the sufficient predictive indices. We further show that the natural method of running multiple regression of target on estimated factors yields a linear estimate that actually falls into this central subspace. Our method and theory allow the number of predictors to be larger than the number of observations. We finally demonstrate that the sufficient forecasting improves upon the linear forecasting in both simulation studies and an empirical study of forecasting macroeconomic variables. PMID:29731537

Understanding Earthquake Hazard & Disaster in Himalaya - A Perspective on Earthquake Forecast in Himalayan Region of South Central Tibet

NASA Astrophysics Data System (ADS)

Shanker, D.; Paudyal, ,; Singh, H.

2010-12-01

It is not only the basic understanding of the phenomenon of earthquake, its resistance offered by the designed structure, but the understanding of the socio-economic factors, engineering properties of the indigenous materials, local skill and technology transfer models are also of vital importance. It is important that the engineering aspects of mitigation should be made a part of public policy documents. Earthquakes, therefore, are and were thought of as one of the worst enemies of mankind. Due to the very nature of release of energy, damage is evident which, however, will not culminate in a disaster unless it strikes a populated area. The word mitigation may be defined as the reduction in severity of something. The Earthquake disaster mitigation, therefore, implies that such measures may be taken which help reduce severity of damage caused by earthquake to life, property and environment. While “earthquake disaster mitigation” usually refers primarily to interventions to strengthen the built environment, and “earthquake protection” is now considered to include human, social and administrative aspects of reducing earthquake effects. It should, however, be noted that reduction of earthquake hazards through prediction is considered to be the one of the effective measures, and much effort is spent on prediction strategies. While earthquake prediction does not guarantee safety and even if predicted correctly the damage to life and property on such a large scale warrants the use of other aspects of mitigation. While earthquake prediction may be of some help, mitigation remains the main focus of attention of the civil society. Present study suggests that anomalous seismic activity/ earthquake swarm existed prior to the medium size earthquakes in the Nepal Himalaya. The mainshocks were preceded by the quiescence period which is an indication for the occurrence of future seismic activity. In all the cases, the identified episodes of anomalous seismic activity were

Multi-model seasonal forecast of Arctic sea-ice: forecast uncertainty at pan-Arctic and regional scales

NASA Astrophysics Data System (ADS)

Blanchard-Wrigglesworth, E.; Barthélemy, A.; Chevallier, M.; Cullather, R.; Fučkar, N.; Massonnet, F.; Posey, P.; Wang, W.; Zhang, J.; Ardilouze, C.; Bitz, C. M.; Vernieres, G.; Wallcraft, A.; Wang, M.

2017-08-01

Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or forecast post-processing (bias correction) techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

Wind-Farm Forecasting Using the HARMONIE Weather Forecast Model and Bayes Model Averaging for Bias Removal.

NASA Astrophysics Data System (ADS)

O'Brien, Enda; McKinstry, Alastair; Ralph, Adam

2015-04-01

Building on previous work presented at EGU 2013 (http://www.sciencedirect.com/science/article/pii/S1876610213016068 ), more results are available now from a different wind-farm in complex terrain in southwest Ireland. The basic approach is to interpolate wind-speed forecasts from an operational weather forecast model (i.e., HARMONIE in the case of Ireland) to the precise location of each wind-turbine, and then use Bayes Model Averaging (BMA; with statistical information collected from a prior training-period of e.g., 25 days) to remove systematic biases. Bias-corrected wind-speed forecasts (and associated power-generation forecasts) are then provided twice daily (at 5am and 5pm) out to 30 hours, with each forecast validation fed back to BMA for future learning. 30-hr forecasts from the operational Met Éireann HARMONIE model at 2.5km resolution have been validated against turbine SCADA observations since Jan. 2014. An extra high-resolution (0.5km grid-spacing) HARMONIE configuration has been run since Nov. 2014 as an extra member of the forecast "ensemble". A new version of HARMONIE with extra filters designed to stabilize high-resolution configurations has been run since Jan. 2015. Measures of forecast skill and forecast errors will be provided, and the contributions made by the various physical and computational enhancements to HARMONIE will be quantified.

Weather Forecaster Understanding of Climate Models

NASA Astrophysics Data System (ADS)

Bol, A.; Kiehl, J. T.; Abshire, W. E.

2013-12-01

Weather forecasters, particularly those in broadcasting, are the primary conduit to the public for information on climate and climate change. However, many weather forecasters remain skeptical of model-based climate projections. To address this issue, The COMET Program developed an hour-long online lesson of how climate models work, targeting an audience of weather forecasters. The module draws on forecasters' pre-existing knowledge of weather, climate, and numerical weather prediction (NWP) models. In order to measure learning outcomes, quizzes were given before and after the lesson. Preliminary results show large learning gains. For all people that took both pre and post-tests (n=238), scores improved from 48% to 80%. Similar pre/post improvement occurred for National Weather Service employees (51% to 87%, n=22 ) and college faculty (50% to 90%, n=7). We believe these results indicate a fundamental misunderstanding among many weather forecasters of (1) the difference between weather and climate models, (2) how researchers use climate models, and (3) how they interpret model results. The quiz results indicate that efforts to educate the public about climate change need to include weather forecasters, a vital link between the research community and the general public.

Thermal Infrared Anomalies of Several Strong Earthquakes

PubMed Central

Wei, Congxin; Guo, Xiao; Qin, Manzhong

2013-01-01

In the history of earthquake thermal infrared research, it is undeniable that before and after strong earthquakes there are significant thermal infrared anomalies which have been interpreted as preseismic precursor in earthquake prediction and forecasting. In this paper, we studied the characteristics of thermal radiation observed before and after the 8 great earthquakes with magnitude up to Ms7.0 by using the satellite infrared remote sensing information. We used new types of data and method to extract the useful anomaly information. Based on the analyses of 8 earthquakes, we got the results as follows. (1) There are significant thermal radiation anomalies before and after earthquakes for all cases. The overall performance of anomalies includes two main stages: expanding first and narrowing later. We easily extracted and identified such seismic anomalies by method of “time-frequency relative power spectrum.” (2) There exist evident and different characteristic periods and magnitudes of thermal abnormal radiation for each case. (3) Thermal radiation anomalies are closely related to the geological structure. (4) Thermal radiation has obvious characteristics in abnormal duration, range, and morphology. In summary, we should be sure that earthquake thermal infrared anomalies as useful earthquake precursor can be used in earthquake prediction and forecasting. PMID:24222728

Thermal infrared anomalies of several strong earthquakes.

PubMed

Wei, Congxin; Zhang, Yuansheng; Guo, Xiao; Hui, Shaoxing; Qin, Manzhong; Zhang, Ying

2013-01-01

In the history of earthquake thermal infrared research, it is undeniable that before and after strong earthquakes there are significant thermal infrared anomalies which have been interpreted as preseismic precursor in earthquake prediction and forecasting. In this paper, we studied the characteristics of thermal radiation observed before and after the 8 great earthquakes with magnitude up to Ms7.0 by using the satellite infrared remote sensing information. We used new types of data and method to extract the useful anomaly information. Based on the analyses of 8 earthquakes, we got the results as follows. (1) There are significant thermal radiation anomalies before and after earthquakes for all cases. The overall performance of anomalies includes two main stages: expanding first and narrowing later. We easily extracted and identified such seismic anomalies by method of "time-frequency relative power spectrum." (2) There exist evident and different characteristic periods and magnitudes of thermal abnormal radiation for each case. (3) Thermal radiation anomalies are closely related to the geological structure. (4) Thermal radiation has obvious characteristics in abnormal duration, range, and morphology. In summary, we should be sure that earthquake thermal infrared anomalies as useful earthquake precursor can be used in earthquake prediction and forecasting.

Conditional Probabilities of Large Earthquake Sequences in California from the Physics-based Rupture Simulator RSQSim

NASA Astrophysics Data System (ADS)

Gilchrist, J. J.; Jordan, T. H.; Shaw, B. E.; Milner, K. R.; Richards-Dinger, K. B.; Dieterich, J. H.

2017-12-01

Within the SCEC Collaboratory for Interseismic Simulation and Modeling (CISM), we are developing physics-based forecasting models for earthquake ruptures in California. We employ the 3D boundary element code RSQSim (Rate-State Earthquake Simulator of Dieterich & Richards-Dinger, 2010) to generate synthetic catalogs with tens of millions of events that span up to a million years each. This code models rupture nucleation by rate- and state-dependent friction and Coulomb stress transfer in complex, fully interacting fault systems. The Uniform California Earthquake Rupture Forecast Version 3 (UCERF3) fault and deformation models are used to specify the fault geometry and long-term slip rates. We have employed the Blue Waters supercomputer to generate long catalogs of simulated California seismicity from which we calculate the forecasting statistics for large events. We have performed probabilistic seismic hazard analysis with RSQSim catalogs that were calibrated with system-wide parameters and found a remarkably good agreement with UCERF3 (Milner et al., this meeting). We build on this analysis, comparing the conditional probabilities of sequences of large events from RSQSim and UCERF3. In making these comparisons, we consider the epistemic uncertainties associated with the RSQSim parameters (e.g., rate- and state-frictional parameters), as well as the effects of model-tuning (e.g., adjusting the RSQSim parameters to match UCERF3 recurrence rates). The comparisons illustrate how physics-based rupture simulators might assist forecasters in understanding the short-term hazards of large aftershocks and multi-event sequences associated with complex, multi-fault ruptures.

Evaluation Of Statistical Models For Forecast Errors From The HBV-Model

NASA Astrophysics Data System (ADS)

Engeland, K.; Kolberg, S.; Renard, B.; Stensland, I.

2009-04-01

Three statistical models for the forecast errors for inflow to the Langvatn reservoir in Northern Norway have been constructed and tested according to how well the distribution and median values of the forecasts errors fit to the observations. For the first model observed and forecasted inflows were transformed by the Box-Cox transformation before a first order autoregressive model was constructed for the forecast errors. The parameters were conditioned on climatic conditions. In the second model the Normal Quantile Transformation (NQT) was applied on observed and forecasted inflows before a similar first order autoregressive model was constructed for the forecast errors. For the last model positive and negative errors were modeled separately. The errors were first NQT-transformed before a model where the mean values were conditioned on climate, forecasted inflow and yesterday's error. To test the three models we applied three criterions: We wanted a) the median values to be close to the observed values; b) the forecast intervals to be narrow; c) the distribution to be correct. The results showed that it is difficult to obtain a correct model for the forecast errors, and that the main challenge is to account for the auto-correlation in the errors. Model 1 and 2 gave similar results, and the main drawback is that the distributions are not correct. The 95% forecast intervals were well identified, but smaller forecast intervals were over-estimated, and larger intervals were under-estimated. Model 3 gave a distribution that fits better, but the median values do not fit well since the auto-correlation is not properly accounted for. If the 95% forecast interval is of interest, Model 2 is recommended. If the whole distribution is of interest, Model 3 is recommended.

EM Earthquake Precursor Detection Associated with Fluid Injection for Hydraulic Fracturing and Tectonic Sources

NASA Astrophysics Data System (ADS)

Jones, Kenneth B., II

2015-04-01

Many attempts have been made to determine an earthquake forecasting method and warn the public in turn. Presently, the animal kingdom leads the precursor list alluding to a transmission related source. By applying the animal-based model to an electromagnetic wave model, various hypotheses were formed, but only two seemed to take shape with the most interesting one requiring a magnetometer of a unique design. To date, numerous, high-end magnetometers have been in use in close proximity to fault zones for potential earthquake forecasting; however, results have had wide variability and problems still reside with what exactly is forecastable and the investigative direction of a true precursor. After a number of custom rock experiments, the two hypotheses were thoroughly tested to correlate the EM wave model. The first hypothesis involved sufficient and continuous electron movement either by surface or penetrative flow, and the second regarded a novel approach to radio wave generation. The second hypothesis resulted best with highly reproducible data, radio wave generation and detection, and worked numerous times with each laboratory test administered. In addition, internally introduced force on a small scale stressed a number of select rock types to emit radio waves well before catastrophic failure, and failure always went to completion. Comparatively, at a larger scale, highly detailed studies were procured to establish legitimate wave guides from potential hypocenters to epicenters and map the results, accordingly. Field testing in Southern California from 2006 to 2011 and outside the NE Texas town of Timpson in February, 2013 was conducted for detecting similar, laboratory generated, radio wave sources. At the Southern California field sites, signals were detected in numerous directions with varying amplitudes; therefore, a reactive approach was investigated in hopes of detecting possible aftershocks from large, tectonically related M5.0+ earthquakes. At the Timpson

Earthquake Clusters and Spatio-temporal Migration of earthquakes in Northeastern Tibetan Plateau: a Finite Element Modeling

NASA Astrophysics Data System (ADS)

Sun, Y.; Luo, G.

2017-12-01

Seismicity in a region is usually characterized by earthquake clusters and earthquake migration along its major fault zones. However, we do not fully understand why and how earthquake clusters and spatio-temporal migration of earthquakes occur. The northeastern Tibetan Plateau is a good example for us to investigate these problems. In this study, we construct and use a three-dimensional viscoelastoplastic finite-element model to simulate earthquake cycles and spatio-temporal migration of earthquakes along major fault zones in northeastern Tibetan Plateau. We calculate stress evolution and fault interactions, and explore effects of topographic loading and viscosity of middle-lower crust and upper mantle on model results. Model results show that earthquakes and fault interactions increase Coulomb stress on the neighboring faults or segments, accelerating the future earthquakes in this region. Thus, earthquakes occur sequentially in a short time, leading to regional earthquake clusters. Through long-term evolution, stresses on some seismogenic faults, which are far apart, may almost simultaneously reach the critical state of fault failure, probably also leading to regional earthquake clusters and earthquake migration. Based on our model synthetic seismic catalog and paleoseismic data, we analyze probability of earthquake migration between major faults in northeastern Tibetan Plateau. We find that following the 1920 M 8.5 Haiyuan earthquake and the 1927 M 8.0 Gulang earthquake, the next big event (M≥7) in northeastern Tibetan Plateau would be most likely to occur on the Haiyuan fault.

Relating stress models of magma emplacement to volcano-tectonic earthquakes

NASA Astrophysics Data System (ADS)

Vargas-Bracamontes, D.; Neuberg, J.

2007-12-01

Among the various types of seismic signals linked to volcanic processes, volcano-tectonic earthquakes are probably the earliest precursors of volcanic eruptions. Understanding their relationship with magma emplacement can provide insight into the mechanisms of magma transport at depth and assist in the ultimate goal of forecasting eruptions. Volcano-tectonic events have been observed to occur on faults that experience increases in Coulomb stress changes as the result of magma intrusions. To simulate stress changes associated with magmatic injections, we test different models of volcanic sources in an elastic half-space. For each source model, we look at several aspects that influence the stress conditions of the magmatic system such as the regional tectonic setting, the effect of varying the elastic parameters of the media, the evolution of the magma with time, as well as the volume and rheology of the ascending magma.

