Alert Optimization of the PLUM Earthquake Early Warning Algorithm for the Western United States

ABSTRACT We determine an optimal alerting configuration for the propagation of local undamped motion (PLUM) earthquake early warning (EEW) algorithm for use by the U.S. ShakeAlert system covering California, Oregon, and Washington. All EEW systems should balance the primary goal of providing timely alerts for impactful or potentially damaging shaking while limiting alerts for shaking that is too low to be of concern (precautionary alerts). The PLUM EEW algorithm forward predicts observed ground motions to nearby sites within a defined radius without accounting for attenuation, avoiding the earthquake source parameter estimation step of most EEW algorithms. PLUM was originally developed in Japan where the alert regions and ground motions for which alerts are issued differ from those implemented by ShakeAlert. We compare predicted ground motions from PLUM to ShakeMap-reported ground motions for a set of 22 U.S. West Coast earthquakes of magnitude 4.4–7.2 and evaluate available warning times. We examine a range of prediction radii (20–100 km), thresholds used to issue an alert (alert threshold), and levels of impactful or potentially damaging shaking (target threshold). We find optimal performance when the alert threshold is close to the target threshold, although higher target ground motions benefit from somewhat lower alert thresholds to ensure timely alerts. We also find that performance, measured as the cost reduction that a user can achieve, depends on the user’s tolerance for precautionary alerts. Users with a low target threshold and high tolerance for precautionary alerts achieve optimal performance when larger prediction radii (60–100 km) are used. In contrast, users with high target thresholds and low tolerance for precautionary alerts achieve better performance for smaller prediction radii (30–60 km). Therefore, setting the PLUM prediction radius to 60 km balances the needs of many users and provides warning times of up to ∼20 s.

The Impact of 3D Finite-Fault Information on Ground-Motion Forecasting for Earthquake Early Warning

ABSTRACT We identify aspects of finite-source parameterization that strongly affect the accuracy of estimated ground motion for earthquake early warning (EEW). EEW systems aim to alert users to impending shaking before it reaches them. The U.S. West Coast EEW system, ShakeAlert, currently uses two algorithms based on seismic data to characterize the earthquake’s location, magnitude, and origin time, treating it as a point or line source. From this information, ShakeAlert calculates shaking intensity and alerts locations where shaking estimates exceed a threshold. Several geodetic EEW algorithms under development would provide 3D finite-fault information. We investigate conditions under which this information produces sufficiently better intensity estimates to potentially improve alerting. Using scenario crustal and subduction interface sources, we (1) identify the most influential source geometry parameters for an EEW algorithm’s shaking forecast, and (2) assess the intensity alert thresholds and magnitude ranges for which more detailed source characterization affects alert accuracy. We find that alert regions determined using 3D-source representations of correct magnitude and faulting mechanism are generally more accurate than those obtained using line sources. If a line-source representation is used and magnitude is calculated from the estimated length, then incorrect length estimates significantly degrade alert region accuracy. In detail, the value of 3D-source characterization depends on the user’s chosen alert threshold, tectonic regime, and faulting style. For the suite of source models we tested, the error in shaking intensity introduced by incorrect geometry could reach levels comparable to the intrinsic uncertainty in ground-motion calculations (e.g., 0.5–1.3 modified Mercalli intensity [MMI] units for MMI 4.5) but, especially for crustal sources, was often less. For subduction interface sources, 3D representations substantially improved alert area accuracy compared to line sources, and incorrect geometry parameters were more likely to cause error in calculated shaking intensity that exceeded uncertainties.

Retrospective Study of FinDer Algorithm During the 2019, Ridgecrest Earthquake Sequence

