Citizen Science to Support Community-based Flood Early Warning and Resilience Building

NASA Astrophysics Data System (ADS)

Paul, J. D.; Buytaert, W.; Allen, S.; Ballesteros-Cánovas, J. A.; Bhusal, J.; Cieslik, K.; Clark, J.; Dewulf, A.; Dhital, M. R.; Hannah, D. M.; Liu, W.; Nayaval, J. L.; Schiller, A.; Smith, P. J.; Stoffel, M.; Supper, R.

2017-12-01

In Disaster Risk Management, an emerging shift has been noted from broad-scale, top-down assessments towards more participatory, community-based, bottom-up approaches. Combined with technologies for robust and low-cost sensor networks, a citizen science approach has recently emerged as a promising direction in the provision of extensive, real-time information for flood early warning systems. Here we present the framework and initial results of a major new international project, Landslide EVO, aimed at increasing local resilience against hydrologically induced disasters in western Nepal by exploiting participatory approaches to knowledge generation and risk governance. We identify three major technological developments that strongly support our approach to flood early warning and resilience building in Nepal. First, distributed sensor networks, participatory monitoring, and citizen science hold great promise in complementing official monitoring networks and remote sensing by generating site-specific information with local buy-in, especially in data-scarce regions. Secondly, the emergence of open source, cloud-based risk analysis platforms supports the construction of a modular, distributed, and potentially decentralised data processing workflow. Finally, linking data analysis platforms to social computer networks and ICT (e.g. mobile phones, tablets) allows tailored interfaces and people-centred decision- and policy-support systems to be built. Our proposition is that maximum impact is created if end-users are involved not only in data collection, but also over the entire project life-cycle, including the analysis and provision of results. In this context, citizen science complements more traditional knowledge generation practices, and also enhances multi-directional information provision, risk management, early-warning systems and local resilience building.

The Self-Organising Seismic Early Warning Information Network

NASA Astrophysics Data System (ADS)

Kühnlenz, F.; Eveslage, I.; Fischer, J.; Fleming, K. M.; Lichtblau, B.; Milkereit, C.; Picozzi, M.

2009-12-01

The Self-Organising Seismic Early Warning Information Network (SOSEWIN) represents a new approach for Earthquake Early Warning Systems (EEWS), consisting in taking advantage of novel wireless communications technologies without the need of a planned, centralised infrastructure. It also sets out to overcome problems of insufficient node density, which typically affects present existing early warning systems, by having the SOSEWIN seismological sensing units being comprised of low-cost components (generally bought "off-the-shelf"), with each unit initially costing 100's of Euros, in contrast to 1,000's to 10,000's for standard seismological stations. The reduced sensitivity of the new sensing units arising from the use of lower-cost components will be compensated by the network's density, which in the future is expected to number 100's to 1000's over areas served currently by the order of 10's of standard stations. The robustness, independence of infrastructure, spontaneous extensibility due to a self-healing/self-organizing character in the case of removing/failing or adding sensors makes SOSEWIN potentially useful for various use cases, e.g. monitoring of building structures or seismic microzonation. Nevertheless its main purpose is the earthquake early warning, for which reason the ground motion is continuously monitored by conventional accelerometers (3-component) and processed within a station. Based on this, the network itself decides whether an event is detected through cooperating stations. SEEDLink is used to store and provide access to the sensor data. Experiences and selected experiment results with the SOSEWIN-prototype installation in the Ataköy district of Istanbul (Turkey) are presented. SOSEWIN considers also the needs of earthquake task forces, which want to set-up a temporary seismic network rapidly and with light-weighted stations to record after-shocks. The wireless and self-organising character of this sensor network is of great value to do this job in a shorter time and with less manpower compared to using common seismic stations as we could see during the L'Aquila earthquake, where SOSEWIN was used to monitor damaged buildings. We present here the graphical front-end of SOSEWIN in its usage for different scenarios. It belongs to a management infrastructure based on GIS and database technologies and therefore coupling with existing infrastructures should be simplified. Connecting the domain expert’s laptop running the management software with a SOSEWIN may be fulfilled via any arbitrary node in the network (on-site access) or via a gateway node from a remote location using the internet. The scenarios focus on the needs of certain domain experts (seismologists or maybe engineers) and include the planning of a network installation, support during the installation process and testing of this installation. Another scenario mentions monitoring aspects of an already installed SOSEWIN and finally a scenario deals with the visualization of the alarming protocol detecting an earthquake event and issuing an early warning.

Early warning of illegal development for protected areas by integrating cellular automata with neural networks.

PubMed

Li, Xia; Lao, Chunhua; Liu, Yilun; Liu, Xiaoping; Chen, Yimin; Li, Shaoying; Ai, Bing; He, Zijian

2013-11-30

Ecological security has become a major issue under fast urbanization in China. As the first two cities in this country, Shenzhen and Dongguan issued the ordinance of Eco-designated Line of Control (ELC) to "wire" ecologically important areas for strict protection in 2005 and 2009 respectively. Early warning systems (EWS) are a useful tool for assisting the implementation ELC. In this study, a multi-model approach is proposed for the early warning of illegal development by integrating cellular automata (CA) and artificial neural networks (ANN). The objective is to prevent the ecological risks or catastrophe caused by such development at an early stage. The integrated model is calibrated by using the empirical information from both remote sensing and handheld GPS (global positioning systems). The MAR indicator which is the ratio of missing alarms to all the warnings is proposed for better assessment of the model performance. It is found that the fast urban development has caused significant threats to natural-area protection in the study area. The integration of CA, ANN and GPS provides a powerful tool for describing and predicting illegal development which is in highly non-linear and fragmented forms. The comparison shows that this multi-model approach has much better performances than the single-model approach for the early warning. Compared with the single models of CA and ANN, this integrated multi-model can improve the value of MAR by 65.48% and 5.17% respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

Earthquake Early Warning and Public Policy: Opportunities and Challenges

NASA Astrophysics Data System (ADS)

Goltz, J. D.; Bourque, L.; Tierney, K.; Riopelle, D.; Shoaf, K.; Seligson, H.; Flores, P.

2003-12-01

Development of an earthquake early warning capability and pilot project were objectives of TriNet, a 5-year (1997-2001) FEMA-funded project to develop a state-of-the-art digital seismic network in southern California. In parallel with research to assemble a protocol for rapid analysis of earthquake data and transmission of a signal by TriNet scientists and engineers, the public policy, communication and educational issues inherent in implementation of an earthquake early warning system were addressed by TriNet's outreach component. These studies included: 1) a survey that identified potential users of an earthquake early warning system and how an earthquake early warning might be used in responding to an event, 2) a review of warning systems and communication issues associated with other natural hazards and how lessons learned might be applied to an alerting system for earthquakes, 3) an analysis of organization, management and public policy issues that must be addressed if a broad-based warning system is to be developed and 4) a plan to provide earthquake early warnings to a small number of organizations in southern California as an experimental prototype. These studies provided needed insights into the social and cultural environment in which this new technology will be introduced, an environment with opportunities to enhance our response capabilities but also an environment with significant barriers to overcome to achieve a system that can be sustained and supported. In this presentation we will address the main public policy issues that were subjects of analysis in these studies. They include a discussion of the possible division of functions among organizations likely to be the principle partners in the management of an earthquake early warning system. Drawing on lessons learned from warning systems for other hazards, we will review the potential impacts of false alarms and missed events on warning system credibility, the acceptability of fully automated warning systems and equity issues associated with possible differential access to warnings. Finally, we will review the status of legal authorities and liabilities faced by organizations that assume various warning system roles and possible approaches to setting up a pilot project to introduce early warning. Our presentation will suggest that introducing an early warning system requires multi-disciplinary and multi-agency cooperation and thoughtful discussion among organizations likely to be providers and participants in an early warning system. Recalling our experience with earthquake prediction, we will look at early warning as a promising but unproven technology and recommend moving forward with caution and patience.

A Risk-Based Multi-Objective Optimization Concept for Early-Warning Monitoring Networks

NASA Astrophysics Data System (ADS)

Bode, F.; Loschko, M.; Nowak, W.

2014-12-01

Groundwater is a resource for drinking water and hence needs to be protected from contaminations. However, many well catchments include an inventory of known and unknown risk sources which cannot be eliminated, especially in urban regions. As matter of risk control, all these risk sources should be monitored. A one-to-one monitoring situation for each risk source would lead to a cost explosion and is even impossible for unknown risk sources. However, smart optimization concepts could help to find promising low-cost monitoring network designs.In this work we develop a concept to plan monitoring networks using multi-objective optimization. Our considered objectives are to maximize the probability of detecting all contaminations and the early warning time and to minimize the installation and operating costs of the monitoring network. A qualitative risk ranking is used to prioritize the known risk sources for monitoring. The unknown risk sources can neither be located nor ranked. Instead, we represent them by a virtual line of risk sources surrounding the production well.We classify risk sources into four different categories: severe, medium and tolerable for known risk sources and an extra category for the unknown ones. With that, early warning time and detection probability become individual objectives for each risk class. Thus, decision makers can identify monitoring networks which are valid for controlling the top risk sources, and evaluate the capabilities (or search for least-cost upgrade) to also cover moderate, tolerable and unknown risk sources. Monitoring networks which are valid for the remaining risk also cover all other risk sources but the early-warning time suffers.The data provided for the optimization algorithm are calculated in a preprocessing step by a flow and transport model. Uncertainties due to hydro(geo)logical phenomena are taken into account by Monte-Carlo simulations. To avoid numerical dispersion during the transport simulations we use the particle-tracking random walk method.

Food Security, Decision Making and the Use of Remote Sensing in Famine Early Warning Systems

NASA Technical Reports Server (NTRS)

Brown, Molly E.

2008-01-01

Famine early warning systems use remote sensing in combination with socio-economic and household food economy analysis to provide timely and rigorous information on emerging food security crises. The Famine Early Warning Systems Network (FEWS NET) is the US Agency for International Development's decision support system in 20 African countries, as well as in Guatemala, Haiti and Afghanistan. FEWS NET provides early and actionable policy guidance for the US Government and its humanitarian aid partners. As we move into an era of climate change where weather hazards will become more frequent and severe, understanding how to provide quantitative and actionable scientific information for policy makers using biophysical data is critical for an appropriate and effective response.

Simulated NASA Satellite Data Products for the NOAA Integrated Coral Reef Observation Network/Coral Reef Early Warning System

NASA Technical Reports Server (NTRS)

Estep, Leland; Spruce, Joseph P.

2007-01-01

This RPC (Rapid Prototyping Capability) experiment will demonstrate the use of VIIRS (Visible/Infrared Imager/Radiometer Suite) and LDCM (Landsat Data Continuity Mission) sensor data as significant input to the NOAA (National Oceanic and Atmospheric Administration) ICON/ CREWS (Integrated Coral Reef Observation System/Coral Reef Early Warning System). The project affects the Coastal Management Program Element of the Applied Sciences Program.

Recommendations to harmonize European early warning dosimetry network systems

NASA Astrophysics Data System (ADS)

Dombrowski, H.; Bleher, M.; De Cort, M.; Dabrowski, R.; Neumaier, S.; Stöhlker, U.

2017-12-01

After the Chernobyl nuclear power plant accident in 1986, followed by the Fukushima Nuclear power plant accident 25 years later, it became obvious that real-time information is required to quickly gain radiological information. As a consequence, the European countries established early warning network systems with the aim to provide an immediate warning in case of a major radiological emergency, to supply reliable information on area dose rates, contamination levels, radioactivity concentrations in air and finally to assess public exposure. This is relevant for governmental decisions on intervention measures in an emergency situation. Since different methods are used by national environmental monitoring systems to measure area dose rate values and activity concentrations, there are significant differences in the results provided by different countries. Because European and neighboring countries report area dose rate data to a central data base operated on behalf of the European Commission, the comparability of the data is crucial for its meaningful interpretation, especially in the case of a nuclear accident with transboundary implications. Only by harmonizing measuring methods and data evaluation, is the comparability of the dose rate data ensured. This publication concentrates on technical requirements and methods with the goal to effectively harmonize area dose rate monitoring data provided by automatic early warning network systems. The requirements and procedures laid down in this publication are based on studies within the MetroERM project, taking into account realistic technical approaches and tested procedures.

ADVANCED SURVEILLANCE OF ENVIROMENTAL RADIATION IN AUTOMATIC NETWORKS.

PubMed

Benito, G; Sáez, J C; Blázquez, J B; Quiñones, J

2018-06-01

The objective of this study is the verification of the operation of a radiation monitoring network conformed by several sensors. The malfunction of a surveillance network has security and economic consequences, which derive from its maintenance and could be avoided with an early detection. The proposed method is based on a kind of multivariate distance, and the verification for the methodology has been tested at CIEMAT's local radiological early warning network.

A spatial Bayesian network model to assess the benefits of early warning for urban flood risk to people

NASA Astrophysics Data System (ADS)

Balbi, Stefano; Villa, Ferdinando; Mojtahed, Vahid; Hegetschweiler, Karin Tessa; Giupponi, Carlo

2016-06-01

This article presents a novel methodology to assess flood risk to people by integrating people's vulnerability and ability to cushion hazards through coping and adapting. The proposed approach extends traditional risk assessments beyond material damages; complements quantitative and semi-quantitative data with subjective and local knowledge, improving the use of commonly available information; and produces estimates of model uncertainty by providing probability distributions for all of its outputs. Flood risk to people is modeled using a spatially explicit Bayesian network model calibrated on expert opinion. Risk is assessed in terms of (1) likelihood of non-fatal physical injury, (2) likelihood of post-traumatic stress disorder and (3) likelihood of death. The study area covers the lower part of the Sihl valley (Switzerland) including the city of Zurich. The model is used to estimate the effect of improving an existing early warning system, taking into account the reliability, lead time and scope (i.e., coverage of people reached by the warning). Model results indicate that the potential benefits of an improved early warning in terms of avoided human impacts are particularly relevant in case of a major flood event.

Study of Water Pollution Early Warning Framework Based on Internet of Things

NASA Astrophysics Data System (ADS)

Chengfang, H.; Xiao, X.; Dingtao, S.; Bo, C.; Xiongfei, W.

2016-06-01

In recent years, with the increasing world environmental pollution happening, sudden water pollution incident has become more and more frequently in China. It has posed a serious threat to water safety of the people living in the water source area. Conventional water pollution monitoring method is manual periodic testing, it maybe miss the best time to find that pollution incident. This paper proposes a water pollution warning framework to change this state. On the basis of the Internet of things, we uses automatic water quality monitoring technology to realize monitoring. We calculate the monitoring data with water pollution model to judge whether the water pollution incident is happen or not. Water pollution warning framework is divided into three layers: terminal as the sensing layer, it with the deployment of the automatic water quality pollution monitoring sensor. The middle layer is the transfer network layer, data information implementation is based on GPRS wireless network transmission. The upper one is the application layer. With these application systems, early warning information of water pollution will realize the high-speed transmission between grassroots units and superior units. The paper finally gives an example that applying this pollution warning framework to water quality monitoring of Beijing, China, it greatly improves the speed of the pollution warning responding of Beijing.

Net Warrior D10 Technology Report: Airborne Early Warning and Control (AEW&C) and Data Link Nodes

DTIC Science & Technology

2012-04-01

ADO ) approach to implementing Network Centric Warfare (NCW) through ‘learning by doing’. Net Warrior was conceived to address, through... frameworks are able to satisfy design needs of applications to produce stable mission and net centric systems. NW-D10 employed a SOA approach to...UNCLASSIFIED Net Warrior D10 Technology Report: Airborne Early Warning and Control (AEW&C) and Data Link Nodes Derek Dominish

Big data managing in a landslide early warning system: experience from a ground-based interferometric radar application

NASA Astrophysics Data System (ADS)

Intrieri, Emanuele; Bardi, Federica; Fanti, Riccardo; Gigli, Giovanni; Fidolini, Francesco; Casagli, Nicola; Costanzo, Sandra; Raffo, Antonio; Di Massa, Giuseppe; Capparelli, Giovanna; Versace, Pasquale

2017-10-01

A big challenge in terms or landslide risk mitigation is represented by increasing the resiliency of society exposed to the risk. Among the possible strategies with which to reach this goal, there is the implementation of early warning systems. This paper describes a procedure to improve early warning activities in areas affected by high landslide risk, such as those classified as critical infrastructures for their central role in society. This research is part of the project LEWIS (Landslides Early Warning Integrated System): An Integrated System for Landslide Monitoring, Early Warning and Risk Mitigation along Lifelines. LEWIS is composed of a susceptibility assessment methodology providing information for single points and areal monitoring systems, a data transmission network and a data collecting and processing center (DCPC), where readings from all monitoring systems and mathematical models converge and which sets the basis for warning and intervention activities. The aim of this paper is to show how logistic issues linked to advanced monitoring techniques, such as big data transfer and storing, can be dealt with compatibly with an early warning system. Therefore, we focus on the interaction between an areal monitoring tool (a ground-based interferometric radar) and the DCPC. By converting complex data into ASCII strings and through appropriate data cropping and average, and by implementing an algorithm for line-of-sight correction, we managed to reduce the data daily output without compromising the capability for performing.

Tsunami Early Warning for the Indian Ocean Region - Status and Outlook

NASA Astrophysics Data System (ADS)

Lauterjung, Joern; Rudloff, Alexander; Muench, Ute; Gitews Project Team

2010-05-01

The German-Indonesian Tsunami Early Warning System (GITEWS) for the Indian Ocean region has gone into operation in Indonesia in November 2008. The system includes a seismological network, together with GPS stations and a network of GPS buoys additionally equipped with ocean bottom pressure sensors and a tide gauge network. The different sensor systems have, for the most part, been installed and now deliver respective data either online or interactively upon request to the Warning Centre in Jakarta. Before 2011, however, the different components requires further optimization and fine tuning, local personnel needs to be trained and eventual problems in the daily operation have to be dealt with. Furthermore a company will be founded in the near future, which will guarantee a sustainable maintenance and operation of the system. This concludes the transfer from a temporarily project into a permanent service. This system established in Indonesia differs from other Tsunami Warning Systems through its application of modern scientific methods and technologies. New procedures for the fast and reliable determination of strong earthquakes, deformation monitoring by GPS, the modeling of tsunamis and the assessment of the situation have been implemented in the Warning System architecture. In particular, the direct incorporation of different sensors provides broad information already at the early stages of Early Warning thus resulting in a stable system and minimizing breakdowns and false alarms. The warning system is designed in an open and modular structure based on the most recent developments and standards of information technology. Therefore, the system can easily integrate additional sensor components to be used for other multi-hazard purposes e.g. meteorological and hydrological events. Up to now the German project group is cooperating in the Indian Ocean region with Sri Lanka, the Maldives, Iran, Yemen, Tanzania and Kenya to set up the equipment primarily for seismological monitoring and data analysis. The automatic seismic data processing software SeisComP3, is not only operational in the warning centre in Jakarta and successfully used for rapid earthquake information, but also in different Indian Ocean rim countries like the once mentioned before as well as in India, Thailand and Pakistan. Close cooperation has been established with Australia, South Africa and India for the real-time exchange mainly of seismological and sea level data.

Development of structural health monitoring and early warning system for reinforced concrete system

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

Iranata, Data, E-mail: iranata-data@yahoo.com, E-mail: data@ce.its.ac.id; Wahyuni, Endah; Murtiadi, Suryawan

Many buildings have been damaged due to earthquakes that occurred recently in Indonesia. The main cause of the damage is the large deformation of the building structural component cannot accommodate properly. Therefore, it is necessary to develop the Structural Health Monitoring System (SHMS) to measure precisely the deformation of the building structural component in the real time conditions. This paper presents the development of SHMS for reinforced concrete structural system. This monitoring system is based on deformation component such as strain of reinforcement bar, concrete strain, and displacement of reinforced concrete component. Since the deformation component has exceeded the limitmore » value, the warning message can be sent to the building occupies. This warning message has also can be performed as early warning system of the reinforced concrete structural system. The warning message can also be sent via Short Message Service (SMS) through the Global System for Mobile Communications (GSM) network. Hence, the SHMS should be integrated with internet modem to connect with GSM network. Additionally, the SHMS program is verified with experimental study of simply supported reinforced concrete beam. Verification results show that the SHMS has good agreement with experimental results.« less

An Offshore Geophysical Network in the Pacific Northwest for Earthquake and Tsunami Early Warning and Hazard Research

NASA Astrophysics Data System (ADS)

Wilcock, W. S. D.; Schmidt, D. A.; Vidale, J. E.; Harrington, M.; Bodin, P.; Cram, G.; Delaney, J. R.; Gonzalez, F. I.; Kelley, D. S.; LeVeque, R. J.; Manalang, D.; McGuire, C.; Roland, E. C.; Tilley, J.; Vogl, C. J.; Stoermer, M.

2016-12-01

The Cascadia subduction zone hosts catastrophic earthquakes every few hundred years. On land, there are extensive geophysical networks available to monitor the subduction zone, but since the locked portion of the plate boundary lies mostly offshore, these networks are ideally complemented by seafloor observations. Such considerations helped motivate the development of scientific cabled observatories that cross the subduction zone at two sites off Vancouver Island and one off central Oregon, but these have a limited spatial footprint along the strike of the subduction zone. The Pacific Northwest Seismic Network is leading a collaborative effort to implement an earthquake early warning system in the Washington and Oregon using data streams from land networks as well as the few existing offshore instruments. For subduction zone earthquakes that initiate offshore, this system will provide a warning. However, the availability of real time offshore instrumentation along the entire subduction zone would improve its reliability and accuracy, add up to 15 s to the warning time, and ensure an early warning for coastal communities near the epicenter. Furthermore, real-time networks of seafloor pressure sensors above the subduction zone would enable monitoring and contribute to accurate predictions of the incoming tsunami. There is also strong scientific motivation for offshore monitoring. We lack a complete knowledge of the plate convergence rate and direction. Measurements of steady deformation and observations of transient processes such as fluid pulsing, microseismic cycles, tremor and slow-slip are necessary for assessing the dimensions of the locked zone and its along-strike segmentation. Long-term monitoring will also provide baseline observations that can be used to detect and evaluate changes in the subduction environment. There are significant engineering challenges to be solved to ensure the system is sufficiently reliable and maintainable. It must provide continuous monitoring over its operational life in the harsh ocean environment and at least parts of the system must continue to operate following a megathrust event. These requirements for robustness must be balanced with the desire for a flexible design that can accommodate new scientific instrumentation over the life of the project.

Development of a GNSS-Enhanced Tsunami Early Warning System

NASA Astrophysics Data System (ADS)

Bawden, G. W.; Melbourne, T. I.; Bock, Y.; Song, Y. T.; Komjathy, A.

2015-12-01

The past decade has witnessed a terrible loss of life and economic disruption caused by large earthquakes and resultant tsunamis impacting coastal communities and infrastructure across the Indo-Pacific region. NASA has funded the early development of a prototype real-time Global Navigation Satellite System (RT-GNSS) based rapid earthquake and tsunami early warning (GNSS-TEW) system that may be used to enhance seismic tsunami early warning systems for large earthquakes. This prototype GNSS-TEW system geodetically estimates fault parameters (earthquake magnitude, location, strike, dip, and slip magnitude/direction on a gridded fault plane both along strike and at depth) and tsunami source parameters (seafloor displacement, tsunami energy scale, and 3D tsunami initials) within minutes after the mainshock based on dynamic numerical inversions/regressions of the real-time measured displacements within a spatially distributed real-time GNSS network(s) spanning the epicentral region. It is also possible to measure fluctuations in the ionosphere's total electron content (TEC) in the RT-GNSS data caused by the pressure wave from the tsunami. This TEC approach can detect if a tsunami has been triggered by an earthquake, track its waves as they propagate through the oceanic basins, and provide upwards of 45 minutes early warning. These combined real-time geodetic approaches will very quickly address a number of important questions in the immediate minutes following a major earthquake: How big was the earthquake and what are its fault parameters? Could the earthquake have produced a tsunami and was a tsunami generated?

Assessment of early warning system performance and improvements since it is in operational phase in Romania

NASA Astrophysics Data System (ADS)

Ionescu, Constantin; Marmureanu, Alexandru; Marmureanu, Gheorghe; Ortansa Cioflan, Carmen

2017-04-01

Earthquake represents a major natural disaster for Romanian territory. The main goal following the occurrence of a strong earthquake is to minimize the total number of fatalities. A rapid early warning system (REWS) was developed in Romania in order to provide 25-35 seconds warning time to Bucharest facilities for the earthquakes with M>5.0. The system consists of four components: a network of strong motion sensors installed in the epicentral area, a redundant communication network, an automatic analyzing system located in the Romanian Data Centre and an alert distribution system. The detection algorithm is based on the magnitude computation using strong motion data and rapid evaluation and scaling relation between the maximum P-wave acceleration measured in the epicentral area and the higher ground motion amplitude recorded in Bucharest. In order to reduce the damages caused by earthquakes, the exploitation of the up to date technology is very important. The information is the key point in the disaster management, and the internet is one of the most used instrument, implying also low costs. The Rapid Early Warning System was expanded to cover all countries affected by major earthquakes originating in the Vrancea seismic area and reduce their impact on existing installations of national interest in neighbouring Romania and elsewhere. REWS provides an efficient instrument for prevention and reaction based on the integrated system for seismic detection in South-Eastern Europe. REWS has been operational since 2013 and sends alert the authorities, hazardous facilities in Romania and Bulgaria (NPP, emergency response agencies etc.) and to public via twitter and some smartphone applications developed in the house. Also, NIEP is part of the UNESCO initiative case on developing a platform on earthquake early warning systems (IP-MEP) that aims to promote and strengthen the development of earthquake early warning systems in earthquake-prone regions of the world by sharing scientific knowledge, capacity building and international cooperation.

A spatial Bayesian network model to assess the benefits of early warning for urban flood risk to people

NASA Astrophysics Data System (ADS)

Balbi, S.; Villa, F.; Mojtahed, V.; Hegetschweiler, K. T.; Giupponi, C.

2015-10-01

This article presents a novel methodology to assess flood risk to people by integrating people's vulnerability and ability to cushion hazards through coping and adapting. The proposed approach extends traditional risk assessments beyond material damages; complements quantitative and semi-quantitative data with subjective and local knowledge, improving the use of commonly available information; produces estimates of model uncertainty by providing probability distributions for all of its outputs. Flood risk to people is modeled using a spatially explicit Bayesian network model calibrated on expert opinion. Risk is assessed in terms of: (1) likelihood of non-fatal physical injury; (2) likelihood of post-traumatic stress disorder; (3) likelihood of death. The study area covers the lower part of the Sihl valley (Switzerland) including the city of Zurich. The model is used to estimate the benefits of improving an existing Early Warning System, taking into account the reliability, lead-time and scope (i.e. coverage of people reached by the warning). Model results indicate that the potential benefits of an improved early warning in terms of avoided human impacts are particularly relevant in case of a major flood event: about 75 % of fatalities, 25 % of injuries and 18 % of post-traumatic stress disorders could be avoided.

Usage of Wireless Sensor Networks in a service based spatial data infrastructure for Landslide Monitoring and Early Warning

NASA Astrophysics Data System (ADS)

Arnhardt, C.; Fernandez-Steeger, T. M.; Walter, K.; Kallash, A.; Niemeyer, F.; Azzam, R.; Bill, R.

2007-12-01

The joint project Sensor based Landslide Early Warning System (SLEWS) aims at a systematic development of a prototyping alarm- and early warning system for the detection of mass movements by application of an ad hoc wireless sensor network (WSN). Next to the development of suitable sensor setups, sensor fusion and network fusion are applied to enhance data quality and reduce false alarm rates. Of special interest is the data retrieval, processing and visualization in GI-Systems. Therefore a suitable serviced based Spatial Data Infrastructure (SDI) will be developed with respect to existing and upcoming Open Geospatial Consortium (OGC) standards.The application of WSN provides a cheap and easy to set up solution for special monitoring and data gathering in large areas. Measurement data from different low-cost transducers for deformation observation (acceleration, displacement, tilting) is collected by distributed sensor nodes (motes), which interact separately and connect each other in a self-organizing manner. Data are collected and aggregated at the beacon (transmission station) and further operations like data pre-processing and compression can be performed. The WSN concept provides next to energy efficiency, miniaturization, real-time monitoring and remote operation, but also new monitoring strategies like sensor and network fusion. Since not only single sensors can be integrated at single motes either cross-validation or redundant sensor setups are possible to enhance data quality. The planned monitoring and information system will include a mobile infrastructure (information technologies and communication components) as well as methods and models to estimate surface deformation parameters (positioning systems). The measurements result in heterogeneous observation sets that have to be integrated in a common adjustment and filtering approach. Reliable real-time information will be obtained using a range of sensor input and algorithms, from which early warnings and prognosis may be derived. Implementation of sensor algorithms is an important task to form the business logic. This will be represented in self-contained web-based processing services (WPS). In the future different types of sensor networks can communicate via an infrastructure of OGC services using an interoperable way by standardized protocols as the Sensor Markup Language (SensorML) and Observations & Measurements Schema (O&M). Synchronous and asynchronous information services as the Sensor Alert Service (SAS) and the Web Notification Services (WNS) will provide defined users and user groups with time-critical readings from the observation site. Techniques using services for visualizing mapping data (WMS), meta data (CSW), vector (WFS) and raster data (WCS) will range from high detailed expert based output to fuzzy graphical warning elements.The expected results will be an advancement regarding classical alarm and early warning systems as the WSN are free scalable, extensible and easy to install.

Multifractality and Network Analysis of Phase Transition

PubMed Central

Li, Wei; Yang, Chunbin; Han, Jihui; Su, Zhu; Zou, Yijiang

2017-01-01

Many models and real complex systems possess critical thresholds at which the systems shift dramatically from one sate to another. The discovery of early-warnings in the vicinity of critical points are of great importance to estimate how far the systems are away from the critical states. Multifractal Detrended Fluctuation analysis (MF-DFA) and visibility graph method have been employed to investigate the multifractal and geometrical properties of the magnetization time series of the two-dimensional Ising model. Multifractality of the time series near the critical point has been uncovered from the generalized Hurst exponents and singularity spectrum. Both long-term correlation and broad probability density function are identified to be the sources of multifractality. Heterogeneous nature of the networks constructed from magnetization time series have validated the fractal properties. Evolution of the topological quantities of the visibility graph, along with the variation of multifractality, serve as new early-warnings of phase transition. Those methods and results may provide new insights about the analysis of phase transition problems and can be used as early-warnings for a variety of complex systems. PMID:28107414

An early warning system for groundwater pollution based on the assessment of groundwater pollution risks.

NASA Astrophysics Data System (ADS)

Zhang, Weihong.; Zhao, Yongsheng; Hong, Mei; Guo, Xiaodong

2009-04-01

Groundwater pollution usually is complex and concealed, remediation of which is difficult, high cost, time-consuming, and ineffective. An early warning system for groundwater pollution is needed that detects groundwater quality problems and gets the information necessary to make sound decisions before massive groundwater quality degradation occurs. Groundwater pollution early warning were performed by considering comprehensively the current groundwater quality, groundwater quality varying trend and groundwater pollution risk . The map of the basic quality of the groundwater was obtained by fuzzy comprehensive evaluation or BP neural network evaluation. Based on multi-annual groundwater monitoring datasets, Water quality state in sometime of the future was forecasted using time-sequenced analyzing methods. Water quality varying trend was analyzed by Spearman's rank correlative coefficient.The relative risk map of groundwater pollution was estimated through a procedure that identifies, cell by cell,the values of three factors, that is inherent vulnerability, load risk of pollution source and contamination hazard. DRASTIC method was used to assess inherent vulnerability of aquifer. Load risk of pollution source was analyzed based on the potential of contamination and pollution degree. Assessment index of load risk of pollution source which involves the variety of pollution source, quantity of contaminants, releasing potential of pollutants, and distance were determined. The load risks of all sources considered by GIS overlay technology. Early warning model of groundwater pollution combined with ComGIS technology organically, the regional groundwater pollution early-warning information system was developed, and applied it into Qiqiha'er groundwater early warning. It can be used to evaluate current water quality, to forecast water quality changing trend, and to analyze space-time influencing range of groundwater quality by natural process and human activities. Keywords: groundwater pollution, early warning, aquifer vulnerability, pollution load, pollution risk, ComGIS

Electric Field Sensor for Lightning Early Warning System

NASA Astrophysics Data System (ADS)

Premlet, B.; Mohammed, R.; Sabu, S.; Joby, N. E.

2017-12-01

Electric field mills are used popularly for atmospheric electric field measurements. Atmospheric Electric Field variation is the primary signature for Lightning Early Warning systems. There is a characteristic change in the atmospheric electric field before lightning during a thundercloud formation.A voltage controlled variable capacitance is being proposed as a method for non-contacting measurement of electric fields. A varactor based mini electric field measurement system is developed, to detect any change in the atmospheric electric field and to issue lightning early warning system. Since this is a low-cost device, this can be used for developing countries which are facing adversities. A network of these devices can help in forming a spatial map of electric field variations over a region, and this can be used for more improved atmospheric electricity studies in developing countries.

Concept, Implementation and Testing of PRESTo: Real-time experimentation in Southern Italy and worldwide applications

NASA Astrophysics Data System (ADS)

Zollo, Aldo; Emolo, Antonio; Festa, Gaetano; Picozzi, Matteo; Elia, Luca; Martino, Claudio; Colombelli, Simona; Brondi, Piero; Caruso, Alessandro

2016-04-01

The past two decades have witnessed a huge progress in the development, implementation and testing of Earthquakes Early Warning Systems (EEWS) worldwide, as the result of a joint effort of the seismological and earthquake engineering communities to set up robust and efficient methodologies for the real-time seismic risk mitigation. This work presents an overview of the worldwide applications of the system PRESTo (PRobabilistic and Evolutionary early warning SysTem), which is the highly configurable and easily portable platform for Earthquake Early Warning developed by the RISSCLab group of the University of Naples Federico II. In particular, we first present the results of the real-time experimentation of PRESTo in Suthern Italy on the data streams of the Irpinia Seismic Network (ISNet), in Southern Italy. ISNet is a dense high-dynamic range, earthquake observing system, which operates in true real-time mode, thanks to a mixed data transmission system based on proprietary digital terrestrial links, standard ADSL and UMTS technologies. Using the seedlink protocol data are transferred to the network center unit, running the software platform PRESTo which is devoted to process the real-time data streaming, estimate source parameters and issue the alert. The software platform PRESTo uses a P-wave, network-based approach which has evolved and improved during the time since its first release. In its original version consisted in a series of modules, aimed at the event detection/picking, probabilistic real-time earthquake location and magnitude estimation, prediction of peak ground motion at distant sites through ground motion prediction equations for the area. In the recent years, PRESTo has been also implemented at the accelerometric and broad-band seismic networks in South Korea, Romania, North-East Italy, and Turkey and off-line tested in Iberian Peninsula, Israel, and Japan. Moreover, the feasibility of a PRESTo-based, EEWS at national scale in Italy, has been tested by evaluating its performance for the Italian Accelerometric Network. These testing experiments and the EEWS performance results will be summarized in the near-future perspective of building the next generation of early warning systems.

Early-warning signals of topological collapse in interbank networks

NASA Astrophysics Data System (ADS)

Squartini, Tiziano; van Lelyveld, Iman; Garlaschelli, Diego

2013-11-01

The financial crisis clearly illustrated the importance of characterizing the level of `systemic' risk associated with an entire credit network, rather than with single institutions. However, the interplay between financial distress and topological changes is still poorly understood. Here we analyze the quarterly interbank exposures among Dutch banks over the period 1998-2008, ending with the crisis. After controlling for the link density, many topological properties display an abrupt change in 2008, providing a clear - but unpredictable - signature of the crisis. By contrast, if the heterogeneity of banks' connectivity is controlled for, the same properties show a gradual transition to the crisis, starting in 2005 and preceded by an even earlier period during which anomalous debt loops could have led to the underestimation of counter-party risk. These early-warning signals are undetectable if the network is reconstructed from partial bank-specific data, as routinely done. We discuss important implications for bank regulatory policies.

Real-Time Surveillance in Emergencies Using the Early Warning Alert and Response Network.

PubMed

Cordes, Kristina M; Cookson, Susan T; Boyd, Andrew T; Hardy, Colleen; Malik, Mamunur Rahman; Mala, Peter; El Tahir, Khalid; Everard, Marthe; Jasiem, Mohamad; Husain, Farah

2017-11-01

Humanitarian emergencies often result in population displacement and increase the risk for transmission of communicable diseases. To address the increased risk for outbreaks during humanitarian emergencies, the World Health Organization developed the Early Warning Alert and Response Network (EWARN) for early detection of epidemic-prone diseases. The US Centers for Disease Control and Prevention has worked with the World Health Organization, ministries of health, and other partners to support EWARN through the implementation and evaluation of these systems and the development of standardized guidance. Although protocols have been developed for the implementation and evaluation of EWARN, a need persists for standardized training and additional guidance on supporting these systems remotely when access to affected areas is restricted. Continued collaboration between partners and the Centers for Disease Control and Prevention for surveillance during emergencies is necessary to strengthen capacity and support global health security.

Real-Time Surveillance in Emergencies Using the Early Warning Alert and Response Network

PubMed Central

Cordes, Kristina M.; Cookson, Susan T.; Boyd, Andrew T.; Hardy, Colleen; Malik, Mamunur Rahman; Mala, Peter; El Tahir, Khalid; Everard, Marthe; Jasiem, Mohamad

2017-01-01

Humanitarian emergencies often result in population displacement and increase the risk for transmission of communicable diseases. To address the increased risk for outbreaks during humanitarian emergencies, the World Health Organization developed the Early Warning Alert and Response Network (EWARN) for early detection of epidemic-prone diseases. The US Centers for Disease Control and Prevention has worked with the World Health Organization, ministries of health, and other partners to support EWARN through the implementation and evaluation of these systems and the development of standardized guidance. Although protocols have been developed for the implementation and evaluation of EWARN, a need persists for standardized training and additional guidance on supporting these systems remotely when access to affected areas is restricted. Continued collaboration between partners and the Centers for Disease Control and Prevention for surveillance during emergencies is necessary to strengthen capacity and support global health security. PMID:29155660

The EarthScope Plate Boundary Observatory and allied networks, the makings of nascent Earthquake and Tsunami Early Warning System in Western North America.

NASA Astrophysics Data System (ADS)

Mattioli, Glen; Mencin, David; Hodgkinson, Kathleen; Meertens, Charles; Phillips, David; Blume, Fredrick; Berglund, Henry; Fox, Otina; Feaux, Karl

2016-04-01

The NSF-funded GAGE Facility, managed by UNAVCO, operates approximately ~1300 GNSS stations distributed across North and Central America and in the circum-Caribbean. Following community input starting in 2011 from several workshops and associated reports,UNAVCO has been exploring ways to increase the capability and utility of the geodetic resources under its management to improve our understanding in diverse areas of geophysics including properties of seismic, volcanic, magmatic and tsunami deformation sources. Networks operated by UNAVCO for the NSF have the potential to profoundly transform our ability to rapidly characterize events, provide rapid characterization and warning, as well as improve hazard mitigation and response. Specific applications currently under development include earthquake early warning, tsunami early warning, and tropospheric modeling with university, commercial, non-profit and government partners on national and international scales. In the case of tsunami early warning, for example, an RT-GNSS network can provide multiple inputs in an operational system starting with rapid assessment of earthquake sources and associated deformation, which leads to the initial model of ocean forcing and tsunami generation. In addition, terrestrial GNSScan provide direct measurements of the tsunami through the associated traveling ionospheric disturbance from several 100's of km away as they approach the shoreline,which can be used to refine tsunami inundation models. Any operational system like this has multiple communities that rely on a pan-Pacific real-time open data set. Other scientific and operational applications for high-rate GPS include glacier and ice sheet motions, tropospheric modeling, and better constraints on the dynamics of space weather. Combining existing data sets and user communities, for example seismic data and tide gauge observations, with GNSS and Met data products has proven complicated because of issues related to metadata, appropriate data formats, data quality assessment in real-time and other issues related to using these products operational forecasting. While progress has been made toward more open and free data access across national borders and toward more cooperation among cognizant government sanctioned "early warning" agencies, some impediments remain making a truly operational system a work in progress. Accordingly, UNAVCO has embarked on significant improvements and improvement goals to the original infrastructure and scope of the PBO. We anticipate that PBO and related networks will form a backbone for these disparate efforts providing high quality, low latency raw and processed GNSS data. This requires substantial upgrades to the entire system from the basic GNNS receiver, through robust data collection, archiving and open distribution mechanisms, to efficient data-processing strategies. UNAVCO is currently in a partnership with the commercial and scientific stakeholders to define, develop and deploy all segments of this improved geodetic network. We present the overarching goals, and current and planned future stateof this international resource.

Technical implementation plan for the ShakeAlert production system: an Earthquake Early Warning system for the West Coast of the United States

USGS Publications Warehouse

Given, Douglas D.; Cochran, Elizabeth S.; Heaton, Thomas; Hauksson, Egill; Allen, Richard; Hellweg, Peggy; Vidale, John; Bodin, Paul

2014-01-01

Earthquake Early Warning (EEW) systems can provide as much as tens of seconds of warning to people and automated systems before strong shaking arrives. The United States Geological Survey (USGS) and its partners are developing such an EEW system, called ShakeAlert, for the West Coast of the United States. This document describes the technical implementation of that system, which leverages existing stations and infrastructure of the Advanced National Seismic System (ANSS) regional networks to achieve this new capability. While significant progress has been made in developing the ShakeAlert early warning system, improved robustness of each component of the system and additional testing and certification are needed for the system to be reliable enough to issue public alerts. Major components of the system include dense networks of ground motion sensors, telecommunications from those sensors to central processing systems, algorithms for event detection and alert creation, and distribution systems to alert users. Capital investment costs for a West Coast EEW system are projected to be $38.3M, with additional annual maintenance and operations totaling $16.1M—in addition to current ANSS expenditures for earthquake monitoring. An EEW system is complementary to, but does not replace, other strategies to mitigate earthquake losses. The system has limitations: false and missed alerts are possible, and the area very near to an earthquake epicenter may receive little or no warning. However, such an EEW system would save lives, reduce injuries and damage, and improve community resilience by reducing longer-term economic losses for both public and private entities.

Istanbul Earthquake Early Warning and Rapid Response System

NASA Astrophysics Data System (ADS)

Erdik, M. O.; Fahjan, Y.; Ozel, O.; Alcik, H.; Aydin, M.; Gul, M.

2003-12-01

As part of the preparations for the future earthquake in Istanbul a Rapid Response and Early Warning system in the metropolitan area is in operation. For the Early Warning system ten strong motion stations were installed as close as possible to the fault zone. Continuous on-line data from these stations via digital radio modem provide early warning for potentially disastrous earthquakes. Considering the complexity of fault rupture and the short fault distances involved, a simple and robust Early Warning algorithm, based on the exceedance of specified threshold time domain amplitude levels is implemented. The band-pass filtered accelerations and the cumulative absolute velocity (CAV) are compared with specified threshold levels. When any acceleration or CAV (on any channel) in a given station exceeds specific threshold values it is considered a vote. Whenever we have 2 station votes within selectable time interval, after the first vote, the first alarm is declared. In order to specify the appropriate threshold levels a data set of near field strong ground motions records form Turkey and the world has been analyzed. Correlations among these thresholds in terms of the epicenter distance the magnitude of the earthquake have been studied. The encrypted early warning signals will be communicated to the respective end users by UHF systems through a "service provider" company. The users of the early warning signal will be power and gas companies, nuclear research facilities, critical chemical factories, subway system and several high-rise buildings. Depending on the location of the earthquake (initiation of fault rupture) and the recipient facility the alarm time can be as high as about 8s. For the rapid response system one hundred 18 bit-resolution strong motion accelerometers were placed in quasi-free field locations (basement of small buildings) in the populated areas of the city, within an area of approximately 50x30km, to constitute a network that will enable early damage assessment and rapid response information after a damaging earthquake. Early response information is achieved through fast acquisition and analysis of processed data obtained from the network. The stations are routinely interrogated on regular basis by the main data center. After triggered by an earthquake, each station processes the streaming strong motion data to yield the spectral accelerations at specific periods, 12Hz filtered PGA and PGV and will send these parameters in the form of SMS messages at every 20s directly to the main data center through a designated GSM network and through a microwave system. A shake map and damage distribution map (using aggregate building inventories and fragility curves) will be automatically generated using the algorithm developed for this purpose. Loss assessment studies are complemented by a large citywide digital database on the topography, geology, soil conditions, building, infrastructure and lifeline inventory. The shake and damage maps will be conveyed to the governor's and mayor's offices, fire, police and army headquarters within 3 minutes using radio modem and GPRS communication. An additional forty strong motion recorders were placed on important structures in several interconnected clusters to monitor the health of these structures after a damaging earthquake.

An online operational rainfall-monitoring resource for epidemic malaria early warning systems in Africa

USGS Publications Warehouse

Grover-Kopec, Emily; Kawano, Mika; Klaver, Robert W.; Blumenthal, Benno; Ceccato, Pietro; Connor, Stephen J.

2005-01-01

Periodic epidemics of malaria are a major public health problem for many sub-Saharan African countries. Populations in epidemic prone areas have a poorly developed immunity to malaria and the disease remains life threatening to all age groups. The impact of epidemics could be minimized by prediction and improved prevention through timely vector control and deployment of appropriate drugs. Malaria Early Warning Systems are advocated as a means of improving the opportunity for preparedness and timely response.Rainfall is one of the major factors triggering epidemics in warm semi-arid and desert-fringe areas. Explosive epidemics often occur in these regions after excessive rains and, where these follow periods of drought and poor food security, can be especially severe. Consequently, rainfall monitoring forms one of the essential elements for the development of integrated Malaria Early Warning Systems for sub-Saharan Africa, as outlined by the World Health Organization.The Roll Back Malaria Technical Resource Network on Prevention and Control of Epidemics recommended that a simple indicator of changes in epidemic risk in regions of marginal transmission, consisting primarily of rainfall anomaly maps, could provide immediate benefit to early warning efforts. In response to these recommendations, the Famine Early Warning Systems Network produced maps that combine information about dekadal rainfall anomalies, and epidemic malaria risk, available via their Africa Data Dissemination Service. These maps were later made available in a format that is directly compatible with HealthMapper, the mapping and surveillance software developed by the WHO's Communicable Disease Surveillance and Response Department. A new monitoring interface has recently been developed at the International Research Institute for Climate Prediction (IRI) that enables the user to gain a more contextual perspective of the current rainfall estimates by comparing them to previous seasons and climatological averages. These resources are available at no cost to the user and are updated on a routine basis.

MUSIC algorithm DoA estimation for cooperative node location in mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Warty, Chirag; Yu, Richard Wai; ElMahgoub, Khaled; Spinsante, Susanna

In recent years the technological development has encouraged several applications based on distributed communications network without any fixed infrastructure. The problem of providing a collaborative early warning system for multiple mobile nodes against a fast moving object. The solution is provided subject to system level constraints: motion of nodes, antenna sensitivity and Doppler effect at 2.4 GHz and 5.8 GHz. This approach consists of three stages. The first phase consists of detecting the incoming object using a highly directive two element antenna at 5.0 GHz band. The second phase consists of broadcasting the warning message using a low directivity broad antenna beam using 2× 2 antenna array which then in third phase will be detected by receiving nodes by using direction of arrival (DOA) estimation technique. The DOA estimation technique is used to estimate the range and bearing of the incoming nodes. The position of fast arriving object can be estimated using the MUSIC algorithm for warning beam DOA estimation. This paper is mainly intended to demonstrate the feasibility of early detection and warning system using a collaborative node to node communication links. The simulation is performed to show the behavior of detecting and broadcasting antennas as well as performance of the detection algorithm. The idea can be further expanded to implement commercial grade detection and warning system

Development of Smart Grid for Community and Cyber based Landslide Hazard Monitoring and Early Warning System

NASA Astrophysics Data System (ADS)

Karnawati, D.; Wilopo, W.; Fathani, T. F.; Fukuoka, H.; Andayani, B.

2012-12-01

A Smart Grid is a cyber-based tool to facilitate a network of sensors for monitoring and communicating the landslide hazard and providing the early warning. The sensor is designed as an electronic sensor installed in the existing monitoring and early warning instruments, and also as the human sensors which comprise selected committed-people at the local community, such as the local surveyor, local observer, member of the local task force for disaster risk reduction, and any person at the local community who has been registered to dedicate their commitments for sending reports related to the landslide symptoms observed at their living environment. This tool is designed to be capable to receive up to thousands of reports/information at the same time through the electronic sensors, text message (mobile phone), the on-line participatory web as well as various social media such as Twitter and Face book. The information that should be recorded/ reported by the sensors is related to the parameters of landslide symptoms, for example the progress of cracks occurrence, ground subsidence or ground deformation. Within 10 minutes, this tool will be able to automatically elaborate and analyse the reported symptoms to predict the landslide hazard and risk levels. The predicted level of hazard/ risk can be sent back to the network of electronic and human sensors as the early warning information. The key parameters indicating the symptoms of landslide hazard were recorded/ monitored by the electrical and the human sensors. Those parameters were identified based on the investigation on geological and geotechnical conditions, supported with the laboratory analysis. The cause and triggering mechanism of landslide in the study area was also analysed in order to define the critical condition to launch the early warning. However, not only the technical but also social system were developed to raise community awareness and commitments to serve the mission as the human sensors, which will be responsible for reporting and informing the early warning. Therefore, a community empowerment and encouragement program through public education was conducted. Strategy and approach for this program was formulated based on the socio-engineering investigation. Finally, the results of technical and social engineering investigations, have been elaborated to further enhance the performance of expert system of the Smart Grid, in order to completely establish this system as an innovative and effective tool for the landslide monitoring and early warning in tropical-developing country.

REWSET: A prototype seismic and tsunami early warning system in Rhodes island, Greece

NASA Astrophysics Data System (ADS)

Papadopoulos, Gerasimos; Argyris, Ilias; Aggelou, Savvas; Karastathis, Vasilis

2014-05-01

Tsunami warning in near-field conditions is a critical issue in the Mediterranean Sea since the most important tsunami sources are situated within tsunami wave travel times starting from about five minutes. The project NEARTOWARN (2012-2013) supported by the EU-DG ECHO contributed substantially to the development of new tools for the near-field tsunami early warning in the Mediterranean. One of the main achievements is the development of a local warning system in the test-site of Rhodes island (Rhodes Early Warning System for Earthquakes and Tsunamis - REWSET). The system is composed by three main subsystems: (1) a network of eight seismic early warning devices installed in four different localities of the island, one in the civil protection, another in the Fire Brigade and another two in municipality buildings; (2) two radar-type (ultrasonic) tide-gauges installed in the eastern coastal zine of the island which was selected since research on the historical earthquake and tsunami activity has indicated that the most important, near-field tsunami sources are situated offshore to the east of Rhodes; (3) a crisis Geographic Management System (GMS), which is a web-based and GIS-based application incorporating a variety of thematic maps and other information types. The seismic early warning devices activate by strong (magnitude around 6 or more) earthquakes occurring at distances up to about 100 km from Rhodes, thus providing immediate mobilization of the civil protection. The tide-gauges transmit sea level data, while during the crisis the GMS supports decisions to be made by civil protection. In the near future it is planned the REWSET system to be integrated with national and international systems. REWSET is a prototype which certainly could be developed in other coastal areas of the Mediterranean and beyond.

Seismic Monitoring of Permafrost During Controlled Thaw: An Active-Source Experiment Using a Surface Orbital Vibrator and Fiber-Optic DAS Arrays

NASA Astrophysics Data System (ADS)

Dou, S.; Wood, T.; Lindsey, N.; Ajo Franklin, J. B.; Freifeld, B. M.; Gelvin, A.; Morales, A.; Saari, S.; Ekblaw, I.; Wagner, A. M.; Daley, T. M.; Robertson, M.; Martin, E. R.; Ulrich, C.; Bjella, K.

2016-12-01

Thawing of permafrost can cause ground deformations that threaten the integrity of civil infrastructure. It is essential to develop early warning systems that can identify critically warmed permafrost and issue warnings for hazard prevention and control. Seismic methods can play a pivotal role in such systems for at least two reasons: First, seismic velocities are indicative of mechanical strength of the subsurface and thus are directly relevant to engineering properties; Second, seismic velocities in permafrost systems are sensitive to pre-thaw warming, which makes it possible to issue early warnings before the occurrence of hazardous subsidence events. However, several questions remain: What are the seismic signatures that can be effectively used for early warning of permafrost thaw? Can seismic methods provide enough warning times for hazard prevention and control? In this study, we investigate the feasibility of using permanently installed seismic networks for early warnings of permafrost thaw. We conducted continuous active-source seismic monitoring of permafrost that was under controlled heating at CRREL's Fairbanks permafrost experiment station. We used a permanently installed surface orbital vibrator (SOV) as source and surface-trenched DAS arrays as receivers. The SOV is characterized by its excellent repeatability, automated operation, high energy level, and the rich frequency content (10-100 Hz) of the generated wavefields. The fiber-optic DAS arrays allow continuous recording of seismic data with dense spatial sampling (1-meter channel spacing), low cost, and low maintenance. This combination of SOV-DAS provides unique seismic datasets for observing time-lapse changes of warming permafrost at the field scale, hence providing an observational basis for design and development of early warning systems for permafrost thaw.

Never Use the Complete Search Space: a Concept to Enhance the Optimization Procedure for Monitoring Networks

NASA Astrophysics Data System (ADS)

Bode, F.; Reuschen, S.; Nowak, W.

2015-12-01

Drinking-water well catchments include many potential sources of contaminations like gas stations or agriculture. Finding optimal positions of early-warning monitoring wells is challenging because there are various parameters (and their uncertainties) that influence the reliability and optimality of any suggested monitoring location or monitoring network.The overall goal of this project is to develop and establish a concept to assess, design and optimize early-warning systems within well catchments. Such optimal monitoring networks need to optimize three competing objectives: a high detection probability, which can be reached by maximizing the "field of vision" of the monitoring network, a long early-warning time such that there is enough time left to install counter measures after first detection, and the overall operating costs of the monitoring network, which should ideally be reduced to a minimum. The method is based on numerical simulation of flow and transport in heterogeneous porous media coupled with geostatistics and Monte-Carlo, scenario analyses for real data, respectively, wrapped up within the framework of formal multi-objective optimization using a genetic algorithm.In order to speed up the optimization process and to better explore the Pareto-front, we developed a concept that forces the algorithm to search only in regions of the search space where promising solutions can be expected. We are going to show how to define these regions beforehand, using knowledge of the optimization problem, but also how to define them independently of problem attributes. With that, our method can be used with and/or without detailed knowledge of the objective functions.In summary, our study helps to improve optimization results in less optimization time by meaningful restrictions of the search space. These restrictions can be done independently of the optimization problem, but also in a problem-specific manner.

Earthquake Early Warning: User Education and Designing Effective Messages

NASA Astrophysics Data System (ADS)

Burkett, E. R.; Sellnow, D. D.; Jones, L.; Sellnow, T. L.

2014-12-01

The U.S. Geological Survey (USGS) and partners are transitioning from test-user trials of a demonstration earthquake early warning system (ShakeAlert) to deciding and preparing how to implement the release of earthquake early warning information, alert messages, and products to the public and other stakeholders. An earthquake early warning system uses seismic station networks to rapidly gather information about an occurring earthquake and send notifications to user devices ahead of the arrival of potentially damaging ground shaking at their locations. Earthquake early warning alerts can thereby allow time for actions to protect lives and property before arrival of damaging shaking, if users are properly educated on how to use and react to such notifications. A collaboration team of risk communications researchers and earth scientists is researching the effectiveness of a chosen subset of potential earthquake early warning interface designs and messages, which could be displayed on a device such as a smartphone. Preliminary results indicate, for instance, that users prefer alerts that include 1) a map to relate their location to the earthquake and 2) instructions for what to do in response to the expected level of shaking. A number of important factors must be considered to design a message that will promote appropriate self-protective behavior. While users prefer to see a map, how much information can be processed in limited time? Are graphical representations of wavefronts helpful or confusing? The most important factor to promote a helpful response is the predicted earthquake intensity, or how strong the expected shaking will be at the user's location. Unlike Japanese users of early warning, few Californians are familiar with the earthquake intensity scale, so we are exploring how differentiating instructions between intensity levels (e.g., "Be aware" for lower shaking levels and "Drop, cover, hold on" at high levels) can be paired with self-directed supplemental information to increase the public's understanding of earthquake shaking and protective behaviors.

Earthquake early warning for Romania - most recent improvements

NASA Astrophysics Data System (ADS)

Marmureanu, Alexandru; Elia, Luca; Martino, Claudio; Colombelli, Simona; Zollo, Aldo; Cioflan, Carmen; Toader, Victorin; Marmureanu, Gheorghe; Marius Craiu, George; Ionescu, Constantin

2014-05-01

EWS for Vrancea earthquakes uses the time interval (28-32 sec.) between the moment when the earthquake is detected by the local seismic network installed in the epicenter area (Vrancea) and the arrival time of the seismic waves in the protected area (Bucharest) to send earthquake warning to users. In the last years, National Institute for Earth Physics (NIEP) upgraded its seismic network in order to cover better the seismic zones of Romania. Currently the National Institute for Earth Physics (NIEP) operates a real-time seismic network designed to monitor the seismic activity on the Romania territory, dominated by the Vrancea intermediate-depth (60-200 km) earthquakes. The NIEP real-time network consists of 102 stations and two seismic arrays equipped with different high quality digitizers (Kinemetrics K2, Quanterra Q330, Quanterra Q330HR, PS6-26, Basalt), broadband and short period seismometers (CMG3ESP, CMG40T, KS2000, KS54000, KS2000, CMG3T,STS2, SH-1, S13, Ranger, gs21, Mark l22) and acceleration sensors (Episensor). Recent improvement of the seismic network and real-time communication technologies allows implementation of a nation-wide EEWS for Vrancea and other seismic sources from Romania. We present a regional approach to Earthquake Early Warning for Romania earthquakes. The regional approach is based on PRESTo (Probabilistic and Evolutionary early warning SysTem) software platform: PRESTo processes in real-time three channel acceleration data streams: once the P-waves arrival have been detected, it provides earthquake location and magnitude estimations, and peak ground motion predictions at target sites. PRESTo is currently implemented in real- time at National Institute for Earth Physics, Bucharest for several months in parallel with a secondary EEWS. The alert notification is issued only when both systems validate each other. Here we present the results obtained using offline earthquakes originating from Vrancea area together with several real-time detection of significant earthquakes from Vrancea and Transylvania areas that occurred in the last months. Currently the warning notification is sent to several users including emergency response units from 12 counties, a big bridge located in Bucharest, a nuclear sterilization facility in Măgurele city and to the nuclear power plant from Cernavoda.

Suitability of Open-Ocean Instrumentation for Use in Near-Field Tsunami Early Warning Along Seismically Active Subduction Zones

NASA Astrophysics Data System (ADS)

Williamson, Amy L.; Newman, Andrew V.

2018-05-01

Over the past decade, the number of open-ocean gauges capable of parsing information about a passing tsunami has steadily increased, particularly through national cable networks and international buoyed efforts such as the Deep-ocean Assessment and Reporting of Tsunami (DART). This information is analyzed to disseminate tsunami warnings to affected regions. However, most current warnings that incorporate tsunami are directed at mid- and far-field localities. In this study, we analyze the region surrounding four seismically active subduction zones, Cascadia, Japan, Chile, and Java, for their potential to facilitate local tsunami early warning using such systems. We assess which locations currently have instrumentation in the right locations for direct tsunami observations with enough time to provide useful warning to the nearest affected coastline—and which are poorly suited for such systems. Our primary findings are that while some regions are ill-suited for this type of early warning, such as the coastlines of Chile, other localities, like Java, Indonesia, could incorporate direct tsunami observations into their hazard forecasts with enough lead time to be effective for coastal community emergency response. We take into account the effect of tsunami propagation with regard to shallow bathymetry on the fore-arc as well as the effect of earthquake source placement. While it is impossible to account for every type of off-shore tsunamigenic event in these locales, this study aims to characterize a typical large tsunamigenic event occurring in the shallow part of the megathrust as a guide in what is feasible with early tsunami warning.

Adapting the EDuMaP method to test the performance of the Norwegian early warning system for weather-induced landslides

NASA Astrophysics Data System (ADS)

Piciullo, Luca; Dahl, Mads-Peter; Devoli, Graziella; Colleuille, Hervé; Calvello, Michele

2017-06-01

The Norwegian national landslide early warning system (LEWS), operational since 2013, is managed by the Norwegian Water Resources and Energy Directorate and was designed for monitoring and forecasting the hydrometeorological conditions potentially triggering slope failures. Decision-making in the LEWS is based upon rainfall thresholds, hydrometeorological and real-time landslide observations as well as on landslide inventory and susceptibility maps. Daily alerts are issued throughout the country considering variable size warning zones. Warnings are issued once per day for the following 3 days and can be updated according to weather forecasts and information gathered by the monitoring network. The performance of the LEWS operational in Norway has been evaluated applying the EDuMaP method, which is based on the computation of a duration matrix relating number of landslides and warning levels issued in a warning zone. In the past, this method has been exclusively employed to analyse the performance of regional early warning models considering fixed warning zones. Herein, an original approach is proposed for the computation of the elements of the duration matrix in the case of early warning models issuing alerts on variable size areas. The approach has been used to evaluate the warnings issued in Western Norway, in the period 2013-2014, considering two datasets of landslides. The results indicate that the landslide datasets do not significantly influence the performance evaluation, although a slightly better performance is registered for the smallest dataset. Different performance results are observed as a function of the values adopted for one of the most important input parameters of EDuMaP, the landslide density criterion (i.e. setting the thresholds to differentiate among classes of landslide events). To investigate this issue, a parametric analysis has been conducted; the results of the analysis show significant differences among computed performances when absolute or relative landslide density criteria are considered.

The Tropical Ecology, Assessment and Monitoring (TEAM) Network: An early warning system for tropical rain forests.

PubMed

Rovero, Francesco; Ahumada, Jorge

2017-01-01

While there are well established early warning systems for a number of natural phenomena (e.g. earthquakes, catastrophic fires, tsunamis), we do not have an early warning system for biodiversity. Yet, we are losing species at an unprecedented rate, and this especially occurs in tropical rainforests, the biologically richest but most eroded biome on earth. Unfortunately, there is a chronic gap in standardized and pan-tropical data in tropical forests, affecting our capacity to monitor changes and anticipate future scenarios. The Tropical Ecology, Assessment and Monitoring (TEAM) Network was established to contribute addressing this issue, as it generates real time data to monitor long-term trends in tropical biodiversity and guide conservation practice. We present the Network and focus primarily on the Terrestrial Vertebrates protocol, that uses systematic camera trapping to detect forest mammals and birds, and secondarily on the Zone of Interaction protocol, that measures changes in the anthroposphere around the core monitoring area. With over 3 million images so far recorded, and managed using advanced information technology, TEAM has created the most important data set on tropical forest mammals globally. We provide examples of site-specific and global analyses that, combined with data on anthropogenic disturbance collected in the larger ecosystem where monitoring sites are, allowed us to understand the drivers of changes of target species and communities in space and time. We discuss the potential of this system as a candidate model towards setting up an early warning system that can effectively anticipate changes in coupled human-natural system, trigger management actions, and hence decrease the gap between research and management responses. In turn, TEAM produces robust biodiversity indicators that meet the requirements set by global policies such as the Aichi Biodiversity Targets. Standardization in data collection and public sharing of data in near real time are essential features of such system. Copyright © 2016 Elsevier B.V. All rights reserved.

MyShake: A smartphone seismic network for earthquake early warning and beyond

PubMed Central

Kong, Qingkai; Allen, Richard M.; Schreier, Louis; Kwon, Young-Woo

2016-01-01

Large magnitude earthquakes in urban environments continue to kill and injure tens to hundreds of thousands of people, inflicting lasting societal and economic disasters. Earthquake early warning (EEW) provides seconds to minutes of warning, allowing people to move to safe zones and automated slowdown and shutdown of transit and other machinery. The handful of EEW systems operating around the world use traditional seismic and geodetic networks that exist only in a few nations. Smartphones are much more prevalent than traditional networks and contain accelerometers that can also be used to detect earthquakes. We report on the development of a new type of seismic system, MyShake, that harnesses personal/private smartphone sensors to collect data and analyze earthquakes. We show that smartphones can record magnitude 5 earthquakes at distances of 10 km or less and develop an on-phone detection capability to separate earthquakes from other everyday shakes. Our proof-of-concept system then collects earthquake data at a central site where a network detection algorithm confirms that an earthquake is under way and estimates the location and magnitude in real time. This information can then be used to issue an alert of forthcoming ground shaking. MyShake could be used to enhance EEW in regions with traditional networks and could provide the only EEW capability in regions without. In addition, the seismic waveforms recorded could be used to deliver rapid microseism maps, study impacts on buildings, and possibly image shallow earth structure and earthquake rupture kinematics. PMID:26933682

MyShake: A smartphone seismic network for earthquake early warning and beyond.

PubMed

Kong, Qingkai; Allen, Richard M; Schreier, Louis; Kwon, Young-Woo

2016-02-01

Large magnitude earthquakes in urban environments continue to kill and injure tens to hundreds of thousands of people, inflicting lasting societal and economic disasters. Earthquake early warning (EEW) provides seconds to minutes of warning, allowing people to move to safe zones and automated slowdown and shutdown of transit and other machinery. The handful of EEW systems operating around the world use traditional seismic and geodetic networks that exist only in a few nations. Smartphones are much more prevalent than traditional networks and contain accelerometers that can also be used to detect earthquakes. We report on the development of a new type of seismic system, MyShake, that harnesses personal/private smartphone sensors to collect data and analyze earthquakes. We show that smartphones can record magnitude 5 earthquakes at distances of 10 km or less and develop an on-phone detection capability to separate earthquakes from other everyday shakes. Our proof-of-concept system then collects earthquake data at a central site where a network detection algorithm confirms that an earthquake is under way and estimates the location and magnitude in real time. This information can then be used to issue an alert of forthcoming ground shaking. MyShake could be used to enhance EEW in regions with traditional networks and could provide the only EEW capability in regions without. In addition, the seismic waveforms recorded could be used to deliver rapid microseism maps, study impacts on buildings, and possibly image shallow earth structure and earthquake rupture kinematics.

Information Operations: Putting the ’I’ Back Into Dime

DTIC Science & Technology

2006-02-01

Texas Early Warning Center 9. Create New York Corporate Warning Network 10. Digital Marshall Plan using residual capability in abandoned satellites... us , and that all raw information—secret, unclassified, operational, logistic—must be brought together across distributed “pits” that are able to...is overt, using methods that do not compromise the integrity or impartiality of the UN, when the information can be shared and become widely known

On the Development of Multi-Hazard Early Warning Networks: Practical experiences from North and Central America.

NASA Astrophysics Data System (ADS)

Mencin, David; Hodgkinson, Kathleen; Braun, John; Meertens, Charles; Mattioli, Glen; Phillips, David; Blume, Fredrick; Berglund, Henry; Fox, Otina; Feaux, Karl

2015-04-01

The GAGE facility, managed by UNAVCO, maintains and operates about 1300 GNSS stations distributed across North and Central America as part of the EarthScope Plate Boundary Observatory (PBO) and the Continuously Operating Caribbean GPS Observational Network (COCONet). UNAVCO has upgraded about 450 stations in these networks to real-time and high-rate (RT-GNSS) and included surface meteorological instruments. The majority of these streaming stations are part of the PBO but also include approximately 50 RT-GNSS stations in the Caribbean and Central American region as part of the COCONet and TLALOCNet projects. Based on community input UNAVCO has been exploring ways to increase the capability and utility of these resources to improve our understanding in diverse areas of geophysics including seismic, volcanic, magmatic and tsunami deformation sources, extreme weather events such as hurricanes and storms, and space weather. The RT-GNSS networks also have the potential to profoundly transform our ability to rapidly characterize geophysical events, provide early warning, as well as improve hazard mitigation and response. Specific applications currently under development with university, commercial, non-profit and government collaboration on national and international scales include earthquake and tsunami early warning systems and near real-time tropospheric modeling of hurricanes and precipitable water vapor estimate assimilation. Using tsunami early warning as an example, an RT-GNSS network can provide multiple inputs in an operational system starting with rapid assessment of earthquake sources and associated deformation which informs the initial modeled tsunami. The networks can then can also provide direct measurements of the tsunami wave heights and propagation by tracking the associated ionospheric disturbance from several 100's of km away as the waves approaches the shoreline. These GNSS based constraints can refine the tsunami and inundation models and potentially mitigate hazards. Other scientific and operational applications for high-rate GPS include glacier and ice sheet motions, tropospheric modeling, and better constraints on the dynamics of space weather. Our operational system has multiple communities that use and depend on a Pan-Pacific real-time open data set. The ability to merge existing data sets and user communities, seismic and tide gauge observations, with GNSS and Met data products has proven complicated because of issues related to meta-data, appropriate data formats, data quality assessment in real-time and specific issues related to using these products in operational forecasting. Additional issues related to data access across national borders and cognizant government sanctioned "early warning" agencies, some committed to specific technologies, methodologies, internal structure and further constrained by data policies make a truly operational system an on-going work in progress. We present a short history of evolving a very large and expensive RT-GNSS network originally designed to answer specific long term scientific questions about structure and evolution of North American plate boundaries into a much needed national hazard system while continuing to serve our core community in long term scientific studies. Out primary focus in this presentation is an analysis of our current goals and impediments to achieving these broader objectives.

Technical note: Efficient online source identification algorithm for integration within a contamination event management system

NASA Astrophysics Data System (ADS)

Deuerlein, Jochen; Meyer-Harries, Lea; Guth, Nicolai

2017-07-01

Drinking water distribution networks are part of critical infrastructures and are exposed to a number of different risks. One of them is the risk of unintended or deliberate contamination of the drinking water within the pipe network. Over the past decade research has focused on the development of new sensors that are able to detect malicious substances in the network and early warning systems for contamination. In addition to the optimal placement of sensors, the automatic identification of the source of a contamination is an important component of an early warning and event management system for security enhancement of water supply networks. Many publications deal with the algorithmic development; however, only little information exists about the integration within a comprehensive real-time event detection and management system. In the following the analytical solution and the software implementation of a real-time source identification module and its integration within a web-based event management system are described. The development was part of the SAFEWATER project, which was funded under FP 7 of the European Commission.

Early-warning signals of topological collapse in interbank networks

PubMed Central

Squartini, Tiziano; van Lelyveld, Iman; Garlaschelli, Diego

2013-01-01

The financial crisis clearly illustrated the importance of characterizing the level of ‘systemic’ risk associated with an entire credit network, rather than with single institutions. However, the interplay between financial distress and topological changes is still poorly understood. Here we analyze the quarterly interbank exposures among Dutch banks over the period 1998–2008, ending with the crisis. After controlling for the link density, many topological properties display an abrupt change in 2008, providing a clear – but unpredictable – signature of the crisis. By contrast, if the heterogeneity of banks' connectivity is controlled for, the same properties show a gradual transition to the crisis, starting in 2005 and preceded by an even earlier period during which anomalous debt loops could have led to the underestimation of counter-party risk. These early-warning signals are undetectable if the network is reconstructed from partial bank-specific data, as routinely done. We discuss important implications for bank regulatory policies. PMID:24285089

Immediate causality network of stock markets

NASA Astrophysics Data System (ADS)

Zhou, Li; Qiu, Lu; Gu, Changgui; Yang, Huijie

2018-02-01

Extensive works show that a network of stocks within a single stock market stores rich information on evolutionary behaviors of the system, such as collapses and/or crises. But a financial event covers usually several markets or even the global financial system. This mismatch of scale leads to lack of concise information to coordinate the event. In this work by using the transfer entropy we reconstruct the influential network between ten typical stock markets distributed in the world. Interesting findings include, before a financial crisis the connection strength reaches a maximum, which can act as an early warning signal of financial crises. The markets in America are monodirectionally and strongly influenced by that in Europe and act as the center. Some strongly linked pairs have also close correlations. The findings are helpful in understanding the evolution and modelling the dynamical process of the global financial system. This method can be extended straightly to find early warning signals for physiological and ecological systems, etc.

G-FAST Early Warning Potential for Great Earthquakes in Chile

NASA Astrophysics Data System (ADS)

Crowell, B.; Schmidt, D. A.; Baker, B. I.; Bodin, P.; Vidale, J. E.

2016-12-01

The importance of GNSS-based earthquake early warning for modeling large earthquakes has been studied extensively over the past decade and several such systems are currently under development. In the Pacific Northwest, we have developed the G-FAST GNSS-based earthquake early warning module for eventual inclusion in the US West-Coast wide ShakeAlert system. We have also created a test system that allows us to replay past and synthetic earthquakes to identify problems with both the network architecture and the algorithms. Between 2010 and 2016, there have been seven M > 8 earthquakes across the globe, of which three struck offshore Chile; the 27 February 2010 Mw 8.8 Maule, the 1 April 2014 Mw 8.2 Iquique, and the 16 September 2015 Mw 8.3 Illapel. Subsequent to these events, the Chilean national GNSS network operated by the Centro Sismologico Nacional (http://www.sismologia.cl/) greatly expanded to over 150 continuous GNSS stations, providing the best recordings of great earthquakes with GNSS outside of Japan. Here we report on retrospective G-FAST performance for those three great earthquakes in Chile. We discuss the interplay of location errors, latency, and data completeness with respect to the precision and timing of G-FAST earthquake source alerts as well as the computational demands of the system.

Cyanobacteria Assessment Network (CyAN)

EPA Pesticide Factsheets

CyAN is a multi-agency project among the National Aeronautics and Space Administration (NASA), National Oceanic and Atmospheric Administration (NOAA), US Geological Survey (USGS), and EPA to develop an early warning indicator system to detect algal blooms.

Delay Analysis of Car-to-Car Reliable Data Delivery Strategies Based on Data Mulling with Network Coding

NASA Astrophysics Data System (ADS)

Park, Joon-Sang; Lee, Uichin; Oh, Soon Young; Gerla, Mario; Lun, Desmond Siumen; Ro, Won Woo; Park, Joonseok

Vehicular ad hoc networks (VANET) aims to enhance vehicle navigation safety by providing an early warning system: any chance of accidents is informed through the wireless communication between vehicles. For the warning system to work, it is crucial that safety messages be reliably delivered to the target vehicles in a timely manner and thus reliable and timely data dissemination service is the key building block of VANET. Data mulling technique combined with three strategies, network codeing, erasure coding and repetition coding, is proposed for the reliable and timely data dissemination service. Particularly, vehicles in the opposite direction on a highway are exploited as data mules, mobile nodes physically delivering data to destinations, to overcome intermittent network connectivity cause by sparse vehicle traffic. Using analytic models, we show that in such a highway data mulling scenario the network coding based strategy outperforms erasure coding and repetition based strategies.

The role of integrating natural and social science concepts for risk governance and the design of people-centred early warning systems. Case study from the German-Indonesian Tsunami Early Warning System Project (GITEWS)

NASA Astrophysics Data System (ADS)

Gebert, Niklas; Post, Joachim

2010-05-01

The development of early warning systems are one of the key domains of adaptation to global environmental change and contribute very much to the development of societal reaction and adaptive capacities to deal with extreme events. Especially, Indonesia is highly exposed to tsunami. In average every three years small and medium size tsunamis occur in the region causing damage and death. In the aftermath of the Indian Ocean Tsunami 2004, the German and Indonesian government agreed on a joint cooperation to develop a People Centered End-to-End Early Warning System (GITEWS). The analysis of risk and vulnerability, as an important step in risk (and early warning) governance, is a precondition for the design of effective early warning structures by delivering the knowledge base for developing institutionalized quick response mechanisms of organizations involved in the issuing of a tsunami warning, and of populations exposed to react to warnings and to manage evacuation before the first tsunami wave hits. Thus, a special challenge for developing countries is the governance of complex cross-sectoral and cross-scale institutional, social and spatial processes and requirements for the conceptualization, implementation and optimization of a people centered tsunami early warning system. In support of this, the risk and vulnerability assessment of the case study aims at identifying those factors that constitute the causal structure of the (dis)functionality between the technological warning and the social response system causing loss of life during an emergency situation: Which social groups are likely to be less able to receive and respond to an early warning alert? And, are people able to evacuate in due time? Here, only an interdisciplinary research approach is capable to analyze the socio-spatial and environmental conditions of vulnerability and risk and to produce valuable results for decision makers and civil society to manage tsunami risk in the early warning context. This requires the integration of natural / spatial and social science concepts, methods and data: E.g. a scenario based approach for tsunami inundation modeling was developed to provide decision makers with options to decide up to what level they aim to protect their people and territory, on the contrary household surveys were conducted for the spatial analysis of the evacuation preparedness of the population as a function of place specific hazard, risk, warning and evacuation perception; remote sensing was applied for the spatial analysis (land-use) of the socio-physical conditions of a city and region for evacuation; and existing social / population statistics were combined with land-use data for the precise spatial mapping of the population exposed to tsunami risks. Only by utilizing such a comprehensive assessment approach valuable information for risk governance can be generated. The results are mapped using GIS and designed according to the specific needs of different end-users, such as public authorities involved in the design of warning dissemination strategies, land-use planners (shelter planning, road network configuration) and NGOs mandated to provide education for the general public on tsunami risk and evacuation behavior. The case study of the city of Padang (one of the pilot areas of GITEWS), Indonesia clearly show, that only by intersecting social (vulnerability) and natural hazards research a comprehensive picture on tsunami risk can be provided with which risk governance in the early warning context can be conducted in a comprehensive, systemic and sustainable manner.

Technical Note: An operational landslide early warning system at regional scale based on space-time-variable rainfall thresholds

NASA Astrophysics Data System (ADS)

Segoni, S.; Battistini, A.; Rossi, G.; Rosi, A.; Lagomarsino, D.; Catani, F.; Moretti, S.; Casagli, N.