Stress release model and proxy measures of earthquake size. Application to Italian seismogenic sources

NASA Astrophysics Data System (ADS)

Varini, Elisa; Rotondi, Renata; Basili, Roberto; Barba, Salvatore

2016-07-01

This study presents a series of self-correcting models that are obtained by integrating information about seismicity and fault sources in Italy. Four versions of the stress release model are analyzed, in which the evolution of the system over time is represented by the level of strain, moment, seismic energy, or energy scaled by the moment. We carry out the analysis on a regional basis by subdividing the study area into eight tectonically coherent regions. In each region, we reconstruct the seismic history and statistically evaluate the completeness of the resulting seismic catalog. Following the Bayesian paradigm, we apply Markov chain Monte Carlo methods to obtain parameter estimates and a measure of their uncertainty expressed by the simulated posterior distribution. The comparison of the four models through the Bayes factor and an information criterion provides evidence (to different degrees depending on the region) in favor of the stress release model based on the energy and the scaled energy. Therefore, among the quantities considered, this turns out to be the measure of the size of an earthquake to use in stress release models. At any instant, the time to the next event turns out to follow a Gompertz distribution, with a shape parameter that depends on time through the value of the conditional intensity at that instant. In light of this result, the issue of forecasting is tackled through both retrospective and prospective approaches. Retrospectively, the forecasting procedure is carried out on the occurrence times of the events recorded in each region, to determine whether the stress release model reproduces the observations used in the estimation procedure. Prospectively, the estimates of the time to the next event are compared with the dates of the earthquakes that occurred after the end of the learning catalog, in the 2003-2012 decade.

Error models for official mortality forecasts.

PubMed

Alho, J M; Spencer, B D

1990-09-01

"The Office of the Actuary, U.S. Social Security Administration, produces alternative forecasts of mortality to reflect uncertainty about the future.... In this article we identify the components and assumptions of the official forecasts and approximate them by stochastic parametric models. We estimate parameters of the models from past data, derive statistical intervals for the forecasts, and compare them with the official high-low intervals. We use the models to evaluate the forecasts rather than to develop different predictions of the future. Analysis of data from 1972 to 1985 shows that the official intervals for mortality forecasts for males or females aged 45-70 have approximately a 95% chance of including the true mortality rate in any year. For other ages the chances are much less than 95%." excerpt

Self-organization in leaky threshold systems: The influence of near-mean field dynamics and its implications for earthquakes, neurobiology, and forecasting

PubMed Central

Rundle, J. B.; Tiampo, K. F.; Klein, W.; Sá Martins, J. S.

2002-01-01

Threshold systems are known to be some of the most important nonlinear self-organizing systems in nature, including networks of earthquake faults, neural networks, superconductors and semiconductors, and the World Wide Web, as well as political, social, and ecological systems. All of these systems have dynamics that are strongly correlated in space and time, and all typically display a multiplicity of spatial and temporal scales. Here we discuss the physics of self-organization in earthquake threshold systems at two distinct scales: (i) The “microscopic” laboratory scale, in which consideration of results from simulations leads to dynamical equations that can be used to derive the results obtained from sliding friction experiments, and (ii) the “macroscopic” earthquake fault-system scale, in which the physics of strongly correlated earthquake fault systems can be understood by using time-dependent state vectors defined in a Hilbert space of eigenstates, similar in many respects to the mathematics of quantum mechanics. In all of these systems, long-range interactions induce the existence of locally ergodic dynamics. The existence of dissipative effects leads to the appearance of a “leaky threshold” dynamics, equivalent to a new scaling field that controls the size of nucleation events relative to the size of background fluctuations. At the macroscopic earthquake fault-system scale, these ideas show considerable promise as a means of forecasting future earthquake activity. PMID:11875204

Real Time Earthquake Information System in Japan

NASA Astrophysics Data System (ADS)

Doi, K.; Kato, T.

2003-12-01

An early earthquake notification system in Japan had been developed by the Japan Meteorological Agency (JMA) as a governmental organization responsible for issuing earthquake information and tsunami forecasts. The system was primarily developed for prompt provision of a tsunami forecast to the public with locating an earthquake and estimating its magnitude as quickly as possible. Years after, a system for a prompt provision of seismic intensity information as indices of degrees of disasters caused by strong ground motion was also developed so that concerned governmental organizations can decide whether it was necessary for them to launch emergency response or not. At present, JMA issues the following kinds of information successively when a large earthquake occurs. 1) Prompt report of occurrence of a large earthquake and major seismic intensities caused by the earthquake in about two minutes after the earthquake occurrence. 2) Tsunami forecast in around three minutes. 3) Information on expected arrival times and maximum heights of tsunami waves in around five minutes. 4) Information on a hypocenter and a magnitude of the earthquake, the seismic intensity at each observation station, the times of high tides in addition to the expected tsunami arrival times in 5-7 minutes. To issue information above, JMA has established; - An advanced nationwide seismic network with about 180 stations for seismic wave observation and about 3,400 stations for instrumental seismic intensity observation including about 2,800 seismic intensity stations maintained by local governments, - Data telemetry networks via landlines and partly via a satellite communication link, - Real-time data processing techniques, for example, the automatic calculation of earthquake location and magnitude, the database driven method for quantitative tsunami estimation, and - Dissemination networks, via computer-to-computer communications and facsimile through dedicated telephone lines. JMA operationally

Flash flood forecasting using simplified hydrological models, radar rainfall forecasts and data assimilation

NASA Astrophysics Data System (ADS)

Smith, P. J.; Beven, K.; Panziera, L.

2012-04-01

The issuing of timely flood alerts may be dependant upon the ability to predict future values of water level or discharge at locations where observations are available. Catchments at risk of flash flooding often have a rapid natural response time, typically less then the forecast lead time desired for issuing alerts. This work focuses on the provision of short-range (up to 6 hours lead time) predictions of discharge in small catchments based on utilising radar forecasts to drive a hydrological model. An example analysis based upon the Verzasca catchment (Ticino, Switzerland) is presented. Parsimonious time series models with a mechanistic interpretation (so called Data-Based Mechanistic model) have been shown to provide reliable accurate forecasts in many hydrological situations. In this study such a model is developed to predict the discharge at an observed location from observed precipitation data. The model is shown to capture the snow melt response at this site. Observed discharge data is assimilated to improve the forecasts, of up to two hours lead time, that can be generated from observed precipitation. To generate forecasts with greater lead time ensemble precipitation forecasts are utilised. In this study the Nowcasting ORographic precipitation in the Alps (NORA) product outlined in more detail elsewhere (Panziera et al. Q. J. R. Meteorol. Soc. 2011; DOI:10.1002/qj.878) is utilised. NORA precipitation forecasts are derived from historical analogues based on the radar field and upper atmospheric conditions. As such, they avoid the need to explicitly model the evolution of the rainfall field through for example Lagrangian diffusion. The uncertainty in the forecasts is represented by characterisation of the joint distribution of the observed discharge, the discharge forecast using the (in operational conditions unknown) future observed precipitation and that forecast utilising the NORA ensembles. Constructing the joint distribution in this way allows the full

New Measurements and Modeling Capability to Improve Real-time Forecast of Cascadia Tsunamis along U.S. West Coast

NASA Astrophysics Data System (ADS)

Wei, Y.; Titov, V. V.; Bernard, E. N.; Spillane, M. C.

2014-12-01

The tragedies of 2004 Sumatra and 2011 Tohoku tsunamis exposed the limits of our knowledge in preparing for devastating tsunamis, especially in the near field. The 1,100-km coastline of the Pacific coast of North America has tectonic and geological settings similar to Sumatra and Japan. The geological records unambiguously show that the Cascadia fault had caused devastating tsunamis in the past and this geological process will cause tsunamis in the future. Existing observational instruments along the Cascadia Subduction Zone are capable of providing tsunami data within minutes of tsunami generation. However, this strategy requires separation of the tsunami signals from the overwhelming high-frequency seismic waves produced during a strong earthquake- a real technical challenge for existing operational tsunami observational network. A new-generation of nano-resolution pressure sensors can provide high temporal resolution of the earthquake and tsunami signals without loosing precision. The nano-resolution pressure sensor offers a state-of the-science ability to separate earthquake vibrations and other oceanic noise from tsunami waveforms, paving the way for accurate, early warnings of local tsunamis. This breakthrough underwater technology has been tested and verified for a couple of micro-tsunami events (Paros et al., 2011). Real-time forecast of Cascadia tsunamis is becoming a possibility with the development of nano-tsunameter technology. The present study provides an investigation on optimizing the placement of these new sensors so that the forecast time can be shortened.. The presentation will cover the optimization of an observational array to quickly detect and forecast a tsunami generated by a strong Cascadia earthquake, including short and long rupture scenarios. Lessons learned from the 2011 Tohoku tsunami will be examined to demonstrate how we can improve the local forecast using the new technology We expect this study to provide useful guideline for

Spatiotemporal drought forecasting using nonlinear models

NASA Astrophysics Data System (ADS)

Vasiliades, Lampros; Loukas, Athanasios

2010-05-01

Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. In order to achieve spatiotemporal forecasting, some mature analysis tools, e.g., time series and spatial statistics are extended to the spatial dimension and the temporal dimension, respectively. Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Despite the widespread application of nonlinear mathematical models, comparative studies on spatiotemporal drought forecasting using different models are still a huge task for modellers. This study uses a promising approach, the Gamma Test (GT), to select the input variables and the training data length, so that the trial and error workload could be greatly reduced. The GT enables to quickly evaluate and estimate the best mean squared error that can be achieved by a smooth model on any unseen data for a given selection of inputs, prior to model construction. The GT is applied to forecast droughts using monthly Standardized Precipitation Index (SPI) timeseries at multiple timescales in several precipitation stations at Pinios river basin in Thessaly region, Greece. Several nonlinear models have been developed efficiently, with the aid of the GT, for 1-month up to 12-month ahead forecasting. Several temporal and spatial statistical indices were considered for the performance evaluation of the models. The predicted results show reasonably good agreement with the actual data for short lead times, whereas the forecasting accuracy decreases with

Quantifying model uncertainty in seasonal Arctic sea-ice forecasts

NASA Astrophysics Data System (ADS)

Blanchard-Wrigglesworth, Edward; Barthélemy, Antoine; Chevallier, Matthieu; Cullather, Richard; Fučkar, Neven; Massonnet, François; Posey, Pamela; Wang, Wanqiu; Zhang, Jinlun; Ardilouze, Constantin; Bitz, Cecilia; Vernieres, Guillaume; Wallcraft, Alan; Wang, Muyin

2017-04-01

Dynamical model forecasts in the Sea Ice Outlook (SIO) of September Arctic sea-ice extent over the last decade have shown lower skill than that found in both idealized model experiments and hindcasts of previous decades. Additionally, it is unclear how different model physics, initial conditions or post-processing techniques contribute to SIO forecast uncertainty. In this work, we have produced a seasonal forecast of 2015 Arctic summer sea ice using SIO dynamical models initialized with identical sea-ice thickness in the central Arctic. Our goals are to calculate the relative contribution of model uncertainty and irreducible error growth to forecast uncertainty and assess the importance of post-processing, and to contrast pan-Arctic forecast uncertainty with regional forecast uncertainty. We find that prior to forecast post-processing, model uncertainty is the main contributor to forecast uncertainty, whereas after forecast post-processing forecast uncertainty is reduced overall, model uncertainty is reduced by an order of magnitude, and irreducible error growth becomes the main contributor to forecast uncertainty. While all models generally agree in their post-processed forecasts of September sea-ice volume and extent, this is not the case for sea-ice concentration. Additionally, forecast uncertainty of sea-ice thickness grows at a much higher rate along Arctic coastlines relative to the central Arctic ocean. Potential ways of offering spatial forecast information based on the timescale over which the forecast signal beats the noise are also explored.

Discrepancy between earthquake rates implied by historic earthquakes and a consensus geologic source model for California

USGS Publications Warehouse

Petersen, M.D.; Cramer, C.H.; Reichle, M.S.; Frankel, A.D.; Hanks, T.C.

2000-01-01

We examine the difference between expected earthquake rates inferred from the historical earthquake catalog and the geologic data that was used to develop the consensus seismic source characterization for the state of California [California Department of Conservation, Division of Mines and Geology (CDMG) and U.S. Geological Survey (USGS) Petersen et al., 1996; Frankel et al., 1996]. On average the historic earthquake catalog and the seismic source model both indicate about one M 6 or greater earthquake per year in the state of California. However, the overall earthquake rates of earthquakes with magnitudes (M) between 6 and 7 in this seismic source model are higher, by at least a factor of 2, than the mean historic earthquake rates for both southern and northern California. The earthquake rate discrepancy results from a seismic source model that includes earthquakes with characteristic (maximum) magnitudes that are primarily between M 6.4 and 7.1. Many of these faults are interpreted to accommodate high strain rates from geologic and geodetic data but have not ruptured in large earthquakes during historic time. Our sensitivity study indicates that the rate differences between magnitudes 6 and 7 can be reduced by adjusting the magnitude-frequency distribution of the source model to reflect more characteristic behavior, by decreasing the moment rate available for seismogenic slip along faults, by increasing the maximum magnitude of the earthquake on a fault, or by decreasing the maximum magnitude of the background seismicity. However, no single parameter can be adjusted, consistent with scientific consensus, to eliminate the earthquake rate discrepancy. Applying a combination of these parametric adjustments yields an alternative earthquake source model that is more compatible with the historic data. The 475-year return period hazard for peak ground and 1-sec spectral acceleration resulting from this alternative source model differs from the hazard resulting from the

Real-Time Earthquake Analysis for Disaster Mitigation (READI) Network

NASA Astrophysics Data System (ADS)

Bock, Y.

2014-12-01

Real-time GNSS networks are making a significant impact on our ability to forecast, assess, and mitigate the effects of geological hazards. I describe the activities of the Real-time Earthquake Analysis for Disaster Mitigation (READI) working group. The group leverages 600+ real-time GPS stations in western North America operated by UNAVCO (PBO network), Central Washington University (PANGA), US Geological Survey & Scripps Institution of Oceanography (SCIGN project), UC Berkeley & US Geological Survey (BARD network), and the Pacific Geosciences Centre (WCDA project). Our goal is to demonstrate an earthquake and tsunami early warning system for western North America. Rapid response is particularly important for those coastal communities that are in the near-source region of large earthquakes and may have only minutes of warning time, and who today are not adequately covered by existing seismic and basin-wide ocean-buoy monitoring systems. The READI working group is performing comparisons of independent real time analyses of 1 Hz GPS data for station displacements and is participating in government-sponsored earthquake and tsunami exercises in the Western U.S. I describe a prototype seismogeodetic system using a cluster of southern California stations that includes GNSS tracking and collocation with MEMS accelerometers for real-time estimation of seismic velocity and displacement waveforms, which has advantages for improved earthquake early warning and tsunami forecasts compared to seismic-only or GPS-only methods. The READI working group's ultimate goal is to participate in an Indo-Pacific Tsunami early warning system that utilizes GNSS real-time displacements and ionospheric measurements along with seismic, near-shore buoys and ocean-bottom pressure sensors, where available, to rapidly estimate magnitude and finite fault slip models for large earthquakes, and then forecast tsunami source, energy scale, geographic extent, inundation and runup. This will require

Earthquake hazards: a national threat

USGS Publications Warehouse

,

2006-01-01

Earthquakes are one of the most costly natural hazards faced by the Nation, posing a significant risk to 75 million Americans in 39 States. The risks that earthquakes pose to society, including death, injury, and economic loss, can be greatly reduced by (1) better planning, construction, and mitigation practices before earthquakes happen, and (2) providing critical and timely information to improve response after they occur. As part of the multi-agency National Earthquake Hazards Reduction Program, the U.S. Geological Survey (USGS) has the lead Federal responsibility to provide notification of earthquakes in order to enhance public safety and to reduce losses through effective forecasts based on the best possible scientific information.

Forecasting in foodservice: model development, testing, and evaluation.