Real-time characterization of evolving rupture is crucial for mitigating against seismic hazards exposed to potentially devastating earthquake events in EEWs (Earthquake Early Warning system). Currently, FinDer (Finite Fault Rupture Detector) algorithm explicitly utilizes observed ground motion pattern to solve for the evolving rupture to generate alerts for early warning purpose, which is currently contributing to ShakeAlert EEW system in West Coast of United States, within the area covered by the Advanced National Seismic System (ANSS) network. Here we implement FinDer offline to explore its feasibility assuming ideal field telemetry on a database of real earthquakes with magnitude M ≥5.0 occurring in Ridgecrest, Southern California in 2019. We specially focus on evaluating the performance of FinDer through end-user-orientated analysis in terms of warning time and accuracy of ground shaking prediction. Overall, FinDer classifies alerts with a rate of success over 74% across a broad range of alert criteria, substantial fraction of sites can be successfully alerted including the most difficult cases with high ground motion intensities regardless of invariable few seconds of warning time. FinDer can be configured to generate more useful alerts with higher cost savings by applying lower alert threshold during the Ridgecrest earthquake sequence. Furthermore, although large fractions of sites would have been timely alerted, it is significantly challenging for predicting accurately the moderate or worse intensities (Modified Mercalli Intensity > 5.5) in advance even if applying lower alert threshold and higher damage threshold. Nonetheless, FinDer performs well in an evolutionary manner to guarantee reliable alerts by resorting to a consistent description of point source or occurring rupture.

Effect of Fixing Earthquake Depth in ShakeAlert Algorithms on Performance for Intraslab Earthquakes

We investigate whether assuming a fixed shallow depth in the ShakeAlert network-based earthquake early warning system is sufficient to produce accurate ground-motion based alerts for intraslab earthquakes. ShakeAlert currently uses a fixed focal depth of 8 km to estimate earthquake location and magnitude. This is an appropriate way to reduce computational costs without compromising alert accuracy in California, where earthquakes typically occur on shallow crustal faults. In the Pacific Northwest (PNW), however, the most common moderate-magnitude events occur within the subducting Juan de Fuca slab at depths between ∼35 and 65 km. Using a dataset of seismic recordings from 37 Mw 4.5+ intraslab earthquakes from the PNW and Chile, we replay events through the Earthquake Point-Source Integrated Code and eqInfo2GM algorithms to estimate source parameters and compute modified Mercalli intensity (MMI) alert threshold contours. Each event is replayed twice—once using a fixed 8 km depth and a second time using the actual catalog earthquake depth. For each depth scenario, we analyze MMI III and IV contours using various performance metrics to determine the number of correctly alerted sites and measure warning times. We determine that shallow depth replays are more likely to produce errors in location estimates of greater than 50 km if the event is located outside of a seismic network. When located within a seismic network, shallow and catalog depth replays have similar epicenter estimates. Results show that applying catalog earthquake depth does not improve the accuracy of magnitude estimates or MMI alert threshold contours, or increase warning times. We conclude that using a fixed shallow earthquake depth for intraslab earthquakes will not significantly impact alert accuracy in the PNW.

Influence of fertilization systems to the soil inorganic compounds. Case study: monocul-tures of cereals, leguminous and oleaginous

<p>The main objective of this article is to observe the variation of the content of inorganic compounds in the soil (cobalt, selenium, barium) under the influence of fertilization systems applied to different monocultures of cereals (wheat, corn), leguminous (peas) and oleaginous (sunflower). High concentrations of cobalt, selenium and barium with phytotoxicity effect on the soil and future crops were recorded mainly in the experimental parcels cultivated with corn, respectively with sunflower and fertilized with farmyard manure. The highest phytotoxicity effect on soil and future crop was recorded in the case of cobalt, for the experimental monoculture variant of corn fertilized with farmyard manure where the cobalt concentration in the soil exceeded the alert threshold / sensitive use (AT/SU) for inorganic compounds in the soil (51.2 mg/kg d.m.).</p>

Predicting malaria epidemics in Burkina Faso with machine learning

Accurately forecasting the case rate of malaria would enable key decision makers to intervene months before the onset of any outbreak, potentially saving lives. Until now, methods that forecast malaria have involved complicated numerical simulations that model transmission through a community. Here we present the first data-driven malaria epidemic early warning system that can predict the 13-week case rate in a primary health facility in Burkina Faso. Using the extraordinarily high-fidelity data of infant consultations taken from the Integrated e-Diagnostic Approach (IeDA) system that has been rolled out throughout Burkina Faso, we train a combination of Gaussian Processes and Random Forest Regressors to estimate the weekly number of malaria cases over a 13 week period. We test our algorithm on historical epidemics and find that for our lowest threshold for an epidemic alert, our algorithm has 30% precision with > 99% recall at raising an alert. This rises to > 99% precision and 5% recall for the high alert threshold. Our two-tailed predictions have an average 1σ and 2σ precision of 5 cases and 30 cases respectively.