2015-04-01

We set up an early warning system for rainfall-induced landslides in Tuscany (23 000 km2). The system is based on a set of state-of-the-art intensity-duration rainfall thresholds (Segoni et al., 2014b) and makes use of LAMI (Limited Area Model Italy) rainfall forecasts and real-time rainfall data provided by an automated network of more than 300 rain gauges. The system was implemented in a WebGIS to ease the operational use in civil protection procedures: it is simple and intuitive to consult, and it provides different outputs. When switching among different views, the system is able to focus both on monitoring of real-time data and on forecasting at different lead times up to 48 h. Moreover, the system can switch between a basic data view where a synoptic scenario of the hazard can be shown all over the region and a more in-depth view were the rainfall path of rain gauges can be displayed and constantly compared with rainfall thresholds. To better account for the variability of the geomorphological and meteorological settings encountered in Tuscany, the region is subdivided into 25 alert zones, each provided with a specific threshold. The warning system reflects this subdivision: using a network of more than 300 rain gauges, it allows for the monitoring of each alert zone separately so that warnings can be issued independently. An important feature of the warning system is that the visualization of the thresholds in the WebGIS interface may vary in time depending on when the starting time of the rainfall event is set. The starting time of the rainfall event is considered as a variable by the early warning system: whenever new rainfall data are available, a recursive algorithm identifies the starting time for which the rainfall path is closest to or overcomes the threshold. This is considered the most hazardous condition, and it is displayed by the WebGIS interface. The early warning system is used to forecast and monitor the landslide hazard in the whole region, providing specific alert levels for 25 distinct alert zones. In addition, the system can be used to gather, analyze, display, explore, interpret and store rainfall data, thus representing a potential support to both decision makers and scientists.

Applying Network Theory to Develop a Dedicated National Intelligence Network

DTIC Science & Technology

2006-09-01

Los Angeles Sheriff’s Department .133 There is an interesting difference between the Washington, D.C. Police Department mission and others in...123 Atlanta, the TEW (Terrorist Early Warning) group (which is part of the Los Angeles Police Department ), and the intelligence and counter...intelligence “fusion” centers and perhaps the Los Angeles Police Department TEW. The

Onsite Portable Alarm System - Its Merit and Application

NASA Astrophysics Data System (ADS)

Saita, J.; Sato, T.; Nakamura, Y.

2007-12-01

Recently an existence of the earthquake early warning system (EEWS) becomes popular. In general, the EEWS will be installed in a fixed observation site and it may consist of several separated components such as a sensing portion, A/D converter, an information processing potion and so on. The processed information for warning may be transmitted to network via fixed communication line, and therefore this kind of alarm system is called as Network Alarm System. On the other hand, after the severe earthquake damage, it is very important to save the disaster victims immediately. These rescue staffs are also under the risk of aftershocks and need a local alarm not depending on the network, so this kind of alarm can be called as Onsite Alarm. But the common early warning system is too complex to set onsite temporary, and even if possible to install, the alarm is too late to receive at the epicentral area. However, the new generation earthquake early warning system FREQL can issue the P wave alarm by minimum 0.2 seconds after P wave detection. And FREQL is characterized as the unique all-in-one seismometer with power unit. At the time of the 2004 Niigata-Ken-Chuetsu earthquake, a land slide attacked a car just passing. A hyper rescue team of Tokyo Fire Department pulled the survivor, one baby, from the land slide area. During their activity the rescue team was exposed to the risk of secondary hazards caused by the aftershocks. It was clear that it is necessary to use a portable warning system to issue the onsite P wave alarm. Because FREQL was originally developed as portable equipment, Tokyo Fire Department asked us to modify it to the portable equipment with the loud sound and the light signal. In this moment, this portable FREQL has equipped in nation wide. When the hyper rescue team of Tokyo Fire Department was sent to Pakistan as a task force for rescue work of the 2005 Pakistan earthquake, the portable FREQL was used as important onsite portable warning system and P wave alarms was actually issued by three times during the rescue work. Although this is one example for the actual application of portable onsite alarm, it is possible to apply the other field as the construction field. In this presentation, Portable Onsite Alarm is discussed from views of its necessity and application.

Integrated SeismoGeodetic Systsem with High-Resolution, Real-Time GNSS and Accelerometer Observation For Earthquake Early Warning Application.

NASA Astrophysics Data System (ADS)

Passmore, P. R.; Jackson, M.; Zimakov, L. G.; Raczka, J.; Davidson, P.

2014-12-01

The key requirements for Earthquake Early Warning and other Rapid Event Notification Systems are: Quick delivery of digital data from a field station to the acquisition and processing center; Data integrity for real-time earthquake notification in order to provide warning prior to significant ground shaking in the given target area. These two requirements are met in the recently developed Trimble SG160-09 SeismoGeodetic System, which integrates both GNSS and acceleration measurements using the Kalman filter algorithm to create a new high-rate (200 sps), real-time displacement with sufficient accuracy and very low latency for rapid delivery of the acquired data to a processing center. The data acquisition algorithm in the SG160-09 System provides output of both acceleration and displacement digital data with 0.2 sec delay. This is a significant reduction in the time interval required for real-time transmission compared to data delivery algorithms available in digitizers currently used in other Earthquake Early Warning networks. Both acceleration and displacement data are recorded and transmitted to the processing site in a specially developed Multiplexed Recording Format (MRF) that minimizes the bandwidth required for real-time data transmission. In addition, a built in algorithm calculates the τc and Pd once the event is declared. The SG160-09 System keeps track of what data has not been acknowledged and re-transmits the data giving priority to current data. Modified REF TEK Protocol Daemon (RTPD) receives the digital data and acknowledges data received without error. It forwards this "good" data to processing clients of various real-time data processing software including Earthworm and SeisComP3. The processing clients cache packets when a data gap occurs due to a dropped packet or network outage. The cache packet time is settable, but should not exceed 0.5 sec in the Earthquake Early Warning network configuration. The rapid data transmission algorithm was tested with different communication media, including Internet, DSL, Wi-Fi, GPRS, etc. The test results show that the data latency via most communication media do not exceed 0.5 sec nominal from a first sample in the data packet. Detailed acquisition algorithm and results of data transmission via different communication media are presented.

Development of communication networks and water quality early warning detection systems at drinking water utilities in the Ohio River Valley Basin.

PubMed

Schulte, J G; Vicory, A H

2005-01-01

Source water quality is of major concern to all drinking water utilities. The accidental introduction of contaminants to their source water is a constant threat to utilities withdrawing water from navigable or industrialized rivers. The events of 11 September, 2001 in the United States have heightened concern for drinking water utility security as their source water and finished water may be targets for terrorist acts. Efforts are underway in several parts of the United States to strengthen early warning capabilities. This paper will focus on those efforts in the Ohio River Valley Basin.

Focus Upon Implementing the GGOS Decadal Vision for Geohazards Monitoring

NASA Astrophysics Data System (ADS)

LaBrecque, John; Stangl, Gunter

2017-04-01

The Global Geodetic Observing System of the IAG identified present and future roles for Geodesy in the development and well being of the global society. The GGOS is focused upon the development of infrastructure, information, analysis, and educational systems to advance the International Global Reference Frame, the International Celestial Reference System, the International Height Reference System, atmospheric dynamics, sea level change and geohazards monitoring. The geohazards initiative is guided by an eleven nation working group initially focused upon the development and integration of regional multi-GNSS networks and analysis systems for earthquake and tsunami early warning. The opportunities and challenges being addressed by the Geohazards working group include regional network design, algorithm development and implementation, communications, funding, and international agreements on data access. This presentation will discuss in further detail these opportunities and challenges for the GGOS focus upon earthquake and tsunami early warning.

Real-time decision support systems: the famine early warning system network

USGS Publications Warehouse

Funk, Christopher C.; Verdin, James P.

2010-01-01

A multi-institutional partnership, the US Agency for International Development’s Famine Early Warning System Network (FEWS NET) provides routine monitoring of climatic, agricultural, market, and socioeconomic conditions in over 20 countries. FEWS NET supports and informs disaster relief decisions that impact millions of people and involve billions of dollars. In this chapter, we focus on some of FEWS NET’s hydrologic monitoring tools, with a specific emphasis on combining “low frequency” and “high frequency” assessment tools. Low frequency assessment tools, tied to water and food balance estimates, enable us to evaluate and map long-term tendencies in food security. High frequency assessments are supported by agrohydrologic models driven by satellite rainfall estimates, such as the Water Requirement Satisfaction Index (WRSI). Focusing on eastern Africa, we suggest that both these high and low frequency approaches are necessary to capture the interaction of slow variations in vulnerability and the relatively rapid onset of climatic shocks.

Towards a certification process for tsunami early warning systems

NASA Astrophysics Data System (ADS)

Löwe, Peter; Wächter, Jochen; Hammitzsch, Martin

2013-04-01

The natural disaster of the Boxing Day Tsunami of 2004 was followed by an information catastrophe. Crucial early warning information could not be delivered to the communities under imminent threat, resulting in over 240,000 casualties in 14 countries. This tragedy sparked the development of a new generation of integrated modular Tsunami Early Warning Systems (TEWS). While significant advances were accomplished in the past years, recent events, like the Chile 2010 and the Tohoku 2011 tsunami demonstrate that the key technical challenge for Tsunami Early Warning research on the supranational scale still lies in the timely issuing of status information and reliable early warning messages in a proven workflow. A second challenge stems from the main objective of the Intergovernmental Oceanographic Commission of UNESCO (IOC) Tsunami Programme, the integration of national TEWS towards ocean-wide networks: Each of the increasing number of integrated Tsunami Early Warning Centres has to cope with the continuing evolution of sensors, hardware and software while having to maintain reliable inter-center information exchange services. To avoid future information catastrophes, the performance of all components, ranging from individual sensors, to Warning Centers within their particular end-to-end Warning System Environments, and up to federated Systems of Tsunami Warning Systems has to be regularly validated against defined criteria. Since 2004, GFZ German Research Centre for Geosciences (GFZ) has built up expertise in the field of TEWS. Within GFZ, the Centre for GeoInformation Technology (CeGIT) has focused its work on the geoinformatics aspects of TEWS in two projects already, being the German Indonesian Tsunami Early Warning System (GITEWS) and the Distant Early Warning System (DEWS). This activity is continued in the TRIDEC project (Collaborative, Complex, and Critical Decision Processes in Evolving Crises) funded under the European Union's seventh Framework Programme (FP7). TRIDEC focuses on real-time intelligent information management in Earth management and its long-term application: The technical development is based on mature system architecture models and industry standards. The use of standards already applies to the operation of individual TRIDEC reference installations and their interlinking into an integrated service infrastructure for supranational warning services. This is a first step towards best practices and service lifecycles for Early Warning Centre IT service management, including Service Level Agreements (SLA) and Service Certification. While on a global scale the integration of TEWS progresses towards Systems of Systems (SoS), there is still an absence of accredited and reliable certifications for national TEWS or regional Tsunami Early Warning Systems of Systems (TEWSoS). Concepts for TEWS operations have already been published under the guidance of the IOC, and can now be complemented by the recent research advances concerning SoS architecture. Combined with feedback from the real world, such as the NEAMwave 2012 Tsunami exercise in the Mediterranean, this can serve as a starting point to formulate initial requirements for TEWS and TEWSoS certification: Certification activities will cover the establishment of new TEWS and TEWSoS, and also both maintenance and enhancement of existing TEWS/TEWSoS. While the IOC is expected to take a central role in the development of the certification strategy, it remains to be defined which bodies will actually conduct the certification process. Certification requirements and results are likely to become a valuable information source for various target groups, ranging from national policy decision makers, government agency planners, national and local government preparedness officials, TWC staff members, Disaster Responders, the media and the insurance industry.

Performance of Earthquake Early Warning Systems during the Major Events of the 2016-2017 Central Italy Seismic Sequence.

NASA Astrophysics Data System (ADS)

Festa, G.; Picozzi, M.; Alessandro, C.; Colombelli, S.; Cattaneo, M.; Chiaraluce, L.; Elia, L.; Martino, C.; Marzorati, S.; Supino, M.; Zollo, A.

2017-12-01

Earthquake early warning systems (EEWS) are systems nowadays contributing to the seismic risk mitigation actions, both in terms of losses and societal resilience, by issuing an alert promptly after the earthquake origin and before the ground shaking impacts the targets to be protected. EEWS systems can be grouped in two main classes: network based and stand-alone systems. Network based EEWS make use of dense seismic networks surrounding the fault (e.g. Near Fault Observatory; NFO) generating the event. The rapid processing of the P-wave early portion allows for the location and magnitude estimation of the event then used to predict the shaking through ground motion prediction equations. Stand-alone systems instead analyze the early P-wave signal to predict the ground shaking carried by the late S or surface waves, through empirically calibrated scaling relationships, at the recording site itself. We compared the network-based (PRESTo, PRobabilistic and Evolutionary early warning SysTem, www.prestoews.org, Satriano et al., 2011) and the stand-alone (SAVE, on-Site-Alert-leVEl, Caruso et al., 2017) systems, by analyzing their performance during the 2016-2017 Central Italy sequence. We analyzed 9 earthquakes having magnitude 5.0 < M < 6.5 at about 200 stations located within 200 km from the epicentral area, including stations of The Altotiberina NFO (TABOO). Performances are evaluated in terms of rate of success of ground shaking intensity prediction and available lead-time, i.e. the time available for security actions. PRESTo also evaluated the accuracy of location and magnitude. Both systems well predict the ground shaking nearby the event source, with a success rate around 90% within the potential damage zone. The lead-time is significantly larger for the network based system, increasing to more than 10s at 40 km from the event epicentre. The stand-alone system better performs in the near-source region showing a positive albeit small lead-time (<3s). Far away from the source, the performances slightly degrade, mostly owing to uncertain calibration of attenuation relationships. This study opens to the possibility of making EEWS operational in Italy, based on the available acceleration networks, by improving the capability of reducing the lead-time related to data telemetry.

Feasibility study of earthquake early warning (EEW) in Hawaii

USGS Publications Warehouse

Thelen, Weston A.; Hotovec-Ellis, Alicia J.; Bodin, Paul

2016-09-30

The effects of earthquake shaking on the population and infrastructure across the State of Hawaii could be catastrophic, and the high seismic hazard in the region emphasizes the likelihood of such an event. Earthquake early warning (EEW) has the potential to give several seconds of warning before strong shaking starts, and thus reduce loss of life and damage to property. The two approaches to EEW are (1) a network approach (such as ShakeAlert or ElarmS) where the regional seismic network is used to detect the earthquake and distribute the alarm and (2) a local approach where a critical facility has a single seismometer (or small array) and a warning system on the premises.The network approach, also referred to here as ShakeAlert or ElarmS, uses the closest stations within a regional seismic network to detect and characterize an earthquake. Most parameters used for a network approach require observations on multiple stations (typically 3 or 4), which slows down the alarm time slightly, but the alarms are generally more reliable than with single-station EEW approaches. The network approach also benefits from having stations closer to the source of any potentially damaging earthquake, so that alarms can be sent ahead to anyone who subscribes to receive the notification. Thus, a fully implemented ShakeAlert system can provide seconds of warning for both critical facilities and general populations ahead of damaging earthquake shaking.The cost to implement and maintain a fully operational ShakeAlert system is high compared to a local approach or single-station solution, but the benefits of a ShakeAlert system would be felt statewide—the warning times for strong shaking are potentially longer for most sources at most locations.The local approach, referred to herein as “single station,” uses measurements from a single seismometer to assess whether strong earthquake shaking can be expected. Because of the reliance on a single station, false alarms are more common than when using a regional network of seismometers. Given the current network, a single-station approach provides more warning for damaging earthquakes that occur close to the station, but it would have limited benefit compared to a fully implemented ShakeAlert system. For Honolulu, for example, the single-station approach provides an advantage over ShakeAlert only for earthquakes that occur in a narrow zone extending northeast and southwest of O‘ahu. Instrumentation and alarms associated with the single-station approach are typically maintained and assessed within the target facility, and thus no outside connectivity is required. A single-station approach, then, is unlikely to help broader populations beyond the individuals at the target facility, but they have the benefit of being commercially available for relatively little cost. The USGS Hawaiian Volcano Observatory (HVO) is the Advanced National Seismic System (ANSS) regional seismic network responsible for locating and characterizing earthquakes across the State of Hawaii. During 2014 and 2015, HVO tested a network-based EEW algorithm within the current seismic network in order to assess the suitability for building a full EEW system. Using the current seismic instrumentation and processing setup at HVO, it is possible for a network approach to release an alarm a little more than 3 seconds after the earthquake is recorded on the fourth seismometer. Presently, earthquakes having M≥3 detected with the ElarmS algorithm have an average location error of approximately 4.5 km and an average magnitude error of -0.3 compared to the reviewed catalog locations from the HVO. Additional stations and upgrades to existing seismic stations would serve to improve solution precision and warning times and additional staffing would be required to provide support for a robust, network-based EEW system. For a critical facility on the Island of Hawaiʻi, such as the telescopes atop Mauna Kea, one phased approach to mitigate losses could be to immediately install a single station system to establish some level of warning. Subsequently, supporting the implementation of a full network-based EEW system on the Island of Hawaiʻi would provide additional benefit in the form of improved warning times once the system is fully installed and operational, which may take several years. Distributed populations across the Hawaiian Islands, including those outside the major cities and far from the likely earthquake source areas, would likely only benefit from a network approach such as ShakeAlert to provide warnings of strong shaking.

A triangular climate-based decision model to forecast crop anomalies in Kenya

NASA Astrophysics Data System (ADS)

Guimarães Nobre, G.; Davenport, F.; Veldkamp, T.; Jongman, B.; Funk, C. C.; Husak, G. J.; Ward, P.; Aerts, J.

2017-12-01

By the end of 2017, the world is expected to experience unprecedented demands for food assistance where, across 45 countries, some 81 million people will face a food security crisis. Prolonged droughts in Eastern Africa are playing a major role in these crises. To mitigate famine risk and save lives, government bodies and international donor organisations are increasingly building up efforts to resolve conflicts and secure humanitarian relief. Disaster-relief and financing organizations traditionally focus on emergency response, providing aid after an extreme drought event, instead of taking actions in advance based on early warning. One of the reasons for this approach is that the seasonal risk information provided by early warning systems is often considered highly uncertain. Overcoming the reluctance to act based on early warnings greatly relies on understanding the risk of acting in vain, and assessing the cost-effectiveness of early actions. This research develops a triangular climate-based decision model for multiple seasonal time-scales to forecast strong anomalies in crop yield shortages in Kenya using Casual Discovery Algorithms and Fast and Frugal Decision Trees. This Triangular decision model (1) estimates the causality and strength of the relationship between crop yields and hydro climatological predictors (extracted from the Famine Early Warning Systems Network's data archive) during the crop growing season; (2) provides probabilistic forecasts of crop yield shortages in multiple time scales before the harvesting season; and (3) evaluates the cost-effectiveness of different financial mechanisms to respond to early warning indicators of crop yield shortages obtained from the model. Furthermore, we reflect on how such a model complements and advances the current state-of-art FEWS Net system, and examine its potential application to improve the management of agricultural risks in Kenya.

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 cooperation with other real-time efforts around the Pacific Rim in terms of sharing, analysis centers, and advisory bulletins to the responsible government agencies. The IAG's Global Geodetic Observing System (GGOS), in particular its natural hazards theme, provides a natural umbrella for achieving this objective.

A new prototype system for earthquake early warning in Taiwan

NASA Astrophysics Data System (ADS)

Hsiao, N.; Wu, Y.; Chen, D.; Kuo, K.; Shin, T.

2009-12-01

Earthquake early warning (EEW) system has already been developed and tested in Taiwan for more than ten years. With the implementation of a real-time strong-motion network by the Central Weather Bureau (CWB), a virtual sub-network (VSN) system based on regional early warning approach was utilized at the first attempt. In order to shorten the processing time, seismic waveforms in a 10-sec time window starting from the first P-wave arrival time at the nearest station are used to determine the hypocenter and earthquake magnitude which is dubbed ML10. Since 2001, this EEW system has responded to a total of 255 events with magnitude greater than 4.5 occurred inland or off the coast of Taiwan. The system is capable of issuing an earthquake report within 20 sec of its occurrence with good magnitude estimations for events up to magnitude 6.5. This will provide early warning for metropolitan areas located 70 km away from the epicentre. In the latest development, a new prototype EEW system based on P-wave method was developed. Instead of ML10, we adopt the “Pd magnitude”, MPd, as our magnitude indicator in the new system. Pd is defined as the peak amplitude of the initial P-wave displacement. In the previous studies, by analyzing the Pd attenuation relationship with earthquake magnitudes, Pd was proved to be a good magnitude estimator for EEW purpose. Therefore, we adopt the Pd magnitude in developing our next generation EEW system. The new system is designed and constructed based on the Central Weather Bureau Seismographic Network (CWBSN). The CWBSN is a real-time seismographic network with more than one hundred digital telemetered seismic stations distributed over the entire Taiwan. Currently, there are three types of seismic instruments installed at the stations, either co-site or separately installed, including short-period seismographs, accelerometers, and broadband instruments. For the need of integral data processing, we use the Earthworm system as a common platform to integrate all real-time signals. In the process, strong-motion and broadband signals are used for automatic P-wave arrival time and Pd determination. However, short-period signals are only used for P-wave arrival time picking. This new system is still under development and being improved, with the hope of replacing the current operational EEW system in the future.

Developing an operational rangeland water requirement satisfaction index

USGS Publications Warehouse

Senay, Gabriel B.; Verdin, James P.; Rowland, James

2011-01-01

Developing an operational water requirement satisfaction index (WRSI) for rangeland monitoring is an important goal of the famine early warning systems network. An operational WRSI has been developed for crop monitoring, but until recently a comparable WRSI for rangeland was not successful because of the extremely poor performance of the index when based on published crop coefficients (K c) for rangelands. To improve the rangeland WRSI, we developed a simple calibration technique that adjusts the K c values for rangeland monitoring using long-term rainfall distribution and reference evapotranspiration data. The premise for adjusting the K c values is based on the assumption that a viable rangeland should exhibit above-average WRSI (values >80%) during a normal year. The normal year was represented by a median dekadal rainfall distribution (satellite rainfall estimate from 1996 to 2006). Similarly, a long-term average for potential evapotranspiration was used as input to the famine early warning systems network WRSI model in combination with soil-water-holding capacity data. A dekadal rangeland WRSI has been operational for east and west Africa since 2005. User feedback has been encouraging, especially with regard to the end-of-season WRSI anomaly products that compare the index's performance to ‘normal’ years. Currently, rangeland WRSI products are generated on a dekadal basis and posted for free distribution on the US Geological Survey early warning website at http://earlywarning.usgs.gov/adds/

Design Principles for resilient cyber-physical Early Warning Systems - Challenges, Experiences, Design Patterns, and Best Practices

NASA Astrophysics Data System (ADS)

Gensch, S.; Wächter, J.; Schnor, B.

2014-12-01

Early warning systems (EWS) are safety-critical IT-infrastructures that serve the purpose of potentially saving lives or assets by observing real-world phenomena and issuing timely warning products to authorities and communities. An EWS consists of sensors, communication networks, data centers, simulation platforms, and dissemination channels. The components of this cyber-physical system may all be affected by both natural hazards and malfunctions of components alike. Resilience engineering so far has mostly been applied to safety-critical systems and processes in transportation (aviation, automobile), construction and medicine. Early warning systems need equivalent techniques to compensate for failures, and furthermore means to adapt to changing threats, emerging technology and research findings. We present threats and pitfalls from our experiences with the German and Indonesian tsunami early warning system, as well as architectural, technological and organizational concepts employed that can enhance an EWS' resilience. The current EWS is comprised of a multi-type sensor data upstream part, different processing and analysis engines, a decision support system, and various warning dissemination channels. Each subsystem requires a set of approaches towards ensuring stable functionality across system layer boundaries, including also institutional borders. Not only must services be available, but also produce correct results. Most sensors are distributed components with restricted resources, communication channels and power supply. An example for successful resilience engineering is the power capacity based functional management for buoy and tide gauge stations. We discuss various fault-models like cause and effect models on linear pathways, interaction of multiple events, complex and non-linear interaction of assumedly reliable subsystems and fault tolerance means implemented to tackle these threats.

Far-field tsunami of 2017 Mw 8.1 Tehuantepec, Mexico earthquake recorded by Chilean tide gauge network: Implications for tsunami warning systems

NASA Astrophysics Data System (ADS)

González-Carrasco, J. F.; Benavente, R. F.; Zelaya, C.; Núñez, C.; Gonzalez, G.

2017-12-01

The 2017 Mw 8.1, Tehuantepec earthquake generated a moderated tsunami, which was registered in near-field tide gauges network activating a tsunami threat state for Mexico issued by PTWC. In the case of Chile, the forecast of tsunami waves indicate amplitudes less than 0.3 meters above the tide level, advising an informative state of threat, without activation of evacuation procedures. Nevertheless, during sea level monitoring of network we detect wave amplitudes (> 0.3 m) indicating a possible change of threat state. Finally, NTWS maintains informative level of threat based on mathematical filtering analysis of sea level records. After 2010 Mw 8.8, Maule earthquake, the Chilean National Tsunami Warning System (NTWS) has increased its observational capabilities to improve early response. Most important operational efforts have focused on strengthening tide gauge network for national area of responsibility. Furthermore, technological initiatives as Integrated Tsunami Prediction and Warning System (SIPAT) has segmented the area of responsibility in blocks to focus early warning and evacuation procedures on most affected coastal areas, while maintaining an informative state for distant areas of near-field earthquake. In the case of far-field events, NTWS follow the recommendations proposed by Pacific Tsunami Warning Center (PTWC), including a comprehensive monitoring of sea level records, such as tide gauges and DART (Deep-Ocean Assessment and Reporting of Tsunami) buoys, to evaluate the state of tsunami threat in the area of responsibility. The main objective of this work is to analyze the first-order physical processes involved in the far-field propagation and coastal impact of tsunami, including implications for decision-making of NTWS. To explore our main question, we construct a finite-fault model of the 2017, Mw 8.1 Tehuantepec earthquake. We employ the rupture model to simulate a transoceanic tsunami modeled by Neowave2D. We generate synthetic time series at tide gauge stations and compare them with recorded sea level data, to dismiss meteorological processes, such as storms and surges. Resonance analysis is performed by wavelet technique.

A New Strategy for Analyzing Time-Series Data Using Dynamic Networks: Identifying Prospective Biomarkers of Hepatocellular Carcinoma.

PubMed

Huang, Xin; Zeng, Jun; Zhou, Lina; Hu, Chunxiu; Yin, Peiyuan; Lin, Xiaohui

2016-08-31

Time-series metabolomics studies can provide insight into the dynamics of disease development and facilitate the discovery of prospective biomarkers. To improve the performance of early risk identification, a new strategy for analyzing time-series data based on dynamic networks (ATSD-DN) in a systematic time dimension is proposed. In ATSD-DN, the non-overlapping ratio was applied to measure the changes in feature ratios during the process of disease development and to construct dynamic networks. Dynamic concentration analysis and network topological structure analysis were performed to extract early warning information. This strategy was applied to the study of time-series lipidomics data from a stepwise hepatocarcinogenesis rat model. A ratio of lyso-phosphatidylcholine (LPC) 18:1/free fatty acid (FFA) 20:5 was identified as the potential biomarker for hepatocellular carcinoma (HCC). It can be used to classify HCC and non-HCC rats, and the area under the curve values in the discovery and external validation sets were 0.980 and 0.972, respectively. This strategy was also compared with a weighted relative difference accumulation algorithm (wRDA), multivariate empirical Bayes statistics (MEBA) and support vector machine-recursive feature elimination (SVM-RFE). The better performance of ATSD-DN suggests its potential for a more complete presentation of time-series changes and effective extraction of early warning information.

A New Strategy for Analyzing Time-Series Data Using Dynamic Networks: Identifying Prospective Biomarkers of Hepatocellular Carcinoma

NASA Astrophysics Data System (ADS)

Huang, Xin; Zeng, Jun; Zhou, Lina; Hu, Chunxiu; Yin, Peiyuan; Lin, Xiaohui

2016-08-01

Time-series metabolomics studies can provide insight into the dynamics of disease development and facilitate the discovery of prospective biomarkers. To improve the performance of early risk identification, a new strategy for analyzing time-series data based on dynamic networks (ATSD-DN) in a systematic time dimension is proposed. In ATSD-DN, the non-overlapping ratio was applied to measure the changes in feature ratios during the process of disease development and to construct dynamic networks. Dynamic concentration analysis and network topological structure analysis were performed to extract early warning information. This strategy was applied to the study of time-series lipidomics data from a stepwise hepatocarcinogenesis rat model. A ratio of lyso-phosphatidylcholine (LPC) 18:1/free fatty acid (FFA) 20:5 was identified as the potential biomarker for hepatocellular carcinoma (HCC). It can be used to classify HCC and non-HCC rats, and the area under the curve values in the discovery and external validation sets were 0.980 and 0.972, respectively. This strategy was also compared with a weighted relative difference accumulation algorithm (wRDA), multivariate empirical Bayes statistics (MEBA) and support vector machine-recursive feature elimination (SVM-RFE). The better performance of ATSD-DN suggests its potential for a more complete presentation of time-series changes and effective extraction of early warning information.

PRESSCA: A regional operative Early Warning System for landslides risk scenario assessment

NASA Astrophysics Data System (ADS)

Ponziani, Francesco; Stelluti, Marco; Berni, Nicola; Brocca, Luca; Moramarco, Tommaso

2013-04-01

The Italian national alert system for the hydraulic and hydrogeological risk is ensured by the National Civil Protection Department, through the "Functional Centres" Network, together with scientific/technical Support Centres, named "Competence Centres". The role of the Functional Centres is to alert regional/national civil protection network, to manage the prediction and the monitoring phases, thus ensuring the flow of data for the management of the emergency. The Umbria regional alerting procedure is based on three increasing warning levels of criticality for 6 sub-areas (~1200 km²). Specifically, for each duration (from 1 to 48 hours), three criticality levels are assigned to the rainfall values corresponding to a recurrence interval of 2, 5, and 10 years. In order to improve confidence on the daily work for hydrogeological risk assessment and management, a simple and operational early warning system for the prediction of shallow landslide triggering on regional scale was implemented. The system is primarily based on rainfall thresholds, which represent the main element of evaluation for the early-warning procedures of the Italian Civil Protection system. Following previous studies highlighting that soil moisture conditions play a key role on landslide triggering, a continuous physically-based soil water balance model was implemented for the estimation of soil moisture conditions over the whole regional territory. In fact, a decreasing trend between the cumulated rainfall values over 24, 36 and 48 hours and the soil moisture conditions prior to past landslide events was observed. This trend provides an easy-to-use tool to dynamically adjust the operational rainfall thresholds with the soil moisture conditions simulated by the soil water balance model prior to rainfall events. The application of this procedure allowed decreasing the uncertainties tied to the application of the rainfall thresholds only. The system is actually operational in real-time and it was recently coupled with quantitative rainfall and temperature forecasts (given by the COSMO ME local scale models for Umbria) to extend the prediction up to 72 hours forecast. The main output is constituted by four spatially distributed early warning indicators (normal, caution, warning, alarm), in compliance with national and regional law, based on the comparison between the observed (forecasted) rainfall and the dynamic thresholds. The early warning indicators, calculated over the whole regional territory, are combined with susceptibility and vulnerability layers using a WEB-GIS platform, in order to build a near real time risk scenario. The main outcome of the system is a spatially distributed landslide hazard map with the highlight of areas where local risk situations may arise due to landslides induced by the interaction between meteorological forcing and the presence of vulnerability elements. The System is inclusive of specific sections dedicated to areas with specific risks (as debris flows prone areas), with specific thresholds. The main purpose of this study is firstly to describe the operational early warning system. Then, the integration of near real-time soil moisture data obtained through the satellite sensor ASCAT (Advanced SCATterometer) within the system is shown. This could allow enhancing the reliability of the modelled soil moisture data over the regional territory. The recent rainfall event of 11-14 November 2012 is used as case study. Reported triggered landslides are studied and used in order to check/refine the early warning system.

Cyber Signal/Noise Characteristics and Sensor Models for Early Cyber Indications and Warning

DTIC Science & Technology

2005-09-01

investigating and simulating attack scenarios. The sensors are, in effect , mathematical functions. These functions range from simple functions of...172 8.1.2 Examine each attack scenario or case to derive the cause- effect network for the attack scenario...threat profiles............................ 174 8.1.4 Develop attack profiles by enlarging the cause- effect network of each attack scenario with

Availability and Reliability of Disaster Early Warning Systems and the IT Infrastructure Library

NASA Astrophysics Data System (ADS)

Wächter, J.; Loewe, P.

2012-12-01

The Boxing Day Tsunami of 2004 caused an information catastrophy. Crucial early warning information could not be delivered to the communities under imminent threat, resulting in over 240,000 casualties in 14 countries. This tragedy sparked the development of a new generation of integrated modular Tsunami Early Warning Systems (TEWS). While significant advances were accomplished in the past years, recent events, like the Chile 2010 and the Tohoku 2011 tsunami demonstrate that the key technical challenge for Tsunami Early Warning research on the supranational scale still lies in the timely issuing of status information and reliable early warning messages. A key challenge stems from the main objective of the IOC Tsunami Programme, the integration of national TEWS towards ocean-wide networks: Each of the increasing number of integrated Tsunami Early Warning Centres has to cope with the continuing evolution of sensors, hardware and software while having to maintain reliable inter-center information exchange services. To avoid future information catastrophes, the performance of all components, ranging from sensors to Warning Centers, has to be regularly validated against defined criteria. This task is complicated by the fact that in term of ICT system life cycles tsunami are very rare event resulting in very difficult framing conditions to safeguard the availability and reliability of TWS. Since 2004, GFZ German Research Centre for Geosciences (GFZ) has built up expertise in the field of TEWS. Within GFZ, the Centre for GeoInformation Technology (CEGIT) has focused its work on the geoinformatics aspects of TEWS in two projects already: The German Indonesian Tsunami Early Warning System (GITEWS) funded by the German Federal Ministry of Education and Research (BMBF) and the Distant Early Warning System (DEWS), a European project funded under the sixth Framework Programme (FP6). These developments are continued in the TRIDEC project (Collaborative, Complex, and Critical Decision Processes in Evolving Crises) funded under the European Union's seventh Framework Programme (FP7). This ongoing project focuses on real-time intelligent information management in Earth management and its long-term application. All technical development in TRIDEC is based on mature system architecture models and industry standards. The use of standards applies also to the operation of individual TRIDEC reference installations and their interlinking into an integrated service infrastructure for supranational warning services: A set of best practices for IT service management is used to align the TEWS software services with the requirements by the Early Warning Centre management by defining Service Level Agreements (SLA) and ensuring appliance. For this, the concept of service lifecycles is adapted for the TEWS domain, which is laid out in the IT Infrastructure Library (ITIL) by the United Kingdom's Office of Government Commerce (OGC). The cyclic procedures, tasks and checklists described by ITIL are used to establish a baseline to plan, implement, and maintain TEWS service components in the long run. This allows to ensure compliance with given international TEWS standards and to measure improvement of the provided services against a gold-standard.

A land data assimilation system for sub-Saharan Africa food and water security applications

PubMed Central

McNally, Amy; Arsenault, Kristi; Kumar, Sujay; Shukla, Shraddhanand; Peterson, Pete; Wang, Shugong; Funk, Chris; Peters-Lidard, Christa D.; Verdin, James P.

2017-01-01

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET’s operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa. PMID:28195575

A land data assimilation system for sub-Saharan Africa food and water security applications

USGS Publications Warehouse

McNally, Amy; Arsenault, Kristi; Kumar, Sujay; Shukla, Shraddhanand; Peterson, Pete; Wang, Shugong; Funk, Chris; Peters-Lidard, Christa; Verdin, James

2017-01-01

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET’s operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

A land data assimilation system for sub-Saharan Africa food and water security applications.

PubMed

McNally, Amy; Arsenault, Kristi; Kumar, Sujay; Shukla, Shraddhanand; Peterson, Pete; Wang, Shugong; Funk, Chris; Peters-Lidard, Christa D; Verdin, James P

2017-02-14

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET's operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

Data Descriptor: A Land Data Assimilation System for Sub-Saharan Africa Food and Water Security Applications

NASA Technical Reports Server (NTRS)

McNally, Amy; Arsenault, Krist; Kumar, Sujay; Shukla, Shraddhanand; Peter, Pete; Wang, Shugong; Funk, Chris; Peters-Lidard, Christa D.; Verdin, James

2017-01-01

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWSNETs operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

A land data assimilation system for sub-Saharan Africa food and water security applications

NASA Astrophysics Data System (ADS)

McNally, Amy; Arsenault, Kristi; Kumar, Sujay; Shukla, Shraddhanand; Peterson, Pete; Wang, Shugong; Funk, Chris; Peters-Lidard, Christa D.; Verdin, James P.

2017-02-01

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET's operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

Crowd-Sourced Global Earthquake Early Warning

NASA Astrophysics Data System (ADS)

Minson, S. E.; Brooks, B. A.; Glennie, C. L.; Murray, J. R.; Langbein, J. O.; Owen, S. E.; Iannucci, B. A.; Hauser, D. L.

2014-12-01

Although earthquake early warning (EEW) has shown great promise for reducing loss of life and property, it has only been implemented in a few regions due, in part, to the prohibitive cost of building the required dense seismic and geodetic networks. However, many cars and consumer smartphones, tablets, laptops, and similar devices contain low-cost versions of the same sensors used for earthquake monitoring. If a workable EEW system could be implemented based on either crowd-sourced observations from consumer devices or very inexpensive networks of instruments built from consumer-quality sensors, EEW coverage could potentially be expanded worldwide. Controlled tests of several accelerometers and global navigation satellite system (GNSS) receivers typically found in consumer devices show that, while they are significantly noisier than scientific-grade instruments, they are still accurate enough to capture displacements from moderate and large magnitude earthquakes. The accuracy of these sensors varies greatly depending on the type of data collected. Raw coarse acquisition (C/A) code GPS data are relatively noisy. These observations have a surface displacement detection threshold approaching ~1 m and would thus only be useful in large Mw 8+ earthquakes. However, incorporating either satellite-based differential corrections or using a Kalman filter to combine the raw GNSS data with low-cost acceleration data (such as from a smartphone) decreases the noise dramatically. These approaches allow detection thresholds as low as 5 cm, potentially enabling accurate warnings for earthquakes as small as Mw 6.5. Simulated performance tests show that, with data contributed from only a very small fraction of the population, a crowd-sourced EEW system would be capable of warning San Francisco and San Jose of a Mw 7 rupture on California's Hayward fault and could have accurately issued both earthquake and tsunami warnings for the 2011 Mw 9 Tohoku-oki, Japan earthquake.

Early warning sensor network for brown-out conditions : phase II - field testing and assessment.

DOT National Transportation Integrated Search

2017-04-26

All three states within the SOLARIS (Nevada, Arizona, New Mexico) domain as well : as other states such as Oklahoma, Texas, and Colorado have had traffic accidents with : fatalities in recent years due to brownout conditions, where windblown dust is ...

Detection of rain events in radiological early warning networks with spectro-dosimetric systems

NASA Astrophysics Data System (ADS)

Dąbrowski, R.; Dombrowski, H.; Kessler, P.; Röttger, A.; Neumaier, S.

2017-10-01

Short-term pronounced increases of the ambient dose equivalent rate, due to rainfall are a well-known phenomenon. Increases in the same order of magnitude or even below may also be caused by a nuclear or radiological event, i.e. by artificial radiation. Hence, it is important to be able to identify natural rain events in dosimetric early warning networks and to distinguish them from radiological events. Novel spectrometric systems based on scintillators may be used to differentiate between the two scenarios, because the measured gamma spectra provide significant nuclide-specific information. This paper describes three simple, automatic methods to check whether an dot H*(10) increase is caused by a rain event or by artificial radiation. These methods were applied to measurements of three spectrometric systems based on CeBr3, LaBr3 and SrI2 scintillation crystals, investigated and tested for their practicability at a free-field reference site of PTB.

Identifying early-warning signals of critical transitions with strong noise by dynamical network markers

PubMed Central

Liu, Rui; Chen, Pei; Aihara, Kazuyuki; Chen, Luonan

2015-01-01

Identifying early-warning signals of a critical transition for a complex system is difficult, especially when the target system is constantly perturbed by big noise, which makes the traditional methods fail due to the strong fluctuations of the observed data. In this work, we show that the critical transition is not traditional state-transition but probability distribution-transition when the noise is not sufficiently small, which, however, is a ubiquitous case in real systems. We present a model-free computational method to detect the warning signals before such transitions. The key idea behind is a strategy: “making big noise smaller” by a distribution-embedding scheme, which transforms the data from the observed state-variables with big noise to their distribution-variables with small noise, and thus makes the traditional criteria effective because of the significantly reduced fluctuations. Specifically, increasing the dimension of the observed data by moment expansion that changes the system from state-dynamics to probability distribution-dynamics, we derive new data in a higher-dimensional space but with much smaller noise. Then, we develop a criterion based on the dynamical network marker (DNM) to signal the impending critical transition using the transformed higher-dimensional data. We also demonstrate the effectiveness of our method in biological, ecological and financial systems. PMID:26647650

Multiple-Threshold Event Detection and Other Enhancements to the Virtual Seismologist (VS) Earthquake Early Warning Algorithm

NASA Astrophysics Data System (ADS)

Fischer, M.; Caprio, M.; Cua, G. B.; Heaton, T. H.; Clinton, J. F.; Wiemer, S.

2009-12-01

The Virtual Seismologist (VS) algorithm is a Bayesian approach to earthquake early warning (EEW) being implemented by the Swiss Seismological Service at ETH Zurich. The application of Bayes’ theorem in earthquake early warning states that the most probable source estimate at any given time is a combination of contributions from a likelihood function that evolves in response to incoming data from the on-going earthquake, and selected prior information, which can include factors such as network topology, the Gutenberg-Richter relationship or previously observed seismicity. The VS algorithm was one of three EEW algorithms involved in the California Integrated Seismic Network (CISN) real-time EEW testing and performance evaluation effort. Its compelling real-time performance in California over the last three years has led to its inclusion in the new USGS-funded effort to develop key components of CISN ShakeAlert, a prototype EEW system that could potentially be implemented in California. A significant portion of VS code development was supported by the SAFER EEW project in Europe. We discuss recent enhancements to the VS EEW algorithm. We developed and continue to test a multiple-threshold event detection scheme, which uses different association / location approaches depending on the peak amplitudes associated with an incoming P pick. With this scheme, an event with sufficiently high initial amplitudes can be declared on the basis of a single station, maximizing warning times for damaging events for which EEW is most relevant. Smaller, non-damaging events, which will have lower initial amplitudes, will require more picks to be declared an event to reduce false alarms. This transforms the VS codes from a regional EEW approach reliant on traditional location estimation (and it requirement of at least 4 picks as implemented by the Binder Earthworm phase associator) to a hybrid on-site/regional approach capable of providing a continuously evolving stream of EEW information starting from the first P-detection. Offline analysis on Swiss and California waveform datasets indicate that the multiple-threshold approach is faster and more reliable for larger events than the earlier version of the VS codes. This multiple-threshold approach is well-suited for implementation on a wide range of devices, from embedded processor systems installed at a seismic stations, to small autonomous networks for local warnings, to large-scale regional networks such as the CISN. In addition, we quantify the influence of systematic use of prior information and Vs30-based corrections for site amplification on VS magnitude estimation performance, and describe how components of the VS algorithm will be integrated into non-EEW standard network processing procedures at CHNet, the national broadband / strong motion network in Switzerland. These enhancements to the VS codes will be transitioned from off-line to real-time testing at CHNet in Europe in the coming months, and will be incorporated into the development of key components of CISN ShakeAlert prototype system in California.

Neuronal network model of interictal and recurrent ictal activity

NASA Astrophysics Data System (ADS)

Lopes, M. A.; Lee, K.-E.; Goltsev, A. V.

2017-12-01

We propose a neuronal network model which undergoes a saddle node on an invariant circle bifurcation as the mechanism of the transition from the interictal to the ictal (seizure) state. In the vicinity of this transition, the model captures important dynamical features of both interictal and ictal states. We study the nature of interictal spikes and early warnings of the transition predicted by this model. We further demonstrate that recurrent seizures emerge due to the interaction between two networks.

Seismogeodesy for rapid earthquake and tsunami characterization

NASA Astrophysics Data System (ADS)

Bock, Y.

2016-12-01

Rapid estimation of earthquake magnitude and fault mechanism is critical for earthquake and tsunami warning systems. Traditionally, the monitoring of earthquakes and tsunamis has been based on seismic networks for estimating earthquake magnitude and slip, and tide gauges and deep-ocean buoys for direct measurement of tsunami waves. These methods are well developed for ocean basin-wide warnings but are not timely enough to protect vulnerable populations and infrastructure from the effects of local tsunamis, where waves may arrive within 15-30 minutes of earthquake onset time. Direct measurements of displacements by GPS networks at subduction zones allow for rapid magnitude and slip estimation in the near-source region, that are not affected by instrumental limitations and magnitude saturation experienced by local seismic networks. However, GPS displacements by themselves are too noisy for strict earthquake early warning (P-wave detection). Optimally combining high-rate GPS and seismic data (in particular, accelerometers that do not clip), referred to as seismogeodesy, provides a broadband instrument that does not clip in the near field, is impervious to magnitude saturation, and provides accurate real-time static and dynamic displacements and velocities in real time. Here we describe a NASA-funded effort to integrate GPS and seismogeodetic observations as part of NOAA's Tsunami Warning Centers in Alaska and Hawaii. It consists of a series of plug-in modules that allow for a hierarchy of rapid seismogeodetic products, including automatic P-wave picking, hypocenter estimation, S-wave prediction, magnitude scaling relationships based on P-wave amplitude (Pd) and peak ground displacement (PGD), finite-source CMT solutions and fault slip models as input for tsunami warnings and models. For the NOAA/NASA project, the modules are being integrated into an existing USGS Earthworm environment, currently limited to traditional seismic data. We are focused on a network of dozens of seismogeodetic stations available through the Pacific Northwest Seismic Network (University of Washington), the Plate Boundary Observatory (UNAVCO) and the Pacific Northwest Geodetic Array (Central Washington University) as the basis for local tsunami warnings for a large subduction zone earthquake in Cascadia.

Enhancing Famine Early Warning Systems with Improved Forecasts, Satellite Observations and Hydrologic Simulations

NASA Astrophysics Data System (ADS)

Funk, C. C.; Verdin, J.; Thiaw, W. M.; Hoell, A.; Korecha, D.; McNally, A.; Shukla, S.; Arsenault, K. R.; Magadzire, T.; Novella, N.; Peters-Lidard, C. D.; Robjohn, M.; Pomposi, C.; Galu, G.; Rowland, J.; Budde, M. E.; Landsfeld, M. F.; Harrison, L.; Davenport, F.; Husak, G. J.; Endalkachew, E.

2017-12-01

Drought early warning science, in support of famine prevention, is a rapidly advancing field that is helping to save lives and livelihoods. In 2015-2017, a series of extreme droughts afflicted Ethiopia, Southern Africa, Eastern Africa in OND and Eastern Africa in MAM, pushing more than 50 million people into severe food insecurity. Improved drought forecasts and monitoring tools, however, helped motivate and target large and effective humanitarian responses. Here we describe new science being developed by a long-established early warning system - the USAID Famine Early Warning Systems Network (FEWS NET). FEWS NET is a leading provider of early warning and analysis on food insecurity. FEWS NET research is advancing rapidly on several fronts, providing better climate forecasts and more effective drought monitoring tools that are being used to support enhanced famine early warning. We explore the philosophy and science underlying these successes, suggesting that a modal view of climate change can support enhanced seasonal prediction. Under this modal perspective, warming of the tropical oceans may interact with natural modes of variability, like the El Niño-Southern Oscillation, to enhance Indo-Pacific sea surface temperature gradients during both El Niño and La Niña-like climate states. Using empirical data and climate change simulations, we suggest that a sequence of droughts may commence in northern Ethiopia and Southern Africa with the advent of a moderate-to-strong El Niño, and then continue with La Niña/West Pacific related droughts in equatorial eastern East Africa. Scientifically, we show that a new hybrid statistical-dynamic precipitation forecast system, the FEWS NET Integrated Forecast System (FIFS), based on reformulations of the Global Ensemble Forecast System weather forecasts and National Multi-Model Ensemble (NMME) seasonal climate predictions, can effectively anticipate recent East and Southern African drought events. Using cross-validation, we evaluate FIFS' skill and compare it to the NMME and the International Research Institute forecasts. Our study concludes with an overview of the satellite observations provided by FEWS NET partners at NOAA, NASA, USGS, and UC Santa Barbara, and the assimilation of these products within the FEWS NET Land Data Assimilation System (FLDAS).

The Mexican Seismic Network (Red Sísmica Mexicana)

NASA Astrophysics Data System (ADS)

Valdes-Gonzales, C. M.; Arreola-Manzano, J.; Castelan-Pescina, G.; Alonso-Rivera, P.; Saldivar-Rangel, M. A.; Rodriguez-Arteaga, O. O.; Lopez-Lena-Villasana, R.

2014-12-01

The Mexican Seismic Network (Red Sísmica Mexicana) was created to give sufficient information and opportune to make decisions in order to mitigate seismic and tsunami risk. This was a Mexican government initiative headed by CENAPRED (National Disaster Prevention Center) who made an effort to integrated academic institutions and civil agencies to work together through a collaboration agreement. This network is supported by Universidad National Autónoma de México (UNAM) and its seismic networks (Broad Band and Strong Motion), the Centro de Instrumentación y Registro Sismico (CIRES) with its Earthquake Early Warning System that covers the Guerrero Gap and Oaxaca earthquakes, The Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE) with the support of its expertise in tsunami observation and the Secretaria de Marina (SEMAR) to monitor the sea level and operate the Mexican Tsunami Warning Center. The institutions involved in this scope have the compromise to interchange and share the data and advice to the Civil Protection authorities.

Adapting ElarmS Earthquake Early Warnings for Cascadia: Development and Testing of ShakeAlerts in the Pacific Northwest

NASA Astrophysics Data System (ADS)

Hartog, J. R.; Kress, V. C.; Thomas, T.; Malone, S. D.; Henson, I. H.; Neuhauser, D. S.

2013-12-01

As a first step in establishing an earthquake early warning system in Cascadia, we have installed the ElarmS component of the ShakeAlert system at the Pacific Northwest Seismic Network. In Cascadia our initial focus is primarily on the development of a seismo-geodetic-based real-time finite fault rupture algorithm to detect and characterize a large plate-boundary rupture in progress (see Crowell et. al., this session). In this regard the goal of the purely seismic-data-based ElarmS implementation is to 'trigger' the finite fault rupture algorithm. At the same time, however, the Cascadian ElarmS will also produce warnings for smaller onshore crustal earthquakes. While warnings from these smaller and closer earthquakes will provide shorter warning times for communities, and for less dramatic earthquakes, we intend to use them for educational purposes, and to coordinate with our regional and collaborating partners. They will also help to guide us to shorten data latencies and learn where additional instrumentation is most needed to increase performance. The accuracy of ElarmS in Cascadia is another major concern, because the current ElarmS model presumes an initial focal depth for earthquakes of 8 km based on California experience, while in Cascadia earthquakes of major concern may be as deep as 50 km, and/or occur beyond the western fringe of the seismic network. To this purpose our testing protocol is aimed at determining what changes are required to ensure top performance of an ElarmS-based warning system in Cascadia. Because of Cascadia's relatively low seismicity rate, and the paucity of data from plate boundary earthquakes there of any size, we have prioritized the development of a test system. The test system permits us to: 1) replay segments of actual seismic waveform data recorded from the PNSN and contributing seismic network stations to represent both earthquakes and noise conditions, and 2) broadcast synthetic data into the system to simulate signals we anticipate from earthquakes for which we have no actual ground motion recordings. The test system lets us also simulate various error conditions (latent and/or out-of-sequence data, telemetry drop-outs, etc.) to explore how to protect the system from them. We have also been testing the ElarmS system on real-time seismic network data for about 6 months as of the time of writing of this abstract. Using 268 channels of streaming strong motion and broad-band data, the system has produced very few false alarms and generally performed well for earthquakes between about magnitudes 2.5 and 4.5. Warning times are shorter (and the 'blind zone' smaller) in parts of the network where station density is higher and/or telemetry more fleet. One significant problem we find is that the discriminant used in northern California to differentiate local earthquake signals from teleseisms often fails in Cascadia. We are working to produce a valid teleseism detector.

Earth Observations for Early Detection of Agricultural Drought: Contributions of the Famine Early Warning Systems Network (FEWS NET)

NASA Astrophysics Data System (ADS)

Budde, M. E.; Funk, C.; Husak, G. J.; Peterson, P.; Rowland, J.; Senay, G. B.; Verdin, J. P.

2016-12-01

The U.S. Geological Survey (USGS) has a long history of supporting the use of Earth observation data for food security monitoring through its role as an implementing partner of the Famine Early Warning Systems Network (FEWS NET) program. The use of remote sensing and crop modeling to address food security threats in the form of drought, floods, pests, and changing climatic regimes has been a core activity in monitoring FEWS NET countries. In recent years, it has become a requirement that FEWS NET apply monitoring and modeling frameworks at global scales to assess emerging crises in regions that FEWS NET does not traditionally monitor. USGS FEWS NET, in collaboration with the University of California, Santa Barbara, has developed a number of new global applications of satellite observations, derived products, and efficient tools for visualization and analyses to address these requirements. (1) A 35-year quasi-global (+/- 50 degrees latitude) time series of gridded rainfall estimates, the Climate Hazards Infrared Precipitation with Stations (CHIRPS) dataset, based on infrared satellite imagery and station observations. Data are available as 5-day (pentadal) accumulations at 0.05 degree spatial resolution. (2) Global actual evapotranspiration data based on application of the Simplified Surface Energy Balance (SSEB) model using 10-day MODIS Land Surface Temperature composites at 1-km resolution. (3) Production of global expedited MODIS (eMODIS) 10-day NDVI composites updated every 5 days. (4) Development of an updated Early Warning eXplorer (EWX) tool for data visualization, analysis, and sharing. (5) Creation of stand-alone tools for enhancement of gridded rainfall data and trend analyses. (6) Establishment of an agro-climatology analysis tool and knowledge base for more than 90 countries of interest to FEWS NET. In addition to these new products and tools, FEWS NET has partnered with the GEOGLAM community to develop a Crop Monitor for Early Warning (CM4EW) which brings together global expertise in agricultural monitoring to reach consensus on growing season status of "countries at risk". Such engagements will result in enhanced capabilities for extending our monitoring efforts globally.

Informing climate change adaptation with insights from famine early warning (Invited)

NASA Astrophysics Data System (ADS)

Funk, C. C.; Verdin, J. P.

2010-12-01

Famine early warning systems provide a unique viewpoint for understanding the implications of climate change on food security, identifying the locations and seasons where millions of food insecure people are dependent upon climate-sensitive agricultural systems. The Famine Early Warning Systems Network (FEWS NET) is a decision support system sponsored by the Office of Food for Peace of the U.S. Agency for International Development (USAID), which distributes over two billion dollars of food aid to more than 40 countries each year. FEWS NET identifies the times and places where food aid is required by the most climatically sensitive and consequently food insecure populations of the developing world. As result, FEWS NET has developed its own "climate service", implemented by USGS, NOAA, and NASA, to support its decision making processes. The foundation of this climate service is the monitoring of current growing conditions for early identification of agricultural drought that might impact food security. Since station networks are sparse in the countries monitored, FEWS NET has a tradition (dating back to 1985) of reliance on satellite remote sensing of vegetation and rainfall. In the last ten years, climate forecasts have become an additional tool for food security assessment, extending the early warning perspective to include expected agricultural outcomes for the season ahead. More recently, research has expanded to include detailed analyses of recent observed climate trends, combined with diagnostic ocean-atmosphere studies. These studies are then used to develop interpretations of GCM scenarios and their implications for future patterns of precipitation and temperature, revealing trends towards warmer/drier climate conditions and increases in the relative frequency of drought. In some regions, like Eastern Africa, such changes seem to be already occurring, with an associated increase in food insecurity. Sub-national analyses for Kenya, for example, point to the need for adaptation through improved agricultural practices, so that increased yields can offset the impacts of rising temperatures and declining rainfall. Future work will focus on assessing temperature-PET linkages, and evaluating pathways for agricultural development.

Building regional early flood warning systems by AI techniques

NASA Astrophysics Data System (ADS)

Chang, F. J.; Chang, L. C.; Amin, M. Z. B. M.

2017-12-01

Building early flood warning system is essential for the protection of the residents against flood hazards and make actions to mitigate the losses. This study implements AI technology for forecasting multi-step-ahead regional flood inundation maps during storm events. The methodology includes three major schemes: (1) configuring the self-organizing map (SOM) to categorize a large number of regional inundation maps into a meaningful topology; (2) building dynamic neural networks to forecast multi-step-ahead average inundated depths (AID); and (3) adjusting the weights of the selected neuron in the constructed SOM based on the forecasted AID to obtain real-time regional inundation maps. The proposed models are trained, and tested based on a large number of inundation data sets collected in regions with the most frequent and serious flooding in the river basin. The results appear that the SOM topological relationships between individual neurons and their neighbouring neurons are visible and clearly distinguishable, and the hybrid model can continuously provide multistep-ahead visible regional inundation maps with high resolution during storm events, which have relatively small RMSE values and high R2 as compared with numerical simulation data sets. The computing time is only few seconds, and thereby leads to real-time regional flood inundation forecasting and make early flood inundation warning system. We demonstrate that the proposed hybrid ANN-based model has a robust and reliable predictive ability and can be used for early warning to mitigate flood disasters.

A Mathematical Framework for Critical Transitions: Normal Forms, Variance and Applications

NASA Astrophysics Data System (ADS)

Kuehn, Christian

2013-06-01

Critical transitions occur in a wide variety of applications including mathematical biology, climate change, human physiology and economics. Therefore it is highly desirable to find early-warning signs. We show that it is possible to classify critical transitions by using bifurcation theory and normal forms in the singular limit. Based on this elementary classification, we analyze stochastic fluctuations and calculate scaling laws of the variance of stochastic sample paths near critical transitions for fast-subsystem bifurcations up to codimension two. The theory is applied to several models: the Stommel-Cessi box model for the thermohaline circulation from geoscience, an epidemic-spreading model on an adaptive network, an activator-inhibitor switch from systems biology, a predator-prey system from ecology and to the Euler buckling problem from classical mechanics. For the Stommel-Cessi model we compare different detrending techniques to calculate early-warning signs. In the epidemics model we show that link densities could be better variables for prediction than population densities. The activator-inhibitor switch demonstrates effects in three time-scale systems and points out that excitable cells and molecular units have information for subthreshold prediction. In the predator-prey model explosive population growth near a codimension-two bifurcation is investigated and we show that early-warnings from normal forms can be misleading in this context. In the biomechanical model we demonstrate that early-warning signs for buckling depend crucially on the control strategy near the instability which illustrates the effect of multiplicative noise.

Raingauge-Based Rainfall Nowcasting with Artificial Neural Network

NASA Astrophysics Data System (ADS)

Liong, Shie-Yui; He, Shan

2010-05-01

Rainfall forecasting and nowcasting are of great importance, for instance, in real-time flood early warning systems. Long term rainfall forecasting demands global climate, land, and sea data, thus, large computing power and storage capacity are required. Rainfall nowcasting's computing requirement, on the other hand, is much less. Rainfall nowcasting may use data captured by radar and/or weather stations. This paper presents the application of Artificial Neural Network (ANN) on rainfall nowcasting using data observed at weather and/or rainfall stations. The study focuses on the North-East monsoon period (December, January and February) in Singapore. Rainfall and weather data from ten stations, between 2000 and 2006, were selected and divided into three groups for training, over-fitting test and validation of the ANN. Several neural network architectures were tried in the study. Two architectures, Backpropagation ANN and Group Method of Data Handling ANN, yielded better rainfall nowcasting, up to two hours, than the other architectures. The obtained rainfall nowcasts were then used by a catchment model to forecast catchment runoff. The results of runoff forecast are encouraging and promising.With ANN's high computational speed, the proposed approach may be deliverable for creating the real-time flood early warning system.

Forecasting infectious disease emergence subject to seasonal forcing.

PubMed

Miller, Paige B; O'Dea, Eamon B; Rohani, Pejman; Drake, John M

2017-09-06

Despite high vaccination coverage, many childhood infections pose a growing threat to human populations. Accurate disease forecasting would be of tremendous value to public health. Forecasting disease emergence using early warning signals (EWS) is possible in non-seasonal models of infectious diseases. Here, we assessed whether EWS also anticipate disease emergence in seasonal models. We simulated the dynamics of an immunizing infectious pathogen approaching the tipping point to disease endemicity. To explore the effect of seasonality on the reliability of early warning statistics, we varied the amplitude of fluctuations around the average transmission. We proposed and analyzed two new early warning signals based on the wavelet spectrum. We measured the reliability of the early warning signals depending on the strength of their trend preceding the tipping point and then calculated the Area Under the Curve (AUC) statistic. Early warning signals were reliable when disease transmission was subject to seasonal forcing. Wavelet-based early warning signals were as reliable as other conventional early warning signals. We found that removing seasonal trends, prior to analysis, did not improve early warning statistics uniformly. Early warning signals anticipate the onset of critical transitions for infectious diseases which are subject to seasonal forcing. Wavelet-based early warning statistics can also be used to forecast infectious disease.

Detecting early signs of the 2007–2008 crisis in the world trade

PubMed Central

Saracco, Fabio; Di Clemente, Riccardo; Gabrielli, Andrea; Squartini, Tiziano

2016-01-01

Since 2007, several contributions have tried to identify early-warning signals of the financial crisis. However, the vast majority of analyses has focused on financial systems and little theoretical work has been done on the economic counterpart. In the present paper we fill this gap and employ the theoretical tools of network theory to shed light on the response of world trade to the financial crisis of 2007 and the economic recession of 2008–2009. We have explored the evolution of the bipartite World Trade Web (WTW) across the years 1995–2010, monitoring the behavior of the system both before and after 2007. Our analysis shows early structural changes in the WTW topology: since 2003, the WTW becomes increasingly compatible with the picture of a network where correlations between countries and products are progressively lost. Moreover, the WTW structural modification can be considered as concluded in 2010, after a seemingly stationary phase of three years. We have also refined our analysis by considering specific subsets of countries and products: the most statistically significant early-warning signals are provided by the most volatile macrosectors, especially when measured on developing countries, suggesting the emerging economies as being the most sensitive ones to the global economic cycles. PMID:27461469

Detecting early signs of the 2007-2008 crisis in the world trade.

PubMed

Saracco, Fabio; Di Clemente, Riccardo; Gabrielli, Andrea; Squartini, Tiziano

2016-07-27

Since 2007, several contributions have tried to identify early-warning signals of the financial crisis. However, the vast majority of analyses has focused on financial systems and little theoretical work has been done on the economic counterpart. In the present paper we fill this gap and employ the theoretical tools of network theory to shed light on the response of world trade to the financial crisis of 2007 and the economic recession of 2008-2009. We have explored the evolution of the bipartite World Trade Web (WTW) across the years 1995-2010, monitoring the behavior of the system both before and after 2007. Our analysis shows early structural changes in the WTW topology: since 2003, the WTW becomes increasingly compatible with the picture of a network where correlations between countries and products are progressively lost. Moreover, the WTW structural modification can be considered as concluded in 2010, after a seemingly stationary phase of three years. We have also refined our analysis by considering specific subsets of countries and products: the most statistically significant early-warning signals are provided by the most volatile macrosectors, especially when measured on developing countries, suggesting the emerging economies as being the most sensitive ones to the global economic cycles.

Detecting early signs of the 2007-2008 crisis in the world trade

NASA Astrophysics Data System (ADS)

Saracco, Fabio; di Clemente, Riccardo; Gabrielli, Andrea; Squartini, Tiziano

2016-07-01

Since 2007, several contributions have tried to identify early-warning signals of the financial crisis. However, the vast majority of analyses has focused on financial systems and little theoretical work has been done on the economic counterpart. In the present paper we fill this gap and employ the theoretical tools of network theory to shed light on the response of world trade to the financial crisis of 2007 and the economic recession of 2008-2009. We have explored the evolution of the bipartite World Trade Web (WTW) across the years 1995-2010, monitoring the behavior of the system both before and after 2007. Our analysis shows early structural changes in the WTW topology: since 2003, the WTW becomes increasingly compatible with the picture of a network where correlations between countries and products are progressively lost. Moreover, the WTW structural modification can be considered as concluded in 2010, after a seemingly stationary phase of three years. We have also refined our analysis by considering specific subsets of countries and products: the most statistically significant early-warning signals are provided by the most volatile macrosectors, especially when measured on developing countries, suggesting the emerging economies as being the most sensitive ones to the global economic cycles.

Enhanced early warning system impact on nursing practice: A phenomenological study.

PubMed

Burns, Kathleen A; Reber, Tracey; Theodore, Karen; Welch, Brenda; Roy, Debra; Siedlecki, Sandra L

2018-05-01

To determine how an enhanced early warning system has an impact on nursing practice. Early warning systems score physiologic measures and alert nurses to subtle changes in patient condition. Critics of early warning systems have expressed concern that nurses would rely on a score rather than assessment skills and critical thinking to determine the need for intervention. Enhancing early warning systems with innovative technology is still in its infancy, so the impact of an enhanced early warning system on nursing behaviours or practice has not yet been studied. Phenomenological design. Scripted, semistructured interviews were conducted in September 2015 with 25 medical/surgical nurses who used the enhanced early warning system. Data were analysed using thematic analysis techniques (coding and bracketing). Emerging themes were examined for relationships and a model describing the enhanced early warning system experience was developed. Nurses identified awareness leading to investigation and ease of prioritization as the enhanced early warning system's most important impact on their nursing practice. There was also an impact on organizational culture, with nurses reporting improved communication, increased collaboration, increased accountability and proactive responses to early changes in patient condition. Rather than hinder critical thinking, as many early warning systems' critics claim, nurses in this study found that the enhanced early warning system increased their awareness of changes in a patient's condition, resulting in earlier response and reassessment times. It also had an impact on the organization by improving communication and collaboration and supporting a culture of proactive rather than reactive response to early signs of deterioration. © 2017 John Wiley & Sons Ltd.

GPS water level measurements for Indonesia's Tsunami Early Warning System

NASA Astrophysics Data System (ADS)

Schöne, T.; Pandoe, W.; Mudita, I.; Roemer, S.; Illigner, J.; Zech, C.; Galas, R.

2011-03-01

On Boxing Day 2004, a severe tsunami was generated by a strong earthquake in Northern Sumatra causing a large number of casualties. At this time, neither an offshore buoy network was in place to measure tsunami waves, nor a system to disseminate tsunami warnings to local governmental entities. Since then, buoys have been developed by Indonesia and Germany, complemented by NOAA's Deep-ocean Assessment and Reporting of Tsunamis (DART) buoys, and have been moored offshore Sumatra and Java. The suite of sensors for offshore tsunami detection in Indonesia has been advanced by adding GPS technology for water level measurements. The usage of GPS buoys in tsunami warning systems is a relatively new approach. The concept of the German Indonesian Tsunami Early Warning System (GITEWS) (Rudloff et al., 2009) combines GPS technology and ocean bottom pressure (OBP) measurements. Especially for near-field installations where the seismic noise may deteriorate the OBP data, GPS-derived sea level heights provide additional information. The GPS buoy technology is precise enough to detect medium to large tsunamis of amplitudes larger than 10 cm. The analysis presented here suggests that for about 68% of the time, tsunamis larger than 5 cm may be detectable.

Agencies collaborate, develop a cyanobacteria assessment network

USGS Publications Warehouse

Schaeffer, Blake A.; Loftin, Keith A.; Stumpf, Richard P.; Werdell, P. Jeremy

2015-01-01

Satellite remote sensing tools may enable policy makers and environmental managers to assess the sustainability of watershed ecosystems and the services they provide, now and in the future. Satellite technology allows us to develop early-warning indicators of cyanobacteria blooms at the local scale while maintaining continuous national coverage.

Development of an early warning sensor and network for brown-\\0xAD\\0x2010out conditions.

DOT National Transportation Integrated Search

2016-03-31

Brownout conditions on motorways are caused by windblown dust and sand from upwind areas where : soils are susceptible to wind erosion. Owing in part to prolonged droughts that have dried : soils and denuded vegetation and biological crusts, large, m...

Collaborative Network Evolution: The Los Angeles Terrorism Early Warning Group

DTIC Science & Technology

2006-03-01

Organizational Diagnosis and Design (Boston: Kluwer Publishers, 1998), 166. 25 Burton and Obel, 165-189. 26 Hocevar, et al. 27 Robert Axelrod and Douglas Dion...Forces 53, No. 2 (Dec 74): 181-190. Burton, Richard & Borge Obel. Strategic Organizational Diagnosis and Design. Boston: Kluwer Publishers, 1998

How to Decide? Multi-Objective Early-Warning Monitoring Networks for Water Suppliers

NASA Astrophysics Data System (ADS)

Bode, Felix; Loschko, Matthias; Nowak, Wolfgang

2015-04-01

Groundwater is a resource for drinking water and hence needs to be protected from contaminations. However, many well catchments include an inventory of known and unknown risk sources, which cannot be eliminated, especially in urban regions. As a matter of risk control, all these risk sources should be monitored. A one-to-one monitoring situation for each risk source would lead to a cost explosion and is even impossible for unknown risk sources. However, smart optimization concepts could help to find promising low-cost monitoring network designs. In this work we develop a concept to plan monitoring networks using multi-objective optimization. Our considered objectives are to maximize the probability of detecting all contaminations, to enhance the early warning time before detected contaminations reach the drinking water well, and to minimize the installation and operating costs of the monitoring network. Using multi-objectives optimization, we avoid the problem of having to weight these objectives to a single objective-function. These objectives are clearly competing, and it is impossible to know their mutual trade-offs beforehand - each catchment differs in many points and it is hardly possible to transfer knowledge between geological formations and risk inventories. To make our optimization results more specific to the type of risk inventory in different catchments we do risk prioritization of all known risk sources. Due to the lack of the required data, quantitative risk ranking is impossible. Instead, we use a qualitative risk ranking to prioritize the known risk sources for monitoring. Additionally, we allow for the existence of unknown risk sources that are totally uncertain in location and in their inherent risk. Therefore, they can neither be located nor ranked. Instead, we represent them by a virtual line of risk sources surrounding the production well. We classify risk sources into four different categories: severe, medium and tolerable for known risk sources and an extra category for the unknown ones. With that, early warning time and detection probability become individual objectives for each risk class. Thus, decision makers can identify monitoring networks valid for controlling the top risk sources, and evaluate the capabilities (or search for least-cost upgrades) to also cover moderate, tolerable and unknown risk sources. Monitoring networks, which are valid for the remaining risk also cover all other risk sources, but only with a relatively poor early-warning time. The data provided for the optimization algorithm are calculated in a preprocessing step by a flow and transport model. It simulates, which potential contaminant plumes from the risk sources would be detectable where and when by all possible candidate positions for monitoring wells. Uncertainties due to hydro(geo)logical phenomena are taken into account by Monte-Carlo simulations. These include uncertainty in ambient flow direction of the groundwater, uncertainty of the conductivity field, and different scenarios for the pumping rates of the production wells. To avoid numerical dispersion during the transport simulations, we use particle-tracking random walk methods when simulating transport.

Real-time earthquake source imaging: An offline test for the 2011 Tohoku earthquake

NASA Astrophysics Data System (ADS)

Zhang, Yong; Wang, Rongjiang; Zschau, Jochen; Parolai, Stefano; Dahm, Torsten

2014-05-01

In recent decades, great efforts have been expended in real-time seismology aiming at earthquake and tsunami early warning. One of the most important issues is the real-time assessment of earthquake rupture processes using near-field seismogeodetic networks. Currently, earthquake early warning systems are mostly based on the rapid estimate of P-wave magnitude, which contains generally large uncertainties and the known saturation problem. In the case of the 2011 Mw9.0 Tohoku earthquake, JMA (Japan Meteorological Agency) released the first warning of the event with M7.2 after 25 s. The following updates of the magnitude even decreased to M6.3-6.6. Finally, the magnitude estimate stabilized at M8.1 after about two minutes. This led consequently to the underestimated tsunami heights. By using the newly developed Iterative Deconvolution and Stacking (IDS) method for automatic source imaging, we demonstrate an offline test for the real-time analysis of the strong-motion and GPS seismograms of the 2011 Tohoku earthquake. The results show that we had been theoretically able to image the complex rupture process of the 2011 Tohoku earthquake automatically soon after or even during the rupture process. In general, what had happened on the fault could be robustly imaged with a time delay of about 30 s by using either the strong-motion (KiK-net) or the GPS (GEONET) real-time data. This implies that the new real-time source imaging technique is helpful to reduce false and missing warnings, and therefore should play an important role in future tsunami early warning and earthquake rapid response systems.

The Earthquake Early Warning System in Japan (Invited)

NASA Astrophysics Data System (ADS)

Mori, J. J.; Yamada, M.

2010-12-01

In Japan, the earthquake early warning system (Kinkyu Jishin Sokuhou in Japanese) maintained by the Japan Meterological Agency (JMA) has been in operation and sending pubic information since October 1, 2007. Messages have been broadcast on television and radio to warn of strong shaking to the public. The threshold for broadcasting a message is an estimated intensity of JMA 5 lower, which is approximately equivalent to MM VII to VIII. During the period from October 2007 through August 2010, messages have been sent 9 times for earthquakes of magnitude 5.2 to 7.0. There have been a few instances of significantly over-estimating or under-estimating the predicted shaking, but in general the performance of the system has been quite good. The quality of the detection system depends on the dense network of high-quality seismometers that cover the Japanese Islands. Consequently, the system works very well for events on or close to the 4 main islands, but there is more uncertainty for events near the smaller and more distant islands where the density of instrumentation is much less The Early Warning System is also tied to an extensive education program so that the public can react appropriately in the short amount of time given by the warning. There appears to be good public support in Japan, where people have become accustomed to a high level of fast information on a daily basis. There has also been development of a number of specific safety applications in schools and industry that work off the backbone information provided in the national system.

Climate Change Implications and Use of Early Warning Systems for Global Dust Storms

NASA Astrophysics Data System (ADS)

Harriman, L.

2014-12-01

Increased changes in land cover and global climate have led to increased frequency and/or intensity of dust storms in some regions of the world. Early detection and warning of dust storms, in conjunction with effective and widespread information broadcasts, will be essential to the prevention and mitigation of future risks and impacts to people and the environment. Since frequency and intensity of dust storms can vary from region to region, there is a demonstrated need for more research to be conducted over longer periods of time to analyze trends of dust storm events [1]. Dust storms impact their origin area, but also land, water and people a great distance away from where dust finally settles [2, 3]. These transboundary movements and accompanying impacts further warrant the need for global collaboration to help predict the onset, duration and path of a dust storm. Early warning systems can help communicate when a dust storm is occurring, the projected intensity of the dust storm and its anticipated physical impact over a particular geographic area. Development of regional dust storm models, such as CUACE/Dust for East Asia, and monitoring networks, like the Sand and Dust Storm Warning Network operated by the World Meteorological Organization, and the use of remote sensing and satellite imagery derived products [4], including MODIS, are currently being incorporated into early warning and monitoring initiatives. However, to increase future certainty of impacts of dust storms on vulnerable populations and ecosystems, more research is needed to analyze the influences of human activities, seasonal variations and long-term climatic patterns on dust storm generation, movement and impact. Sources: [1] Goudie, A.S. (2009), Dust storms: recent developments, J Environ. Manage., 90. [2] Lee, H., and Liu, C. (2004), Coping with dust storm events: information, impacts, and policymaking in Taiwan, TAO, 15(5). [3] Marx, S.K., McGowan, H.A., and Balz, K.S. (2009), Long-range dust transport from eastern Australia: a proxy for Holocene aridity and ENSO-type climate variability, Earth Planet Sci. Lett., 282. [4] Kimura, R. (2012), Factors contributing to dust storms in source regions producing the yellow-sand phenomena observed in Japan from 1993 to 2002, J. Arid Environ. 80

The Role of North American Aerospace Defense Command (NORAD) In Military Cyber Attack Warning

DTIC Science & Technology

2015-09-01

WARNING MISSIONS .....................................5  1.  Early North American Air Defense Warning ...................................5  2...BLANK xi LIST OF FIGURES Figure 1.   North American Distant Early Warning (DEW) Site. .......................................6  Figure 2.   Original... Early Warning (AEW) Aircraft .........................................11  Figure 7.   Headquarters NORAD and USNORTHCOM

Tipping point analysis of seismological data

NASA Astrophysics Data System (ADS)

Livina, Valerie N.; Tolkova, Elena

2014-05-01

We apply the tipping point toolbox [1-7] to study sensor data of pressure variations and vertical velocity of the sea floor after two seismic events: 21 October 2010, M6.9, D10km (California) and 11 March 2011, M9.0, D30km (Japan). One type of datasets was measured by nano-resolution pressure sensor [8], while the other, for comparison, by a co-located ocean bottom seismometer. Both sensors registered the seismic wave, and we investigated the early warning and detection signals of the wave arrival for possible application with a remote and cabled tsunami warning detector network (NOAA DART system and Japan Trench Tsunami Observation System). We study the early warning and detection signals of the wave arrival using methodology that combines degenerate fingerprinting and potential analysis techniques for anticipation, detection and forecast of tipping points in a dynamical system. Degenerate fingerprinting indicator is a dynamically derived lag-1 autocorrelation, ACF (or, alternatively, short-range scaling exponent of Detrended Fluctuation Analysis, DFA [1]), which shows short-term memory in a series. When such values rise monotonically, this indicates an upcoming transition or bifurcation in a series and can be used for early warning signals analysis. The potential analysis detects a transition or bifurcation in a series at the time when it happens, which is illustrated in a special contour plot mapping the potential dynamics of the system [2-6]. The methodology has been extensively tested on artificial data and on various geophysical, ecological and industrial sensor datasets [2-5,7], and proved to be applicable to trajectories of dynamical systems of arbitrary origin [9]. In this seismological application, we have obtained early warning signals in the described series using ACF- and DFA-indicators and detected the Rayleigh wave arrival in the potential contour plots. In the case of the event in 2010, the early warning signal starts appearing about 2 min before the first peak of the Rayleigh train is detected by the sensor, whereas in the case of event of 2011, the early warning signal appears closer to the peak arrival, within 1 min. The different strength of early warning signals of the Rayleigh trains may be due to different depths of the events (10 and 30 km), which we plan to test in further analysis. References: [1] Livina and Lenton, GRL 2007; [2] Livina et al, Climate of the Past 2010; [3] Livina et al, Climate Dynamics 2011; [4] Livina et al, Physica A 2012; [5] Livina and Lenton, Cryosphere 2013; [6] Livina et al, Physica A 2013; [7] Livina et al, Journal of Civil Structural Health Monitoring, in press; [8] Tolkova and Schaad, arXiv:1401.0096v1; [9] Vaz Martins et al, PRE 2010.