PubMed

Miller, J L; Thompson, P A; Orabella, M M

1991-05-01

This study was designed to develop, test, and evaluate mathematical models appropriate for forecasting menu-item production demand in foodservice. Data were collected from residence and dining hall foodservices at Ohio State University. Objectives of the study were to collect, code, and analyze the data; develop and test models using actual operation data; and compare forecasting results with current methods in use. Customer count was forecast using deseasonalized simple exponential smoothing. Menu-item demand was forecast by multiplying the count forecast by a predicted preference statistic. Forecasting models were evaluated using mean squared error, mean absolute deviation, and mean absolute percentage error techniques. All models were more accurate than current methods. A broad spectrum of forecasting techniques could be used by foodservice managers with access to a personal computer and spread-sheet and database-management software. The findings indicate that mathematical forecasting techniques may be effective in foodservice operations to control costs, increase productivity, and maximize profits.

Earthquake Rupture Forecast of M>= 6 for the Corinth Rift System

NASA Astrophysics Data System (ADS)

Scotti, O.; Boiselet, A.; Lyon-Caen, H.; Albini, P.; Bernard, P.; Briole, P.; Ford, M.; Lambotte, S.; Matrullo, E.; Rovida, A.; Satriano, C.

2014-12-01

Fourteen years of multidisciplinary observations and data collection in the Western Corinth Rift (WCR) near-fault observatory have been recently synthesized (Boiselet, Ph.D. 2014) for the purpose of providing earthquake rupture forecasts (ERF) of M>=6 in WCR. The main contribution of this work consisted in paving the road towards the development of a "community-based" fault model reflecting the level of knowledge gathered thus far by the WCR working group. The most relevant available data used for this exercise are: - onshore/offshore fault traces, based on geological and high-resolution seismics, revealing a complex network of E-W striking, ~10 km long fault segments; microseismicity recorded by a dense network ( > 60000 events; 1.5=5 19th century events and a few paleoseismological investigations, allowing to consider time-dependent ERF. B-value estimates are found to be catalogue-dependent (WCR, homogenized NOA+Thessaloniki, SHARE), which may call for a potential break in scaling relationship. Furthermore, observed discrepancies between seismicity rates assumed for the modeled faults and those expected from GPS deformation rates call for the presence of aseismic deformation. Uncertainty in the ERF resulting from the lack of precise knowledge concerning both, fault geometries and seismic slip rates, is quantified through a logic tree exploration. Median and precentile predictions are then compared to ERF assuming a uniform seismicity rate in the WCR region. The issues raised by this work will be discussed in the light of seismic hazard assessment.

Real-time forecasts of tomorrow's earthquakes in California: a new mapping tool

USGS Publications Warehouse

Gerstenberger, Matt; Wiemer, Stefan; Jones, Lucy

2004-01-01

We have derived a multi-model approach to calculate time-dependent earthquake hazard resulting from earthquake clustering. This file report explains the theoretical background behind the approach, the specific details that are used in applying the method to California, as well as the statistical testing to validate the technique. We have implemented our algorithm as a real-time tool that has been automatically generating short-term hazard maps for California since May of 2002, at http://step.wr.usgs.gov

Predictability of Landslide Timing From Quasi-Periodic Precursory Earthquakes

NASA Astrophysics Data System (ADS)

Bell, Andrew F.

2018-02-01

Accelerating rates of geophysical signals are observed before a range of material failure phenomena. They provide insights into the physical processes controlling failure and the basis for failure forecasts. However, examples of accelerating seismicity before landslides are rare, and their behavior and forecasting potential are largely unknown. Here I use a Bayesian methodology to apply a novel gamma point process model to investigate a sequence of quasiperiodic repeating earthquakes preceding a large landslide at Nuugaatsiaq in Greenland in June 2017. The evolution in earthquake rate is best explained by an inverse power law increase with time toward failure, as predicted by material failure theory. However, the commonly accepted power law exponent value of 1.0 is inconsistent with the data. Instead, the mean posterior value of 0.71 indicates a particularly rapid acceleration toward failure and suggests that only relatively short warning times may be possible for similar landslides in future.

Forecasting the (un)productivity of the 2014 M 6.0 South Napa aftershock sequence

USGS Publications Warehouse

Llenos, Andrea L.; Michael, Andrew J.

2017-01-01

The 24 August 2014 Mw 6.0 South Napa mainshock produced fewer aftershocks than expected for a California earthquake of its magnitude. In the first 4.5 days, only 59 M≥1.8 aftershocks occurred, the largest of which was an M 3.9 that happened a little over two days after the mainshock. We investigate the aftershock productivity of the South Napa sequence and compare it with other M≥5.5 California strike‐slip mainshock–aftershock sequences. While the productivity of the South Napa sequence is among the lowest, northern California mainshocks generally have fewer aftershocks than mainshocks further south, although the productivities vary widely in both regions. An epidemic‐type aftershock sequence (ETAS) model (Ogata, 1988) fit to Napa seismicity from 1980 to 23 August 2014 fits the sequence well and suggests that low‐productivity sequences are typical of this area. Utilizing regional variations in productivity could improve operational earthquake forecasting (OEF) by improving the model used immediately after the mainshock. We show this by comparing the daily rate of M≥2 aftershocks to forecasts made with the generic California model (Reasenberg and Jones, 1989; hereafter, RJ89), RJ89 models with productivity updated daily, a generic California ETAS model, an ETAS model based on premainshock seismicity, and ETAS models updated daily following the mainshock. RJ89 models for which only the productivity is updated provide better forecasts than the generic RJ89 California model, and the Napa‐specific ETAS models forecast the aftershock rates more accurately than either generic model. Therefore, forecasts that use localized initial parameters and that rapidly update the productivity may be better for OEF than using a generic model and/or updating all parameters.

Prospective Validation of Pre-earthquake Atmospheric Signals and Their Potential for Short–term Earthquake Forecasting

NASA Astrophysics Data System (ADS)

Ouzounov, Dimitar; Pulinets, Sergey; Hattori, Katsumi; Lee, Lou; Liu, Tiger; Kafatos, Menas

2015-04-01

We are presenting the latest development in multi-sensors observations of short-term pre-earthquake phenomena preceding major earthquakes. Our challenge question is: "Whether such pre-earthquake atmospheric/ionospheric signals are significant and could be useful for early warning of large earthquakes?" To check the predictive potential of atmospheric pre-earthquake signals we have started to validate anomalous ionospheric / atmospheric signals in retrospective and prospective modes. The integrated satellite and terrestrial framework (ISTF) is our method for validation and is based on a joint analysis of several physical and environmental parameters (Satellite thermal infrared radiation (STIR), electron concentration in the ionosphere (GPS/TEC), radon/ion activities, air temperature and seismicity patterns) that were found to be associated with earthquakes. The science rationale for multidisciplinary analysis is based on concept Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) [Pulinets and Ouzounov, 2011], which explains the synergy of different geospace processes and anomalous variations, usually named short-term pre-earthquake anomalies. Our validation processes consist in two steps: (1) A continuous retrospective analysis preformed over two different regions with high seismicity- Taiwan and Japan for 2003-2009 (2) Prospective testing of STIR anomalies with potential for M5.5+ events. The retrospective tests (100+ major earthquakes, M>5.9, Taiwan and Japan) show STIR anomalous behavior before all of these events with false negatives close to zero. False alarm ratio for false positives is less then 25%. The initial prospective testing for STIR shows systematic appearance of anomalies in advance (1-30 days) to the M5.5+ events for Taiwan, Kamchatka-Sakhalin (Russia) and Japan. Our initial prospective results suggest that our approach show a systematic appearance of atmospheric anomalies, one to several days prior to the largest earthquakes That feature could be

Validating induced seismicity forecast models—Induced Seismicity Test Bench

NASA Astrophysics Data System (ADS)

Király-Proag, Eszter; Zechar, J. Douglas; Gischig, Valentin; Wiemer, Stefan; Karvounis, Dimitrios; Doetsch, Joseph

2016-08-01

Induced earthquakes often accompany fluid injection, and the seismic hazard they pose threatens various underground engineering projects. Models to monitor and control induced seismic hazard with traffic light systems should be probabilistic, forward-looking, and updated as new data arrive. In this study, we propose an Induced Seismicity Test Bench to test and rank such models; this test bench can be used for model development, model selection, and ensemble model building. We apply the test bench to data from the Basel 2006 and Soultz-sous-Forêts 2004 geothermal stimulation projects, and we assess forecasts from two models: Shapiro and Smoothed Seismicity (SaSS) and Hydraulics and Seismics (HySei). These models incorporate a different mix of physics-based elements and stochastic representation of the induced sequences. Our results show that neither model is fully superior to the other. Generally, HySei forecasts the seismicity rate better after shut-in but is only mediocre at forecasting the spatial distribution. On the other hand, SaSS forecasts the spatial distribution better and gives better seismicity rate estimates before shut-in. The shut-in phase is a difficult moment for both models in both reservoirs: the models tend to underpredict the seismicity rate around, and shortly after, shut-in.

Water balance models in one-month-ahead streamflow forecasting

USGS Publications Warehouse

Alley, William M.

1985-01-01

Techniques are tested that incorporate information from water balance models in making 1-month-ahead streamflow forecasts in New Jersey. The results are compared to those based on simple autoregressive time series models. The relative performance of the models is dependent on the month of the year in question. The water balance models are most useful for forecasts of April and May flows. For the stations in northern New Jersey, the April and May forecasts were made in order of decreasing reliability using the water-balance-based approaches, using the historical monthly means, and using simple autoregressive models. The water balance models were useful to a lesser extent for forecasts during the fall months. For the rest of the year the improvements in forecasts over those obtained using the simpler autoregressive models were either very small or the simpler models provided better forecasts. When using the water balance models, monthly corrections for bias are found to improve minimum mean-square-error forecasts as well as to improve estimates of the forecast conditional distributions.

Mitigating earthquakes; the federal role

USGS Publications Warehouse

Press, F.

1977-01-01

With rapid approach of a capability to make reliable earthquake forecasts, it essential that the Federal Government play a strong, positive role in formulating and implementing plans to reduce earthquake hazards. Many steps are being taken in this direction, with the President looking to the Office of Science and Technology Policy (OSTP) in his Executive Office to provide leadership in establishing and coordinating Federal activities. 

Historical and recent large megathrust earthquakes in Chile

NASA Astrophysics Data System (ADS)

Ruiz, S.; Madariaga, R.

2018-05-01

Recent earthquakes in Chile, 2014, Mw 8.2 Iquique, 2015, Mw 8.3 Illapel and 2016, Mw 7.6 Chiloé have put in evidence some problems with the straightforward application of ideas about seismic gaps, earthquake periodicity and the general forecast of large megathrust earthquakes. In northern Chile, before the 2014 Iquique earthquake 4 large earthquakes were reported in written chronicles, 1877, 1786, 1615 and 1543; in North-Central Chile, before the 2015 Illapel event, 3 large earthquakes 1943, 1880, 1730 were reported; and the 2016 Chiloé earthquake occurred in the southern zone of the 1960 Valdivia megathrust rupture, where other large earthquakes occurred in 1575, 1737 and 1837. The periodicity of these events has been proposed as a good long-term forecasting. However, the seismological aspects of historical Chilean earthquakes were inferred mainly from old chronicles written before subduction in Chile was discovered. Here we use the original description of earthquakes to re-analyze the historical archives. Our interpretation shows that a-priori ideas, like seismic gaps and characteristic earthquakes, influenced the estimation of magnitude, location and rupture area of the older Chilean events. On the other hand, the advance in the characterization of the rheological aspects that controlled the contact between Nazca and South-American plate and the study of tsunami effects provide better estimations of the location of historical earthquakes along the seismogenic plate interface. Our re-interpretation of historical earthquakes shows a large diversity of earthquakes types; there is a major difference between giant earthquakes that break the entire plate interface and those of Mw 8.0 that only break a portion of it.

Nambe Pueblo Water Budget and Forecasting model.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brainard, James Robert

2009-10-01

This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Watermore » Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.« less

Earthquake casualty models within the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) system

USGS Publications Warehouse

Jaiswal, Kishor; Wald, David J.; Earle, Paul S.; Porter, Keith A.; Hearne, Mike

2011-01-01

Since the launch of the USGS’s Prompt Assessment of Global Earthquakes for Response (PAGER) system in fall of 2007, the time needed for the U.S. Geological Survey (USGS) to determine and comprehend the scope of any major earthquake disaster anywhere in the world has been dramatically reduced to less than 30 min. PAGER alerts consist of estimated shaking hazard from the ShakeMap system, estimates of population exposure at various shaking intensities, and a list of the most severely shaken cities in the epicentral area. These estimates help government, scientific, and relief agencies to guide their responses in the immediate aftermath of a significant earthquake. To account for wide variability and uncertainty associated with inventory, structural vulnerability and casualty data, PAGER employs three different global earthquake fatality/loss computation models. This article describes the development of the models and demonstrates the loss estimation capability for earthquakes that have occurred since 2007. The empirical model relies on country-specific earthquake loss data from past earthquakes and makes use of calibrated casualty rates for future prediction. The semi-empirical and analytical models are engineering-based and rely on complex datasets including building inventories, time-dependent population distributions within different occupancies, the vulnerability of regional building stocks, and casualty rates given structural collapse.

Modeled Forecasts of Dengue Fever in San Juan, Puerto Rico Using NASA Satellite Enhanced Weather Forecasts

NASA Astrophysics Data System (ADS)

Morin, C.; Quattrochi, D. A.; Zavodsky, B.; Case, J.

2015-12-01

Dengue fever (DF) is an important mosquito transmitted disease that is strongly influenced by meteorological and environmental conditions. Recent research has focused on forecasting DF case numbers based on meteorological data. However, these forecasting tools have generally relied on empirical models that require long DF time series to train. Additionally, their accuracy has been tested retrospectively, using past meteorological data. Consequently, the operational utility of the forecasts are still in question because the error associated with weather and climate forecasts are not reflected in the results. Using up-to-date weekly dengue case numbers for model parameterization and weather forecast data as meteorological input, we produced weekly forecasts of DF cases in San Juan, Puerto Rico. Each week, the past weeks' case counts were used to re-parameterize a process-based DF model driven with updated weather forecast data to generate forecasts of DF case numbers. Real-time weather forecast data was produced using the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) system enhanced using additional high-resolution NASA satellite data. This methodology was conducted in a weekly iterative process with each DF forecast being evaluated using county-level DF cases reported by the Puerto Rico Department of Health. The one week DF forecasts were accurate especially considering the two sources of model error. First, weather forecasts were sometimes inaccurate and generally produced lower than observed temperatures. Second, the DF model was often overly influenced by the previous weeks DF case numbers, though this phenomenon could be lessened by increasing the number of simulations included in the forecast. Although these results are promising, we would like to develop a methodology to produce longer range forecasts so that public health workers can better prepare for dengue epidemics.

Expanding the Delivery of Rapid Earthquake Information and Warnings for Response and Recovery

NASA Astrophysics Data System (ADS)

Blanpied, M. L.; McBride, S.; Hardebeck, J.; Michael, A. J.; van der Elst, N.