CONTRIBUTIONS TO THE STUDY OF HEAVY METALS CONTENT IN THE SOILS OF THE BALTI URBAN ECOSYSTEM

The paper presents the evaluation of the heavy content in the soils of the Balti urban ecosystem. Is predominates typically moderately humiferous chernozem soils. Based on the obtained results, it was established that the soils pH is weak-alkaline. The content of heavy metals in the edaphic component in some research sites exceeded the Alert Threshold for Pb, Cu, Zn. Values of total Pb content ranged from low to very high (18.5-98.61 mg/kg), Cu from low (17.48 mg/kg) to very high (134.63 mg/kg), Zn from low (38.92 mg/kg) to very high (311.34 mg/kg). Greater pollution with these heavy metals was founds in the Central-Western part of the city. For Cr were recorded very low content, and Ni – medium. Because the pH of the soil is weak-alkaline, these concentrations do not pose a danger to biotic components.

Assessment of public health notification thresholds for Clostridioides difficile in acute-care hospitals—Colorado and Tennessee, 2018

Objectives: We aimed to identify a threshold number of Clostridioides difficile infections (CDI) for acute-care hospitals (ACHs) to notify public health agencies of outbreaks and we aimed to determine whether thresholds can be used with existing surveillance strategies to further infection reduction goals. Design: Descriptive analysis of laboratory-identified CDI reported to the National Healthcare Safety Network by Colorado and Tennessee ACH inpatient units in 2018. Methods: Threshold levels of ≥2, ≥3, and ≥4 CDI events per calendar month per unit (unit month) were assessed to identify units that would trigger facility reporting to public health. Values meeting thresholds were defined as alerts. Recurrent alerts were defined as alerts from units meeting the threshold ≥2 times within 12 months. The presence of alerts was compared to the number of excess infections to identify high-burden facilities. Results: At an alert threshold of ≥2 CDI events per unit month, 204 alerts occurred among 43 Colorado ACHs and 290 among 78 Tennessee ACHs. At a threshold of ≥3, there were 59 and 61 alerts, and at a threshold of ≥4, there were 17 and 10 alerts in Colorado and Tennessee, respectively. In both Colorado and Tennessee, at a threshold of ≥3 nearly 50% of alerts were recurrent, and facilities with at least one alert in 2018 accounted for ∼85% of the statewide excess infections. Conclusions: An alert threshold of ≥3 CDI events per unit month is feasible for rapid identification of outbreaks in ACHs. This threshold can facilitate earlier assessments and interventions in high-burden facilities.

The Heavy Metal Status of Some Agricultural Soils

In order to evaluate the loadings of some agricultural soils with heavy metals, field studies were made across the Iasi County. The heavy metals concentration range were as follows: 15.4 - 36 mg/kg (Cu), 49 - 115 mg/kg (Zn), 7.4 - 20.4 mg/kg (Pb), 0.13 - 0.43 mg/kg (Cd), 6.9 - 13.15 mg/kg (Co), 25 - 100 mg/kg (Ni) and 463 - 798 mg/kg (Mn), respectively. The median of the heavy metals decreased in the next order: Mn (589) ] Zn (67) ] Ni (46) ]Cu (22,1)]Pb (12.1)]Co (10.2)]Cd (0.32). The studied heavy metal median was higher than the same metal median from European soils. According to the Romanian legislation, the normal values are exceeding in 13% the samples for Zn, 73% for Cu, 93% for Ni, and in one case, the value of Ni exceeded the alert threshold (75 mg/kg). A direct relationship between Cu, Pb, Zn and Co was noticed, which may indicate a common source of these metals. The Pearson`s coefficients of these elements were: Pb-Cu (0.863), Cu-Zn (0.826), Pb-Zn (0.74), Cu-Co (0.730), Pb-Co (0.703). According to the values of Pearson correlation coefficient, the significant positive correlations were identified between Cu, Zn, Pb, Co and clay content, while the same metals are highly negative correlated with CaCO3 and fine sand contents. In case of Pb, Co, and Mn no influence of agricultural activities can be detected, wich suggestes that geogenic factors control the contents of these heavy metals. The Cu content exhibited a positive correlation with total Nitrogen, while the Cd content showed a positive significant relationship only with Km content. On the other hand, the Ni content exhibited correlation with both Pm and Km concentrations. The correlations of Cu-Nt, Cd-Km, Ni-Pm, and Ni-Km could be an index of the anthropogenic input of Cd, Cu, and Ni from the use of fertilizers.