Hybrid Intrusion Forecasting Framework for Early Warning System

NASA Astrophysics Data System (ADS)

Kim, Sehun; Shin, Seong-Jun; Kim, Hyunwoo; Kwon, Ki Hoon; Han, Younggoo

Recently, cyber attacks have become a serious hindrance to the stability of Internet. These attacks exploit interconnectivity of networks, propagate in an instant, and have become more sophisticated and evolutionary. Traditional Internet security systems such as firewalls, IDS and IPS are limited in terms of detecting recent cyber attacks in advance as these systems respond to Internet attacks only after the attacks inflict serious damage. In this paper, we propose a hybrid intrusion forecasting system framework for an early warning system. The proposed system utilizes three types of forecasting methods: time-series analysis, probabilistic modeling, and data mining method. By combining these methods, it is possible to take advantage of the forecasting technique of each while overcoming their drawbacks. Experimental results show that the hybrid intrusion forecasting method outperforms each of three forecasting methods.

Evaluating the Use of Remote Sensing Data in the USAID Famine Early Warning Systems Network

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Brickley, Elizabeth B.

2011-01-01

The US Agency for International Development (USAID) s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. Here we analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000-2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices and food access parameters in their analysis of food security problems. The reports display large scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data was used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10%, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

Geo-Spatial Social Network Analysis of Social Media to Mitigate Disasters

NASA Astrophysics Data System (ADS)

Carley, K. M.

2017-12-01

Understanding the spatial layout of human activity can afford a better understanding many phenomena - such as local cultural, the spread of ideas, and the scope of a disaster. Today, social media is one of the key sensors for acquiring information on socio-cultural activity, some with cues as to the geo-location. We ask, What can be learned by putting such data on maps? For example, are people who chat on line more likely to be near each other? Can Twitter data support disaster planning or early warning? In this talk, such issues are examined using data collected via Twitter and analyzed using ORA. ORA is a network analysis and visualization system. It supports not just social networks (who is interacting with whom), but also high dimensional networks with many types of nodes (e.g. people, organizations, resources, activities …) and relations, geo-spatial network analysis, dynamic network analysis, & geo-temporal analysis. Using ORA lessons learned from five case studies are considered: Arab Spring, Tsunami warning in Padang Indonesia, Twitter around Fukushima in Japan, Typhoon Haiyan (Yolanda), & regional conflict. Using Padang Indonesia data, we characterize the strengths and limitations of social media data to support disaster planning & early warning, identify at risk areas & issues of concern, and estimate where people are and which areas are impacted. Using Fukushima Japanese data, social media is used to estimate geo-spatial regularities in movement and communication that can inform disaster response and risk estimation. Using Arab Spring data, we find that the spread of bots & extremists varies by country and time, to the extent that using twitter to understand who is important or what ideas are critical can be compromised. Bots and extremists can exploit disaster messaging to create havoc and facilitate criminal activity e.g. human trafficking. Event discovery mechanisms support isolating geo-epi-centers for key events become crucial. Spatial inference enables improved country, and city identification. Geo-network analytics with and without these inferences reveal that explicitly geo-tagged data may not be representative and that improved location estimation provides better insight into the social condition. These results demonstrate the value of these technique to mitigate the social impact of disasters.

Prevention of Targeted School Violence by Responding to Students' Psychosocial Crises: The NETWASS Program

ERIC Educational Resources Information Center

Leuschner, Vincenz; Fiedler, Nora; Schultze, Martin; Ahlig, Nadine; Göbel, Kristin; Sommer, Friederike; Scholl, Johanna; Cornell, Dewey; Scheithauer, Herbert

2017-01-01

The standardized, indicated school-based prevention program "Networks Against School Shootings" combines a threat assessment approach with a general model of prevention of emergency situations in schools through early intervention in student psychosocial crises and training teachers to recognize warning signs of targeted school violence.…

Dynamical predictors of an imminent phenotypic switch in bacteria

NASA Astrophysics Data System (ADS)

Wang, Huijing; Ray, J. Christian J.

2017-08-01

Single cells can stochastically switch across thresholds imposed by regulatory networks. Such thresholds can act as a tipping point, drastically changing global phenotypic states. In ecology and economics, imminent transitions across such tipping points can be predicted using dynamical early warning indicators. A typical example is ‘flickering’ of a fast variable, predicting a longer-lasting switch from a low to a high state or vice versa. Considering the different timescales between metabolite and protein fluctuations in bacteria, we hypothesized that metabolic early warning indicators predict imminent transitions across a network threshold caused by enzyme saturation. We used stochastic simulations to determine if flickering predicts phenotypic transitions, accounting for a variety of molecular physiological parameters, including enzyme affinity, burstiness of enzyme gene expression, homeostatic feedback, and rates of metabolic precursor influx. In most cases, we found that metabolic flickering rates are robustly peaked near the enzyme saturation threshold. The degree of fluctuation was amplified by product inhibition of the enzyme. We conclude that sensitivity to flickering in fast variables may be a possible natural or synthetic strategy to prepare physiological states for an imminent transition.

Exploring the feasibility of a nationwide earthquake early warning system in Italy

NASA Astrophysics Data System (ADS)

Picozzi, M.; Zollo, A.; Brondi, P.; Colombelli, S.; Elia, L.; Martino, C.

2015-04-01

When accompanied by appropriate training and preparedness of a population, Earthquake Early Warning Systems (EEWS) are effective and viable tools for the real-time reduction of societal exposure to seismic events in metropolitan areas. The Italian Accelerometric Network, RAN, which consists of about 500 stations installed over all the active seismic zones, as well as many cities and strategic infrastructures in Italy, has the potential to serve as a nationwide early warning system. In this work, we present a feasibility study for a nationwide EEWS in Italy obtained by the integration of the RAN and the software platform PRobabilistic and Evolutionary early warning SysTem (PRESTo). The performance of the RAN-PRESTo EEWS is first assessed by testing it on real strong motion recordings of 40 of the largest earthquakes that have occurred during the last 10 years in Italy. Furthermore, we extend the analysis to regions that did not experience earthquakes by considering a nationwide grid of synthetic sources capable of generating Gutenberg-Richter sequences corresponding to the one adopted by the seismic hazard map of the Italian territory. Our results indicate that the RAN-PRESTo EEWS could theoretically provide for higher seismic hazard areas reliable alert messages within about 5 to 10 s and maximum lead times of about 25 s. In case of large events (M > 6.5), this amount of lead time would be sufficient for taking basic protective measures (e.g., duck and cover, move away from windows or equipment) in tens to hundreds of municipalities affected by large ground shaking.

Early Warning and Outbreak Detection Using Social Networking Websites: The Potential of Twitter

NASA Astrophysics Data System (ADS)

de Quincey, Ed; Kostkova, Patty

Epidemic Intelligence is being used to gather information about potential diseases outbreaks from both formal and increasingly informal sources. A potential addition to these informal sources are social networking sites such as Facebook and Twitter. In this paper we describe a method for extracting messages, called "tweets" from the Twitter website and the results of a pilot study which collected over 135,000 tweets in a week during the current Swine Flu pandemic.

Neural Network Classifies Teleoperation Data

NASA Technical Reports Server (NTRS)

Fiorini, Paolo; Giancaspro, Antonio; Losito, Sergio; Pasquariello, Guido

1994-01-01

Prototype artificial neural network, implemented in software, identifies phases of telemanipulator tasks in real time by analyzing feedback signals from force sensors on manipulator hand. Prototype is early, subsystem-level product of continuing effort to develop automated system that assists in training and supervising human control operator: provides symbolic feedback (e.g., warnings of impending collisions or evaluations of performance) to operator in real time during successive executions of same task. Also simplifies transition between teleoperation and autonomous modes of telerobotic system.

Safety Early Warning Research for Highway Construction Based on Case-Based Reasoning and Variable Fuzzy Sets

PubMed Central

Liu, Yan; Xu, Zhen-Jun

2013-01-01

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods' effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established. PMID:24191134

Safety early warning research for highway construction based on case-based reasoning and variable fuzzy sets.

PubMed

Liu, Yan; Yi, Ting-Hua; Xu, Zhen-Jun

2013-01-01

As a high-risk subindustry involved in construction projects, highway construction safety has experienced major developments in the past 20 years, mainly due to the lack of safe early warnings in Chinese construction projects. By combining the current state of early warning technology with the requirements of the State Administration of Work Safety and using case-based reasoning (CBR), this paper expounds on the concept and flow of highway construction safety early warnings based on CBR. The present study provides solutions to three key issues, index selection, accident cause association analysis, and warning degree forecasting implementation, through the use of association rule mining, support vector machine classifiers, and variable fuzzy qualitative and quantitative change criterion modes, which fully cover the needs of safe early warning systems. Using a detailed description of the principles and advantages of each method and by proving the methods' effectiveness and ability to act together in safe early warning applications, effective means and intelligent technology for a safe highway construction early warning system are established.

Study on Early-Warning System of Cotton Production in Hebei Province

NASA Astrophysics Data System (ADS)

Zhang, Runqing; Ma, Teng

Cotton production plays an important role in Hebei. It straightly influences cotton farmers’ life, agricultural production and national economic development as well. In recent years, due to cotton production frequently fluctuating, two situations, “difficult selling cotton” and “difficult buying cotton” have alternately occurred, and brought disadvantages to producers, businesses and national finance. Therefore, it is very crucial to research the early warning of cotton production for solving the problem of cotton production’s frequent fluctuation and ensuring the cotton industry’s sustainable development. This paper founds a signal lamp model of early warning through employing time-difference correlation analysis method to select early-warning indicators and statistical analysis method associated with empirical analysis to determine early-warning limits. Finally, it not only obtained warning conditions of cotton production from 1993 to 2006 and forecast 2007’s condition, but also put forward corresponding countermeasures to prevent cotton production from fluctuating. Furthermore, an early-warning software of cotton production is completed through computer programming on the basis of the early warning model above.

A new, ultra-low latency data transmission protocol for Earthquake Early Warning Systems

NASA Astrophysics Data System (ADS)

Hill, P.; Hicks, S. P.; McGowan, M.

2016-12-01

One measure used to assess the performance of Earthquake Early Warning Systems (EEWS) is the delay time between earthquake origin and issued alert. EEWS latency is dependent on a number of sources (e.g. P-wave propagation, digitisation, transmission, receiver processing, triggering, event declaration). Many regional seismic networks use the SEEDlink protocol; however, packet size is fixed to 512-byte miniSEED records, resulting in transmission latencies of >0.5 s. Data packetisation is seen as one of the main sources of delays in EEWS (Brown et al., 2011). Optimising data-logger and telemetry configurations is a cost-effective strategy to improve EEWS alert times (Behr et al., 2015). Digitisers with smaller, selectable packets can result in faster alerts (Sokos et al., 2016). We propose a new seismic protocol for regional seismic networks benefiting low-latency applications such as EEWS. The protocol, based on Güralp's existing GDI-link format is an efficient and flexible method to exchange data between seismic stations and data centers for a range of network configurations. The main principle is to stream data sample-by-sample instead of fixed-length packets to minimise transmission latency. Self-adaptive packetisation with compression maximises available telemetry bandwidth. Highly flexible metadata fields within GDI-link are compatible with existing miniSEED definitions. Data is sent as integers or floats, supporting a wide range of data formats, including discrete parameters such as Pd & τC for on-site earthquake early warning. Other advantages include: streaming station state-of-health information, instrument control, support of backfilling and fail-over strategies during telemetry outages. Based on tests carried out on the Güralp Minimus data-logger, we show our new protocol can reduce transmission latency to as low as 1 ms. The low-latency protocol is currently being implemented with common processing packages. The results of these tests will help to highlight latency levels that can be achieved with next-generation EEWS.

Detection of severe respiratory disease epidemic outbreaks by CUSUM-based overcrowd-severe-respiratory-disease-index model.

PubMed

Polanco, Carlos; Castañón-González, Jorge Alberto; Macías, Alejandro E; Samaniego, José Lino; Buhse, Thomas; Villanueva-Martínez, Sebastián

2013-01-01

A severe respiratory disease epidemic outbreak correlates with a high demand of specific supplies and specialized personnel to hold it back in a wide region or set of regions; these supplies would be beds, storage areas, hemodynamic monitors, and mechanical ventilators, as well as physicians, respiratory technicians, and specialized nurses. We describe an online cumulative sum based model named Overcrowd-Severe-Respiratory-Disease-Index based on the Modified Overcrowd Index that simultaneously monitors and informs the demand of those supplies and personnel in a healthcare network generating early warnings of severe respiratory disease epidemic outbreaks through the interpretation of such variables. A post hoc historical archive is generated, helping physicians in charge to improve the transit and future allocation of supplies in the entire hospital network during the outbreak. The model was thoroughly verified in a virtual scenario, generating multiple epidemic outbreaks in a 6-year span for a 13-hospital network. When it was superimposed over the H1N1 influenza outbreak census (2008-2010) taken by the National Institute of Medical Sciences and Nutrition Salvador Zubiran in Mexico City, it showed that it is an effective algorithm to notify early warnings of severe respiratory disease epidemic outbreaks with a minimal rate of false alerts.

Detection of Severe Respiratory Disease Epidemic Outbreaks by CUSUM-Based Overcrowd-Severe-Respiratory-Disease-Index Model

PubMed Central

Castañón-González, Jorge Alberto; Macías, Alejandro E.; Samaniego, José Lino; Buhse, Thomas; Villanueva-Martínez, Sebastián

2013-01-01

A severe respiratory disease epidemic outbreak correlates with a high demand of specific supplies and specialized personnel to hold it back in a wide region or set of regions; these supplies would be beds, storage areas, hemodynamic monitors, and mechanical ventilators, as well as physicians, respiratory technicians, and specialized nurses. We describe an online cumulative sum based model named Overcrowd-Severe-Respiratory-Disease-Index based on the Modified Overcrowd Index that simultaneously monitors and informs the demand of those supplies and personnel in a healthcare network generating early warnings of severe respiratory disease epidemic outbreaks through the interpretation of such variables. A post hoc historical archive is generated, helping physicians in charge to improve the transit and future allocation of supplies in the entire hospital network during the outbreak. The model was thoroughly verified in a virtual scenario, generating multiple epidemic outbreaks in a 6-year span for a 13-hospital network. When it was superimposed over the H1N1 influenza outbreak census (2008–2010) taken by the National Institute of Medical Sciences and Nutrition Salvador Zubiran in Mexico City, it showed that it is an effective algorithm to notify early warnings of severe respiratory disease epidemic outbreaks with a minimal rate of false alerts. PMID:24069063

Implementing Obstetric Early Warning Systems.

PubMed

Friedman, Alexander M; Campbell, Mary L; Kline, Carolyn R; Wiesner, Suzanne; D'Alton, Mary E; Shields, Laurence E

2018-04-01

Severe maternal morbidity and mortality are often preventable and obstetric early warning systems that alert care providers of potential impending critical illness may improve maternal safety. While literature on outcomes and test characteristics of maternal early warning systems is evolving, there is limited guidance on implementation. Given current interest in early warning systems and their potential role in care, the 2017 Society for Maternal-Fetal Medicine (SMFM) Annual Meeting dedicated a session to exploring early warning implementation across a wide range of hospital settings. This manuscript reports on key points from this session. While implementation experiences varied based on factors specific to individual sites, common themes relevant to all hospitals presenting were identified. Successful implementation of early warnings systems requires administrative and leadership support, dedication of resources, improved coordination between nurses, providers, and ancillary staff, optimization of information technology, effective education, evaluation of and change in hospital culture and practices, and support in provider decision-making. Evolving data on outcomes on early warning systems suggest that maternal risk may be reduced. To effectively reduce maternal, risk early warning systems that capture deterioration from a broad range of conditions may be required in addition to bundles tailored to specific conditions such as hemorrhage, thromboembolism, and hypertension.

Knowledge of stroke risk factors and early warning signs of stroke among students enrolled in allied health programs: a pilot study.

PubMed

Milner, Abby; Lewis, William J; Ellis, Charles

2008-01-01

The inclusion of stroke education modules early in medical school curricula has resulted in improved stroke knowledge in graduate physicians. The success of these programs suggests that allied health professions programs should also consider strategies to improve stroke knowledge in students preparing for allied health careers that also require knowledge of stroke risk factors and early warning signs. Currently, little is known about stroke knowledge in students enrolled in allied health professions programs. 208 first- and second-year students enrolled in allied health programs completed a survey of stroke risk factors and early warning signs of stroke. Risk factor knowledge - 99% identified smoking as a risk factor; 67% identified diabetes; 93% identified high cholesterol; 89% identified age; and 92% identified physical inactivity. Less than 50% of the students identified all 5 risk factors. There were no differences between first- and second-year students in risk factor knowledge. Early warning signs and first response knowledge - 89% recognized sudden confusion or trouble speaking; 94% recognized sudden facial, arm, or leg weakness; 65% recognized sudden vision loss; 82% recognized sudden trouble walking; and 73% recognized sudden headache as early warning signs of stroke. Eighty-one percent recognized calling 9-1-1 as the appropriate first action. However, only 25% recognized all five early warning signs and only 20% recognized all five early warning signs and would call 9-1-1 as the first action. There were differences between first- and second-year students in recognizing 3 of 5 early warning signs and appropriate first action to call 9-1-1. Most students recognized individual stroke risk factors and early warning signs but few recognized multiple risk factors and early warning signs of stroke.

CISN ShakeAlert: Using early warnings for earthquakes in California

NASA Astrophysics Data System (ADS)

Vinci, M.; Hellweg, M.; Jones, L. M.; Khainovski, O.; Schwartz, K.; Lehrer, D.; Allen, R. M.; Neuhauser, D. S.

2009-12-01

Educated users who have developed response plans and procedures are just as important for an earthquake early warning (EEW) system as are the algorithms and computers that process the data and produce the warnings. In Japan, for example, the implementation of the EEW system which now provides advanced alerts of ground shaking included intense outreach efforts to both institutional and individual recipients. Alerts are now used in automatic control systems that stop trains, place sensitive equipment in safe mode and isolate hazards while the public takes cover. In California, the California Integrated Seismic Network (CISN) is now developing and implementing components of a prototype system for EEW, ShakeAlert. As this processing system is developed, we invite a suite of perspective users from critical industries and institutions throughout California to partner with us in developing useful ShakeAlert products and procedures. At the same time, we will support their efforts to determine and implement appropriate responses to an early warning of earthquake shaking. As a first step, in a collaboration with BART, we have developed a basic system allowing BART’s operation center to receive realtime ground shaking information from more than 150 seismic stations operating in the San Francisco Bay Area. BART engineers are implementing a display system for this information. Later phases will include the development of improved response procedures utilizing this information. We plan to continue this collaboration to include more sophisticated information from the prototype CISN ShakeAlert system.

Feasibility Study of Earthquake Early Warning in Hawai`i For the Mauna Kea Thirty Meter Telescope

NASA Astrophysics Data System (ADS)

Okubo, P.; Hotovec-Ellis, A. J.; Thelen, W. A.; Bodin, P.; Vidale, J. E.

2014-12-01

Earthquakes, including large damaging events, are as central to the geologic evolution of the Island of Hawai`i as its more famous volcanic eruptions and lava flows. Increasing and expanding development of facilities and infrastructure on the island continues to increase exposure and risk associated with strong ground shaking resulting from future large local earthquakes. Damaging earthquakes over the last fifty years have shaken the most heavily developed areas and critical infrastructure of the island to levels corresponding to at least Modified Mercalli Intensity VII. Hawai`i's most recent damaging earthquakes, the M6.7 Kiholo Bay and M6.0 Mahukona earthquakes, struck within seven minutes of one another off of the northwest coast of the island in October 2006. These earthquakes resulted in damage at all thirteen of the telescopes near the summit of Mauna Kea that led to gaps in telescope operations ranging from days up to four months. With the experiences of 2006 and Hawai`i's history of damaging earthquakes, we have begun a study to explore the feasibility of implementing earthquake early warning systems to provide advanced warnings to the Thirty Meter Telescope of imminent strong ground shaking from future local earthquakes. One of the major challenges for earthquake early warning in Hawai`i is the variety of earthquake sources, from shallow crustal faults to deeper mantle sources, including the basal decollement separating the volcanic pile from the ancient oceanic crust. Infrastructure on the Island of Hawai`i may only be tens of kilometers from these sources, allowing warning times of only 20 s or less. We assess the capability of the current seismic network to produce alerts for major historic earthquakes, and we will provide recommendations for upgrades to improve performance.

Machine Learning Seismic Wave Discrimination: Application to Earthquake Early Warning

NASA Astrophysics Data System (ADS)

Li, Zefeng; Meier, Men-Andrin; Hauksson, Egill; Zhan, Zhongwen; Andrews, Jennifer

2018-05-01

Performance of earthquake early warning systems suffers from false alerts caused by local impulsive noise from natural or anthropogenic sources. To mitigate this problem, we train a generative adversarial network (GAN) to learn the characteristics of first-arrival earthquake P waves, using 300,000 waveforms recorded in southern California and Japan. We apply the GAN critic as an automatic feature extractor and train a Random Forest classifier with about 700,000 earthquake and noise waveforms. We show that the discriminator can recognize 99.2% of the earthquake P waves and 98.4% of the noise signals. This state-of-the-art performance is expected to reduce significantly the number of false triggers from local impulsive noise. Our study demonstrates that GANs can discover a compact and effective representation of seismic waves, which has the potential for wide applications in seismology.

Design and internal validation of an obstetric early warning score: secondary analysis of the Intensive Care National Audit and Research Centre Case Mix Programme database.

PubMed

Carle, C; Alexander, P; Columb, M; Johal, J

2013-04-01

We designed and internally validated an aggregate weighted early warning scoring system specific to the obstetric population that has the potential for use in the ward environment. Direct obstetric admissions from the Intensive Care National Audit and Research Centre's Case Mix Programme Database were randomly allocated to model development (n = 2240) or validation (n = 2200) sets. Physiological variables collected during the first 24 h of critical care admission were analysed. Logistic regression analysis for mortality in the model development set was initially used to create a statistically based early warning score. The statistical score was then modified to create a clinically acceptable early warning score. Important features of this clinical obstetric early warning score are that the variables are weighted according to their statistical importance, a surrogate for the FI O2 /Pa O2 relationship is included, conscious level is assessed using a simplified alert/not alert variable, and the score, trigger thresholds and response are consistent with the new non-obstetric National Early Warning Score system. The statistical and clinical early warning scores were internally validated using the validation set. The area under the receiver operating characteristic curve was 0.995 (95% CI 0.992-0.998) for the statistical score and 0.957 (95% CI 0.923-0.991) for the clinical score. Pre-existing empirically designed early warning scores were also validated in the same way for comparison. The area under the receiver operating characteristic curve was 0.955 (95% CI 0.922-0.988) for Swanton et al.'s Modified Early Obstetric Warning System, 0.937 (95% CI 0.884-0.991) for the obstetric early warning score suggested in the 2003-2005 Report on Confidential Enquiries into Maternal Deaths in the UK, and 0.973 (95% CI 0.957-0.989) for the non-obstetric National Early Warning Score. This highlights that the new clinical obstetric early warning score has an excellent ability to discriminate survivors from non-survivors in this critical care data set. Further work is needed to validate our new clinical early warning score externally in the obstetric ward environment. Anaesthesia © 2013 The Association of Anaesthetists of Great Britain and Ireland.

Earthquake Early Warning: New Strategies for Seismic Hardware

NASA Astrophysics Data System (ADS)

Allardice, S.; Hill, P.

2017-12-01

Implementing Earthquake Early Warning System (EEWS) triggering algorithms into seismic networks has been a hot topic of discussion for some years now. With digitizer technology now available, such as the Güralp Minimus, with on average 40-60ms delay time (latency) from earthquake origin to issuing an alert the next step is to provide network operators with a simple interface for on board parameter calculations from a seismic station. A voting mechanism is implemented on board which mitigates the risk of false positives being communicated. Each Minimus can be configured to with a `score' from various sources i.e. Z channel on seismometer, N/S E/W channels on accelerometer and MEMS inside Minimus. If the score exceeds the set threshold then an alert is sent to the `Master Minimus'. The Master Minimus within the network will also be configured as to when the alert should be issued i.e. at least 3 stations must have triggered. Industry standard algorithms focus around the calculation of Peak Ground Acceleration (PGA), Peak Ground Velocity (PGV), Peak Ground Displacement (PGD) and C. Calculating these single station parameters on-board in order to stream only the results could help network operators with possible issues, such as restricted bandwidth. Developments on the Minimus allow these parameters to be calculated and distributed through Common Alert Protocol (CAP). CAP is the XML based data format used for exchanging and describing public warnings and emergencies. Whenever the trigger conditions are met the Minimus can send a signed UDP packet to the configured CAP receiver which can then send the alert via SMS, e-mail or CAP forwarding. Increasing network redundancy is also a consideration when developing these features, therefore the forwarding CAP message can be sent to multiple destinations. This allows for a hierarchical approach by which the single station (or network) parameters can be streamed to another Minimus, or data centre, or both, so that there is no one single point of failure. Developments on the Guralp Minimus to calculate these on board parameters which are capable of streaming single station parameters, accompanied with the ultra-low latency is the next generation of EEWS and Güralps contribution to the community.

Early Warning System Implementation Guide: For Use with the National High School Center's Early Warning System Tool v2.0

ERIC Educational Resources Information Center

Therriault, Susan Bowles; Heppen, Jessica; O'Cummings, Mindee; Fryer, Lindsay; Johnson, Amy

2010-01-01

This Early Warning System (EWS) Implementation Guide is a supporting document for schools and districts that are implementing the National High School Center's Early Warning System (EWS) Tool v2.0. Developed by the National High School Center at the American Institutes for Research (AIR), the guide and tool support the establishment and…

MACROINVERTEBRATE INVENTORIES OF THE WHITE RIVER, COLORADO AND UTAH: SIGNIFICANCE OF ANNUAL, SEASONAL, AND SPATIAL VARIATION IN THE DESIGN OF BIOMONITORING NETWORKS FOR POLLUTION DETECTION

EPA Science Inventory

An aquatic macroinvertebrate monitoring program is suggested for 'early warning' detection of toxic discharges to streams in oil shale development areas. Changes in stream biota are used to signal need for increasing levels of chemical analyses to identify and quantify toxic poll...

CISN ShakeAlert: Faster Warning Information Through Multiple Threshold Event Detection in the Virtual Seismologist (VS) Early Warning Algorithm

NASA Astrophysics Data System (ADS)

Cua, G. B.; Fischer, M.; Caprio, M.; Heaton, T. H.; Cisn Earthquake Early Warning Project Team

2010-12-01

The Virtual Seismologist (VS) earthquake early warning (EEW) algorithm is one of 3 EEW approaches being incorporated into the California Integrated Seismic Network (CISN) ShakeAlert system, a prototype EEW system that could potentially be implemented in California. The VS algorithm, implemented by the Swiss Seismological Service at ETH Zurich, is a Bayesian approach to EEW, wherein the most probable source estimate at any given time is a combination of contributions from a likehihood function that evolves in response to incoming data from the on-going earthquake, and selected prior information, which can include factors such as network topology, the Gutenberg-Richter relationship or previously observed seismicity. The VS codes have been running in real-time at the Southern California Seismic Network since July 2008, and at the Northern California Seismic Network since February 2009. We discuss recent enhancements to the VS EEW algorithm that are being integrated into CISN ShakeAlert. We developed and continue to test a multiple-threshold event detection scheme, which uses different association / location approaches depending on the peak amplitudes associated with an incoming P pick. With this scheme, an event with sufficiently high initial amplitudes can be declared on the basis of a single station, maximizing warning times for damaging events for which EEW is most relevant. Smaller, non-damaging events, which will have lower initial amplitudes, will require more picks to initiate an event declaration, with the goal of reducing false alarms. This transforms the VS codes from a regional EEW approach reliant on traditional location estimation (and the requirement of at least 4 picks as implemented by the Binder Earthworm phase associator) into an on-site/regional approach capable of providing a continuously evolving stream of EEW information starting from the first P-detection. Real-time and offline analysis on Swiss and California waveform datasets indicate that the multiple-threshold approach is faster and more reliable for larger events than the earlier version of the VS codes. In addition, we provide evolutionary estimates of the probability of false alarms (PFA), which is an envisioned output stream of the CISN ShakeAlert system. The real-time decision-making approach envisioned for CISN ShakeAlert users, where users specify a threshhold PFA in addition to thresholds on peak ground motion estimates, has the potential to increase the available warning time for users with high tolerance to false alarms without compromising the needs of users with lower tolerances to false alarms.

Application of the Risk-Based Early Warning Method in a Fracture-Karst Water Source, North China.

PubMed

Guo, Yongli; Wu, Qing; Li, Changsuo; Zhao, Zhenhua; Sun, Bin; He, Shiyi; Jiang, Guanghui; Zhai, Yuanzheng; Guo, Fang

2018-03-01

  The paper proposes a risk-based early warning considering characteristics of fracture-karst aquifer in North China and applied it in a super-large fracture-karst water source. Groundwater vulnerability, types of land use, water abundance, transmissivity and spatial temporal variation of groundwater quality were chosen as indexes of the method. Weights of factors were obtained by using AHP method based on relative importance of factors, maps of factors were zoned by GIS, early warning map was conducted based on extension theory with the help of GIS, ENVI+IDL. The early warning map fused five factors very well, serious and tremendous warning areas are mainly located in northwest and east with high or relatively high transmissivity and groundwater pollutant loading, and obviously deteriorated or deteriorated trend of petroleum. The early warning map warns people where more attention should be paid, and the paper guides decision making to take appropriate protection actions in different warning levels areas.

Data Delivery Latency Improvements And First Steps Towards The Distributed Computing Of The Caltech/USGS Southern California Seismic Network Earthquake Early Warning System

NASA Astrophysics Data System (ADS)

Stubailo, I.; Watkins, M.; Devora, A.; Bhadha, R. J.; Hauksson, E.; Thomas, V. I.

2016-12-01

The USGS/Caltech Southern California Seismic Network (SCSN) is a modern digital ground motion seismic network. It develops and maintains Earthquake Early Warning (EEW) data collection and delivery systems in southern California as well as real-time EEW algorithms. Recently, Behr et al., SRL, 2016 analyzed data from several regional seismic networks deployed around the globe. They showed that the SCSN was the network with the smallest data communication delays or latency. Since then, we have reduced further the telemetry delays for many of the 330 current sites. The latency has been reduced on average from 2-6 sec to 0.4 seconds by tuning the datalogger parameters and/or deploying software upgrades. Recognizing the latency data as one of the crucial parameters in EEW, we have started archiving the per-packet latencies in mseed format for all the participating sites in a similar way it is traditionally done for the seismic waveform data. The archived latency values enable us to understand and document long-term changes in performance of the telemetry links. We can also retroactively investigate how latent the waveform data were during a specific event or during a specific time period. In addition the near-real time latency values are useful for monitoring and displaying the real-time station latency, in particular to compare different telemetry technologies. A future step to reduce the latency is to deploy the algorithms on the dataloggers at the seismic stations and transmit either the final solutions or intermediate parameters to a central processing center. To implement this approach, we are developing a stand-alone version of the OnSite algorithm to run on the dataloggers in the field. This will increase the resiliency of the SCSN to potential telemetry restrictions in the immediate aftermath of a large earthquake, either by allowing local alarming by the single station, or permitting transmission of lightweight parametric information rather than continuous waveform data to the central processing facility. State-of-the-art development of Internet of Things (IoT) tools and platforms, which can be used to distribute and maintain software on a large number of remote devices are making this approach to earthquake early warning more feasible.

Real-time earthquake monitoring: Early warning and rapid response

NASA Technical Reports Server (NTRS)

1991-01-01

A panel was established to investigate the subject of real-time earthquake monitoring (RTEM) and suggest recommendations on the feasibility of using a real-time earthquake warning system to mitigate earthquake damage in regions of the United States. The findings of the investigation and the related recommendations are described in this report. A brief review of existing real-time seismic systems is presented with particular emphasis given to the current California seismic networks. Specific applications of a real-time monitoring system are discussed along with issues related to system deployment and technical feasibility. In addition, several non-technical considerations are addressed including cost-benefit analysis, public perceptions, safety, and liability.

Evaluating the Use of Remote Sensing Data in the U.S. Agency for International Development Famine Early Warning Systems Network

NASA Technical Reports Server (NTRS)

Brown, Molly Elizabeth; Brickley, Elizabeth B

2012-01-01

The U.S. Agency for International Development (USAID)'s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods, and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. We analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000 to 2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices, and food access parameters in their analysis of food security problems. The reports display large-scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data were used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10% of the time, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

Introduction of Drought Monitoring and Forecasting System based on Real-time Water Information Using ICT

NASA Astrophysics Data System (ADS)

Lee, Y., II; Kim, H. S.; Chun, G.

2016-12-01

There were severe damages such as restriction on water supply caused by continuous drought from 2014 to 2015 in South Korea. Through this drought event, government of South Korea decided to establish National Drought Information Analysis Center in K-water(Korea Water Resources Corporation) and introduce a national drought monitoring and early warning system to mitigate those damages. Drought index such as SPI(Standard Precipitation Index), PDSI(Palmer Drought Severity Index) and SMI(Soil Moisture Index) etc. have been developed and are widely used to provide drought information in many countries. However, drought indexes are not appropriate for drought monitoring and early warning in civilized countries with high population density such as South Korea because it could not consider complicated water supply network. For the national drought monitoring and forecasting of South Korea, `Drought Information Analysis System' (D.I.A.S) which is based on the real time data(storage, flowrate, waterlevel etc.) was developed. Based on its advanced methodology, `DIAS' is changing the paradigm of drought monitoring and early warning systems. Because `D.I.A.S' contains the information of water supply network from water sources to the people across the nation and provides drought information considering the real-time hydrological conditions of each and every water source. For instance, in case the water level of a specific dam declines to predetermined level of caution, `D.I.A.S' will notify people who uses the dam as a source of residential or industrial water. It is expected to provide credible drought monitoring and forecasting information with a strong relationship between drought information and the feelings of people rely on water users by `D.I.A.S'.

Assessing the performance of regional landslide early warning models: the EDuMaP method

NASA Astrophysics Data System (ADS)

Calvello, M.; Piciullo, L.

2016-01-01

A schematic of the components of regional early warning systems for rainfall-induced landslides is herein proposed, based on a clear distinction between warning models and warning systems. According to this framework an early warning system comprises a warning model as well as a monitoring and warning strategy, a communication strategy and an emergency plan. The paper proposes the evaluation of regional landslide warning models by means of an original approach, called the "event, duration matrix, performance" (EDuMaP) method, comprising three successive steps: identification and analysis of the events, i.e., landslide events and warning events derived from available landslides and warnings databases; definition and computation of a duration matrix, whose elements report the time associated with the occurrence of landslide events in relation to the occurrence of warning events, in their respective classes; evaluation of the early warning model performance by means of performance criteria and indicators applied to the duration matrix. During the first step the analyst identifies and classifies the landslide and warning events, according to their spatial and temporal characteristics, by means of a number of model parameters. In the second step, the analyst computes a time-based duration matrix with a number of rows and columns equal to the number of classes defined for the warning and landslide events, respectively. In the third step, the analyst computes a series of model performance indicators derived from a set of performance criteria, which need to be defined by considering, once again, the features of the warning model. The applicability, potentialities and limitations of the EDuMaP method are tested and discussed using real landslides and warning data from the municipal early warning system operating in Rio de Janeiro (Brazil).

Putting Man in the Machine: Exploiting Expertise to Enhance Multiobjective Design of Water Supply Monitoring Network

NASA Astrophysics Data System (ADS)

Bode, F.; Nowak, W.; Reed, P. M.; Reuschen, S.

2016-12-01

Drinking-water well catchments need effective early-warning monitoring networks. Groundwater water supply wells in complex urban environments are in close proximity to a myriad of potential industrial pollutant sources that could irreversibly damage their source aquifers. These urban environments pose fiscal and physical challenges to designing monitoring networks. Ideal early-warning monitoring networks would satisfy three objectives: to detect (1) all potential contaminations within the catchment (2) as early as possible before they reach the pumping wells, (3) while minimizing costs. Obviously, the ideal case is nonexistent, so we search for tradeoffs using multiobjective optimization. The challenge of this optimization problem is the high number of potential monitoring-well positions (the search space) and the non-linearity of the underlying groundwater flow-and-transport problem. This study evaluates (1) different ways to effectively restrict the search space in an efficient way, with and without expert knowledge, (2) different methods to represent the search space during the optimization and (3) the influence of incremental increases in uncertainty in the system. Conductivity, regional flow direction and potential source locations are explored as key uncertainties. We show the need and the benefit of our methods by comparing optimized monitoring networks for different uncertainty levels with networks that seek to effectively exploit expert knowledge. The study's main contributions are the different approaches restricting and representing the search space. The restriction algorithms are based on a point-wise comparison of decision elements of the search space. The representation of the search space can be either binary or continuous. For both cases, the search space must be adjusted properly. Our results show the benefits and drawbacks of binary versus continuous search space representations and the high potential of automated search space restriction algorithms for high-dimensional, highly non-linear optimization problems.

Examining the value of global seasonal reference evapotranspiration forecasts to support FEWS NET’s food insecurity outlooks

USGS Publications Warehouse

Shukla, Shraddhanand; McEvoy, Daniel; Hobbins, Michael; Husak, Gregory; Huntington, Justin; Funk, Chris; Macharia, Denis; Verdin, James P.

2017-01-01

The Famine Early Warning Systems Network (FEWS NET) team provides food insecurity outlooks for several developing countries in Africa, Central Asia, and Central America. This study describes development of a new global reference evapotranspiration (ETo) seasonal reforecast and skill evaluation with a particular emphasis on the potential use of this dataset by the FEWS NET to support food insecurity early warning. The ETo reforecasts span the 1982-2009 period and are calculated following ASCE’s formulation of Penman-Monteith method driven by seasonal climate forecasts of monthly mean temperature, humidity, wind speed, and solar radiation from NCEP’s CFSv2 and NASA’s GEOS-5 models. The skill evaluation using deterministic and probabilistic scores, focuses on the December-February (DJF), March-May (MAM), June-August (JJA) and September-November (SON) seasons. The results indicate that ETo forecasts are a promising tool for early warning of drought and food insecurity. Globally, the regions where forecasts are most skillful (correlation >0.35 at lead-2) include Western U.S., northern parts of South America, parts of Sahel region and Southern Africa. The FEWS NET regions where forecasts are most skillful (correlation >0.35 at lead-3) include Northern Sub-Saharan Africa (DJF, dry season), Central America (DJF, dry season), parts of East Africa (JJA, wet Season), Southern Africa (JJA, dry season), and Central Asia (MAM, wet season). A case study over parts of East Africa for the JJA season shows that ETo forecasts in combination with the precipitation forecasts could have provided early warning of recent severe drought events (e.g., 2002, 2004, 2009) that contributed to substantial food insecurity in the region.

New early warning system for gravity-driven ruptures based on codetection of acoustic signal

NASA Astrophysics Data System (ADS)

Faillettaz, J.

2016-12-01

Gravity-driven rupture phenomena in natural media - e.g. landslide, rockfalls, snow or ice avalanches - represent an important class of natural hazards in mountainous regions. To protect the population against such events, a timely evacuation often constitutes the only effective way to secure the potentially endangered area. However, reliable prediction of imminence of such failure events remains challenging due to the nonlinear and complex nature of geological material failure hampered by inherent heterogeneity, unknown initial mechanical state, and complex load application (rainfall, temperature, etc.). Here, a simple method for real-time early warning that considers both the heterogeneity of natural media and characteristics of acoustic emissions attenuation is proposed. This new method capitalizes on codetection of elastic waves emanating from microcracks by multiple and spatially separated sensors. Event-codetection is considered as surrogate for large event size with more frequent codetected events (i.e., detected concurrently on more than one sensor) marking imminence of catastrophic failure. Simple numerical model based on a Fiber Bundle Model considering signal attenuation and hypothetical arrays of sensors confirms the early warning potential of codetection principles. Results suggest that although statistical properties of attenuated signal amplitude could lead to misleading results, monitoring the emergence of large events announcing impeding failure is possible even with attenuated signals depending on sensor network geometry and detection threshold. Preliminary application of the proposed method to acoustic emissions during failure of snow samples has confirmed the potential use of codetection as indicator for imminent failure at lab scale. The applicability of such simple and cheap early warning system is now investigated at a larger scale (hillslope). First results of such a pilot field experiment are presented and analysed.

Examining the value of global seasonal reference evapotranspiration forecasts tosupport FEWS NET's food insecurity outlooks

NASA Astrophysics Data System (ADS)

Shukla, S.; McEvoy, D.; Hobbins, M.; Husak, G. J.; Huntington, J. L.; Funk, C.; Verdin, J.; Macharia, D.

2017-12-01

The Famine Early Warning Systems Network (FEWS NET) team provides food insecurity outlooks for several developing countries in Africa, Central Asia, and Central America. Thus far in terms of agroclimatic conditions that influence food insecurity, FEWS NET's primary focus has been on the seasonal precipitation forecasts while not adequately accounting for the atmospheric evaporative demand, which is also directly related to agricultural production and hence food insecurity, and is most often estimated by reference evapotranspiration (ETo). This presentation reports on the development of a new global ETo seasonal reforecast and skill evaluation with a particular emphasis on the potential use of this dataset by the FEWS NET to support food insecurity early warning. The ETo reforecasts span the 1982-2009 period and are calculated following ASCE's formulation of Penman-Monteith method driven by seasonal climate forecasts of monthly mean temperature, humidity, wind speed, and solar radiation from NCEP's CFSv2 and NASA's GEOS-5 models. The skill evaluation using deterministic and probabilistic scores focuses on the December-February (DJF), March-May (MAM), June-August (JJA) and September-November (SON) seasons. The results indicate that ETo forecasts are a promising tool for early warning of drought and food insecurity. The FEWS NET regions with promising level of skill (correlation >0.35 at lead times of 3 months) include Northern Sub-Saharan Africa (DJF, dry season), Central America (DJF, dry season), parts of East Africa (JJA, wet Season), Southern Africa (JJA, dry season), and Central Asia (MAM, wet season). A case study over parts of East Africa for the JJA season shows that, in combination with the precipitation forecasts, ETo forecasts could have provided early warning of recent severe drought events (e.g., 2002, 2004, 2009) that contributed to substantial food insecurity in the region.

Ballistic Missile Early Warning System Clear Air Force Station, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Ballistic Missile Early Warning System - Clear Air Force Station, Ballistic Missile Early Warning System Site II, One mile west of mile marker 293.5 on Parks Highway, 5 miles southwest of Anderson, Anderson, Denali Borough, AK

A proposed Primary Health Early Warning Score (PHEWS) with emphasis on early detection of sepsis in the elderly.

PubMed

Anderson, Ian

2016-03-01

There are several secondary care early warning scores which alert for severe illness including sepsis. None are specifically adjusted for primary care. A Primary Health Early Warning Score (PHEWS) is proposed which incorporates practical parameters from both secondary and primary care.

Estimation for aerial detection effectiveness with cooperation efficiency factors of early-warning aircraft in early-warning detection SoS under BSC framework

NASA Astrophysics Data System (ADS)

Zhu, Feng; Hu, Xiaofeng; He, Xiaoyuan; Guo, Rui; Li, Kaiming; Yang, Lu

2017-11-01

In the military field, the performance evaluation of early-warning aircraft deployment or construction is always an important problem needing to be explored. As an effective approach of enterprise management and performance evaluation, Balanced Score Card (BSC) attracts more and more attentions and is studied more and more widely all over the world. It can also bring feasible ideas and technical approaches for studying the issue of the performance evaluation of the deployment or construction of early-warning aircraft which is the important component in early-warning detection system of systems (SoS). Therefore, the deep explored researches are carried out based on the previously research works. On the basis of the characteristics of space exploration and aerial detection effectiveness of early-warning detection SoS and the cardinal principle of BSC are analyzed simply, and the performance evaluation framework of the deployment or construction of early-warning aircraft is given, under this framework, aimed at the evaluation issue of aerial detection effectiveness of early-warning detection SoS with the cooperation efficiency factors of the early-warning aircraft and other land based radars, the evaluation indexes are further designed and the relative evaluation model is further established, especially the evaluation radar chart being also drawn to obtain the evaluation results from a direct sight angle. Finally, some practical computer simulations are launched to prove the validity and feasibility of the research thinking and technologic approaches which are proposed in the paper.

People-centred landslide early warning systems in the context of risk management

NASA Astrophysics Data System (ADS)

Haß, S.; Asch, K.; Fernandez-Steeger, T.; Arnhardt, C.

2009-04-01

In the current hazard research people-centred warning becomes more and more important, because different types of organizations and groups have to be involved in the warning process. This fact has to be taken into account when developing early warning systems. The effectiveness of early warning depends not only on technical capabilities but also on the preparedness of decision makers and their immediate response on how to act in case of emergency. Hence early warning systems have to be regarded in the context of an integrated and holistic risk management. Disaster Risk Reduction (DRR) measures include people-centred, timely and understandable warning. Further responsible authorities have to be identified in advance and standards for risk communication have to be established. Up to now, hazard and risk assessment for geohazards focuses on the development of inventory, susceptibility, hazard and risk maps. But often, especially in Europe, there are no institutional structures for managing geohazards and in addition there is a lack of an authority that is legally obliged to alarm on landslides at national or regional level. One of the main characteristics within the warning process for natural hazards e.g. in Germany is the split of responsibility between scientific authorities (wissenschaftliche Fachbehörde) and enforcement authorities (Vollzugsbehörde). The scientific authority provides the experts who define the methods and measures for monitoring and evaluate the hazard level. The main focus is the acquisition and evaluation of data and subsequently the distribution of information. The enforcement authority issues official warnings about dangerous natural phenomena. Hence the information chain in the context of early warning ranges over two different institutions, the forecast service and the warning service. But there doesn't exist a framework for warning processes in terms of landslides as yet. The concept for managing natural disasters is often reduced to hazard assessment and emergency response. Great importance is attached to the scientific understanding of hazards and protective structures, while analysis of socio-economic impacts and risk assessment are not considered enough. The reduction of vulnerability has to be taken into greater account. Also the information needs of different stakeholders have to be identified at an early stage and should be integrated in the development of early warning systems. The content of the warning message must be simple, understandable and should cover instructions on how to react. Further the timeliness of the messages has to be guarented. In this context the aim of the landslide monitoring and early warning system SLEWS (Sensor Based Landslide Early Warning System) is to integrate the above mentioned aspects of a holistic disaster and risk management. The technology of spatial data infrastructures and web services provides the use of multiple communication channels within an early warning system. Thus people-centred early warning messages and information about slope stability can be sent in nearly real-time. It has to be underlined that the technological information process is just one element of an effective warning system. Moreover the warning system has also to be considered as a social system and has to make allowance to socio-economic and gender aspects : «[...] Develop early warning systems that are people centered, in particular systems whose warnings are timely and understandable to those at risk, which take into account the demographic, gender, cultural and livelihood characteristics of the target audiences, including guidance on how to act upon warnings, and that support effective operations by disaster managers and other decision makers » (Hyogo Framework, 2005) References : UNITED NATIONS INTERNATIONAL STRATEGY FOR DISASTER REDUCTION SECRETARIAT (UNISDR) (2006): Developing early warning systems: a checklist, Third international conference on early warning (EWC III): from concept to action: 27-29 March 2006, Bonn, Germany. Geneva, Switzerland: International Strategy for Disaster Reduction. WORLD CONFERENCE ON DISASTER REDUCTION (2005) : Report of the World Conference on Disaster Reduction: Kobe, Hyogo, Japan, 18-22 January 2005. Geneva, Switzerland, Secretariat, World Conference on Disaster Reduction. INTER-AGENCY SECRETARIAT OF THE ISDR & GLOBAL PLATFORM FOR DISASTER RISK REDUCTION (2007): Disaster risk reduction: 2007 global review. Geneva, UN, ISDR.

Alaskan Air Defense and Early Warning Systems Clear Air ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Alaskan Air Defense and Early Warning Systems - Clear Air Force Station, Ballistic Missile Early Warning System Site II, One mile west of mile marker 293.5 on Parks Highway, 5 miles southwest of Anderson, Anderson, Denali Borough, AK

Assessing the performance of regional landslide early warning models: the EDuMaP method

NASA Astrophysics Data System (ADS)

Calvello, M.; Piciullo, L.

2015-10-01

The paper proposes the evaluation of the technical performance of a regional landslide early warning system by means of an original approach, called EDuMaP method, comprising three successive steps: identification and analysis of the Events (E), i.e. landslide events and warning events derived from available landslides and warnings databases; definition and computation of a Duration Matrix (DuMa), whose elements report the time associated with the occurrence of landslide events in relation to the occurrence of warning events, in their respective classes; evaluation of the early warning model Performance (P) by means of performance criteria and indicators applied to the duration matrix. During the first step, the analyst takes into account the features of the warning model by means of ten input parameters, which are used to identify and classify landslide and warning events according to their spatial and temporal characteristics. In the second step, the analyst computes a time-based duration matrix having a number of rows and columns equal to the number of classes defined for the warning and landslide events, respectively. In the third step, the analyst computes a series of model performance indicators derived from a set of performance criteria, which need to be defined by considering, once again, the features of the warning model. The proposed method is based on a framework clearly distinguishing between local and regional landslide early warning systems as well as among correlation laws, warning models and warning systems. The applicability, potentialities and limitations of the EDuMaP method are tested and discussed using real landslides and warnings data from the municipal early warning system operating in Rio de Janeiro (Brazil).

Application of τc*Pd for identifying damaging earthquakes for earthquake early warning

NASA Astrophysics Data System (ADS)

Huang, P. L.; Lin, T. L.; Wu, Y. M.

2014-12-01

Earthquake Early Warning System (EEWS) is an effective approach to mitigate earthquake damage. In this study, we used the seismic record by the Kiban Kyoshin network (KiK-net), because it has dense station coverage and co-located borehole strong-motion seismometers along with the free-surface strong-motion seismometers. We used inland earthquakes with moment magnitude (Mw) from 5.0 to 7.3 between 1998 and 2012. We choose 135 events and 10950 strong ground accelerograms recorded by the 696 strong ground accelerographs. Both the free-surface and the borehole data are used to calculate τc and Pd, respectively. The results show that τc*Pd has a good correlation with PGV and is a robust parameter for assessing the potential of damaging earthquake. We propose the value of τc*Pd determined from seconds after the arrival of P wave could be a threshold for the on-site type of EEW.

A possible space-based tsunami early warning system using observations of the tsunami ionospheric hole.

PubMed

Kamogawa, Masashi; Orihara, Yoshiaki; Tsurudome, Chiaki; Tomida, Yuto; Kanaya, Tatsuya; Ikeda, Daiki; Gusman, Aditya Riadi; Kakinami, Yoshihiro; Liu, Jann-Yenq; Toyoda, Atsushi

2016-12-01

Ionospheric plasma disturbances after a large tsunami can be detected by measurement of the total electron content (TEC) between a Global Positioning System (GPS) satellite and its ground-based receivers. TEC depression lasting for a few minutes to tens of minutes termed as tsunami ionospheric hole (TIH) is formed above the tsunami source area. Here we describe the quantitative relationship between initial tsunami height and the TEC depression rate caused by a TIH from seven tsunamigenic earthquakes in Japan and Chile. We found that the percentage of TEC depression and initial tsunami height are correlated and the largest TEC depressions appear 10 to 20 minutes after the main shocks. Our findings imply that Ionospheric TEC measurement using the existing ground receiver networks could be used in an early warning system for near-field tsunamis that take more than 20 minutes to arrive in coastal areas.

A possible space-based tsunami early warning system using observations of the tsunami ionospheric hole

PubMed Central

Kamogawa, Masashi; Orihara, Yoshiaki; Tsurudome, Chiaki; Tomida, Yuto; Kanaya, Tatsuya; Ikeda, Daiki; Gusman, Aditya Riadi; Kakinami, Yoshihiro; Liu, Jann-Yenq; Toyoda, Atsushi

2016-01-01

Ionospheric plasma disturbances after a large tsunami can be detected by measurement of the total electron content (TEC) between a Global Positioning System (GPS) satellite and its ground-based receivers. TEC depression lasting for a few minutes to tens of minutes termed as tsunami ionospheric hole (TIH) is formed above the tsunami source area. Here we describe the quantitative relationship between initial tsunami height and the TEC depression rate caused by a TIH from seven tsunamigenic earthquakes in Japan and Chile. We found that the percentage of TEC depression and initial tsunami height are correlated and the largest TEC depressions appear 10 to 20 minutes after the main shocks. Our findings imply that Ionospheric TEC measurement using the existing ground receiver networks could be used in an early warning system for near-field tsunamis that take more than 20 minutes to arrive in coastal areas. PMID:27905487

The impact of the disease early warning system in responding to natural disasters and conflict crises in Pakistan.

PubMed

Rahim, M; Kazi, B M; Bile, K M; Munir, M; Khan, A R

2010-01-01

The disease early warning system (DEWS) was introduced in the immediate aftermath of the 2005 earthquake in Pakistan, with the objective to undertake prompt investigation and mitigation of disease outbreaks. The DEWS network was replicated successfully during subsequent flood and earthquake disasters as well as during the 2008-09 internally displaced persons' crisis. DEWS-generated alerts, prompt investigations and timely responses had an effective contribution to the control of epidemics. Through DEWS, 1360 reported alerts during 2005-09 averted the risk of disease outbreaks through pre-emptive necessary measures, while the 187 confirmed outbreaks were effectively controlled. In the aftermath of the disasters, DEWS technology also facilitated the development of a disease-surveillance system that became an integral part of the district health system. This study aims to report the DEWS success and substantiate its lead role as a priority emergency health response intervention.

The Global Public Health Intelligence Network and early warning outbreak detection: a Canadian contribution to global public health.

PubMed

Mykhalovskiy, Eric; Weir, Lorna

2006-01-01

The recent SARS epidemic has renewed widespread concerns about the global transmission of infectious diseases. In this commentary, we explore novel approaches to global infectious disease surveillance through a focus on an important Canadian contribution to the area--the Global Public Health Intelligence Network (GPHIN). GPHIN is a cutting-edge initiative that draws on the capacity of the Internet and newly available 24/7 global news coverage of health events to create a unique form of early warning outbreak detection. This commentary outlines the operation and development of GPHIN and compares it to ProMED-mail, another Internet-based approach to global health surveillance. We argue that GPHIN has created an important shift in the relationship of public health and news information. By exiting the pyramid of official reporting, GPHIN has created a new monitoring technique that has disrupted national boundaries of outbreak notification, while creating new possibilities for global outbreak response. By incorporating news within the emerging apparatus of global infectious disease surveillance, GPHIN has effectively responded to the global media's challenge to official country reporting of outbreak and enhanced the effectiveness and credibility of international public health.

Evaluating the Real-time and Offline Performance of the Virtual Seismologist Earthquake Early Warning Algorithm

NASA Astrophysics Data System (ADS)

Cua, G.; Fischer, M.; Heaton, T.; Wiemer, S.

2009-04-01

The Virtual Seismologist (VS) algorithm is a Bayesian approach to regional, network-based earthquake early warning (EEW). Bayes' theorem as applied in the VS algorithm states that the most probable source estimates at any given time is a combination of contributions from relatively static prior information that does not change over the timescale of earthquake rupture and a likelihood function that evolves with time to take into account incoming pick and amplitude observations from the on-going earthquake. Potentially useful types of prior information include network topology or station health status, regional hazard maps, earthquake forecasts, and the Gutenberg-Richter magnitude-frequency relationship. The VS codes provide magnitude and location estimates once picks are available at 4 stations; these source estimates are subsequently updated each second. The algorithm predicts the geographical distribution of peak ground acceleration and velocity using the estimated magnitude and location and appropriate ground motion prediction equations; the peak ground motion estimates are also updated each second. Implementation of the VS algorithm in California and Switzerland is funded by the Seismic Early Warning for Europe (SAFER) project. The VS method is one of three EEW algorithms whose real-time performance is being evaluated and tested by the California Integrated Seismic Network (CISN) EEW project. A crucial component of operational EEW algorithms is the ability to distinguish between noise and earthquake-related signals in real-time. We discuss various empirical approaches that allow the VS algorithm to operate in the presence of noise. Real-time operation of the VS codes at the Southern California Seismic Network (SCSN) began in July 2008. On average, the VS algorithm provides initial magnitude, location, origin time, and ground motion distribution estimates within 17 seconds of the earthquake origin time. These initial estimate times are dominated by the time for 4 acceptable picks to be available, and thus are heavily influenced by the station density in a given region; these initial estimate times also include the effects of telemetry delay, which ranges between 6 and 15 seconds at the SCSN, and processing time (~1 second). Other relevant performance statistics include: 95% of initial real-time location estimates are within 20 km of the actual epicenter, 97% of initial real-time magnitude estimates are within one magnitude unit of the network magnitude. Extension of real-time VS operations to networks in Northern California is an on-going effort. In Switzerland, the VS codes have been run on offline waveform data from over 125 earthquakes recorded by the Swiss Digital Seismic Network (SDSN) and the Swiss Strong Motion Network (SSMS). We discuss the performance of the VS algorithm on these datasets in terms of magnitude, location, and ground motion estimation.

The Promise and Challenges of High Rate GNSS for Environmental Monitoring and Response

NASA Astrophysics Data System (ADS)

LaBrecque, John

2017-04-01

The decadal vision Global Geodetic Observing System recognizes the potential of high rate real time GNSS for environmental monitoring. The GGOS initiated a program to advance GNSS real time high rate measurements to augment seismic and other sensor systems for earthquake and tsunami early warning. High rate multi-GNSS networks can provide ionospheric tomography for the detection and tracking of land, ocean and atmospheric gravity waves that can provide coastal warning of tsunamis induced by earthquakes, volcanic eruptions, severe weather and other catastrophic events. NASA has collaborated on a microsatellite constellation of GPS receivers to measure ocean surface roughness to improve severe storm tracking and a equatorial system of GPS occultation receivers to measure ionospheric and atmospheric dynamics. Systems such as these will be significantly enhanced by the availability of a four fold increase in GNSS satellite systems with new and enhanced signal structures and by the densification of regional multi-GNSS networks. These new GNSS capabilities will rely upon improved and cost effective communications infrastructure for a network of coordinated real time analysis centers with input to national warning systems. Most important, the implementation of these new real time GNSS capabilities will rely upon the broad international support for the sharing of real time GNSS much as is done in weather and seismic observing systems and as supported by the Committee of Experts on UN Global Geodetic Information Management (UNGGIM).

The effectiveness of physiologically based early warning or track and trigger systems after triage in adult patients presenting to emergency departments: a systematic review.

PubMed

Wuytack, Francesca; Meskell, Pauline; Conway, Aislinn; McDaid, Fiona; Santesso, Nancy; Hickey, Fergal G; Gillespie, Paddy; Raymakers, Adam J N; Smith, Valerie; Devane, Declan

2017-12-06

Changes to physiological parameters precede deterioration of ill patients. Early warning and track and trigger systems (TTS) use routine physiological measurements with pre-specified thresholds to identify deteriorating patients and trigger appropriate and timely escalation of care. Patients presenting to the emergency department (ED) are undiagnosed, undifferentiated and of varying acuity, yet the effectiveness and cost-effectiveness of using early warning systems and TTS in this setting is unclear. We aimed to systematically review the evidence on the use, development/validation, clinical effectiveness and cost-effectiveness of physiologically based early warning systems and TTS for the detection of deterioration in adult patients presenting to EDs. We searched for any study design in scientific databases and grey literature resources up to March 2016. Two reviewers independently screened results and conducted quality assessment. One reviewer extracted data with independent verification of 50% by a second reviewer. Only information available in English was included. Due to the heterogeneity of reporting across studies, results were synthesised narratively and in evidence tables. We identified 6397 citations of which 47 studies and 1 clinical trial registration were included. Although early warning systems are increasingly used in EDs, compliance varies. One non-randomised controlled trial found that using an early warning system in the ED may lead to a change in patient management but may not reduce adverse events; however, this is uncertain, considering the very low quality of evidence. Twenty-eight different early warning systems were developed/validated in 36 studies. There is relatively good evidence on the predictive ability of certain early warning systems on mortality and ICU/hospital admission. No health economic data were identified. Early warning systems seem to predict adverse outcomes in adult patients of varying acuity presenting to the ED but there is a lack of high quality comparative studies to examine the effect of using early warning systems on patient outcomes. Such studies should include health economics assessments.

Development of an advanced radioactive airborne particle monitoring system for use in early warning networks.

PubMed

Baeza, A; Corbacho, J A; Caballero, J M; Ontalba, M A; Vasco, J; Valencia, D

2017-09-25

Automatic real-time warning networks are essential for the almost immediate detection of anomalous levels of radioactivity in the environment. In the case of Extremadura region (SW Spain), a radiological network (RARE) has been operational in the vicinity of the Almaraz nuclear power plant and in other areas farther away since 1992. There are ten air monitoring stations equipped with Geiger-Müller counters in order to evaluate the external ambient gamma dose rate. Four of these stations have a commercial system that provides estimates of the total artificial alpha and beta activity concentrations in aerosols, and of the 131 I activity (gaseous fraction). Despite experience having demonstrated the benefits and robustness of these commercial systems, important improvements have been made to one of these air monitoring systems. In this paper, the analytical and maintenance shortcomings of the original commercial air monitoring system are described first; the new custom-designed advanced air monitoring system is then presented. This system is based mainly on the incorporation of gamma spectrometry using two scintillation detectors, one of NaI:Tl and the other of LaBr 3 :Ce, and compact multichannel analysers. Next, a comparison made of the results provided by the two systems operating simultaneously at the same location for three months shows the advantages of the new advanced air monitoring system. As a result, the gamma spectrometry analysis allows passing from global alpha and beta activity determinations due to artificial radionuclides in aerosols, and the inaccurate measurement of the gaseous 131 I activity concentration, to the possibility of identifying a large number of radionuclides and quantifying each of their activity concentrations. Moreover, the new station's dual capacity is designed to work in early warning monitoring mode and surveillance monitoring mode. This is based on custom developed software that includes an intelligent system to issue the necessary warnings when radiological anomalies or technical problems are identified. Implicitly, for the construction of the advanced station, substantial mechanical and electronic developments have been required. They have essentially consisted of integrating a new replacement device, whose operation has reduced the maintenance tasks.

Using a neural network approach and time series data from an international monitoring station in the Yellow Sea for modeling marine ecosystems.

PubMed

Zhang, Yingying; Wang, Juncheng; Vorontsov, A M; Hou, Guangli; Nikanorova, M N; Wang, Hongliang

2014-01-01

The international marine ecological safety monitoring demonstration station in the Yellow Sea was developed as a collaborative project between China and Russia. It is a nonprofit technical workstation designed as a facility for marine scientific research for public welfare. By undertaking long-term monitoring of the marine environment and automatic data collection, this station will provide valuable information for marine ecological protection and disaster prevention and reduction. The results of some initial research by scientists at the research station into predictive modeling of marine ecological environments and early warning are described in this paper. Marine ecological processes are influenced by many factors including hydrological and meteorological conditions, biological factors, and human activities. Consequently, it is very difficult to incorporate all these influences and their interactions in a deterministic or analysis model. A prediction model integrating a time series prediction approach with neural network nonlinear modeling is proposed for marine ecological parameters. The model explores the natural fluctuations in marine ecological parameters by learning from the latest observed data automatically, and then predicting future values of the parameter. The model is updated in a "rolling" fashion with new observed data from the monitoring station. Prediction experiments results showed that the neural network prediction model based on time series data is effective for marine ecological prediction and can be used for the development of early warning systems.

Critical slowing down as early warning for the onset of collapse in mutualistic communities.

PubMed

Dakos, Vasilis; Bascompte, Jordi

2014-12-09

Tipping points are crossed when small changes in external conditions cause abrupt unexpected responses in the current state of a system. In the case of ecological communities under stress, the risk of approaching a tipping point is unknown, but its stakes are high. Here, we test recently developed critical slowing-down indicators as early-warning signals for detecting the proximity to a potential tipping point in structurally complex ecological communities. We use the structure of 79 empirical mutualistic networks to simulate a scenario of gradual environmental change that leads to an abrupt first extinction event followed by a sequence of species losses until the point of complete community collapse. We find that critical slowing-down indicators derived from time series of biomasses measured at the species and community level signal the proximity to the onset of community collapse. In particular, we identify specialist species as likely the best-indicator species for monitoring the proximity of a community to collapse. In addition, trends in slowing-down indicators are strongly correlated to the timing of species extinctions. This correlation offers a promising way for mapping species resilience and ranking species risk to extinction in a given community. Our findings pave the road for combining theory on tipping points with patterns of network structure that might prove useful for the management of a broad class of ecological networks under global environmental change.

An Experimental Seismic Data and Parameter Exchange System for Tsunami Warning Systems

NASA Astrophysics Data System (ADS)

Hoffmann, T. L.; Hanka, W.; Saul, J.; Weber, B.; Becker, J.; Heinloo, A.; Hoffmann, M.

2009-12-01

For several years GFZ Potsdam is operating a global earthquake monitoring system. Since the beginning of 2008, this system is also used as an experimental seismic background data center for two different regional Tsunami Warning Systems (TWS), the IOTWS (Indian Ocean) and the interim NEAMTWS (NE Atlantic and Mediterranean). The SeisComP3 (SC3) software, developed within the GITEWS (German Indian Ocean Tsunami Early Warning System) project, capable to acquire, archive and process real-time data feeds, was extended for export and import of individual processing results within the two clusters of connected SC3 systems. Therefore not only real-time waveform data are routed to the attached warning centers through GFZ but also processing results. While the current experimental NEAMTWS cluster consists of SC3 systems in six designated national warning centers in Europe, the IOTWS cluster presently includes seven centers, with another three likely to join in 2009/10. For NEAMTWS purposes, the GFZ virtual real-time seismic network (GEOFON Extended Virtual Network -GEVN) in Europe was substantially extended by adding many stations from Western European countries optimizing the station distribution. In parallel to the data collection over the Internet, a GFZ VSAT hub for secured data collection of the EuroMED GEOFON and NEAMTWS backbone network stations became operational and first data links were established through this backbone. For the Southeast Asia region, a VSAT hub has been established in Jakarta already in 2006, with some other partner networks connecting to this backbone via the Internet. Since its establishment, the experimental system has had the opportunity to prove its performance in a number of relevant earthquakes. Reliable solutions derived from a minimum of 25 stations were very promising in terms of speed. For important events, automatic alerts were released and disseminated by emails and SMS. Manually verified solutions are added as soon as they become available. The results are also promising in terms of accuracy since epicenter coordinates, depth and magnitude estimates were sufficiently accurate from the very beginning, and usually do not differ substantially from the final solutions. In summary, automatic seismic event processing has shown to work well as a first step for starting a Tsunami Warning process. However, for the secured assessment of the tsunami potential of a given event, 24/7-manned regional TWCs are mandatory for reliable manual verification of the automatic seismic results. At this time, GFZ itself provides manual verification only when staff is available, not on a 24/7 basis, while the actual national tsunami warning centers have all a reliable 24/7 service.

Air quality early-warning system for cities in China

NASA Astrophysics Data System (ADS)

Xu, Yunzhen; Yang, Wendong; Wang, Jianzhou

2017-01-01

Air pollution has become a serious issue in many developing countries, especially in China, and could generate adverse effects on human beings. Air quality early-warning systems play an increasingly significant role in regulatory plans that reduce and control emissions of air pollutants and inform the public in advance when harmful air pollution is foreseen. However, building a robust early-warning system that will improve the ability of early-warning is not only a challenge but also a critical issue for the entire society. Relevant research is still poor in China and cannot always satisfy the growing requirements of regulatory planning, despite the issue's significance. Therefore, in this paper, a hybrid air quality early-warning system was successfully developed, composed of forecasting and evaluation. First, a hybrid forecasting model was proposed as an important part of this system based on the theory of "decomposition and ensemble" and combined with the advanced data processing technique, support vector machine, the latest bio-inspired optimization algorithm and the leave-one-out strategy for deciding weights. Afterwards, to intensify the research, fuzzy evaluation was performed, which also plays an indispensable role in the early-warning system. The forecasting model and fuzzy evaluation approaches are complementary. Case studies using daily air pollution concentrations of six air pollutants from three cities in China (i.e., Taiyuan, Harbin and Chongqing) are used as examples to evaluate the efficiency and effectiveness of the developed air quality early-warning system. Experimental results demonstrate that both the accuracy and the effectiveness of the developed system are greatly superior for air quality early warning. Furthermore, the application of forecasting and evaluation enables the informative and effective quantification of future air quality, offering a significant advantage, and can be employed to develop rapid air quality early-warning systems.

Nanosensors-Cellphone Integration for Extended Chemical Sensing Network

NASA Technical Reports Server (NTRS)

Li, Jing

2011-01-01

This poster is to present the development of a cellphone sensor network for extended chemical sensing. The nanosensors using carbon nanotubes and other nanostructures are used with low power and high sensitivity for chemical detection. The sensing module has been miniaturized to a small size that can plug in or clip on to a smartphone. The chemical information detected by the nanosensors are acquired by a smartphone and transmitted via cellphone 3g or WiFi network to an internet server. The whole integrated sensing system from sensor to cellphone to a cloud will provide an extended chemical sensing network that can cover nation wide and even cover global wide for early warning of a hazardous event.

Urban Flood Prevention and Early Warning System in Jinan City

NASA Astrophysics Data System (ADS)

Feng, Shiyuan; Li, Qingguo

2018-06-01

The system construction of urban flood control and disaster reduction in China is facing pressure and challenge from new urban water disaster. Under the circumstances that it is difficult to build high standards of flood protection engineering measures in urban areas, it is particularly important to carry out urban flood early warning. In Jinan City, a representative inland area, based on the index system of early warning of flood in Jinan urban area, the method of fuzzy comprehensive evaluation was adopted to evaluate the level of early warning. Based on the cumulative rainfall of 3 hours, the CAflood simulation results based on cellular automaton model of urban flooding were used as evaluation indexes to realize the accuracy and integration of urban flood control early warning.

Cable Overheating Risk Warning Method Based on Impedance Parameter Estimation in Distribution Network

NASA Astrophysics Data System (ADS)

Yu, Zhang; Xiaohui, Song; Jianfang, Li; Fei, Gao

2017-05-01

Cable overheating will lead to the cable insulation level reducing, speed up the cable insulation aging, even easy to cause short circuit faults. Cable overheating risk identification and warning is nessesary for distribution network operators. Cable overheating risk warning method based on impedance parameter estimation is proposed in the paper to improve the safty and reliability operation of distribution network. Firstly, cable impedance estimation model is established by using least square method based on the data from distribiton SCADA system to improve the impedance parameter estimation accuracy. Secondly, calculate the threshold value of cable impedance based on the historical data and the forecast value of cable impedance based on the forecasting data in future from distribiton SCADA system. Thirdly, establish risks warning rules library of cable overheating, calculate the cable impedance forecast value and analysis the change rate of impedance, and then warn the overheating risk of cable line based on the overheating risk warning rules library according to the variation relationship between impedance and line temperature rise. Overheating risk warning method is simulated in the paper. The simulation results shows that the method can identify the imedance and forecast the temperature rise of cable line in distribution network accurately. The result of overheating risk warning can provide decision basis for operation maintenance and repair.

Sensor Fusion of Position- and Micro-Sensors (MEMS) integrated in a Wireless Sensor Network for movement detection in landslide areas

NASA Astrophysics Data System (ADS)

Arnhardt, Christian; Fernández-Steeger, Tomas; Azzam, Rafig

2010-05-01

Monitoring systems in landslide areas are important elements of effective Early Warning structures. Data acquisition and retrieval allows the detection of movement processes and thus is essential to generate warnings in time. Apart from the precise measurement, the reliability of data is fundamental, because outliers can trigger false alarms and leads to the loss of acceptance of such systems. For the monitoring of mass movements and their risk it is important to know, if there is movement, how fast it is and how trustworthy is the information. The joint project "Sensorbased landslide early warning system" (SLEWS) deals with these questions, and tries to improve data quality and to reduce false alarm rates, due to the combination of sensor date (sensor fusion). The project concentrates on the development of a prototypic Alarm- and Early Warning system (EWS) for different types of landslides by using various low-cost sensors, integrated in a wireless sensor network (WSN). The network consists of numerous connection points (nodes) that transfer data directly or over other nodes (Multi-Hop) in real-time to a data collection point (gateway). From there all the data packages are transmitted to a spatial data infrastructure (SDI) for further processing, analyzing and visualizing with respect to end-user specifications. The ad-hoc characteristic of the network allows the autonomous crosslinking of the nodes according to existing connections and communication strength. Due to the independent finding of new or more stable connections (self healing) a breakdown of the whole system is avoided. The bidirectional data stream enables the receiving of data from the network but also allows the transfer of commands and pointed requests into the WSN. For the detection of surface deformations in landslide areas small low-cost Micro-Electro-Mechanical-Systems (MEMS) and positionsensors from the automobile industries, different industrial applications and from other measurement technologies were chosen. The MEMS-Sensors are acceleration-, tilt- and barometric pressure sensors. The positionsensors are draw wire and linear displacement transducers. In first laboratory tests the accuracy and resolution were investigated. The tests showed good results for all sensors. For example tilt-movements can be monitored with an accuracy of +/- 0,06° and a resolution of 0,1°. With the displacement transducer change in length of >0,1mm is possible. Apart from laboratory tests, field tests in South France and Germany were done to prove data stability and movement detection under real conditions. The results obtained were very satisfying, too. In the next step the combination of numerous sensors (sensor fusion) of the same type (redundancy) or different types (complementary) was researched. Different experiments showed that there is a high concordance between identical sensor-types. According to different sensor parameters (sensitivity, accuracy, resolution) some sensor-types can identify changes earlier. Taking this into consideration, good correlations between different kinds of sensors were achieved, too. Thus the experiments showed that combination of sensors is possible and this could improve the detection of movement and movement rate but also outliers. Based on this results various algorithms were setup that include different statistical methods (outlier tests, testing of hypotheses) and procedures from decision theories (Hurwicz-criteria). These calculation formulas will be implemented in the spatial data infrastructure (SDI) for the further data processing and validation. In comparison with today existing mainly punctually working monitoring systems, the application of wireless sensor networks in combination with low-cost, but precise micro-sensors provides an inexpensive and easy to set up monitoring system also in large areas. The correlation of same but also different sensor-types permits a good data control. Thus the sensor fusion is a promising tool to detect movement more reliable and thus contributes essential to the improvement of Early Warning Systems.

On the importance of a correct divulgation of monitoring results for an efficient management of landslide emergencies

NASA Astrophysics Data System (ADS)

Giordan, Daniele; Manconi, Andrea; Allasia, Paolo

2015-04-01

In the last decades, technological evolution has strongly increased the number of instruments that can be used to monitor landslide phenomena. Robotized Total Stations, GB-InSAR, and GPS are only few examples of the systems that can be used for the control of the topographic changes due to the landslide activity. These monitoring systems are often merged in a complex network, aimed at controlling the most important physical parameters influencing the evolution of landslide activity. The technological level reached by these systems allows us to use them for early warning purposes. Critical thresholds are identified and, when overcome, emergency actions are associated to protect population living in areas potentially involved by landslide failure. The use of these early warning systems can be very useful for the decision makers, which have to manage emergency conditions due to a landslide acceleration likely precursor of a collapse. At this stage, every instrument has a proper management system and the dataset obtained is often not compatible with the results of the others systems. The level of complexity increases with the number of monitoring systems and often could generate a paradox: the source of data are so numerous and difficult to interpret that a full understanding of the phenomenon could be hampered. Nowadays, a correct divulgation of the recent evolution of a landslide potentially dangerous for the population is very important. The Geohazard Monitoring Group of CNR IRPI developed a communication strategy to divulgate the monitoring network results based on both, a dedicated web page (for the publication in near real time of last updates), and periodical bulletins (for a deeper analysis of the available dataset). To manage the near real time application we developed a system called ADVICE (ADVanced dIsplaCement monitoring system for Early warning) that collects all the available data of a monitoring network and creates user-friendly representations of the recent landslide evolution. The system is also able to manage early warnings based on pre-defined thresholds (usually related to the analysis of displacement and/or velocity) sending emails and SMS. Starting from the same dataset, the representations are different if the information has to be delivered to the population or the technicians involved in the landslide emergency. Our communication strategy considers three different levels of representations of the acquired dataset to be able to communicate the results to the different stakeholders potentially involved in the emergency. This communication scheme has been achieved over time, thank to the experience acquired during the management of monitoring networks relevant to different case studies, such as: Mt. de La Saxe Landslide (Aosta Valley, NW Italy), Ripoli landslide (Emilia Romagna region, central Italy), Montaguto landslide (Campania region, south Italy). Here we present how the correct and user-friendly communication of the monitoring results has been an important added value to support decision makers and population during emergency scenarios.

A Feasibility Study for Earthquake Early Warning in a School in Southern Italy

NASA Astrophysics Data System (ADS)

Emolo, A.; Martino, C.; Picozzi, M.; Zollo, A.; Elia, L.; Festa, G.; Colombelli, S.; Caruso, A.; Brondi, P.; Miranda, N.