2017-12-01

Scientific organizations like the United States Geological Survey (USGS) release information to support effective responses during an earthquake crisis. Information is delivered to the White House, the National Command Center, the Departments of Defense, Homeland Security (including FEMA), Transportation, Energy, and Interior. Other crucial stakeholders include state officials and decision makers, emergency responders, numerous public and private infrastructure management centers (e.g., highways, railroads and pipelines), the media, and the public. To meet the diverse information requirements of these users, rapid earthquake notifications have been developed to be delivered by e-mail and text message, as well as a suite of earthquake information resources such as ShakeMaps, Did You Feel It?, PAGER impact estimates, and data are delivered via the web. The ShakeAlert earthquake early warning system being developed for the U.S. West Coast will identify and characterize an earthquake a few seconds after it begins, estimate the likely intensity of ground shaking, and deliver brief but critically important warnings to people and infrastructure in harm's way. Currently the USGS is also developing a capability to deliver Operational Earthquake Forecasts (OEF). These provide estimates of potential seismic behavior after large earthquakes and during evolving aftershock sequences. Similar work is underway in New Zealand, Japan, and Italy. In the development of OEF forecasts, social science research conducted during these sequences indicates that aftershock forecasts are valued for a variety of reasons, from informing critical response and recovery decisions to psychologically preparing for more earthquakes. New tools will allow users to customize map-based, spatiotemporal forecasts to their specific needs. Hazard curves and other advanced information will also be available. For such authoritative information to be understood and used during the pressures of an earthquake

Earthquake forecast for the Wasatch Front region of the Intermountain West

USGS Publications Warehouse

DuRoss, Christopher B.

2016-04-18

The Working Group on Utah Earthquake Probabilities has assessed the probability of large earthquakes in the Wasatch Front region. There is a 43 percent probability of one or more magnitude 6.75 or greater earthquakes and a 57 percent probability of one or more magnitude 6.0 or greater earthquakes in the region in the next 50 years. These results highlight the threat of large earthquakes in the region.

Development and application of an atmospheric-hydrologic-hydraulic flood forecasting model driven by TIGGE ensemble forecasts

NASA Astrophysics Data System (ADS)

Bao, Hongjun; Zhao, Linna

2012-02-01

A coupled atmospheric-hydrologic-hydraulic ensemble flood forecasting model, driven by The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data, has been developed for flood forecasting over the Huaihe River. The incorporation of numerical weather prediction (NWP) information into flood forecasting systems may increase forecast lead time from a few hours to a few days. A single NWP model forecast from a single forecast center, however, is insufficient as it involves considerable non-predictable uncertainties and leads to a high number of false alarms. The availability of global ensemble NWP systems through TIGGE offers a new opportunity for flood forecast. The Xinanjiang model used for hydrological rainfall-runoff modeling and the one-dimensional unsteady flow model applied to channel flood routing are coupled with ensemble weather predictions based on the TIGGE data from the Canadian Meteorological Centre (CMC), the European Centre for Medium-Range Weather Forecasts (ECMWF), the UK Met Office (UKMO), and the US National Centers for Environmental Prediction (NCEP). The developed ensemble flood forecasting model is applied to flood forecasting of the 2007 flood season as a test case. The test case is chosen over the upper reaches of the Huaihe River above Lutaizi station with flood diversion and retarding areas. The input flood discharge hydrograph from the main channel to the flood diversion area is estimated with the fixed split ratio of the main channel discharge. The flood flow inside the flood retarding area is calculated as a reservoir with the water balance method. The Muskingum method is used for flood routing in the flood diversion area. A probabilistic discharge and flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE ensemble forecasts. The results demonstrate satisfactory flood forecasting with clear signals of probability of floods up to a

Sources of information for tsunami forecasting in New Zealand

NASA Astrophysics Data System (ADS)

Barberopoulou, A.; Ristau, J. P.; D'Anastasio, E.; Wang, X.

2013-12-01

Tsunami science has evolved considerably in the last two decades due to technological advancements which also helped push for better numerical modelling of the tsunami phases (generation to inundation). The deployment of DART buoys has also been a considerable milestone in tsunami forecasting. Tsunami forecasting is one of the parts that tsunami modelling feeds into and is related to response, preparedness and planning. Usually tsunami forecasting refers to short-term forecasting that takes place in real-time after a tsunami has or appears to have been generated. In this report we refer to all types of forecasting (short-term or long-term) related to work in advance of a tsunami impacting a coastline that would help in response, planning or preparedness. We look at the standard types of data (seismic, GPS, water level) that are available in New Zealand for tsunami forecasting, how they are currently being used, other ways to use these data and provide recommendations for better utilisation. The main findings are: -Current investigations of the use of seismic parameters quickly obtained after an earthquake, have potential to provide critical information about the tsunamigenic potential of earthquakes. Further analysis of the most promising methods should be undertaken to determine a path to full implementation. -Network communication of the largest part of the GPS network is not currently at a stage that can provide sufficient data early enough for tsunami warning. It is believed that it has potential, but changes including data transmission improvements may have to happen before real-time processing oriented to tsunami early warning is implemented on the data that is currently provided. -Tide gauge data is currently under-utilised for tsunami forecasting. Spectral analysis, modal analysis based on identified modes and arrival times extracted from the records can be useful in forecasting. -The current study is by no means exhaustive of the ways the different types

Testing prediction methods: Earthquake clustering versus the Poisson model

USGS Publications Warehouse

Michael, A.J.

1997-01-01

Testing earthquake prediction methods requires statistical techniques that compare observed success to random chance. One technique is to produce simulated earthquake catalogs and measure the relative success of predicting real and simulated earthquakes. The accuracy of these tests depends on the validity of the statistical model used to simulate the earthquakes. This study tests the effect of clustering in the statistical earthquake model on the results. Three simulation models were used to produce significance levels for a VLF earthquake prediction method. As the degree of simulated clustering increases, the statistical significance drops. Hence, the use of a seismicity model with insufficient clustering can lead to overly optimistic results. A successful method must pass the statistical tests with a model that fully replicates the observed clustering. However, a method can be rejected based on tests with a model that contains insufficient clustering. U.S. copyright. Published in 1997 by the American Geophysical Union.

Improving of local ozone forecasting by integrated models.

PubMed

Gradišar, Dejan; Grašič, Boštjan; Božnar, Marija Zlata; Mlakar, Primož; Kocijan, Juš

2016-09-01

This paper discuss the problem of forecasting the maximum ozone concentrations in urban microlocations, where reliable alerting of the local population when thresholds have been surpassed is necessary. To improve the forecast, the methodology of integrated models is proposed. The model is based on multilayer perceptron neural networks that use as inputs all available information from QualeAria air-quality model, WRF numerical weather prediction model and onsite measurements of meteorology and air pollution. While air-quality and meteorological models cover large geographical 3-dimensional space, their local resolution is often not satisfactory. On the other hand, empirical methods have the advantage of good local forecasts. In this paper, integrated models are used for improved 1-day-ahead forecasting of the maximum hourly value of ozone within each day for representative locations in Slovenia. The WRF meteorological model is used for forecasting meteorological variables and the QualeAria air-quality model for gas concentrations. Their predictions, together with measurements from ground stations, are used as inputs to a neural network. The model validation results show that integrated models noticeably improve ozone forecasts and provide better alert systems.

Statistical evaluation of forecasts

NASA Astrophysics Data System (ADS)

Mader, Malenka; Mader, Wolfgang; Gluckman, Bruce J.; Timmer, Jens; Schelter, Björn

2014-08-01

Reliable forecasts of extreme but rare events, such as earthquakes, financial crashes, and epileptic seizures, would render interventions and precautions possible. Therefore, forecasting methods have been developed which intend to raise an alarm if an extreme event is about to occur. In order to statistically validate the performance of a prediction system, it must be compared to the performance of a random predictor, which raises alarms independent of the events. Such a random predictor can be obtained by bootstrapping or analytically. We propose an analytic statistical framework which, in contrast to conventional methods, allows for validating independently the sensitivity and specificity of a forecasting method. Moreover, our method accounts for the periods during which an event has to remain absent or occur after a respective forecast.

A post-Tohoku earthquake review of earthquake probabilities in the Southern Kanto District, Japan

NASA Astrophysics Data System (ADS)

Somerville, Paul G.

2014-12-01

The 2011 Mw 9.0 Tohoku earthquake generated an aftershock sequence that affected a large part of northern Honshu, and has given rise to widely divergent forecasts of changes in earthquake occurrence probabilities in northern Honshu. The objective of this review is to assess these forecasts as they relate to potential changes in the occurrence probabilities of damaging earthquakes in the Kanto Region. It is generally agreed that the 2011 Mw 9.0 Tohoku earthquake increased the stress on faults in the southern Kanto district. Toda and Stein (Geophys Res Lett 686, 40: doi:10.1002, 2013) further conclude that the probability of earthquakes in the Kanto Corridor has increased by a factor of 2.5 for the time period 11 March 2013 to 10 March 2018 in the Kanto Corridor. Estimates of earthquake probabilities in a wider region of the Southern Kanto District by Nanjo et al. (Geophys J Int, doi:10.1093, 2013) indicate that any increase in the probability of earthquakes is insignificant in this larger region. Uchida et al. (Earth Planet Sci Lett 374: 81-91, 2013) conclude that the Philippine Sea plate the extends well north of the northern margin of Tokyo Bay, inconsistent with the Kanto Fragment hypothesis of Toda et al. (Nat Geosci, 1:1-6,2008), which attributes deep earthquakes in this region, which they term the Kanto Corridor, to a broken fragment of the Pacific plate. The results of Uchida and Matsuzawa (J Geophys Res 115:B07309, 2013)support the conclusion that fault creep in southern Kanto may be slowly relaxing the stress increase caused by the Tohoku earthquake without causing more large earthquakes. Stress transfer calculations indicate a large stress transfer to the Off Boso Segment as a result of the 2011 Tohoku earthquake. However, Ozawa et al. (J Geophys Res 117:B07404, 2012) used onshore GPS measurements to infer large post-Tohoku creep on the plate interface in the Off-Boso region, and Uchida and Matsuzawa (ibid.) measured similar large creep off the Boso

A physically-based earthquake recurrence model for estimation of long-term earthquake probabilities

USGS Publications Warehouse

Ellsworth, William L.; Matthews, Mark V.; Nadeau, Robert M.; Nishenko, Stuart P.; Reasenberg, Paul A.; Simpson, Robert W.

1999-01-01

A physically-motivated model for earthquake recurrence based on the Brownian relaxation oscillator is introduced. The renewal process defining this point process model can be described by the steady rise of a state variable from the ground state to failure threshold as modulated by Brownian motion. Failure times in this model follow the Brownian passage time (BPT) distribution, which is specified by the mean time to failure, μ, and the aperiodicity of the mean, α (equivalent to the familiar coefficient of variation). Analysis of 37 series of recurrent earthquakes, M -0.7 to 9.2, suggests a provisional generic value of α = 0.5. For this value of α, the hazard function (instantaneous failure rate of survivors) exceeds the mean rate for times > μ⁄2, and is ~ ~ 2 ⁄ μ for all times > μ. Application of this model to the next M 6 earthquake on the San Andreas fault at Parkfield, California suggests that the annual probability of the earthquake is between 1:10 and 1:13.

Adaptive time-variant models for fuzzy-time-series forecasting.

PubMed

Wong, Wai-Keung; Bai, Enjian; Chu, Alice Wai-Ching

2010-12-01

A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, and other domains. Related studies mainly focus on three factors, namely, the partition of discourse, the content of forecasting rules, and the methods of defuzzification, all of which greatly influence the prediction accuracy of forecasting models. These studies use fixed analysis window sizes for forecasting. In this paper, an adaptive time-variant fuzzy-time-series forecasting model (ATVF) is proposed to improve forecasting accuracy. The proposed model automatically adapts the analysis window size of fuzzy time series based on the prediction accuracy in the training phase and uses heuristic rules to generate forecasting values in the testing phase. The performance of the ATVF model is tested using both simulated and actual time series including the enrollments at the University of Alabama, Tuscaloosa, and the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). The experiment results show that the proposed ATVF model achieves a significant improvement in forecasting accuracy as compared to other fuzzy-time-series forecasting models.

Pre-earthquake signatures in atmosphere/ionosphere and their potential for short-term earthquake forecasting. Case studies for 2015

NASA Astrophysics Data System (ADS)

Ouzounov, Dimitar; Pulinets, Sergey; Davidenko, Dmitry; Hernández-Pajares, Manuel; García-Rigo, Alberto; Petrrov, Leonid; Hatzopoulos, Nikolaos; Kafatos, Menas

2016-04-01

We are conducting validation studies on temporal-spatial pattern of pre-earthquake signatures in atmosphere and ionosphere associated with M>7 earthquakes in 2015. Our approach is based on the Lithosphere Atmosphere Ionosphere Coupling (LAIC) physical concept integrated with Multi-sensor-networking analysis (MSNA) of several non-correlated observations that can potentially yield predictive information. In this study we present two type of results: 1/ prospective testing of MSNA-LAIC for M7+ in 2015 and 2:/ retrospective analysis of temporal-spatial variations in atmosphere and ionosphere several days before the two M7.8 and M7.3 in Nepal and M8.3 Chile earthquakes. During the prospective test 18 earthquakes M>7 occurred worldwide, from which 15 were alerted in advance with the time lag between 2 up to 30 days and with different level of accuracy. The retrospective analysis included different physical parameters from space: Outgoing long-wavelength radiation (OLR obtained from NPOES, NASA/AQUA) on the top of the atmosphere, Atmospheric potential (ACP obtained from NASA assimilation models) and electron density variations in the ionosphere via GPS Total Electron Content (GPS/TEC). Concerning M7.8 in Nepal of April 24, rapid increase of OLR reached the maximum on April 21-22. GPS/TEC data indicate maximum value during April 22-24 periods. Strong negative TEC anomaly was detected in the crest of EIA (Equatorial Ionospheric Anomaly) on April 21st and strong positive on April 24th, 2015. For May 12 M7.3 aftershock similar pre- earthquake patterns in OLR and GPS/TEC were observed. Concerning the M8.3 Chile of Sept 16, the OLR strongest transient feature was observed of Sept 12. GPS/TEC analysis data confirm abnormal values on Sept 14. Also on the same day the degradation of EIA and disappearance of the crests of EIA as is characteristic for pre-dawn and early morning hours (11 LT) was observed. On Sept 16 co-seismic ionospheric signatures consistent with defined circular

The Global Earthquake Model - Past, Present, Future

NASA Astrophysics Data System (ADS)

Smolka, Anselm; Schneider, John; Stein, Ross

2014-05-01

The Global Earthquake Model (GEM) is a unique collaborative effort that aims to provide organizations and individuals with tools and resources for transparent assessment of earthquake risk anywhere in the world. By pooling data, knowledge and people, GEM acts as an international forum for collaboration and exchange. Sharing of data and risk information, best practices, and approaches across the globe are key to assessing risk more effectively. Through consortium driven global projects, open-source IT development and collaborations with more than 10 regions, leading experts are developing unique global datasets, best practice, open tools and models for seismic hazard and risk assessment. The year 2013 has seen the completion of ten global data sets or components addressing various aspects of earthquake hazard and risk, as well as two GEM-related, but independently managed regional projects SHARE and EMME. Notably, the International Seismological Centre (ISC) led the development of a new ISC-GEM global instrumental earthquake catalogue, which was made publicly available in early 2013. It has set a new standard for global earthquake catalogues and has found widespread acceptance and application in the global earthquake community. By the end of 2014, GEM's OpenQuake computational platform will provide the OpenQuake hazard/risk assessment software and integrate all GEM data and information products. The public release of OpenQuake is planned for the end of this 2014, and will comprise the following datasets and models: • ISC-GEM Instrumental Earthquake Catalogue (released January 2013) • Global Earthquake History Catalogue [1000-1903] • Global Geodetic Strain Rate Database and Model • Global Active Fault Database • Tectonic Regionalisation Model • Global Exposure Database • Buildings and Population Database • Earthquake Consequences Database • Physical Vulnerabilities Database • Socio-Economic Vulnerability and Resilience Indicators • Seismic

Load Modeling and Forecasting | Grid Modernization | NREL

Science.gov Websites

Load Modeling and Forecasting Load Modeling and Forecasting NREL's work in load modeling is focused resources (such as rooftop photovoltaic systems) and changing customer energy use profiles, new load models distribution system. In addition, NREL researchers are developing load models for individual appliances and

Afterslip behavior following the M6.0, 2014 South Napa earthquake with implications for afterslip forecasting on other seismogenic faults

USGS Publications Warehouse

Lienkaemper, James J.; DeLong, Stephen B.; Domrose, Carolyn J; Rosa, Carla M.