2015-12-01

We present the results of a feasibility study on the application of earthquake early-warning procedures in the high school ITIS E. Majorana, Somma Vesuviana, Naples, located about 80 km far from the seismogenic Irpinia region. The study was performed in the framework of the European REAKT project. The school was equipped with an EEWS composed of: a small seismic network of accelerometers, the PRESToPlus software platform, and an actuator, named Sentinel. The Sentinel is made up of low-cost hardware (i.e., Arduino®) programmed to accomplish three main tasks: 1) listen and interpret messages delivered by the EEW system PRESToPlus on the ground motion severity expected at the target site; 2) provides different warnings as alert levels by the control of different hardware (i.e., alarm bells, emergency lights, and so on); 3) declare the end of the most threatening condition, which will assist the emergency coordinator starting the evacuation plan defined by the current legislation. The Sentinel was developed within REAKT in close collaboration with the students and the teachers of the school. The EEW system and the Sentinel were successfully tested during some blind drills performed during normal school activities.

Technology-Based Early Warning Systems for Bipolar Disorder: A Conceptual Framework

PubMed Central

Torous, John; Thompson, Wesley

2016-01-01

Recognition and timely action around “warning signs” of illness exacerbation is central to the self-management of bipolar disorder. Due to its heterogeneity and fluctuating course, passive and active mobile technologies have been increasingly evaluated as adjunctive or standalone tools to predict and prevent risk of worsening of course in bipolar disorder. As predictive analytics approaches to big data from mobile health (mHealth) applications and ancillary sensors advance, it is likely that early warning systems will increasingly become available to patients. Such systems could reduce the amount of time spent experiencing symptoms and diminish the immense disability experienced by people with bipolar disorder. However, in addition to the challenges in validating such systems, we argue that early warning systems may not be without harms. Probabilistic warnings may be delivered to individuals who may not be able to interpret the warning, have limited information about what behaviors to change, or are unprepared to or cannot feasibly act due to time or logistic constraints. We propose five essential elements for early warning systems and provide a conceptual framework for designing, incorporating stakeholder input, and validating early warning systems for bipolar disorder with a focus on pragmatic considerations. PMID:27604265

Famine Early Warning System Network (FEWS NET)

USGS Publications Warehouse

Verdin, James P.

2006-01-01

The FEWS NET mission is to identify potentially food-insecure conditions early through the provision of timely and analytical hazard and vulnerability information. U.S. Government decision-makers act on this information to authorize mitigation and response activities. The U.S. Geological Survey (USGS) FEWS NET provides tools and data for monitoring and forecasting the incidence of drought and flooding to identify shocks to the food supply system that could lead to famine. Historically focused on Africa, the scope of the network has expanded to be global coverage. FEWS NET implementing partners include the USGS, National Aeronautics and Space Administration (NASA), National Oceanic and Atmospheric Administration (NOAA), United States Agency for International Development (USAID), United States Department of Agriculture (USDA), and Chemonics International.

Application of Seismic Array Processing to Tsunami Early Warning

NASA Astrophysics Data System (ADS)

An, C.; Meng, L.

2015-12-01

Tsunami wave predictions of the current tsunami warning systems rely on accurate earthquake source inversions of wave height data. They are of limited effectiveness for the near-field areas since the tsunami waves arrive before data are collected. Recent seismic and tsunami disasters have revealed the need for early warning to protect near-source coastal populations. In this work we developed the basis for a tsunami warning system based on rapid earthquake source characterisation through regional seismic array back-projections. We explored rapid earthquake source imaging using onshore dense seismic arrays located at regional distances on the order of 1000 km, which provides faster source images than conventional teleseismic back-projections. We implement this method in a simulated real-time environment, and analysed the 2011 Tohoku earthquake rupture with two clusters of Hi-net stations in Kyushu and Northern Hokkaido, and the 2014 Iquique event with the Earthscope USArray Transportable Array. The results yield reasonable estimates of rupture area, which is approximated by an ellipse and leads to the construction of simple slip models based on empirical scaling of the rupture area, seismic moment and average slip. The slip model is then used as the input of the tsunami simulation package COMCOT to predict the tsunami waves. In the example of the Tohoku event, the earthquake source model can be acquired within 6 minutes from the start of rupture and the simulation of tsunami waves takes less than 2 min, which could facilitate a timely tsunami warning. The predicted arrival time and wave amplitude reasonably fit observations. Based on this method, we propose to develop an automatic warning mechanism that provides rapid near-field warning for areas of high tsunami risk. The initial focus will be Japan, Pacific Northwest and Alaska, where dense seismic networks with the capability of real-time data telemetry and open data accessibility, such as the Japanese HiNet (>800 instruments) and the Earthscope USArray Transportable Array (~400 instruments), are established.

[Ecological security early-warning in Zhoushan Islands based on variable weight model].

PubMed

Zhou, Bin; Zhong, Lin-sheng; Chen, Tian; Zhou, Rui

2015-06-01

Ecological security early warning, as an important content of ecological security research, is of indicating significance in maintaining regional ecological security. Based on driving force, pressure, state, impact and response (D-P-S-I-R) framework model, this paper took Zhoushan Islands in Zhejiang Province as an example to construct the ecological security early warning index system, test degrees of ecological security early warning of Zhoushan Islands from 2000 to 2012 by using the method of variable weight model, and forecast ecological security state of 2013-2018 by Markov prediction method. The results showed that the variable weight model could meet the study needs of ecological security early warning of Zhoushan Islands. There was a fluctuant rising ecological security early warning index from 0.286 to 0.484 in Zhoushan Islands between year 2000 and 2012, in which the security grade turned from "serious alert" into " medium alert" and the indicator light turned from "orange" to "yellow". The degree of ecological security warning was "medium alert" with the light of "yellow" for Zhoushan Islands from 2013 to 2018. These findings could provide a reference for ecological security maintenance of Zhoushan Islands.

A Sustainable Early Warning System for Climate Change Impacts on Water Quality Management

NASA Astrophysics Data System (ADS)

Lee, T.; Tung, C.; Chung, N.

2007-12-01

In this era of rapid social and technological change leading to interesting life complexity and environmental displacement, both positive and negative effects among ecosystems call for a balance in which there are impacts by climate changes. Early warning systems for climate change impacts are necessary in order to allow society as a whole to properly and usefully assimilate the masses of new information and knowledge. Therefore, our research addresses to build up a sustainable early warning mechanism. The main goal is to mitigate the cumulative impacts on the environment of climate change and enhance adaptive capacities. An effective early warning system has been proven for protection. However, there is a problem that estimate future climate changes would be faced with high uncertainty. In general, take estimations for climate change impacts would use the data from General Circulation Models and take the analysis as the Intergovernmental Panel on Climate Change declared. We follow the course of the method for analyzing climate change impacts and attempt to accomplish the sustainable early warning system for water quality management. Climate changes impact not only on individual situation but on short-term variation and long-term gradually changes. This kind characteristic should adopt the suitable warning system for long-term formulation and short- term operation. To continue the on-going research of the long-term early warning system for climate change impacts on water quality management, the short-term early warning system is established by using local observation data for reappraising the warning issue. The combination of long-term and short-term system can provide more circumstantial details. In Taiwan, a number of studies have revealed that climate change impacts on water quality, especially in arid period, the concentration of biological oxygen demand may turn into worse. Rapid population growth would also inflict injury on its assimilative capacity to degenerate. To concern about those items, the sustainable early warning system is established and the initiative fall into the following categories: considering the implications for policies, applying adaptive strategies and informing the new climate changes. By setting up the framework of early warning system expectantly can defend stream area from impacts damaging and in sure the sustainable development.

49 CFR Appendix C to Part 512 - Early Warning Reporting Class Determinations

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 6 2011-10-01 2011-10-01 false Early Warning Reporting Class Determinations C Appendix C to Part 512 Transportation Other Regulations Relating to Transportation (Continued) NATIONAL.... 512, App. C Appendix C to Part 512—Early Warning Reporting Class Determinations (a) The Chief Counsel...

49 CFR Appendix C to Part 512 - Early Warning Reporting Class Determinations

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 6 2012-10-01 2012-10-01 false Early Warning Reporting Class Determinations C Appendix C to Part 512 Transportation Other Regulations Relating to Transportation (Continued) NATIONAL.... 512, App. C Appendix C to Part 512—Early Warning Reporting Class Determinations (a) The Chief Counsel...

49 CFR Appendix C to Part 512 - Early Warning Reporting Class Determinations

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 6 2010-10-01 2010-10-01 false Early Warning Reporting Class Determinations C Appendix C to Part 512 Transportation Other Regulations Relating to Transportation (Continued) NATIONAL.... 512, App. C Appendix C to Part 512—Early Warning Reporting Class Determinations (a) The Chief Counsel...

49 CFR Appendix C to Part 512 - Early Warning Reporting Class Determinations

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 6 2013-10-01 2013-10-01 false Early Warning Reporting Class Determinations C Appendix C to Part 512 Transportation Other Regulations Relating to Transportation (Continued) NATIONAL.... 512, App. C Appendix C to Part 512—Early Warning Reporting Class Determinations (a) The Chief Counsel...

49 CFR Appendix C to Part 512 - Early Warning Reporting Class Determinations

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 6 2014-10-01 2014-10-01 false Early Warning Reporting Class Determinations C Appendix C to Part 512 Transportation Other Regulations Relating to Transportation (Continued) NATIONAL.... 512, App. C Appendix C to Part 512—Early Warning Reporting Class Determinations (a) The Chief Counsel...

Real-Time Earthquake Risk Mitigation Of Infrastructures Using Istanbul Earthquake Early Warning and Rapid Response Network

NASA Astrophysics Data System (ADS)

Zulfikar, Can; Pinar, Ali; Tunc, Suleyman; Erdik, Mustafa

2014-05-01

The Istanbul EEW network consisting of 10 inland and 5 OBS strong motion stations located close to the Main Marmara Fault zone is operated by KOERI. Data transmission between the remote stations and the base station at KOERI is provided both with satellite and fiber optic cable systems. The continuous on-line data from these stations is used to provide real time warning for emerging potentially disastrous earthquakes. The data transmission time from the remote stations to the KOERI data center is a few milliseconds through fiber optic lines and less than a second via satellites. The early warning signal (consisting three alarm levels) is communicated to the appropriate servo shut-down systems of the receipent facilities, that automatically decide proper action based on the alarm level. Istanbul Gas Distribution Corporation (IGDAS) is one of the end users of the EEW signal. IGDAS, the primary natural gas provider in Istanbul, operates an extensive system 9,867 km of gas lines with 550 district regulators and 474,000 service boxes. State of-the-art protection systems automatically cut natural gas flow when breaks in the pipelines are detected. Since 2005, buildings in Istanbul using natural gas are required to install seismometers that automatically cut natural gas flow when certain thresholds are exceeded. IGDAS uses a sophisticated SCADA (supervisory control and data acquisition) system to monitor the state-of-health of its pipeline network. This system provides real-time information about quantities related to pipeline monitoring, including input-output pressure, drawing information, positions of station and RTU (remote terminal unit) gates, slum shut mechanism status at 581 district regulator sites. The SCADA system of IGDAŞ receives the EEW signal from KOERI and decide the proper actions according to the previously specified ground acceleration levels. Presently, KOERI sends EEW signal to the SCADA system of IGDAS Natural Gas Network of Istanbul. The EEW signal of KOERI is also transmitted to the serve shut down system of the Marmaray Rail Tube Tunnel and Commuter Rail Mass Transit System in Istanbul. The Marmaray system includes an undersea railway tunnel under the Bosphorus Strait. Several strong motion instruments are installed within the tunnel for taking measurements against strong ground shaking and early warning purposes. This system is integrated with the KOERI EEW System. KOERI sends the EEW signal to the command center of Marmaray. Having received the signal, the command center put into action the previously defined measurements. For example, the trains within the tunnel will be stopped at the nearest station, no access to the tunnel will be allowed to the trains approaching the tunnel, water protective caps will be closed to protect flood closing the connection between the onshore and offshore tunnels.

The Role of Cash Flow in Financial Early Warning of Agricultural Enterprises Based on Logistic Model

NASA Astrophysics Data System (ADS)

Sun, Fengru

2018-01-01

This paper chooses the agricultural listed companies as the research object, compares the financial situation of the enterprise and the theory of financial early warning, combines the financial status of the agricultural listed companies, selects the relevant cash flow indicators, discusses the application of the Logistic financial early warning model in the agricultural listed companies, Agricultural enterprises get better development. Research on financial early warning of agricultural listed companies will help the agricultural listed companies to predict the financial crisis. Financial early warning model is simple to establish, operational and strong, the use of financial early warning model, to help enterprises in the financial crisis before taking rapid and effective measures, which can avoid losses. Help enterprises to discover signs of deterioration of the financial situation in time to maintain the sustainable development of agricultural enterprises. In addition, through the financial early warning model, investors can correctly identify the financial situation of agricultural enterprises, and can evaluate the financial situation of agricultural enterprises and to help investors to invest in scientific and rational, beneficial to investors to analyze the safety of investment. But also help the relevant regulatory agencies to effectively monitor the market and promote the healthy and stable development of the market.

Prototype Early Warning Systems for Vector-Borne Diseases in Europe

PubMed Central

Semenza, Jan C.

2015-01-01

Globalization and environmental change, social and demographic determinants and health system capacity are significant drivers of infectious diseases which can also act as epidemic precursors. Thus, monitoring changes in these drivers can help anticipate, or even forecast, an upsurge of infectious diseases. The European Environment and Epidemiology (E3) Network has been built for this purpose and applied to three early warning case studies: (1) The environmental suitability of malaria transmission in Greece was mapped in order to target epidemiological and entomological surveillance and vector control activities. Malaria transmission in these areas was interrupted in 2013 through such integrated preparedness and response activities. (2) Since 2010, recurrent West Nile fever outbreaks have ensued in South/eastern Europe. Temperature deviations from a thirty year average proved to be associated with the 2010 outbreak. Drivers of subsequent outbreaks were computed through multivariate logistic regression models and included monthly temperature anomalies for July and a normalized water index. (3) Dengue is a tropical disease but sustained transmission has recently emerged in Madeira. Autochthonous transmission has also occurred repeatedly in France and in Croatia mainly due to travel importation. The risk of dengue importation into Europe in 2010 was computed with the volume of international travelers from dengue affected areas worldwide.These prototype early warning systems indicate that monitoring drivers of infectious diseases can help predict vector-borne disease threats. PMID:26042370

Nowcasting of Lightning-Related Accidents in Africa

NASA Astrophysics Data System (ADS)

Ihrlich, Laura; Price, Colin

2016-04-01

Tropical Africa is the world capital of thunderstorm activity with the highest density of strikes per square kilometer per year. As a result it is also the continent with perhaps the highest casualties and injuries from direct lightning strikes. This region of the globe also has little lightning protection of rural homes and schools, while many casualties occur during outdoor activities (e.g. farming, fishing, sports, etc.) In this study we investigated two lightning-caused accidents that got wide press coverage: A lightning strike to a Cheetah Center in Namibia which caused a huge fire and great destruction (16 October 2013), and a plane crash in Mali where 116 people died (24 July 2014). Using data from the World Wide Lightning Location Network (WWLLN) we show that the lightning data alone can provide important early warning information that can be used to reduce risks and damages and loss of life from lightning strikes. We have developed a now-casting scheme that allows for early warnings across Africa with a relatively low false alarm rate. To verify the accuracy of our now-cast, we have performed some statistical analysis showing relatively high skill at providing early warnings (lead time of a few hours) based on lightning alone. Furthermore, our analysis can be used in forensic meteorology for determining if such accidents are caused by lightning strikes.

Prototype early warning systems for vector-borne diseases in Europe.

PubMed

Semenza, Jan C

2015-06-02

Globalization and environmental change, social and demographic determinants and health system capacity are significant drivers of infectious diseases which can also act as epidemic precursors. Thus, monitoring changes in these drivers can help anticipate, or even forecast, an upsurge of infectious diseases. The European Environment and Epidemiology (E3) Network has been built for this purpose and applied to three early warning case studies: (1) The environmental suitability of malaria transmission in Greece was mapped in order to target epidemiological and entomological surveillance and vector control activities. Malaria transmission in these areas was interrupted in 2013 through such integrated preparedness and response activities. (2) Since 2010, recurrent West Nile fever outbreaks have ensued in South/eastern Europe. Temperature deviations from a thirty year average proved to be associated with the 2010 outbreak. Drivers of subsequent outbreaks were computed through multivariate logistic regression models and included monthly temperature anomalies for July and a normalized water index. (3) Dengue is a tropical disease but sustained transmission has recently emerged in Madeira. Autochthonous transmission has also occurred repeatedly in France and in Croatia mainly due to travel importation. The risk of dengue importation into Europe in 2010 was computed with the volume of international travelers from dengue affected areas worldwide.These prototype early warning systems indicate that monitoring drivers of infectious diseases can help predict vector-borne disease threats.

Efforts Toward an Early Warning Crop Monitor for Countries at Risk

NASA Astrophysics Data System (ADS)

Budde, M. E.; Verdin, J. P.; Barker, B.; Humber, M. L.; Becker-Reshef, I.; Justice, C. O.; Magadzire, T.; Galu, G.; Rodriguez, M.; Jayanthi, H.

2015-12-01

Assessing crop growing conditions is a crucial aspect of monitoring food security in the developing world. One of the core components of the Group on Earth Observations - Global Agricultural Monitoring (GEOGLAM) targets monitoring Countries at Risk (component 3). The Famine Early Warning Systems Network (FEWS NET) has a long history of utilizing remote sensing and crop modeling to address food security threats in the form of drought, floods, pest infestation, and climate change in some of the world's most at risk countries. FEWS NET scientists at the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center and the University of Maryland Department of Geography have undertaken efforts to address component 3, by promoting the development of a collaborative Early Warning Crop Monitor (EWCM) that would specifically address Countries at Risk. A number of organizations utilize combinations of satellite earth observations, field campaigns, network partner inputs, and crop modeling techniques to monitor crop conditions throughout the world. Agencies such as the Food and Agriculture Organization of the United Nations (FAO), United Nations World Food Programme (WFP), and the European Commission's Joint Research Centre (JRC) provide agricultural monitoring information and reporting across a broad number of areas at risk and in many cases, organizations routinely report on the same countries. The latter offers an opportunity for collaboration on crop growing conditions among agencies. The reduction of uncertainty and achievement of consensus will help strengthen confidence in decisions to commit resources for mitigation of acute food insecurity and support for resilience and development programs. In addition, the development of a collaborative global EWCM will provide each of the partner agencies with the ability to quickly gather crop condition information for areas where they may not typically work or have access to local networks. Using a framework developed by GEOGLAM for monitoring crop conditions in support of the Agricultural Market Information System, we developed an EWCM system for countries at risk. We present the current status of that implementation and highlight achievements to date along with future plans to support the needs of the global agricultural monitoring community.

CISN ShakeAlert: Accounting for site amplification effects and quantifying time and spatial dependence of uncertainty estimates in the Virtual Seismologist earthquake early warning algorithm

NASA Astrophysics Data System (ADS)

Caprio, M.; Cua, G. B.; Wiemer, S.; Fischer, M.; Heaton, T. H.; CISN EEW Team

2011-12-01

The Virtual Seismologist (VS) earthquake early warning (EEW) algorithm is one of 3 EEW approaches being incorporated into the California Integrated Seismic Network (CISN) ShakeAlert system, a prototype EEW system being tested in real-time in California. The VS algorithm, implemented by the Swiss Seismological Service at ETH Zurich, is a Bayesian approach to EEW, wherein the most probable source estimate at any given time is a combination of contributions from a likehihood function that evolves in response to incoming data from the on-going earthquake, and selected prior information, which can include factors such as network topology, the Gutenberg-Richter relationship or previously observed seismicity. The VS codes have been running in real-time at the Southern California Seismic Network (SCSN) since July 2008, and at the Northern California Seismic Network (NCSN) since February 2009. With the aim of improving the convergence of real-time VS magnitude estimates to network magnitudes, we evaluate various empirical and Vs30-based approaches to accounting for site amplification. Empirical station corrections for SCSN stations are derived from M>3.0 events from 2005 through 2009. We evaluate the performance of the various approaches using an independent 2010 dataset. In addition, we analyze real-time VS performance from 2008 to the present to quantify the time and spatial dependence of VS uncertainty estimates. We also summarize real-time VS performance for significant 2011 events in California. Improved magnitude and uncertainty estimates potentially increase the utility of EEW information for end-users, particularly those intending to automate damage-mitigating actions based on real-time information.

Integrating Low-Cost Mems Accelerometer Mini-Arrays (mama) in Earthquake Early Warning Systems

NASA Astrophysics Data System (ADS)

Nof, R. N.; Chung, A. I.; Rademacher, H.; Allen, R. M.

2016-12-01

Current operational Earthquake Early Warning Systems (EEWS) acquire data with networks of single seismic stations, and compute source parameters assuming earthquakes to be point sources. For large events, the point-source assumption leads to an underestimation of magnitude, and the use of single stations leads to large uncertainties in the locations of events outside the network. We propose the use of mini-arrays to improve EEWS. Mini-arrays have the potential to: (a) estimate reliable hypocentral locations by beam forming (FK-analysis) techniques; (b) characterize the rupture dimensions and account for finite-source effects, leading to more reliable estimates for large magnitudes. Previously, the high price of multiple seismometers has made creating arrays cost-prohibitive. However, we propose setting up mini-arrays of a new seismometer based on low-cost (<$150), high-performance MEMS accelerometer around conventional seismic stations. The expected benefits of such an approach include decreasing alert-times, improving real-time shaking predictions and mitigating false alarms. We use low-resolution 14-bit Quake Catcher Network (QCN) data collected during Rapid Aftershock Mobilization Program (RAMP) in Christchurch, NZ following the M7.1 Darfield earthquake in September 2010. As the QCN network was so dense, we were able to use small sub-array of up to ten sensors spread along a maximum area of 1.7x2.2 km2 to demonstrate our approach and to solve for the BAZ of two events (Mw4.7 and Mw5.1) with less than ±10° error. We will also present the new 24-bit device details, benchmarks, and real-time measurements.

Massachusetts Early Warning Indicator System (EWIS). "Technical Descriptions of Risk Model Development": Early and Late Elementary Age Groupings (Grades 1-6)

ERIC Educational Resources Information Center

Massachusetts Department of Elementary and Secondary Education, 2013

2013-01-01

The Massachusetts Department of Elementary and Secondary Education (Department) created the grades 1-12 Early Warning Indicator System (EWIS) in response to district interest in the Early Warning Indicator Index (EWII) that the Department previously created for rising grade 9 students. Districts shared that the EWII data were helpful, but also…

Organizing Schools to Address Early Warning Indicators (EWIs): Common Practices and Challenges

ERIC Educational Resources Information Center

Davis, Marcia; Herzog, Liza; Legters, Nettie

2013-01-01

An early warning system is an intentional process whereby school personnel collectively analyze student data to monitor students at risk of falling off track for graduation and to provide the interventions and resources to intervene. We studied the process of monitoring the early warning indicators and implementing interventions to ascertain…

78 FR 78321 - Early Warning Reporting, Foreign Defect Reporting, and Motor Vehicle and Equipment Recall...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-26

... DEPARTMENT OF TRANSPORTATION National Highway Traffic Safety Administration 49 CFR Parts 573, 577, and 579 [Docket No. NHTSA--2012-0068; Notice 3] RIN 2127-AK72 Early Warning Reporting, Foreign Defect... final rule. Id. Manufacturers with early warning reporting (EWR) accounts may obtain a copy of the VIN...

Looming auditory collision warnings for driving.

PubMed

Gray, Rob

2011-02-01

A driving simulator was used to compare the effectiveness of increasing intensity (looming) auditory warning signals with other types of auditory warnings. Auditory warnings have been shown to speed driver reaction time in rear-end collision situations; however, it is not clear which type of signal is the most effective. Although verbal and symbolic (e.g., a car horn) warnings have faster response times than abstract warnings, they often lead to more response errors. Participants (N=20) experienced four nonlooming auditory warnings (constant intensity, pulsed, ramped, and car horn), three looming auditory warnings ("veridical," "early," and "late"), and a no-warning condition. In 80% of the trials, warnings were activated when a critical response was required, and in 20% of the trials, the warnings were false alarms. For the early (late) looming warnings, the rate of change of intensity signaled a time to collision (TTC) that was shorter (longer) than the actual TTC. Veridical looming and car horn warnings had significantly faster brake reaction times (BRT) compared with the other nonlooming warnings (by 80 to 160 ms). However, the number of braking responses in false alarm conditions was significantly greater for the car horn. BRT increased significantly and systematically as the TTC signaled by the looming warning was changed from early to veridical to late. Looming auditory warnings produce the best combination of response speed and accuracy. The results indicate that looming auditory warnings can be used to effectively warn a driver about an impending collision.

Validation of a Pediatric Early Warning Score in Hospitalized Pediatric Oncology and Hematopoietic Stem Cell Transplant Patients.

PubMed

Agulnik, Asya; Forbes, Peter W; Stenquist, Nicole; Rodriguez-Galindo, Carlos; Kleinman, Monica

2016-04-01

To evaluate the correlation of a Pediatric Early Warning Score with unplanned transfer to the PICU in hospitalized oncology and hematopoietic stem cell transplant patients. We performed a retrospective matched case-control study, comparing the highest documented Pediatric Early Warning Score within 24 hours prior to unplanned PICU transfers in hospitalized pediatric oncology and hematopoietic stem cell transplant patients between September 2011 and December 2013. Controls were patients who remained on the inpatient unit and were matched 2:1 using age, condition (oncology vs hematopoietic stem cell transplant), and length of hospital stay. Pediatric Early Warning Scores were documented by nursing staff at least every 4 hours as part of routine care. Need for transfer was determined by a PICU physician called to evaluate the patient. A large tertiary/quaternary free-standing academic children's hospital. One hundred ten hospitalized pediatric oncology patients (42 oncology, 68 hematopoietic stem cell transplant) requiring unplanned PICU transfer and 220 matched controls. None. Using the highest score in the 24 hours prior to transfer for cases and a matched time period for controls, the Pediatric Early Warning Score was highly correlated with the need for PICU transfer overall (area under the receiver operating characteristic = 0.96), and in the oncology and hematopoietic stem cell transplant groups individually (area under the receiver operating characteristic = 0.95 and 0.96, respectively). The difference in Pediatric Early Warning Score results between the cases and controls was noted as early as 24 hours prior to PICU admission. Seventeen patients died (15.4%). Patients with higher Pediatric Early Warning Scores prior to transfer had increased PICU mortality (p = 0.028) and length of stay (p = 0.004). We demonstrate that our institution's Pediatric Early Warning Score is highly correlated with the need for unplanned PICU transfer in hospitalized oncology and hematopoietic stem cell transplant patients. Furthermore, we found an association between higher scores and PICU mortality. This is the first validation of a Pediatric Early Warning Score specific to the pediatric oncology and hematopoietic stem cell transplant populations, and supports the use of Pediatric Early Warning Scores as a method of early identification of clinical deterioration in this high-risk population.

Exploring the Role of Social Memory of Floods for Designing Flood Early Warning Operations

NASA Astrophysics Data System (ADS)

Girons Lopez, Marc; Di Baldassarre, Giuliano; Grabs, Thomas; Halldin, Sven; Seibert, Jan

2016-04-01

Early warning systems are an important tool for natural disaster mitigation practices, especially for flooding events. Warnings rely on near-future forecasts to provide time to take preventive actions before a flood occurs, thus reducing potential losses. However, on top of the technical capacities, successful warnings require an efficient coordination and communication among a range of different actors and stakeholders. The complexity of integrating the technical and social spheres of warning systems has, however, resulted in system designs neglecting a number of important aspects such as social awareness of floods thus leading to suboptimal results. A better understanding of the interactions and feedbacks among the different elements of early warning systems is therefore needed to improve their efficiency and therefore social resilience. When designing an early warning system two important decisions need to be made regarding (i) the hazard magnitude at and from which a warning should be issued and (ii) the degree of confidence required for issuing a warning. The first decision is usually taken based on the social vulnerability and climatic variability while the second one is related to the performance (i.e. accuracy) of the forecasting tools. Consequently, by estimating the vulnerability and the accuracy of the forecasts, these two variables can be optimized to minimize the costs and losses. Important parameters with a strong influence on the efficiency of warning systems such as social awareness are however not considered in their design. In this study we present a theoretical exploration of the impact of social awareness on the design of early warning systems. For this purpose we use a definition of social memory of flood events as a proxy for flood risk awareness and test its effect on the optimization of the warning system design variables. Understanding the impact of social awareness on warning system design is important to make more robust warnings that can better adapt to different social settings and more efficiently reduce vulnerability.

Managing Risks? Early Warning Systems for Climate Change

NASA Astrophysics Data System (ADS)

Sitati, A. M.; Zommers, Z. A.; Habilov, M.

2014-12-01

Early warning systems are a tool with which to minimize risks posed by climate related hazards. Although great strides have been made in developing early warning systems most deal with one hazard, only provide short-term warnings and do not reach the most vulnerable. This presentation will review research results of the United Nations Environment Programme's CLIM-WARN project. The project seeks to identify how governments can better communicate risks by designing multi-hazard early warning systems that deliver actionable warnings across timescales. Household surveys and focus group discussions were conducted in 36 communities in Kenya, Ghana and Burkina Faso in order to identify relevant climate related hazards, current response strategies and early warning needs. Preliminary results show significant variability in both risks and needs within and between countries. For instance, floods are more frequent in rural western parts of Kenya. Droughts are frequent in the north while populations in urban areas face a range of hazards - floods, droughts, disease outbreaks - that sometimes occur simultaneously. The majority of the rural population, especially women, the disabled and the elderly, do not have access to modern media such as radio, television, or internet. While 55% of rural populace never watches television, 64% of urban respondents watch television on a daily basis. Communities have different concepts of how to design warning systems. It will be a challenge for national governments to create systems that accommodate such diversity yet provide standard quality of service to all. There is a need for flexible and forward-looking early warning systems that deliver broader information about risks. Information disseminated through the system could not only include details of hazards, but also long-term adaptation options, general education, and health information, thus increasingly both capabilities and response options.

Real-Time Integration of Positioning and Accelerometer Data for Early Earthquake Warning on Canada's West Coast

NASA Astrophysics Data System (ADS)

Biffard, B.; Rosenberger, A.; Pirenne, B.; Valenzuela, M.; MacArthur, M.

2017-12-01

Ocean Networks Canada (ONC) operates ocean and coastal observatories on all three of Canada's coasts, and more particularly across the Cascadia subduction zone. The data are acquired, parsed, calibrated and archived by ONC's data management system (Oceans 2.0), with real-time event detection, reaction and access capabilities. As such, ONC is in a unique position to develop early warning systems for earthquakes, near- and far-field tsunamis and other events. ONC is leading the development of a system to alert southwestern British Columbia of an impending Cascadia subduction zone earthquake on behalf of the provincial government and with the support of the Canadian Federal Government. Similarly to other early earthquake warning systems, an array of accelerometers is used to detect the initial earthquake p-waves. This can provide 5-60 seconds of warning to subscribers who can then take action, such as stopping trains and surgeries, closing valves, taking cover, etc. To maximize the detection capability and the time available to react to a notification, instruments are placed both underwater and on land on Vancouver Island. A novel feature of ONC's system is, for land-based sites, the combination of real-time satellite positioning (GNSS) and accelerometer data in the calculations to improve earthquake intensity estimates. This results in higher accuracy, dynamic range and responsiveness than either type of sensor is capable of alone. P-wave detections and displacement data are sent from remote stations to a data centre that must calculate epicentre locations and magnitude. The latter are then delivered to subscribers with client software that, given their position, will calculate arrival time and intensity. All of this must occur with very high standards for latency, reliability and accuracy.

Fast Moment Magnitude Determination from P-wave Trains for Bucharest Rapid Early Warning System (BREWS)

NASA Astrophysics Data System (ADS)

Lizurek, Grzegorz; Marmureanu, Alexandru; Wiszniowski, Jan

2017-03-01

Bucharest, with a population of approximately 2 million people, has suffered damage from earthquakes in the Vrancea seismic zone, which is located about 170 km from Bucharest, at a depth of 80-200 km. Consequently, an earthquake early warning system (Bucharest Rapid earthquake Early Warning System or BREWS) was constructed to provide some warning about impending shaking from large earthquakes in the Vrancea zone. In order to provide quick estimates of magnitude, seismic moment was first determined from P-waves and then a moment magnitude was determined from the moment. However, this magnitude may not be consistent with previous estimates of magnitude from the Romanian Seismic Network. This paper introduces the algorithm using P-wave spectral levels and compares them with catalog estimates. The testing procedure used waveforms from about 90 events with catalog magnitudes from 3.5 to 5.4. Corrections to the P-wave determined magnitudes according to dominant intermediate depth events mechanism were tested for November 22, 2014, M5.6 and October 17, M6 events. The corrections worked well, but unveiled overestimation of the average magnitude result of about 0.2 magnitude unit in the case of shallow depth event ( H < 60 km). The P-wave spectral approach allows for the relatively fast estimates of magnitude for use in BREWS. The average correction taking into account the most common focal mechanism for radiation pattern coefficient may lead to overestimation of the magnitude for shallow events of about 0.2 magnitude unit. However, in case of events of intermediate depth of M6 the resulting M w is underestimated at about 0.1-0.2. We conclude that our P-wave spectral approach is sufficiently robust for the needs of BREWS for both shallow and intermediate depth events.

Definition of rainfall thresholds for shallow landslide early warning in Italy

NASA Astrophysics Data System (ADS)

Cancelliere, A.; Peres, D. J.

2011-12-01

Extreme rainfall is the main cause of shallow landslides. For risk mitigation, landslide early warning systems can be implemented, on the basis of rainfall monitoring and forecasting, and the use of a landslide triggering model. Several empirical, also referred to as statistical, rainfall-landslide triggering models have been proposed in the scientific literature, and used for early warning systems activated worldwide. Nonetheless, it is not clear how effective are landslide warning systems, and it is difficult to quantify the induced benefits for the implemented ones. Many rainfall thresholds have been determined through the statistical analysis of the rainfall events that have been the cause of past landslides only, thus neglecting the cases of true negatives and false positives, with negative effects on the robustness of the proposed threshold and, probably, on the effectiveness of the warning system. In the present work we address the issue of establishing warning thresholds, which, although in an approximate way, account for the related benefits. We propose the maximization of an objective function, that measures the trade-off between true and false warning issues. A ratio between the disadvantages of false positive and false negatives, not greater than one, is introduced in the function. The effect of this ratio on the determination of the thresholds is analysed. The proposed method is based on the availability of a continuous rainfall time series. In Italy, continuous rainfall time series are available from the 1920s, but practical difficulties arise for using them, as they are not published in the Hydrological Annual Reports, by the Servizio Idrografico e Mareografico Nazionale (National Hydrologic and Oceanographic Service), the manager of the most important rainfall monitoring network in Italy. However, it is possible to have a good approximation of the most intense rainfall events, in terms total rainfall, by using the data of annual maxima of precipitation for given durations, which are available in those Reports. The National Research Council's AVI database, the most complete systematic inventory of landslides events occurred in the past century in Italy, can be exploited to determine the thresholds. Hence the method has applicability for whole Italy, and uses large datasets of easy availability. As the method is based on the analysis of subdaily data, it is reliable for shallow landslides, for which low influence of antecedent precipitation on landslide triggering can be supposed. The method is illustrated through its application to case study areas in Sicily, for which there is high interest for activating early warning systems, after that the 1st October 2009 debris flow caused the loss of 37 lives and severe damage to nearby urban areas in the Peloritan Mountains.

The Earthquake Early Warning System In Southern Italy: Performance Tests And Next Developments

NASA Astrophysics Data System (ADS)

Zollo, A.; Elia, L.; Martino, C.; Colombelli, S.; Emolo, A.; Festa, G.; Iannaccone, G.

2011-12-01

PRESTo (PRobabilistic and Evolutionary early warning SysTem) is the software platform for Earthquake Early Warning (EEW) in Southern Italy, that integrates recent algorithms for real-time earthquake location, magnitude estimation and damage assessment, into a highly configurable and easily portable package. The system is under active experimentation based on the Irpinia Seismic Network (ISNet). PRESTo processes the live streams of 3C acceleration data for P-wave arrival detection and, while an event is occurring, promptly performs event detection and provides location, magnitude estimations and peak ground shaking predictions at target sites. The earthquake location is obtained by an evolutionary, real-time probabilistic approach based on an equal differential time formulation. At each time step, it uses information from both triggered and not-yet-triggered stations. Magnitude estimation exploits an empirical relationship that correlates it to the filtered Peak Displacement (Pd), measured over the first 2-4 s of P-signal. Peak ground-motion parameters at any distance can be finally estimated by ground motion prediction equations. Alarm messages containing the updated estimates of these parameters can thus reach target sites before the destructive waves, enabling automatic safety procedures. Using the real-time data streaming from the ISNet network, PRESTo has produced a bulletin for about a hundred low-magnitude events occurred during last two years. Meanwhile, the performances of the EEW system were assessed off-line playing-back the records for moderate and large events from Italy, Spain and Japan and synthetic waveforms for large historical events in Italy. These tests have shown that, when a dense seismic network is deployed in the fault area, PRESTo produces reliable estimates of earthquake location and size within 5-6 s from the event origin time (To). Estimates are provided as probability density functions whose uncertainty typically decreases with time, obtaining a stable solution within 10 s from To. The regional approach was recently integrated with a threshold-based early warning method for the definition of alert levels and the estimation of the Potential Damaged Zone (PDZ) in which the highest intensity levels are expected. The dominant period Tau_c and the peak displacement (Pd) are simultaneously measured in a 3s window after the first P-arrival time. Pd and Tau_c are then compared with threshold values, previously established through an empirical regression analysis, that define a decisional table with four alert levels. According to the real-time measured values of Pd and tau_c, each station provides a local alert level that can be used to warn distant sites and to define the extent of the PDZ. The integrated system was validated off-line for the M6.3, 2009 Central Italy earthquake and ten large Japanese events, due to the low-magnitude events currently occurring in Irpinia. The results confirmed the feasibility and the robustness of such an approach, providing reliable predictions of the earthquake damaging effects, that is a relevant information for the efficient planning of the rescue operations in the immediate post-event emergency phase.

Early warning system for Douglas-fir tussock moth outbreaks in the Western United States.

Treesearch

Gary E. Daterman; John M. Wenz; Katharine A. Sheehan

2004-01-01

The Early Warning System is a pheromone-based trapping system used to detect outbreaks of Douglas-fir tussock moth (DFTM, Orgyia pseudotsugata) in the western United States. Millions of acres are susceptible to DFTM defoliation, but Early Warning System monitoring focuses attention only on the relatively limited areas where outbreaks may be...

Enhancing Community Based Early Warning Systems in Nepal with Flood Forecasting Using Local and Global Models

NASA Astrophysics Data System (ADS)

Dugar, Sumit; Smith, Paul; Parajuli, Binod; Khanal, Sonu; Brown, Sarah; Gautam, Dilip; Bhandari, Dinanath; Gurung, Gehendra; Shakya, Puja; Kharbuja, RamGopal; Uprety, Madhab

2017-04-01

Operationalising effective Flood Early Warning Systems (EWS) in developing countries like Nepal poses numerous challenges, with complex topography and geology, sparse network of river and rainfall gauging stations and diverse socio-economic conditions. Despite these challenges, simple real-time monitoring based EWSs have been in place for the past decade. A key constraint of these simple systems is the very limited lead time for response - as little as 2-3 hours, especially for rivers originating from steep mountainous catchments. Efforts to increase lead time for early warning are focusing on imbedding forecasts into the existing early warning systems. In 2016, the Nepal Department of Hydrology and Meteorology (DHM) piloted an operational Probabilistic Flood Forecasting Model in major river basins across Nepal. This comprised a low data approach to forecast water levels, developed jointly through a research/practitioner partnership with Lancaster University and WaterNumbers (UK) and the International NGO Practical Action. Using Data-Based Mechanistic Modelling (DBM) techniques, the model assimilated rainfall and water levels to generate localised hourly flood predictions, which are presented as probabilistic forecasts, increasing lead times from 2-3 hours to 7-8 hours. The Nepal DHM has simultaneously started utilizing forecasts from the Global Flood Awareness System (GLoFAS) that provides streamflow predictions at the global scale based upon distributed hydrological simulations using numerical ensemble weather forecasts from the ECMWF (European Centre for Medium-Range Weather Forecasts). The aforementioned global and local models have already affected the approach to early warning in Nepal, being operational during the 2016 monsoon in the West Rapti basin in Western Nepal. On 24 July 2016, GLoFAS hydrological forecasts for the West Rapti indicated a sharp rise in river discharge above 1500 m3/sec (equivalent to the river warning level at 5 meters) with 53% probability of exceeding the Medium Level Alert in two days. Rainfall stations upstream of the West Rapti catchment recorded heavy rainfall on 26 July, and localized forecasts from the probabilistic model at 8 am suggested that the water level would cross a pre-determined warning level in the next 3 hours. The Flood Forecasting Section at DHM issued a flood advisory, and disseminated SMS flood alerts to more than 13,000 at-risk people residing along the floodplains. Water levels crossed the danger threshold (5.4 meters) at 11 am, peaking at 8.15 meters at 10 pm. Extension of the warning lead time from probabilistic forecasts was significant in minimising the risk to lives and livelihoods as communities gained extra time to prepare, evacuate and respond. Likewise, longer timescale forecasts from GLoFAS could be potentially linked with no-regret early actions leading to improved preparedness and emergency response. These forecasting tools have contributed to enhance the effectiveness and efficiency of existing community based systems, increasing the lead time for response. Nevertheless, extensive work is required on appropriate ways to interpret and disseminate probabilistic forecasts having longer (2-14 days) and shorter (3-5 hours) time horizon for operational deployment as there are numerous uncertainties associated with predictions.

Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis

NASA Astrophysics Data System (ADS)

Li, Yuanyuan; Jin, Suoqin; Lei, Lei; Pan, Zishu; Zou, Xiufen

2015-03-01

The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.

The Quake Catcher Network: Cyberinfrastructure Bringing Seismology into Schools and Homes

NASA Astrophysics Data System (ADS)

Lawrence, J. F.; Cochran, E. S.

2007-12-01

We propose to implement a high density, low cost strong-motion network for rapid response and early warning by placing sensors in schools, homes, and offices. The Quake Catcher Network (QCN) will employ existing networked laptops and desktops to form the world's largest high-density, distributed computing seismic network. Costs for this network will be minimal because the QCN will use 1) strong motion sensors (accelerometers) already internal to many laptops and 2) nearly identical low-cost universal serial bus (USB) accelerometers for use with desktops. The Berkeley Open Infrastructure for Network Computing (BOINC!) provides a free, proven paradigm for involving the public in large-scale computational research projects. As evidenced by the SETI@home program and others, individuals are especially willing to donate their unused computing power to projects that they deem relevant, worthwhile, and educational. The client- and server-side software will rapidly monitor incoming seismic signals, detect the magnitudes and locations of significant earthquakes, and may even provide early warnings to other computers and users before they can feel the earthquake. The software will provide the client-user with a screen-saver displaying seismic data recorded on their laptop, recently detected earthquakes, and general information about earthquakes and the geosciences. Furthermore, this project will install USB sensors in K-12 classrooms as an educational tool for teaching science. Through a variety of interactive experiments students will learn about earthquakes and the hazards earthquakes pose. For example, students can learn how the vibrations of an earthquake decrease with distance by jumping up and down at increasing distances from the sensor and plotting the decreased amplitude of the seismic signal measured on their computer. We hope to include an audio component so that students can hear and better understand the difference between low and high frequency seismic signals. The QCN will provide a natural way to engage students and the public in earthquake detection and research.

Computing Systemic Risk Using Multiple Behavioral and Keystone Networks: The Emergence of a Crisis in Primate Societies and Banks*

PubMed Central

Fushing, Hsieh; Jordà, Òscar; Beisner, Brianne; McCowan, Brenda

2015-01-01

What do the behavior of monkeys in captivity and the financial system have in common? The nodes in such social systems relate to each other through multiple and keystone networks, not just one network. Each network in the system has its own topology, and the interactions among the system’s networks change over time. In such systems, the lead into a crisis appears to be characterized by a decoupling of the networks from the keystone network. This decoupling can also be seen in the crumbling of the keystone’s power structure toward a more horizontal hierarchy. This paper develops nonparametric methods for describing the joint model of the latent architecture of interconnected networks in order to describe this process of decoupling, and hence provide an early warning system of an impending crisis. PMID:26056422

Multi-model data fusion to improve an early warning system for hypo-/hyperglycemic events.

PubMed

Botwey, Ransford Henry; Daskalaki, Elena; Diem, Peter; Mougiakakou, Stavroula G

2014-01-01

Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.

Development of systems for detection, early warning, and control of pipeline leakage in drinking water distribution: a case study.

PubMed

Li, Weifeng; Ling, Wencui; Liu, Suoxiang; Zhao, Jing; Liu, Ruiping; Chen, Qiuwen; Qiang, Zhimin; Qu, Jiuhui

2011-01-01

Water leakage in drinking water distribution systems is a serious problem for many cities and a huge challenge for water utilities. An integrated system for the detection, early warning, and control of pipeline leakage has been developed and successfully used to manage the pipeline networks in selected areas of Beijing. A method based on the geographic information system has been proposed to quickly and automatically optimize the layout of the instruments which detect leaks. Methods are also proposed to estimate the probability of each pipe segment leaking (on the basis of historic leakage data), and to assist in locating the leakage points (based on leakage signals). The district metering area (DMA) strategy is used. Guidelines and a flowchart for establishing a DMA to manage the large-scale looped networks in Beijing are proposed. These different functions have been implemented into a central software system to simplify the day-to-day use of the system. In 2007 the system detected 102 non-obvious leakages (i.e., 14.2% of the total detected in Beijing) in the selected areas, which was estimated to save a total volume of 2,385,000 m3 of water. These results indicate the feasibility, efficiency and wider applicability of this system.

Body size shifts and early warning signals precede the historic collapse of whale stocks.

PubMed

Clements, Christopher F; Blanchard, Julia L; Nash, Kirsty L; Hindell, Mark A; Ozgul, Arpat

2017-06-22

Predicting population declines is a key challenge in the face of global environmental change. Abundance-based early warning signals have been shown to precede population collapses; however, such signals are sensitive to the low reliability of abundance estimates. Here, using historical data on whales harvested during the 20th century, we demonstrate that early warning signals can be present not only in the abundance data, but also in the more reliable body size data of wild populations. We show that during the period of commercial whaling, the mean body size of caught whales declined dramatically (by up to 4 m over a 70-year period), leading to early warning signals being detectable up to 40 years before the global collapse of whale stocks. Combining abundance and body size data can reduce the length of the time series required to predict collapse, and decrease the chances of false positive early warning signals.

Landslide risk mitigation by means of early warning systems

NASA Astrophysics Data System (ADS)

Calvello, Michele

2017-04-01

Among the many options available to mitigate landslide risk, early warning systems may be used where, in specific circumstances, the risk to life increases above tolerable levels. A coherent framework to classify and analyse landslide early warning systems (LEWS) is herein presented. Once the objectives of an early warning strategy are defined depending on the scale of analysis and the type of landslides to address, the process of designing and managing a LEWS should synergically employ technical and social skills. A classification scheme for the main components of LEWSs is proposed for weather-induced landslides. The scheme is based on a clear distinction among: i) the landslide model, i.e. a functional relationship between weather characteristics and landslide events considering the geotechnical, geomorphological and hydro-geological characterization of the area as well as an adequate monitoring strategy; ii) the warning model, i.e. the landslide model plus procedures to define the warning events and to issue the warnings; iii) the warning system, i.e. the warning model plus warning dissemination procedures, communication and education tools, strategies for community involvement and emergency plans. Each component of a LEWS is related to a number of actors involved with their deployment, operational activities and management. For instance, communication and education, community involvement and emergency plans are all significantly influenced by people's risk perception and by operational aspects system managers need to address in cooperation with scientists.

Accuracy of a pediatric early warning score in the recognition of clinical deterioration.

PubMed

Miranda, Juliana de Oliveira Freitas; Camargo, Climene Laura de; Nascimento, Carlito Lopes; Portela, Daniel Sales; Monaghan, Alan

2017-07-10

to evaluate the accuracy of the version of the Brighton Pediatric Early Warning Score translated and adapted for the Brazilian context, in the recognition of clinical deterioration. a diagnostic test study to measure the accuracy of the Brighton Pediatric Early Warning Score for the Brazilian context, in relation to a reference standard. The sample consisted of 271 children, aged 0 to 10 years, blindly evaluated by a nurse and a physician, specialists in pediatrics, with interval of 5 to 10 minutes between the evaluations, for the application of the Brighton Pediatric Early Warning Score for the Brazilian context and of the reference standard. The data were processed and analyzed using the Statistical Package for the Social Sciences and VassarStats.net programs. The performance of the Brighton Pediatric Early Warning Score for the Brazilian context was evaluated through the indicators of sensitivity, specificity, predictive values, area under the ROC curve, likelihood ratios and post-test probability. the Brighton Pediatric Early Warning Score for the Brazilian context showed sensitivity of 73.9%, specificity of 95.5%, positive predictive value of 73.3%, negative predictive value of 94.7%, area under Receiver Operating Characteristic Curve of 91.9% and the positive post-test probability was 80%. the Brighton Pediatric Early Warning Score for the Brazilian context, presented good performance, considered valid for the recognition of clinical deterioration warning signs of the children studied. avaliar a acurácia da versão traduzida e adaptada do Brighton Paediatric Early Warning Score para o contexto brasileiro, no reconhecimento da deterioração clínica. estudo de teste diagnóstico para medir a acurácia do Brighton Paediatric Early Warning Score, para o contexto brasileiro, em relação a um padrão de referência. A amostra foi composta por 271 crianças de 0 a 10 anos, avaliadas de forma cega por uma enfermeira e um médico, especialistas em pediatria, com intervalo de 5 a 10 minutos entre as avaliações, para aplicação do Brighton Paediatric Early Warning Score, para o contexto brasileiro e do padrão de referência. Os dados foram processados e analisados nos programas Statistical Package for the Social Sciences e VassarStats.net. O desempenho do Brighton Paediatric Early Warning Score para o contexto brasileiro foi avaliado por meio dos indicadores de sensibilidade, especificidade, valores preditivos, área sob a curva ROC, razões de probabilidades e probabilidade pós-teste. o Brighton Paediatric Early Warning Score para o contexto brasileiro apresentou sensibilidade de 73,9%, especificidade de 95,5%, valor preditivo positivo de 73,3%, valor preditivo negativo de 94,7%, área sob a Receiver Operating Characteristic Curve de 91,9% e a probabilidade pós-teste positivo foi de 80%. o Brighton Paediatric Early Warning Score, para o contexto brasileiro, apresentou bom desempenho, considerado válido para o reconhecimento de sinais de alerta de deterioração clínica das crianças estudadas. evaluar la precisión de la versión traducida y adaptada del Brighton Paediatric Early Warning Score para el contexto brasileño, en el reconocimiento de la deterioración clínica. estudio de test diagnóstico para medir la precisión del Brighton Paediatric Early Warning Score para el contexto brasileño, en relación a un estándar de referencia. La muestra estuvo compuesta por 271 niños de 0 a 10 años, evaluadas de forma ciega por especialistas en pediatría, una enfermera y un médico, con intervalo de 5 a 10 minutos entre las evaluaciones, para aplicación del Brighton Paediatric Early Warning Score para el contexto brasileño. Los datos fueron procesados y analizados en los programas Statistical Package for the Social Sciences y VassarStats.net. El desempeño del Brighton Paediatric Early Warning Score para el contexto brasileño fue evaluado por medio de los indicadores de sensibilidad, especificidad, valores predictivos, área debajo de la curva ROC, razones de probabilidades y probabilidad postest. el Brighton Paediatric Early Warning Score para el contexto brasileño presentó sensibilidad de 73,9%, especificidad de 95,5%, valor predictivo positivo de 73,3%, valor predictivo negativo de 94,7%, área bajo la Receiver Operating Characteristic Curve de 91,9% y la probabilidad postest positivo fue de 80%. el Brighton Paediatric Early Warning Score para el contexto brasileño, presentó buen desempeño, considerado válido para el reconocimiento de señales de alerta de deterioración clínica de los niños estudiados.

A national survey of obstetric early warning systems in the United Kingdom: five years on.

PubMed

Isaacs, R A; Wee, M Y K; Bick, D E; Beake, S; Sheppard, Z A; Thomas, S; Hundley, V; Smith, G B; van Teijlingen, E; Thomas, P W

2014-07-01

The Confidential Enquiries into Maternal Deaths in the UK have recommended obstetric early warning systems for early identification of clinical deterioration to reduce maternal morbidity and mortality. This survey explored early warning systems currently used by maternity units in the UK. An electronic questionnaire was sent to all 205 lead obstetric anaesthetists under the auspices of the Obstetric Anaesthetists' Association, generating 130 (63%) responses. All respondents reported use of an obstetric early warning system, compared with 19% in a similar survey in 2007. Respondents agreed that the six most important physiological parameters to record were respiratory rate, heart rate, temperature, systolic and diastolic blood pressure and oxygen saturation. One hundred and eighteen (91%) lead anaesthetists agreed that early warning systems helped to prevent obstetric morbidity. Staffing pressures were perceived as the greatest barrier to their use, and improved audit, education and training for healthcare professionals were identified as priority areas. © 2014 The Association of Anaesthetists of Great Britain and Ireland.

Most Common Foodborne Pathogens and Mycotoxins on Fresh Produce: A Review of Recent Outbreaks.

PubMed

Yeni, F; Yavaş, S; Alpas, H; Soyer, Y

2016-07-03

Every year millions of people are affected and thousands of them die due to infections and intoxication as a result of foodborne outbreaks, which also cause billions of dollars' worth of damage, public health problems, and agricultural product loss. A considerable portion of these outbreaks is related to fresh produce and caused by foodborne pathogens on fresh produce and mycotoxins. Escherichia coli O104:H4 outbreak, occurred in Germany in 2011, has attracted a great attention on foodborne outbreaks caused by contaminated fresh produce, and especially the vulnerability and gaps in the early warning and notification networks in the surveillance systems in all around the world. In the frame of this paper, we reviewed the most common foodborne pathogens on fresh produce, traceback investigations of the outbreaks caused by these pathogens, and lastly international early warning and notification systems, including PulseNet International and Rapid Alert System for Food and Feed, aiming to detect foodborne outbreaks.

Floods in 2002 and 2013: comparing flood warnings and emergency measures from the perspective of affected parties

NASA Astrophysics Data System (ADS)

Kreibich, Heidi; Pech, Ina; Schröter, Kai; Müller, Meike; Thieken, Annegret

2016-04-01

Early warning is essential for protecting people and mitigating damage in case of flood events. However, early warning is only helpful if the flood-endangered parties are reached by the warning and if they know how to react effectively. Finding suitable methods for communicating helpful warnings to the "last mile" remains a challenge, but not much information is available. Surveys were undertaken after the August 2002 and the June 2013 floods in Germany, asking affected private households and companies about warnings they received and emergency measures they undertook. Results show, that in 2002 early warning did not work well: in too many areas warnings came too late or were too imprecise and many people (27%) and companies (45%) did not receive a flood warning. Afterwards, the warning systems were significantly improved, so that in 2013 only a small share of the affected people (7%) and companies (7 %) was not reached by any warning. Additionally, private households and companies were hardly aware of the flood risk in the Elbe catchment before 2002, mainly due to a lack of flood experience. For instance, in 2002 only 14% of private households clearly knew how to protect themselves and their assets when the warning reached them, in 2013 this fraction was 46 %. Although the share of companies which had an emergency plan in place had increased from 10 % in 2002 to 26 % in 2013, and the share of those conducting regular emergency exercises had increased from 4 % to 13 %, there is still plenty of room for improvement. Therefore, integrated early warning systems from monitoring through to the reaction of the affected parties as well as effective risk and emergency communication need continuous further improvement to protect people and mitigate residual risks in case of floods.

Neonatal Early Warning Tools for recognising and responding to clinical deterioration in neonates cared for in the maternity setting: A retrospective case-control study.

PubMed

Paliwoda, Michelle; New, Karen; Bogossian, Fiona

2016-09-01

All newborns are at risk of deterioration as a result of failing to make the transition to extra uterine life. Signs of deterioration can be subtle and easily missed. It has been postulated that the use of an Early Warning Tool may assist clinicians in recognising and responding to signs of deterioration earlier in neonates, thereby preventing a serious adverse event. To examine whether observations from a Standard Observation Tool, applied to three neonatal Early Warning Tools, would hypothetically trigger an escalation of care more frequently than actual escalation of care using the Standard Observation Tool. A retrospective case-control study. A maternity unit in a tertiary public hospital in Australia. Neonates born in 2013 of greater than or equal to 34(+0) weeks gestation, admitted directly to the maternity ward from their birthing location and whose subsequent deterioration required admission to the neonatal unit, were identified as cases from databases of the study hospital. Each case was matched with three controls, inborn during the same period and who did not experience deterioration and neonatal unit admission. Clinical and physiological data recorded on a Standard Observation Tool, from time of admission to the maternity ward, for cases and controls were charted onto each of three Early Warning Tools. The primary outcome was whether the tool 'triggered an escalation of care'. Descriptive statistics (n, %, Mean and SD) were employed. Cases (n=26) comprised late preterm, early term and post-term neonates and matched by gestational age group with 3 controls (n=78). Overall, the Standard Observation Tool triggered an escalation of care for 92.3% of cases compared to the Early Warning Tools; New South Wales Health 80.8%, United Kingdom Newborn Early Warning Chart 57.7% and The Australian Capital Territory Neonatal Early Warning Score 11.5%. Subgroup analysis by gestational age found differences between the tools in hypothetically triggering an escalation of care. The Standard Observation Tool triggered an escalation of care more frequently than the Early Warning Tools, which may be as a result of behavioural data captured on the Standard Observation Tool and escalated, which could not be on the Early Warning Tools. Findings demonstrate that a single tool applied to all gestational age ranges may not be effective in identifying early deterioration or may over trigger an escalation of care. Further research is required into the sensitivity and specificity of Early Warning Tools in neonatal sub-populations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Early warning signals of regime shifts in coupled human–environment systems

PubMed Central

Bauch, Chris T.; Sigdel, Ram; Pharaon, Joe; Anand, Madhur

2016-01-01

In complex systems, a critical transition is a shift in a system’s dynamical regime from its current state to a strongly contrasting state as external conditions move beyond a tipping point. These transitions are often preceded by characteristic early warning signals such as increased system variability. However, early warning signals in complex, coupled human–environment systems (HESs) remain little studied. Here, we compare critical transitions and their early warning signals in a coupled HES model to an equivalent environment model uncoupled from the human system. We parameterize the HES model, using social and ecological data from old-growth forests in Oregon. We find that the coupled HES exhibits a richer variety of dynamics and regime shifts than the uncoupled environment system. Moreover, the early warning signals in the coupled HES can be ambiguous, heralding either an era of ecosystem conservationism or collapse of both forest ecosystems and conservationism. The presence of human feedback in the coupled HES can also mitigate the early warning signal, making it more difficult to detect the oncoming regime shift. We furthermore show how the coupled HES can be “doomed to criticality”: Strategic human interactions cause the system to remain perpetually in the vicinity of a collapse threshold, as humans become complacent when the resource seems protected but respond rapidly when it is under immediate threat. We conclude that the opportunities, benefits, and challenges of modeling regime shifts and early warning signals in coupled HESs merit further research. PMID:27815533

Efficient detection of contagious outbreaks in massive metropolitan encounter networks

PubMed Central

Sun, Lijun; Axhausen, Kay W.; Lee, Der-Horng; Cebrian, Manuel

2014-01-01

Physical contact remains difficult to trace in large metropolitan networks, though it is a key vehicle for the transmission of contagious outbreaks. Co-presence encounters during daily transit use provide us with a city-scale time-resolved physical contact network, consisting of 1 billion contacts among 3 million transit users. Here, we study the advantage that knowledge of such co-presence structures may provide for early detection of contagious outbreaks. We first examine the “friend sensor” scheme - a simple, but universal strategy requiring only local information - and demonstrate that it provides significant early detection of simulated outbreaks. Taking advantage of the full network structure, we then identify advanced “global sensor sets”, obtaining substantial early warning times savings over the friends sensor scheme. Individuals with highest number of encounters are the most efficient sensors, with performance comparable to individuals with the highest travel frequency, exploratory behavior and structural centrality. An efficiency balance emerges when testing the dependency on sensor size and evaluating sensor reliability; we find that substantial and reliable lead-time could be attained by monitoring only 0.01% of the population with the highest degree. PMID:24903017

Using Satellite Data to Build Climate Resilience: A Novel East Africa Drought Monitor

NASA Astrophysics Data System (ADS)

Slinski, K.; Hogue, T. S.; McCray, J. E.

2016-12-01

East Africa is affected by recurrent drought. The 2015-2016 El Niño triggered a severe drought across East Africa causing serious impacts to regional water security, health, and livelihoods. Ethiopia was the hardest hit, with the United Nations Office for the Coordination of Humanitarian Affairs calling the recent drought the worst in 50 years. Resources to monitor the severity and progression of droughts are a critical component to disaster risk reduction, but are challenging to implement in regions with sparse data collection networks such as East Africa. Satellite data is used by the United Nations Food and Agriculture Organization Global Information and Early Warning System, the USAID Famine Early Warning System, and the Africa Drought and Flood Monitor. These systems use remotely sensed vegetation, soil moisture, and meteorological data to develop drought indices. However, they do not directly monitor impacts to water resources, which is necessary to appropriately target drought mitigation efforts. The current study combines new radar data from the European Space Agency's Sentinel-1 mission with satellite imagery to perform a retrospective analysis of the impact of the 2015-2016 drought in East Africa on regional surface water. Inland water body extents during the drought are compared to historical trends to identify the most severely impacted areas. The developed tool has the potential to support on-the-ground humanitarian relief efforts and to refine predictions of water scarcity and crop impacts from existing hydrologic models and famine early warning systems.

Web-based Tsunami Early Warning System with instant Tsunami Propagation Calculations in the GPU Cloud

NASA Astrophysics Data System (ADS)

Hammitzsch, M.; Spazier, J.; Reißland, S.

2014-12-01

Usually, tsunami early warning and mitigation systems (TWS or TEWS) are based on several software components deployed in a client-server based infrastructure. The vast majority of systems importantly include desktop-based clients with a graphical user interface (GUI) for the operators in early warning centers. However, in times of cloud computing and ubiquitous computing the use of concepts and paradigms, introduced by continuously evolving approaches in information and communications technology (ICT), have to be considered even for early warning systems (EWS). Based on the experiences and the knowledge gained in three research projects - 'German Indonesian Tsunami Early Warning System' (GITEWS), 'Distant Early Warning System' (DEWS), and 'Collaborative, Complex, and Critical Decision-Support in Evolving Crises' (TRIDEC) - new technologies are exploited to implement a cloud-based and web-based prototype to open up new prospects for EWS. This prototype, named 'TRIDEC Cloud', merges several complementary external and in-house cloud-based services into one platform for automated background computation with graphics processing units (GPU), for web-mapping of hazard specific geospatial data, and for serving relevant functionality to handle, share, and communicate threat specific information in a collaborative and distributed environment. The prototype in its current version addresses tsunami early warning and mitigation. The integration of GPU accelerated tsunami simulation computations have been an integral part of this prototype to foster early warning with on-demand tsunami predictions based on actual source parameters. However, the platform is meant for researchers around the world to make use of the cloud-based GPU computation to analyze other types of geohazards and natural hazards and react upon the computed situation picture with a web-based GUI in a web browser at remote sites. The current website is an early alpha version for demonstration purposes to give the concept a whirl and to shape science's future. Further functionality, improvements and possible profound changes have to implemented successively based on the users' evolving needs.

Massachusetts Early Warning Indicator System (EWIS). "Technical Descriptions of Risk Model Development": Middle and High School Age Groupings (Grades 7-12)

ERIC Educational Resources Information Center

Massachusetts Department of Elementary and Secondary Education, 2013

2013-01-01

The Massachusetts Department of Elementary and Secondary Education (Department) created the grades 1-12 Early Warning Indicator System (EWIS) in response to district interest in the Early Warning Indicator Index (EWII) that the Department previously created for rising grade 9 students. Districts shared that the EWII data were helpful, but also…

Clinical significance of automatic warning function of cardiac remote monitoring systems in preventing acute cardiac episodes

PubMed Central

Chen, Shou-Qiang; Xing, Shan-Shan; Gao, Hai-Qing

2014-01-01

Objective: In addition to ambulatory Holter electrocardiographic recording and transtelephonic electrocardiographic monitoring (TTM), a cardiac remote monitoring system can provide an automatic warning function through the general packet radio service (GPRS) network, enabling earlier diagnosis, treatment and improved outcome of cardiac diseases. The purpose of this study was to estimate its clinical significance in preventing acute cardiac episodes. Methods: Using 2 leads (V1 and V5 leads) and the automatic warning mode, 7160 patients were tested with a cardiac remote monitoring system from October 2004 to September 2007. If malignant arrhythmias or obvious ST-T changes appeared in the electrocardiogram records was automatically transferred to the monitoring center, the patient and his family members were informed, and the corresponding precautionary or therapeutic measures were implemented immediately. Results: In our study, 274 cases of malignant arrhythmia, including sinus standstill and ventricular tachycardia, and 43 cases of obvious ST-segment elevation were detected and treated. Because of early detection, there was no death or deformity. Conclusions: A cardiac remote monitoring system providing an automatic warning function can play an important role in preventing acute cardiac episodes. PMID:25674124

Land Surface Modeling Applications for Famine Early Warning

NASA Astrophysics Data System (ADS)

McNally, A.; Verdin, J. P.; Peters-Lidard, C. D.; Arsenault, K. R.; Wang, S.; Kumar, S.; Shukla, S.; Funk, C. C.; Pervez, M. S.; Fall, G. M.; Karsten, L. R.

2015-12-01

AGU 2015 Fall Meeting Session ID#: 7598 Remote Sensing Applications for Water Resources Management Land Surface Modeling Applications for Famine Early Warning James Verdin, USGS EROS Christa Peters-Lidard, NASA GSFC Amy McNally, NASA GSFC, UMD/ESSIC Kristi Arsenault, NASA GSFC, SAIC Shugong Wang, NASA GSFC, SAIC Sujay Kumar, NASA GSFC, SAIC Shrad Shukla, UCSB Chris Funk, USGS EROS Greg Fall, NOAA Logan Karsten, NOAA, UCAR Famine early warning has traditionally required close monitoring of agro-climatological conditions, putting them in historical context, and projecting them forward to anticipate end-of-season outcomes. In recent years, it has become necessary to factor in the effects of a changing climate as well. There has also been a growing appreciation of the linkage between food security and water availability. In 2009, Famine Early Warning Systems Network (FEWS NET) science partners began developing land surface modeling (LSM) applications to address these needs. With support from the NASA Applied Sciences Program, an instance of the Land Information System (LIS) was developed to specifically support FEWS NET. A simple crop water balance model (GeoWRSI) traditionally used by FEWS NET took its place alongside the Noah land surface model and the latest version of the Variable Infiltration Capacity (VIC) model, and LIS data readers were developed for FEWS NET precipitation forcings (NOAA's RFE and USGS/UCSB's CHIRPS). The resulting system was successfully used to monitor and project soil moisture conditions in the Horn of Africa, foretelling poor crop outcomes in the OND 2013 and MAM 2014 seasons. In parallel, NOAA created another instance of LIS to monitor snow water resources in Afghanistan, which are an early indicator of water availability for irrigation and crop production. These successes have been followed by investment in LSM implementations to track and project water availability in Sub-Saharan Africa and Yemen, work that is now underway. Adoption of LSM and data assimilation technology has enabled FEWS NET to take greater advantage of remote sensing observations to robustly estimate key agro-climatological states, like soil moisture and snow water equivalent, building confidence in our understanding of conditions in data sparse regions of the world.

Early Warning Signals of Ecological Transitions: Methods for Spatial Patterns

PubMed Central

Brock, William A.; Carpenter, Stephen R.; Ellison, Aaron M.; Livina, Valerie N.; Seekell, David A.; Scheffer, Marten; van Nes, Egbert H.; Dakos, Vasilis

2014-01-01

A number of ecosystems can exhibit abrupt shifts between alternative stable states. Because of their important ecological and economic consequences, recent research has focused on devising early warning signals for anticipating such abrupt ecological transitions. In particular, theoretical studies show that changes in spatial characteristics of the system could provide early warnings of approaching transitions. However, the empirical validation of these indicators lag behind their theoretical developments. Here, we summarize a range of currently available spatial early warning signals, suggest potential null models to interpret their trends, and apply them to three simulated spatial data sets of systems undergoing an abrupt transition. In addition to providing a step-by-step methodology for applying these signals to spatial data sets, we propose a statistical toolbox that may be used to help detect approaching transitions in a wide range of spatial data. We hope that our methodology together with the computer codes will stimulate the application and testing of spatial early warning signals on real spatial data. PMID:24658137

The GNSS-based Ground Tracking System (GTS) of GFZ; from GITEWS to PROTECTS and beyond

NASA Astrophysics Data System (ADS)

Falck, Carsten; Merx, Alexander; Ramatschi, Markus

2013-04-01

Introduction An automatic system for the near real-time determination and visualization of ground motions, respectively co-seismic deformations of the Earth's surface, was developed by GFZ (German Research Centre for Geosciences) within the project GITEWS (German Indonesian Tsunami Early Warning System). The system is capable to deliver 3D-displacement vectors for locations with appropriate GPS-equipment in the vicinity of an earthquake's epicenter with a delay of only a few minutes. These vectors can help to assess the earthquake causing tectonic movements, which must be known to make reliable early warning predictions, e.g., concerning the generation of tsunami waves. The GTS (Ground Tracking System) has been integrated into InaTEWS (Indonesian Tsunami Early Warning System) and is in operation at the national warning center in Jakarta since November 2008. After the end of the project GITEWS GFZ continues to support the GTS in Indonesia within the frame of PROTECTS (Project for Training, Education and Consulting for Tsunami Early Warning Systems) and recently some new developments have been introduced. We now aim to make further use of the achievements made, e.g., by developing a license model for the GTS software package. Motivation After the Tsunami of 26th December 2004 the German government initiated the GITEWS project to develop the main components for a tsunami early warning system in Indonesia. The GFZ, as the consortial leader of GITEWS, had several work packages, most of them related to sensor systems. The geodetic branch (Department 1) of GFZ was assigned to develop a GNSS-based component, which since then is known as the GTS (Ground Tracking System). System benefit The ground motion information delivered by the GTS is a valuable source for a fast understanding of an earthquake's mechanism with a high relevance to assess the probability and magnitude of a potentially following tsunami. The system may detect highest displacement vector values, where seismic systems may tend to have problems with the determination of earthquake magnitudes, e.g. close to an earthquake epicenter. By considering displacement vectors the GTS may significantly support the decision finding process whether a tsunami has been generated. Brief system description The GTS may be divided into three main components: 1) The data acquisition component receives and manages data from GNSS-stations being transferred either in real-time, file based or both in parallel, including, e.g., format conversions and real-time spreading to other services. It also acquires the most actual auxiliary data needed for data processing, e.g., GNSS-satellite orbit data or, in case of internet problems, generates them from ephemeris broadcast transmissions, received by the connected GNSS-network stations. 2) The automatic GNSS-data processing unit calculates coordinate time series for all GNSS-stations providing data. The processing kernel is the robust working and well supported »Bernese GPS Software«, but wrapped into adaptations for a fully automatic near real-time processing. The final products of this unit are 3D-displacement vectors, which are calculated as differences to the mean coordinates of the latest timespan prior to an earthquake. 3) The graphical user interface (GUI) of the GTS supports both, a quick view for all staff members at the warning centre (24h/7d shifts) and deeper analysis by experts. The states of the connected GNSS-networks and of the automatic data processing system are displayed. Other views are available, e.g., to check intermediate processing steps or historic data. The GTS final products, the 3D-displacement vectors, are displayed as arrows and bars on a map view. The GUI system is implemented as a web-based application and allows all views to be displayed on many screens at the same time, even at remote locations. Acknowledgements The projects GITEWS (German Indonesian Tsunami Early Warning System) and PROTECTS (Project for Training, Education and Consulting for Tsunami Early Warning System) are carried out by a large group of scientists and engineers from (GFZ) German Research Centre for Geosciences and its partners from the German Aerospace Centre (DLR), the Alfred Wegener Institute for Polar and Marine Research (AWI), the GKSS Research Centre, the Konsortium Deutsche Meeresforschung (KDM), the Leibniz Institute for Marine Sciences (IFM-GEOMAR), the United Nations University (UNU), the Federal Institute for Geosciences and Natural Resources (BGR), the German Agency for Technical Cooperation (GTZ) and other international partners. Funding is provided by the German Federal Ministry for Education and Research (BMBF), Grant 03TSU01 and 03TSU07.

Study on the early warning mechanism for the security of blast furnace hearths

NASA Astrophysics Data System (ADS)

Zhao, Hong-bo; Huo, Shou-feng; Cheng, Shu-sen

2013-04-01

The campaign life of blast furnace (BF) hearths has become the limiting factor for safety and high efficiency production of modern BFs. However, the early warning mechanism of hearth security has not been clear. In this article, based on heat transfer calculations, heat flux and erosion monitoring, the features of heat flux and erosion were analyzed and compared among different types of hearths. The primary detecting elements, mathematical models, evaluating standards, and warning methods were discussed. A novel early warning mechanism with the three-level quantificational standards was proposed for BF hearth security.

Research on early-warning index of the spatial temperature field in concrete dams.

PubMed

Yang, Guang; Gu, Chongshi; Bao, Tengfei; Cui, Zhenming; Kan, Kan

2016-01-01

Warning indicators of the dam body's temperature are required for the real-time monitoring of the service conditions of concrete dams to ensure safety and normal operations. Warnings theories are traditionally targeted at a single point which have limitations, and the scientific warning theories on global behavior of the temperature field are non-existent. In this paper, first, in 3D space, the behavior of temperature field has regional dissimilarity. Through the Ward spatial clustering method, the temperature field was divided into regions. Second, the degree of order and degree of disorder of the temperature monitoring points were defined by the probability method. Third, the weight values of monitoring points of each regions were explored via projection pursuit. Forth, a temperature entropy expression that can describe degree of order of the spatial temperature field in concrete dams was established. Fifth, the early-warning index of temperature entropy was set up according to the calculated sequential value of temperature entropy. Finally, project cases verified the feasibility of the proposed theories. The early-warning index of temperature entropy is conducive to the improvement of early-warning ability and safety management levels during the operation of high concrete dams.

CISN ShakeAlert: Improving the Virtual Seismologist (VS) earthquake early warning framework to provide faster, more robust warning information

NASA Astrophysics Data System (ADS)

Meier, M.; Cua, G. B.; Wiemer, S.; Fischer, M.

2011-12-01

The Virtual Seismologist (VS) method is a Bayesian approach to regional network-based earthquake early warning (EEW) that uses observed phase arrivals, ground motion amplitudes and selected prior information to estimate earthquake magnitude, location and origin time, and predict the distribution of peak ground motion throughout a region using envelope attenuation relationships. Implementation of the VS algorithm in California is an on-going effort of the Swiss Seismological Service (SED) at ETH Zürich. VS is one of three EEW algorithms - the other two being ElarmS (Allen and Kanamori, 2003) and On-Site (Wu and Kanamori, 2005; Boese et al., 2008) - that form the basis of the California Integrated Seismic Network ShakeAlert system, a prototype end-to-end EEW system that could potentially be implemented in California. The current prototype version of VS in California requires picks at 4 stations to initiate an event declaration. On average, taking into account data latency, variable station distribution, and processing time, this initial estimate is available about 20 seconds after the earthquake origin time, corresponding to a blind zone of about 70 km around the epicenter which would receive no warning, but where it would be the most useful. To increase the available warning time, we want to produce EEW estimates faster (with less than 4 stations). However, working with less than 4 stations with our current approach would increase the number of false alerts, for which there is very little tolerance in a useful EEW system. We explore the use of back-azimuth estimations and the Voronoi-based concept of not-yet-arrived data for reducing false alerts of the earliest VS estimates. The concept of not-yet-arrived data was originally used to provide evolutionary location estimates in EEW (Horiuchi, 2005; Cua and Heaton, 2007; Satriano et al. 2008). However, it can also be applied in discriminating between earthquake and non-earthquake signals. For real earthquakes, the constraints on earthquake location from the not-yet-arrived data and the back-azimuth estimations are consistent with location constraints from the available picks. For non-earthquake signals, these different location constraints are in most cases inconsistent. We use archived event data from the Northern and Southern California Seismic Networks as well as archived continuous waveform data from where the current VS codes erroneously declared events to quantify how using a combination of pick-based and not-yet-arrived data constraints can reduce VS false alert rates while providing faster warning information. The consistency of the pick-based and not-yet-arrived data constraints are mapped into the VS likelihood parameter, which reflects the degree of believe that the signals come from a real earthquake. This approach contributes towards improving the robustness of the Virtual Seismologist Multiple Threshold Event Detection (VS-MTED), which allows for single-station event declarations, when signal amplitudes are large enough.

Building Better Drought Resilience Through Improved Monitoring and Early Warning: Learning From Stakeholders in Europe, the USA, and Australia

NASA Astrophysics Data System (ADS)

Stahl, K.; Hannaford, J.; Bachmair, S.; Tijdeman, E.; Collins, K.; Svoboda, M.; Knutson, C. L.; Wall, N.; Smith, K. H.; Bernadt, T.; Crossman, N. D.; Overton, I. C.; Barker, L. J.; Acreman, M. C.

2016-12-01

With climate projections suggesting that droughts will intensify in many regions in future, improved drought risk management may reduce potential threats to freshwater security across the globe. One aspect that has been called for in this respect is an improvement of the linkage of drought monitoring and early warning, which currently focuses largely on indicators from meteorology and hydrology, to drought impacts on environment and society. However, a survey of existing monitoring and early warning systems globally, that we report on in this contribution, demonstrates that although impacts are being monitored, there is limited work, and certainly little consensus, on how to best achieve this linkage. The Belmont Forum project DrIVER (Drought impacts: Vulnerability thresholds in monitoring and early-warning research) carried out a number of stakeholder workshops in North America, Europe and Australia to elaborate on options for such improvements. A first round of workshops explored current drought management practices among a very diverse range of stakeholders, and their expectations from monitoring and early warning systems (particularly regarding impact characterization). The workshops revealed some disconnects between the indices used in the public early warning systems and those used by local decision-makers, e.g. to trigger drought measures. Follow-up workshops then explored how the links between information at these different scales can be bridged and applied. Impact information plays a key role in this task. This contribution draws on the lessons learned from the transdisciplinary interactions in DrIVER, to enhance the usability of drought monitoring and early-warning systems and other risk management strategies.

Impact of social preparedness on flood early warning systems

NASA Astrophysics Data System (ADS)

Girons Lopez, M.; Di Baldassarre, G.; Seibert, J.

2017-01-01

Flood early warning systems play a major role in the disaster risk reduction paradigm as cost-effective methods to mitigate flood disaster damage. The connections and feedbacks between the hydrological and social spheres of early warning systems are increasingly being considered as key aspects for successful flood mitigation. The behavior of the public and first responders during flood situations, determined by their preparedness, is heavily influenced by many behavioral traits such as perceived benefits, risk awareness, or even denial. In this study, we use the recency of flood experiences as a proxy for social preparedness to assess its impact on the efficiency of flood early warning systems through a simple stylized model and implemented this model using a simple mathematical description. The main findings, which are based on synthetic data, point to the importance of social preparedness for flood loss mitigation, especially in circumstances where the technical forecasting and warning capabilities are limited. Furthermore, we found that efforts to promote and preserve social preparedness may help to reduce disaster-induced losses by almost one half. The findings provide important insights into the role of social preparedness that may help guide decision-making in the field of flood early warning systems.

The Financial Benefit of Early Flood Warnings in Europe

NASA Astrophysics Data System (ADS)

Pappenberger, Florian; Cloke, Hannah L.; Wetterhall, Fredrik; Parker, Dennis J.; Richardson, David; Thielen, Jutta

2015-04-01

Effective disaster risk management relies on science based solutions to close the gap between prevention and preparedness measures. The outcome of consultations on the UNIDSR post-2015 framework for disaster risk reduction highlight the need for cross-border early warning systems to strengthen the preparedness phases of disaster risk management in order to save people's lives and property and reduce the overall impact of severe events. In particular, continental and global scale flood forecasting systems provide vital information to various decision makers with which early warnings of floods can be made. Here the potential monetary benefits of early flood warnings using the example of the European Flood Awareness System (EFAS) are calculated based on pan-European Flood damage data and calculations of potential flood damage reductions. The benefits are of the order of 400 Euro for every 1 Euro invested. Because of the uncertainties which accompany the calculation, a large sensitivity analysis is performed in order to develop an envelope of possible financial benefits. Current EFAS system skill is compared against perfect forecasts to demonstrate the importance of further improving the skill of the forecasts. Improving the response to warnings is also essential in reaping the benefits of flood early warnings.

School disengagement as a predictor of dropout, delinquency, and problem substance use during adolescence and early adulthood.

PubMed

Henry, Kimberly L; Knight, Kelly E; Thornberry, Terence P

2012-02-01

Over the past 5 years, a great deal of attention has been paid to the development of early warning systems for dropout prevention. These warning systems use a set of indicators based on official school records to identify youth at risk for dropout and then appropriately target intervention. The current study builds on this work by assessing the extent to which a school disengagement warning index predicts not only dropout but also other problem behaviors during middle adolescence, late adolescence, and early adulthood. Data from the Rochester Youth Development Study (N = 911, 73% male, 68% African American, and 17% Latino) were used to examine the effects of a school disengagement warning index based on official 8th and 9th grade school records on subsequent dropout, as well as serious delinquency, official offending, and problem substance use during middle adolescence, late adolescence, and early adulthood. Results indicate that the school disengagement warning index is robustly related to dropout as well as serious problem behaviors across the three developmental stages, even after controlling for important potential confounders. High school dropout mediates the effect of the warning index on serious problem behaviors in early adulthood.

School Disengagement as a Predictor of Dropout, Delinquency, and Problem Substance Use during Adolescence and Early Adulthood

PubMed Central

Henry, Kimberly L.; Knight, Kelly E.; Thornberry, Terence P.

2015-01-01

Over the past five years, a great deal of attention has been paid to the development of early warning systems for dropout prevention. These warning systems use a set of indicators based on official school records to identify youth at risk for dropout and then appropriately target intervention. The current study builds on this work by assessing the extent to which a school disengagement warning index predicts not only dropout but also other problem behaviors during middle adolescence, late adolescence, and early adulthood. Data from the Rochester Youth Development Study (n=911, 73% male, 68% African American, and 17% Latino) were used to examine the effects of a school disengagement warning index based on official 8th and 9th grade school records on subsequent dropout, as well as serious delinquency, official offending, and problem substance use during middle adolescence, late adolescence, and early adulthood. Results indicate that the school disengagement warning index is robustly related to dropout as well as serious problem behaviors across the three developmental stages, even after controlling for important potential confounders. High school dropout mediates the effect of the warning index on serious problem behaviors in early adulthood. PMID:21523389

[Tourism ecological security early warning of Zhangjiajie, China based on the improved TOPSIS method and the grey GM (1,1)model].

PubMed

Xu, Mei; Liu, Chun la; Li, Dan; Zhong, Xiao Lin

2017-11-01

Tourism ecological security early warning is of great significance both to the coordination of ecological environment protection and tourism industry rapid development in tourism destination, and the sustainable and healthy development of regional social and economy. Firstly, based on the DPSIR model, the tourism ecological security early warning index system of Zhangjiajie was constructed from 5 aspects, which were driving force, pressure, state, impact and response. Then, by using the improved TOPSIS method, the tourism ecological security situation of Zhangjiajie from 2001 to 2014 was analyzed. Lastly, by using the grey GM (1,1) model, the tourism ecological security evolution trend of 2015-2020 was predicted. The results indicated that, on the whole, the close degree of Zhangjiajie's tourism ecological security showed a slightly upward trend during 2001-2014, the warning degree was the moderate warning. In terms of each subsystem, warning degree of the driving force system and the pressure system of Zhangjiajie's tourism ecological secu-rity were on the rise, which evolved from light warning to heavy warning; warning degree of the state system and the impact system had not changed so much, and had been in the moderate warning; warning degree of the response system was on the decline, which changed from huge warning to no warning during 2001-2014. According to the current development trend, the close degree of Zhangjiajie's tourism ecological security would rise further in 2015-2020, and the warning degree would turn from moderate warning into light warning, but the task of coordinating the relationship between tourism development and ecological construction and environmental protection would be still arduous.

Technical Note: An operational landslide early warning system at regional scale based on space-time variable rainfall thresholds

NASA Astrophysics Data System (ADS)

Segoni, S.; Battistini, A.; Rossi, G.; Rosi, A.; Lagomarsino, D.; Catani, F.; Moretti, S.; Casagli, N.

2014-10-01

We set up an early warning system for rainfall-induced landslides in Tuscany (23 000 km2). The system is based on a set of state-of-the-art intensity-duration rainfall thresholds (Segoni et al., 2014b), makes use of LAMI rainfall forecasts and real-time rainfall data provided by an automated network of more than 300 rain-gauges. The system was implemented in a WebGIS to ease the operational use in civil protection procedures: it is simple and intuitive to consult and it provides different outputs. Switching among different views, the system is able to focus both on monitoring of real time data and on forecasting at different lead times up to 48 h. Moreover, the system can switch between a very straightforward view where a synoptic scenario of the hazard can be shown all over the region and a more in-depth view were the rainfall path of rain-gauges can be displayed and constantly compared with rainfall thresholds. To better account for the high spatial variability of the physical features, which affects the relationship between rainfall and landslides, the region is subdivided into 25 alert zones, each provided with a specific threshold. The warning system reflects this subdivision: using a network of 332 rain gauges, it allows monitoring each alert zone separately and warnings can be issued independently from an alert zone to another. An important feature of the warning system is the use of thresholds that may vary in time adapting at the conditions of the rainfall path recorded by the rain-gauges. Depending on when the starting time of the rainfall event is set, the comparison with the threshold may produce different outcomes. Therefore, a recursive algorithm was developed to check and compare with the thresholds all possible starting times, highlighting the worst scenario and showing in the WebGIS interface at what time and how much the rainfall path has exceeded or will exceed the most critical threshold. Besides forecasting and monitoring the hazard scenario over the whole region with hazard levels differentiated for 25 distinct alert zones, the system can be used to gather, analyze, visualize, explore, interpret and store rainfall data, thus representing a potential support to both decision makers and scientists.

"A tempest in a cocktail glass": mothers, alcohol, and television, 1977-1996.

PubMed

Golden, J

2000-06-01

This article examines the portrayal of pregnancy and alcohol in thirty-six national network evening news broadcasts (ABC, CBS, NBC). Early coverage focused on white, middle-class women, as scientific authorities and government officials warned against drinking during pregnancy. After 1987, however, women who drank during pregnancy were depicted as members of minority groups and as a danger to society. The thematic transition began before warning labels appeared on alcoholic beverages and gained strength from official government efforts to prevent fetal alcohol syndrome. The greatest impetus for the revised discourse, however, was the eruption of a "moral panic" over crack cocaine use. By linking fetal harm to substance abuse, the panic suggested it was in the public's interest to control the behavior of pregnant women.

Earthquake early Warning ShakeAlert system: West coast wide production prototype

USGS Publications Warehouse

Kohler, Monica D.; Cochran, Elizabeth S.; Given, Douglas; Guiwits, Stephen; Neuhauser, Doug; Hensen, Ivan; Hartog, Renate; Bodin, Paul; Kress, Victor; Thompson, Stephen; Felizardo, Claude; Brody, Jeff; Bhadha, Rayo; Schwarz, Stan

2017-01-01

Earthquake early warning (EEW) is an application of seismological science that can give people, as well as mechanical and electrical systems, up to tens of seconds to take protective actions before peak earthquake shaking arrives at a location. Since 2006, the U.S. Geological Survey has been working in collaboration with several partners to develop EEW for the United States. The goal is to create and operate an EEW system, called ShakeAlert, for the highest risk areas of the United States, starting with the West Coast states of California, Oregon, and Washington. In early 2016, the Production Prototype v.1.0 was established for California; then, in early 2017, v.1.2 was established for the West Coast, with earthquake notifications being distributed to a group of beta users in California, Oregon, and Washington. The new ShakeAlert Production Prototype was an outgrowth from an earlier demonstration EEW system that began sending test notifications to selected users in California in January 2012. ShakeAlert leverages the considerable physical, technical, and organizational earthquake monitoring infrastructure of the Advanced National Seismic System, a nationwide federation of cooperating seismic networks. When fully implemented, the ShakeAlert system may reduce damage and injury caused by large earthquakes, improve the nation’s resilience, and speed recovery.

Early detection of ecosystem regime shifts: a multiple method evaluation for management application.

PubMed

Lindegren, Martin; Dakos, Vasilis; Gröger, Joachim P; Gårdmark, Anna; Kornilovs, Georgs; Otto, Saskia A; Möllmann, Christian

2012-01-01

Critical transitions between alternative stable states have been shown to occur across an array of complex systems. While our ability to identify abrupt regime shifts in natural ecosystems has improved, detection of potential early-warning signals previous to such shifts is still very limited. Using real monitoring data of a key ecosystem component, we here apply multiple early-warning indicators in order to assess their ability to forewarn a major ecosystem regime shift in the Central Baltic Sea. We show that some indicators and methods can result in clear early-warning signals, while other methods may have limited utility in ecosystem-based management as they show no or weak potential for early-warning. We therefore propose a multiple method approach for early detection of ecosystem regime shifts in monitoring data that may be useful in informing timely management actions in the face of ecosystem change.

Early Detection of Ecosystem Regime Shifts: A Multiple Method Evaluation for Management Application

PubMed Central

Lindegren, Martin; Dakos, Vasilis; Gröger, Joachim P.; Gårdmark, Anna; Kornilovs, Georgs; Otto, Saskia A.; Möllmann, Christian

2012-01-01

Critical transitions between alternative stable states have been shown to occur across an array of complex systems. While our ability to identify abrupt regime shifts in natural ecosystems has improved, detection of potential early-warning signals previous to such shifts is still very limited. Using real monitoring data of a key ecosystem component, we here apply multiple early-warning indicators in order to assess their ability to forewarn a major ecosystem regime shift in the Central Baltic Sea. We show that some indicators and methods can result in clear early-warning signals, while other methods may have limited utility in ecosystem-based management as they show no or weak potential for early-warning. We therefore propose a multiple method approach for early detection of ecosystem regime shifts in monitoring data that may be useful in informing timely management actions in the face of ecosystem change. PMID:22808007

Automated information-analytical system for thunderstorm monitoring and early warning alarms using modern physical sensors and information technologies with elements of artificial intelligence

NASA Astrophysics Data System (ADS)

Boldyreff, Anton S.; Bespalov, Dmitry A.; Adzhiev, Anatoly Kh.

2017-05-01

Methods of artificial intelligence are a good solution for weather phenomena forecasting. They allow to process a large amount of diverse data. Recirculation Neural Networks is implemented in the paper for the system of thunderstorm events prediction. Large amounts of experimental data from lightning sensors and electric field mills networks are received and analyzed. The average recognition accuracy of sensor signals is calculated. It is shown that Recirculation Neural Networks is a promising solution in the forecasting of thunderstorms and weather phenomena, characterized by the high efficiency of the recognition elements of the sensor signals, allows to compress images and highlight their characteristic features for subsequent recognition.

How do I know if I’ve improved my continental scale flood early warning system?

NASA Astrophysics Data System (ADS)

Cloke, Hannah L.; Pappenberger, Florian; Smith, Paul J.; Wetterhall, Fredrik

2017-04-01

Flood early warning systems mitigate damages and loss of life and are an economically efficient way of enhancing disaster resilience. The use of continental scale flood early warning systems is rapidly growing. The European Flood Awareness System (EFAS) is a pan-European flood early warning system forced by a multi-model ensemble of numerical weather predictions. Responses to scientific and technical changes can be complex in these computationally expensive continental scale systems, and improvements need to be tested by evaluating runs of the whole system. It is demonstrated here that forecast skill is not correlated with the value of warnings. In order to tell if the system has been improved an evaluation strategy is required that considers both forecast skill and warning value. The combination of a multi-forcing ensemble of EFAS flood forecasts is evaluated with a new skill-value strategy. The full multi-forcing ensemble is recommended for operational forecasting, but, there are spatial variations in the optimal forecast combination. Results indicate that optimizing forecasts based on value rather than skill alters the optimal forcing combination and the forecast performance. Also indicated is that model diversity and ensemble size are both important in achieving best overall performance. The use of several evaluation measures that consider both skill and value is strongly recommended when considering improvements to early warning systems.

Constructing early warning information release system in towns enterprise clean production

NASA Astrophysics Data System (ADS)

Yuwen, Huixin; He, Xueqiu; Qian, Xinming; Yuan, Mengqi

2017-08-01

China’s industry boom has not only brought unprecedented prosperity, but also caused the gradual depletion of various resources and the worsening of the natural environment. Experts admit that China is facing serious environmental problem, but they believe that they can seek a new path to overcome it through joint efforts. Early warning information release and clean production are the important concepts in addressing the imminent crisis. Early warning information release system can monitor and forecast the risk that affects the clean production. The author drawn the experiences and lessons from developed countries, combined with China’s reality, put forward countermeasures and suggestions about constructing early warning information release system in process of Chinese town-scaled enterprises clean production.

Early warning signal for interior crises in excitable systems.

PubMed

Karnatak, Rajat; Kantz, Holger; Bialonski, Stephan

2017-10-01

The ability to reliably predict critical transitions in dynamical systems is a long-standing goal of diverse scientific communities. Previous work focused on early warning signals related to local bifurcations (critical slowing down) and nonbifurcation-type transitions. We extend this toolbox and report on a characteristic scaling behavior (critical attractor growth) which is indicative of an impending global bifurcation, an interior crisis in excitable systems. We demonstrate our early warning signal in a conceptual climate model as well as in a model of coupled neurons known to exhibit extreme events. We observed critical attractor growth prior to interior crises of chaotic as well as strange-nonchaotic attractors. These observations promise to extend the classes of transitions that can be predicted via early warning signals.

Internet-Based Solutions for a Secure and Efficient Seismic Network

NASA Astrophysics Data System (ADS)

Bhadha, R.; Black, M.; Bruton, C.; Hauksson, E.; Stubailo, I.; Watkins, M.; Alvarez, M.; Thomas, V.

2017-12-01

The Southern California Seismic Network (SCSN), operated by Caltech and USGS, leverages modern Internet-based computing technologies to provide timely earthquake early warning for damage reduction, event notification, ShakeMap, and other data products. Here we present recent and ongoing innovations in telemetry, security, cloud computing, virtualization, and data analysis that have allowed us to develop a network that runs securely and efficiently.Earthquake early warning systems must process seismic data within seconds of being recorded, and SCSN maintains a robust and resilient network of more than 350 digital strong motion and broadband seismic stations to achieve this goal. We have continued to improve the path diversity and fault tolerance within our network, and have also developed new tools for latency monitoring and archiving.Cyberattacks are in the news almost daily, and with most of our seismic data streams running over the Internet, it is only a matter of time before SCSN is targeted. To ensure system integrity and availability across our network, we have implemented strong security, including encryption and Virtual Private Networks (VPNs).SCSN operates its own data center at Caltech, but we have also installed real-time servers on Amazon Web Services (AWS), to provide an additional level of redundancy, and eventually to allow full off-site operations continuity for our network. Our AWS systems receive data from Caltech-based import servers and directly from field locations, and are able to process the seismic data, calculate earthquake locations and magnitudes, and distribute earthquake alerts, directly from the cloud.We have also begun a virtualization project at our Caltech data center, allowing us to serve data from Virtual Machines (VMs), making efficient use of high-performance hardware and increasing flexibility and scalability of our data processing systems.Finally, we have developed new monitoring of station average noise levels at most stations. Noise monitoring is effective at identifying anthropogenic noise sources and malfunctioning acquisition equipment. We have built a dynamic display of results with sorting and mapping capabilities that allow us to quickly identify problematic sites and areas with elevated noise.

Landslide susceptibility and early warning model for shallow landslide in Taiwan

NASA Astrophysics Data System (ADS)

Huang, Chun-Ming; Wei, Lun-Wei; Chi, Chun-Chi; Chang, Kan-Tsun; Lee, Chyi-Tyi

2017-04-01

This study aims to development a regional susceptibility model and warning threshold as well as the establishment of early warning system in order to prevent and reduce the losses caused by rainfall-induced shallow landslides in Taiwan. For the purpose of practical application, Taiwan is divided into nearly 185,000 slope units. The susceptibility and warning threshold of each slope unit were analyzed as basic information for disaster prevention. The geological characteristics, mechanism and the occurrence time of landslides were recorded for more than 900 cases through field investigation and interview of residents in order to discuss the relationship between landslides and rainfall. Logistic regression analysis was performed to evaluate the landslide susceptibility and an I3-R24 rainfall threshold model was proposed for the early warning of landslides. The validations of recent landslide cases show that the model was suitable for the warning of regional shallow landslide and most of the cases can be warned 3 to 6 hours in advanced. We also propose a slope unit area weighted method to establish local rainfall threshold on landslide for vulnerable villages in order to improve the practical application. Validations of the local rainfall threshold also show a good agreement to the occurrence time reported by newspapers. Finally, a web based "Rainfall-induced Landslide Early Warning System" is built and connected to real-time radar rainfall data so that landslide real-time warning can be achieved. Keywords: landslide, susceptibility analysis, rainfall threshold

DRUG ABUSE WARNING NETWORK (DAWN) DATABASE

EPA Science Inventory

The Drug Abuse Warning Network (DAWN) is an ongoing drug abuse data collection system sponsored by SAMHSA's Office of Applied Studies. DAWN collects data from: (1) hospital emergency departments (EDs) and (2) medical examiners (MEs). The DAWN ED component relies on a nationally r...

Technical report on prototype intelligent network flow optimization (INFLO) dynamic speed harmonization and queue warning.

DOT National Transportation Integrated Search

2015-06-01

This Technical Report on Prototype Intelligent Network Flow Optimization (INFLO) Dynamic Speed Harmonization and Queue Warning is the final report for the project. It describes the prototyping, acceptance testing and small-scale demonstration of the ...

How can we deal with ANN in flood forecasting? As a simulation model or updating kernel!

NASA Astrophysics Data System (ADS)

Hassan Saddagh, Mohammad; Javad Abedini, Mohammad

2010-05-01

Flood forecasting and early warning, as a non-structural measure for flood control, is often considered to be the most effective and suitable alternative to mitigate the damage and human loss caused by flood. Forecast results which are output of hydrologic, hydraulic and/or black box models should secure accuracy of flood values and timing, especially for long lead time. The application of the artificial neural network (ANN) in flood forecasting has received extensive attentions in recent years due to its capability to capture the dynamics inherent in complex processes including flood. However, results obtained from executing plain ANN as simulation model demonstrate dramatic reduction in performance indices as lead time increases. This paper is intended to monitor the performance indices as it relates to flood forecasting and early warning using two different methodologies. While the first method employs a multilayer neural network trained using back-propagation scheme to forecast output hydrograph of a hypothetical river for various forecast lead time up to 6.0 hr, the second method uses 1D hydrodynamic MIKE11 model as forecasting model and multilayer neural network as updating kernel to monitor and assess the performance indices compared to ANN alone in light of increase in lead time. Results presented in both graphical and tabular format indicate superiority of MIKE11 coupled with ANN as updating kernel compared to ANN as simulation model alone. While plain ANN produces more accurate results for short lead time, the errors increase expeditiously for longer lead time. The second methodology provides more accurate and reliable results for longer forecast lead time.

Exploring the Potential of a Global Emerging Contaminant Early Warning Network through the Use of Retrospective Suspect Screening with High-Resolution Mass Spectrometry.

PubMed

Alygizakis, Nikiforos A; Samanipour, Saer; Hollender, Juliane; Ibáñez, María; Kaserzon, Sarit; Kokkali, Varvara; van Leerdam, Jan A; Mueller, Jochen F; Pijnappels, Martijn; Reid, Malcolm J; Schymanski, Emma L; Slobodnik, Jaroslav; Thomaidis, Nikolaos S; Thomas, Kevin V

2018-05-01

A key challenge in the environmental and exposure sciences is to establish experimental evidence of the role of chemical exposure in human and environmental systems. High resolution and accurate tandem mass spectrometry (HRMS) is increasingly being used for the analysis of environmental samples. One lauded benefit of HRMS is the possibility to retrospectively process data for (previously omitted) compounds that has led to the archiving of HRMS data. Archived HRMS data affords the possibility of exploiting historical data to rapidly and effectively establish the temporal and spatial occurrence of newly identified contaminants through retrospective suspect screening. We propose to establish a global emerging contaminant early warning network to rapidly assess the spatial and temporal distribution of contaminants of emerging concern in environmental samples through performing retrospective analysis on HRMS data. The effectiveness of such a network is demonstrated through a pilot study, where eight reference laboratories with available archived HRMS data retrospectively screened data acquired from aqueous environmental samples collected in 14 countries on 3 different continents. The widespread spatial occurrence of several surfactants (e.g., polyethylene glycols ( PEGs ) and C12AEO-PEGs ), transformation products of selected drugs (e.g., gabapentin-lactam, metoprolol-acid, carbamazepine-10-hydroxy, omeprazole-4-hydroxy-sulfide, and 2-benzothiazole-sulfonic-acid), and industrial chemicals (3-nitrobenzenesulfonate and bisphenol-S) was revealed. Obtaining identifications of increased reliability through retrospective suspect screening is challenging, and recommendations for dealing with issues such as broad chromatographic peaks, data acquisition, and sensitivity are provided.

Forests and Phenology: Designing the Early Warning System to Understand Forest Change

NASA Astrophysics Data System (ADS)

Pierce, T.; Phillips, M. B.; Hargrove, W. W.; Dobson, G.; Hicks, J.; Hutchins, M.; Lichtenstein, K.

2010-12-01

Vegetative phenology is the study of plant development and changes with the seasons, such as the greening-up and browning-down of forests, and how these events are influenced by variations in climate. A National Phenology Data Set, based on Moderate Resolution Imaging Spectroradiometer satellite images covering 2002 through 2009, is now available from work by NASA, the US Forest Service, and Oak Ridge National Laboratory. This new data set provides an easily interpretable product useful for detecting changes to the landscape due to long-term factors such as climate change, as well as finding areas affected by short-term forest threats such as insects or disease. The Early Warning System (EWS) is a toolset being developed by the US Forest Service and the University of North Carolina-Asheville to support distribution and use of the National Phenology Data Set. The Early Warning System will help research scientists, US Forest Service personnel, forest and natural resources managers, decision makers, and the public in the use of phenology data to better understand unexpected change within our nation’s forests. These changes could have multiple natural sources such as insects, disease, or storm damage, or may be due to human-induced events, like thinning, harvest, forest conversion to agriculture, or residential and commercial use. The primary goal of the Early Warning System is to provide a seamless integration between monitoring, detection, early warning and prediction of these forest disturbances as observed through phenological data. The system consists of PC and web-based components that are structured to support four user stages of increasing knowledge and data sophistication. Building Literacy: This stage of the Early Warning System educates potential users about the system, why the system should be used, and the fundamentals about the data the system uses. The channels for this education include a website, interactive tutorials, pamphlets, and other technology transfer methodologies. Achieving Context and Meaning: To provide deeper meaning and knowledge about the Early Warning System to users, this stage of the Early Warning System provides more information about specific examples of disturbances seen in the phenological data, as well the spatial and temporal context to these disturbances. The main components of this stage are specific case studies of forest disturbances. Accessing Data: This component of the Early Warning System includes products for research scientists, the aerial detection survey sketch mapper community, and others who will access and analyze the Early Warning System and phenological data. Products and data will be available through online GIS mashups and WMS and KML downloads. Utilizing Services: The final stage of the Early Warning System supports the analysis of phenological data and serves the results to those end users, including forest managers, the forest industry, and the public, who need to locate past, present, and potential forest disturbances. The main components of this stage include data-driven web tools, automated analysis processes, and end user training programs.

ShakeAlert—An earthquake early warning system for the United States west coast

USGS Publications Warehouse

Burkett, Erin R.; Given, Douglas D.; Jones, Lucile M.

2014-08-29

Earthquake early warning systems use earthquake science and the technology of monitoring systems to alert devices and people when shaking waves generated by an earthquake are expected to arrive at their location. The seconds to minutes of advance warning can allow people and systems to take actions to protect life and property from destructive shaking. The U.S. Geological Survey (USGS), in collaboration with several partners, has been working to develop an early warning system for the United States. ShakeAlert, a system currently under development, is designed to cover the West Coast States of California, Oregon, and Washington.

Biosurveillance: Efforts to Develop a National Biosurveillance Capability Need a National Strategy and a Designated Leader

DTIC Science & Technology

2010-06-01

was due to jalapeno and Serrano peppers grown and packed in Mexico and distributed in the United States. According to the USDA Rural Cooperative, the...early warning and active syndromic illness and disease monitoring network operating in the United States (U.S.)- Mexico Border Region and targets...Mexican national policies. Primary Users State and local public health epidemiologists at the U.S.- Mexico border Primary Providers of Data Data are

The Good, the Bad and the Ugly: Remarks on data policies, their influence on system architecture, and the resilience of circumbasin countries against tsunami

NASA Astrophysics Data System (ADS)

Küppers, A. N.

2012-04-01

The performance of early warning systems directly depends on the swift provision of data from various sources. Deployed in wide areas and conceived as cross-border installations they have to serve very wide ranges of different geographical, ethno-cultural, linguistic and socio-economic groups and identities, thus bearing a high degree of intrinsic complexity besides a significant technological incoherence. In the scope of the EU FP7-projects DEWS and TRIDEC, analysis of the availability of data which is supposed to originate from seismological networks, GPS, buoys, tide gauges, ocean bottom instrumentation and satellites, was performed. The situation in the Indian Ocean basin and the Mediterranean basin both exhibit a wide range of obstacles against in time delivery of critical data. While the complete lack or poor maintenance state of sensors and the slow or hampered data transmission are the most frequent physical reasons of insufficient data generation and data flow, bureaucratic hindrances, competition between network owners, lack of standards and finally political friction between states or even nations are the overarching impediments. Based on post-disaster investigations performed in Japan and Indonesia, a set of key performance indicators for tsunami early warning systems is suggested. It is proposed to employ them as a tool for the overall improvement of data policies through high level briefings by means of supra-national initiatives.

Long term real-time GB_InSAR monitoring of a large rock slide

NASA Astrophysics Data System (ADS)

Crosta, G. B.; Agliardi, F.; Sosio, R.; Rivolta, C.; Mannucci, G.

2011-12-01

We analyze a long term monitoring dataset collected for a deep-seated rockslide (Ruinon, Lombardy, Italy). The rockslide has been actively monitored since 1997 by means of an in situ monitoring network (topographic benchmarks, GPS, wire extensometers) and since 2006 by a ground based radar. Monitoring data have been used to set-up and update the geological model, to identify rockslide extent and geometry, to analyse the sensitivity to seasonal changes and their impact on the reliability and early warning potential of monitoring data. GB-InSAR data allowed us to identify sectors characterized by different behaviours and associated to outcropping bedrock, thick debris cover, major structures. GB-Insar data have been used to set-up a "virtual monitoring network" by a posteriori selection of critical locations. Displacement time series extracted from GB-InSAR data provide a large amount of information even in debris-covered areas, when ground-based instrumentation fails. Such spatially-distributed, improved information, validated by selected ground-based measurements, allowed to establish new velocity and displacement thresholds for early warning purposes. The data are analysed to verify the dependency of the observed displacements on the line of sight orientation as well as on that of the framed resolution cell. Relationships with rainfall and morphological slope characteristics have been analysed to verify the sensitivity to rain intensity and amount and to distinguish among the different possible mechanisms.

Ionospheric earthquake effects detection based on Total Electron Content (TEC) GPS Correlation

NASA Astrophysics Data System (ADS)

Sunardi, Bambang; Muslim, Buldan; Eka Sakya, Andi; Rohadi, Supriyanto; Sulastri; Murjaya, Jaya

2018-03-01

Advances in science and technology showed that ground-based GPS receiver was able to detect ionospheric Total Electron Content (TEC) disturbances caused by various natural phenomena such as earthquakes. One study of Tohoku (Japan) earthquake, March 11, 2011, magnitude M 9.0 showed TEC fluctuations observed from GPS observation network spread around the disaster area. This paper discussed the ionospheric earthquake effects detection using TEC GPS data. The case studies taken were Kebumen earthquake, January 25, 2014, magnitude M 6.2, Sumba earthquake, February 12, 2016, M 6.2 and Halmahera earthquake, February 17, 2016, M 6.1. TEC-GIM (Global Ionosphere Map) correlation methods for 31 days were used to monitor TEC anomaly in ionosphere. To ensure the geomagnetic disturbances due to solar activity, we also compare with Dst index in the same time window. The results showed anomalous ratio of correlation coefficient deviation to its standard deviation upon occurrences of Kebumen and Sumba earthquake, but not detected a similar anomaly for the Halmahera earthquake. It was needed a continous monitoring of TEC GPS data to detect the earthquake effects in ionosphere. This study giving hope in strengthening the earthquake effect early warning system using TEC GPS data. The method development of continuous TEC GPS observation derived from GPS observation network that already exists in Indonesia is needed to support earthquake effects early warning systems.

Connecting global change science with communities: About the conformation of a social network for early warnings in Colombia

NASA Astrophysics Data System (ADS)

Arias, P. A.; Vidal, L. M.; Serna, A. M.; Vieira, C.; Machado, J.; Cadavid, C. A.

2014-12-01

The risk associated with natural and social phenomena has notably increased in modern societies. On the other hand, socio-natural hazards have increased and diversified, in association with economic development. During 2010 and 2011, Colombia faced one of the most severe wet seasons in decades. One of the most significant impacts of this flood emergency was the demonstration of poor preparedness of communities, local authorities, and regional and national authorities to confront situations of large coverage. The emergencies occurred during 2010 and 2011, induced in association with a strong La Niña event, immediately demanded environmental and risk management authorities to provide communities with basic tools to understand the dynamics associated with excesses of rainfall and mitigate the possible impacts in their populations. For this reason, the Regional Autonomous Corporation of Central Antioquia, Colombia (CORANTIOQUIA) funded a project aimed to the design and conformation of a social network for early warnings of events associated to floods, torrential floods, and mass movements in 80 municipalities of the department of Antioquia, Colombia. For the execution of this project, the Corporation invited the Faculty of Engineering of the University of Antioquia. This talk aims to socialize this inititative that looked for integrating scientific and technical knowledge with popular knowledge in order to provide Latin American communities with tools to mitigate the possible impacts of global change.

Using SMAP data to improve drought early warning over the US Great Plains

NASA Astrophysics Data System (ADS)

Fu, R.; Fernando, N.; Tang, W.

2015-12-01

A drought prone region such as the Great Plains of the United States (US GP) requires credible and actionable drought early warning. Such information cannot simply be extracted from available climate forecasts because of their large uncertainties at regional scales, and unclear connections to the needs of the decision makers. In particular, current dynamic seasonal predictions and climate projections, such as those produced by the NOAA North American Multi-Model Ensemble experiment (NMME) are much more reliable for winter and spring than for the summer season for the US GP. To mitigate the weaknesses of dynamic prediction/projections, we have identified three key processes behind the spring-to-summer dry memory through observational studies, as the scientific basis for a statistical drought early warning system. This system uses percentile soil moisture anomalies in spring as a key input to provide a probabilistic summer drought early warning. The latter outperforms the dynamic prediction over the US Southern Plains and has been used by the Texas state water agency to support state drought preparedness. A main source of uncertainty for this drought early warning system is the soil moisture input obtained from the NOAA Climate Forecasting System (CFS). We are testing use of the beta version of NASA Soil Moisture Active Passive (SMAP) soil moisture data, along with the Soil Moisture and Ocean Salinity (SMOS), and the long-term Essential Climate Variable Soil Moisture (ECV-SM) soil moisture data, to reduce this uncertainty. Preliminary results based on ECV-SM suggests satellite based soil moisture data could improve early warning of rainfall anomalies over the western US GP with less dense vegetation. The skill degrades over the eastern US GP where denser vegetation is found. We evaluate our SMAP-based drought early warning for 2015 summer against observations.

How one might miss early warning signals of critical transitions in time series data: A systematic study of two major currency pairs

PubMed Central

Ciamarra, Massimo Pica; Cheong, Siew Ann

2018-01-01

There is growing interest in the use of critical slowing down and critical fluctuations as early warning signals for critical transitions in different complex systems. However, while some studies found them effective, others found the opposite. In this paper, we investigated why this might be so, by testing three commonly used indicators: lag-1 autocorrelation, variance, and low-frequency power spectrum at anticipating critical transitions in the very-high-frequency time series data of the Australian Dollar-Japanese Yen and Swiss Franc-Japanese Yen exchange rates. Besides testing rising trends in these indicators at a strict level of confidence using the Kendall-tau test, we also required statistically significant early warning signals to be concurrent in the three indicators, which must rise to appreciable values. We then found for our data set the optimum parameters for discovering critical transitions, and showed that the set of critical transitions found is generally insensitive to variations in the parameters. Suspecting that negative results in the literature are the results of low data frequencies, we created time series with time intervals over three orders of magnitude from the raw data, and tested them for early warning signals. Early warning signals can be reliably found only if the time interval of the data is shorter than the time scale of critical transitions in our complex system of interest. Finally, we compared the set of time windows with statistically significant early warning signals with the set of time windows followed by large movements, to conclude that the early warning signals indeed provide reliable information on impending critical transitions. This reliability becomes more compelling statistically the more events we test. PMID:29538373

How one might miss early warning signals of critical transitions in time series data: A systematic study of two major currency pairs.

PubMed

Wen, Haoyu; Ciamarra, Massimo Pica; Cheong, Siew Ann

2018-01-01

There is growing interest in the use of critical slowing down and critical fluctuations as early warning signals for critical transitions in different complex systems. However, while some studies found them effective, others found the opposite. In this paper, we investigated why this might be so, by testing three commonly used indicators: lag-1 autocorrelation, variance, and low-frequency power spectrum at anticipating critical transitions in the very-high-frequency time series data of the Australian Dollar-Japanese Yen and Swiss Franc-Japanese Yen exchange rates. Besides testing rising trends in these indicators at a strict level of confidence using the Kendall-tau test, we also required statistically significant early warning signals to be concurrent in the three indicators, which must rise to appreciable values. We then found for our data set the optimum parameters for discovering critical transitions, and showed that the set of critical transitions found is generally insensitive to variations in the parameters. Suspecting that negative results in the literature are the results of low data frequencies, we created time series with time intervals over three orders of magnitude from the raw data, and tested them for early warning signals. Early warning signals can be reliably found only if the time interval of the data is shorter than the time scale of critical transitions in our complex system of interest. Finally, we compared the set of time windows with statistically significant early warning signals with the set of time windows followed by large movements, to conclude that the early warning signals indeed provide reliable information on impending critical transitions. This reliability becomes more compelling statistically the more events we test.

A Walk through TRIDEC's intermediate Tsunami Early Warning System

NASA Astrophysics Data System (ADS)

Hammitzsch, M.; Reißland, S.; Lendholt, M.

2012-04-01

The management of natural crises is an important application field of the technology developed in the project Collaborative, Complex, and Critical Decision-Support in Evolving Crises (TRIDEC), co-funded by the European Commission in its Seventh Framework Programme. TRIDEC is based on the development of the German Indonesian Tsunami Early Warning System (GITEWS) and the Distant Early Warning System (DEWS) providing a service platform for both sensor integration and warning dissemination. In TRIDEC new developments in Information and Communication Technology (ICT) are used to extend the existing platform realising a component-based technology framework for building distributed tsunami warning systems for deployment, e.g. in the North-eastern Atlantic, the Mediterranean and Connected Seas (NEAM) region. The TRIDEC system will be implemented in three phases, each with a demonstrator. Successively, the demonstrators are addressing challenges, such as the design and implementation of a robust and scalable service infrastructure supporting the integration and utilisation of existing resources with accelerated generation of large volumes of data. These include sensor systems, geo-information repositories, simulation tools and data fusion tools. In addition to conventional sensors also unconventional sensors and sensor networks play an important role in TRIDEC. The system version presented is based on service-oriented architecture (SOA) concepts and on relevant standards of the Open Geospatial Consortium (OGC), the World Wide Web Consortium (W3C) and the Organization for the Advancement of Structured Information Standards (OASIS). In this way the system continuously gathers, processes and displays events and data coming from open sensor platforms to enable operators to quickly decide whether an early warning is necessary and to send personalized warning messages to the authorities and the population at large through a wide range of communication channels. The system integrates OGC Sensor Web Enablement (SWE) compliant sensor systems for the rapid detection of hazardous events, like earthquakes, sea level anomalies, ocean floor occurrences, and ground displacements. Using OGC Web Map Service (WMS) and Web Feature Service (WFS) spatial data are utilized to depict the situation picture. The integration of a simulation system to identify affected areas is considered using the OGC Web Processing Service (WPS). Warning messages are compiled and transmitted in the OASIS Common Alerting Protocol (CAP) together with addressing information defined via the OASIS Emergency Data Exchange Language - Distribution Element (EDXL-DE). The first system demonstrator has been designed and implemented to support plausible scenarios demonstrating the treatment of simulated tsunami threats with an essential subset of a National Tsunami Warning Centre (NTWC). The feasibility and the potentials of the implemented approach are demonstrated covering standard operations as well as tsunami detection and alerting functions. The demonstrator presented addresses information management and decision-support processes in a hypothetical natural crisis situation caused by a tsunami in the Eastern Mediterranean. Developments of the system are based to the largest extent on free and open source software (FOSS) components and industry standards. Emphasis has been and will be made on leveraging open source technologies that support mature system architecture models wherever appropriate. All open source software produced is foreseen to be published on a publicly available software repository thus allowing others to reuse results achieved and enabling further development and collaboration with a wide community including scientists, developers, users and stakeholders. This live demonstration is linked with the talk "TRIDEC Natural Crisis Management Demonstrator for Tsunamis" (EGU2012-7275) given in the session "Architecture of Future Tsunami Warning Systems" (NH5.7/ESSI1.7).

Seismogeodetic monitoring techniques for tsunami and earthquake early warning and rapid assessment of structural damage

NASA Astrophysics Data System (ADS)

Haase, J. S.; Bock, Y.; Saunders, J. K.; Goldberg, D.; Restrepo, J. I.

2016-12-01

As part of an effort to promote the use of NASA-sponsored Earth science information for disaster risk reduction, real-time high-rate seismogeodetic data are being incorporated into early warning and structural monitoring systems. Seismogeodesy combines seismic acceleration and GPS displacement measurements using a tightly-coupled Kalman filter to provide absolute estimates of seismic acceleration, velocity and displacement. Traditionally, the monitoring of earthquakes and tsunamis has been based on seismic networks for estimating earthquake magnitude and slip, and tide gauges and deep-ocean buoys for direct measurement of tsunami waves. Real-time seismogeodetic observations at subduction zones allow for more robust and rapid magnitude and slip estimation that increase warning time in the near-source region. A NASA-funded effort to utilize GPS and seismogeodesy in NOAA's Tsunami Warning Centers in Alaska and Hawaii integrates new modules for picking, locating, and estimating magnitudes and moment tensors for earthquakes into the USGS earthworm environment at the TWCs. In a related project, NASA supports the transition of this research to seismogeodetic tools for disaster preparedness, specifically by implementing GPS and low-cost MEMS accelerometers for structural monitoring in partnership with earthquake engineers. Real-time high-rate seismogeodetic structural monitoring has been implemented on two structures. The first is a parking garage at the Autonomous University of Baja California Faculty of Medicine in Mexicali, not far from the rupture of the 2011 Mw 7.2 El Mayor Cucapah earthquake enabled through a UCMexus collaboration. The second is the 8-story Geisel Library at University of California, San Diego (UCSD). The system has also been installed for several proof-of-concept experiments at the UCSD Network for Earthquake Engineering Simulation (NEES) Large High Performance Outdoor Shake Table. We present MEMS-based seismogeodetic observations from the 10 June 2016 Mw 5.2 Borrego Springs earthquake of strong ground motions in near field close to the San Jacinto fault, as well as observations that show the response of the 3 story parking garage. The occurrence of this recent earthquake provided a useful demonstration of structural monitoring applications with seismogeodesy.

Integrating TWES and Satellite-based remote sensing: Lessons learned from the Honshu 2011 Tsunami

NASA Astrophysics Data System (ADS)

Löwe, Peter; Wächter, Joachim

2013-04-01

The Boxing Day Tsunami killed 240,000 people and inundated the affected shorelines with waves reaching heights up to 30m. Tsunami Early Warning Capabilities have improved in the meantime by continuing development of modular Tsunami Early Warning Systems (TEWS). However, recent tsunami events, like the Chile 2010 and the Honshu 2011 tsunami demonstrate that the key challenge for TEWS research still lies in the timely issuing of reliable early warning messages to areas at risk, but also to other stakeholders professionally involved in the unfolding event. Until now remote sensing products for Tsunami events, including crisis maps and change detection products, are exclusively linked to those phases of the disaster life cycle, which follow after the early warning stage: Response, recovery and mitigation. The International Charter for Space and Major Disasters has been initiated by the European Space Agency (ESA) and the Centre National d'Etudes Spatiales (CNES) in 1999. It coordinates a voluntary group of governmental space agencies and industry partners, to provide rapid crisis imaging and mapping to disaster and relief organisations to mitigate the effects of disasters on human life, property and the environment. The efficiency of this approach has been demonstrated in the field of Tsunami early warning by Charter activations following the Boxing Day Tsunami 2004, the Chile Tsunami 2010 and the Honshu Tsunami 2011. Traditional single-satellite operations allow at best bimonthly repeat rates over a given Area of Interest (AOI). This allows a lot of time for image acquisition campaign planning between imaging windows for the same AOI. The advent of constellations of identical remote sensing satellites in the early 21st century resulted both in daily AOI revisit capabilities and drastically reduced time frames for acquisition planning. However, the image acquisition planning for optical remote sensing satellite constellations is constrained by orbital and communication requirements: Defined time slots exist to commandeer the tasking of image acquisitions. If such a time slot has been missed, another attempt to image an AOI again can only be attempted ca. 24 hours later, due to the sun-synchronous satellite orbits Therefore it is critical to establish automated Disaster Early Warning dissemination services for the remote sensing community, to supply them with the timeliest opportunity to trigger the tasking process for the affected AOI. For very large events like a Tsunami in the Pacific, this approach provides the chance to gain additional pre-disaster imagery as a reference for change detection. In the case of the Tohoku earthquake, an ad-hoc warning dissemination process was manually dispatched by the Centre for Geoinformation Technology (CeGIT) at the German Research Centre for Geoscience, contacting RapidEye AG, once the severity of the earthquake event had been confirmed by the GEOFON geoseismic network. RapidEye AG decided to launch an imaging campaign which yielded 78 georectified image tiles (L3A) of Honshu island during the next imaging window. Of these, 26 tiles cover the affected coastline, resulting in 16,250km² of content for crisis mapping effort such as the Humanitarian Open Street Map (OSM) Team. This data was made available by RapidEye as a part of the Charter Activiation requested by Japan on March 11 2011. [1] Hoja, D., Schwinger, M.,Wendleder A.,Löwe, P., Konstanski, H., Weichelt, H.: Optimised Near-Real Time Data Acquisition for Disaster Related Rapid Mapping

Early Warning for Large Magnitude Earthquakes: Is it feasible?

NASA Astrophysics Data System (ADS)

Zollo, A.; Colombelli, S.; Kanamori, H.

2011-12-01

The mega-thrust, Mw 9.0, 2011 Tohoku earthquake has re-opened the discussion among the scientific community about the effectiveness of Earthquake Early Warning (EEW) systems, when applied to such large events. Many EEW systems are now under-testing or -development worldwide and most of them are based on the real-time measurement of ground motion parameters in a few second window after the P-wave arrival. Currently, we are using the initial Peak Displacement (Pd), and the Predominant Period (τc), among other parameters, to rapidly estimate the earthquake magnitude and damage potential. A well known problem about the real-time estimation of the magnitude is the parameter saturation. Several authors have shown that the scaling laws between early warning parameters and magnitude are robust and effective up to magnitude 6.5-7; the correlation, however, has not yet been verified for larger events. The Tohoku earthquake occurred near the East coast of Honshu, Japan, on the subduction boundary between the Pacific and the Okhotsk plates. The high quality Kik- and K- networks provided a large quantity of strong motion records of the mainshock, with a wide azimuthal coverage both along the Japan coast and inland. More than 300 3-component accelerograms have been available, with an epicentral distance ranging from about 100 km up to more than 500 km. This earthquake thus presents an optimal case study for testing the physical bases of early warning and to investigate the feasibility of a real-time estimation of earthquake size and damage potential even for M > 7 earthquakes. In the present work we used the acceleration waveform data of the main shock for stations along the coast, up to 200 km epicentral distance. We measured the early warning parameters, Pd and τc, within different time windows, starting from 3 seconds, and expanding the testing time window up to 30 seconds. The aim is to verify the correlation of these parameters with Peak Ground Velocity and Magnitude, respectively, as a function of the length of the P-wave window. The entire rupture process of the Tohoku earthquake lasted more than 120 seconds, as shown by the source time functions obtained by several authors. When a 3 second window is used to measure Pd and τc the result is an obvious underestimation of the event size and final PGV. However, as the time window increases up to 27-30 seconds, the measured values of Pd and τc become comparable with those expected for a magnitude M≥8.5 earthquake, according to the τc vs. M and the PGV vs. Pd relationships obtained in a previous work. Since we did not observe any saturation effect for the predominant period and peak displacement measured within a P-wave, 30-seconds window, we infer that, at least from a theoretical point of view, the estimation of earthquake damage potential through the early warning parameters is still feasible for large events, provided that a longer time window is used for parameter measurement. The off-line analysis of the Tohoku event records shows that reliable estimations of the damage potential could have been obtained 40-50 seconds after the origin time, by updating the measurements of the early warning parameters in progressively enlarged P-wave time windows from 3 to 30 seconds.

[Evaluation and analysis of monitoring and early warning functions of the occupational disease reporting system in China].

PubMed

Zhu, Xiaojun; Li, Tao; Liu, Mengxuan

2015-06-01

To evaluate the monitoring and early warning functions of the occupational disease reporting system right now in China, and to analyze their influencing factors. An improved audit tool (ODIT) was used to score the monitoring and early warning functions with a total score of 10. The nine indices were completeness of information on the reporting form, coverage of the reporting system, accessibility of criteria or guidelines for diagnosis, education and training for physicians, completeness of the reporting system, statistical methods, investigation of special cases, release of monitoring information, and release of early warning information. According to the evaluation, the occupational disease reporting system in China had a score of 5.5 in monitoring existing occupational diseases with a low score for release of monitoring information; the reporting system had a score of 6.5 in early warning of newly occurring occupational diseases with low scores for education and training for physicians as well as completeness of the reporting system. The occupational disease reporting system in China still does not have full function in monitoring and early warning. It is the education and participation of physicians from general hospitals in the diagnosis and treatment of occupational diseases and suspected occupational diseases that need to be enhanced. In addition, the problem of monitoring the incidence of occupational diseases needs to be solved as soon as possible.

A SDMS Model: Early Warning Coordination Centres

NASA Astrophysics Data System (ADS)

Santos-Reyes, Jaime

2010-05-01

Following the tsunami disaster in 2004, the General Secretary of the United Nations (UN) Kofi Annan called for a global early warning system for all hazards and for all communities. He also requested the ISDR (International Strategy fort Disaster Reduction) and its UN partners to conduct a global survey of capacities, gaps and opportunities in relation to early warning systems. The produced report, "Global survey of Early Warning Systems", concluded that there are many gaps and shortcomings and that much progress has been made on early warning systems and great capabilities are available around the world. However, it may be argued that an early warning system (EWS) may not be enough to prevent fatalities due to a natural hazard; i.e., it should be seen as part of a ‘wider' or total system. Furthermore, an EWS may work very well when assessed individually but it is not clear whether it will contribute to accomplish the purpose of the ‘total disaster management system'; i.e., to prevent fatalities. For instance, a regional EWS may only work if it is well co-ordinated with the local warning and emergency response systems that ensure that the warning is received, communicated and acted upon by the potentially affected communities. It may be argued that without these local measures being in place, a regional EWS will have little impact in saving lives. Researchers argued that unless people are warned in remote areas, the technology is useless; for instance McGuire [5] argues that: "I have no doubt that the technical element of the warning system will work very well,"…"But there has to be an effective and efficient communications cascade from the warning centre to the fisherman on the beach and his family and the bar owners." Similarly, McFadden [6] states that: "There's no point in spending all the money on a fancy monitoring and a fancy analysis system unless we can make sure the infrastructure for the broadcast system is there,"… "That's going to require a lot of work. If it's a tsunami, you've got to get it down to the last Joe on the beach. This is the stuff that is really very hard." Given the above, the paper argues that there is a need for a systemic approach to early warning centres. Systemic means looking upon things as a system; systemic means seeing pattern and inter-relationship within a complex whole; i.e., to see events as products of the working of a system. System may be defined as a whole which is made of parts and relationships. Given this, ‘failure' may be seen as the product of a system and, within that, see death/injury/property loss etc. as results of the working of systems. This paper proposes a preliminary model of ‘early warning coordination centres' (EWCC); it should be highlighted that an EWCC is a subsystem of the Systemic Disaster Management System (SDMS) model.

Famines in Africa: is early warning early enough?

PubMed Central

Kim, Jeeyon Janet; Guha-Sapir, Debarati

2012-01-01

Following the second Sahelian famine in 1984–1985, major investments were made to establish Early Warning Systems. These systems help to ensure that timely warnings and vulnerability information are available to decision makers to anticipate and avert food crises. In the recent crisis in the Horn of Africa, alarming levels of acute malnutrition were documented from March 2010, and by August 2010, an impending food crisis was forecast. Despite these measures, the situation remained unrecognised, and further deteriorated causing malnutrition levels to grow in severity and scope. By the time the United Nations officially declared famine on 20 July 2011, and the humanitarian community sluggishly went into response mode, levels of malnutrition and mortality exceeded catastrophic levels. At this time, an estimated 11 million people were in desperate and immediate need for food. With warnings of food crises in the Sahel, South Sudan, and forecast of the drought returning to the Horn, there is an immediate need to institutionalize change in the health response during humanitarian emergencies. Early warning systems are only effective if they trigger an early response. PMID:22745628

Famines in Africa: is early warning early enough?

PubMed

Kim, Jeeyon Janet; Guha-Sapir, Debarati

2012-01-01

Following the second Sahelian famine in 1984-1985, major investments were made to establish Early Warning Systems. These systems help to ensure that timely warnings and vulnerability information are available to decision makers to anticipate and avert food crises. In the recent crisis in the Horn of Africa, alarming levels of acute malnutrition were documented from March 2010, and by August 2010, an impending food crisis was forecast. Despite these measures, the situation remained unrecognised, and further deteriorated causing malnutrition levels to grow in severity and scope. By the time the United Nations officially declared famine on 20 July 2011, and the humanitarian community sluggishly went into response mode, levels of malnutrition and mortality exceeded catastrophic levels. At this time, an estimated 11 million people were in desperate and immediate need for food. With warnings of food crises in the Sahel, South Sudan, and forecast of the drought returning to the Horn, there is an immediate need to institutionalize change in the health response during humanitarian emergencies. Early warning systems are only effective if they trigger an early response.

Implementing drought early warning systems: policy lessons and future needs

NASA Astrophysics Data System (ADS)

Iglesias, Ana; Werner, Micha; Maia, Rodrigo; Garrote, Luis; Nyabeze, Washington

2014-05-01

Drought forecasting and Warning provides the potential of reducing impacts to society due to drought events. The implementation of effective drought forecasting and warning, however, requires not only science to support reliable forecasting, but also adequate policy and societal response. Here we propose a protocol to develop drought forecasting and early warning based in the international cooperation of African and European institutions in the DEWFORA project (EC, 7th Framework Programme). The protocol includes four major phases that address the scientific knowledge and the social capacity to use the knowledge: (a) What is the science available? Evaluating how signs of impending drought can be detected and predicted, defining risk levels, and analysing of the signs of drought in an integrated vulnerability approach. (b) What are the societal capacities? In this the institutional framework that enables policy development is evaluated. The protocol gathers information on vulnerability and pending hazard in advance so that early warnings can be declared at sufficient lead time and drought mitigation planning can be implemented at an early stage. (c) How can science be translated into policy? Linking science indicators into the actions/interventions that society needs to implement, and evaluating how policy is implemented. Key limitations to planning for drought are the social capacities to implement early warning systems. Vulnerability assessment contributes to identify these limitations and therefore provides crucial information to policy development. Based on the assessment of vulnerability we suggest thresholds for management actions to respond to drought forecasts and link predictive indicators to relevant potential mitigation strategies. Vulnerability assessment is crucial to identify relief, coping and management responses that contribute to a more resilient society. (d) How can society benefit from the forecast? Evaluating how information is provided to potentially affected groups, and how mitigation strategies can be taken in response. This paper presents an outline of the protocol that was developed in the DEWFORA project, outlining the complementary roles of science, policy and societal uptake in effective drought forecasting and warning. A consensus on the need to emphasise the social component of early warning was reached when testing the DEWFORA early warning system protocol among experts from 18 countries.

Performance of Social Network Sensors during Hurricane Sandy

PubMed Central

Kryvasheyeu, Yury; Chen, Haohui; Moro, Esteban; Van Hentenryck, Pascal; Cebrian, Manuel

2015-01-01

Information flow during catastrophic events is a critical aspect of disaster management. Modern communication platforms, in particular online social networks, provide an opportunity to study such flow and derive early-warning sensors, thus improving emergency preparedness and response. Performance of the social networks sensor method, based on topological and behavioral properties derived from the “friendship paradox”, is studied here for over 50 million Twitter messages posted before, during, and after Hurricane Sandy. We find that differences in users’ network centrality effectively translate into moderate awareness advantage (up to 26 hours); and that geo-location of users within or outside of the hurricane-affected area plays a significant role in determining the scale of such an advantage. Emotional response appears to be universal regardless of the position in the network topology, and displays characteristic, easily detectable patterns, opening a possibility to implement a simple “sentiment sensing” technique that can detect and locate disasters. PMID:25692690

Performance of social network sensors during Hurricane Sandy.

PubMed

Kryvasheyeu, Yury; Chen, Haohui; Moro, Esteban; Van Hentenryck, Pascal; Cebrian, Manuel

2015-01-01

Information flow during catastrophic events is a critical aspect of disaster management. Modern communication platforms, in particular online social networks, provide an opportunity to study such flow and derive early-warning sensors, thus improving emergency preparedness and response. Performance of the social networks sensor method, based on topological and behavioral properties derived from the "friendship paradox", is studied here for over 50 million Twitter messages posted before, during, and after Hurricane Sandy. We find that differences in users' network centrality effectively translate into moderate awareness advantage (up to 26 hours); and that geo-location of users within or outside of the hurricane-affected area plays a significant role in determining the scale of such an advantage. Emotional response appears to be universal regardless of the position in the network topology, and displays characteristic, easily detectable patterns, opening a possibility to implement a simple "sentiment sensing" technique that can detect and locate disasters.

An early warning and control system for urban, drinking water quality protection: China's experience.

PubMed

Hou, Dibo; Song, Xiaoxuan; Zhang, Guangxin; Zhang, Hongjian; Loaiciga, Hugo

2013-07-01

An event-driven, urban, drinking water quality early warning and control system (DEWS) is proposed to cope with China's urgent need for protecting its urban drinking water. The DEWS has a web service structure and provides users with water quality monitoring functions, water quality early warning functions, and water quality accident decision-making functions. The DEWS functionality is guided by the principles of control theory and risk assessment as applied to the feedback control of urban water supply systems. The DEWS has been deployed in several large Chinese cities and found to perform well insofar as water quality early warning and emergency decision-making is concerned. This paper describes a DEWS for urban water quality protection that has been developed in China.

Climate change implications and use of early warning systems for global dust storms

USGS Publications Warehouse

Harriman, Lindsey M.

2014-01-01

With increased changes in land cover and global climate, early detection and warning of dust storms in conjunction with effective and widespread information broadcasts will be essential to the prevention and mitigation of future risks and impacts. Human activities, seasonal variations and long-term climatic patterns influence dust storms. More research is needed to analyse these factors of dust mobilisation to create more certainty for the fate of vulnerable populations and ecosystems in the future. Early warning and communication systems, when in place and effectively implemented, can offer some relief to these vulnerable areas. As an issue that affects many regions of the world, there is a profound need to understand the potential changes and ultimately create better early warning systems for dust storms.

Studying the response of drivers against different collision warning systems: a review

NASA Astrophysics Data System (ADS)

Muzammel, M.; Yusoff, M. Zuki; Malik, A. Saeed; Mohamad Saad, M. Naufal; Meriaudeau, F.

2017-03-01

The number of vehicle accidents is rapidly increasing and causing significant economic losses in many countries. According to the World Health Organization, road accidents will become the fifth major cause of death by the year 2030. To minimize these accidents different types of collision warning systems have been proposed for motor vehicle drivers. These systems can early detect and warn the drivers about the potential danger, up to a certain accuracy. Many researchers study the effectiveness of these systems by using different methods, including Electroencephalography (EEG). From the literature review, it has been observed that, these systems increase the drivers' response and can help to minimize the accidents that may occur due to drivers unconsciousness. For these collision warning systems, tactile early warnings are found more effective as compared to the auditory and visual early warnings. This review also highlights the areas, where further research can be performed to fully analyze the collision warning system. For example, some contradictions are found among researchers, about these systems' performance for drivers within different age groups. Similarly, most of the EEG studies focus on the front collision warning systems and only give beep sound to alert the drivers. Therefore, EEG study can be performed for the rear end collision warning systems, against proper auditory warning messages which indicate the types of hazards. This EEG study will help to design more friendly collision warning system and may save many lives.

A new air quality monitoring and early warning system: Air quality assessment and air pollutant concentration prediction.

PubMed

Yang, Zhongshan; Wang, Jian

2017-10-01

Air pollution in many countries is worsening with industrialization and urbanization, resulting in climate change and affecting people's health, thus, making the work of policymakers more difficult. It is therefore both urgent and necessary to establish amore scientific air quality monitoring and early warning system to evaluate the degree of air pollution objectively, and predict pollutant concentrations accurately. However, the integration of air quality assessment and air pollutant concentration prediction to establish an air quality system is not common. In this paper, we propose a new air quality monitoring and early warning system, including an assessment module and forecasting module. In the air quality assessment module, fuzzy comprehensive evaluation is used to determine the main pollutants and evaluate the degree of air pollution more scientifically. In the air pollutant concentration prediction module, a novel hybridization model combining complementary ensemble empirical mode decomposition, a modified cuckoo search and differential evolution algorithm, and an Elman neural network, is proposed to improve the forecasting accuracy of six main air pollutant concentrations. To verify the effectiveness of this system, pollutant data for two cities in China are used. The result of the fuzzy comprehensive evaluation shows that the major air pollutants in Xi'an and Jinan are PM 10 and PM 2.5 respectively, and that the air quality of Xi'an is better than that of Jinan. The forecasting results indicate that the proposed hybrid model is remarkably superior to all benchmark models on account of its higher prediction accuracy and stability. Copyright © 2017 Elsevier Inc. All rights reserved.

Preparing for floods: flood forecasting and early warning

NASA Astrophysics Data System (ADS)

Cloke, Hannah

2016-04-01

Flood forecasting and early warning has continued to stride ahead in strengthening the preparedness phases of disaster risk management, saving lives and property and reducing the overall impact of severe flood events. For example, continental and global scale flood forecasting systems such as the European Flood Awareness System and the Global Flood Awareness System provide early information about upcoming floods in real time to various decisionmakers. Studies have found that there are monetary benefits to implementing these early flood warning systems, and with the science also in place to provide evidence of benefit and hydrometeorological institutional outlooks warming to the use of probabilistic forecasts, the uptake over the last decade has been rapid and sustained. However, there are many further challenges that lie ahead to improve the science supporting flood early warning and to ensure that appropriate decisions are made to maximise flood preparedness.

An Emergency Packet Forwarding Scheme for V2V Communication Networks

PubMed Central

2014-01-01

This paper proposes an effective warning message forwarding scheme for cooperative collision avoidance. In an emergency situation, an emergency-detecting vehicle warns the neighbor vehicles via an emergency warning message. Since the transmission range is limited, the warning message is broadcast in a multihop manner. Broadcast packets lead two challenges to forward the warning message in the vehicular network: redundancy of warning messages and competition with nonemergency transmissions. In this paper, we study and address the two major challenges to achieve low latency in delivery of the warning message. To reduce the intervehicle latency and end-to-end latency, which cause chain collisions, we propose a two-way intelligent broadcasting method with an adaptable distance-dependent backoff algorithm. Considering locations of vehicles, the proposed algorithm controls the broadcast of a warning message to reduce redundant EWM messages and adaptively chooses the contention window to compete with nonemergency transmission. Via simulations, we show that our proposed algorithm reduces the probability of rear-end crashes by 70% compared to previous algorithms by reducing the intervehicle delay. We also show that the end-to-end propagation delay of the warning message is reduced by 55%. PMID:25054181

Towards Operational Meteotsunami Early Warning System: the Adriatic Project MESSI

NASA Astrophysics Data System (ADS)

Vilibic, I.; Sepic, J.; Denamiel, C. L.; Mihanovic, H.; Muslim, S.; Tudor, M.; Ivankovic, D.; Jelavic, D.; Kovacevic, V.; Masce, T.; Dadic, V.; Gacic, M.; Horvath, K.; Monserrat, S.; Rabinovich, A.; Telisman-Prtenjak, M.

2017-12-01

A number of destructive meteotsunamis - atmospherically-driven long ocean waves in a tsunami frequency band - occurred during the last decade through the world oceans. Owing to significant damage caused by these meteotsunamis, several scientific groups (occasionally in collaboration with public offices) have started developing meteotsunami warning systems. Creation of one such system has been initialized in the late 2015 within the MESSI (Meteotsunamis, destructive long ocean waves in the tsunami frequency band: from observations and simulations towards a warning system) project. Main goal of this project is to build a prototype of a meteotsunami warning system for the eastern Adriatic coast. The system will be based on real-time measurements, operational atmosphere and ocean modeling and real time decision-making process. Envisioned MESSI meteotsunami warning system consists of three modules: (1) synoptic warning module, which will use established correlation between forecasted synoptic fields and high-frequency sea level oscillations to provide qualitative meteotsunami forecasts for up to a week in advance, (2) probabilistic premodeling prediction module, which will use operational WRF-ROMS-ADCIRC modeling system and compare the forecast with an atlas of presimulations to get the probabilistic meteotsunami forecast for up to three days in advance, and (3) real-time module, which is based on real time tracking of properties of air pressure disturbance (amplitude, speed, direction, period, ...) and their real-time comparison with the atlas of meteotsunami simulations. System will be tested on recent meteotsunami events which were recorded in the MESSI area shortly after the operational meteotsunami network installation. Albeit complex, such a multilevel warning system has a potential to be adapted to most meteotsunami hot spots, simply by tuning the system parameters to the available atmospheric and ocean data.

GPS-TEC of the Ionospheric Disturbances as a Tool for Early Tsunami Warning

NASA Astrophysics Data System (ADS)

Kunitsyn, Viacheslav E.; Nesterov, Ivan A.; Shalimov, Sergey L.; Krysanov, Boris Yu.; Padokhin, Artem M.; Rekenthaler, Douglas

2013-04-01

Recently, the GPS measurements were used for retrieving the information on the various types of ionospheric responses to seismic events (earthquakes, seismic Rayleigh waves, and tsunami) which generate atmospheric waves propagating up to the ionospheric altitudes where the collisions between the neutrals and charge particles give rise to the motion of the ionospheric plasma. These experimental results can well be used in architecture of the future tsunami warning system. The point is an earlier (in comparison with seismological methods) detection of the ionospheric signal that can indicate the moment of tsunami generation. As an example we consider the two-dimensional distributions of the vertical total electron content (TEC) variations in the ionosphere both close to and far from the epicenter of the Japan undersea earthquake of March 11, 2011 using radio tomographic (RT) reconstruction of high-temporal-resolution (2-minute) data from the Japan and the US GPS networks. Near-zone TEC variations shows a diverging ionospheric perturbation with multi-component spectral composition emerging after the main shock. The initial phase of the disturbance can be used as an indicator of the tsunami generation and subsequently for the tsunami early warning. Far-zone TEC variations reveals distinct wave train associated with gravity waves generated by tsunami. According to observations tsunami arrives at Hawaii and further at the coast of Southern California with delay relative to the gravity waves. Therefore the gravity wave pattern can be used in the early tsunami warning. We support this scenario by the results of modeling with the parameters of the ocean surface perturbation corresponding to the considered earthquake. In addition it was observed in the modeling that at long distance from the source the gravity wave can pass ahead of the tsunami. The work was supported by the Russian Foundation for Basic Research (grants 11-05-01157 and 12-05-33065).

Sensors Provide Early Warning of Biological Threats

NASA Technical Reports Server (NTRS)

2009-01-01

Early Warning Inc. of Troy, New York, licensed powerful biosensor technology from Ames Research Center. Incorporating carbon nanotubes tipped with single strands of nucleic acid from waterborne pathogens, the sensor can detect even minute amounts of targeted, disease causing bacteria, viruses, and parasites. Early Warning features the NASA biosensor in its water analyzer, which can provide advance alert of potential biological hazards in water used for agriculture, food and beverages, showers, and at beaches and lakes -- within hours instead of the days required by conventional laboratory methods.

Climate Engine - Monitoring Drought with Google Earth Engine

NASA Astrophysics Data System (ADS)

Hegewisch, K.; Daudert, B.; Morton, C.; McEvoy, D.; Huntington, J. L.; Abatzoglou, J. T.

2016-12-01

Drought has adverse effects on society through reduced water availability and agricultural production and increased wildfire risk. An abundance of remotely sensed imagery and climate data are being collected in near-real time that can provide place-based monitoring and early warning of drought and related hazards. However, in an era of increasing wealth of earth observations, tools that quickly access, compute, and visualize archives, and provide answers at relevant scales to better inform decision-making are lacking. We have developed ClimateEngine.org, a web application that uses Google's Earth Engine platform to enable users to quickly compute and visualize real-time observations. A suite of drought indices allow us to monitor and track drought from local (30-meters) to regional scales and contextualize current droughts within the historical record. Climate Engine is currently being used by U.S. federal agencies and researchers to develop baseline conditions and impact assessments related to agricultural, ecological, and hydrological drought. Climate Engine is also working with the Famine Early Warning Systems Network (FEWS NET) to expedite monitoring agricultural drought over broad areas at risk of food insecurity globally.

National dengue surveillance in the Lao People's Democratic Republic, 2006–2012: epidemiological and laboratory findings

PubMed Central

Khampapongpane, Bouaphanh; Ketmayoon, Pakapak; Phonekeo, Darouny; Somoulay, Virasack; Khamsing, Amphai; Phengxay, Manilay; Sisouk, Thongchanh; Vongphrachanh, Phengta; Bryant, Juliet E

2014-01-01

Although dengue has been a public health problem for several decades in the Lao People's Democratic Republic, the magnitude of the disease burden and epidemiological trends remain poorly understood. We analysed national dengue surveillance and laboratory data from 2006 to 2012 by person, place and time. Between 2006 and 2012, the annual dengue notification rate ranged between 62 and 367 cases per 100 000 population with an apparent geographical expansion of transmission throughout the country in recent years and concurrent co-circulation of all four dengue virus subtypes. An electronic database, called Lao People's Democratic Republic Early Warning Alert and Response Network, was introduced in 2008 to provide automated early warning for outbreaks and epidemics. Village outbreaks continue to be notified primarily through event-based surveillance, whereas the weekly indicator-based system provides systematic assessment of annual epidemic cycles. The dengue case data indicate a high and increasing burden of disease. Efforts now need to focus on using available data to prompt more effective outbreak response and to guide the design and implementation of intervention strategies. PMID:24734212

Decision Support Tool Evaluation Report for Coral Reef Early Warning System (CREWS) Version 7.0

NASA Technical Reports Server (NTRS)

D'Sa, Eurico; Hall, Callie; Zanoni, Vicki; Holland, Donald; Blonski, Slawomir; Pagnutti, Mary; Spruce, Joseph P.

2004-01-01

The Coral Reef Early Warning System (CREWS) is operated by NOAA's Office of Oceanic and Atmospheric Research as part of its Coral Reef Watch program in response to the deteriorating global state of coral reef and related benthic ecosystems. In addition to sea surface temperatures (SSTs), the two most important parameters used by the CREWS network in generating coral reef bleaching alerts are 1) wind speed and direction and 2) photosynthetically available radiation (PAR). NASA remote sensing products that can enhance CREWS in these areas include SST and PAR products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and wind data from the Quick Scatterometer (QuikSCAT). CREWS researchers are also interested in chlorophyll, chromophoric dissolved organic matter (CDOM), and salinity. Chlorophyll and CDOM are directly available as NASA products, while rainfall (an available NASA product) can be used as a proxy for salinity. Other potential NASA inputs include surface reflectance products from MODIS, the Advanced Spaceborne Thermal Emission and Reflection Radiometer, and Landsat. This report also identifies NASA-supported ocean circulation models and products from future satellite missions that might enchance the CREWS DST.

MyShake - A smartphone app to detect earthquake

NASA Astrophysics Data System (ADS)

Kong, Q.; Allen, R. M.; Schreier, L.; Kwon, Y. W.

2015-12-01

We designed an android app that harnesses the accelerometers in personal smartphones to record earthquake-shaking data for research, hazard information and warnings. The app has the function to distinguish earthquake shakings from daily human activities based on the different patterns behind the movements. It also can be triggered by the traditional earthquake early warning (EEW) system to record for a certain amount of time to collect earthquake data. When the app is triggered by the earthquake-like movements, it sends the trigger information back to our server which contains time and location of the trigger, at the same time, it stores the waveform data on local phone first, and upload to our server later. Trigger information from multiple phones will be processed in real time on the server to find the coherent signal to confirm the earthquakes. Therefore, the app provides the basis to form a smartphone seismic network that can detect earthquake and even provide warnings. A planned public roll-out of MyShake could collect millions of seismic recordings for large earthquakes in many regions around the world.

Toward tsunami early warning system in Indonesia by using rapid rupture durations estimation

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

Madlazim

2012-06-20

Indonesia has Indonesian Tsunami Early Warning System (Ina-TEWS) since 2008. The Ina-TEWS has used automatic processing on hypocenter; Mwp, Mw (mB) and Mj. If earthquake occurred in Ocean, depth < 70 km and magnitude > 7, then Ina-TEWS announce early warning that the earthquake can generate tsunami. However, the announcement of the Ina-TEWS is still not accuracy. Purposes of this research are to estimate earthquake rupture duration of large Indonesia earthquakes that occurred in Indian Ocean, Java, Timor sea, Banda sea, Arafura sea and Pasific ocean. We analyzed at least 330 vertical seismogram recorded by IRIS-DMC network using a directmore » procedure for rapid assessment of earthquake tsunami potential using simple measures on P-wave vertical seismograms on the velocity records, and the likelihood that the high-frequency, apparent rupture duration, T{sub dur}. T{sub dur} can be related to the critical parameters rupture length (L), depth (z), and shear modulus ({mu}) while T{sub dur} may be related to wide (W), slip (D), z or {mu}. Our analysis shows that the rupture duration has a stronger influence to generate tsunami than Mw and depth. The rupture duration gives more information on tsunami impact, Mo/{mu}, depth and size than Mw and other currently used discriminants. We show more information which known from the rupture durations. The longer rupture duration, the shallower source of the earthquake. For rupture duration greater than 50 s, the depth less than 50 km, Mw greater than 7, the longer rupture length, because T{sub dur} is proportional L and greater Mo/{mu}. Because Mo/{mu} is proportional L. So, with rupture duration information can be known information of the four parameters. We also suggest that tsunami potential is not directly related to the faulting type of source and for events that have rupture duration greater than 50 s, the earthquakes generated tsunami. With available real-time seismogram data, rapid calculation, rupture duration discriminant can be completed within 4-5 min after an earthquake occurs and thus can aid in effective, accuracy and reliable tsunami early warning for Indonesia region.« less

ERT to aid in WSN based early warning system for landslides

NASA Astrophysics Data System (ADS)

T, H.

2017-12-01

Amrita University's landslide monitoring and early warning system using Wireless Sensor Networks (WSN) consists of heterogeneous sensors like rain gauge, moisture sensor, piezometer, geophone, inclinometer, tilt meter etc. The information from the sensors are accurate and limited to that point. In order to monitor a large area, ERT can be used in conjunction with WSN technology. To accomplish the feasibility of ERT in landslide early warning along with WSN technology, we have conducted experiments in Amrita's landslide laboratory setup. The experiment was aimed to simulate landslide, and monitor the changes happening in the soil using moisture sensor and ERT. Simulating moisture values from resistivity measurements to a greater accuracy can help in landslide monitoring for large areas. For accomplishing the same we have adapted two mathematical approaches, 1) Regression analysis between resistivity measurements and actual moisture values from moisture sensor, and 2) Using Waxman Smith model to simulate moisture values from resistivity measurements. The simulated moisture values from Waxman Smith model is compared with the actual moisture values and the Mean Square Error (MSE) is found to be 46.33. Regression curve is drawn for the resistivity vs simulated moisture values from Waxman model, and it is compared with the regression curve of actual model, which is shown in figure-1. From figure-1, it is clear that there the regression curve from actual moisture values and the regression curve from simulated moisture values, follow the similar pattern and there is a small difference between them. Moisture values can be simulated to a greater accuracy using actual regression equation, but the limitation is that, regression curves will differ for different sites and different soils. Regression equation from actual moisture values can be used, if we have conducted experiment in the laboratory for a particular soil sample, otherwise with the knowledge of soil properties, Waxman model can be used to simulate moisture values. The promising results assure that, ERT measurements when used in conjunction with WSN technique, vital paramters triggering landslides like moisture can be simulated for a large area, which will help in providing early warning for large areas.

Early Warnings for Local Labor Markets

ERIC Educational Resources Information Center

Matland, Marc A.

1976-01-01

This articles summarizes the National Planning Association's (NPA) experience in its initial efforts to develop an early warning system to anticipate job openings generated in local communities by large Federal procurement contracts. (WL)

U.S. Unmanned Aerial Vehicles (UAVs) and Network Centric Warfare (NCW): Impacts on Combat Aviation Tactics from Gulf War I Through 2007 Iraq

DTIC Science & Technology

2008-03-01

early warning AIM Air-intercept missile AJCN Adaptive, joint, C4ISR node AOR Area of responsibility ARM Anti-radiation missile ATARS Advanced...Tactical Airborne Reconnaissance System ( ATARS ) on F-16 and F/A-18 aircraft, and satellites. Manned platforms were adapted to multiple mission scenarios... Psychological Ops X Tern/Leaflet Dispensing, 2004 All Weather/ Night Strike X DASH/Vietnam, 1960s Predator/Afghanistan/Iraq, 2001 36

A Distributed Architecture for Tsunami Early Warning and Collaborative Decision-support in Crises

NASA Astrophysics Data System (ADS)

Moßgraber, J.; Middleton, S.; Hammitzsch, M.; Poslad, S.