2016-01-01

The M6.0, 24 Aug. 2014 South Napa, California, earthquake exhibited unusually large slip for a California strike-slip event of its size with a maximum coseismic surface slip of 40-50 cm in the north section of the 15 km-long rupture. Although only minor (<10 cm) surface slip occurred coseismically in the southern 9-km section of the rupture, there was considerable postseismic slip, so that the maximum total slip one year after the event approached 40-50 cm, about equal to the coseismic maximum in the north. We measured the accumulation of postseismic surface slip on four, ~100-m-long alignment arrays for one year following the event. Because prolonged afterslip can delay reconstruction of fault-damaged buildings and infrastructure, we analyzed its gradual decay to estimate when significant afterslip would likely end. This forecasting of Napa afterslip suggests how we might approach the scientific and engineering challenges of afterslip from a much larger M~7 earthquake anticipated on the nearby, urban Hayward Fault. However, we expect its afterslip to last much longer than one year.The M6.0, 24 Aug. 2014 South Napa, California, earthquake exhibited unusually large slip for a California strike-slip event of its size with a maximum coseismic surface slip of 40-50 cm in the north section of the 15 km-long rupture. Although only minor (<10 cm) surface slip occurred coseismically in the southern 9-km section of the rupture, there was considerable postseismic slip, so that the maximum total slip one year after the event approached 40-50 cm, about equal to the coseismic maximum in the north. We measured the accumulation of postseismic surface slip on four, ~100-m-long alignment arrays for one year following the event. Because prolonged afterslip can delay reconstruction of fault-damaged buildings and infrastructure, we analyzed its gradual decay to estimate when significant afterslip would likely end. This forecasting of Napa afterslip suggests how we might approach the

Deviant Earthquakes: Data-driven Constraints on the Variability in Earthquake Source Properties and Seismic Hazard

NASA Astrophysics Data System (ADS)

Trugman, Daniel Taylor

The complexity of the earthquake rupture process makes earthquakes inherently unpredictable. Seismic hazard forecasts often presume that the rate of earthquake occurrence can be adequately modeled as a space-time homogenenous or stationary Poisson process and that the relation between the dynamical source properties of small and large earthquakes obey self-similar scaling relations. While these simplified models provide useful approximations and encapsulate the first-order statistical features of the historical seismic record, they are inconsistent with the complexity underlying earthquake occurrence and can lead to misleading assessments of seismic hazard when applied in practice. The six principle chapters of this thesis explore the extent to which the behavior of real earthquakes deviates from these simplified models, and the implications that the observed deviations have for our understanding of earthquake rupture processes and seismic hazard. Chapter 1 provides a brief thematic overview and introduction to the scope of this thesis. Chapter 2 examines the complexity of the 2010 M7.2 El Mayor-Cucapah earthquake, focusing on the relation between its unexpected and unprecedented occurrence and anthropogenic stresses from the nearby Cerro Prieto Geothermal Field. Chapter 3 compares long-term changes in seismicity within California's three largest geothermal fields in an effort to characterize the relative influence of natural and anthropogenic stress transients on local seismic hazard. Chapter 4 describes a hybrid, hierarchical clustering algorithm that can be used to relocate earthquakes using waveform cross-correlation, and applies the new algorithm to study the spatiotemporal evolution of two recent seismic swarms in western Nevada. Chapter 5 describes a new spectral decomposition technique that can be used to analyze the dynamic source properties of large datasets of earthquakes, and applies this approach to revisit the question of self-similar scaling of

Statistical distributions of earthquake numbers: consequence of branching process

NASA Astrophysics Data System (ADS)

Kagan, Yan Y.

2010-03-01

We discuss various statistical distributions of earthquake numbers. Previously, we derived several discrete distributions to describe earthquake numbers for the branching model of earthquake occurrence: these distributions are the Poisson, geometric, logarithmic and the negative binomial (NBD). The theoretical model is the `birth and immigration' population process. The first three distributions above can be considered special cases of the NBD. In particular, a point branching process along the magnitude (or log seismic moment) axis with independent events (immigrants) explains the magnitude/moment-frequency relation and the NBD of earthquake counts in large time/space windows, as well as the dependence of the NBD parameters on the magnitude threshold (magnitude of an earthquake catalogue completeness). We discuss applying these distributions, especially the NBD, to approximate event numbers in earthquake catalogues. There are many different representations of the NBD. Most can be traced either to the Pascal distribution or to the mixture of the Poisson distribution with the gamma law. We discuss advantages and drawbacks of both representations for statistical analysis of earthquake catalogues. We also consider applying the NBD to earthquake forecasts and describe the limits of the application for the given equations. In contrast to the one-parameter Poisson distribution so widely used to describe earthquake occurrence, the NBD has two parameters. The second parameter can be used to characterize clustering or overdispersion of a process. We determine the parameter values and their uncertainties for several local and global catalogues, and their subdivisions in various time intervals, magnitude thresholds, spatial windows, and tectonic categories. The theoretical model of how the clustering parameter depends on the corner (maximum) magnitude can be used to predict future earthquake number distribution in regions where very large earthquakes have not yet occurred.

Journal of the Chinese Institute of Engineers. Special Issue: Commemoration of Chi-Chi Earthquake (II)

NASA Astrophysics Data System (ADS)

2002-09-01

Contents include the following: Deep Electromagnetic Images of Seismogenic Zone of the Chi-Chi (Taiwan) Earthquake; New Techniques for Stress-Forecasting Earthquakes; Aspects of Characteristics of Near-Fault Ground Motions of the 1999 Chi-Chi (Taiwan) Earthquake; Liquefaction Damage and Related Remediation in Wufeng after the Chi-Chi Earthquake; Fines Content Effects on Liquefaction Potential Evaluation for Sites Liquefied during Chi-Chi Earthquake 1999; Damage Investigation and Liquefaction Potential Analysis of Gravelly Soil; Dynamic Characteristics of Soils in Yuan-Lin Liquefaction Area; A Preliminary Study of Earthquake Building Damage and Life Loss Due to the Chi-Chi Earthquake; Statistical Analyses of Relation between Mortality and Building Type in the 1999 Chi-Chi Earthquake; Development of an After Earthquake Disaster Shelter Evaluation Model; Posttraumatic Stress Reactions in Children and Adolescents One Year after the 1999 Taiwan Chi-Chi Earthquake; Changes or Not is the Question: the Meaning of Posttraumatic Stress Reactions One Year after the Taiwan Chi-Chi Earthquake.

Robustness of disaggregate oil and gas discovery forecasting models

USGS Publications Warehouse

Attanasi, E.D.; Schuenemeyer, J.H.

1989-01-01

The trend in forecasting oil and gas discoveries has been to develop and use models that allow forecasts of the size distribution of future discoveries. From such forecasts, exploration and development costs can more readily be computed. Two classes of these forecasting models are the Arps-Roberts type models and the 'creaming method' models. This paper examines the robustness of the forecasts made by these models when the historical data on which the models are based have been subject to economic upheavals or when historical discovery data are aggregated from areas having widely differing economic structures. Model performance is examined in the context of forecasting discoveries for offshore Texas State and Federal areas. The analysis shows how the model forecasts are limited by information contained in the historical discovery data. Because the Arps-Roberts type models require more regularity in discovery sequence than the creaming models, prior information had to be introduced into the Arps-Roberts models to accommodate the influence of economic changes. The creaming methods captured the overall decline in discovery size but did not easily allow introduction of exogenous information to compensate for incomplete historical data. Moreover, the predictive log normal distribution associated with the creaming model methods appears to understate the importance of the potential contribution of small fields. ?? 1989.

Testing new methodologies for short -term earthquake forecasting: Multi-parameters precursors

NASA Astrophysics Data System (ADS)

Ouzounov, Dimitar; Pulinets, Sergey; Tramutoli, Valerio; Lee, Lou; Liu, Tiger; Hattori, Katsumi; Kafatos, Menas

2014-05-01

We are conducting real-time tests involving multi-parameter observations over different seismo-tectonics regions in our investigation of phenomena preceding major earthquakes. Our approach is based on a systematic analysis of several selected parameters, namely: gas discharge; thermal infrared radiation; ionospheric electron density; and atmospheric temperature and humidity, which we believe are all associated with the earthquake preparation phase. We are testing a methodology capable to produce alerts in advance of major earthquakes (M > 5.5) in different regions of active earthquakes and volcanoes. During 2012-2013 we established a collaborative framework with PRE-EARTHQUAKE (EU) and iSTEP3 (Taiwan) projects for coordinated measurements and prospective validation over seven testing regions: Southern California (USA), Eastern Honshu (Japan), Italy, Greece, Turkey, Taiwan (ROC), Kamchatka and Sakhalin (Russia). The current experiment provided a "stress test" opportunity to validate the physical based earthquake precursor approach over regions of high seismicity. Our initial results are: (1) Real-time tests have shown the presence of anomalies in the atmosphere and ionosphere before most of the significant (M>5.5) earthquakes; (2) False positives exist and ratios are different for each region, varying between 50% for (Southern Italy), 35% (California) down to 25% (Taiwan, Kamchatka and Japan) with a significant reduction of false positives as soon as at least two geophysical parameters are contemporarily used; (3) Main problems remain related to the systematic collection and real-time integration of pre-earthquake observations. Our findings suggest that real-time testing of physically based pre-earthquake signals provides a short-term predictive power (in all three important parameters, namely location, time and magnitude) for the occurrence of major earthquakes in the tested regions and this result encourages testing to continue with a more detailed analysis of

Tsunami simulation method initiated from waveforms observed by ocean bottom pressure sensors for real-time tsunami forecast; Applied for 2011 Tohoku Tsunami

NASA Astrophysics Data System (ADS)

Tanioka, Yuichiro

2017-04-01

After tsunami disaster due to the 2011 Tohoku-oki great earthquake, improvement of the tsunami forecast has been an urgent issue in Japan. National Institute of Disaster Prevention is installing a cable network system of earthquake and tsunami observation (S-NET) at the ocean bottom along the Japan and Kurile trench. This cable system includes 125 pressure sensors (tsunami meters) which are separated by 30 km. Along the Nankai trough, JAMSTEC already installed and operated the cable network system of seismometers and pressure sensors (DONET and DONET2). Those systems are the most dense observation network systems on top of source areas of great underthrust earthquakes in the world. Real-time tsunami forecast has depended on estimation of earthquake parameters, such as epicenter, depth, and magnitude of earthquakes. Recently, tsunami forecast method has been developed using the estimation of tsunami source from tsunami waveforms observed at the ocean bottom pressure sensors. However, when we have many pressure sensors separated by 30km on top of the source area, we do not need to estimate the tsunami source or earthquake source to compute tsunami. Instead, we can initiate a tsunami simulation from those dense tsunami observed data. Observed tsunami height differences with a time interval at the ocean bottom pressure sensors separated by 30 km were used to estimate tsunami height distribution at a particular time. In our new method, tsunami numerical simulation was initiated from those estimated tsunami height distribution. In this paper, the above method is improved and applied for the tsunami generated by the 2011 Tohoku-oki great earthquake. Tsunami source model of the 2011 Tohoku-oki great earthquake estimated using observed tsunami waveforms, coseimic deformation observed by GPS and ocean bottom sensors by Gusman et al. (2012) is used in this study. The ocean surface deformation is computed from the source model and used as an initial condition of tsunami

Simulation of Earthquake-Generated Sea-Surface Deformation

NASA Astrophysics Data System (ADS)

Vogl, Chris; Leveque, Randy

2016-11-01

Earthquake-generated tsunamis can carry with them a powerful, destructive force. One of the most well-known, recent examples is the tsunami generated by the Tohoku earthquake, which was responsible for the nuclear disaster in Fukushima. Tsunami simulation and forecasting, a necessary element of emergency procedure planning and execution, is typically done using the shallow-water equations. A typical initial condition is that using the Okada solution for a homogeneous, elastic half-space. This work focuses on simulating earthquake-generated sea-surface deformations that are more true to the physics of the materials involved. In particular, a water layer is added on top of the half-space that models the seabed. Sea-surface deformations are then simulated using the Clawpack hyperbolic PDE package. Results from considering the water layer both as linearly elastic and as "nearly incompressible" are compared to that of the Okada solution.

Development of Ensemble Model Based Water Demand Forecasting Model

NASA Astrophysics Data System (ADS)

Kwon, Hyun-Han; So, Byung-Jin; Kim, Seong-Hyeon; Kim, Byung-Seop

2014-05-01

In recent years, Smart Water Grid (SWG) concept has globally emerged over the last decade and also gained significant recognition in South Korea. Especially, there has been growing interest in water demand forecast and optimal pump operation and this has led to various studies regarding energy saving and improvement of water supply reliability. Existing water demand forecasting models are categorized into two groups in view of modeling and predicting their behavior in time series. One is to consider embedded patterns such as seasonality, periodicity and trends, and the other one is an autoregressive model that is using short memory Markovian processes (Emmanuel et al., 2012). The main disadvantage of the abovementioned model is that there is a limit to predictability of water demands of about sub-daily scale because the system is nonlinear. In this regard, this study aims to develop a nonlinear ensemble model for hourly water demand forecasting which allow us to estimate uncertainties across different model classes. The proposed model is consist of two parts. One is a multi-model scheme that is based on combination of independent prediction model. The other one is a cross validation scheme named Bagging approach introduced by Brieman (1996) to derive weighting factors corresponding to individual models. Individual forecasting models that used in this study are linear regression analysis model, polynomial regression, multivariate adaptive regression splines(MARS), SVM(support vector machine). The concepts are demonstrated through application to observed from water plant at several locations in the South Korea. Keywords: water demand, non-linear model, the ensemble forecasting model, uncertainty. Acknowledgements This subject is supported by Korea Ministry of Environment as "Projects for Developing Eco-Innovation Technologies (GT-11-G-02-001-6)

Statistical validation of earthquake related observations

NASA Astrophysics Data System (ADS)

Kossobokov, V. G.

2011-12-01

The confirmed fractal nature of earthquakes and their distribution in space and time implies that many traditional estimations of seismic hazard (from term-less to short-term ones) are usually based on erroneous assumptions of easy tractable or, conversely, delicately-designed models. The widespread practice of deceptive modeling considered as a "reasonable proxy" of the natural seismic process leads to seismic hazard assessment of unknown quality, which errors propagate non-linearly into inflicted estimates of risk and, eventually, into unexpected societal losses of unacceptable level. The studies aimed at forecast/prediction of earthquakes must include validation in the retro- (at least) and, eventually, in prospective tests. In the absence of such control a suggested "precursor/signal" remains a "candidate", which link to target seismic event is a model assumption. Predicting in advance is the only decisive test of forecast/predictions and, therefore, the score-card of any "established precursor/signal" represented by the empirical probabilities of alarms and failures-to-predict achieved in prospective testing must prove statistical significance rejecting the null-hypothesis of random coincidental occurrence in advance target earthquakes. We reiterate suggesting so-called "Seismic Roulette" null-hypothesis as the most adequate undisturbed random alternative accounting for the empirical spatial distribution of earthquakes: (i) Consider a roulette wheel with as many sectors as the number of earthquake locations from a sample catalog representing seismic locus, a sector per each location and (ii) make your bet according to prediction (i.e., determine, which locations are inside area of alarm, and put one chip in each of the corresponding sectors); (iii) Nature turns the wheel; (iv) accumulate statistics of wins and losses along with the number of chips spent. If a precursor in charge of prediction exposes an imperfection of Seismic Roulette then, having in mind

Visible Earthquakes: a web-based tool for visualizing and modeling InSAR earthquake data

NASA Astrophysics Data System (ADS)

Funning, G. J.; Cockett, R.