2012-04-01

The presentation will describe work on the system architecture that is being developed in the EU FP7 project TRIDEC on "Collaborative, Complex and Critical Decision-Support in Evolving Crises". The challenges for a Tsunami Early Warning System (TEWS) are manifold and the success of a system depends crucially on the system's architecture. A modern warning system following a system-of-systems approach has to integrate various components and sub-systems such as different information sources, services and simulation systems. Furthermore, it has to take into account the distributed and collaborative nature of warning systems. In order to create an architecture that supports the whole spectrum of a modern, distributed and collaborative warning system one must deal with multiple challenges. Obviously, one cannot expect to tackle these challenges adequately with a monolithic system or with a single technology. Therefore, a system architecture providing the blueprints to implement the system-of-systems approach has to combine multiple technologies and architectural styles. At the bottom layer it has to reliably integrate a large set of conventional sensors, such as seismic sensors and sensor networks, buoys and tide gauges, and also innovative and unconventional sensors, such as streams of messages from social media services. At the top layer it has to support collaboration on high-level decision processes and facilitates information sharing between organizations. In between, the system has to process all data and integrate information on a semantic level in a timely manner. This complex communication follows an event-driven mechanism allowing events to be published, detected and consumed by various applications within the architecture. Therefore, at the upper layer the event-driven architecture (EDA) aspects are combined with principles of service-oriented architectures (SOA) using standards for communication and data exchange. The most prominent challenges on this layer include providing a framework for information integration on a syntactic and semantic level, leveraging distributed processing resources for a scalable data processing platform, and automating data processing and decision support workflows.

Continuous estimates on the earthquake early warning magnitude by use of the near-field acceleration records

NASA Astrophysics Data System (ADS)

Li, Jun; Jin, Xing; Wei, Yongxiang; Zhang, Hongcai

2013-10-01

In this article, the seismic records of Japan's Kik-net are selected to measure the acceleration, displacement, and effective peak acceleration of each seismic record within a certain time after P wave, then a continuous estimation is given on earthquake early warning magnitude through statistical analysis method, and Wenchuan earthquake record is utilized to check the method. The results show that the reliability of earthquake early warning magnitude continuously increases with the increase of the seismic information, the biggest residual happens if the acceleration is adopted to fit earthquake magnitude, which may be caused by rich high-frequency components and large dispersion of peak value in acceleration record, the influence caused by the high-frequency components can be effectively reduced if the effective peak acceleration and peak displacement is adopted, it is estimated that the dispersion of earthquake magnitude obviously reduces, but it is easy for peak displacement to be affected by long-period drifting. In various components, the residual enlargement phenomenon at vertical direction is almost unobvious, thus it is recommended in this article that the effective peak acceleration at vertical direction is preferred to estimate earthquake early warning magnitude. Through adopting Wenchuan strong earthquake record to check the method mentioned in this article, it is found that this method can be used to quickly, stably, and accurately estimate the early warning magnitude of this earthquake, which shows that this method is completely applicable for earthquake early warning.

On the Potential Uses of Static Offsets Derived From Low-Cost Community Instruments and Crowd-Sourcing for Earthquake Monitoring and Rapid Response

NASA Astrophysics Data System (ADS)

Minson, S. E.; Brooks, B. A.; Murray, J. R.; Iannucci, R. A.

2013-12-01

We explore the efficacy of low-cost community instruments (LCCIs) and crowd-sourcing to produce rapid estimates of earthquake magnitude and rupture characteristics which can be used for earthquake loss reduction such as issuing tsunami warnings and guiding rapid response efforts. Real-time high-rate GPS data are just beginning to be incorporated into earthquake early warning (EEW) systems. These data are showing promising utility including producing moment magnitude estimates which do not saturate for the largest earthquakes and determining the geometry and slip distribution of the earthquake rupture in real-time. However, building a network of scientific-quality real-time high-rate GPS stations requires substantial infrastructure investment which is not practicable in many parts of the world. To expand the benefits of real-time geodetic monitoring globally, we consider the potential of pseudorange-based GPS locations such as the real-time positioning done onboard cell phones or on LCCIs that could be distributed in the same way accelerometers are distributed as part of the Quake Catcher Network (QCN). While location information from LCCIs often have large uncertainties, their low cost means that large numbers of instruments can be deployed. A monitoring network that includes smartphones could collect data from potentially millions of instruments. These observations could be averaged together to substantially decrease errors associated with estimated earthquake source parameters. While these data will be inferior to data recorded by scientific-grade seismometers and GPS instruments, there are features of community-based data collection (and possibly analysis) that are very attractive. This approach creates a system where every user can host an instrument or download an application to their smartphone that both provides them with earthquake and tsunami warnings while also providing the data on which the warning system operates. This symbiosis helps to encourage people to both become users of the warning system and to contribute data to the system. Further, there is some potential to take advantage of the LCCI hosts' computing and communications resources to do some of the analysis required for the warning system. We will present examples of the type of data which might be observed by pseudorange-based positioning for both actual earthquakes and laboratory tests as well as performance tests of potential earthquake source modeling derived from pseudorange data. A highlight of these performance tests is a case study of the 2011 Mw 9 Tohoku-oki earthquake.

Toward Global Drought Early Warning Capability - Expanding International Cooperation for the Development of a Framework for Monitoring and Forecasting

NASA Technical Reports Server (NTRS)

Pozzi, Will; Sheffield, Justin; Stefanski, Robert; Cripe, Douglas; Pulwarty, Roger; Vogt, Jurgen V.; Heim, Richard R., Jr.; Brewer, Michael J.; Svoboda, Mark; Westerhoff, Rogier;

Feasibility of Using Elastic Wave Velocity Monitoring for Early Warning of Rainfall-Induced Slope Failure.

PubMed

Chen, Yulong; Irfan, Muhammad; Uchimura, Taro; Zhang, Ke

2018-03-27

Rainfall-induced landslides are one of the most widespread slope instability phenomena posing a serious risk to public safety worldwide so that their temporal prediction is of great interest to establish effective warning systems. The objective of this study is to determine the effectiveness of elastic wave velocities in the surface layer of the slope in monitoring, prediction and early warning of landslide. The small-scale fixed and varied, and large-scale slope model tests were conducted. Analysis of the results has established that the elastic wave velocity continuously decreases in response of moisture content and deformation and there was a distinct surge in the decrease rate of wave velocity when failure was initiated. Based on the preliminary results of this analysis, the method using the change in elastic wave velocity proves superior for landslide early warning and suggests that a warning be issued at switch of wave velocity decrease rate.

Research to Operations: From Point Positions, Earthquake and Tsunami Modeling to GNSS-augmented Tsunami Early Warning

NASA Astrophysics Data System (ADS)

Stough, T.; Green, D. S.

2017-12-01

This collaborative research to operations demonstration brings together the data and algorithms from NASA research, technology, and applications-funded projects to deliver relevant data streams, algorithms, predictive models, and visualization tools to the NOAA National Tsunami Warning Center (NTWC) and Pacific Tsunami Warning Center (PTWC). Using real-time GNSS data and models in an operational environment, we will test and evaluate an augmented capability for tsunami early warning. Each of three research groups collect data from a selected network of real-time GNSS stations, exchange data consisting of independently processed 1 Hz station displacements, and merge the output into a single, more accurate and reliable set. The resulting merged data stream is delivered from three redundant locations to the TWCs with a latency of 5-10 seconds. Data from a number of seismogeodetic stations with collocated GPS and accelerometer instruments are processed for displacements and seismic velocities and also delivered. Algorithms for locating and determining the magnitude of earthquakes as well as algorithms that compute the source function of a potential tsunami using this new data stream are included in the demonstration. The delivered data, algorithms, models and tools are hosted on NOAA-operated machines at both warning centers, and, once tested, the results will be evaluated for utility in improving the speed and accuracy of tsunami warnings. This collaboration has the potential to dramatically improve the speed and accuracy of the TWCs local tsunami information over the current seismometer-only based methods. In our first year of this work, we have established and deployed an architecture for data movement and algorithm installation at the TWC's. We are addressing data quality issues and porting algorithms into the TWCs operating environment. Our initial module deliveries will focus on estimating moment magnitude (Mw) from Peak Ground Displacement (PGD), within 2-3 minutes of the event, and coseismic displacements converging to static offsets. We will also develop visualizations of module outputs tailored to the operational environment. In the context of this work, we will also discuss this research to operations approach and other opportunities within the NASA Applied Science Disaster Program.

A Cardiac Early Warning System with Multi Channel SCG and ECG Monitoring for Mobile Health

PubMed Central

Sahoo, Prasan Kumar; Thakkar, Hiren Kumar; Lee, Ming-Yih

2017-01-01

Use of information and communication technology such as smart phone, smart watch, smart glass and portable health monitoring devices for healthcare services has made Mobile Health (mHealth) an emerging research area. Coronary Heart Disease (CHD) is considered as a leading cause of death world wide and an increasing number of people die prematurely due to CHD. Under such circumstances, there is a growing demand for a reliable cardiac monitoring system to catch the intermittent abnormalities and detect critical cardiac behaviors which lead to sudden death. Use of mobile devices to collect Electrocardiography (ECG), Seismocardiography (SCG) data and efficient analysis of those data can monitor a patient’s cardiac activities for early warning. This paper presents a novel cardiac data acquisition method and combined analysis of Electrocardiography (ECG) and multi channel Seismocardiography (SCG) data. An early warning system is implemented to monitor the cardiac activities of a person and accuracy assessment of the early warning system is conducted for the ECG data only. The assessment shows 88% accuracy and effectiveness of our proposed analysis, which implies the viability and applicability of the proposed early warning system. PMID:28353681

A Cardiac Early Warning System with Multi Channel SCG and ECG Monitoring for Mobile Health.

PubMed

Sahoo, Prasan Kumar; Thakkar, Hiren Kumar; Lee, Ming-Yih

2017-03-29

Use of information and communication technology such as smart phone, smart watch, smart glass and portable health monitoring devices for healthcare services has made Mobile Health (mHealth) an emerging research area. Coronary Heart Disease (CHD) is considered as a leading cause of death world wide and an increasing number of people die prematurely due to CHD. Under such circumstances, there is a growing demand for a reliable cardiac monitoring system to catch the intermittent abnormalities and detect critical cardiac behaviors which lead to sudden death. Use of mobile devices to collect Electrocardiography (ECG), Seismocardiography (SCG) data and efficient analysis of those data can monitor a patient's cardiac activities for early warning. This paper presents a novel cardiac data acquisition method and combined analysis of Electrocardiography (ECG) and multi channel Seismocardiography (SCG) data. An early warning system is implemented to monitor the cardiac activities of a person and accuracy assessment of the early warning system is conducted for the ECG data only. The assessment shows 88% accuracy and effectiveness of our proposed analysis, which implies the viability and applicability of the proposed early warning system.

The seismic project of the National Tsunami Hazard Mitigation Program

USGS Publications Warehouse

Oppenheimer, D.H.; Bittenbinder, A.N.; Bogaert, B.M.; Buland, R.P.; Dietz, L.D.; Hansen, R.A.; Malone, S.D.; McCreery, C.S.; Sokolowski, T.J.; Whitmore, P.M.; Weaver, C.S.

2005-01-01

In 1997, the Federal Emergency Management Agency (FEMA), National Oceanic and Atmospheric Administration (NOAA), U.S. Geological Survey (USGS), and the five western States of Alaska, California, Hawaii, Oregon, and Washington joined in a partnership called the National Tsunami Hazard Mitigation Program (NTHMP) to enhance the quality and quantity of seismic data provided to the NOAA tsunami warning centers in Alaska and Hawaii. The NTHMP funded a seismic project that now provides the warning centers with real-time seismic data over dedicated communication links and the Internet from regional seismic networks monitoring earthquakes in the five western states, the U.S. National Seismic Network in Colorado, and from domestic and global seismic stations operated by other agencies. The goal of the project is to reduce the time needed to issue a tsunami warning by providing the warning centers with high-dynamic range, broadband waveforms in near real time. An additional goal is to reduce the likelihood of issuing false tsunami warnings by rapidly providing to the warning centers parametric information on earthquakes that could indicate their tsunamigenic potential, such as hypocenters, magnitudes, moment tensors, and shake distribution maps. New or upgraded field instrumentation was installed over a 5-year period at 53 seismic stations in the five western states. Data from these instruments has been integrated into the seismic network utilizing Earthworm software. This network has significantly reduced the time needed to respond to teleseismic and regional earthquakes. Notably, the West Coast/Alaska Tsunami Warning Center responded to the 28 February 2001 Mw 6.8 Nisqually earthquake beneath Olympia, Washington within 2 minutes compared to an average response time of over 10 minutes for the previous 18 years. ?? Springer 2005.

Anatomy of Historical Tsunamis: Lessons Learned for Tsunami Warning

NASA Astrophysics Data System (ADS)

Igarashi, Y.; Kong, L.; Yamamoto, M.; McCreery, C. S.

2011-11-01

Tsunamis are high-impact disasters that can cause death and destruction locally within a few minutes of their occurrence and across oceans hours, even up to a day, afterward. Efforts to establish tsunami warning systems to protect life and property began in the Pacific after the 1946 Aleutian Islands tsunami caused casualties in Hawaii. Seismic and sea level data were used by a central control center to evaluate tsunamigenic potential and then issue alerts and warnings. The ensuing events of 1952, 1957, and 1960 tested the new system, which continued to expand and evolve from a United States system to an international system in 1965. The Tsunami Warning System in the Pacific (ITSU) steadily improved through the decades as more stations became available in real and near-real time through better communications technology and greater bandwidth. New analysis techniques, coupled with more data of higher quality, resulted in better detection, greater solution accuracy, and more reliable warnings, but limitations still exist in constraining the source and in accurately predicting propagation of the wave from source to shore. Tsunami event data collected over the last two decades through international tsunami science surveys have led to more realistic models for source generation and inundation, and within the warning centers, real-time tsunami wave forecasting will become a reality in the near future. The tsunami warning system is an international cooperative effort amongst countries supported by global and national monitoring networks and dedicated tsunami warning centers; the research community has contributed to the system by advancing and improving its analysis tools. Lessons learned from the earliest tsunamis provided the backbone for the present system, but despite 45 years of experience, the 2004 Indian Ocean tsunami reminded us that tsunamis strike and kill everywhere, not just in the Pacific. Today, a global intergovernmental tsunami warning system is coordinated under the United Nations. This paper reviews historical tsunamis, their warning activities, and their sea level records to highlight lessons learned with the focus on how these insights have helped to drive further development of tsunami warning systems and their tsunami warning centers. While the international systems do well for teletsunamis, faster detection, more accurate evaluations, and widespread timely alerts are still the goals, and challenges still remain to achieving early warning against the more frequent and destructive local tsunamis.

Landslide monitoring and early warning systems in Lower Austria - current situation and new developments

NASA Astrophysics Data System (ADS)

Thiebes, Benni; Glade, Thomas; Schweigl, Joachim; Jäger, Stefan; Canli, Ekrem

2014-05-01

Landslides represent significant hazards in the mountainous areas of Austria. The Regional Geological Surveys are responsible to inform and protect the population, and to mitigate damage to infrastructure. Efforts of the Regional Geological Survey of Lower Austria include detailed site investigations, the planning and installation of protective structures (e.g. rock fall nets) as well as preventive measures such as regional scale landslide susceptibility assessments. For potentially endangered areas, where protection works are not feasible or would simply be too costly, monitoring systems have been installed. However, these systems are dominantly not automatic and require regular field visits to take measurements. Therefore, it is difficult to establish any relation between initiating and controlling factors, thus to fully understand the underlying process mechanism which is essential for any early warning system. Consequently, the implementation of new state-of-the-art monitoring and early warning systems has been started. In this presentation, the design of four landslide monitoring and early warning systems is introduced. The investigated landslide process types include a deep-seated landslide, a rock fall site, a complex earth flow, and a debris flow catchment. The monitoring equipment was chosen depending on the landslide processes and their activity. It aims to allow for a detailed investigation of process mechanisms in relation to its triggers and for reliable prediction of future landslide activities. The deep-seated landslide will be investigated by manual and automatic inclinometers to get detailed insights into subsurface displacements. In addition, TDR sensors and a weather station will be employed to get a better understanding on the influence of rainfall on sub-surface hydrology. For the rockfall site, a wireless sensor network will be installed to get real-time information on acceleration and inclination of potentially unstable blocks. The movement of the earth flow site will be monitored by differential GPS to get high precision information on displacements of marked points. Photogrammtetry based on octocopter surveys will provide spatial information on movement patterns. A similar approach will be followed for the debris flow catchment. Here, the focus lies on a monitoring of the landslide failures in the source area which prepares the material for subsequent debris flow transport. In addition to the methods already mentioned, repeated terrestrial laserscanning campaigns will be used to monitor geomorphological changes at all sites. All important data, which can be single measurements, episodic or continuous monitoring data for a given point (e.g. rainfall, inclination) or of spatial character (e.g. LiDAR measurements), are collected and analysed on an external server. Automatic data analysis methods, such as progressive failure analysis, are carried out automatically based on field measurements. The data and results from all monitoring sites are visualised on a web-based platform which enables registered users to analyse the respective information in near-real-time. Moreover, thresholds can be determined which trigger automated warning messages to the involved scientists if thresholds are exceeded by field measurements. The described system will enable scientists and decision-makers to access the latest data from the monitoring systems. Automatic alarms are raised when thresholds are exceeded to inform them about potentially hazardous changes. Thereby, a more efficient hazard management and early warning can be achieved. Keywords: landslide, rockfall, debris flow, earth flow, monitoring, early warning system.

Landslide and Flood Warning System Prototypes based on Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Hloupis, George; Stavrakas, Ilias; Triantis, Dimos

2010-05-01

Wireless sensor networks (WSNs) are one of the emerging areas that received great attention during the last few years. This is mainly due to the fact that WSNs have provided scientists with the capability of developing real-time monitoring systems equipped with sensors based on Micro-Electro-Mechanical Systems (MEMS). WSNs have great potential for many applications in environmental monitoring since the sensor nodes that comprised from can host several MEMS sensors (such as temperature, humidity, inertial, pressure, strain-gauge) and transducers (such as position, velocity, acceleration, vibration). The resulting devices are small and inexpensive but with limited memory and computing resources. Each sensor node contains a sensing module which along with an RF transceiver. The communication is broadcast-based since the network topology can change rapidly due to node failures [1]. Sensor nodes can transmit their measurements to central servers through gateway nodes without any processing or they make preliminary calculations locally in order to produce results that will be sent to central servers [2]. Based on the above characteristics, two prototypes using WSNs are presented in this paper: A Landslide detection system and a Flood warning system. Both systems sent their data to central processing server where the core of processing routines exists. Transmission is made using Zigbee and IEEE 802.11b protocol but is capable to use VSAT communication also. Landslide detection system uses structured network topology. Each measuring node comprises of a columnar module that is half buried to the area under investigation. Each sensing module contains a geophone, an inclinometer and a set of strain gauges. Data transmitted to central processing server where possible landslide evolution is monitored. Flood detection system uses unstructured network topology since the failure rate of sensor nodes is expected higher. Each sensing module contains a custom water level sensor (based on plastic optical fiber). Data transmitted directly to server where the early warning algorithms monitor the water level variations in real time. Both sensor nodes use power harvesting techniques in order to extend their battery life as much as possible. [1] Yick J.; Mukherjee, B.; Ghosal, D. Wireless sensor network survey. Comput. Netw. 2008, 52, 2292-2330. [2] Garcia, M.; Bri, D.; Boronat, F.; Lloret, J. A new neighbor selection strategy for group-based wireless sensor networks, In The Fourth International Conference on Networking and Services (ICNS 2008), Gosier, Guadalupe, March 16-21, 2008.

Advanced instrumentation for the collection, retrieval, and processing of urban stormwater data

USGS Publications Warehouse

Robinson, Jerald B.; Bales, Jerad D.; Young, Wendi S.; ,

1995-01-01

The U.S. Geological Survey, in cooperation with the City of Charlotte and Mecklenburg County, North Carolina, has developed a data-collection network that uses advanced instrumentation to automatically collect, retrieve, and process urban stormwater data. Precipitation measurement and water-quality networks provide data for (1) planned watershed simulation models, (2) early warning of possible flooding, (3) computation of material export, and (4) characterization of water quality in relation to basin conditions. Advantages of advanced instrumentation include remote access to real-time data, reduced demands on and more efficient use of limited human resources, and direct importation of data into a geographical information system for display and graphic analysis.

Tritium-powered radiation sensor network

NASA Astrophysics Data System (ADS)

Litz, Marc S.; Russo, Johnny A.; Katsis, Dimos

2016-05-01

Isotope power supplies offer long-lived (100 years using 63Ni), low-power energy sources, enabling sensors or communications nodes for the lifetime of infrastructure. A tritium beta-source (12.5-year half-life) encapsulated in a phosphor-lined vial couples directly to a photovoltaic (PV) to generate a trickle current into an electrical load. An inexpensive design is described using commercial-of-the-shelf (COTS) components that generate 100 μWe for nextgeneration compact electronics/sensors. A matched radiation sensor has been built for long-duration missions utilizing microprocessor-controlled sleep modes, low-power electronic components, and a passive interrupt driven environmental wake-up. The low-power early-warning radiation detector network and isotope power source enables no-maintenance mission lifetimes.

RED Alert – Early warning or detection of global re-emerging infectious disease (RED)

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

Deshpande, Alina

This is the PDF of a presentation for a webinar given by Los Alamos National Laboratory (LANL) on the early warning or detection of global re-emerging infectious disease (RED). First, there is an overview of LANL biosurveillance tools. Then, information is given about RED Alert. Next, a demonstration is given of a component prototype. RED Alert is an analysis tool that can provide early warning or detection of the re-emergence of an infectious disease at the global level, but through a local lens.

The use of early warning scores to recognise and respond to patient deterioration in district nursing.

PubMed

Tucker, Guy; Lusher, Adele

2018-02-02

This discussion article focuses on the literature surrounding early warning scoring systems and their use in primary care, specifically within district nursing. Patient deterioration is a global concern, associated with high mortality rates and avoidable deaths. Early recognition and response by nursing and other health care staff has been attributed to early warning scoring systems (EWSS) and tools. However, the use of equivalent tools in the community appears to be lacking. This review concludes that there is no consensus over the use of EWSS in district nursing and culture of practice is varied, rather than standardised.

Evaluation of Real-Time and Off-Line Performance of the Virtual Seismologist Earthquake Early Warning Algorithm in Switzerland

NASA Astrophysics Data System (ADS)

Behr, Yannik; Clinton, John; Cua, Georgia; Cauzzi, Carlo; Heimers, Stefan; Kästli, Philipp; Becker, Jan; Heaton, Thomas

2013-04-01

The Virtual Seismologist (VS) method is a Bayesian approach to regional network-based earthquake early warning (EEW) originally formulated by Cua and Heaton (2007). Implementation of VS into real-time EEW codes has been an on-going effort of the Swiss Seismological Service at ETH Zürich since 2006, with support from ETH Zürich, various European projects, and the United States Geological Survey (USGS). VS is one of three EEW algorithms that form the basis of the California Integrated Seismic Network (CISN) ShakeAlert system, a USGS-funded prototype end-to-end EEW system that could potentially be implemented in California. In Europe, VS is currently operating as a real-time test system in Switzerland. As part of the on-going EU project REAKT (Strategies and Tools for Real-Time Earthquake Risk Reduction), VS installations in southern Italy, western Greece, Istanbul, Romania, and Iceland are planned or underway. In Switzerland, VS has been running in real-time on stations monitored by the Swiss Seismological Service (including stations from Austria, France, Germany, and Italy) since 2010. While originally based on the Earthworm system it has recently been ported to the SeisComp3 system. Besides taking advantage of SeisComp3's picking and phase association capabilities it greatly simplifies the potential installation of VS at networks in particular those already running SeisComp3. We present the architecture of the new SeisComp3 based version and compare its results from off-line tests with the real-time performance of VS in Switzerland over the past two years. We further show that the empirical relationships used by VS to estimate magnitudes and ground motion, originally derived from southern California data, perform well in Switzerland.

Impacts assessment of dynamic speed harmonization with queue warning : task 3, impacts assessment report.

DOT National Transportation Integrated Search

2015-06-01

This report assesses the impacts of a prototype of Dynamic Speed Harmonization (SPD-HARM) with Queue Warning (Q-WARN), which are two component applications of the Intelligent Network Flow Optimization (INFLO) bundle. The assessment is based on an ext...

Early warning, warning or alarm systems for natural hazards? A generic classification.

NASA Astrophysics Data System (ADS)

Sättele, Martina; Bründl, Michael; Straub, Daniel

2013-04-01

Early warning, warning and alarm systems have gained popularity in recent years as cost-efficient measures for dangerous natural hazard processes such as floods, storms, rock and snow avalanches, debris flows, rock and ice falls, landslides, flash floods, glacier lake outburst floods, forest fires and even earthquakes. These systems can generate information before an event causes loss of property and life. In this way, they mainly mitigate the overall risk by reducing the presence probability of endangered objects. These systems are typically prototypes tailored to specific project needs. Despite their importance there is no recognised system classification. This contribution classifies warning and alarm systems into three classes: i) threshold systems, ii) expert systems and iii) model-based expert systems. The result is a generic classification, which takes the characteristics of the natural hazard process itself and the related monitoring possibilities into account. The choice of the monitoring parameters directly determines the system's lead time. The classification of 52 active systems moreover revealed typical system characteristics for each system class. i) Threshold systems monitor dynamic process parameters of ongoing events (e.g. water level of a debris flow) and incorporate minor lead times. They have a local geographical coverage and a predefined threshold determines if an alarm is automatically activated to warn endangered objects, authorities and system operators. ii) Expert systems monitor direct changes in the variable disposition (e.g crack opening before a rock avalanche) or trigger events (e.g. heavy rain) at a local scale before the main event starts and thus offer extended lead times. The final alarm decision incorporates human, model and organisational related factors. iii) Model-based expert systems monitor indirect changes in the variable disposition (e.g. snow temperature, height or solar radiation that influence the occurrence probability of snow avalanches) or trigger events (e.g. heavy snow fall) to predict spontaneous hazard events in advance. They encompass regional or national measuring networks and satisfy additional demands such as the standardisation of the measuring stations. The developed classification and the characteristics, which were revealed for each class, yield a valuable input to quantifying the reliability of warning and alarm systems. Importantly, this will facilitate to compare them with well-established standard mitigation measures such as dams, nets and galleries within an integrated risk management approach.

MyShake - Smartphone seismic network powered by citizen scientists

NASA Astrophysics Data System (ADS)

Kong, Q.; Allen, R. M.; Schreier, L.; Strauss, J. A.

2017-12-01

MyShake is a global smartphone seismic network that harnesses the power of crowdsourcing. It is driven by the citizen scientists that run MyShake on their personal smartphones. It has two components: an android application running on the smartphones to detect earthquake-like motion, and a network detection algorithm to aggregate results from multiple smartphones to confirm when an earthquake occurs. The MyShake application was released to the public on Feb 12th 2016. Within the first year, more than 250,000 people downloaded MyShake app around the world. There are more than 500 earthquakes recorded by the smartphones in this period, including events in Chile, Argentina, Mexico, Morocco, Greece, Nepal, New Zealand, Taiwan, Japan, and across North America. Currently, we are working on earthquake early warning with MyShake network and the shaking data provided by MyShake is a unique dataset that can be used for the research community.

Early Warning Look Ahead Metrics: The Percent Milestone Backlog Metric

NASA Technical Reports Server (NTRS)

Shinn, Stephen A.; Anderson, Timothy P.

2017-01-01

All complex development projects experience delays and corresponding backlogs of their project control milestones during their acquisition lifecycles. NASA Goddard Space Flight Center (GSFC) Flight Projects Directorate (FPD) teamed with The Aerospace Corporation (Aerospace) to develop a collection of Early Warning Look Ahead metrics that would provide GSFC leadership with some independent indication of the programmatic health of GSFC flight projects. As part of the collection of Early Warning Look Ahead metrics, the Percent Milestone Backlog metric is particularly revealing, and has utility as a stand-alone execution performance monitoring tool. This paper describes the purpose, development methodology, and utility of the Percent Milestone Backlog metric. The other four Early Warning Look Ahead metrics are also briefly discussed. Finally, an example of the use of the Percent Milestone Backlog metric in providing actionable insight is described, along with examples of its potential use in other commodities.

Research on the Risk Early Warning Method of Material Supplier Performance in Power Industry

NASA Astrophysics Data System (ADS)

Chen, Peng; Zhang, Xi

2018-01-01

The early warning of supplier performance risk is still in the initial stage interiorly, and research on the early warning mechanism to identify, analyze and prevent the performance risk is few. In this paper, a new method aiming at marerial supplier performance risk in power industry is proposed, firstly, establishing a set of risk early warning indexes, Then use the ECM method to classify the indexes to form different risk grades. Then, improving Crock Ford risk quantization model by considering three indicators, including the stability of power system, economic losses and successful bid ratio to form the predictive risk grade, and ultimately using short board effect principle to form the ultimate risk grade to truly reflect the supplier performance risk. Finally, making empirical analysis on supplier performance and putting forward the counter measures and prevention strategies for different risks.

Early warning method of Glacial Lake Outburst Floods based on temperature and rainfall

NASA Astrophysics Data System (ADS)

Liu, Jingjing; Su, Pengcheng; Cheng, Zunlan

2017-04-01

Glacial lake outburst floods (GLOFs) are serious disasters in glacial areas. At present, glaciers are retreating while glacial lake area and the outburst risk increases due to the global warming. Therefore, the research of early warning method of GLOFs is important to prevent and reduce the disasters. This paper provides an early warning method using the temperature and rainfall as indices. The daily growth rate of positive antecedent accumulative temperature and the antecedent thirty days accumulative precipitation are calculated for 21 events of GLOF before 2010, based on data from the 21 meteorological stations nearby. The result shows that all the events are above the curve, TV = -0.0193RDC + 3.0018, which can be taken as the early warning threshold curve. This has been verified by the GLOF events in the Ranzeaco glacial lake on 2013-07-05.

Landslide early warning system prototype with GIS analysis indicates by soil movement and rainfall

NASA Astrophysics Data System (ADS)

Artha, Y.; Julian, E. S.

2018-01-01

The aim of this paper is developing and testing of landslide early warning system. The early warning system uses accelerometersas ground movement and tilt-sensing device and a water flow sensor. A microcentroller is used to process the input signal and activate the alarm. An LCD is used to display the acceleration in x,y and z axis. When the soil moved or shifted and rainfall reached 100 mm/day, the alarm rang and signal were sentto the monitoring center via a telemetry system.Data logging information and GIS spatial data can be monitored remotely as tables and graphics as well as in the form of geographical map with the help of web-GIS interface. The system were tested at Kampung Gerendong, Desa Putat Nutug, Kecamatan Ciseeng, Kabupaten Bogor. This area has 3.15 cumulative score, which mean vulnerable to landslide. The results show that the early warning system worked as planned.

HRAS: a webserver for early warning of human health risk brought by aflatoxin.

PubMed

Hu, Ruifeng; Zeng, Xu; Gao, Weiwei; Wang, Qian; Liu, Zhihua

2013-02-01

Most people are aware that outdoor air pollution can damage their health, but many do not know that indoor air pollution can also exhibit significant negative health effects. Fungi parasitizing in air conditioning and ventilation systems can be one of indoor air pollution sources. Aflatoxin produced by Aspergillus flavus (A. flavus) became a central focus of indoor air pollution, especially in farmer markets. Therefore we developed an early warning system, Health Risk Assessment System, to estimate the growth rate of A. flavus, predict the amount of aflatoxin and provide early warning information. Firstly, the growth of A. flavus and the production of aflatoxin under different conditions were widely obtained through a comprehensive literature review. Secondly, three mathematical models were established to predict the A. flavus colony growth rate, lag phase duration and aflatoxin content, as functions of temperature and water activity based on present studies. Finally, all the results were evaluated by the user-supplied data using PHP programming language. We utilized the web page to show the results and display warning information. The JpGraph library was used to create a dynamic line chart, refreshing the warning information dynamically in real-time. The HARS provides accurate information for early warning purposes to let us take timely steps to protect ourselves.

A hazard-independent approach for the standardised multi-channel dissemination of warning messages

NASA Astrophysics Data System (ADS)

Esbri Palomares, M. A.; Hammitzsch, M.; Lendholt, M.

2012-04-01

The tsunami disaster affecting the Indian Ocean region on Christmas 2004 demonstrated very clearly the shortcomings in tsunami detection, public warning processes as well as intergovernmental warning message exchange in the Indian Ocean region. In that regard, early warning systems require that the dissemination of early warning messages has to be executed in way that ensures that the message delivery is timely; the message content is understandable, usable and accurate. To that end, diverse and multiple dissemination channels must be used to increase the chance of the messages reaching all affected persons in a hazard scenario. In addition to this, usage of internationally accepted standards for the warning dissemination such as the Common Alerting Protocol (CAP) and Emergency Data Exchange Language (EDXL) Distribution Element specified by the Organization for the Advancement of Structured Information Standards (OASIS) increase the interoperability among different warning systems enabling thus the concept of system-of-systems proposed by GEOSS. The project Distant Early Warning System (DEWS), co-funded by the European Commission under the 6th Framework Programme, aims at strengthening the early warning capacities by building an innovative generation of interoperable tsunami early warning systems based on the above mentioned concepts following a Service-oriented Architecture (SOA) approach. The project focuses on the downstream part of the hazard information processing where customized, user-tailored warning messages and alerts flow from the warning centre to the responsible authorities and/or the public with their different needs and responsibilities. The information logistics services within DEWS generate tailored EDXL-DE/CAP warning messages for each user that must receive the message according to their preferences, e.g., settings for language, interested areas, dissemination channels, etc.. However, the significant difference in the implementation and capabilities of different dissemination channels such as SMS, email and television, have bearing on the information processing required for delivery and consumption of a DEWS EDXL-DE/CAP message over each dissemination channel. These messages may include additional information in the form of maps, graphs, documents, sensor observations, etc. Therefore, the generated messages are pre-processed by channel adaptors in the information dissemination services converting it into a format that is suitable for end-to-end delivery over the dissemination channels without any semantic distortion. The approach followed by DEWS for disseminating warnings not only relies on traditional communication ways used by the already established early warnings such as the delivery of faxes and phone calls but takes into consideration the use of other broadly used communication channels such as SMS, email, narrowcast and broadcast television, instant messaging, Voice over IP, and radio. It also takes advantage of social media channels like RSS feeds, Facebook, Twitter, etc., enabling a multiplier effect, like in the case of radio and television, and thus allowing to create mash-ups by aggregating other sources of information to the original message. Finally, status information is also important in order to assess and understand whether the process of disseminating the warning to the message consumers has been successfully completed or the process failed at some point of the dissemination chain. To that end, CAP-based messages generated within the information dissemination services provide the semantics for those fields that are of interest within the context of reporting the warning dissemination status in DEWS.

The impact of Early Warning Score and Rapid Response Systems on nurses' competence: An integrative literature review and synthesis.

PubMed

Jensen, Jørghild Karlotte; Skår, Randi; Tveit, Bodil

2018-04-01

To describe, interpret and synthesise the current research findings on the impact of the Early Warning Score and Rapid Response Systems on nurses' competence in identifying and managing deteriorating patients in general hospital wards. As patient safety initiatives designed to ensure the early identification and management of deteriorating patients, the Early Warning Score and Rapid Response Systems have broad appeal. However, it is still unclear how these systems impact nurses' competence when these systems are used in general hospital wards. CINAHL, PubMed, Cochrane, EMBASE and Ovid MEDLINE databases were systematically searched for relevant articles. Articles were appraised, a thematic analysis was conducted, and similar and divergent perspectives on emergent themes and subthemes were extracted by a team of researchers. Thirty-six studies met the inclusion criteria. The analysis of findings showed how the Early Warning Score and Rapid Response Systems impacted three competence areas: (i) Nurses' competence in assessing and caring for patients related to the subthemes: (a) sensing clinical deterioration and (b) the development of skills and knowledge. (ii). Nurses' competence in referring patients, related to the subthemes: (a) deciding whether to summon help and (b) the language and communication lines in the referral process. (ii) Nurses' coping and mastery experiences. The impact of the Early Warning Score and Rapid Response Systems on nurses' competence in identifying and managing deteriorating patients is beneficial but also somewhat contradictory. A greater understanding of nurses' development of competence when using the Early Warning Score and Rapid Response Systems will facilitate the design of implementation strategies and the use of these systems to improve practice. © 2017 John Wiley & Sons Ltd.

Early Warning Systems: Re-Engaging Chronic Truants

ERIC Educational Resources Information Center

Chorneau, Tom

2012-01-01

School attendance can be an early indicator that something is going wrong with a student. Gathering, analyzing, and acting on attendance information is a first step toward school improvement. Meanwhile, the majority of the states are moving to build and enhance what are called "early warning systems," intended to flag at-risk students during their…

Design of a reliable and operational landslide early warning system at regional scale

NASA Astrophysics Data System (ADS)

Calvello, Michele; Piciullo, Luca; Gariano, Stefano Luigi; Melillo, Massimo; Brunetti, Maria Teresa; Peruccacci, Silvia; Guzzetti, Fausto

2017-04-01

Landslide early warning systems at regional scale are used to warn authorities, civil protection personnel and the population about the occurrence of rainfall-induced landslides over wide areas, typically through the prediction and measurement of meteorological variables. A warning model for these systems must include a regional correlation law and a decision algorithm. A regional correlation law can be defined as a functional relationship between rainfall and landslides; it is typically based on thresholds of rainfall indicators (e.g., cumulated rainfall, rainfall duration) related to different exceedance probabilities of landslide occurrence. A decision algorithm can be defined as a set of assumptions and procedures linking rainfall thresholds to warning levels. The design and the employment of an operational and reliable early warning system for rainfall-induced landslides at regional scale depend on the identification of a reliable correlation law as well as on the definition of a suitable decision algorithm. Herein, a five-step process chain addressing both issues and based on rainfall thresholds is proposed; the procedure is tested in a landslide-prone area of the Campania region in southern Italy. To this purpose, a database of 96 shallow landslides triggered by rainfall in the period 2003-2010 and rainfall data gathered from 58 rain gauges are used. First, a set of rainfall thresholds are defined applying a frequentist method to reconstructed rainfall conditions triggering landslides in the test area. In the second step, several thresholds at different exceedance probabilities are evaluated, and different percentile combinations are selected for the activation of three warning levels. Subsequently, within steps three and four, the issuing of warning levels is based on the comparison, over time and for each combination, between the measured rainfall and the pre-defined warning level thresholds. Finally, the optimal percentile combination to be employed in the regional early warning system is selected evaluating the model performance in terms of success and error indicators by means of the "event, duration matrix, performance" (EDuMaP) method.

TrigDB for improving the reliability of the epicenter locations by considering the neighborhood station's trigger and cutting out of outliers in operation of Earthquake Early Warning System.

NASA Astrophysics Data System (ADS)

Chi, H. C.; Park, J. H.; Lim, I. S.; Seong, Y. J.

2016-12-01

TrigDB is initially developed for the discrimination of teleseismic-origin false alarm in the case with unreasonably associated triggers producing mis-located epicenters. We have applied TrigDB to the current EEWS(Earthquake Early Warning System) from 2014. During the early stage of testing EEWS from 2011, we adapted ElarmS from US Berkeley BSL to Korean seismic network and applied more than 5 years. We found out that the real-time testing results of EEWS in Korea showed that all events inside of seismic network with bigger than magnitude 3.0 were well detected. However, two events located at sea area gave false location results with magnitude over 4.0 due to the long period and relatively high amplitude signals related to the teleseismic waves or regional deep sources. These teleseismic-relevant false events were caused by logical co-relation during association procedure and the corresponding geometric distribution of associated stations is crescent-shaped. Seismic stations are not deployed uniformly, so the expected bias ratio varies with evaluated epicentral location. This ratio is calculated in advance and stored into database, called as TrigDB, for the discrimination of teleseismic-origin false alarm. We upgraded this method, so called `TrigDB back filling', updating location with supplementary association of stations comparing triggered times between sandwiched stations which was not associated previously based on predefined criteria such as travel-time. And we have tested a module to reject outlier trigger times by setting a criteria comparing statistical values(Sigma) to the triggered times. The criteria of cutting off the outlier is slightly slow to work until the number of stations more than 8, however, the result of location is very much improved.

Exploring the utility of real-time hydrologic data for landslide early warning

NASA Astrophysics Data System (ADS)

Mirus, B. B.; Smith, J. B.; Becker, R.; Baum, R. L.; Koss, E.

2017-12-01

Early warning systems can provide critical information for operations managers, emergency planners, and the public to help reduce fatalities, injuries, and economic losses due to landsliding. For shallow, rainfall-triggered landslides early warning systems typically use empirical rainfall thresholds, whereas the actual triggering mechanism involves the non-linear hydrological processes of infiltration, evapotranspiration, and hillslope drainage that are more difficult to quantify. Because hydrologic monitoring has demonstrated that shallow landslides are often preceded by a rise in soil moisture and pore-water pressures, some researchers have developed early warning criteria that attempt to account for these antecedent wetness conditions through relatively simplistic storage metrics or soil-water balance modeling. Here we explore the potential for directly incorporating antecedent wetness into landslide early warning criteria using recent landslide inventories and in-situ hydrologic monitoring near Seattle, WA, and Portland, OR. We use continuous, near-real-time telemetered soil moisture and pore-water pressure data measured within a few landslide-prone hillslopes in combination with measured and forecasted rainfall totals to inform easy-to-interpret landslide initiation thresholds. Objective evaluation using somewhat limited landslide inventories suggests that our new thresholds based on subsurface hydrologic monitoring and rainfall data compare favorably to the capabilities of existing rainfall-only thresholds for the Seattle area, whereas there are no established rainfall thresholds for the Portland area. This preliminary investigation provides a proof-of-concept for the utility of developing landslide early warning criteria in two different geologic settings using real-time subsurface hydrologic measurements from in-situ instrumentation.

Effects of stressor characteristics on early warning signs of critical transitions and "critical coupling" in complex dynamical systems.

PubMed

Blume, Steffen O P; Sansavini, Giovanni

2017-12-01

Complex dynamical systems face abrupt transitions into unstable and catastrophic regimes. These critical transitions are triggered by gradual modifications in stressors, which push the dynamical system towards unstable regimes. Bifurcation analysis can characterize such critical thresholds, beyond which systems become unstable. Moreover, the stochasticity of the external stressors causes small-scale fluctuations in the system response. In some systems, the decomposition of these signal fluctuations into precursor signals can reveal early warning signs prior to the critical transition. Here, we present a dynamical analysis of a power system subjected to an increasing load level and small-scale stochastic load perturbations. We show that the auto- and cross-correlations of bus voltage magnitudes increase, leading up to a Hopf bifurcation point, and further grow until the system collapses. This evidences a gradual transition into a state of "critical coupling," which is complementary to the established concept of "critical slowing down." Furthermore, we analyze the effects of the type of load perturbation and load characteristics on early warning signs and find that gradient changes in the autocorrelation provide early warning signs of the imminent critical transition under white-noise but not for auto-correlated load perturbations. Furthermore, the cross-correlation between all voltage magnitude pairs generally increases prior to and beyond the Hopf bifurcation point, indicating "critical coupling," but cannot provide early warning indications. Finally, we show that the established early warning indicators are oblivious to limit-induced bifurcations and, in the case of the power system model considered here, only react to an approaching Hopf bifurcation.

The effect of adult Early Warning Systems education on nurses' knowledge, confidence and clinical performance: A systematic review.

PubMed

Saab, Mohamad M; McCarthy, Bridie; Andrews, Tom; Savage, Eileen; Drummond, Frances J; Walshe, Nuala; Forde, Mary; Breen, Dorothy; Henn, Patrick; Drennan, Jonathan; Hegarty, Josephine

2017-11-01

This review aims to determine the effect of adult Early Warning Systems education on nurses' knowledge, confidence and clinical performance. Early Warning Systems support timely identification of clinical deterioration and prevention of avoidable deaths. Several educational programmes have been designed to help nurses recognize and manage deteriorating patients. Little is known as to the effectiveness of these programmes. Systematic review. Academic Search Complete, CINAHL, MEDLINE, PsycINFO, PsycARTICLES, Psychology and Behavioral Science Collection, SocINDEX and the UK & Ireland Reference Centre, EMBASE, the Turning Research Into Practice database, the Cochrane Central Register of Controlled Trials (CENTRAL) and Grey Literature sources were searched between October and November 2015. This is a quantitative systematic review using Cochrane methods. Studies published between January 2011 - November 2015 in English were sought. The risk of bias, level of evidence and the quality of evidence per outcome were assessed. Eleven articles with 10 studies were included. Nine studies addressed clinical performance, four addressed knowledge and two addressed confidence. Knowledge, vital signs recording and Early Warning Score calculation were improved in the short term. Two interventions had no effect on nurses' response to clinical deterioration and use of communication tools. This review highlights the importance of measuring outcomes using standardized tools and valid and reliable instruments. Using longitudinal designs, researchers are encouraged to investigate the effect of Early Warning Systems educational programmes. These can include interactive e-learning, on-site interdisciplinary Early Warning Scoring systems training sessions and simulated scenarios. © 2017 John Wiley & Sons Ltd.

RESPONSE OF THE GREEK EARLY WARNING SYSTEM REUTER-STOKES IONIZATION CHAMBERS TO TERRESTRIAL AND COSMIC RADIATION EVALUATED IN COMPARISON WITH SPECTROSCOPIC DATA AND TIME SERIES ANALYSIS.

PubMed

Leontaris, F; Clouvas, A; Xanthos, S; Maltezos, A; Potiriadis, C; Kiriakopoulos, E; Guilhot, J

2018-02-01

The Telemetric Early Warning System Network of the Greek Atomic Energy Commission consists mainly of a network of 24 Reuter-Stokes high-pressure ionization chambers (HPIC) for gamma dose rate measurements and covers all Greece. In the present work, the response of the Reuter-Stokes HPIC to terrestrial and cosmic radiation was evaluated in comparison with spectroscopic data obtained by in situ gamma spectrometry measurements with portable hyper pure Germanium detectors (HPGe), near the Reuter-Stokes detectors and time series analysis. For the HPIC detectors, a conversion factor for the measured absorbed dose rate in air (in nGy h-1) to the total ambient dose equivalent rate Ḣ*(10), due to terrestrial and cosmic component, was deduced by the field measurements. Time series analysis of the mean monthly dose rate (measured by the Reuter-Stokes detector in Thessaloniki, northern Greece, from 2001 to 2016) was performed with advanced statistical methods (Fast Fourier Analysis and Zhao Atlas Marks Transform). Fourier analysis reveals several periodicities (periodogram). The periodogram of the absorbed dose rate in air values was compared with the periodogram of the values measured for the same period (2001-16) and in the same location with a NaI (Tl) detector which in principle is not sensitive to cosmic radiation. The obtained results are presented and discussed. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Early warning reporting categories analysis of recall and complaints data.

DOT National Transportation Integrated Search

2001-12-31

This analysis was performed to assist the National Highway Traffic Safety Administration (NHTSA) in identifying components and systems to be included in early warning reporting (EWR) categories that would be based upon historical safety-related recal...

The Multi-Parameter Wireless Sensing System (MPwise): Its Description and Application to Earthquake Risk Mitigation.

PubMed

Boxberger, Tobias; Fleming, Kevin; Pittore, Massimiliano; Parolai, Stefano; Pilz, Marco; Mikulla, Stefan

2017-10-20

The Multi-Parameter Wireless Sensing (MPwise) system is an innovative instrumental design that allows different sensor types to be combined with relatively high-performance computing and communications components. These units, which incorporate off-the-shelf components, can undertake complex information integration and processing tasks at the individual unit or node level (when used in a network), allowing the establishment of networks that are linked by advanced, robust and rapid communications routing and network topologies. The system (and its predecessors) was originally designed for earthquake risk mitigation, including earthquake early warning (EEW), rapid response actions, structural health monitoring, and site-effect characterization. For EEW, MPwise units are capable of on-site, decentralized, independent analysis of the recorded ground motion and based on this, may issue an appropriate warning, either by the unit itself or transmitted throughout a network by dedicated alarming procedures. The multi-sensor capabilities of the system allow it to be instrumented with standard strong- and weak-motion sensors, broadband sensors, MEMS (namely accelerometers), cameras, temperature and humidity sensors, and GNSS receivers. In this work, the MPwise hardware, software and communications schema are described, as well as an overview of its possible applications. While focusing on earthquake risk mitigation actions, the aim in the future is to expand its capabilities towards a more multi-hazard and risk mitigation role. Overall, MPwise offers considerable flexibility and has great potential in contributing to natural hazard risk mitigation.

The Multi-Parameter Wireless Sensing System (MPwise): Its Description and Application to Earthquake Risk Mitigation

PubMed Central

Boxberger, Tobias; Fleming, Kevin; Pittore, Massimiliano; Parolai, Stefano; Pilz, Marco; Mikulla, Stefan

2017-01-01

The Multi-Parameter Wireless Sensing (MPwise) system is an innovative instrumental design that allows different sensor types to be combined with relatively high-performance computing and communications components. These units, which incorporate off-the-shelf components, can undertake complex information integration and processing tasks at the individual unit or node level (when used in a network), allowing the establishment of networks that are linked by advanced, robust and rapid communications routing and network topologies. The system (and its predecessors) was originally designed for earthquake risk mitigation, including earthquake early warning (EEW), rapid response actions, structural health monitoring, and site-effect characterization. For EEW, MPwise units are capable of on-site, decentralized, independent analysis of the recorded ground motion and based on this, may issue an appropriate warning, either by the unit itself or transmitted throughout a network by dedicated alarming procedures. The multi-sensor capabilities of the system allow it to be instrumented with standard strong- and weak-motion sensors, broadband sensors, MEMS (namely accelerometers), cameras, temperature and humidity sensors, and GNSS receivers. In this work, the MPwise hardware, software and communications schema are described, as well as an overview of its possible applications. While focusing on earthquake risk mitigation actions, the aim in the future is to expand its capabilities towards a more multi-hazard and risk mitigation role. Overall, MPwise offers considerable flexibility and has great potential in contributing to natural hazard risk mitigation. PMID:29053608

A new type of tri-axial accelerometers with high dynamic range MEMS for earthquake early warning

NASA Astrophysics Data System (ADS)

Peng, Chaoyong; Chen, Yang; Chen, Quansheng; Yang, Jiansi; Wang, Hongti; Zhu, Xiaoyi; Xu, Zhiqiang; Zheng, Yu

2017-03-01

Earthquake Early Warning System (EEWS) has shown its efficiency for earthquake damage mitigation. As the progress of low-cost Micro Electro Mechanical System (MEMS), many types of MEMS-based accelerometers have been developed and widely used in deploying large-scale, dense seismic networks for EEWS. However, the noise performance of these commercially available MEMS is still insufficient for weak seismic signals, leading to the large scatter of early-warning parameters estimation. In this study, we developed a new type of tri-axial accelerometer based on high dynamic range MEMS with low noise level using for EEWS. It is a MEMS-integrated data logger with built-in seismological processing. The device is built on a custom-tailored Linux 2.6.27 operating system and the method for automatic detecting seismic events is STA/LTA algorithms. When a seismic event is detected, peak ground parameters of all data components will be calculated at an interval of 1 s, and τc-Pd values will be evaluated using the initial 3 s of P wave. These values will then be organized as a trigger packet actively sent to the processing center for event combining detection. The output data of all three components are calibrated to sensitivity 500 counts/cm/s2. Several tests and a real field test deployment were performed to obtain the performances of this device. The results show that the dynamic range can reach 98 dB for the vertical component and 99 dB for the horizontal components, and majority of bias temperature coefficients are lower than 200 μg/°C. In addition, the results of event detection and real field deployment have shown its capabilities for EEWS and rapid intensity reporting.

New insights into flood warning reception and emergency response by affected parties

NASA Astrophysics Data System (ADS)

Kreibich, Heidi; Müller, Meike; Schröter, Kai; Thieken, Annegret H.

2017-11-01

Flood damage can be mitigated if the parties at risk are reached by flood warnings and if they know how to react appropriately. To gain more knowledge about warning reception and emergency response of private households and companies, surveys were undertaken after the August 2002 and the June 2013 floods in Germany. Despite pronounced regional differences, the results show a clear overall picture: in 2002, early warnings did not work well; e.g. many households (27 %) and companies (45 %) stated that they had not received any flood warnings. Additionally, the preparedness of private households and companies was low in 2002, mainly due to a lack of flood experience. After the 2002 flood, many initiatives were launched and investments undertaken to improve flood risk management, including early warnings and an emergency response in Germany. In 2013, only a small share of the affected households (5 %) and companies (3 %) were not reached by any warnings. Additionally, private households and companies were better prepared. For instance, the share of companies which have an emergency plan in place has increased from 10 % in 2002 to 34 % in 2013. However, there is still room for improvement, which needs to be triggered mainly by effective risk and emergency communication. The challenge is to continuously maintain and advance an integrated early warning and emergency response system even without the occurrence of extreme floods.

Towards an Earthquake and Tsunami Early Warning in the Caribbean

NASA Astrophysics Data System (ADS)

Huerfano Moreno, V. A.; Vanacore, E. A.

2017-12-01

The Caribbean region (CR) has a documented history of large damaging earthquakes and tsunamis that have affected coastal areas, including the events of Jamaica in 1692, Virgin Islands in 1867, Puerto Rico in 1918, the Dominican Republic in 1946 and Haiti in 2010. There is clear evidence that tsunamis have been triggered by large earthquakes that deformed the ocean floor around the Caribbean Plate boundary. The CR is monitored jointly by national/regional/local seismic, geodetic and sea level networks. All monitoring institutions are participating in the UNESCO ICG/Caribe EWS, the purpose of this initiative is to minimize loss of life and destruction of property, and to mitigate against catastrophic economic impacts via promoting local research, real time (RT) earthquake, geodetic and sea level data sharing and improving warning capabilities and enhancing education and outreach strategies. Currently more than, 100 broad-band seismic, 65 sea levels and 50 GPS high rate stations are available in real or near real-time. These real-time streams are used by Local/Regional or Worldwide detection and warning institutions to provide earthquake source parameters in a timely manner. Currently, any Caribbean event detected to have a magnitude greater than 4.5 is evaluated, and sea level is measured, by the TWC for tsumanigenic potential. The regional cooperation is motivated both by research interests as well as geodetic, seismic and tsunami hazard monitoring and warning. It will allow the imaging of the tectonic structure of the Caribbean region to a high resolution which will consequently permit further understanding of the seismic source properties for moderate and large events and the application of this knowledge to procedures of civil protection. To reach its goals, the virtual network has been designed following the highest technical standards: BB sensors, 24 bits A/D converters with 140 dB dynamic range, real-time telemetry. Here we will discuss the state of the PR component of this virtual network as well as current advances in the imaging of the PR tectonic structure. The goal of this presentation is to describe the Puerto Rico Seismic Network (PRSN) system, including the real time earthquake and tsunami monitoring as well as the specific protocols used to broadcast earthquake/tsunami messages locally.

The quality and value of seasonal precipitation forecasts for an early warning of large-scale droughts and floods in West Africa

NASA Astrophysics Data System (ADS)

Bliefernicht, Jan; Seidel, Jochen; Salack, Seyni; Waongo, Moussa; Laux, Patrick; Kunstmann, Harald

2017-04-01

Seasonal precipitation forecasts are a crucial source of information for an early warning of hydro-meteorological extremes in West Africa. However, the current seasonal forecasting system used by the West African weather services in the framework of the West African Climate Outlook forum (PRESAO) is limited to probabilistic precipitation forecasts of 1-month lead time. To improve this provision, we use an ensemble-based quantile-quantile transformation for bias correction of precipitation forecasts provided by a global seasonal ensemble prediction system, the Climate Forecast System Version 2 (CFS2). The statistical technique eliminates systematic differences between global forecasts and observations with the potential to preserve the signal from the model. The technique has also the advantage that it can be easily implemented at national weather services with low capacities. The statistical technique is used to generate probabilistic forecasts of monthly and seasonal precipitation amount and other precipitation indices useful for an early warning of large-scale drought and floods in West Africa. The evaluation of the statistical technique is done using CFS hindcasts (1982 to 2009) in a cross-validation mode to determine the performance of the precipitation forecasts for several lead times focusing on drought and flood events depicted over the Volta and Niger basins. In addition, operational forecasts provided by PRESAO are analyzed from 1998 to 2015. The precipitation forecasts are compared to low-skill reference forecasts generated from gridded observations (i.e. GPCC, CHIRPS) and a novel in-situ gauge database from national observation networks (see Poster EGU2017-10271). The forecasts are evaluated using state-of-the-art verification techniques to determine specific quality attributes of probabilistic forecasts such as reliability, accuracy and skill. In addition, cost-loss approaches are used to determine the value of probabilistic forecasts for multiple users in warning situations. The outcomes of the hindcasts experiment for the Volta basin illustrate that the statistical technique can clearly improve the CFS precipitation forecasts with the potential to provide skillful and valuable early precipitation warnings for large-scale drought and flood situations several months in ahead. In this presentation we give a detailed overview about the ensemble-based quantile-quantile-transformation, its validation and verification and the possibilities of this technique to complement PRESAO. We also highlight the performance of this technique for extremes such as the Sahel drought in the 80ties and in comparison to the various reference data sets (e.g. CFS2, PRESAO, observational data sets) used in this study.

A review of influenza detection and prediction through social networking sites.

PubMed

Alessa, Ali; Faezipour, Miad

2018-02-01

Early prediction of seasonal epidemics such as influenza may reduce their impact in daily lives. Nowadays, the web can be used for surveillance of diseases. Search engines and social networking sites can be used to track trends of different diseases seven to ten days faster than government agencies such as Center of Disease Control and Prevention (CDC). CDC uses the Illness-Like Influenza Surveillance Network (ILINet), which is a program used to monitor Influenza-Like Illness (ILI) sent by thousands of health care providers in order to detect influenza outbreaks. It is a reliable tool, however, it is slow and expensive. For that reason, many studies aim to develop methods that do real time analysis to track ILI using social networking sites. Social media data such as Twitter can be used to predict the spread of flu in the population and can help in getting early warnings. Today, social networking sites (SNS) are used widely by many people to share thoughts and even health status. Therefore, SNS provides an efficient resource for disease surveillance and a good way to communicate to prevent disease outbreaks. The goal of this study is to review existing alternative solutions that track flu outbreak in real time using social networking sites and web blogs. Many studies have shown that social networking sites can be used to conduct real time analysis for better predictions.

A Multi-User Game-Theoretical Multipath Routing Protocol to Send Video-Warning Messages over Mobile Ad Hoc Networks.

PubMed

Mezher, Ahmad Mohamad; Igartua, Mónica Aguilar; de la Cruz Llopis, Luis J; Pallarès Segarra, Esteve; Tripp-Barba, Carolina; Urquiza-Aguiar, Luis; Forné, Jordi; Sanvicente Gargallo, Emilio

2015-04-17

The prevention of accidents is one of the most important goals of ad hoc networks in smart cities. When an accident happens, dynamic sensors (e.g., citizens with smart phones or tablets, smart vehicles and buses, etc.) could shoot a video clip of the accident and send it through the ad hoc network. With a video message, the level of seriousness of the accident could be much better evaluated by the authorities (e.g., health care units, police and ambulance drivers) rather than with just a simple text message. Besides, other citizens would be rapidly aware of the incident. In this way, smart dynamic sensors could participate in reporting a situation in the city using the ad hoc network so it would be possible to have a quick reaction warning citizens and emergency units. The deployment of an efficient routing protocol to manage video-warning messages in mobile Ad hoc Networks (MANETs) has important benefits by allowing a fast warning of the incident, which potentially can save lives. To contribute with this goal, we propose a multipath routing protocol to provide video-warning messages in MANETs using a novel game-theoretical approach. As a base for our work, we start from our previous work, where a 2-players game-theoretical routing protocol was proposed to provide video-streaming services over MANETs. In this article, we further generalize the analysis made for a general number of N players in the MANET. Simulations have been carried out to show the benefits of our proposal, taking into account the mobility of the nodes and the presence of interfering traffic. Finally, we also have tested our approach in a vehicular ad hoc network as an incipient start point to develop a novel proposal specifically designed for VANETs.

Combination of High Rate, Real-Time GNSS and Accelerometer Observations and Rapid Seismic Event Notification for Earthquake Early Warning and Volcano Monitoring with a Focus on the Pacific Rim.

NASA Astrophysics Data System (ADS)

Zimakov, L. G.; Passmore, P.; Raczka, J.; Alvarez, M.; Jackson, M.

2014-12-01

Scientific GNSS networks are moving towards a model of real-time data acquisition, epoch-by-epoch storage integrity, and on-board real-time position and displacement calculations. This new paradigm allows the integration of real-time, high-rate GNSS displacement information with acceleration and velocity data to create very high-rate displacement records. The mating of these two instruments allows the creation of a new, very high-rate (200 sps) displacement observable that has the full-scale displacement characteristics of GNSS and high-precision dynamic motions of seismic technologies. It is envisioned that these new observables can be used for earthquake early warning studies, volcano monitoring, and critical infrastructure monitoring applications. Our presentation will focus on the characteristics of GNSS, seismic, and strong motion sensors in high dynamic environments, including historic earthquakes in Southern California and the Pacific Rim, replicated on a shake table, over a range of displacements and frequencies. We will explore the optimum integration of these sensors from a filtering perspective including simple harmonic impulses over varying frequencies and amplitudes and under the dynamic conditions of various earthquake scenarios. In addition we will discuss implementation of a Rapid Seismic Event Notification System that provides quick delivery of digital data from seismic stations to the acquisition and processing center and a full data integrity model for real-time earthquake notification that provides warning prior to significant ground shaking.

The analysis results of EEWS(Earthquake Early Warning System) about Iksan(Ml4.3) and Ulsan(Ml5.0) earthquakes in Korea

NASA Astrophysics Data System (ADS)

Park, J. H.; Chi, H. C.; Lim, I. S.; Seong, Y. J.; Pak, J.

2016-12-01

EEW(Earthquake Early Warning) service to the public has been officially operated by KMA (Korea Meteorological Administration) from 2015 in Korea. For the KMA's official EEW service, KIGAM has adopted ElarmS from UC Berkeley BSL and modified local magnitude relation, 1-D travel time curves and association procedures with real time waveforms from about 160 seismic stations of KMA and KIGAM. We have checked the performance of EEWS(Earthquake Early Warning System) reviewing two moderate size earthquakes: one is Iksan Eq.(Ml4.3) inside of networks and the other is Ulsan Eq.(Ml5.0) happened at the southern east sea of Korea outside of networks. The first trigger time at NPR station of the Iksan Eq. took 2.3 sec and BUY and JEO2 stations were associated to produce the first event version in 10.07 sec from the origin time respectively. Because the epicentral distance of JEO2 station is about 30 km and the estimated travel time is 6.2 sec, the delay time including transmission and processing is estimated as 3.87 sec with assumption that P wave velocity is 5 km/sec and the focal depth is 8 km. The first magnitude was M4.9 which was a little bigger than Ml4.3 by KIGAM. After adding 3 more triggers of stations (CHO, KMSA, PORA), the estimated magnitude became to M4.6 and the final was settled down to M4.3 with 10 stations. In the case of Ulsan the first trigger time took 11.04 sec and the first alert time with 3 stations in 14.8 sec from the origin time (OT) respectively. The first magnitude was M5.2, however, the difference between the first EEW epicenter and the manual final result was about 63 km due to the poor azimuth coverage outside of seismic network. After 16.2 sec from OT the fourth station YSB was used to update the location near to the manual results within 6 km with magnitude 5.0 and location and magnitude were stable with more stations. Ulsan Eq. was the first case announced to the public by EEWS and the process and result were successful, however, we have to make more effort to reduce the delay times and improve tools for the communication with the public in Korea.

Recent Progress of Seismic Observation Networks in Japan

NASA Astrophysics Data System (ADS)

Okada, Y.

2013-04-01

Before the occurrence of disastrous Kobe earthquake in 1995, the number of high sensitivity seismograph stations operated in Japan was nearly 550 and was concentrated in the Kanto and Tokai districts, central Japan. In the wake of the Kobe earthquake, Japanese government has newly established the Headquarters for Earthquake Research Promotion and started the reconstruction of seismic networks to evenly cover the whole Japan. The basic network is composed of three seismographs, i.e. high sensitivity seismograph (Hi-net), broadband seismograph (F-net), and strong motion seismograph (K-NET). A large majority of Hi-net stations are also equipped with a pair of strong motion sensors at the bottom of borehole and the ground surface (KiK-net). A plenty of high quality data obtained from these networks are circulated at once and is producing several new seismological findings as well as providing the basis for the Earthquake Early Warning system. In March 11, 2011, "Off the Pacific coast of Tohoku Earthquake" was generated with magnitude 9.0, which records the largest in the history of seismic observation in Japan. The greatest disaster on record was brought by huge tsunami with nearly 20 thousand killed or missing people. We are again noticed that seismic observation system is quite poor in the oceanic region compared to the richness of it in the inland region. In 2012, NIED has started the construction of ocean bottom seismic and tsunami observation network along the Japan Trench. It is planned to layout 154 stations with an average spacing of 30km, each of which is equipped with an accelerometer for seismic observation and a water pressure gauge for tsunami observation. We are expecting that more rapid and accurate warning of earthquake and tsunami becomes possible by this observing network.

77 FR 55605 - Early Warning Reporting, Foreign Defect Reporting, and Motor Vehicle and Equipment Recall...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-10

... requires quarterly reporting of early warning information: Production information; information on incidents... manufacturers, and other equipment manufacturers) and the annual production of the entity. The EWR information... vehicle type as part of [[Page 55608

Coral Reef Early Warning System (CREWS) RPC Experiment

NASA Technical Reports Server (NTRS)

Estep, Leland; Spruce, Joseph P.; Hall, Callie

2007-01-01

This viewgraph document reviews the background, objectives, methodology, validation, and present status of the Coral Reef Early Warning System (CREWS) Rapid Prototyping Capability (RPC) experiment. The potential NASA contribution to CREWS Decision Support Tool (DST) centers on remotely sensed imagery products.

Early warning systems for the management of chronic heart failure: a systematic literature review of cost-effectiveness models.

PubMed

Albuquerque De Almeida, Fernando; Al, Maiwenn; Koymans, Ron; Caliskan, Kadir; Kerstens, Ankie; Severens, Johan L

2018-04-01

Describing the general and methodological characteristics of decision-analytical models used in the economic evaluation of early warning systems for the management of chronic heart failure patients and performing a quality assessment of their methodological characteristics is expected to provide concise and useful insight to inform the future development of decision-analytical models in the field of heart failure management. Areas covered: The literature on decision-analytical models for the economic evaluation of early warning systems for the management of chronic heart failure patients was systematically reviewed. Nine electronic databases were searched through the combination of synonyms for heart failure and sensitive filters for cost-effectiveness and early warning systems. Expert commentary: The retrieved models show some variability with regards to their general study characteristics. Overall, they display satisfactory methodological quality, even though some points could be improved, namely on the consideration and discussion of any competing theories regarding model structure and disease progression, identification of key parameters and the use of expert opinion, and uncertainty analyses. A comprehensive definition of early warning systems and further research under this label should be pursued. To improve the transparency of economic evaluation publications, authors should make available detailed technical information regarding the published models.

Research and application of a novel hybrid air quality early-warning system: A case study in China.

PubMed

Li, Chen; Zhu, Zhijie

2018-06-01

As one of the most serious meteorological disasters in modern society, air pollution has received extensive attention from both citizens and decision-makers. With the complexity of pollution components and the uncertainty of prediction, it is both critical and challenging to construct an effective and practical early-warning system. In this paper, a novel hybrid air quality early-warning system for pollution contaminant monitoring and analysis was proposed. To improve the efficiency of the system, an advanced attribute selection method based on fuzzy evaluation and rough set theory was developed to select the main pollution contaminants for cities. Moreover, a hybrid model composed of the theory of "decomposition and ensemble", an extreme learning machine and an advanced heuristic algorithm was developed for pollution contaminant prediction; it provides deterministic and interval forecasting for tackling the uncertainty of future air quality. Daily pollution contaminants of six major cities in China were selected as a dataset to evaluate the practicality and effectiveness of the developed air quality early-warning system. The superior experimental performance determined by the values of several error indexes illustrated that the proposed early-warning system was of great effectiveness and efficiency. Copyright © 2018 Elsevier B.V. All rights reserved.

Community-based early warning systems for flood risk mitigation in Nepal

NASA Astrophysics Data System (ADS)

Smith, Paul J.; Brown, Sarah; Dugar, Sumit

2017-03-01

This paper focuses on the use of community-based early warning systems for flood resilience in Nepal. The first part of the work outlines the evolution and current status of these community-based systems, highlighting the limited lead times currently available for early warning. The second part of the paper focuses on the development of a robust operational flood forecasting methodology for use by the Nepal Department of Hydrology and Meteorology (DHM) to enhance early warning lead times. The methodology uses data-based physically interpretable time series models and data assimilation to generate probabilistic forecasts, which are presented in a simple visual tool. The approach is designed to work in situations of limited data availability with an emphasis on sustainability and appropriate technology. The successful application of the forecast methodology to the flood-prone Karnali River basin in western Nepal is outlined, increasing lead times from 2-3 to 7-8 h. The challenges faced in communicating probabilistic forecasts to the last mile of the existing community-based early warning systems across Nepal is discussed. The paper concludes with an assessment of the applicability of this approach in basins and countries beyond Karnali and Nepal and an overview of key lessons learnt from this initiative.

Information spread of emergency events: path searching on social networks.

PubMed

Dai, Weihui; Hu, Hongzhi; Wu, Tunan; Dai, Yonghui

2014-01-01

Emergency has attracted global attentions of government and the public, and it will easily trigger a series of serious social problems if it is not supervised effectively in the dissemination process. In the Internet world, people communicate with each other and form various virtual communities based on social networks, which lead to a complex and fast information spread pattern of emergency events. This paper collects Internet data based on data acquisition and topic detection technology, analyzes the process of information spread on social networks, describes the diffusions and impacts of that information from the perspective of random graph, and finally seeks the key paths through an improved IBF algorithm. Application cases have shown that this algorithm can search the shortest spread paths efficiently, which may help us to guide and control the information dissemination of emergency events on early warning.

Feasibility of Using Elastic Wave Velocity Monitoring for Early Warning of Rainfall-Induced Slope Failure

PubMed Central

Chen, Yulong; Irfan, Muhammad; Uchimura, Taro; Zhang, Ke

2018-01-01

Rainfall-induced landslides are one of the most widespread slope instability phenomena posing a serious risk to public safety worldwide so that their temporal prediction is of great interest to establish effective warning systems. The objective of this study is to determine the effectiveness of elastic wave velocities in the surface layer of the slope in monitoring, prediction and early warning of landslide. The small-scale fixed and varied, and large-scale slope model tests were conducted. Analysis of the results has established that the elastic wave velocity continuously decreases in response of moisture content and deformation and there was a distinct surge in the decrease rate of wave velocity when failure was initiated. Based on the preliminary results of this analysis, the method using the change in elastic wave velocity proves superior for landslide early warning and suggests that a warning be issued at switch of wave velocity decrease rate. PMID:29584699

An Envelope Based Feedback Control System for Earthquake Early Warning: Reality Check Algorithm

NASA Astrophysics Data System (ADS)

Heaton, T. H.; Karakus, G.; Beck, J. L.

2016-12-01

Earthquake early warning systems are, in general, designed to be open loop control systems in such a way that the output, i.e., the warning messages, only depend on the input, i.e., recorded ground motions, up to the moment when the message is issued in real-time. We propose an algorithm, which is called Reality Check Algorithm (RCA), which would assess the accuracy of issued warning messages, and then feed the outcome of the assessment back into the system. Then, the system would modify its messages if necessary. That is, we are proposing to convert earthquake early warning systems into feedback control systems by integrating them with RCA. RCA works by continuously monitoring and comparing the observed ground motions' envelopes to the predicted envelopes of Virtual Seismologist (Cua 2005). Accuracy of magnitude and location (both spatial and temporal) estimations of the system are assessed separately by probabilistic classification models, which are trained by a Sparse Bayesian Learning technique called Automatic Relevance Determination prior.

Earthquake Early Warning: A Prospective User's Perspective (Invited)

NASA Astrophysics Data System (ADS)

Nishenko, S. P.; Savage, W. U.; Johnson, T.

2009-12-01

With more than 25 million people at risk from high hazard faults in California alone, Earthquake Early Warning (EEW) presents a promising public safety and emergency response tool. EEW represents the real-time end of an earthquake information spectrum which also includes near real-time notifications of earthquake location, magnitude, and shaking levels; as well as geographic information system (GIS)-based products for compiling and visually displaying processed earthquake data such as ShakeMap and ShakeCast. Improvements to and increased multi-national implementation of EEW have stimulated interest in how such information products could be used in the future. Lifeline organizations, consisting of utilities and transportation systems, can use both onsite and regional EEW information as part of their risk management and public safety programs. Regional EEW information can provide improved situational awareness to system operators before automatic system protection devices activate, and allow trained personnel to take precautionary measures. On-site EEW is used for earthquake-actuated automatic gas shutoff valves, triggered garage door openers at fire stations, system controls, etc. While there is no public policy framework for preemptive, precautionary electricity or gas service shutdowns by utilities in the United States, gas shut-off devices are being required at the building owner level by some local governments. In the transportation sector, high-speed rail systems have already demonstrated the ‘proof of concept’ for EEW in several countries, and more EEW systems are being installed. Recently the Bay Area Rapid Transit District (BART) began collaborating with the California Integrated Seismic Network (CISN) and others to assess the potential benefits of EEW technology to mass transit operations and emergency response in the San Francisco Bay region. A key issue in this assessment is that significant earthquakes are likely to occur close to or within the BART system, limiting the time available for an EEW-based response (i.e., slowing or stopping trains). While EEW systems are currently being tested in California, the societal benefits may be even more pronounced in other earthquake-prone parts of the United States. In the central and eastern United States, strong ground motions are felt over significantly larger areas than in California, enabling both a larger area and longer lead times for warnings ahead of the arrival of strong shaking. Because these regions are less resistant to earthquake shaking, such warnings may be even more important for safety and emergency response. However, in many areas a significant increase in the instrumentation density would be required for EEW to become a reality. Although the details of EEW systems are specific to earthquakes, the operation of sensor networks, real-time data analysis, and rapid notification to lifelines is an emerging technology that can be used for real-time detection and early warning of other types of natural and human-caused disasters and emergencies.

Deep Recurrent Neural Networks for seizure detection and early seizure detection systems

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

Talathi, S. S.

Epilepsy is common neurological diseases, affecting about 0.6-0.8 % of world population. Epileptic patients suffer from chronic unprovoked seizures, which can result in broad spectrum of debilitating medical and social consequences. Since seizures, in general, occur infrequently and are unpredictable, automated seizure detection systems are recommended to screen for seizures during long-term electroencephalogram (EEG) recordings. In addition, systems for early seizure detection can lead to the development of new types of intervention systems that are designed to control or shorten the duration of seizure events. In this article, we investigate the utility of recurrent neural networks (RNNs) in designing seizuremore » detection and early seizure detection systems. We propose a deep learning framework via the use of Gated Recurrent Unit (GRU) RNNs for seizure detection. We use publicly available data in order to evaluate our method and demonstrate very promising evaluation results with overall accuracy close to 100 %. We also systematically investigate the application of our method for early seizure warning systems. Our method can detect about 98% of seizure events within the first 5 seconds of the overall epileptic seizure duration.« less

Cross-border Portfolio Investment Networks and Indicators for Financial Crises

PubMed Central

Joseph, Andreas C.; Joseph, Stephan E.; Chen, Guanrong

2014-01-01

Cross-border equity and long-term debt securities portfolio investment networks are analysed from 2002 to 2012, covering the 2008 global financial crisis. They serve as network-proxies for measuring the robustness of the global financial system and the interdependence of financial markets, respectively. Two early-warning indicators for financial crises are identified: First, the algebraic connectivity of the equity securities network, as a measure for structural robustness, drops close to zero already in 2005, while there is an over-representation of high-degree off-shore financial centres among the countries most-related to this observation, suggesting an investigation of such nodes with respect to the structural stability of the global financial system. Second, using a phenomenological model, the edge density of the debt securities network is found to describe, and even forecast, the proliferation of several over-the-counter-traded financial derivatives, most prominently credit default swaps, enabling one to detect potentially dangerous levels of market interdependence and systemic risk. PMID:24510060

Cross-border Portfolio Investment Networks and Indicators for Financial Crises

NASA Astrophysics Data System (ADS)

Joseph, Andreas C.; Joseph, Stephan E.; Chen, Guanrong

2014-02-01

Cross-border equity and long-term debt securities portfolio investment networks are analysed from 2002 to 2012, covering the 2008 global financial crisis. They serve as network-proxies for measuring the robustness of the global financial system and the interdependence of financial markets, respectively. Two early-warning indicators for financial crises are identified: First, the algebraic connectivity of the equity securities network, as a measure for structural robustness, drops close to zero already in 2005, while there is an over-representation of high-degree off-shore financial centres among the countries most-related to this observation, suggesting an investigation of such nodes with respect to the structural stability of the global financial system. Second, using a phenomenological model, the edge density of the debt securities network is found to describe, and even forecast, the proliferation of several over-the-counter-traded financial derivatives, most prominently credit default swaps, enabling one to detect potentially dangerous levels of market interdependence and systemic risk.

Cross-border portfolio investment networks and indicators for financial crises.

PubMed

Joseph, Andreas C; Joseph, Stephan E; Chen, Guanrong

2014-02-10

Cross-border equity and long-term debt securities portfolio investment networks are analysed from 2002 to 2012, covering the 2008 global financial crisis. They serve as network-proxies for measuring the robustness of the global financial system and the interdependence of financial markets, respectively. Two early-warning indicators for financial crises are identified: First, the algebraic connectivity of the equity securities network, as a measure for structural robustness, drops close to zero already in 2005, while there is an over-representation of high-degree off-shore financial centres among the countries most-related to this observation, suggesting an investigation of such nodes with respect to the structural stability of the global financial system. Second, using a phenomenological model, the edge density of the debt securities network is found to describe, and even forecast, the proliferation of several over-the-counter-traded financial derivatives, most prominently credit default swaps, enabling one to detect potentially dangerous levels of market interdependence and systemic risk.