2012-12-01

InSAR (Interferometric Synthetic Aperture Radar) is a technique for measuring the deformation of the ground using satellite radar data. One of the principal applications of this method is in the study of earthquakes; in the past 20 years over 70 earthquakes have been studied in this way, and forthcoming satellite missions promise to enable the routine and timely study of events in the future. Despite the utility of the technique and its widespread adoption by the research community, InSAR does not feature in the teaching curricula of most university geoscience departments. This is, we believe, due to a lack of accessibility to software and data. Existing tools for the visualization and modeling of interferograms are often research-oriented, command line-based and/or prohibitively expensive. Here we present a new web-based interactive tool for comparing real InSAR data with simple elastic models. The overall design of this tool was focused on ease of access and use. This tool should allow interested nonspecialists to gain a feel for the use of such data and greatly facilitate integration of InSAR into upper division geoscience courses, giving students practice in comparing actual data to modeled results. The tool, provisionally named 'Visible Earthquakes', uses web-based technologies to instantly render the displacement field that would be observable using InSAR for a given fault location, geometry, orientation, and slip. The user can adjust these 'source parameters' using a simple, clickable interface, and see how these affect the resulting model interferogram. By visually matching the model interferogram to a real earthquake interferogram (processed separately and included in the web tool) a user can produce their own estimates of the earthquake's source parameters. Once satisfied with the fit of their models, users can submit their results and see how they compare with the distribution of all other contributed earthquake models, as well as the mean and median

Geological and historical evidence of irregular recurrent earthquakes in Japan.

PubMed

Satake, Kenji

2015-10-28

Great (M∼8) earthquakes repeatedly occur along the subduction zones around Japan and cause fault slip of a few to several metres releasing strains accumulated from decades to centuries of plate motions. Assuming a simple 'characteristic earthquake' model that similar earthquakes repeat at regular intervals, probabilities of future earthquake occurrence have been calculated by a government committee. However, recent studies on past earthquakes including geological traces from giant (M∼9) earthquakes indicate a variety of size and recurrence interval of interplate earthquakes. Along the Kuril Trench off Hokkaido, limited historical records indicate that average recurrence interval of great earthquakes is approximately 100 years, but the tsunami deposits show that giant earthquakes occurred at a much longer interval of approximately 400 years. Along the Japan Trench off northern Honshu, recurrence of giant earthquakes similar to the 2011 Tohoku earthquake with an interval of approximately 600 years is inferred from historical records and tsunami deposits. Along the Sagami Trough near Tokyo, two types of Kanto earthquakes with recurrence interval of a few hundred years and a few thousand years had been recognized, but studies show that the recent three Kanto earthquakes had different source extents. Along the Nankai Trough off western Japan, recurrence of great earthquakes with an interval of approximately 100 years has been identified from historical literature, but tsunami deposits indicate that the sizes of the recurrent earthquakes are variable. Such variability makes it difficult to apply a simple 'characteristic earthquake' model for the long-term forecast, and several attempts such as use of geological data for the evaluation of future earthquake probabilities or the estimation of maximum earthquake size in each subduction zone are being conducted by government committees. © 2015 The Author(s).

Implications for earthquake risk reduction in the United States from the Kocaeli, Turkey, earthquake of August 17, 1999

USGS Publications Warehouse

,

2000-01-01

This report documents implications for earthquake risk reduction in the U.S. The magnitude 7.4 earthquake caused 17,127 deaths, 43,953 injuries, and displaced more than 250,000 people from their homes. The report warns that similar disasters are possible in the United States where earthquakes of comparable size strike the heart of American urban areas. Another concern described in the report is the delayed emergency response that was caused by the inadequate seismic monitoring system in Turkey, a problem that contrasts sharply with rapid assessment and response to the September Chi-Chi earthquake in Taiwan. Additionally, the experience in Turkey suggests that techniques for forecasting earthquakes may be improving.

Environmental forecasting and turbulence modeling

NASA Astrophysics Data System (ADS)

Hunt, J. C. R.

This review describes the fundamental assumptions and current methodologies of the two main kinds of environmental forecast; the first is valid for a limited period of time into the future and over a limited space-time ‘target’, and is largely determined by the initial and preceding state of the environment, such as the weather or pollution levels, up to the time when the forecast is issued and by its state at the edges of the region being considered; the second kind provides statistical information over long periods of time and/or over large space-time targets, so that they only depend on the statistical averages of the initial and ‘edge’ conditions. Environmental forecasts depend on the various ways that models are constructed. These range from those based on the ‘reductionist’ methodology (i.e., the combination of separate, scientifically based, models for the relevant processes) to those based on statistical methodologies, using a mixture of data and scientifically based empirical modeling. These are, as a rule, focused on specific quantities required for the forecast. The persistence and predictability of events associated with environmental and turbulent flows and the reasons for variation in the accuracy of their forecasts (of the first and second kinds) are now better understood and better modeled. This has partly resulted from using analogous results of disordered chaotic systems, and using the techniques of calculating ensembles of realizations, ideally involving several different models, so as to incorporate in the probabilistic forecasts a wider range of possible events. The rationale for such an approach needs to be developed. However, other insights have resulted from the recognition of the ordered, though randomly occurring, nature of the persistent motions in these flows, whose scales range from those of synoptic weather patterns (whether storms or ‘blocked’ anticyclones) to small scale vortices. These eigen states can be predicted

Forecast first: An argument for groundwater modeling in reverse

USGS Publications Warehouse

White, Jeremy

2017-01-01

Numerical groundwater models are important compo-nents of groundwater analyses that are used for makingcritical decisions related to the management of ground-water resources. In this support role, models are oftenconstructed to serve a specific purpose that is to provideinsights, through simulation, related to a specific func-tion of a complex aquifer system that cannot be observeddirectly (Anderson et al. 2015).For any given modeling analysis, several modelinput datasets must be prepared. Herein, the datasetsrequired to simulate the historical conditions are referredto as the calibration model, and the datasets requiredto simulate the model’s purpose are referred to as theforecast model. Future groundwater conditions or otherunobserved aspects of the groundwater system may besimulated by the forecast model—the outputs of interestfrom the forecast model represent the purpose of themodeling analysis. Unfortunately, the forecast model,needed to simulate the purpose of the modeling analysis,is seemingly an afterthought—calibration is where themajority of time and effort are expended and calibrationis usually completed before the forecast model is evenconstructed. Herein, I am proposing a new groundwatermodeling workflow, referred to as the “forecast first”workflow, where the forecast model is constructed at anearlier stage in the modeling analysis and the outputsof interest from the forecast model are evaluated duringsubsequent tasks in the workflow.

Applying Binary Forecasting Approaches to Induced Seismicity in the Western Canada Sedimentary Basin

NASA Astrophysics Data System (ADS)

Kahue, R.; Shcherbakov, R.

2016-12-01

The Western Canada Sedimentary Basin has been chosen as a focus due to an increase in the recent observed seismicity there which is most likely linked to anthropogenic activities related to unconventional oil and gas exploration. Seismicity caused by these types of activities is called induced seismicity. The occurrence of moderate to larger induced earthquakes in areas where critical infrastructure is present can be potentially problematic. Here we use a binary forecast method to analyze past seismicity and well production data in order to quantify future areas of increased seismicity. This method splits the given region into spatial cells. The binary forecast method used here has been suggested in the past to retroactively forecast large earthquakes occurring globally in areas called alarm cells. An alarm cell, or alert zone, is a bin in which there is a higher likelihood for earthquakes to occur based on previous data. The first method utilizes the cumulative Benioff strain, based on earthquakes that had occurred in each bin above a given magnitude over a time interval called the training period. The second method utilizes the cumulative well production data within each bin. Earthquakes that occurred within an alert zone in the retrospective forecast period contribute to the hit rate, while alert zones that did not have an earthquake occur within them in the forecast period contribute to the false alarm rate. In the resulting analysis the hit rate and false alarm rate are determined after optimizing and modifying the initial parameters using the receiver operating characteristic diagram. It is found that when modifying the cell size and threshold magnitude parameters within various training periods, hit and false alarm rates are obtained for specific regions in Western Canada using both recent seismicity and cumulative well production data. Certain areas are thus shown to be more prone to potential larger earthquakes based on both datasets. This has implications

Seismic‐hazard forecast for 2016 including induced and natural earthquakes in the central and eastern United States

USGS Publications Warehouse

Petersen, Mark D.; Mueller, Charles; Moschetti, Morgan P.; Hoover, Susan M.; Llenos, Andrea L.; Ellsworth, William L.; Michael, Andrew J.; Rubinstein, Justin L.; McGarr, Arthur F.; Rukstales, Kenneth S.

2016-01-01

The U.S. Geological Survey (USGS) has produced a one‐year (2016) probabilistic seismic‐hazard assessment for the central and eastern United States (CEUS) that includes contributions from both induced and natural earthquakes that are constructed with probabilistic methods using alternative data and inputs. This hazard assessment builds on our 2016 final model (Petersen et al., 2016) by adding sensitivity studies, illustrating hazard in new ways, incorporating new population data, and discussing potential improvements. The model considers short‐term seismic activity rates (primarily 2014–2015) and assumes that the activity rates will remain stationary over short time intervals. The final model considers different ways of categorizing induced and natural earthquakes by incorporating two equally weighted earthquake rate submodels that are composed of alternative earthquake inputs for catalog duration, smoothing parameters, maximum magnitudes, and ground‐motion models. These alternatives represent uncertainties on how we calculate earthquake occurrence and the diversity of opinion within the science community. In this article, we also test sensitivity to the minimum moment magnitude between M 4 and M 4.7 and the choice of applying a declustered catalog with b=1.0 rather than the full catalog with b=1.3. We incorporate two earthquake rate submodels: in the informed submodel we classify earthquakes as induced or natural, and in the adaptive submodel we do not differentiate. The alternative submodel hazard maps both depict high hazard and these are combined in the final model. Results depict several ground‐shaking measures as well as intensity and include maps showing a high‐hazard level (1% probability of exceedance in 1 year or greater). Ground motions reach 0.6g horizontal peak ground acceleration (PGA) in north‐central Oklahoma and southern Kansas, and about 0.2g PGA in the Raton basin of Colorado and New Mexico, in central Arkansas, and in

Time-Series Forecast Modeling on High-Bandwidth Network Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoo, Wucherl; Sim, Alex

With the increasing number of geographically distributed scientific collaborations and the growing sizes of scientific data, it has become challenging for users to achieve the best possible network performance on a shared network. In this paper, we have developed a model to forecast expected bandwidth utilization on high-bandwidth wide area networks. The forecast model can improve the efficiency of the resource utilization and scheduling of data movements on high-bandwidth networks to accommodate ever increasing data volume for large-scale scientific data applications. A univariate time-series forecast model is developed with the Seasonal decomposition of Time series by Loess (STL) and themore » AutoRegressive Integrated Moving Average (ARIMA) on Simple Network Management Protocol (SNMP) path utilization measurement data. Compared with the traditional approach such as Box-Jenkins methodology to train the ARIMA model, our forecast model reduces computation time up to 92.6 %. It also shows resilience against abrupt network usage changes. Finally, our forecast model conducts the large number of multi-step forecast, and the forecast errors are within the mean absolute deviation (MAD) of the monitored measurements.« less

Time-Series Forecast Modeling on High-Bandwidth Network Measurements

DOE PAGES

Yoo, Wucherl; Sim, Alex

2016-06-24

With the increasing number of geographically distributed scientific collaborations and the growing sizes of scientific data, it has become challenging for users to achieve the best possible network performance on a shared network. In this paper, we have developed a model to forecast expected bandwidth utilization on high-bandwidth wide area networks. The forecast model can improve the efficiency of the resource utilization and scheduling of data movements on high-bandwidth networks to accommodate ever increasing data volume for large-scale scientific data applications. A univariate time-series forecast model is developed with the Seasonal decomposition of Time series by Loess (STL) and themore » AutoRegressive Integrated Moving Average (ARIMA) on Simple Network Management Protocol (SNMP) path utilization measurement data. Compared with the traditional approach such as Box-Jenkins methodology to train the ARIMA model, our forecast model reduces computation time up to 92.6 %. It also shows resilience against abrupt network usage changes. Finally, our forecast model conducts the large number of multi-step forecast, and the forecast errors are within the mean absolute deviation (MAD) of the monitored measurements.« less

Verification of short lead time forecast models: applied to Kp and Dst forecasting

NASA Astrophysics Data System (ADS)

Wintoft, Peter; Wik, Magnus

2016-04-01

In the ongoing EU/H2020 project PROGRESS models that predicts Kp, Dst, and AE from L1 solar wind data will be used as inputs to radiation belt models. The possible lead times from L1 measurements are shorter (10s of minutes to hours) than the typical duration of the physical phenomena that should be forecast. Under these circumstances several metrics fail to single out trivial cases, such as persistence. In this work we explore metrics and approaches for short lead time forecasts. We apply these to current Kp and Dst forecast models. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 637302.

Detecting and Characterizing Repeating Earthquake Sequences During Volcanic Eruptions

NASA Astrophysics Data System (ADS)

Tepp, G.; Haney, M. M.; Wech, A.

2017-12-01

A major challenge in volcano seismology is forecasting eruptions. Repeating earthquake sequences often precede volcanic eruptions or lava dome activity, providing an opportunity for short-term eruption forecasting. Automatic detection of these sequences can lead to timely eruption notification and aid in continuous monitoring of volcanic systems. However, repeating earthquake sequences may also occur after eruptions or along with magma intrusions that do not immediately lead to an eruption. This additional challenge requires a better understanding of the processes involved in producing these sequences to distinguish those that are precursory. Calculation of the inverse moment rate and concepts from the material failure forecast method can lead to such insights. The temporal evolution of the inverse moment rate is observed to differ for precursory and non-precursory sequences, and multiple earthquake sequences may occur concurrently. These observations suggest that sequences may occur in different locations or through different processes. We developed an automated repeating earthquake sequence detector and near real-time alarm to send alerts when an in-progress sequence is identified. Near real-time inverse moment rate measurements can further improve our ability to forecast eruptions by allowing for characterization of sequences. We apply the detector to eruptions of two Alaskan volcanoes: Bogoslof in 2016-2017 and Redoubt Volcano in 2009. The Bogoslof eruption produced almost 40 repeating earthquake sequences between its start in mid-December 2016 and early June 2017, 21 of which preceded an explosive eruption, and 2 sequences in the months before eruptive activity. Three of the sequences occurred after the implementation of the alarm in late March 2017 and successfully triggered alerts. The nearest seismometers to Bogoslof are over 45 km away, requiring a detector that can work with few stations and a relatively low signal-to-noise ratio. During the Redoubt

Global Earthquake Activity Rate models based on version 2 of the Global Strain Rate Map

NASA Astrophysics Data System (ADS)

Bird, P.; Kreemer, C.; Kagan, Y. Y.; Jackson, D. D.

2013-12-01

Global Earthquake Activity Rate (GEAR) models have usually been based on either relative tectonic motion (fault slip rates and/or distributed strain rates), or on smoothing of seismic catalogs. However, a hybrid approach appears to perform better than either parent, at least in some retrospective tests. First, we construct a Tectonic ('T') forecast of shallow (≤ 70 km) seismicity based on global plate-boundary strain rates from version 2 of the Global Strain Rate Map. Our approach is the SHIFT (Seismic Hazard Inferred From Tectonics) method described by Bird et al. [2010, SRL], in which the character of the strain rate tensor (thrusting and/or strike-slip and/or normal) is used to select the most comparable type of plate boundary for calibration of the coupled seismogenic lithosphere thickness and corner magnitude. One difference is that activity of offshore plate boundaries is spatially smoothed using empirical half-widths [Bird & Kagan, 2004, BSSA] before conversion to seismicity. Another is that the velocity-dependence of coupling in subduction and continental-convergent boundaries [Bird et al., 2009, BSSA] is incorporated. Another forecast component is the smoothed-seismicity ('S') forecast model of [Kagan & Jackson, 1994, JGR; Kagan & Jackson, 2010, GJI], which was based on optimized smoothing of the shallow part of the GCMT catalog, years 1977-2004. Both forecasts were prepared for threshold magnitude 5.767. Then, we create hybrid forecasts by one of 3 methods: (a) taking the greater of S or T; (b) simple weighted-average of S and T; or (c) log of the forecast rate is a weighted average of the logs of S and T. In methods (b) and (c) there is one free parameter, which is the fractional contribution from S. All hybrid forecasts are normalized to the same global rate. Pseudo-prospective tests for 2005-2012 (using versions of S and T calibrated on years 1977-2004) show that many hybrid models outperform both parents (S and T), and that the optimal weight on S

Weather forecasting based on hybrid neural model

NASA Astrophysics Data System (ADS)

Saba, Tanzila; Rehman, Amjad; AlGhamdi, Jarallah S.

2017-11-01

Making deductions and expectations about climate has been a challenge all through mankind's history. Challenges with exact meteorological directions assist to foresee and handle problems well in time. Different strategies have been investigated using various machine learning techniques in reported forecasting systems. Current research investigates climate as a major challenge for machine information mining and deduction. Accordingly, this paper presents a hybrid neural model (MLP and RBF) to enhance the accuracy of weather forecasting. Proposed hybrid model ensure precise forecasting due to the specialty of climate anticipating frameworks. The study concentrates on the data representing Saudi Arabia weather forecasting. The main input features employed to train individual and hybrid neural networks that include average dew point, minimum temperature, maximum temperature, mean temperature, average relative moistness, precipitation, normal wind speed, high wind speed and average cloudiness. The output layer composed of two neurons to represent rainy and dry weathers. Moreover, trial and error approach is adopted to select an appropriate number of inputs to the hybrid neural network. Correlation coefficient, RMSE and scatter index are the standard yard sticks adopted for forecast accuracy measurement. On individual standing MLP forecasting results are better than RBF, however, the proposed simplified hybrid neural model comes out with better forecasting accuracy as compared to both individual networks. Additionally, results are better than reported in the state of art, using a simple neural structure that reduces training time and complexity.

Toward a comprehensive areal model of earthquake-induced landslides

USGS Publications Warehouse

Miles, S.B.; Keefer, D.K.

2009-01-01

This paper provides a review of regional-scale modeling of earthquake-induced landslide hazard with respect to the needs for disaster risk reduction and sustainable development. Based on this review, it sets out important research themes and suggests computing with words (CW), a methodology that includes fuzzy logic systems, as a fruitful modeling methodology for addressing many of these research themes. A range of research, reviewed here, has been conducted applying CW to various aspects of earthquake-induced landslide hazard zonation, but none facilitate comprehensive modeling of all types of earthquake-induced landslides. A new comprehensive areal model of earthquake-induced landslides (CAMEL) is introduced here that was developed using fuzzy logic systems. CAMEL provides an integrated framework for modeling all types of earthquake-induced landslides using geographic information systems. CAMEL is designed to facilitate quantitative and qualitative representation of terrain conditions and knowledge about these conditions on the likely areal concentration of each landslide type. CAMEL is highly modifiable and adaptable; new knowledge can be easily added, while existing knowledge can be changed to better match local knowledge and conditions. As such, CAMEL should not be viewed as a complete alternative to other earthquake-induced landslide models. CAMEL provides an open framework for incorporating other models, such as Newmark's displacement method, together with previously incompatible empirical and local knowledge. ?? 2009 ASCE.

Assessment of GNSS-based height data of multiple ships for measuring and forecasting great tsunamis

NASA Astrophysics Data System (ADS)

Inazu, Daisuke; Waseda, Takuji; Hibiya, Toshiyuki; Ohta, Yusaku

2016-12-01

Ship height positioning by the Global Navigation Satellite System (GNSS) was investigated for measuring and forecasting great tsunamis. We first examined GNSS height-positioning data of a navigating vessel. If we use the kinematic precise point positioning (PPP) method, tsunamis greater than 10-1 m will be detected by ship height positioning. Based on Automatic Identification System (AIS) data, we found that tens of cargo ships and tankers are usually identified to navigate over the Nankai Trough, southwest Japan. We assumed that a future Nankai Trough great earthquake tsunami will be observed by the kinematic PPP height positioning of an AIS-derived ship distribution, and examined the tsunami forecast capability of the offshore tsunami measurements based on the PPP-based ship height. A method to estimate the initial tsunami height distribution using offshore tsunami observations was used for forecasting. Tsunami forecast tests were carried out using simulated tsunami data by the PPP-based ship height of 92 cargo ships/tankers, and by currently operating deep-sea pressure and Global Positioning System (GPS) buoy observations at 71 stations over the Nankai Trough. The forecast capability using the PPP-based height of the 92 ships was shown to be comparable to or better than that using the operating offshore observatories at the 71 stations. We suppose that, immediately after the occurrence of a great earthquake, stations receiving successive ship information (AIS data) along certain areas of the coast would fail to acquire ship data due to strong ground shaking, especially near the epicenter. Such a situation would significantly deteriorate the tsunami-forecast capability using ship data. On the other hand, operational real-time analysis of seismic/geodetic data would be carried out for estimating a tsunamigenic fault model. Incorporating the seismic/geodetic fault model estimation into the tsunami forecast above possibly compensates for the deteriorated forecast

Forecasting database for the tsunami warning regional center for the western Mediterranean Sea

NASA Astrophysics Data System (ADS)

Gailler, A.; Hebert, H.; Loevenbruck, A.; Hernandez, B.

2010-12-01

Improvements in the availability of sea-level observations and advances in numerical modeling techniques are increasing the potential for tsunami warnings to be based on numerical model forecasts. Numerical tsunami propagation and inundation models are well developed, but they present a challenge to run in real-time, partly due to computational limitations and also to a lack of detailed knowledge on the earthquake rupture parameters. Through the establishment of the tsunami warning regional center for NE Atlantic and western Mediterranean Sea, the CEA is especially in charge of providing rapidly a map with uncertainties showing zones in the main axis of energy at the Mediterranean scale. The strategy is based initially on a pre-computed tsunami scenarios database, as source parameters available a short time after an earthquake occurs are preliminary and may be somewhat inaccurate. Existing numerical models are good enough to provide a useful guidance for warning structures to be quickly disseminated. When an event will occur, an appropriate variety of offshore tsunami propagation scenarios by combining pre-computed propagation solutions (single or multi sources) may be recalled through an automatic interface. This approach would provide quick estimates of tsunami offshore propagation, and aid hazard assessment and evacuation decision-making. As numerical model accuracy is inherently limited by errors in bathymetry and topography, and as inundation maps calculation is more complex and expensive in term of computational time, only tsunami offshore propagation modeling will be included in the forecasting database using a single sparse bathymetric computation grid for the numerical modeling. Because of too much variability in the mechanism of tsunamigenic earthquakes, all possible magnitudes cannot be represented in the scenarios database. In principle, an infinite number of tsunami propagation scenarios can be constructed by linear combinations of a finite number of

A radon-thoron isotope pair as a reliable earthquake precursor

PubMed Central

Hwa Oh, Yong; Kim, Guebuem

2015-01-01

Abnormal increases in radon (222Rn, half-life = 3.82 days) activity have occasionally been observed in underground environments before major earthquakes. However, 222Rn alone could not be used to forecast earthquakes since it can also be increased due to diffusive inputs over its lifetime. Here, we show that a very short-lived isotope, thoron (220Rn, half-life = 55.6 s; mean life = 80 s), in a cave can record earthquake signals without interference from other environmental effects. We monitored 220Rn together with 222Rn in air of a limestone-cave in Korea for one year. Unusually large 220Rn peaks were observed only in February 2011, preceding the 2011 M9.0 Tohoku-Oki Earthquake, Japan, while large 222Rn peaks were observed in both February 2011 and the summer. Based on our analyses, we suggest that the anomalous peaks of 222Rn and 220Rn activities observed in February were precursory signals related to the Tohoku-Oki Earthquake. Thus, the 220Rn-222Rn combined isotope pair method can present new opportunities for earthquake forecasting if the technique is extensively employed in earthquake monitoring networks around the world. PMID:26269105

Air Quality Forecasts Using the NASA GEOS Model

NASA Technical Reports Server (NTRS)

Keller, Christoph A.; Knowland, K. Emma; Nielsen, Jon E.; Orbe, Clara; Ott, Lesley; Pawson, Steven; Saunders, Emily; Duncan, Bryan; Follette-Cook, Melanie; Liu, Junhua;

Earthquake Predictability: Results From Aggregating Seismicity Data And Assessment Of Theoretical Individual Cases Via Synthetic Data

NASA Astrophysics Data System (ADS)

Adamaki, A.; Roberts, R.

2016-12-01

For many years an important aim in seismological studies has been forecasting the occurrence of large earthquakes. Despite some well-established statistical behavior of earthquake sequences, expressed by e.g. the Omori law for aftershock sequences and the Gutenburg-Richter distribution of event magnitudes, purely statistical approaches to short-term earthquake prediction have in general not been successful. It seems that better understanding of the processes leading to critical stress build-up prior to larger events is necessary to identify useful precursory activity, if this exists, and statistical analyses are an important tool in this context. There has been considerable debate on the usefulness or otherwise of foreshock studies for short-term earthquake prediction. We investigate generic patterns of foreshock activity using aggregated data and by studying not only strong but also moderate magnitude events. Aggregating empirical local seismicity time series prior to larger events observed in and around Greece reveals a statistically significant increasing rate of seismicity over 20 days prior to M>3.5 earthquakes. This increase cannot be explained by tempo-spatial clustering models such as ETAS, implying genuine changes in the mechanical situation just prior to larger events and thus the possible existence of useful precursory information. Because of tempo-spatial clustering, including aftershocks to foreshocks, even if such generic behavior exists it does not necessarily follow that foreshocks have the potential to provide useful precursory information for individual larger events. Using synthetic catalogs produced based on different clustering models and different presumed system sensitivities we are now investigating to what extent the apparently established generic foreshock rate acceleration may or may not imply that the foreshocks have potential in the context of routine forecasting of larger events. Preliminary results suggest that this is the case, but

Dispersion Modeling Using Ensemble Forecasts Compared to ETEX Measurements.

NASA Astrophysics Data System (ADS)

Straume, Anne Grete; N'dri Koffi, Ernest; Nodop, Katrin

1998-11-01

Numerous numerical models are developed to predict long-range transport of hazardous air pollution in connection with accidental releases. When evaluating and improving such a model, it is important to detect uncertainties connected to the meteorological input data. A Lagrangian dispersion model, the Severe Nuclear Accident Program, is used here to investigate the effect of errors in the meteorological input data due to analysis error. An ensemble forecast, produced at the European Centre for Medium-Range Weather Forecasts, is then used as model input. The ensemble forecast members are generated by perturbing the initial meteorological fields of the weather forecast. The perturbations are calculated from singular vectors meant to represent possible forecast developments generated by instabilities in the atmospheric flow during the early part of the forecast. The instabilities are generated by errors in the analyzed fields. Puff predictions from the dispersion model, using ensemble forecast input, are compared, and a large spread in the predicted puff evolutions is found. This shows that the quality of the meteorological input data is important for the success of the dispersion model. In order to evaluate the dispersion model, the calculations are compared with measurements from the European Tracer Experiment. The model manages to predict the measured puff evolution concerning shape and time of arrival to a fairly high extent, up to 60 h after the start of the release. The modeled puff is still too narrow in the advection direction.

Forecasting the mortality rates using Lee-Carter model and Heligman-Pollard model

NASA Astrophysics Data System (ADS)

Ibrahim, R. I.; Ngataman, N.; Abrisam, W. N. A. Wan Mohd

2017-09-01

Improvement in life expectancies has driven further declines in mortality. The sustained reduction in mortality rates and its systematic underestimation has been attracting the significant interest of researchers in recent years because of its potential impact on population size and structure, social security systems, and (from an actuarial perspective) the life insurance and pensions industry worldwide. Among all forecasting methods, the Lee-Carter model has been widely accepted by the actuarial community and Heligman-Pollard model has been widely used by researchers in modelling and forecasting future mortality. Therefore, this paper only focuses on Lee-Carter model and Heligman-Pollard model. The main objective of this paper is to investigate how accurately these two models will perform using Malaysian data. Since these models involves nonlinear equations that are explicitly difficult to solve, the Matrix Laboratory Version 8.0 (MATLAB 8.0) software will be used to estimate the parameters of the models. Autoregressive Integrated Moving Average (ARIMA) procedure is applied to acquire the forecasted parameters for both models as the forecasted mortality rates are obtained by using all the values of forecasted parameters. To investigate the accuracy of the estimation, the forecasted results will be compared against actual data of mortality rates. The results indicate that both models provide better results for male population. However, for the elderly female population, Heligman-Pollard model seems to underestimate to the mortality rates while Lee-Carter model seems to overestimate to the mortality rates.

Multilayer Stock Forecasting Model Using Fuzzy Time Series

PubMed Central

Javedani Sadaei, Hossein; Lee, Muhammad Hisyam

2014-01-01

After reviewing the vast body of literature on using FTS in stock market forecasting, certain deficiencies are distinguished in the hybridization of findings. In addition, the lack of constructive systematic framework, which can be helpful to indicate direction of growth in entire FTS forecasting systems, is outstanding. In this study, we propose a multilayer model for stock market forecasting including five logical significant layers. Every single layer has its detailed concern to assist forecast development by reconciling certain problems exclusively. To verify the model, a set of huge data containing Taiwan Stock Index (TAIEX), National Association of Securities Dealers Automated Quotations (NASDAQ), Dow Jones Industrial Average (DJI), and S&P 500 have been chosen as experimental datasets. The results indicate that the proposed methodology has the potential to be accepted as a framework for model development in stock market forecasts using FTS. PMID:24605058

Probabilistic In Situ Stress Estimation and Forecasting using Sequential Data Assimilation

NASA Astrophysics Data System (ADS)

Fichtner, A.; van Dinther, Y.; Kuensch, H. R.