Development of a Global Evaporative Stress Index Based on Thermal and Microwave LST towards Improved Monitoring of Agricultural Drought

NASA Astrophysics Data System (ADS)

Hain, C.; Anderson, M. C.; Otkin, J.; Holmes, T. R.; Gao, F.

2017-12-01

This presentation will describe the development of a global agricultural monitoring tool, with a focus on providing early warning of developing vegetation stress for agricultural decision-makers and stakeholders at relatively high spatial resolution (5-km). The tool is based on remotely sensed estimates of evapotranspiration, retrieved via energy balance principals using observations of land surface temperature. The Evaporative Stress Index (ESI) represents anomalies in the ratio of actual-to-potential ET generated with the ALEXI surface energy balance model. The LST inputs to ESI have been shown to provide early warning information about the development of vegetation stress with stress-elevated canopy temperatures observed well before a decrease in greenness is detected in remotely sensed vegetation indices. As a diagnostic indicator of actual ET, the ESI requires no information regarding antecedent precipitation or soil moisture storage capacity - the current available moisture to vegetation is deduced directly from the remotely sensed LST signal. This signal also inherently accounts for both precipitation and non-precipitation related inputs/sinks to the plant-available soil moisture pool (e.g., irrigation) which can modify crop response to rainfall anomalies. Independence from precipitation data is a benefit for global agricultural monitoring applications due to sparseness in existing ground-based precipitation networks, and time delays in public reporting. Several enhancements to the current ESI framework will be addressed as requested from project stakeholders: (a) integration of "all-sky" MW Ka-band LST retrievals to augment "clear-sky" thermal-only ESI in persistently cloudy regions; (b) operational production of ESI Rapid Change Indices which provide important early warning information related to onset of actual vegetation stress; and (c) assessment of ESI as a predictor of global yield anomalies; initial studies have shown the ability of intra-seasonal ESI to provide an early indication of at-harvest agricultural yield anomalies.

Volvo and Infiniti drivers' experiences with select crash avoidance technologies.

PubMed

Braitman, Keli A; McCartt, Anne T; Zuby, David S; Singer, Jeremiah

2010-06-01

Vehicle-based crash avoidance systems can potentially reduce crashes, but success depends on driver acceptance and understanding. This study gauged driver use, experience, and acceptance among early adopters of select technologies. Telephone interviews were conducted in early 2009 with 380 owners of Volvo vehicles equipped with forward collision warning with autobrake, lane departure warning, side-view assist, and/or active bi-xenon headlights and 485 owners of Infiniti vehicles with lane departure warning/prevention. Most owners kept systems turned on most of the time, especially forward collision warning with autobrake and side-view assist. The exception was lane departure prevention; many owners were unaware they had it, and the system must be activated each time the vehicle is started. Most owners reported being safer with the technologies and would want them again on their next vehicles. Perceived false or unnecessary warnings were fairly common, particularly with side-view assist. Some systems were annoying, especially lane departure warning. Many owners reported safer driving behaviors such as greater use of turn signals (lane departure warning), increased following distance (forward collision warning), and checking side mirrors more frequently (side-view assist), but some reported driving faster at night (active headlights). Despite some unnecessary or annoying warnings, most Volvo and Infiniti owners use crash avoidance systems most of the time. Among early adopters, the first requirement of effective warning systems (that owners use the technology) seems largely met. Systems requiring activation by drivers for each trip are used less often. Owner experience with the latest technologies from other automobile manufacturers should be studied, as well as for vehicles on which technologies are standard (versus optional) equipment. The effectiveness of technologies in preventing and mitigating crashes and injuries, and user acceptance of interfaces, should be examined as more vehicles with advanced technologies penetrate the fleet.

[Reliability and validity of warning signs checklist for screening psychological, behavioral and developmental problems of children].

PubMed

Huang, X N; Zhang, Y; Feng, W W; Wang, H S; Cao, B; Zhang, B; Yang, Y F; Wang, H M; Zheng, Y; Jin, X M; Jia, M X; Zou, X B; Zhao, C X; Robert, J; Jing, Jin

2017-06-02

Objective: To evaluate the reliability and validity of warning signs checklist developed by the National Health and Family Planning Commission of the People's Republic of China (NHFPC), so as to determine the screening effectiveness of warning signs on developmental problems of early childhood. Method: Stratified random sampling method was used to assess the reliability and validity of checklist of warning sign and 2 110 children 0 to 6 years of age(1 513 low-risk subjects and 597 high-risk subjects) were recruited from 11 provinces of China. The reliability evaluation for the warning signs included the test-retest reliability and interrater reliability. With the use of Age and Stage Questionnaire (ASQ) and Gesell Development Diagnosis Scale (GESELL) as the criterion scales, criterion validity was assessed by determining the correlation and consistency between the screening results of warning signs and the criterion scales. Result: In terms of the warning signs, the screening positive rates at different ages ranged from 10.8%(21/141) to 26.2%(51/137). The median (interquartile) testing time for each subject was 1(0.6) minute. Both the test-retest reliability and interrater reliability of warning signs reached 0.7 or above, indicating that the stability was good. In terms of validity assessment, there was remarkable consistency between ASQ and warning signs, with the Kappa value of 0.63. With the use of GESELL as criterion, it was determined that the sensitivity of warning signs in children with suspected developmental delay was 82.2%, and the specificity was 77.7%. The overall Youden index was 0.6. Conclusion: The reliability and validity of warning signs checklist for screening early childhood developmental problems have met the basic requirements of psychological screening scales, with the characteristics of short testing time and easy operation. Thus, this warning signs checklist can be used for screening psychological and behavioral problems of early childhood, especially in community settings.

Optical Embedded Dust Sensor for Engine Protection and Early Warning on M1 Abrams/Ground Combat Vehicles

DTIC Science & Technology

2012-04-11

warning of seal leakage or deterioration of air filters, thereby reducing engine damage and improving vehicle operational readiness. To be effective , the...for a comprehensive early warning and health management solution. To address the need for an effective dust detector for the AGT1500 engine and M1...an optical dust sensor for real-time continuous monitoring, and its effectiveness in quantitatively measuring dust penetration in the AGT1500 engine

[System construction of early warning for ecological security at cultural and natural heritage mixed sites and its application: a case study of Wuyishan Scenery District].

PubMed

You, Wei-Bin; He, Dong-Jin; Qin, De-Hua; Ji, Zhi-Rong; Wu, Li-Yun; Yu, Jian-An; Chen, Bing-Rong; Tan, Yong

2014-05-01

This paper proposed a new concept of ecological security for protection by a comprehensive analysis of the contents and standards of world heritage sites. A frame concept model named "Pressure-State-Control" for early warning of ecological security at world heritage mixed sites was constructed and evaluation indicators of this frame were also selected. Wuyishan Scenery District was chosen for a case study, which has been severely disturbed by natural and artificial factors. Based on the frame model of "Pressure-State-Control" and by employing extension analysis, the matter-element model was established to assess the ecological security status of this cultural and natural world heritage mixed site. The results showed that the accuracy of ecological security early warning reached 84%. Early warning rank was I level (no alert status) in 1997 and 2009, but that in 2009 had a higher possibility to convert into II level. Likewise, the early-warning indices of sensitive ranks were different between 1997 and 2009. Population density, population growth rate, area index for tea garden, cultivated land owned per capita, level of drought, and investment for ecological and environmental construction were the main limiting factors to hinder the development of ecological security from 2009 to future. In general, the status of Wuyishan Scenery District ecological security was relatively good and considered as no alert level, while risk conditions also existed in terms of a few early-warning indicators. We still need to pay more attention to serious alert indicators and adopt effective prevention and control measures to maintain a good ecological security status of this heritage site.

Refuting the ticagrelor-aspirin black box warning: and proposing a ticagrelor early-PCI black box warning.

PubMed

DiNicolantonio, James J; Serebruany, Victor L; Tomek, Ales

2013-10-03

Ticagrelor, a novel reversible antiplatelet agent, has a black box warning to avoid maintenance doses of aspirin>100mg. However, a significant ticagrelor-early percutaneous coronary intervention (PCI) interaction exists. To discuss the inappropriateness of the black box warning for aspirin doses>100mg with ticagrelor and the appropriateness (and need) for a black box warning for ticagrelor patients needing early (within 24 hours of randomization) PCI. The FDA Complete Response Review for ticagrelor indicates that aspirin doses ≥ 300 mg/daily was not a significant interaction. In the ticagrelor-aspirin ≥ 300 mg cohort, all-cause mortality (through study end) and cardiovascular (CV) mortality (through study end) were not significantly increased (HR=1.27; 95% CI, 0.84-1.93, p=0.262 and HR=1.39; 95% CI:0.87-2.2, p=0.170), respectively. However, in patients treated with early (within 24 hours) PCI, ticagrelor significantly increased all-cause mortality (30 day: HR=1.89; 95% CI: 1.26-2.81, p=0.002, and through study end, HR=1.41; 95% CI,1.08-1.84, p=0.012) and increased CV mortality (30 day: HR=1.31; 95% CI: 0.97-1.77, p=0.075, and through study end, HR=1.35; 95% CI, 0.995-1.82, p=0.054) compared to clopidogrel. Early-PCI was more prevalent in the US versus outside-US regions (61% versus 49%). The black box warning for the use of maintenance aspirin doses over 100mg/daily with ticagrelor is inappropriate and ignores the more important, credible, and highly significant ticagrelor-early PCI adverse interaction in PLATO. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Small-scale (flash) flood early warning in the light of operational requirements: opportunities and limits with regard to user demands, driving data, and hydrologic modeling techniques

NASA Astrophysics Data System (ADS)

Philipp, Andy; Kerl, Florian; Büttner, Uwe; Metzkes, Christine; Singer, Thomas; Wagner, Michael; Schütze, Niels

2016-05-01

In recent years, the Free State of Saxony (Eastern Germany) was repeatedly hit by both extensive riverine flooding, as well as flash flood events, emerging foremost from convective heavy rainfall. Especially after a couple of small-scale, yet disastrous events in 2010, preconditions, drivers, and methods for deriving flash flood related early warning products are investigated. This is to clarify the feasibility and the limits of envisaged early warning procedures for small catchments, hit by flashy heavy rain events. Early warning about potentially flash flood prone situations (i.e., with a suitable lead time with regard to required reaction-time needs of the stakeholders involved in flood risk management) needs to take into account not only hydrological, but also meteorological, as well as communication issues. Therefore, we propose a threefold methodology to identify potential benefits and limitations in a real-world warning/reaction context. First, the user demands (with respect to desired/required warning products, preparation times, etc.) are investigated. Second, focusing on small catchments of some hundred square kilometers, two quantitative precipitation forecasts are verified. Third, considering the user needs, as well as the input parameter uncertainty (i.e., foremost emerging from an uncertain QPF), a feasible, yet robust hydrological modeling approach is proposed on the basis of pilot studies, employing deterministic, data-driven, and simple scoring methods.

The reconnaissance and early-warning optical system design for dual field of space-based "solar blind ultraviolet"

NASA Astrophysics Data System (ADS)

Wang, Wen-cong; Jin, Dong-dong; Shao, Fei; Hu, Hui-jun; Shi, Yu-feng; Song, Juan; Zhang, Yu-tu; Yong, Liu

2016-07-01

With the development of modern technology, especially the development of information technology at high speed, the ultraviolet early warning system plays an increasingly important role. In the modern warfare, how to detect the threats earlier, prevent and reduce the attack of precision-guided missile has become a new challenge. Because the ultraviolet warning technology has high environmental adaptability, the low false alarm rate, small volume and other advantages, in the military field applications it has been developed rapidly. According to current application demands for solar blind ultraviolet detection and warning, this paper proposes a reconnaissance and early-warning optical system, which covers solar blind ultraviolet (250nm-280nm) and dual field. This structure takes advantage of a narrow field of view and long focal length optical system to achieve the target object detection, uses wide-field and short focal length optical system to achieve early warning of the target object. It makes use of an ultraviolet beam-splitter to achieve the separation of two optical systems. According to the detector and the corresponding application needs of two visual field of the optical system, the calculation and optical system design were completed. After the design, the MTF of the two optical system is more than 0.8@39lp/mm. A single pixel energy concentration is greater than 80%.

Hydrological information system based on on-line monitoring--from strategy to implementation in the Brantas River Basin, East Java, Indonesia.

PubMed

Marini, G W; Wellguni, H

2003-01-01

The worsening environmental situation of the Brantas River, East Java, is addressed by a comprehensive basin management strategy which relies on accurate water quantity and quality data retrieved from a newly installed online monitoring network. Integrated into a Hydrological Information System, the continuously measured indicative parameters allow early warning, control and polluter identification. Additionally, long-term analyses have been initiated for improving modelling applications like flood forecasting, water resource management and pollutant propagation. Preliminary results illustrate the efficiency of the installed system.

Design and Implementation of a Wireless Sensor Network-Based Remote Water-Level Monitoring System

PubMed Central

Li, Xiuhong; Cheng, Xiao; Gong, Peng; Yan, Ke

2011-01-01

The proposed remote water-level monitoring system (RWMS) consists of a field sensor module, a base station module, adata center module and aWEB releasing module. It has advantages in real time and synchronized remote control, expandability, and anti-jamming capabilities. The RWMS can realize real-time remote monitoring, providing early warning of events and protection of the safety of monitoring personnel under certain dangerous circumstances. This system has been successfully applied in Poyanghu Lake. The cost of the whole system is approximately 1,500 yuan (RMB). PMID:22319377

A climate trend analysis of Uganda

USGS Publications Warehouse

Funk, Christopher C.; Rowland, Jim; Eilerts, Gary; White, Libby

2012-01-01

This brief report, drawing from a multi-year effort by the U.S. Agency for International Development (USAID) Famine Early Warning Systems Network (FEWS NET), identifies observed changes in rainfall and temperature in Uganda, based on an analysis of a quality-controlled, long time series of station observations throughout Uganda. Extending recent trends forward, it also provides a current and near-future context for understanding the actual nature of climate change impacts in the country, and a basis for identifying climate adaptations that may protect and improve the country's food security.

Design and implementation of a wireless sensor network-based remote water-level monitoring system.

PubMed

Li, Xiuhong; Cheng, Xiao; Gong, Peng; Yan, Ke

2011-01-01

The proposed remote water-level monitoring system (RWMS) consists of a field sensor module, a base station module, a data center module and a WEB releasing module. It has advantages in real time and synchronized remote control, expandability, and anti-jamming capabilities. The RWMS can realize real-time remote monitoring, providing early warning of events and protection of the safety of monitoring personnel under certain dangerous circumstances. This system has been successfully applied in Poyanghu Lake. The cost of the whole system is approximately 1,500 yuan (RMB).

7 Warning Signs of Alzheimer's | Alzheimer's disease | NIH MedlinePlus the Magazine

MedlinePlus

... please turn Javascript on. Feature: Alzheimer's Disease 7 Warning Signs of Alzheimer's Past Issues / Fall 2010 Table ... is to alert the public to the early warning signs of Alzheimer's disease. If someone has several ...

Tourism hazard potentials in Mount Merapi: how to deal with the risk

NASA Astrophysics Data System (ADS)

Muthiah, J.; Muntasib, E. K. S. H.; Meilani, R.

2018-05-01

Mount Merapi as one of the most popular natural tourism destination in Indonesia, indicated as disaster prone area. Hazard management is required to ensure visitors safety. Hazard identification and mapping are prerequisite in developing proper hazard management recommendation. This study aimed to map hazard potentials’ geographical positions obtained with geographical positioning system and to identify the hazard management being implemented. Data collection was carried out in Mei – June 2017 through observation and interview. Hiking trail and Lava tour area was selected as the study site, since the sites are the main areas for tourism activities in Mount Merapi. The type of hazards found in the area included lava, tephra, eruption cloud, ash, earthquake, land slide, extreme weather, slope and loose rock. Early warning system had been developed in this area, however the mechanism to regulate tourism activities still had to be improved. Local tourism entrepreneurs should be involved in the network of early warning system stakeholders to ensure tourist safety, and their capacity should be improved in order to be able to perform the measures needed for handling accident and disaster occurrences. Interpretive media explaining hazard potentials may be used to improve visitors’ awareness and ability to cope with the risk.

Review of FEWS NET Biophysical Monitoring Requirements

NASA Technical Reports Server (NTRS)

Ross, K. W.; Brown, Molly E.; Verdin, J.; Underwood, L. W.

2009-01-01

The Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to famine and food insecurity. FEWS NET transforms satellite remote sensing data into rainfall and vegetation information that can be used by these decision makers. The National Aeronautics and Space Administration has recently funded activities to enhance remote sensing inputs to FEWS NET. To elicit Earth observation requirements, a professional review questionnaire was disseminated to FEWS NET expert end-users: it focused upon operational requirements to determine additional useful remote sensing data and; subsequently, beneficial FEWS NET biophysical supplementary inputs. The review was completed by over 40 experts from around the world, enabling a robust set of professional perspectives to be gathered and analyzed rapidly. Reviewers were asked to evaluate the relative importance of environmental variables and spatio-temporal requirements for Earth science data products, in particular for rainfall and vegetation products. The results showed that spatio-temporal resolution requirements are complex and need to vary according to place, time, and hazard: that high resolution remote sensing products continue to be in demand, and that rainfall and vegetation products were valued as data that provide actionable food security information.

Structural stability of interaction networks against negative external fields

NASA Astrophysics Data System (ADS)

Yoon, S.; Goltsev, A. V.; Mendes, J. F. F.

2018-04-01

We explore structural stability of weighted and unweighted networks of positively interacting agents against a negative external field. We study how the agents support the activity of each other to confront the negative field, which suppresses the activity of agents and can lead to collapse of the whole network. The competition between the interactions and the field shape the structure of stable states of the system. In unweighted networks (uniform interactions) the stable states have the structure of k -cores of the interaction network. The interplay between the topology and the distribution of weights (heterogeneous interactions) impacts strongly the structural stability against a negative field, especially in the case of fat-tailed distributions of weights. We show that apart from critical slowing down there is also a critical change in the system structure that precedes the network collapse. The change can serve as an early warning of the critical transition. To characterize changes of network structure we develop a method based on statistical analysis of the k -core organization and so-called "corona" clusters belonging to the k -cores.

Educator Evaluation and the Use of the Early Warning Indicator System (EWIS). Updated September 9, 2013

ERIC Educational Resources Information Center

Massachusetts Department of Elementary and Secondary Education, 2013

2013-01-01

The Massachusetts Department of Elementary and Secondary Education first released the Early Warning Indicator System (EWIS) data for grades 1-12 in the 2012-13 school year. The Department created the EWIS in direct response to educators' requests for early indicator data across multiple grade levels. The EWIS is a "tool to systematically…

Theory and Application of Early Warning Systems for High School and Beyond

ERIC Educational Resources Information Center

Carl, Bradley; Richardson, Jed T.; Cheng, Emily; Kim, HeeJin; Meyer, Robert H.

2013-01-01

This article describes the development of early warning indicators for high school and beyond in the Milwaukee Public Schools (MPS) by the Value-Added Research Center (VARC) at the University of Wisconsin-Madison, working in conjunction with staff from the Division of Research and Evaluation at MPS. Our work in MPS builds on prior early warning…

ON-LINE TOXICITY MONITORS AND WATERSHED EARLY WARNING SYSTEMS

EPA Science Inventory

A Water Quality Early Warning System using On-line Toxicity Monitors (OTMs) has been deployed in the East Fork of the Little Miami River, Clermont County, OH. Living organisms have long been used to determine the toxicity of environmental samples. With advancements in electronic ...

IG Statement: Arthur A. Elkins, Jr., on OIG report Early Warning Report: Main EPA Headquarters Warehouse in Landover, Maryland, Requires Immediate EPA Attention

EPA Pesticide Factsheets

Statement of Inspector General Arthur A. Elkins, Jr., on the Office of Inspector General (OIG) report Early Warning Report: Main EPA Headquarters Warehouse in Landover, Maryland, Requires Immediate EPA Attention.

Including trait-based early warning signals helps predict population collapse

PubMed Central

Clements, Christopher F.; Ozgul, Arpat

2016-01-01

Foreseeing population collapse is an on-going target in ecology, and this has led to the development of early warning signals based on expected changes in leading indicators before a bifurcation. Such signals have been sought for in abundance time-series data on a population of interest, with varying degrees of success. Here we move beyond these established methods by including parallel time-series data of abundance and fitness-related trait dynamics. Using data from a microcosm experiment, we show that including information on the dynamics of phenotypic traits such as body size into composite early warning indices can produce more accurate inferences of whether a population is approaching a critical transition than using abundance time-series alone. By including fitness-related trait information alongside traditional abundance-based early warning signals in a single metric of risk, our generalizable approach provides a powerful new way to assess what populations may be on the verge of collapse. PMID:27009968

A vantage from space can detect earlier drought onset: an approach using relative humidity.

PubMed

Farahmand, Alireza; AghaKouchak, Amir; Teixeira, Joao

2015-02-25

Each year, droughts cause significant economic and agricultural losses across the world. The early warning and onset detection of drought is of particular importance for effective agriculture and water resource management. Previous studies show that the Standard Precipitation Index (SPI), a measure of precipitation deficit, detects drought onset earlier than other indicators. Here we show that satellite-based near surface air relative humidity data can further improve drought onset detection and early warning. This paper introduces the Standardized Relative Humidity Index (SRHI) based on the NASA Atmospheric Infrared Sounder (AIRS) observations. The results indicate that the SRHI typically detects the drought onset earlier than the SPI. While the AIRS mission was not originally designed for drought monitoring, we show that its relative humidity data offers a new and unique avenue for drought monitoring and early warning. We conclude that the early warning aspects of SRHI may have merit for integration into current drought monitoring systems.

A Vantage from Space Can Detect Earlier Drought Onset: An Approach Using Relative Humidity

PubMed Central

Farahmand, Alireza; AghaKouchak, Amir; Teixeira, Joao

2015-01-01

Each year, droughts cause significant economic and agricultural losses across the world. The early warning and onset detection of drought is of particular importance for effective agriculture and water resource management. Previous studies show that the Standard Precipitation Index (SPI), a measure of precipitation deficit, detects drought onset earlier than other indicators. Here we show that satellite-based near surface air relative humidity data can further improve drought onset detection and early warning. This paper introduces the Standardized Relative Humidity Index (SRHI) based on the NASA Atmospheric Infrared Sounder (AIRS) observations. The results indicate that the SRHI typically detects the drought onset earlier than the SPI. While the AIRS mission was not originally designed for drought monitoring, we show that its relative humidity data offers a new and unique avenue for drought monitoring and early warning. We conclude that the early warning aspects of SRHI may have merit for integration into current drought monitoring systems. PMID:25711500

Early warning indicators for monitoring the process failure of anaerobic digestion system of food waste.

PubMed

Li, Lei; He, Qingming; Wei, Yunmei; He, Qin; Peng, Xuya

2014-11-01

To determine reliable state parameters which could be used as early warning indicators of process failure due to the acidification of anaerobic digestion of food waste, three mesophilic anaerobic digesters of food waste with different operation conditions were investigated. Such parameters as gas production, methane content, pH, concentrations of volatile fatty acid (VFA), alkalinity and their combined indicators were evaluated. Results revealed that operation conditions significantly affect the responses of parameters and thus the optimal early warning indicators of each reactor differ from each other. None of the single indicators was universally valid for all the systems. The universally valid indicators should combine several parameters to supply complementary information. A combination of total VFA, the ratio of VFA to total alkalinity (VFA/TA) and the ratio of bicarbonate alkalinity to total alkalinity (BA/TA) can reflect the metabolism of the digesting system and realize rapid and effective early warning. Copyright © 2014 Elsevier Ltd. All rights reserved.

Early warnings of the potential for malaria transmission in Rural Africa using the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS)

NASA Astrophysics Data System (ADS)

Yamana, T. K.; Eltahir, E. A.

2010-12-01

Early warnings of malaria transmission allow health officials to better prepare for future epidemics. Monitoring rainfall is recognized as an important part of malaria early warning systems, as outlined by the Roll Back Malaria Initiative. The Hydrology, Entomology and Malaria Simulator (HYDREMATS) is a mechanistic model that relates rainfall to malaria transmission, and could be used to provide early warnings of malaria epidemics. HYDREMATS is used to make predictions of mosquito populations and vectorial capacity for 2005, 2006, and 2007 in Banizoumbou village in western Niger. HYDREMATS is forced by observed rainfall, followed by a rainfall prediction based on the seasonal mean rainfall for a period two or four weeks into the future. Predictions made using this method provided reasonable estimates of mosquito populations and vectorial capacity, two to four weeks in advance. The predictions were significantly improved compared to those made when HYDREMATS was forced with seasonal mean rainfall alone.

a Process-Based Drought Early Warning Indicator for Supporting State Drought Mitigation Decision

NASA Astrophysics Data System (ADS)

Fu, R.; Fernando, D. N.; Pu, B.

2014-12-01

Drought prone states such as Texas requires creditable and actionable drought early warning ranging from seasonal to multi-decadal scales. Such information cannot be simply extracted from the available climate prediction and projections because of their large uncertainties at regional scales and unclear connections to the needs of the decision makers. In particular, current dynamic seasonal predictions and climate projections, such as those produced by the NOAA national multi-models ensemble experiment (NMME) and the IPCC AR5 (CMIP5) models, are much more reliable for winter and spring than for the summer season for the US Southern Plains. They also show little connection between the droughts in winter/spring and those in summer, in contrast to the observed dry memory from spring to summer over that region. To mitigate the weakness of dynamic prediction/projections, we have identified three key processes behind the spring-to-summer dry memory through observational studies. Based on these key processes and related fields, we have developed a multivariate principle component statistical model to provide a probabilistic summer drought early warning indicator, using the observed or predicted climate conditions in winter and spring on seasonal scale and climate projection for the mid-21stcentury. The summer drought early warning indicator is constructed in a similar way to the NOAA probabilistic predictions that are familiar to water resource managers. The indicator skill is assessed using the standard NOAA climate prediction assessment tools, i.e., the two alternative forced choice (2AFC) and the Receiver Operating Characteristic (ROC). Comparison with long-term observations suggest that this summer drought early warning indicator is able to capture nearly all the strong summer droughts and outperform the dynamic prediction in this regard over the US Southern Plains. This early warning indicator has been used by the state water agency in May 2014 in briefing the state drought preparedness council and will be provided to stake holders through the website of the Texas state water planning agency. We will also present the results of our ongoing work on using NASA satellite based soil moisture and vegetation stress measurements to further improve the reliability of the summer drought early warning indicator.

Sepsis in Obstetrics: Clinical Features and Early Warning Tools.

PubMed

Parfitt, Sheryl E; Bogat, Mary L; Hering, Sandra L; Ottley, Charlotte; Roth, Cheryl

Morbidity and mortality associated with sepsis has gained widespread attention on a local, state, and national level, yet, it remains a complicated disorder that can be difficult to identify in a timely manner. Sepsis in obstetric patients further complicates the diagnosis as alterations in physiology related to pregnancy can mask sepsis indicators normally seen in the general population. If early signs of sepsis go unrecognized, septic shock can develop, leading to organ dysfunction and potential death. Maternal early warning tools have been designed to assist clinicians in recognizing early indications of illness. Through use of clinical pathway-specific tools, disease processes may be detected early, subsequently benefitting patients with aggressive treatment management and intervention.This article is the second in a series of three that discuss the importance of sepsis and septic shock in pregnancy. Risk factors, causes of sepsis, signs and symptoms, and maternal early warning tools are discussed.

Research on intelligent scenic security early warning platform based on high resolution image: real scene linkage and real-time LBS

NASA Astrophysics Data System (ADS)

Li, Baishou; Huang, Yu; Lan, Guangquan; Li, Tingting; Lu, Ting; Yao, Mingxing; Luo, Yuandan; Li, Boxiang; Qian, Yongyou; Gao, Yujiu

2015-12-01

This paper design and implement security monitor system within a scenic spot for tourists, the scenic spot staff can be automatic real time for visitors to perception and monitoring, and visitors can also know about themselves location in the scenic, real-time and obtain the 3D imaging conditions of scenic area. Through early warning can realize "parent-child relation", preventing the old man and child lost and wandering. Research results to the further development of virtual reality to provide effective security early warning platform of the theoretical basis and practical reference.

Application of Virtual Rain and Stream Gauge Information Service for Improved Flood Early Warning System in Lower Mekong Countries

NASA Astrophysics Data System (ADS)

Basnayake, S. B.; Jayasinghe, S.; Meechaiya, C.; Markert, K. N.; Lee, H.; Towashiraporn, P.; Anderson, E.; Okeowo, M. A.

2017-12-01

Asia is the most vulnerable region in the world to hydro-meteorological extreme events, exacerbated by climate variability and change. Impacts of floods have been on the rapid increase in the recent decades. Myanmar is one of the most vulnerable countries in the lower Mekong region due to its socioeconomic situation (eg; Nargis in 2008, monsoon floods in 2015, etc). Early warning is an effective way to prepare for hydro-meteorological hazards, to minimize disaster risks; however, early warning systems in Myanmar are seriously hampered by limited observation networks. The Virtual Rain and Stream Gauge Information Service (VRSGIS) has been developed by SERVIR-Mekong program of Asian Disaster Preparedness Center (ADPC) to address these gaps and to provide dense, satellite-based rainfall and water level data, which are calibrated and validated with available in-situ observations. This service would enhance decision making in lower Mekong countries, including Myanmar, to minimize impacts of impending disasters. This service contains rainfall data from GPM IMERG and GSMap, CMORPH, TRMM, and CHIRPS, and water levels for 15 locations using Jason-2/3 altimetry. The virtual daily rainfall data sets are being calibrated with Gamma distribution method and are made publicly accessible through a user-friendly web interface.This paper presents a case study of satellite-derived rainfall data accessed from VRSGIS for hydrological modeling in Myanmar, to estimate inundation areas in Kalay township area of Chindwin River basin during the country's worst flood in 2015. Twelve out of fourteen States of Myanmar were severely affected, 103 people were killed, and one million were displaced due to heavy rains associated with Komen cyclone. The aforementioned rainfall data products are used as inputs for HEC-HMS hydrological runoff model to calculate river flows along Chindwin River, and HEC-RAS hydraulic model is used to estimate inundation areas in downstream including Kalay township area. Model results (inundations) are compared with the estimates of water levels of Jason 2/3 measurements from two locations along the river. The results encourage us to use satellite-derived rainfall data over upstream areas to improve flood modeling, which contributes to improved flood early warning in Myanmar and other lower Mekong countries.

The Nature and Variability of Automated Practice Alerts Derived from Electronic Health Records in a U.S. Nationwide Critical Care Research Network.

PubMed

Benthin, Cody; Pannu, Sonal; Khan, Akram; Gong, Michelle

2016-10-01

The nature, variability, and extent of early warning clinical practice alerts derived from automated query of electronic health records (e-alerts) currently used in acute care settings for clinical care or research is unknown. To describe e-alerts in current use in acute care settings at medical centers participating in a nationwide critical care research network. We surveyed investigators at 38 institutions involved in the National Institutes of Health-funded Clinical Trials Network for the Prevention and Early Treatment of Acute Lung Injury (PETAL) for quantitative and qualitative analysis. Thirty sites completed the survey (79% response rate). All sites used electronic health record systems. Epic Systems was used at 56% of sites; the others used alternate commercially available vendors or homegrown systems. Respondents at 57% of sites represented in this survey used e-alerts. All but 1 of these 17 sites used an e-alert for early detection of sepsis-related syndromes, and 35% used an e-alert for pneumonia. E-alerts were triggered by abnormal laboratory values (37%), vital signs (37%), or radiology reports (15%) and were used about equally for clinical decision support and research. Only 59% of sites with e-alerts have evaluated them either for accuracy or for validity. A majority of the research network sites participating in this survey use e-alerts for early notification of potential threats to hospitalized patients; however, there was significant variability in the nature of e-alerts between institutions. Use of one common electronic health record vendor at more than half of the participating sites suggests that it may be possible to standardize e-alerts across multiple sites in research networks, particularly among sites using the same medical record platform.

Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model

NASA Astrophysics Data System (ADS)

Boulton, Chris A.; Allison, Lesley C.; Lenton, Timothy M.

2014-12-01

The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached.

Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model

PubMed Central

Boulton, Chris A.; Allison, Lesley C.; Lenton, Timothy M.

2014-01-01

The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached. PMID:25482065

Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model.

PubMed

Boulton, Chris A; Allison, Lesley C; Lenton, Timothy M

2014-12-08

The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached.

Implementing an Inpatient Social Early Warning System for Child Maltreatment

ERIC Educational Resources Information Center

Atabaki, Armita; Heddaeus, Daniela; Metzner, Franka; Schulz, Holger; Siefert, Sonke; Pawils, Silke

2013-01-01

Objectives: The current article describes the process evaluation of a social early warning system (SEWS) for the prevention of child maltreatment in the federal state of Hamburg. This prevention initiative targets expectant mothers and their partners including an initial screening of risk factors for child maltreatment, a subsequent structured…

Improving Early Warning Systems with Categorized Course Resource Usage

ERIC Educational Resources Information Center

Waddington, R. Joseph; Nam, SungJin; Lonn, Steven; Teasley, Stephanie D.

2016-01-01

Early Warning Systems (EWSs) aggregate multiple sources of data to provide timely information to stakeholders about students in need of academic support. There is an increasing need to incorporate relevant data about student behaviors into the algorithms underlying EWSs to improve predictors of students' success or failure. Many EWSs currently…

78 FR 68831 - Agency Information Collection Activities; Submission to the Office of Management and Budget for...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-15

... Early Warning and Intervention Monitoring System AGENCY: Institute of Education Sciences/National Center... Intervention Monitoring System. OMB Control Number: 1850-NEW. Type of Review: New collection. Respondents... planning a two-part evaluation of the Early Warning and Intervention Monitoring System (EWIMS), consisting...

78 FR 48863 - Agency Information Collection Activities; Comment Request; Evaluation of the Early Warning and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-12

... DEPARTMENT OF EDUCATION [Docket No.: ED-2013-ICCD-0106] Agency Information Collection Activities; Comment Request; Evaluation of the Early Warning and Intervention Monitoring System AGENCY: Institute of... Intervention Monitoring System. OMB Control Number: 1850-NEW. Type of Review: A new information collection...

Real-time earthquake data feasible

NASA Astrophysics Data System (ADS)

Bush, Susan

Scientists agree that early warning devices and monitoring of both Hurricane Hugo and the Mt. Pinatubo volcanic eruption saved thousands of lives. What would it take to develop this sort of early warning and monitoring system for earthquake activity?Not all that much, claims a panel assigned to study the feasibility, costs, and technology needed to establish a real-time earthquake monitoring (RTEM) system. The panel, drafted by the National Academy of Science's Committee on Seismology, has presented its findings in Real-Time Earthquake Monitoring. The recently released report states that “present technology is entirely capable of recording and processing data so as to provide real-time information, enabling people to mitigate somewhat the earthquake disaster.” RTEM systems would consist of two parts—an early warning system that would give a few seconds warning before severe shaking, and immediate postquake information within minutes of the quake that would give actual measurements of the magnitude. At this time, however, this type of warning system has not been addressed at the national level for the United States and is not included in the National Earthquake Hazard Reduction Program, according to the report.

Feasibility study on earthquake early warning application to schools: the example of the ITIS 'E. Majorana', Somma Vesuviana, Naples (Italy)

NASA Astrophysics Data System (ADS)

Emolo, Antonio; Zollo, Aldo; Picozzi, Matteo; Martino, Claudio; Elia, Luca; Verderame, Gerardo; De Risi, Maria Teresa; Ricci, Paolo; Lombardi, Anna; Bindi, Dino; Parolai, Stefano; Boxberger, Tobias; Miranda, Nicola

2014-05-01

One of the main objective of the WP7 (Strategic Applications and Capacity Building) in the framework of the REAKT-Strategies and tools for Real Time Earthquake RisK ReducTion FP7 European project, is to evaluate the effectiveness of EEW and real-time risk assessment procedures in reducing seismic risk to various industrial partners and end-users. In the context of the REAKT project, the AMRA-RISSCLab group is engaged in a feasibility study on the application of earthquake early-warning procedures in two high schools located in the Irpinia region (South Italy), an area that in the 1980 was struck by a magnitude 6.9 earthquake. In this work we report on the activities carried out during the last 24 Months at the school ITIS 'E. Majorana', located in Somma Vesuviana, a village in the neighbourhood of Naples. In order to perform a continuous seismic monitoring of the site, which includes a rather complex structure building, 5 accelerometric stations have been installed in different part of the school. In particular, a 24-bit ADC (Sigma/Delta) Agecodagis-Kefren data-logger has been installed with a Guralp CMG-5TC accelerometer with a 0.25g full-scale in the school courtyard, while 4 SOSEWIN sensors have been also installed at different locations within the building. Commercial ADSL lines provide transmission of real-time data to the EEW centre. Data streams are now acquired in real-time in the PRESToPlus (regional and on-site, threshold-based early-warning) software platform [1]. The recent December 29, 2013 M 5.1 Monti del Matese Earthquake, gave us the unique opportunity to use real strong motion data to test the performance of threshold-based early warning method at the school. The on-site method [2] aims to define alert levels at the monitored site. In particular, at each station the characteristic P-waves period (τc) and the peak displacement (Pd) are measured on the initial P-wave signal. They are compared with threshold values, previously established through an empirical regression analysis, to produce an alert level at each station that can be correlated with the expected local damage in a robust way. At the same time, by means of the software PRESTo and a newly developed prototype of a low-cost EEW sentinel, these data have been also used to run an EEW drill at a few school classes. Finally, the preliminary results of the vulnerability study carried out at the school will be also shown. Indeed, after some preliminary in-situ surveys, structural and non-structural components, which are involved in the vulnerability analysis, have been identified. Hence, geometrical and mechanical model definition was performed and dynamic properties were carried out through a modal analysis. The evaluation of the seismic capacity has been performed through an incremental nonlinear static analysis approach, thus identifying seismic intensity levels leading to different Damage States in structural and non-structural components. References Satriano, Elia et al. (2010). PRESTo, the earthquake early warning system for Southern Italy: Concepts, capabilities and future perspectives. Soil Dyn Earthq Eng, doi 10.1016/j.soildyn.2010.06.008. Zollo et al. (2010). A threshold-based earthquake early warning using dense accelerometer networks. Geophys. J. Int. 183, 963-974.

Information Spread of Emergency Events: Path Searching on Social Networks

PubMed Central

Hu, Hongzhi; Wu, Tunan

2014-01-01

Emergency has attracted global attentions of government and the public, and it will easily trigger a series of serious social problems if it is not supervised effectively in the dissemination process. In the Internet world, people communicate with each other and form various virtual communities based on social networks, which lead to a complex and fast information spread pattern of emergency events. This paper collects Internet data based on data acquisition and topic detection technology, analyzes the process of information spread on social networks, describes the diffusions and impacts of that information from the perspective of random graph, and finally seeks the key paths through an improved IBF algorithm. Application cases have shown that this algorithm can search the shortest spread paths efficiently, which may help us to guide and control the information dissemination of emergency events on early warning. PMID:24600323

Urban MEMS based seismic network for post-earthquakes rapid disaster assessment

NASA Astrophysics Data System (ADS)

D'Alessandro, A.; Luzio, D.; D'Anna, G.

2014-09-01

In this paper, we introduce a project for the realization of the first European real-time urban seismic network based on Micro Electro-Mechanical Systems (MEMS) technology. MEMS accelerometers are a highly enabling technology, and nowadays, the sensitivity and the dynamic range of these sensors are such as to allow the recording of earthquakes of moderate magnitude even at a distance of several tens of kilometers. Moreover, thanks to their low cost and smaller size, MEMS accelerometers can be easily installed in urban areas in order to achieve an urban seismic network constituted by high density of observation points. The network is being implemented in the Acireale Municipality (Sicily, Italy), an area among those with the highest hazard, vulnerability and exposure to the earthquake of the Italian territory. The main objective of the implemented urban network will be to achieve an effective system for post-earthquake rapid disaster assessment. The earthquake recorded, also that with moderate magnitude will be used for the effective seismic microzonation of the area covered by the network. The implemented system will be also used to realize a site-specific earthquakes early warning system.

Drought monitoring and assessment: Remote sensing and modeling approaches for the Famine Early Warning Systems Network

USGS Publications Warehouse

Senay, Gabriel; Velpuri, Naga Manohar; Bohms, Stefanie; Budde, Michael; Young, Claudia; Rowland, James; Verdin, James

2015-01-01

Drought monitoring is an essential component of drought risk management. It is usually carried out using drought indices/indicators that are continuous functions of rainfall and other hydrometeorological variables. This chapter presents a few examples of how remote sensing and hydrologic modeling techniques are being used to generate a suite of drought monitoring indicators at dekadal (10-day), monthly, seasonal, and annual time scales for several selected regions around the world. Satellite-based rainfall estimates are being used to produce drought indicators such as standardized precipitation index, dryness indicators, and start of season analysis. The Normalized Difference Vegetation Index is being used to monitor vegetation condition. Several satellite data products are combined using agrohydrologic models to produce multiple short- and long-term indicators of droughts. All the data sets are being produced and updated in near-real time to provide information about the onset, progression, extent, and intensity of drought conditions. The data and products produced are available for download from the Famine Early Warning Systems Network (FEWS NET) data portal at http://earlywarning.usgs.gov. The availability of timely information and products support the decision-making processes in drought-related hazard assessment, monitoring, and management with the FEWS NET. The drought-hazard monitoring approach perfected by the U.S. Geological Survey for FEWS NET through the integration of satellite data and hydrologic modeling can form the basis for similar decision support systems. Such systems can operationally produce reliable and useful regional information that is relevant for local, district-level decision making.

Early Warning/Track-and-Trigger Systems to Detect Deterioration and Improve Outcomes in Hospitalized Patients.

PubMed

Shiloh, Ariel L; Lominadze, George; Gong, Michelle N; Savel, Richard H

2016-02-01

As a global effort toward improving patient safety, a specific area of focus has been the early recognition and rapid intervention in deteriorating ward patients. This focus on "failure to rescue" has led to the construction of early warning/track-and-trigger systems. In this review article, we present a description of the data behind the creation and implementation of such systems, including multiple algorithms and strategies for deployment. Additionally, the strengths and weaknesses of the various systems and their evaluation in the literature are emphasized. Despite the limitations of the current literature, the potential benefit of these early warning/track-and-trigger systems to improve patient outcomes remains significant. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Experience from three years of local capacity development for tsunami early warning in Indonesia: challenges, lessons and the way ahead

NASA Astrophysics Data System (ADS)

Spahn, H.; Hoppe, M.; Vidiarina, H. D.; Usdianto, B.

2010-07-01

Five years after the 2004 tsunami, a lot has been achieved to make communities in Indonesia better prepared for tsunamis. This achievement is primarily linked to the development of the Indonesian Tsunami Early Warning System (InaTEWS). However, many challenges remain. This paper describes the experience with local capacity development for tsunami early warning (TEW) in Indonesia, based on the activities of a pilot project. TEW in Indonesia is still new to disaster management institutions and the public, as is the paradigm of Disaster Risk Reduction (DRR). The technology components of InaTEWS will soon be fully operational. The major challenge for the system is the establishment of clear institutional arrangements and capacities at national and local levels that support the development of public and institutional response capability at the local level. Due to a lack of information and national guidance, most local actors have a limited understanding of InaTEWS and DRR, and often show little political will and priority to engage in TEW. The often-limited capacity of local governments is contrasted by strong engagement of civil society organisations that opt for early warning based on natural warning signs rather than technology-based early warning. Bringing together the various actors, developing capacities in a multi-stakeholder cooperation for an effective warning system are key challenges for the end-to-end approach of InaTEWS. The development of local response capability needs to receive the same commitment as the development of the system's technology components. Public understanding of and trust in the system comes with knowledge and awareness on the part of the end users of the system and convincing performance on the part of the public service provider. Both sides need to be strengthened. This requires the integration of TEW into DRR, clear institutional arrangements, national guidance and intensive support for capacity development at local levels as well as dialogue between the various actors.

Forewarning of hypotensive events using a Bayesian artificial neural network in neurocritical care.

PubMed

Donald, Rob; Howells, Tim; Piper, Ian; Enblad, P; Nilsson, P; Chambers, I; Gregson, B; Citerio, G; Kiening, K; Neumann, J; Ragauskas, A; Sahuquillo, J; Sinnott, R; Stell, A

2018-05-24

Traumatically brain injured (TBI) patients are at risk from secondary insults. Arterial hypotension, critically low blood pressure, is one of the most dangerous secondary insults and is related to poor outcome in patients. The overall aim of this study was to get proof of the concept that advanced statistical techniques (machine learning) are methods that are able to provide early warning of impending hypotensive events before they occur during neuro-critical care. A Bayesian artificial neural network (BANN) model predicting episodes of hypotension was developed using data from 104 patients selected from the BrainIT multi-center database. Arterial hypotension events were recorded and defined using the Edinburgh University Secondary Insult Grades (EUSIG) physiological adverse event scoring system. The BANN was trained on a random selection of 50% of the available patients (n = 52) and validated on the remaining cohort. A multi-center prospective pilot study (Phase 1, n = 30) was then conducted with the system running live in the clinical environment, followed by a second validation pilot study (Phase 2, n = 49). From these prospectively collected data, a final evaluation study was done on 69 of these patients with 10 patients excluded from the Phase 2 study because of insufficient or invalid data. Each data collection phase was a prospective non-interventional observational study conducted in a live clinical setting to test the data collection systems and the model performance. No prediction information was available to the clinical teams during a patient's stay in the ICU. The final cohort (n = 69), using a decision threshold of 0.4, and including false positive checks, gave a sensitivity of 39.3% (95% CI 32.9-46.1) and a specificity of 91.5% (95% CI 89.0-93.7). Using a decision threshold of 0.3, and false positive correction, gave a sensitivity of 46.6% (95% CI 40.1-53.2) and specificity of 85.6% (95% CI 82.3-88.8). With a decision threshold of 0.3, > 15 min warning of patient instability can be achieved. We have shown, using advanced machine learning techniques running in a live neuro-critical care environment, that it would be possible to give neurointensive teams early warning of potential hypotensive events before they emerge, allowing closer monitoring and earlier clinical assessment in an attempt to prevent the onset of hypotension. The multi-centre clinical infrastructure developed to support the clinical studies provides a solid base for further collaborative research on data quality, false positive correction and the display of early warning data in a clinical setting.

Early warning of orographically induced floods and landslides in Western Norway

NASA Astrophysics Data System (ADS)

Leine, Ann-Live; Wang, Thea; Boje, Søren

2017-04-01

In Western Norway, landslides and debris flows are commonly initiated by short-term orographic rainfall or intensity peaks during a prolonged rainfall event. In recent years, the flood warning service in Norway has evolved from being solely a flood forecasting service to also integrating landslides into its early warning systems. As both floods and landslides are closely related to the same hydrometeorological processes, particularly in small catchments, there is a natural synergy between monitoring flood and landslide risk. The Norwegian Flood and Landslide Hazard Forecasting and Warning Service issues regional landslide hazard warnings based on hydrological models, threshold values, observations and weather forecasts. Intense rainfall events and/or orographic precipitation that, under certain topographic conditions, significantly increase the risk of debris avalanches and debris floods are lately receiving more research focus from the Norwegian warning service. Orographic precipitation is a common feature in W-Norway, when moist and relatively mild air arrives from the Atlantic. Steep mountain slopes covered by glacial till makes the region prone to landslides, as well as flooding. The operational early warning system in Norway requires constant improvement, especially with the enhanced number of intense rainfall events that occur in a warming climate. Here, we examine different cases of intense rainfall events which have lead to landslides and debris flows, as well as increased runoff in fast responding small catchments. The main objective is to increase the understanding of the hydrometeorological conditions related to these events, in order to make priorities for the future development of the warning service.

Early warning system for aftershocks

USGS Publications Warehouse

Bakun, W.H.; Fischer, F.G.; Jensen, E.G.; VanSchaack, J.

1994-01-01

A prototype early warning system to provide San Francisco and Oakland, California a few tens-of-seconds warning of incoming strong ground shaking from already-occurred M ≧ 3.7 aftershocks of the magnitude 7.1 17 October 1989 Loma Prieta earthquake was operational on 28 October 1989. The prototype system consisted of four components: ground motion sensors in the epicentral area, a central receiver, a radio repeater, and radio receivers. One of the radio receivers was deployed at the California Department of Transportation (CALTRANS) headquarters at the damaged Cypress Street section of the I-880 freeway in Oakland, California on 28 October 1989 and provided about 20 sec of warning before shaking from the M 4.5 Loma Prieta aftershock that occurred on 2 November 1989 at 0550 UTC. In its first 6 months of operation, the system generated triggers for all 12 M > 3.7 aftershocks for which trigger documentation is preserved, did not trigger on any M ≦ 3.6 aftershocks, and produced one false trigger as a result of a now-corrected single point of failure design flaw. Because the prototype system demonstrated that potentially useful warnings of strong shaking from aftershocks are feasible, the USGS has completed a portable early warning system for aftershocks that can be deployed anywhere.

Research and application of a hybrid model based on dynamic fuzzy synthetic evaluation for establishing air quality forecasting and early warning system: A case study in China.

PubMed

Xu, Yunzhen; Du, Pei; Wang, Jianzhou

2017-04-01

As the atmospheric environment pollution has been becoming more and more serious in China, it is highly desirable to develop a scientific and effective early warning system that plays a great significant role in analyzing and monitoring air quality. However, establishing a robust early warning system for warning the public in advance and ameliorating air quality is not only an extremely challenging task but also a public concerned problem for human health. Most previous studies are focused on improving the prediction accuracy, which usually ignore the significance of uncertainty information and comprehensive evaluation concerning air pollutants. Therefore, in this paper a novel robust early warning system was successfully developed, which consists of three modules: evaluation module, forecasting module and characteristics estimating module. In this system, a new dynamic fuzzy synthetic evaluation is proposed and applied to determine air quality levels and primary pollutants, which can be regarded as the research objectives; Moreover, to further mine and analyze the characteristics of air pollutants, four different distribution functions and interval forecasting method are also employed that can not only provide predictive range, confidence level and the other uncertain information of the pollutants future values, but also assist decision-makers in reducing and controlling the emissions of atmospheric pollutants. Case studies utilizing hourly PM 2.5 , PM 10 and SO 2 data collected from Tianjin and Shanghai in China are applied as illustrative examples to estimate the effectiveness and efficiency of the proposed system. Experimental results obviously indicated that the developed novel early warning system is much suitable for analyzing and monitoring air pollution, which can also add a novel viable option for decision-makers. Copyright © 2017 Elsevier Ltd. All rights reserved.

SeismoGeodesy: Combination of High Rate, Real-time GNSS and Accelerometer Observations and Rapid Seismic Event Notification for Earth Quake Early Warning and Volcano Monitoring

NASA Astrophysics Data System (ADS)

Jackson, Michael; Zimakov, Leonid; Moessmer, Matthias

2015-04-01

Scientific GNSS networks are moving towards a model of real-time data acquisition, epoch-by-epoch storage integrity, and on-board real-time position and displacement calculations. This new paradigm allows the integration of real-time, high-rate GNSS displacement information with acceleration and velocity data to create very high-rate displacement records. The mating of these two instruments allows the creation of a new, very high-rate (200 Hz) displacement observable that has the full-scale displacement characteristics of GNSS and high-precision dynamic motions of seismic technologies. It is envisioned that these new observables can be used for earthquake early warning studies, volcano monitoring, and critical infrastructure monitoring applications. Our presentation will focus on the characteristics of GNSS, seismic, and strong motion sensors in high dynamic environments, including historic earthquakes replicated on a shake table over a range of displacements and frequencies. We will explore the optimum integration of these sensors from a filtering perspective including simple harmonic impulses over varying frequencies and amplitudes and under the dynamic conditions of various earthquake scenarios. We will also explore the tradeoffs between various GNSS processing schemes including real-time precise point positioning (PPP) and real-time kinematic (RTK) as applied to seismogeodesy. In addition we will discuss implementation of a Rapid Seismic Event Notification System that provides quick delivery of digital data from seismic stations to the acquisition and processing center and a full data integrity model for real-time earthquake notification that provides warning prior to significant ground shaking.

Study of flash floods over some parts of Brazil using precipitation index

NASA Astrophysics Data System (ADS)

Souza, D.; de Souza, R. L. M.; Araujo, R.

2016-12-01

In Brazil, the main phenomena related to natural disasters are derived from the Earth's external dynamics such as floods and flash floods, landslides and storms, where the flash flood phenomenon causes the second highest number of victims, totaling more than 32% of deaths. Floods and flash floods are natural events often triggered by storms or long period of rains, usually associated with rising volume of rainfall on the watershed, leading the river to exceed its maximum. Whereas the occurrence of natural disasters in Brazil is increasing in recent years, the use of more accurate tools to aid in the monitoring of extreme hydrological events it becomes necessary, aiming to decrease the number of human and material losses. In this context, this paper aims to implement an early warning and monitoring system related to extreme precipitation values and hydrological processes. So, initially was studied flood events in the states of São Paulo and Paraná, aimed de determination of the characteristics of rainfall and atmosphere. Later it was used an indicator of precipitation based on the climatology, which indicates warning points on the drainage network related to extreme precipitation, which are obtained by remote sensing sources, for example, radar and satellite, and numerical weather prediction data of short and very short term. The results indicated that most of the flood events over the study area was related to rainfall of deep convection. The use of precipitation indicators also helped the monitoring and the early warning, showing this to be an excellent tool for applications related to flash floods.

Global early warning systems for natural hazards: systematic and people-centred.

PubMed

Basher, Reid

2006-08-15

To be effective, early warning systems for natural hazards need to have not only a sound scientific and technical basis, but also a strong focus on the people exposed to risk, and with a systems approach that incorporates all of the relevant factors in that risk, whether arising from the natural hazards or social vulnerabilities, and from short-term or long-term processes. Disasters are increasing in number and severity and international institutional frameworks to reduce disasters are being strengthened under United Nations oversight. Since the Indian Ocean tsunami of 26 December 2004, there has been a surge of interest in developing early warning systems to cater to the needs of all countries and all hazards.

Surveillance and early warning systems of infectious disease in China: From 2012 to 2014.

PubMed

Zhang, Honglong; Wang, Liping; Lai, Shengjie; Li, Zhongjie; Sun, Qiao; Zhang, Peng

2017-07-01

Appropriate surveillance and early warning of infectious diseases have very useful roles in disease control and prevention. In 2004, China established the National Notifiable Infectious Disease Surveillance System and the Public Health Emergency Event Surveillance System to report disease surveillance and events on the basis of data sources from the National Notifiable Infectious Disease Surveillance System, China Infectious Disease Automated-alert and Response System in this country. This study provided a descriptive summary and a data analysis, from 2012 to 2014, of these 3 key surveillance and early warning systems of infectious disease in China with the intent to provide suggestions for system improvement and perfection. Copyright © 2017 John Wiley & Sons, Ltd.

Military Intervention to Stop Mass Atrocities

DTIC Science & Technology

2017-05-04

the circumstances where the United States should respond militarily. Early warning and prevention strategies are vital since these approaches allow...34genocide." As early as 1933, Lemkin addressed the issue of genocide in a paper he sent to a League of Nations conference in Madrid, Spain. He...2017, https://www.ushmm.org/confront- genocide/speakers-and-events/all-speakers-and-events/ early -warning-and-prevention/the-united-states- measures-to

Monitoring of slope-instabilities and deformations with Micro-Electro-Mechanical-Systems (MEMS) in wireless ad-hoc Sensor Networks

NASA Astrophysics Data System (ADS)

Arnhardt, C.; Fernández-Steeger, T. M.; Azzam, R.

2009-04-01

In most mountainous regions, landslides represent a major threat to human life, properties and infrastructures. Nowadays existing landslide monitoring systems are often characterized by high efforts in terms of purchase, installation, maintenance, manpower and material. In addition (or because of this) only small areas or selective points of the endangered zone can be observed by the system. Therefore the improvement of existing and the development of new monitoring and warning systems are of high relevance. The joint project "Sensor based Landslide Early Warning Systems" (SLEWS) deals with the development of a prototypic Alarm- and Early Warning system (EWS) for different types of landslides using low-cost micro-sensors (MEMS) integrated in a wireless sensor network (WSN). Modern so called Ad-Hoc, Multi-Hop wireless sensor networks (WSN) are characterized by a self organizing and self-healing capacity of the system (autonomous systems). The network consists of numerous individual and own energy-supply operating sensor nodes, that can send data packages from their measuring devices (here: MEMS) over other nodes (Multi-Hop) to a collection point (gateway). The gateway provides the interface to central processing and data retrieval units (PC, Laptop or server) outside the network. In order to detect and monitor the different landslide processes (like fall, topple, spreading or sliding) 3D MEMS capacitive sensors made from single silicon crystals and glass were chosen to measure acceleration, tilting and altitude changes. Based on the so called MEMS (Micro-Electro-Mechanical Systems) technology, the sensors combine very small mechanical and electronic units, sensing elements and transducers on a small microchip. The mass production of such type of sensors allows low cost applications in different areas (like automobile industries, medicine, and automation technology). Apart from the small and so space saving size and the low costs another advantage is the energy efficiency that permits measurements over a long period of time. A special sensor-board that accommodates the measuring sensors and the node of the WSN was developed. The standardized interfaces of the measuring sensors permit an easy interaction with the node and thus enable an uncomplicated data transfer to the gateway. The 3-axis acceleration sensor (measuring range: +/- 2g), the 2-axis inclination sensor (measuring range: +/- 30°) for measuring tilt and the barometric pressure sensor (measuring rang: 30kPa - 120 kPa) for measuring sub-meter height changes (altimeter) are currently integrated into the sensor network and are tested in realistic experiments. In addition sensor nodes with precise potentiometric displacement and linear magnetorestrictive position transducer are used for extension and convergence measurements. According to the accuracy of the first developed test stations, the results of the experiments showed that the selected sensors meet the requirement profile, as the stability is satisfying and the spreading of the data is quite low. Therefore the jet developed sensor boards can be tested in a larger environment of a sensor network. In order to get more information about accuracy in detail, experiments in a new more precise test bed and tests with different sampling rates will follow. Another increasingly important aspect for the future is the fusion of sensor data (i.e. combination and comparison) to identify malfunctions and to reduce false alarm rates, while increasing data quality at the same time. The correlation of different (complementary sensor fusion) but also identical sensor-types (redundant sensor fusion) permits a validation of measuring data. The development of special algorithms allows in a further step to analyze and evaluate the data from all nodes of the network together (sensor node fusion). The sensor fusion contributes to the decision making of alarm and early warning systems and allows a better interpretation of data. The network data are processed outside the network in a service orientated special data infrastructure (SDI) by standardized OGC (open Geospatial Consortium) conformal services and visualized according to the requirements of the end-user. The modular setup of the hardware, combined with standardized interfaces and open services for data processing allows an easy adaption or integration in existing solutions and other networks. The Monitoring system described here is characterized by very flexible structure, cost efficiency and high fail-safe level. The application of WSN in combination with MEMS provides an inexpensive, easy to set up and intelligent monitoring system for spatial data gathering in large areas.

A Multi-User Game-Theoretical Multipath Routing Protocol to Send Video-Warning Messages over Mobile Ad Hoc Networks

PubMed Central

Mezher, Ahmad Mohamad; Igartua, Mónica Aguilar; de la Cruz Llopis, Luis J.; Segarra, Esteve Pallarès; Tripp-Barba, Carolina; Urquiza-Aguiar, Luis; Forné, Jordi; Gargallo, Emilio Sanvicente

2015-01-01

The prevention of accidents is one of the most important goals of ad hoc networks in smart cities. When an accident happens, dynamic sensors (e.g., citizens with smart phones or tablets, smart vehicles and buses, etc.) could shoot a video clip of the accident and send it through the ad hoc network. With a video message, the level of seriousness of the accident could be much better evaluated by the authorities (e.g., health care units, police and ambulance drivers) rather than with just a simple text message. Besides, other citizens would be rapidly aware of the incident. In this way, smart dynamic sensors could participate in reporting a situation in the city using the ad hoc network so it would be possible to have a quick reaction warning citizens and emergency units. The deployment of an efficient routing protocol to manage video-warning messages in mobile Ad hoc Networks (MANETs) has important benefits by allowing a fast warning of the incident, which potentially can save lives. To contribute with this goal, we propose a multipath routing protocol to provide video-warning messages in MANETs using a novel game-theoretical approach. As a base for our work, we start from our previous work, where a 2-players game-theoretical routing protocol was proposed to provide video-streaming services over MANETs. In this article, we further generalize the analysis made for a general number of N players in the MANET. Simulations have been carried out to show the benefits of our proposal, taking into account the mobility of the nodes and the presence of interfering traffic.Finally, we also have tested our approach in a vehicular ad hoc network as an incipient start point to develop a novel proposal specifically designed for VANETs. PMID:25897496

Flood and landslide warning based on rainfall thresholds and soil moisture indexes: the HEWS (Hydrohazards Early Warning System) for Sicily

NASA Astrophysics Data System (ADS)

Brigandì, Giuseppina; Tito Aronica, Giuseppe; Bonaccorso, Brunella; Gueli, Roberto; Basile, Giuseppe

2017-09-01

The main focus of the paper is to present a flood and landslide early warning system, named HEWS (Hydrohazards Early Warning System), specifically developed for the Civil Protection Department of Sicily, based on the combined use of rainfall thresholds, soil moisture modelling and quantitative precipitation forecast (QPF). The warning system is referred to 9 different Alert Zones in which Sicily has been divided into and based on a threshold system of three different increasing critical levels: ordinary, moderate and high. In this system, for early flood warning, a Soil Moisture Accounting (SMA) model provides daily soil moisture conditions, which allow to select a specific set of three rainfall thresholds, one for each critical level considered, to be used for issue the alert bulletin. Wetness indexes, representative of the soil moisture conditions of a catchment, are calculated using a simple, spatially-lumped rainfall-streamflow model, based on the SCS-CN method, and on the unit hydrograph approach, that require daily observed and/or predicted rainfall, and temperature data as input. For the calibration of this model daily continuous time series of rainfall, streamflow and air temperature data are used. An event based lumped rainfall-runoff model has been, instead, used for the derivation of the rainfall thresholds for each catchment in Sicily characterised by an area larger than 50 km2. In particular, a Kinematic Instantaneous Unit Hydrograph based lumped rainfall-runoff model with the SCS-CN routine for net rainfall was developed for this purpose. For rainfall-induced shallow landslide warning, empirical rainfall thresholds provided by Gariano et al. (2015) have been included in the system. They were derived on an empirical basis starting from a catalogue of 265 shallow landslides in Sicily in the period 2002-2012. Finally, Delft-FEWS operational forecasting platform has been applied to link input data, SMA model and rainfall threshold models to produce warning on a daily basis for the entire region.

Credit Default Swaps networks and systemic risk

PubMed Central

Puliga, Michelangelo; Caldarelli, Guido; Battiston, Stefano

2014-01-01

Credit Default Swaps (CDS) spreads should reflect default risk of the underlying corporate debt. Actually, it has been recognized that CDS spread time series did not anticipate but only followed the increasing risk of default before the financial crisis. In principle, the network of correlations among CDS spread time series could at least display some form of structural change to be used as an early warning of systemic risk. Here we study a set of 176 CDS time series of financial institutions from 2002 to 2011. Networks are constructed in various ways, some of which display structural change at the onset of the credit crisis of 2008, but never before. By taking these networks as a proxy of interdependencies among financial institutions, we run stress-test based on Group DebtRank. Systemic risk before 2008 increases only when incorporating a macroeconomic indicator reflecting the potential losses of financial assets associated with house prices in the US. This approach indicates a promising way to detect systemic instabilities. PMID:25366654

Credit Default Swaps networks and systemic risk.

PubMed

Puliga, Michelangelo; Caldarelli, Guido; Battiston, Stefano

2014-11-04

Credit Default Swaps (CDS) spreads should reflect default risk of the underlying corporate debt. Actually, it has been recognized that CDS spread time series did not anticipate but only followed the increasing risk of default before the financial crisis. In principle, the network of correlations among CDS spread time series could at least display some form of structural change to be used as an early warning of systemic risk. Here we study a set of 176 CDS time series of financial institutions from 2002 to 2011. Networks are constructed in various ways, some of which display structural change at the onset of the credit crisis of 2008, but never before. By taking these networks as a proxy of interdependencies among financial institutions, we run stress-test based on Group DebtRank. Systemic risk before 2008 increases only when incorporating a macroeconomic indicator reflecting the potential losses of financial assets associated with house prices in the US. This approach indicates a promising way to detect systemic instabilities.

Preliminary Results form the Japanese Total Lightning Network

NASA Astrophysics Data System (ADS)

Hobara, Y.; Ishii, H.; Kumagai, Y.; Liu, C.; Heckman, S.; Price, C. G.; Williams, E. R.

2015-12-01

We report on the initial observational results from the first Japanese Total Lightning Detection Network (JTLN) in relation to severe weather phenomena. The University of Electro-Communications (UEC) has deployed the Earth Networks (EN) Total Lightning System over Japan to carry out research on the relationship between thunderstorm activity and severe weather phenomena since 2013. In this paper we first demonstrate the current status of our new network followed by the initial scientific results. The lightning jump algorithm was applied to our total lightning data to study the relationship between total lighting activity and hazardous weather events such as gust fronts and tornadoes over land reported by the JMA (Japanese Meteorological Agency) in 2014. As a result, a clear increase in total lighting flash rate as well as lightning jumps are observed prior to most hazardous weather events (~20 min) indicating potential usefulness for early warning in Japan. Furthermore we are going to demonstrate the relationship of total lightning activities with meteorological radar data focusing particularly on Japanese Tornadic storms.

Credit Default Swaps networks and systemic risk

NASA Astrophysics Data System (ADS)

Puliga, Michelangelo; Caldarelli, Guido; Battiston, Stefano

2014-11-01

Credit Default Swaps (CDS) spreads should reflect default risk of the underlying corporate debt. Actually, it has been recognized that CDS spread time series did not anticipate but only followed the increasing risk of default before the financial crisis. In principle, the network of correlations among CDS spread time series could at least display some form of structural change to be used as an early warning of systemic risk. Here we study a set of 176 CDS time series of financial institutions from 2002 to 2011. Networks are constructed in various ways, some of which display structural change at the onset of the credit crisis of 2008, but never before. By taking these networks as a proxy of interdependencies among financial institutions, we run stress-test based on Group DebtRank. Systemic risk before 2008 increases only when incorporating a macroeconomic indicator reflecting the potential losses of financial assets associated with house prices in the US. This approach indicates a promising way to detect systemic instabilities.

Geoethical considerations in early warning of flooding and landslides: Case study from Norway

NASA Astrophysics Data System (ADS)

Devoli, Graziella; Kleivane Krøgli, Ingeborg; Dahl, Mads Peter; Colleuille, Hervé; Nykjær Boje, Søren; Sund, Monica

2015-04-01

The Norwegian Water Resources and Energy Directorate (NVE) runs the national early warning systems (EWS) for flooding and shallow landslides in Norway. The two EWSs have been operational since the late 1980s and 2013 respectively, and are based on weather forecasts, various hydro-meteorological prognosis and expert evaluation. Daily warning levels and related information to the public is prepared and presented through custom build internet platforms. In natural hazards sciences, the risk of a specific threat is defined as the product of hazard and consequence. In this context an EWS is intended to work as a mitigation measure in lowering the consequence and thus the risk of the threat. One of several factors determining the quality of such an EWS, is how warnings are communicated to the public. In contrary to what is common practice in some other countries, experts working with EWS in Norway cannot be held personally responsible for consequences of warnings being issued or not. However, the communication of warnings for flooding and landslides at NVE still implies many considerations of geoethical kind. Which are the consequences today for the forecasters when erroneous warning messages are sent because based on a poorly documented analysis? What is for example the most responsible way to describe uncertainties in warnings issued? What is the optimal compromise between avoiding false alarms and not sending out a specific warning? Is it responsible to rely on a "gut feeling"? Some authorities complain in receiving warning messages too often. Is it responsible to begin notifying these, only in cases of "high hazard level" and no longer in cases of "moderate hazard level"? Is it acceptable to issue general warnings for large geographical areas without being able to pinpoint the treat on local scale? What responsibility lies within the EWS in recommending evacuation or other practical measures to local authorities? By presenting how early warnings of flooding and landslides are communicated in Norway and discussing the questions above, we intend to add to the discussion on what is the ethical responsibility for scientists performing forecasting and communication of natural hazards.

Application of τc*Pd in earthquake early warning

NASA Astrophysics Data System (ADS)

Huang, Po-Lun; Lin, Ting-Li; Wu, Yih-Min

2015-03-01

Rapid assessment of damage potential and size of an earthquake at the station is highly demanded for onsite earthquake early warning. We study the application of τc*Pd for its estimation on the earthquake size using 123 events recorded by the borehole stations of KiK-net in Japan. The new type of earthquake size determined by τc*Pd is more related to the damage potential. We find that τc*Pd provides another parameter to measure the size of earthquake and the threshold to warn strong ground motion.

Early Warning Signs. A Solution-Finding Report

ERIC Educational Resources Information Center

Sullivan, Robert, Comp.

2017-01-01

This Solution-Finding Report provides information, requested by Tara Zuber with the Great Lakes Comprehensive Center (GLCC) at American Institutes for Research (AIR), for resources with evidence-based practices that look at the social and emotional causes that impact the lack of student learning and engagement, for GLCC's Early Warning Signs work.…

Research on Disaster Early Warning and Disaster Relief Integrated Service System Based on Block Data Theory

NASA Astrophysics Data System (ADS)

Yang, J.; Zhang, H.; Wang, C.; Tang, D.

2018-04-01

With the continuous development of social economy, the interaction between mankind and nature has become increasingly evident. Disastrous global catastrophes have occurred from time to time, causing huge losses to people's lives and property. All governments recognize the importance of the establishment of disaster early warning and release mechanisms, and it is also an urgent issue to improve the comprehensive service level of emergency response and disaster relief. However, disaster early warning and emergency relief information is usually generated by different departments, and the diverse data sources, difficult integration, and limited release speed have always been difficult issues to be solved. Block data is the aggregation of various distributed (point data) and segmentation (data) big data on a specific platform and make them happen continuous polymerization effect, block data theory is a good solution to cross-sectoral, cross-platform Disaster information data sharing and integration problems. This paper attempts to discuss the integrated service mechanism of disaster information aggregation and disaster relief based on block data theory and introduces a location-based integrated service system for disaster early warning and disaster relief.

Relation between stability and resilience determines the performance of early warning signals under different environmental drivers.

PubMed

Dai, Lei; Korolev, Kirill S; Gore, Jeff

2015-08-11

Shifting patterns of temporal fluctuations have been found to signal critical transitions in a variety of systems, from ecological communities to human physiology. However, failure of these early warning signals in some systems calls for a better understanding of their limitations. In particular, little is known about the generality of early warning signals in different deteriorating environments. In this study, we characterized how multiple environmental drivers influence the dynamics of laboratory yeast populations, which was previously shown to display alternative stable states [Dai et al., Science, 2012]. We observed that both the coefficient of variation and autocorrelation increased before population collapse in two slowly deteriorating environments, one with a rising death rate and the other one with decreasing nutrient availability. We compared the performance of early warning signals across multiple environments as "indicators for loss of resilience." We find that the varying performance is determined by how a system responds to changes in a specific driver, which can be captured by a relation between stability (recovery rate) and resilience (size of the basin of attraction). Furthermore, we demonstrate that the positive correlation between stability and resilience, as the essential assumption of indicators based on critical slowing down, can break down in this system when multiple environmental drivers are changed simultaneously. Our results suggest that the stability-resilience relation needs to be better understood for the application of early warning signals in different scenarios.

Relation between stability and resilience determines the performance of early warning signals under different environmental drivers

PubMed Central

Dai, Lei; Korolev, Kirill S.; Gore, Jeff

2015-01-01

Shifting patterns of temporal fluctuations have been found to signal critical transitions in a variety of systems, from ecological communities to human physiology. However, failure of these early warning signals in some systems calls for a better understanding of their limitations. In particular, little is known about the generality of early warning signals in different deteriorating environments. In this study, we characterized how multiple environmental drivers influence the dynamics of laboratory yeast populations, which was previously shown to display alternative stable states [Dai et al., Science, 2012]. We observed that both the coefficient of variation and autocorrelation increased before population collapse in two slowly deteriorating environments, one with a rising death rate and the other one with decreasing nutrient availability. We compared the performance of early warning signals across multiple environments as “indicators for loss of resilience.” We find that the varying performance is determined by how a system responds to changes in a specific driver, which can be captured by a relation between stability (recovery rate) and resilience (size of the basin of attraction). Furthermore, we demonstrate that the positive correlation between stability and resilience, as the essential assumption of indicators based on critical slowing down, can break down in this system when multiple environmental drivers are changed simultaneously. Our results suggest that the stability–resilience relation needs to be better understood for the application of early warning signals in different scenarios. PMID:26216946

Report on dynamic speed harmonization and queue warning algorithm design.

DOT National Transportation Integrated Search

2014-02-01

This report provides a detailed description of the algorithms that will be used to generate harmonized recommended speeds and queue warning information in the proposed Intelligent Network Flow Optimization (INFLO) prototype. This document describes t...

Challenges for implementing Earthquake Early Warning: A Case Study in Nicaragua

NASA Astrophysics Data System (ADS)

Massin, F.; Clinton, J. F.; Boese, M.; Cauzzi, C.; Strauch, W.

2017-12-01

Earthquake early warning (EEW) systems aim at providing fast and accurate estimates of event parameters or local ground shaking over wide ranges of source dimensions and epicentral distances. The Swiss Seismological Service (SED) has integrated EEW solutions into the SeisComP3 (SC3) professional earthquake monitoring software. VS(SC3) provides fast magnitude estimates for network-based point-sources using conventional triggering and phases association techniques, while FinDer(SC3) matches the evolving patterns of ground motion to track on-going rupture extent, and can provide accurate ground motion predictions for finite fault ruptures. SC3 is widely used, including in Central America, and at INETER in Nicaragua. In 2016, SED and INETER started a joint project to assess the feasibility of EEW in Nicaragua and Central America and to set up a prototype EEW system. We test VS(SC3) and FinDer(SC3) softwares at INETER since 2016. Excellent relations between regional seismic networks mean broadband and strong motion seismic data are exchanged across Central America in real time, which means the network is sufficient to warrant investigation into its potential for EEW. We report on the successes and challenges of operating an EEW system where seismicity is high, but infrastructure is fragile and the design and operation of a seismic network is challenging (in Nicaragua, on average 50% of all stations do not work effectively for EEW). The current best EEW delays for on-shore earthquakes in Nicaragua is in the order of 20s and 40s offshore. However, the current network should be able to provide EEW in 10 to 15s on-shore and 20 to 25s off-shore which correspond to potential EEW intensities over or equal to VII. We compare the performances of EEW in Nicaragua with an ideal setting, featuring optimized data availability. We evaluate improvements strategies of the Nicaraguan and the Joint Central American Seismic Networks for EEW. And we discuss how to combine real-time EEW reports from VS(SC3) and FinDer(SC3) algorithms to provide a single EEW using existing probabilistic ground motion comparison methods. The project is funded by the Swiss Development Agency and supported by Nicaragua.

A fundamental conflict of care: Nurses' accounts of balancing patients' sleep with taking vital sign observations at night.

PubMed

Hope, Joanna; Recio-Saucedo, Alejandra; Fogg, Carole; Griffiths, Peter; Smith, Gary B; Westwood, Greta; Schmidt, Paul E

2017-12-21

To explore why adherence to vital sign observations scheduled by an early warning score protocol reduces at night. Regular vital sign observations can reduce avoidable deterioration in hospital. early warning score protocols set the frequency of these observations by the severity of a patient's condition. Vital sign observations are taken less frequently at night, even with an early warning score in place, but no literature has explored why. A qualitative interpretative design informed this study. Seventeen semi-structured interviews with nursing staff working on wards with varying levels of adherence to scheduled vital sign observations. A thematic analysis approach was used. At night, nursing teams found it difficult to balance the competing care goals of supporting sleep with taking vital sign observations. The night-time frequency of these observations was determined by clinical judgement, ward-level expectations of observation timing and the risk of disturbing other patients. Patients with COPD or dementia could be under-monitored, while patients nearing the end of life could be over-monitored. In this study, we found an early warning score algorithm focused on deterioration prevention did not account for long-term management or palliative care trajectories. Nurses were therefore less inclined to wake such patients to take vital sign observations at night. However, the perception of widespread exceptions and lack of evidence regarding optimum frequency risks delegitimising the early warning score approach. This may pose a risk to patient safety, particularly patients with dementia or chronic conditions. Nurses should document exceptions and discuss these with the wider team. Hospitals should monitor why vital sign observations are missed at night, identify which groups are under-monitored and provide guidance on prioritising competing expectations. early warning score protocols should take account of different care trajectories. © 2017 The Authors. Journal of Clinical Nursing Published by John Wiley & Sons Ltd.

Monitoring Regional Forest Disturbances across the US with Near Real Time MODIS NDVI Products included in the ForWarn Forest Threat Early Warning System

NASA Technical Reports Server (NTRS)

Spruce, Joseph; Hargrove, William W.; Gasser, Gerald; Norman, Steve

2013-01-01

U.S. forests occupy approx.1/3 of total land area (approx. 304 million ha). Since 2000, a growing number of regionally evident forest disturbances have occurred due to abiotic and biotic agents. Regional forest disturbances can threaten human life and property, bio-diversity and water supplies. Timely regional forest disturbance monitoring products are needed to aid forest health management work. Near Real Time (NRT) twice daily MODIS NDVI data provide a means to monitor U.S. regional forest disturbances every 8 days. Since 2010, these NRT forest change products have been produced and posted on the US Forest Service ForWarn Early Warning System for Forest Threats.

Early warning signals for critical transitions in a thermoacoustic system

PubMed Central

Gopalakrishnan, E. A.; Sharma, Yogita; John, Tony; Dutta, Partha Sharathi; Sujith, R. I.