2017-12-01

Our physical understanding and forecasting ability of earthquakes, and other solid Earth dynamic processes, is significantly hampered by limited indications on the evolving state of stress and strength on faults. Integrating observations and physics-based numerical modeling to quantitatively estimate this evolution of a fault's state is crucial. However, systematic attempts are limited and tenuous, especially in light of the scarcity and uncertainty of natural data and the difficulty of modelling the physics governing earthquakes. We adopt the statistical framework of sequential data assimilation - extensively developed for weather forecasting - to efficiently integrate observations and prior knowledge in a forward model, while acknowledging errors in both. To prove this concept we perform a perfect model test in a simplified subduction zone setup, where we assimilate synthetic noised data on velocities and stresses from a single location. Using an Ensemble Kalman Filter, these data and their errors are assimilated to update 150 ensemble members from a Partial Differential Equation-driven seismic cycle model. Probabilistic estimates of fault stress and dynamic strength evolution capture the truth exceptionally well. This is possible, because the sampled error covariance matrix contains prior information from the physics that relates velocities, stresses and pressure at the surface to those at the fault. During the analysis step, stress and strength distributions are thus reconstructed such that fault coupling can be updated to either inhibit or trigger events. In the subsequent forecast step the physical equations are solved to propagate the updated states forward in time and thus provide probabilistic information on the occurrence of the next event. At subsequent assimilation steps, the system's forecasting ability turns out to be significantly better than that of a periodic recurrence model (requiring an alarm 17% vs. 68% of the time). This thus provides distinct

Real-time Social Internet Data to Guide Forecasting Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Del Valle, Sara Y.

Our goal is to improve decision support by monitoring and forecasting events using social media, mathematical models, and quantifying model uncertainty. Our approach is real-time, data-driven forecasts with quantified uncertainty: Not just for weather anymore. Information flow from human observations of events through an Internet system and classification algorithms is used to produce quantitatively uncertain forecast. In summary, we want to develop new tools to extract useful information from Internet data streams, develop new approaches to assimilate real-time information into predictive models, validate approaches by forecasting events, and our ultimate goal is to develop an event forecasting system using mathematicalmore » approaches and heterogeneous data streams.« less

Excel, Earthquakes, and Moneyball: exploring Cascadia earthquake probabilities using spreadsheets and baseball analogies

NASA Astrophysics Data System (ADS)

Campbell, M. R.; Salditch, L.; Brooks, E. M.; Stein, S.; Spencer, B. D.

2017-12-01

Much recent media attention focuses on Cascadia's earthquake hazard. A widely cited magazine article starts "An earthquake will destroy a sizable portion of the coastal Northwest. The question is when." Stories include statements like "a massive earthquake is overdue", "in the next 50 years, there is a 1-in-10 chance a "really big one" will erupt," or "the odds of the big Cascadia earthquake happening in the next fifty years are roughly one in three." These lead students to ask where the quoted probabilities come from and what they mean. These probability estimates involve two primary choices: what data are used to describe when past earthquakes happened and what models are used to forecast when future earthquakes will happen. The data come from a 10,000-year record of large paleoearthquakes compiled from subsidence data on land and turbidites, offshore deposits recording submarine slope failure. Earthquakes seem to have happened in clusters of four or five events, separated by gaps. Earthquakes within a cluster occur more frequently and regularly than in the full record. Hence the next earthquake is more likely if we assume that we are in the recent cluster that started about 1700 years ago, than if we assume the cluster is over. Students can explore how changing assumptions drastically changes probability estimates using easy-to-write and display spreadsheets, like those shown below. Insight can also come from baseball analogies. The cluster issue is like deciding whether to assume that a hitter's performance in the next game is better described by his lifetime record, or by the past few games, since he may be hitting unusually well or in a slump. The other big choice is whether to assume that the probability of an earthquake is constant with time, or is small immediately after one occurs and then grows with time. This is like whether to assume that a player's performance is the same from year to year, or changes over their career. Thus saying "the chance of

Solomon Islands 2007 Tsunami Near-Field Modeling and Source Earthquake Deformation

NASA Astrophysics Data System (ADS)

Uslu, B.; Wei, Y.; Fritz, H.; Titov, V.; Chamberlin, C.

2008-12-01

The earthquake of 1 April 2007 left behind momentous footages of crust rupture and tsunami impact along the coastline of Solomon Islands (Fritz and Kalligeris, 2008; Taylor et al., 2008; McAdoo et al., 2008; PARI, 2008), while the undisturbed tsunami signals were also recorded at nearby deep-ocean tsunameters and coastal tide stations. These multi-dimensional measurements provide valuable datasets to tackle the challenging aspects at the tsunami source directly by inversion from tsunameter records in real time (available in a time frame of minutes), and its relationship with the seismic source derived either from the seismometer records (available in a time frame of hours or days) or from the crust rupture measurements (available in a time frame of months or years). The tsunami measurements in the near field, including the complex vertical crust motion and tsunami runup, are particularly critical to help interpreting the tsunami source. This study develops high-resolution inundation models for the Solomon Islands to compute the near-field tsunami impact. Using these models, this research compares the tsunameter-derived tsunami source with the seismic-derived earthquake sources from comprehensive perceptions, including vertical uplift and subsidence, tsunami runup heights and their distributional pattern among the islands, deep-ocean tsunameter measurements, and near- and far-field tide gauge records. The present study stresses the significance of the tsunami magnitude, source location, bathymetry and topography in accurately modeling the generation, propagation and inundation of the tsunami waves. This study highlights the accuracy and efficiency of the tsunameter-derived tsunami source in modeling the near-field tsunami impact. As the high- resolution models developed in this study will become part of NOAA's tsunami forecast system, these results also suggest expanding the system for potential applications in tsunami hazard assessment, search and rescue operations

The Geological Susceptibility of Induced Earthquakes in the Duvernay Play

NASA Astrophysics Data System (ADS)

Pawley, Steven; Schultz, Ryan; Playter, Tiffany; Corlett, Hilary; Shipman, Todd; Lyster, Steven; Hauck, Tyler

2018-02-01

Presently, consensus on the incorporation of induced earthquakes into seismic hazard has yet to be established. For example, the nonstationary, spatiotemporal nature of induced earthquakes is not well understood. Specific to the Western Canada Sedimentary Basin, geological bias in seismogenic activation potential has been suggested to control the spatial distribution of induced earthquakes regionally. In this paper, we train a machine learning algorithm to systemically evaluate tectonic, geomechanical, and hydrological proxies suspected to control induced seismicity. Feature importance suggests that proximity to basement, in situ stress, proximity to fossil reef margins, lithium concentration, and rate of natural seismicity are among the strongest model predictors. Our derived seismogenic potential map faithfully reproduces the current distribution of induced seismicity and is suggestive of other regions which may be prone to induced earthquakes. The refinement of induced seismicity geological susceptibility may become an important technique to identify significant underlying geological features and address induced seismic hazard forecasting issues.

Stigma in science: the case of earthquake prediction.

PubMed

Joffe, Helene; Rossetto, Tiziana; Bradley, Caroline; O'Connor, Cliodhna

2018-01-01

This paper explores how earthquake scientists conceptualise earthquake prediction, particularly given the conviction of six earthquake scientists for manslaughter (subsequently overturned) on 22 October 2012 for having given inappropriate advice to the public prior to the L'Aquila earthquake of 6 April 2009. In the first study of its kind, semi-structured interviews were conducted with 17 earthquake scientists and the transcribed interviews were analysed thematically. The scientists primarily denigrated earthquake prediction, showing strong emotive responses and distancing themselves from earthquake 'prediction' in favour of 'forecasting'. Earthquake prediction was regarded as impossible and harmful. The stigmatisation of the subject is discussed in the light of research on boundary work and stigma in science. The evaluation reveals how mitigation becomes the more favoured endeavour, creating a normative environment that disadvantages those who continue to pursue earthquake prediction research. Recommendations are made for communication with the public on earthquake risk, with a focus on how scientists portray uncertainty. © 2018 The Author(s). Disasters © Overseas Development Institute, 2018.

Sensitivity of Earthquake Loss Estimates to Source Modeling Assumptions and Uncertainty

USGS Publications Warehouse

Reasenberg, Paul A.; Shostak, Nan; Terwilliger, Sharon

2006-01-01

Introduction: This report explores how uncertainty in an earthquake source model may affect estimates of earthquake economic loss. Specifically, it focuses on the earthquake source model for the San Francisco Bay region (SFBR) created by the Working Group on California Earthquake Probabilities. The loss calculations are made using HAZUS-MH, a publicly available computer program developed by the Federal Emergency Management Agency (FEMA) for calculating future losses from earthquakes, floods and hurricanes within the United States. The database built into HAZUS-MH includes a detailed building inventory, population data, data on transportation corridors, bridges, utility lifelines, etc. Earthquake hazard in the loss calculations is based upon expected (median value) ground motion maps called ShakeMaps calculated for the scenario earthquake sources defined in WGCEP. The study considers the effect of relaxing certain assumptions in the WG02 model, and explores the effect of hypothetical reductions in epistemic uncertainty in parts of the model. For example, it addresses questions such as what would happen to the calculated loss distribution if the uncertainty in slip rate in the WG02 model were reduced (say, by obtaining additional geologic data)? What would happen if the geometry or amount of aseismic slip (creep) on the region's faults were better known? And what would be the effect on the calculated loss distribution if the time-dependent earthquake probability were better constrained, either by eliminating certain probability models or by better constraining the inherent randomness in earthquake recurrence? The study does not consider the effect of reducing uncertainty in the hazard introduced through models of attenuation and local site characteristics, although these may have a comparable or greater effect than does source-related uncertainty. Nor does it consider sources of uncertainty in the building inventory, building fragility curves, and other assumptions

Method to Determine Appropriate Source Models of Large Earthquakes Including Tsunami Earthquakes for Tsunami Early Warning in Central America

NASA Astrophysics Data System (ADS)

Tanioka, Yuichiro; Miranda, Greyving Jose Arguello; Gusman, Aditya Riadi; Fujii, Yushiro

2017-08-01

Large earthquakes, such as the Mw 7.7 1992 Nicaragua earthquake, have occurred off the Pacific coasts of El Salvador and Nicaragua in Central America and have generated distractive tsunamis along these coasts. It is necessary to determine appropriate fault models before large tsunamis hit the coast. In this study, first, fault parameters were estimated from the W-phase inversion, and then an appropriate fault model was determined from the fault parameters and scaling relationships with a depth dependent rigidity. The method was tested for four large earthquakes, the 1992 Nicaragua tsunami earthquake (Mw7.7), the 2001 El Salvador earthquake (Mw7.7), the 2004 El Astillero earthquake (Mw7.0), and the 2012 El Salvador-Nicaragua earthquake (Mw7.3), which occurred off El Salvador and Nicaragua in Central America. The tsunami numerical simulations were carried out from the determined fault models. We found that the observed tsunami heights, run-up heights, and inundation areas were reasonably well explained by the computed ones. Therefore, our method for tsunami early warning purpose should work to estimate a fault model which reproduces tsunami heights near the coast of El Salvador and Nicaragua due to large earthquakes in the subduction zone.

Human-model hybrid Korean air quality forecasting system.

PubMed

Chang, Lim-Seok; Cho, Ara; Park, Hyunju; Nam, Kipyo; Kim, Deokrae; Hong, Ji-Hyoung; Song, Chang-Keun

2016-09-01

The Korean national air quality forecasting system, consisting of the Weather Research and Forecasting, the Sparse Matrix Operator Kernel Emissions, and the Community Modeling and Analysis (CMAQ), commenced from August 31, 2013 with target pollutants of particulate matters (PM) and ozone. Factors contributing to PM forecasting accuracy include CMAQ inputs of meteorological field and emissions, forecasters' capacity, and inherent CMAQ limit. Four numerical experiments were conducted including two global meteorological inputs from the Global Forecast System (GFS) and the Unified Model (UM), two emissions from the Model Intercomparison Study Asia (MICS-Asia) and the Intercontinental Chemical Transport Experiment (INTEX-B) for the Northeast Asia with Clear Air Policy Support System (CAPSS) for South Korea, and data assimilation of the Monitoring Atmospheric Composition and Climate (MACC). Significant PM underpredictions by using both emissions were found for PM mass and major components (sulfate and organic carbon). CMAQ predicts PM2.5 much better than PM10 (NMB of PM2.5: -20~-25%, PM10: -43~-47%). Forecasters' error usually occurred at the next day of high PM event. Once CMAQ fails to predict high PM event the day before, forecasters are likely to dismiss the model predictions on the next day which turns out to be true. The best combination of CMAQ inputs is the set of UM global meteorological field, MICS-Asia and CAPSS 2010 emissions with the NMB of -12.3%, the RMSE of 16.6μ/m(3) and the R(2) of 0.68. By using MACC data as an initial and boundary condition, the performance skill of CMAQ would be improved, especially in the case of undefined coarse emission. A variety of methods such as ensemble and data assimilation are considered to improve further the accuracy of air quality forecasting, especially for high PM events to be comparable to for all cases. The growing utilization of the air quality forecast induced the public strongly to demand that the accuracy of the

A channel dynamics model for real-time flood forecasting

USGS Publications Warehouse

Hoos, Anne B.; Koussis, Antonis D.; Beale, Guy O.

1989-01-01

A new channel dynamics scheme (alternative system predictor in real time (ASPIRE)), designed specifically for real-time river flow forecasting, is introduced to reduce uncertainty in the forecast. ASPIRE is a storage routing model that limits the influence of catchment model forecast errors to the downstream station closest to the catchment. Comparisons with the Muskingum routing scheme in field tests suggest that the ASPIRE scheme can provide more accurate forecasts, probably because discharge observations are used to a maximum advantage and routing reaches (and model errors in each reach) are uncoupled. Using ASPIRE in conjunction with the Kalman filter did not improve forecast accuracy relative to a deterministic updating procedure. Theoretical analysis suggests that this is due to a large process noise to measurement noise ratio.

Improving wave forecasting by integrating ensemble modelling and machine learning

NASA Astrophysics Data System (ADS)

O'Donncha, F.; Zhang, Y.; James, S. C.

2017-12-01

Modern smart-grid networks use technologies to instantly relay information on supply and demand to support effective decision making. Integration of renewable-energy resources with these systems demands accurate forecasting of energy production (and demand) capacities. For wave-energy converters, this requires wave-condition forecasting to enable estimates of energy production. Current operational wave forecasting systems exhibit substantial errors with wave-height RMSEs of 40 to 60 cm being typical, which limits the reliability of energy-generation predictions thereby impeding integration with the distribution grid. In this study, we integrate physics-based models with statistical learning aggregation techniques that combine forecasts from multiple, independent models into a single "best-estimate" prediction of the true state. The Simulating Waves Nearshore physics-based model is used to compute wind- and currents-augmented waves in the Monterey Bay area. Ensembles are developed based on multiple simulations perturbing input data (wave characteristics supplied at the model boundaries and winds) to the model. A learning-aggregation technique uses past observations and past model forecasts to calculate a weight for each model. The aggregated forecasts are compared to observation data to quantify the performance of the model ensemble and aggregation techniques. The appropriately weighted ensemble model outperforms an individual ensemble member with regard to forecasting wave conditions.

Seismic Moment, Seismic Energy, and Source Duration of Slow Earthquakes: Application of Brownian slow earthquake model to three major subduction zones

NASA Astrophysics Data System (ADS)

Ide, Satoshi; Maury, Julie

2018-04-01

Tectonic tremors, low-frequency earthquakes, very low-frequency earthquakes, and slow slip events are all regarded as components of broadband slow earthquakes, which can be modeled as a stochastic process using Brownian motion. Here we show that the Brownian slow earthquake model provides theoretical relationships among the seismic moment, seismic energy, and source duration of slow earthquakes and that this model explains various estimates of these quantities in three major subduction zones: Japan, Cascadia, and Mexico. While the estimates for these three regions are similar at the seismological frequencies, the seismic moment rates are significantly different in the geodetic observation. This difference is ascribed to the difference in the characteristic times of the Brownian slow earthquake model, which is controlled by the width of the source area. We also show that the model can include non-Gaussian fluctuations, which better explains recent findings of a near-constant source duration for low-frequency earthquake families.