2016-01-01

Dynamical systems can undergo critical transitions where the system suddenly shifts from one stable state to another at a critical threshold called the tipping point. The decrease in recovery rate to equilibrium (critical slowing down) as the system approaches the tipping point can be used to identify the proximity to a critical transition. Several measures have been adopted to provide early indications of critical transitions that happen in a variety of complex systems. In this study, we use early warning indicators to predict subcritical Hopf bifurcation occurring in a thermoacoustic system by analyzing the observables from experiments and from a theoretical model. We find that the early warning measures perform as robust indicators in the presence and absence of external noise. Thus, we illustrate the applicability of these indicators in an engineering system depicting critical transitions. PMID:27767065

Development and Experimental Application of International Affairs Indicators. Volume B. Supportive Research

DTIC Science & Technology

1974-06-01

i INDICATORS Approaches to Early Warning The Quantitative Indicators Approach: A ... 5 Summary Indicators and Early Warning...Indicators for Early ^ Wa rning 3. Quantitative Signs of Unusual or Ominous Activity 9 13 4. Simulated Cables 25 5 . TEXSCAN...Behavior) for Czechoslovakia 1 mmmmm mmm LIST OF FIGURES vi Pa£« 1. 2. 3. 4. 5 . 6. 7. 8. 9. 10. U. 12. 13. 14. 15. 16. 17. 18

Neural correlates of cigarette health warning avoidance among smokers.

PubMed

Stothart, George; Maynard, Olivia; Lavis, Rosie; Munafò, Marcus

2016-04-01

Eye-tracking technology has indicated that daily smokers actively avoid pictorial cigarette package health warnings. Avoidance may be due to a pre-cognitive perceptual bias or a higher order cognitive bias, such as reduced emotional processing. Using electroencephalography (EEG), this study aimed to identify the temporal point at which smokers' responses to health warnings begin to differ. Non-smokers (n=20) and daily smokers (n=20) viewed pictorial cigarette package health warnings and neutral control stimuli. These elicited Event Related Potentials reflecting early perceptual processing (visual P1), pre-attentive change detection (visual Mismatch Negativity), selective attentional orientation (P3) and a measure of emotional processing, the Late Positive Potential (LPP). There was no evidence for a difference in P1 responses between smokers and non-smokers. There was no difference in vMMN and P3 amplitude but some evidence for a delay in vMMN latency amongst smokers. There was strong evidence for delayed and reduced LPP to health warning stimuli amongst smokers compared to non-smokers. We find no evidence for an early perceptual bias in smokers' visual perception of health warnings but strong evidence that smokers are less sensitive to the emotional content of cigarette health warnings. Future health warning development should focus on increasing the emotional salience of pictorial health warning content amongst smokers. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Quantum geodesy

NASA Astrophysics Data System (ADS)

Jitrik, Oliverio; Lanzagorta, Marco; Uhlmann, Jeffrey; Venegas-Andraca, Salvador E.

2017-05-01

The study of plate tectonic motion is important to generate theoretical models of the structure and dynamics of the Earth. In turn, understanding tectonic motion provides insight to develop sophisticated models that can be used for earthquake early warning systems and for nuclear forensics. Tectonic geodesy uses the position of a network of points on the surface of earth to determine the motion of tectonic plates and the deformation of the earths crust. GPS and interferometric synthetic aperture radar are commonly used techniques used in tectonic geodesy. In this paper we will describe the feasibility of interferometric synthetic aperture quantum radar and its theoretical performance for tectonic geodesy.

Adolescents perceived effectiveness of the proposed European graphic tobacco warning labels.

PubMed

Vardavas, Constantine I; Connolly, Gregory; Karamanolis, Kostas; Kafatos, Anthony

2009-04-01

Graphical tobacco product labelling is a prominent source of health information and has an important position among tobacco control initiatives. However, little is known about its effectiveness among adolescents. With this above in mind, we aimed to research into how adolescents perceive the proposed EU graphic tobacco product warning labels as an effective means of preventing smoking initiation in comparison to the current EU text-only warning labels. Five hundred seventy four adolescents (13-18, 54% male) from Greece were privately interviewed, with the use of a digital questionnaire and randomly shown seven existing EU text-only and proposed EU graphic warning labels. Non-smoking respondents were asked to compare and rate the warnings effectiveness in regard to preventing them from smoking on a 1-5 Likert type scale. Irrespective of the warning category shown, on all occasions, non-smoking adolescents rated the suggested EU graphic labels as more effective in preventing them from smoking in comparison to the existing EU text-only warnings. Controlling for gender, age, current smoking status and number of cigarettes smoked per month, younger adolescents were found to opt for graphic warnings more often, and also perceive graphic warning labels as a more effective means of preventing them from smoking, in comparison to their elder peers (P < 0.001). The proposed EU graphic warning labels may play an important role in preventing of smoking initiation during the crucial years of early adolescence when smoking experimentation and early addiction usually take place.

Global Tsunami Warning System Development Since 2004

NASA Astrophysics Data System (ADS)

Weinstein, S.; Becker, N. C.; Wang, D.; Fryer, G. J.; McCreery, C.; Hirshorn, B. F.

2014-12-01

The 9.1 Mw Great Sumatra Earthquake of Dec. 26, 2004, generated the most destructive tsunami in history killing 227,000 people along Indian Ocean coastlines and was recorded by sea-level instruments world-wide. This tragedy showed the Indian Ocean needed a tsunami warning system to prevent another tragedy on this scale. The Great Sumatra Earthquake also highlighted the need for tsunami warning systems in other ocean basins. Instruments for recording earthquakes and sea-level data useful for tsunami monitoring did not exist outside of the Pacific Ocean in 2004. Seismometers were few in number, and even fewer were high-quality long period broadband instruments. Nor was much of their data made available to the US tsunami warning centers (TWCs). In 2004 the US TWCs relied exclusively on instrumentation provided and maintained by IRIS and the USGS for areas outside of the Pacific.Since 2004, the US TWCs and their partners have made substantial improvements to seismic and sea-level monitoring networks with the addition of new and better instruments, densification of existing networks, better communications infrastructure, and improved data sharing among tsunami warning centers. In particular, the number of sea-level stations transmitting data in near real-time and the amount of seismic data available to the tsunami warning centers has more than tripled. The DART network that consisted of a half-dozen Pacific stations in 2004 now totals nearly 60 stations worldwide. Earthquake and tsunami science has progressed as well. It took nearly three weeks to obtain the first reliable estimates of the 2004 Sumatra Earthquake's magnitude. Today, thanks to improved seismic networks and modern computing power, TWCs use the W-phase seismic moment method to determine accurate earthquake magnitudes and focal mechanisms for great earthquakes within 25 minutes. TWC scientists have also leveraged these modern computers to generate tsunami forecasts in a matter of minutes.Progress towards a global tsunami warning system has been substantial and today fully-functioning TWCs protect most of the world's coastlines. These improvements have also led to a substantial reduction of time required by the TWCs to detect, locate, and assess the tsunami threat from earthquakes occurring worldwide.

Wireless technologies for the monitoring of strategic civil infrastructures: an ambient vibration test of the Faith Bridge, Istanbul, Turkey

NASA Astrophysics Data System (ADS)

Picozzi, M.; Milkereit, C.; Zulfikar, C.; Ditommaso, R.; Erdik, M.; Safak, E.; Fleming, K.; Ozel, O.; Zschau, J.; Apaydin, N.

2008-12-01

The monitoring of strategic civil infrastructures to ensure their structural integrity is a task of major importance, especially in earthquake-prone areas. Classical approaches to such monitoring are based on visual inspections and the use of wired systems. While the former has the drawback that the structure is only superficially examined and discontinuously in time, wired systems are relatively expensive and time consuming to install. Today, however, wireless systems represent an advanced, easily installed and operated tool to be used for monitoring purposes, resulting in a wide and interesting range of possible applications. Within the framework of the earthquake early warning projects SAFER (Seismic eArly warning For EuRope) and EDIM (Earthquake Disaster Information systems for the Marmara Sea region, Turkey), new low-cost wireless sensors with the capability to automatically rearrange their communications scheme are being developed. The reduced sensitivity of these sensors, arising from the use of low-cost components, is compensated by the possibility of deploying high-density self-organizing networks performing real-time data acquisition and analysis. Thanks to the developed system's versatility, it has been possible to perform an experimental ambient vibration test with a network of 24 sensors on the Fatih Sultan Mehmet Bridge, Istanbul (Turkey), a gravity-anchored suspension bridge spanning the Bosphorus Strait with distance between its towers of 1090 m. Preliminary analysis of the data has demonstrated that the main modal properties of the bridge can be retrieved, and may therefore be regularly re-evaluated as part of a long-term monitoring program. Using a multi-hop communications technique, data could be exchanged among groups of sensors over distances of a few hundred meters. Thus, the test showed that, although more work is required to optimize the communication parameters, the performance of the network offers encouragement for us to follow this research direction in developing wireless systems for the monitoring of civil infrastructures.

Development and Use of Early Warning Systems. SLDS Spotlight

ERIC Educational Resources Information Center

Curtin, Jenny; Hurwitch, Bill; Olson, Tom

2012-01-01

An early warning system is a data-based tool that helps predict which students are on the right path towards eventual graduation or other grade-appropriate goals. Through such systems, stakeholders at the school and district levels can view data from a wide range of perspectives and gain a deeper understanding of student data. This "Statewide…

Vantage point - Early warning flaws.

PubMed

Swinden, Donna

2014-08-28

USING AN EARLY warning score (EWS) system should improve the detection of acutely deteriorating patients. Under such a system, a score is allocated to each of six physiological measurements including respiratory rate and oxygen saturations, which are aggregated to produce an overall score. An aggregated score of seven or higher prompts nursing staff to refer a patient for emergency assessment.

Early Warning Indicator System: Supporting K-12 Educators in the Identification, Support, and Monitoring of At-Risk Students

ERIC Educational Resources Information Center

Massachusetts Department of Elementary and Secondary Education, 2016

2016-01-01

A rise in data availability gives educators the opportunity to tailor instructional practices and interventions to student needs and invest resources in areas where students require the most support. Massachusetts developed the Early Warning Indicator System (EWIS), which synthesizes the wealth of student data available in the state, including…

Regional drought early warning, impacts, and assessment for water and agriculture in the lower Rio Grande basin, 2016-2017

USDA-ARS?s Scientific Manuscript database

USDA’s Southern Plains Climate Hub (SPCH) and the University of Oklahoma’s Southern Climate Impacts Planning Program (SCIPP) contributed to a broad, multi-partnered effort to provide drought early warning information to water and agriculture management interests in the middle and lower Rio Grande ba...

A Practitioner's Guide to Implementing Early Warning Systems. REL 2015-056

ERIC Educational Resources Information Center

Frazelle, Sarah; Nagel, Aisling

2015-01-01

To stem the tide of students dropping out, many schools and districts are turning to early warning systems (EWS) that signal whether a student is at risk of not graduating from high school. While some research exists about establishing these systems, there is little information about the actual implementation strategies that are being used across…

An Analysis of the 1992 New Jersey Grade 8 Early Warning Test.

ERIC Educational Resources Information Center

Tambini, Robert F.

The quality and the effectiveness of the 1992 New Jersey Grade 8 Early Warning Test (NJEWT) are assessed. Standardized tests possess clear advantages for educators, especially in the case of administration and scoring, but there are clear disadvantages as well, including the possibility of bias. Four criteria are applied to the NJEWT: adequacy,…

Overview and highlights of Early Warning and Crop Condition Assessment project

NASA Technical Reports Server (NTRS)

Boatwright, G. O.; Whitehead, V. S.

1985-01-01

Work of the Early Warning and Crop Condition Assessment (EW/CCA) project, one of eight projects in the Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing (AgRISTARS), is reviewed. Its mission, to develop and test remote sensing techniques that enhance operational methodologies for crop condition assessment, was in response to initiatives issued by the Secretary of Agriculture. Meteorologically driven crop stress indicator models have been developed or modified for wheat, maize, grain sorghum, and soybeans. These models provide early warning alerts of potential or actual crop stresses due to water deficits, adverse temperatures, and water excess that could delay planting or harvesting operations. Recommendations are given for future research involving vegetative index numbers and the NOAA and Landsat satellites.

MyShake: Initial Observations from a Global Smartphone Seismic Network

NASA Astrophysics Data System (ADS)

Kong, Q.; Allen, R. M.; Schreier, L.

2016-12-01

MyShake is a global smartphone seismic network that harnesses the power of crowdsourcing. It has two component: an android application running on the personal smartphones to detect earthquake-like motion, and a network detection algorithm to aggregate results from multiple smartphones to detect earthquakes. The MyShake application was released to the public on Feb 12th 2016. Within the first 5 months, there are more than 200 earthquakes recorded by the smartphones all over the world, including events in Chile, Argentina, Mexico, Morocco, Greece, Nepal, New Zealand, Taiwan, Japan, and across North America. In this presentation, we will show the waveforms we recorded from the smartphones for different earthquakes, and the evidences for using this data as a supplementary to the current earthquake early warning system. We will also show the performance of MyShake system during the some earthquakes in US. In short, MyShake smartphone seismic network can be a nice complementary system to the current traditional seismic network, at the same time, it can be a standalone system in places where few seismic stations were installed to reduce the earthquake hazards.

An analysis of the early-warning system in emerging markets for reducing the financial crisis

NASA Astrophysics Data System (ADS)

Shen, Xiangguang; Song, Xiaozhong

2009-07-01

The large number of financial crises in emerging markets over the past ten years has left many observers, both from academia and financial institutions, puzzled by an apparent lack of homogenous causal relations between endogenous economic variables and the bursting of large financial shocks. The frequency of financial crises in the last 20 years can be attributed to the lack of a comprehensive theory of financial regulation to guide policy makers. Existing theories fail to define the range of regulatory models, the causes of regulatory failure, and how to measure and prevent it. Faulty design of regulatory models, and the lack of ongoing performance monitoring incorporating early warning systems, is disrupting economic and social development. The main aim of this article is to propose an early warning system (EWS) which purposes issuing warning signal against the possible financial crisis in the emerging market, and makes the emerging market survived the first wave of the crisis be able to continue their operation in the following years.

The effects of volcanoes on health: preparedness in Mexico.

PubMed

Zeballos, J L; Meli, R; Vilchis, A; Barrios, L

1996-01-01

The article reviews the most important aspects of volcanic eruptions and presents a summary of the harmful materials they emit. The main health effects can be classified as either physical (trauma, respiratory diseases, etc.) or psychological (depression, anxiety, nightmares, neurosis, etc.). Popocatépetl, the most famous active volcano in Mexico, lies on the borders of the States of Mexico, Puebla and Morelos. In 1993, seismic activity intensified, as did as the emission of fumaroles, followed in December 1994 by moderate tremors and strong emissions of gases and ash. In 1996, a number of seismic events led to an unexpected explosion. A daily emission of 8,000 to 15,000 tonnes of sulfur dioxide has been measured. Popocatépetl is located in a densely populated region of Mexico. A complex network to monitor the volcano using sophisticated equipment has been set up, including visual surveillance, seismic, geochemical and geodesic monitoring. An early warning system (SINAPROC/CENAPRED) has been developed to keep the population permanently informed. The warning system uses colour codes: green for normal, yellow for alert, and red for warning and evacuation. An emergency plan has been prepared, including evacuation and preparation for medical centres and hospitals in the region, as well as intense public information campaigns.

Tsunami warnings: Understanding in Hawai'i

USGS Publications Warehouse

Gregg, Chris E.; Houghton, Bruce F.; Paton, Douglas; Johnston, David M.; Swanson, D.A.; Yanagi, B.S.

2007-01-01

The devastating southeast Asian tsunami of December 26, 2004 has brought home the destructive consequences of coastal hazards in an absence of effective warning systems. Since the 1946 tsunami that destroyed much of Hilo, Hawai'i, a network of pole mounted sirens has been used to provide an early public alert of future tsunamis. However, studies in the 1960s showed that understanding of the meaning of siren soundings was very low and that ambiguity in understanding had contributed to fatalities in the 1960 tsunami that again destroyed much of Hilo. The Hawaiian public has since been exposed to monthly tests of the sirens for more than 25 years and descriptions of the system have been widely published in telephone books for at least 45 years. However, currently there remains some uncertainty in the level of public understanding of the sirens and their implications for behavioral response. Here, we show from recent surveys of Hawai'i residents that awareness of the siren tests and test frequency is high, but these factors do not equate with increased understanding of the meaning of the siren, which remains disturbingly low (13%). Furthermore, the length of time people have lived in Hawai'i is not correlated systematically with understanding of the meaning of the sirens. An additional issue is that warning times for tsunamis gene rated locally in Hawai'i will be of the order of minutes to tens of minutes and limit the immediate utility of the sirens. Natural warning signs of such tsunamis may provide the earliest warning to residents. Analysis of a survey subgroup from Hilo suggests that awareness of natural signs is only moderate, and a majority may expect notification via alerts provided by official sources. We conclude that a major change is needed in tsunami education, even in Hawai'i, to increase public understanding of, and effective response to, both future official alerts and natural warning signs of future tsunamis. ?? Springer 2006.

Packaging: a grounded theory of how to report physiological deterioration effectively.

PubMed

Andrews, Tom; Waterman, Heather

2005-12-01

The aim of this paper is to present a study of how ward-based staff use vital signs and the Early Warning Score to package physiological deterioration effectively to ensure successful referral to doctors. The literature tends to emphasize the identification of premonitory signs in predicting physiological deterioration. However, these signs lack sensitivity and specificity, and there is evidence that nurses rely on subjective and subtle indicators. The Early Warning Score was developed for the early detection of deterioration and has been widely implemented, with various modifications. The data reported here form part of a larger study investigating the practical problems faced by general ward staff in detecting physiological deterioration. During 2002, interviews and observations were carried out using a grounded theory approach, and a total of 44 participants were interviewed (30 nurses, 7 doctors and 7 health care support workers). Participants reported that quantifiable evidence is the most effective means of referring patients to doctors, and the Early Warning Score achieves this by improving communication between professionals. Rather than reporting changes in individual vital signs, the Early Warning Score effectively packages them together, resulting in a much more convincing referral. It gives nurses a precise, concise and unambiguous means of communicating deterioration, and confidence in using medical language. Thus, nurses are empowered and doctors can focus quickly on identified problems. The Early Warning Score leads to successful referral of patients by providing an agreed framework for assessment, increasing confidence in the use of medical language and empowering nurses. It is essential that nurses and nursing students are supported in its use and in developing confidence in using medical language by continued emphasis on physiology and pathophysiology in the nursing curriculum.

Which System Variables Carry Robust Early Signs of Upcoming Phase Transition? An Ecological Example.

PubMed

Negahbani, Ehsan; Steyn-Ross, D Alistair; Steyn-Ross, Moira L; Aguirre, Luis A

2016-01-01

Growth of critical fluctuations prior to catastrophic state transition is generally regarded as a universal phenomenon, providing a valuable early warning signal in dynamical systems. Using an ecological fisheries model of three populations (juvenile prey J, adult prey A and predator P), a recent study has reported silent early warning signals obtained from P and A populations prior to saddle-node (SN) bifurcation, and thus concluded that early warning signals are not universal. By performing a full eigenvalue analysis of the same system we demonstrate that while J and P populations undergo SN bifurcation, A does not jump to a new state, so it is not expected to carry early warning signs. In contrast with the previous study, we capture a significant increase in the noise-induced fluctuations in the P population, but only on close approach to the bifurcation point; it is not clear why the P variance initially shows a decaying trend. Here we resolve this puzzle using observability measures from control theory. By computing the observability coefficient for the system from the recordings of each population considered one at a time, we are able to quantify their ability to describe changing internal dynamics. We demonstrate that precursor fluctuations are best observed using only the J variable, and also P variable if close to transition. Using observability analysis we are able to describe why a poorly observable variable (P) has poor forecasting capabilities although a full eigenvalue analysis shows that this variable undergoes a bifurcation. We conclude that observability analysis provides complementary information to identify the variables carrying early-warning signs about impending state transition.

A introduction of a Scientific Research Program on Chinese Drought

NASA Astrophysics Data System (ADS)

Li, Y.

2014-12-01

Drought is one of the major meteorological disasters, with high frequencies, wide distributions and serious conditions. It is one of the biggest impacts on global agricultural productions, ecological environment and socioeconomic sustainable developments. China is particularly one of the countries in the world with serious drought disasters. The goal of this project is improving the capabilities in drought monitoring and forecasting based on an in-depth theories of drought. The project will be implemented in the typical extreme drought area based on comprehensive and systemic observation network and numerical experiments It will show a complete feedback mechanism among the atmospheric, water, biological and other spheres for forming drought. First, the atmospheric droughts that leads to agriculture and hydrologic drought and the possible causes for these disasters will be explored using our observation data sets. Second, the capability of monitoring, forecasting and early warning for drought will be developed with numerical model (regional climate model and land surface model, etc.). Last but not the least, evaluation approaches for the risk of drought and the strategy of predicting/prohibiting the drought at regional scale will be proposed. Meanwhile, service system and information sharing platform of drought monitoring and early warning will be established to improve the technical level of drought disaster preparedness and response in China.

UNAVCO Real-Time GNSS Positioning: High-Precision Static and Kinematic Testing of the Next Generation GNSS network.

NASA Astrophysics Data System (ADS)

Berglund, H. T.; Hodgkinson, K. M.; Blume, F.; Mencin, D.; Phillips, D. A.; Meertens, C. M.; Mattioli, G. S.

2014-12-01

The GAGE Facility, managed by UNAVCO, operates a real-time GNSS (RT-GNSS) network of ~450 stations. The majority of the streaming stations are part of the EarthScope Plate Boundary Observatory (PBO). Following community input from a real-time GNSS data products and formats meeting hosted by UNAVCO in Spring of 2011, UNAVCO now provides real-time PPP positions, and network solutions where practical, for all available stations using Trimble's PIVOT RTX server software and TrackRT. The UNAVCO real-time system has the potential to enhance our understanding of earthquakes, seismic wave propagation, volcanic eruptions, magmatic intrusions, movement of ice, landslides, and the dynamics of the atmosphere. Beyond the ever increasing applications in science and engineering, RT-GNSS has the potential to provide early warning of hazards to emergency managers, utilities, other infrastructure managers, first responders and others. Upgrades to the network include eight Trimble NetR9 GNSS receivers with GLONASS and receiver-based RTX capabilities and sixteen new co-located MEMS based accelerometers. These new capabilities will allow integration of GNSS and strong motion data to produce broad-spectrum waveforms improving Earthquake Early Warning systems. Controlled outdoor kinematic and static experiments provide a useful method for evaluating and comparing real-time systems. UNAVCO has developed a portable low-cost antenna actuator to characterize the kinematic performance of receiver- and server-based real-time positioning algorithms and identify system limitations. We have performed tests using controlled 1-d antenna motions and will present comparisons between these and other post-processed kinematic algorithms including GIPSY-OASIS and TRACK. In addition to kinematic testing, long-term static testing of Trimble's RTX service is ongoing at UNAVCO and will be used to characterize the stability of the position time-series produced by RTX. In addition, with the goal of characterizing stability and improving software and higher level products based on real-time and high frequency GNSS time series, we present an overview of the UNAVCO RT-GPS system, a comparison of the UNAVCO generated real-time, static and community data products, and an overview of available common data sets.

The analysis of behavior in orbit GSS two series of US early-warning system

NASA Astrophysics Data System (ADS)

Sukhov, P. P.; Epishev, V. P.; Sukhov, K. P.; Motrunych, I. I.

2016-09-01

Satellites Early Warning System Series class SBIRS US Air Force must replace on GEO early series DSP Series. During 2014-2016 the authors received more than 30 light curves "DSP-18 and "Sbirs-Geo 2". The analysis of the behavior of these satellites in orbit by a coordinate and photometric data. It is shown that for the monitoring of the Earth's surface is enough to place GEO 4 unit SBIRS across 90 deg.

ElarmS Earthquake Early Warning System 2016 Performance and New Research

NASA Astrophysics Data System (ADS)

Chung, A. I.; Allen, R. M.; Hellweg, M.; Henson, I. H.; Neuhauser, D. S.

2016-12-01

The ElarmS earthquake early warning system has been detecting earthquakes throughout California since 2007. It is one of the algorithms that contributes to the West Coast ShakeAlert, a prototype earthquake early warning system being developed for the US West Coast. ElarmS is also running in the Pacific Northwest, and in Israel, Chile, Turkey, and Peru in test mode. We summarize the performance of the ElarmS system over the past year and review some of the more problematic events that the system has encountered. During the first half of 2016 (2016-01-01 through 2016-07-21), ElarmS successfully alerted on all events with ANSS catalog magnitudes M>3 in the Los Angeles area. The mean alert time for these 9 events was just 4.84 seconds. In the San Francisco Bay Area, ElarmS detected 26 events with ANSS catalog magnitudes M>3. The alert times for these events is 9.12 seconds. The alert times are longer in the Bay Area than in the Los Angeles area due to the sparser network of stations in the Bay Area. 7 Bay Area events were not detected by ElarmS. These events occurred in areas where there is less dense station coverage. In addition, ElarmS sent alerts for 13 of the 16 moderately-sized (ANSS catalog magnitudes M>4) events that occurred throughout the state of California. One of those missed events was a M4.5 that occurred far offshore in the northernmost part of the state. The other two missed events occurred inland in regions with sparse station coverage. Over the past year, we have worked towards the implementation of a new filterbank teleseismic filter algorithm, which we will discuss. Other than teleseismic events, a significant cause of false alerts and severely mislocated events is spurious triggers being associated with triggers from a real earthquake. Here, we address new approaches to filtering out problematic triggers.

Combined wave propagation analysis of earthquake recordings from borehole and building sensors

NASA Astrophysics Data System (ADS)

Petrovic, B.; Parolai, S.; Dikmen, U.; Safak, E.; Moldobekov, B.; Orunbaev, S.

2015-12-01

In regions highly exposed to natural hazards, Early Warning Systems can play a central role in risk management and mitigation procedures. To improve at a relatively low cost the spatial resolution of regional earthquake early warning (EEW) systems, decentralized onsite EEW and building monitoring, a wireless sensing unit, the Self-Organizing Seismic Early Warning Information Network (SOSEWIN) was developed and further improved to include the multi-parameter acquisition. SOSEWINs working in continuous real time mode are currently tested on various sites. In Bishkek and Istanbul, an instrumented building is located close to a borehole equipped with downhole sensors. The joint data analysis of building and borehole earthquake recordings allows the study of the behavior of the building, characteristics of the soil, and soil-structure interactions. The interferometric approach applied to recordings of the building response is particularly suitable to characterize the wave propagation inside a building, including the propagation velocity of shear waves and attenuation. Applied to borehole sensors, it gives insights into velocity changes in different layers, reflections and mode conversion, and allows the estimation of the quality factor Qs. We used combined building and borehole data from the two test sites: 1) to estimate the characteristics of wave propagation through the building to the soil and back, and 2) to obtain an empirical insight into soil-structure interactions. The two test sites represent two different building and soil types, and soil structure impedance contrasts. The wave propagation through the soil to the building and back is investigated by the joint interferometric approach. The propagation of up and down-going waves through the building and soil is clearly imaged and the reflection of P and S waves from the earth surface and the top of the building identified. An estimate of the reflected and transmitted energy amounts is given, too.

Assessing the add value of ensemble forecast in a drought early warning

NASA Astrophysics Data System (ADS)

Calmanti, Sandro; Bosi, Lorenzo; Fernandez, Jesus; De Felice, Matteo

2015-04-01

The EU-FP7 project EUPORIAS is developing a prototype climate service to enhance the existing food security drought early warning system in Ethiopia. The Livelihoods, Early Assessment and Protection (LEAP) system is the Government of Ethiopia's national food security early warning system, established with the support of WFP and the World Bank in 2008. LEAP was designed to increase the predictability and timeliness of response to drought-related food crises in Ethiopia. It combines early warning with contingency planning and contingency funding, to allow the government, WFP and other partners to provide early assistance in anticipation of an impending catastrophes. Currently, LEAP uses satellite based rainfall estimates to monitor drought conditions and to compute needs. The main aim of the prototype is to use seasonal hindcast data to assess the added value of using ensemble climate rainfall forecasts to estimate the cost of assistance of population hit by major droughts. We outline the decision making process that is informed by the prototype climate service, and we discuss the analysis of the expected and skill of the available rainfall forecast data over Ethiopia. One critical outcome of this analysis is the strong dependence of the expected skill on the observational estimate assumed as reference. A preliminary evaluation of the full prototype products (drought indices and needs estimated) using hindcasts data will also be presented.

DISTANT EARLY WARNING SYSTEM for Tsunamis - A wide-area and multi-hazard approach

NASA Astrophysics Data System (ADS)

Hammitzsch, Martin; Lendholt, Matthias; Wächter, Joachim

2010-05-01

The DEWS (Distant Early Warning System) [1] project, funded under the 6th Framework Programme of the European Union, has the objective to create a new generation of interoperable early warning systems based on an open sensor platform. This platform integrates OGC [2] SWE [3] compliant sensor systems for the rapid detection of hazardous events, like earthquakes, sea level anomalies, ocean floor occurrences, and ground displacements in the case of tsunami early warning. Based on the upstream information flow DEWS focuses on the improvement of downstream capacities of warning centres especially by improving information logistics for effective and targeted warning message aggregation for a multilingual environment. Multiple telecommunication channels will be used for the dissemination of warning messages. Wherever possible, existing standards have been integrated. The Command and Control User Interface (CCUI), a rich client application based on Eclipse RCP (Rich Client Platform) [4] and the open source GIS uDig [5], integrates various OGC services. Using WMS (Web Map Service) [6] and WFS (Web Feature Service) [7] spatial data are utilized to depict the situation picture and to integrate a simulation system via WPS (Web Processing Service) [8] to identify affected areas. Warning messages are compiled and transmitted in the OASIS [9] CAP (Common Alerting Protocol) [10] standard together with addressing information defined via EDXL-DE (Emergency Data Exchange Language - Distribution Element) [11]. Internal interfaces are realized with SOAP [12] web services. Based on results of GITEWS [13] - in particular the GITEWS Tsunami Service Bus [14] - the DEWS approach provides an implementation for tsunami early warning systems but other geological paradigms are going to follow, e.g. volcanic eruptions or landslides. Therefore in future also multi-hazard functionality is conceivable. The specific software architecture of DEWS makes it possible to dock varying sensors to the system and to extend the CCUI with hazard specific functionality. The presentation covers the DEWS project, the system architecture and the CCUI in conjunction with details of information logistics. The DEWS Wide Area Centre connecting national centres to allow the international communication and warning exchange is presented also. REFERENCES: [1] DEWS, www.dews-online.org [2] OGC, www.opengeospatial.org [3] SWE, www.opengeospatial.org/projects/groups/sensorweb [4] Eclipse RCP, www.eclipse.org/home/categories/rcp.php [5] uDig, udig.refractions.net [6] WMS, www.opengeospatial.org/standards/wms [7] WFS, www.opengeospatial.org/standards/wfs [8] WPS, www.opengeospatial.org/standards/wps [9] OASIS, www.oasis-open.org [10] CAP, www.oasis-open.org/specs/#capv1.1 [11] EDXL-DE, www.oasis-open.org/specs/#edxlde-v1.0 [12] SOAP, www.w3.org/TR/soap [13] GITEWS (German Indonesian Tsunami Early Warning System) is a project of the German Federal Government to aid the recon¬struction of the tsunami-prone Indian Ocean region, www.gitews.org [14] The Tsunami Service Bus is the GITEWS sensor system integration platform offering standardised services for the detection and monitoring of tsunamis

An integrated earthquake early warning system and its performance at schools in Taiwan

NASA Astrophysics Data System (ADS)

Wu, Bing-Ru; Hsiao, Nai-Chi; Lin, Pei-Yang; Hsu, Ting-Yu; Chen, Chiou-Yun; Huang, Shieh-Kung; Chiang, Hung-Wei

2017-01-01

An earthquake early warning (EEW) system with integration of regional and onsite approaches was installed at nine demonstration stations in several districts of Taiwan for taking advantages of both approaches. The system performance was evaluated by a 3-year experiment at schools, which experienced five major earthquakes during this period. The blind zone of warning was effectively reduced by the integrated EEW system. The predicted intensities from EEW demonstration stations showed acceptable accuracy compared to field observations. The operation experience from an earthquake event proved that students could calmly carry out correct action before the seismic wave arrived using some warning time provided by the EEW system. Through successful operation in practice, the integrated EEW system was verified as an effective tool for disaster prevention at schools.

SafeLand guidelines for landslide monitoring and early warning systems in Europe - Design and required technology

NASA Astrophysics Data System (ADS)

Bazin, S.

2012-04-01

Landslide monitoring means the comparison of landslide characteristics like areal extent, speed of movement, surface topography and soil humidity from different periods in order to assess landslide activity. An ultimate "universal" methodology for this purpose does not exist; every technology has its own advantages and disadvantages. End-users should carefully consider each one to select the methodologies that represent the best compromise between pros and cons, and are best suited for their needs. Besides monitoring technology, there are many factors governing the choice of an Early Warning System (EWS). A people-centred EWS necessarily comprises five key elements: (1) knowledge of the risks; (2) identification, monitoring, analysis and forecasting of the hazards; (3) operational centre; (4) communication or dissemination of alerts and warnings; and (5) local capabilities to respond to the warnings received. The expression "end-to-end warning system" is also used to emphasize that EWSs need to span all steps from hazard detection through to community response. The aim of the present work is to provide guidelines for establishing the different components for landslide EWSs. One of the main deliverables of the EC-FP7 SafeLand project addresses the technical and practical issues related to monitoring and early warning for landslides, and identifies the best technologies available in the context of both hazard assessment and design of EWSs. This deliverable targets the end-users and aims to facilitate the decision process by providing guidelines. For the purpose of sharing the globally accumulated expertise, a screening study was done on 14 EWSs from 8 different countries. On these bases, the report presents a synoptic view of existing monitoring methodologies and early-warning strategies and their applicability for different landslide types, scales and risk management steps. Several comprehensive checklists and toolboxes are also included to support informed decisions. The deliverable was compiled with contributions from experts on landslides, monitoring technologies, remote sensing, and social researchers from 16 European institutions. The deliverable addresses one of the main objectives of the SafeLand project, namely to merge experience and expert judgment and create synergies on European level towards guidelines for early warning and to make these results available to end-users and local stakeholders.

Performance Analysis of a Citywide Real-time Landslide Early Warning System in Korea

NASA Astrophysics Data System (ADS)

Park, Joon-Young; Lee, Seung-Rae; Kang, Sinhang; Lee, Deuk-hwan; Nedumpallile Vasu, Nikhil

2017-04-01

Rainfall-induced landslide has been one of the major disasters in Korea since the beginning of 21st century when the global climate change started to give rise to the growth of the magnitude and frequency of extreme precipitation events. In order to mitigate the increasing damage to properties and loss of lives and to provide an effective tool for public officials to manage the landslide disasters, a real-time landslide early warning system with an advanced concept has been developed by taking into account for Busan, the second largest metropolitan city in Korea, as an operational test-bed. The system provides with warning information based on a five-level alert scheme (Normal, Attention, Watch, Alert, and Emergency) using the forecasted/observed rainfall data or the data obtained from ground monitoring (volumetric water content and matric suction). The alert levels are determined by applying seven different thresholds in a step-wise manner following a decision tree. In the pursuit of improved reliability of an early warning level assigned to a specific area, the system makes assessments repetitively using the thresholds of different theoretical backgrounds including statistical(empirical), physically-based, and mathematical analyses as well as direct measurement-based approaches. By mapping the distribution of the five early warning levels determined independently for each of tens of millions grids covering the entire mountainous area of Busan, the regional-scale system can also provide with the early warning information for a specific local area. The fact that the highest warning level is determined by using a concept of a numerically-modelled potential debris-flow risk is another distinctive feature of the system. This study tested the system performance by applying it for four previous rainy seasons in order to validate the operational applicability. During the rainy seasons of 2009, 2011, and 2014, the number of landslides recorded throughout Busan's territory reached 156, 64, and 37, respectively. In 2016, only three landslides were recorded even though the city experienced a couple of heavy rainfall events during the rainy season. The system performance test results show good agreement with the observation results for the past rainfall events. It seems that the system can also provide with reliable warning information for the future rainfall events.

Preliminary numerical simulations of the 27 February 2010 Chile tsunami: first results and hints in a tsunami early warning perspective

NASA Astrophysics Data System (ADS)

Tinti, S.; Tonini, R.; Armigliato, A.; Zaniboni, F.; Pagnoni, G.; Gallazzi, Sara; Bressan, Lidia

2010-05-01

The tsunamigenic earthquake (M 8.8) that occurred offshore central Chile on 27 February 2010 can be classified as a typical subduction-zone earthquake. The effects of the ensuing tsunami have been devastating along the Chile coasts, and especially between the cities of Valparaiso and Talcahuano, and in the Juan Fernandez islands. The tsunami propagated across the entire Pacific Ocean, hitting with variable intensity almost all the coasts facing the basin. While the far-field propagation was quite well tracked almost in real-time by the warning centres and reasonably well reproduced by the forecast models, the toll of lives and the severity of the damage caused by the tsunami in the near-field occurred with no local alert nor warning and sadly confirms that the protection of the communities placed close to the tsunami sources is still an unresolved problem in the tsunami early warning field. The purpose of this study is two-fold. On one side we perform numerical simulations of the tsunami starting from different earthquake models which we built on the basis of the preliminary seismic parameters (location, magnitude and focal mechanism) made available by the seismological agencies immediately after the event, or retrieved from more detailed and refined studies published online in the following days and weeks. The comparison with the available records of both offshore DART buoys and coastal tide-gauges is used to put some preliminary constraints on the best-fitting fault model. The numerical simulations are performed by means of the finite-difference code UBO-TSUFD, developed and maintained by the Tsunami Research Team of the University of Bologna, Italy, which can solve both the linear and non-linear versions of the shallow-water equations on nested grids. The second purpose of this study is to use the conclusions drawn in the previous part in a tsunami early warning perspective. In the framework of the EU-funded project DEWS (Distant Early Warning System), we will try to give some clues for discussion on the deficiencies of the existing tsunami early warning concepts as regards the warning to the areas which are found close to the tsunami source, and on the strategies that should be followed in the near future in order to make significant progress in the protection and safeguarding of local communities.

Patient attitudes towards remote continuous vital signs monitoring on general surgery wards: An interview study.

PubMed

Downey, C L; Brown, J M; Jayne, D G; Randell, R

2018-06-01

Vital signs monitoring is used to identify deteriorating patients in hospital. The most common tool for vital signs monitoring is an early warning score, although emerging technologies allow for remote, continuous patient monitoring. A number of reviews have examined the impact of continuous monitoring on patient outcomes, but little is known about the patient experience. This study aims to discover what patients think of monitoring in hospital, with a particular emphasis on intermittent early warning scores versus remote continuous monitoring, in order to inform future implementations of continuous monitoring technology. Semi-structured interviews were undertaken with 12 surgical inpatients as part of a study testing a remote continuous monitoring device. All patients were monitored with both an early warning score and the new device. Interviews were audio-recorded, transcribed verbatim and analysed using thematic analysis. Patients can see the value in remote, continuous monitoring, particularly overnight. However, patients appreciate the face-to-face aspect of early warning score monitoring as it allows for reassurance, social interaction, and gives them further opportunity to ask questions about their medical care. Early warning score systems are widely used to facilitate detection of the deteriorating patient. Continuous monitoring technologies may provide added reassurance. However, patients value personal contact with their healthcare professionals and remote monitoring should not replace this. We suggest that remote monitoring is best introduced in a phased manner, and initially as an adjunct to usual care, with careful consideration of the patient experience throughout. Copyright © 2018 Elsevier B.V. All rights reserved.

Developing a drought early warning information system for coastal ecosystems in the Carolinas

Treesearch

Kirsten Lackstrom; Amanda Brennan; Paul Conrads; Lisa Darby; Kirstin Dow; Daniel Tuford

2016-01-01

The National Integrated Drought Information System (NIDIS) and the Carolinas Integrated Sciences and Assessments (CISA), a National Oceanic and Atmospheric Administration (NOAA)- funded Regional Integrated Sciences and Assessments (RISA) program, are partnering to develop and support a Carolinas Drought Early Warning System pilot program. Research and projects focus on...

Comparing Methodologies for Developing an Early Warning System: Classification and Regression Tree Model versus Logistic Regression. REL 2015-077

ERIC Educational Resources Information Center

Koon, Sharon; Petscher, Yaacov

2015-01-01

The purpose of this report was to explicate the use of logistic regression and classification and regression tree (CART) analysis in the development of early warning systems. It was motivated by state education leaders' interest in maintaining high classification accuracy while simultaneously improving practitioner understanding of the rules by…

Early warning signals of regime shifts from cross-scale connectivity of land-cover patterns

Treesearch

Giovanni Zurlini; Kenneth Bruce Jones; Kurt Hans Riitters; Bai-Lian Li; Irene Petrosillo

2014-01-01

Increasing external pressures from human activities and climate change can lead to desertification, affecting the livelihood of more than 25% of the world’s population. Thus, determining proximity to transition to desertification is particularly central for arid regions before they may convert into deserts, and recent research has focused on devising early warning...

On Track for Success: The Use of Early Warning Indicator and Intervention Systems to Build a Grad Nation

ERIC Educational Resources Information Center

Bruce, Mary; Bridgeland, John M.; Fox, Joanna Hornig; Balfanz, Robert

2011-01-01

Over the past decade, schools, districts, and states have become increasingly savvy with data collection and analysis to drive student outcomes. The development and use of Early Warning Indicator and Intervention Systems (EWS) are at the cutting edge of the data- driven, outcomes-focused, high-impact education movement. These systems can increase…

Of Needles and Haystacks: Building an Accurate Statewide Dropout Early Warning System in Wisconsin

ERIC Educational Resources Information Center

Knowles, Jared E.

2015-01-01

The state of Wisconsin has one of the highest four year graduation rates in the nation, but deep disparities among student subgroups remain. To address this the state has created the Wisconsin Dropout Early Warning System (DEWS), a predictive model of student dropout risk for students in grades six through nine. The Wisconsin DEWS is in use…

Detection of the Early Warning Signs of Cancer by Community Pharmacists: An Evaluation of Training on Professional Behavior

ERIC Educational Resources Information Center

Benfield, William R.; And Others

1977-01-01

In a study of 702 pharmacists in 211 communities, an effort was made to determine the effect of a unit of education on the community pharmacist's ability and/or tendency to detect the early warning signs of cancer when manifested by patrons. The success of such a program is shown. (LBH)

Four Signs Your District Is Ready for an Early Warning System. A Discussion Guide

ERIC Educational Resources Information Center

Regional Educational Laboratory Pacific, 2016

2016-01-01

Although high school graduation rates continue to rise in the United States, reaching 81 percent in the 2012-2013 school year (U.S. Department of Education, 2015), dropout remains a pervasive issue for education systems across the nation. In recent years, Early Warning Systems (EWS), which utilize administrative data to identify students at risk…

Toward a national early warning system for forest disturbances using remotely sensed canopy phenology

Treesearch

William W. Hargrove; Joseph P. Spruce; Gerald E. Gasser; Forrest M. Hoffman

2009-01-01

Imagine a national system with the ability to quickly identify forested areas under attack from insects or disease. Such an early warning system might minimize surprises such as the explosion of caterpillars referred to in the quotation above. Moderate resolution (ca. 500m) remote sensing repeated at frequent (ca. weekly) intervals could power such a monitoring system...

Geospatiotemporal data mining in an early warning system for forest threats in the United States

Treesearch

F.M. Hoffman; R.T. Mills; J. Kumar; S.S. Vulli; W.W. Hargrove

2010-01-01

We investigate the potential of geospatiotemporal data mining of multi-year land surface phenology data (250 m Normalized Difference Vegetation Index (NDVI) values derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) in this study) for the conterminous United States as part of an early warning system to identify threats to forest ecosystems. Cluster...

Application of satellite products and hydrological modelling for flood early warning

NASA Astrophysics Data System (ADS)

Koriche, Sifan A.; Rientjes, Tom H. M.

2016-06-01

Floods have caused devastating impacts to the environment and society in Awash River Basin, Ethiopia. Since flooding events are frequent, this marks the need to develop tools for flood early warning. In this study, we propose a satellite based flood index to identify the runoff source areas that largely contribute to extreme runoff production and floods in the basin. Satellite based products used for development of the flood index are CMORPH (Climate Prediction Center MORPHing technique: 0.25° by 0.25°, daily) product for calculation of the Standard Precipitation Index (SPI) and a Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) for calculation of the Topographic Wetness Index (TWI). Other satellite products used in this study are for rainfall-runoff modelling to represent rainfall, potential evapotranspiration, vegetation cover and topography. Results of the study show that assessment of spatial and temporal rainfall variability by satellite products may well serve in flood early warning. Preliminary findings on effectiveness of the flood index developed in this study indicate that the index is well suited for flood early warning. The index combines SPI and TWI, and preliminary results illustrate the spatial distribution of likely runoff source areas that cause floods in flood prone areas.

Demonstration of the Cascadia G‐FAST geodetic earthquake early warning system for the Nisqually, Washington, earthquake

USGS Publications Warehouse

Crowell, Brendan; Schmidt, David; Bodin, Paul; Vidale, John; Gomberg, Joan S.; Hartog, Renate; Kress, Victor; Melbourne, Tim; Santillian, Marcelo; Minson, Sarah E.; Jamison, Dylan

2016-01-01

A prototype earthquake early warning (EEW) system is currently in development in the Pacific Northwest. We have taken a two‐stage approach to EEW: (1) detection and initial characterization using strong‐motion data with the Earthquake Alarm Systems (ElarmS) seismic early warning package and (2) the triggering of geodetic modeling modules using Global Navigation Satellite Systems data that help provide robust estimates of large‐magnitude earthquakes. In this article we demonstrate the performance of the latter, the Geodetic First Approximation of Size and Time (G‐FAST) geodetic early warning system, using simulated displacements for the 2001Mw 6.8 Nisqually earthquake. We test the timing and performance of the two G‐FAST source characterization modules, peak ground displacement scaling, and Centroid Moment Tensor‐driven finite‐fault‐slip modeling under ideal, latent, noisy, and incomplete data conditions. We show good agreement between source parameters computed by G‐FAST with previously published and postprocessed seismic and geodetic results for all test cases and modeling modules, and we discuss the challenges with integration into the U.S. Geological Survey’s ShakeAlert EEW system.

Environmental data analysis and remote sensing for early detection of dengue and malaria

NASA Astrophysics Data System (ADS)

Rahman, Md Z.; Roytman, Leonid; Kadik, Abdelhamid; Rosy, Dilara A.

2014-06-01

Malaria and dengue fever are the two most common mosquito-transmitted diseases, leading to millions of serious illnesses and deaths each year. Because the mosquito vectors are sensitive to environmental conditions such as temperature, precipitation, and humidity, it is possible to map areas currently or imminently at high risk for disease outbreaks using satellite remote sensing. In this paper we propose the development of an operational geospatial system for malaria and dengue fever early warning; this can be done by bringing together geographic information system (GIS) tools, artificial neural networks (ANN) for efficient pattern recognition, the best available ground-based epidemiological and vector ecology data, and current satellite remote sensing capabilities. We use Vegetation Health Indices (VHI) derived from visible and infrared radiances measured by satellite-mounted Advanced Very High Resolution Radiometers (AVHRR) and available weekly at 4-km resolution as one predictor of malaria and dengue fever risk in Bangladesh. As a study area, we focus on Bangladesh where malaria and dengue fever are serious public health threats. The technology developed will, however, be largely portable to other countries in the world and applicable to other disease threats. A malaria and dengue fever early warning system will be a boon to international public health, enabling resources to be focused where they will do the most good for stopping pandemics, and will be an invaluable decision support tool for national security assessment and potential troop deployment in regions susceptible to disease outbreaks.

Performance analysis of landslide early warning systems at regional scale: the EDuMaP method

NASA Astrophysics Data System (ADS)

Piciullo, Luca; Calvello, Michele

2016-04-01

Landslide early warning systems (LEWSs) reduce landslide risk by disseminating timely and meaningful warnings when the level of risk is judged intolerably high. Two categories of LEWSs, can be defined on the basis of their scale of analysis: "local" systems and "regional" systems. LEWSs at regional scale (ReLEWSs) are used to assess the probability of occurrence of landslides over appropriately-defined homogeneous warning zones of relevant extension, typically through the prediction and monitoring of meteorological variables, in order to give generalized warnings to the public. Despite many studies on ReLEWSs, no standard requirements exist for assessing their performance. Empirical evaluations are often carried out by simply analysing the time frames during which significant high-consequence landslides occurred in the test area. Alternatively, the performance evaluation is based on 2x2 contingency tables computed for the joint frequency distribution of landslides and alerts, both considered as dichotomous variables. In all these cases, model performance is assessed neglecting some important aspects which are peculiar to ReLEWSs, among which: the possible occurrence of multiple landslides in the warning zone; the duration of the warnings in relation to the time of occurrence of the landslides; the level of the warning issued in relation to the landslide spatial density in the warning zone; the relative importance system managers attribute to different types of errors. An original approach, called EDuMaP method, is proposed to assess the performance of landslide early warning models operating at regional scale. The method is composed by three main phases: Events analysis, Duration Matrix, Performance analysis. The events analysis phase focuses on the definition of landslide (LEs) and warning events (WEs), which are derived from available landslides and warnings databases according to their spatial and temporal characteristics by means of ten input parameters. The evaluation of time associated with the occurrence of landslide events (LE) in relation to the occurrence of warning events (WE) in their respective classes is a fundamental step to determine the duration matrix elements. On the other hand the classification of LEs and WEs establishes the structure of the duration matrix. Indeed, the number of rows and columns of the matrix is equal to the number of classes defined for the warning and landslide events, respectively. Thus the matrix is not expressed as a 2x2 contingency and LEs and WEs are not expressed as dichotomous variables. The final phase of the method is the evaluation of the duration matrix based on a set of performance criteria assigning a performance meaning to the element of the matrix. To this aim different criteria can be defined, for instance employing an alert classification scheme derived from 2x2 contingency tables or assigning a colour code to the elements of the matrix in relation to their grade of correctness. Finally, performance indicators can be derived from the performance criteria to quantify successes and errors of the early warning models. EDuMaP has been already applied to different real case studies, highlighting the adaptability of the method to analyse the performance of structurally different ReLEWSs.

Capturing early signs of deterioration: the dutch-early-nurse-worry-indicator-score and its value in the Rapid Response System.

PubMed

Douw, Gooske; Huisman-de Waal, Getty; van Zanten, Arthur R H; van der Hoeven, Johannes G; Schoonhoven, Lisette

2017-09-01

To determine the predictive value of individual and combined dutch-early-nurse-worry-indicator-score indicators at various Early Warning Score levels, differentiating between Early Warning Scores reaching the trigger threshold to call a rapid response team and Early Warning Score levels not reaching this point. Dutch-early-nurse-worry-indicator-score comprises nine indicators underlying nurses' 'worry' about a patient's condition. All indicators independently show significant association with unplanned intensive care/high dependency unit admission or unexpected mortality. Prediction of this outcome improved by adding the dutch-early-nurse-worry-indicator-score indicators to an Early Warning Score based on vital signs. An observational cohort study was conducted on three surgical wards in a tertiary university-affiliated teaching hospital. Included were surgical, native-speaking, adult patients. Nurses scored presence of 'worry' and/or dutch-early-nurse-worry-indicator-score indicators every shift or when worried. Vital signs were measured according to the prevailing protocol. Unplanned intensive care/high dependency unit admission or unexpected mortality was the composite endpoint. Percentages of 'worry' and dutch-early-nurse-worry-indicator-score indicators were calculated at various Early Warning Score levels in control and event groups. Entering all dutch-early-nurse-worry-indicator-score indicators in a multiple logistic regression analysis, we calculated a weighted score and calculated sensitivity, specificity, positive predicted value and negative predicted value for each possible total score. In 3522 patients, 102 (2·9%) had an unplanned intensive care/high dependency unit admissions (n = 97) or unexpected mortality (n = 5). Patients with such events and only slightly changed vital signs had significantly higher percentages of 'worry' and dutch-early-nurse-worry-indicator-score indicators expressed than patients in the control group. Increasing number of dutch-early-nurse-worry-indicator-score indicators showed higher positive predictive values. Dutch-early-nurse-worry-indicator-score indicators alert in an early stage of deterioration, before reaching the trigger threshold to call a rapid response team and can improve interdisciplinary communication on surgical wards during regular rounds, and when calling for assistance. Dutch-early-nurse-worry-indicator-score structures communication and recording of signs known to be associated with a decline in a patient's condition and can empower nurses to call assistance on the 'worry' criterion in an early stage of deterioration. © 2016 John Wiley & Sons Ltd.

An integrated information system for the acquisition, management and sharing of environmental data aimed to decision making

NASA Astrophysics Data System (ADS)

La Loggia, Goffredo; Arnone, Elisa; Ciraolo, Giuseppe; Maltese, Antonino; Noto, Leonardo; Pernice, Umberto

2012-09-01

This paper reports the first results of the Project SESAMO - SistEma informativo integrato per l'acquisizione, geStione e condivisione di dati AMbientali per il supportO alle decisioni (Integrated Information System for the acquisition, management and sharing of environmental data aimed to decision making). The main aim of the project is to design and develop an integrated environmental information platform able to provide monitoring services for decision support, integrating data from different environmental monitoring systems (including WSN). This ICT platform, based on a service-oriented architecture (SOA), will be developed to coordinate a wide variety of data acquisition systems, based on heterogeneous technologies and communication protocols, providing different sort of environmental monitoring services. The implementation and validation of the SESAMO platform and its services will involve three specific environmental domains: 1) Urban water losses; 2) Early warning system for rainfall-induced landslides; 3) Precision irrigation planning. Services in the first domain are enabled by a low cost sensors network collecting and transmitting data, in order to allow the pipeline network managers to analyze pressure, velocity and discharge data for reducing water losses in an urban contest. This paper outlines the SESAMO functional and technological structure and then gives a concise description of the service design and development process for the second and third domain. Services in the second domain are enabled by a prototypal early warning system able to identify in near-real time high-risk zones of rainfall-induced landslides. Services in the third domain are aimed to optimize irrigation planning of vineyards depending on plant water stress.

The limits of earthquake early warning: Timeliness of ground motion estimates

USGS Publications Warehouse

Minson, Sarah E.; Meier, Men-Andrin; Baltay, Annemarie S.; Hanks, Thomas C.; Cochran, Elizabeth S.

2018-01-01

The basic physics of earthquakes is such that strong ground motion cannot be expected from an earthquake unless the earthquake itself is very close or has grown to be very large. We use simple seismological relationships to calculate the minimum time that must elapse before such ground motion can be expected at a distance from the earthquake, assuming that the earthquake magnitude is not predictable. Earthquake early warning (EEW) systems are in operation or development for many regions around the world, with the goal of providing enough warning of incoming ground shaking to allow people and automated systems to take protective actions to mitigate losses. However, the question of how much warning time is physically possible for specified levels of ground motion has not been addressed. We consider a zero-latency EEW system to determine possible warning times a user could receive in an ideal case. In this case, the only limitation on warning time is the time required for the earthquake to evolve and the time for strong ground motion to arrive at a user’s location. We find that users who wish to be alerted at lower ground motion thresholds will receive more robust warnings with longer average warning times than users who receive warnings for higher ground motion thresholds. EEW systems have the greatest potential benefit for users willing to take action at relatively low ground motion thresholds, whereas users who set relatively high thresholds for taking action are less likely to receive timely and actionable information.

The limits of earthquake early warning: Timeliness of ground motion estimates

PubMed Central

Hanks, Thomas C.

2018-01-01

The basic physics of earthquakes is such that strong ground motion cannot be expected from an earthquake unless the earthquake itself is very close or has grown to be very large. We use simple seismological relationships to calculate the minimum time that must elapse before such ground motion can be expected at a distance from the earthquake, assuming that the earthquake magnitude is not predictable. Earthquake early warning (EEW) systems are in operation or development for many regions around the world, with the goal of providing enough warning of incoming ground shaking to allow people and automated systems to take protective actions to mitigate losses. However, the question of how much warning time is physically possible for specified levels of ground motion has not been addressed. We consider a zero-latency EEW system to determine possible warning times a user could receive in an ideal case. In this case, the only limitation on warning time is the time required for the earthquake to evolve and the time for strong ground motion to arrive at a user’s location. We find that users who wish to be alerted at lower ground motion thresholds will receive more robust warnings with longer average warning times than users who receive warnings for higher ground motion thresholds. EEW systems have the greatest potential benefit for users willing to take action at relatively low ground motion thresholds, whereas users who set relatively high thresholds for taking action are less likely to receive timely and actionable information. PMID:29750190

Progress and lessons learned from water-quality monitoring networks

USGS Publications Warehouse

Myers, Donna N.; Ludtke, Amy S.

2017-01-01

Stream-quality monitoring networks in the United States were initiated and expanded after passage of successive federal water-pollution control laws from 1948 to 1972. The first networks addressed information gaps on the extent and severity of stream pollution and served as early warning systems for spills. From 1965 to 1972, monitoring networks expanded to evaluate compliance with stream standards, track emerging issues, and assess water-quality status and trends. After 1972, concerns arose regarding the ability of monitoring networks to determine if water quality was getting better or worse and why. As a result, monitoring networks adopted a hydrologic systems approach targeted to key water-quality issues, accounted for human and natural factors affecting water quality, innovated new statistical methods, and introduced geographic information systems and models that predict water quality at unmeasured locations. Despite improvements, national-scale monitoring networks have declined over time. Only about 1%, or 217, of more than 36,000 US Geological Survey monitoring sites sampled from 1975 to 2014 have been operated throughout the four decades since passage of the 1972 Clean Water Act. Efforts to sustain monitoring networks are important because these networks have collected information crucial to the description of water-quality trends over time and are providing information against which to evaluate future trends.

Development of Hydrometeorological Monitoring and Forecasting as AN Essential Component of the Early Flood Warning System:

NASA Astrophysics Data System (ADS)

Manukalo, V.

2012-12-01

Defining issue The river inundations are the most common and destructive natural hazards in Ukraine. Among non-structural flood management and protection measures a creation of the Early Flood Warning System is extremely important to be able to timely recognize dangerous situations in the flood-prone areas. Hydrometeorological information and forecasts are a core importance in this system. The primary factors affecting reliability and a lead - time of forecasts include: accuracy, speed and reliability with which real - time data are collected. The existing individual conception of monitoring and forecasting resulted in a need in reconsideration of the concept of integrated monitoring and forecasting approach - from "sensors to database and forecasters". Result presentation The Project: "Development of Flood Monitoring and Forecasting in the Ukrainian part of the Dniester River Basin" is presented. The project is developed by the Ukrainian Hydrometeorological Service in a conjunction with the Water Management Agency and the Energy Company "Ukrhydroenergo". The implementation of the Project is funded by the Ukrainian Government and the World Bank. The author is nominated as the responsible person for coordination of activity of organizations involved in the Project. The term of the Project implementation: 2012 - 2014. The principal objectives of the Project are: a) designing integrated automatic hydrometeorological measurement network (including using remote sensing technologies); b) hydrometeorological GIS database construction and coupling with electronic maps for flood risk assessment; c) interface-construction classic numerical database -GIS and with satellite images, and radar data collection; d) providing the real-time data dissemination from observation points to forecasting centers; e) developing hydrometeoroogical forecasting methods; f) providing a flood hazards risk assessment for different temporal and spatial scales; g) providing a dissemination of current information, forecasts and warnings to consumers automatically. Besides scientific and technical issues the implementation of these objectives requires solution of a number of organizational issues. Thus, as a result of the increased complexity of types of hydrometeorological data and in order to develop forecasting methods, a reconsideration of meteorological and hydrological measurement networks should be carried out. The "optimal density of measuring networks" is proposed taking into account principal terms: a) minimizing an uncertainty in characterizing the spacial distribution of hydrometeorological parameters; b) minimizing the Total Life Cycle Cost of creation and maintenance of measurement networks. Much attention will be given to training Ukrainian disaster management authorities from the Ministry of Emergencies and the Water Management Agency to identify the flood hazard risk level and to indicate the best protection measures on the basis of continuous monitoring and forecasts of evolution of meteorological and hydrological conditions in the river basin.

Research on Early Warning of Chinese Food Safety Based on Social Physics

NASA Astrophysics Data System (ADS)

Ma, Yonghuan; Niu, Wenyuan; Li, Qianqian

Based on social physics, this paper designs the index system of food safety, builds early warning model of food safety, calculates the degree of food safety, and assesses the state of early warning of 2007 in China. The result shows the degree of food safety is near 0.7 in securer state, belonging to slight emergency. It is much lower in eastern areas of developed regions, belonging to insecure state in the mass. That the food safety is ensured in major grain producing areas, Inner Mongolia, Ningxia and Xinjiang is the prerequisite of realizing the food safety of China. The result also shows four significant indices, grain production capacity, grain circulation order, grain demand and grain supply, which are important indicatio to control food safety.

Early warning signals detect critical impacts of experimental warming.

PubMed

Jarvis, Lauren; McCann, Kevin; Tunney, Tyler; Gellner, Gabriel; Fryxell, John M

2016-09-01

Earth's surface temperatures are projected to increase by ~1-4°C over the next century, threatening the future of global biodiversity and ecosystem stability. While this has fueled major progress in the field of physiological trait responses to warming, it is currently unclear whether routine population monitoring data can be used to predict temperature-induced population collapse. Here, we integrate trait performance theory with that of critical tipping points to test whether early warning signals can be reliably used to anticipate thermally induced extinction events. We find that a model parameterized by experimental growth rates exhibits critical slowing down in the vicinity of an experimentally tested critical threshold, suggesting that dynamical early warning signals may be useful in detecting the potentially precipitous onset of population collapse due to global climate change.

Novel Algorithms Enabling Rapid, Real-Time Earthquake Monitoring and Tsunami Early Warning Worldwide

NASA Astrophysics Data System (ADS)

Lomax, A.; Michelini, A.

2012-12-01

We have introduced recently new methods to determine rapidly the tsunami potential and magnitude of large earthquakes (e.g., Lomax and Michelini, 2009ab, 2011, 2012). To validate these methods we have implemented them along with other new algorithms within the Early-est earthquake monitor at INGV-Rome (http://early-est.rm.ingv.it, http://early-est.alomax.net). Early-est is a lightweight software package for real-time earthquake monitoring (including phase picking, phase association and event detection, location, magnitude determination, first-motion mechanism determination, ...), and for tsunami early warning based on discriminants for earthquake tsunami potential. In a simulation using archived broadband seismograms for the devastating M9, 2011 Tohoku earthquake and tsunami, Early-est determines: the epicenter within 3 min after the event origin time, discriminants showing very high tsunami potential within 5-7 min, and magnitude Mwpd(RT) 9.0-9.2 and a correct shallow-thrusting mechanism within 8 min. Real-time monitoring with Early-est givess similar results for most large earthquakes using currently available, real-time seismogram data. Here we summarize some of the key algorithms within Early-est that enable rapid, real-time earthquake monitoring and tsunami early warning worldwide: >>> FilterPicker - a general purpose, broad-band, phase detector and picker (http://alomax.net/FilterPicker); >>> Robust, simultaneous association and location using a probabilistic, global-search; >>> Period-duration discriminants TdT0 and TdT50Ex for tsunami potential available within 5 min; >>> Mwpd(RT) magnitude for very large earthquakes available within 10 min; >>> Waveform P polarities determined on broad-band displacement traces, focal mechanisms obtained with the HASH program (Hardebeck and Shearer, 2002); >>> SeisGramWeb - a portable-device ready seismogram viewer using web-services in a browser (http://alomax.net/webtools/sgweb/info.html). References (see also: http://alomax.net/pub_list.html): Lomax, A. and A. Michelini (2012), Tsunami early warning within 5 minutes, Pure and Applied Geophysics, 169, nnn-nnn, doi: 10.1007/s00024-012-0512-6. Lomax, A. and A. Michelini (2011), Tsunami early warning using earthquake rupture duration and P-wave dominant period: the importance of length and depth of faulting, Geophys. J. Int., 185, 283-291, doi: 10.1111/j.1365-246X.2010.04916.x. Lomax, A. and A. Michelini (2009b), Tsunami early warning using earthquake rupture duration, Geophys. Res. Lett., 36, L09306, doi:10.1029/2009GL037223. Lomax, A. and A. Michelini (2009a), Mwpd: A Duration-Amplitude Procedure for Rapid Determination of Earthquake Magnitude and Tsunamigenic Potential from P Waveforms, Geophys. J. Int.,176, 200-214, doi:10.1111/j.1365-246X.2008.03974.x

The Early Warning System(EWS) as First Stage to Generate and Develop Shake Map for Bucharest to Deep Vrancea Earthquakes

NASA Astrophysics Data System (ADS)

Marmureanu, G.; Ionescu, C.; Marmureanu, A.; Grecu, B.; Cioflan, C.

2007-12-01

EWS made by NIEP is the first European system for real-time early detection and warning of the seismic waves in case of strong deep earthquakes. EWS uses the time interval (28-32 seconds) between the moment when earthquake is detected by the borehole and surface local accelerometers network installed in the epicenter area (Vrancea) and the arrival time of the seismic waves in the protected area, to deliver timely integrated information in order to enable actions to be taken before a main destructive shaking takes place. Early warning system is viewed as part of an real-time information system that provide rapid information, about an earthquake impeding hazard, to the public and disaster relief organizations before (early warning) and after a strong earthquake (shake map).This product is fitting in with other new product on way of National Institute for Earth Physics, that is, the shake map which is a representation of ground shaking produced by an event and it will be generated automatically following large Vrancea earthquakes. Bucharest City is located in the central part of the Moesian platform (age: Precambrian and Paleozoic) in the Romanian Plain, at about 140 km far from Vrancea area. Above a Cretaceous and a Miocene deposit (with the bottom at roundly 1,400 m of depth), a Pliocene shallow water deposit (~ 700m thick) was settled. The surface geology consists mainly of Quaternary alluvial deposits. Later loess covered these deposits and the two rivers crossing the city (Dambovita and Colentina) carved the present landscape. During the last century Bucharest suffered heavy damage and casualties due to 1940 (Mw = 7.7) and 1977 (Mw = 7.4) Vrancea earthquakes. For example, 32 high tall buildings collapsed and more then 1500 people died during the 1977 event. The innovation with comparable or related systems worldwide is that NIEP will use the EWS to generate a virtual shake map for Bucharest (140 km away of epicentre) immediately after the magnitude is estimated (in 3-4 seconds after the detection in epicentre) and later make corrections by using real time dataflow from each K2 accelerometers installed in Bucharest area, inclusively nonlinear effects. Thus, developing of a near real-time shake map for Bucharest urban area is of highest interest, providing valuable information to the civil defense, decision makers and general public on the area where the ground motion is most severe. EWS made by NIEP can be considered the first stage to generate and develop the shake map for Bucharest to deep Vrancea earthquakes.

The design of composite monitoring scheme for multilevel information in crop early diseases

NASA Astrophysics Data System (ADS)

Zhang, Yan; Meng, Qinglong; Shang, Jing

2018-02-01

It is difficult to monitor and predict the crops early diseases in that the crop disease monitoring is usually monitored by visible light images and the availabilities in early warning are poor at present. The features of common nondestructive testing technology applied to the crop diseases were analyzed in this paper. Based on the changeable characteristics of the virus from the incubation period to the onset period of crop activities, the multilevel composite information monitoring scheme were designed by applying infrared thermal imaging, visible near infrared hyperspectral imaging, micro-imaging technology to the monitoring of multilevel information of crop disease infection comprehensively. The early warning process and key monitoring parameters of compound monitoring scheme are given by taking the temperature, color, structure and texture of crops as the key monitoring characteristics of disease. With overcoming the deficiency that the conventional monitoring scheme is only suitable for the observation of diseases with naked eyes, the monitoring and early warning of the incubation and early onset of the infection crops can be realized by the composite monitoring program as mentioned in this paper.

The TRIDEC Project: Future-Saving FOSS GIS Applications for Tsunami Early Warning

NASA Astrophysics Data System (ADS)

Loewe, P.; Wächter, J.; Hammitzsch, M.

2011-12-01

The Boxing Day Tsunami of 2004 killed over 240,000 people in 14 countries and inundated the affected shorelines with waves reaching heights up to 30m. This natural disaster coincided with an information catastrophy, as potentially life-saving early warning information existed, yet no means were available to deliver it to the communities under imminent threat. Tsunami Early Warning Capabilities have improved in the meantime by continuing development of modular Tsunami Early Warning Systems (TEWS). However, recent tsunami events, like the Chile 2010 and the Tohoku 2011 tsunami demonstrate that the key challenge for ongoing TEWS research on the supranational scale still lies in the timely issuing of reliable early warning messages. Since 2004, the GFZ German Research Centre for Geosciences has built up expertise in the field of TEWS. Within GFZ, the Centre for GeoInformation Technology (CEGIT) has focused its work on the geoinformatics aspects of TEWS in two projects already: The German Indonesian Tsunami Early Warning System (GITEWS) funded by the German Federal Ministry of Education and Research (BMBF) and the Distant Early Warning System (DEWS), a European project funded under the sixth Framework Programme (FP6). These developments are continued in the TRIDEC project (Collaborative, Complex, and Critical Decision Processes in Evolving Crises) funded under the European Union's seventh Framework Programme (FP7). This ongoing project focuses on real-time intelligent information management in Earth management and its long-term application. All TRIDEC developments are based on Free and Open Source Software (FOSS) components and industry standards where-ever possible. Tsunami Early Warning in TRIDEC is also based on mature system architecture models to ensure long-term usability and the flexibility to adapt to future generations of Tsunami sensors. All open source software produced by the project consortium are foreseen to be published on FOSSLAB, a publicly available software repository provided by CEGIT. FOSSLAB serves as a platform for the development of FOSS projects in geospatial context, allowing to save, advance and reuse results achieved in previous and on-going project activities and enabling further development and collaboration with a wide community including scientists, developers, users and stakeholders. FOSSLABs potential to preserve and advance existing best practices for reuse in new scenarios is documented by a first case study: For TEWS education and public outreach a comprehensive approach to generate high resolution globe maps was compiled using GRASS GIS and the POV-Ray rendering software. The task resulted in the merging of isolated technical know-how into publicly available best practices, which had been previously maintained in disparate GIS- and rendering communities. Beyond the scope of TRIDEC, FOSSLAB constitutes an umbrella encompassing several geoinformatics-related activities, such as the documentation of Best Practices for experiences and results while working with Spatial Data Infrastructures (SDI), Geographic Information Systems (GIS), Geomatics, and future spatial processing on Computation Clusters and in Cloud Computing.

Developing effective warning systems: Ongoing research at Ruapehu volcano, New Zealand

NASA Astrophysics Data System (ADS)

Leonard, Graham S.; Johnston, David M.; Paton, Douglas; Christianson, Amy; Becker, Julia; Keys, Harry

2008-05-01

PurposeThis paper examines the unique challenges to volcanic risk management associated with having a ski area on an active volcano. Using a series of simulated eruption/lahar events at Ruapehu volcano, New Zealand, as a context, a model of risk management that integrates warning system design and technology, risk perceptions and the human response is explored. Principal resultsDespite increases in the observed audibility and comprehension of the warning message, recall of public education content, and people's awareness of volcanic risk, a persistent minority of the public continued to demonstrate only moderate awareness of the correct actions to take during a warning and failed to respond effectively. A relationship between level of staff competence and correct public response allowed the level of public response to be used to identify residual risk and additional staff training needs. The quality of staff awareness, action and decision-making has emerged as a critical factor, from detailed staff and public interviews and from exercise observations. Staff actions are especially important for mobilising correct public response at Ruapehu ski areas due to the transient nature of the visitor population. Introduction of education material and staff training strategies that included the development of emergency decision-making competencies improved knowledge of correct actions, and increased the proportion of people moving out of harm's way during blind tests. Major conclusionsWarning effectiveness is a function of more than good hazard knowledge and the generation and notification of an early warning message. For warning systems to be effective, these factors must be complemented by accurate knowledge of risk and risk management actions. By combining the Ruapehu findings with those of other warning system studies in New Zealand, and internationally, a practical five-step model for effective early warning systems is discussed. These steps must be based upon sound and regularly updated underpinning science and be tied to formal effectiveness evaluation, which is fed back into system improvements. The model presented emphasises human considerations, the development of which arguably require even more effort than the hardware components of early warning systems.

Identifying and tracking attacks on networks: C3I displays and related technologies

NASA Astrophysics Data System (ADS)

Manes, Gavin W.; Dawkins, J.; Shenoi, Sujeet; Hale, John C.

2003-09-01

Converged network security is extremely challenging for several reasons; expanded system and technology perimeters, unexpected feature interaction, and complex interfaces all conspire to provide hackers with greater opportunities for compromising large networks. Preventive security services and architectures are essential, but in and of themselves do not eliminate all threat of compromise. Attack management systems mitigate this residual risk by facilitating incident detection, analysis and response. There are a wealth of attack detection and response tools for IP networks, but a dearth of such tools for wireless and public telephone networks. Moreover, methodologies and formalisms have yet to be identified that can yield a common model for vulnerabilities and attacks in converged networks. A comprehensive attack management system must coordinate detection tools for converged networks, derive fully-integrated attack and network models, perform vulnerability and multi-stage attack analysis, support large-scale attack visualization, and orchestrate strategic responses to cyber attacks that cross network boundaries. We present an architecture that embodies these principles for attack management. The attack management system described engages a suite of detection tools for various networking domains, feeding real-time attack data to a comprehensive modeling, analysis and visualization subsystem. The resulting early warning system not only provides network administrators with a heads-up cockpit display of their entire network, it also supports guided response and predictive capabilities for multi-stage attacks in converged networks.

Wireless sensor networks for heritage object deformation detection and tracking algorithm.

PubMed

Xie, Zhijun; Huang, Guangyan; Zarei, Roozbeh; He, Jing; Zhang, Yanchun; Ye, Hongwu

2014-10-31

Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection.

Dynamical Response of Networks Under External Perturbations: Exact Results

NASA Astrophysics Data System (ADS)

Chinellato, David D.; Epstein, Irving R.; Braha, Dan; Bar-Yam, Yaneer; de Aguiar, Marcus A. M.

2015-04-01

We give exact statistical distributions for the dynamic response of influence networks subjected to external perturbations. We consider networks whose nodes have two internal states labeled 0 and 1. We let nodes be frozen in state 0, in state 1, and the remaining nodes change by adopting the state of a connected node with a fixed probability per time step. The frozen nodes can be interpreted as external perturbations to the subnetwork of free nodes. Analytically extending and to be smaller than 1 enables modeling the case of weak coupling. We solve the dynamical equations exactly for fully connected networks, obtaining the equilibrium distribution, transition probabilities between any two states and the characteristic time to equilibration. Our exact results are excellent approximations for other topologies, including random, regular lattice, scale-free and small world networks, when the numbers of fixed nodes are adjusted to take account of the effect of topology on coupling to the environment. This model can describe a variety of complex systems, from magnetic spins to social networks to population genetics, and was recently applied as a framework for early warning signals for real-world self-organized economic market crises.

Wireless Sensor Networks for Heritage Object Deformation Detection and Tracking Algorithm

PubMed Central

Xie, Zhijun; Huang, Guangyan; Zarei, Roozbeh; He, Jing; Zhang, Yanchun; Ye, Hongwu

2014-01-01

Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection. PMID:25365458

Red warning for air pollution in China: Exploring residents' perceptions of the first two red warnings in Beijing.

PubMed

Zhao, Hanping; Wang, Fangping; Niu, Chence; Wang, Han; Zhang, Xiaoxue

2018-02-01

Air pollution early warnings have been issued in China to mitigate the effects of high pollution days. Public perceptions and views about early warning signals can affect individual behaviors and play a major role in the public's response to air pollution risks. This study examined public attitudes and responses to the first two red warnings for air pollution in Beijing in 2015. An online survey was sent out, and 664 respondents (response rate = 90%) provided their perspectives on the red warnings. Descriptive statistics, sign tests and binary logit models were used to analyze the data. More than half of the respondents reported that their life and work were affected by the red warning in December 2015. In contrast to their perceptions about the second red warning period, the public thought that the first red warning should have been issued earlier and that the number of consecutive days of warnings should have been reduced. The respondents also recommended that instead of reducing the number of red warnings, the red warning emergency measures should be adjusted. Specifically, the public preferred the installation of air purifiers in schools rather than closing schools and strengthening road flushing and dust pollution controls over restrictions on driving. Data analyses were conducted to examine the affected groups and different groups' perceptions of the necessity of implementing emergency measures. The results indicated that men and more educated respondents were more likely to be affected by driving limitations, and men were less supportive of these limitations. The age and education of respondents were significantly negatively associated with the opinion that schools should be closed, whereas wealthier respondents were more supportive of school closings. The finding of a negative attitude among the public toward the first two red warnings may be used to help local governments modify protective measures and pollution mitigation initiatives to increase acceptance. Copyright © 2017 Elsevier Inc. All rights reserved.

Tsunami early warning system for the western coast of the Black Sea

NASA Astrophysics Data System (ADS)

Ionescu, Constantin; Partheniu, Raluca; Cioflan, Carmen; Constantin, Angela; Danet, Anton; Diaconescu, Mihai; Ghica, Daniela; Grecu, Bogdan; Manea, Liviu; Marmureanu, Alexandru; Moldovan, Iren; Neagoe, Cristian; Radulian, Mircea; Raileanu, Victor; Verdes, Ioan

2014-05-01

The Black Sea area is liable to tsunamis generation and the statistics show that more than twenty tsunamis have been observed in the past. The last tsunami was observed on 31st of March 1901 in the western part of the Black Sea, in the Shabla area. An earthquake of magnitude generated at a depth of 15 km below the sea level , triggered tsunami waves of 5 m height and material losses as well. The oldest tsunami ever recorded close to the Romanian shore-line dates from year 104. This paper emphasises the participation of The National Institute for Earth Physics (NIEP) to the development of a tsunami warning system for the western cost of the Black Sea. In collaboration with the National Institute for Marine Geology and Geoecology (GeoEcoMar), the Institute of Oceanology and the Geological Institute, the last two belonging to the Bulgarian Academy of Science, NIEP has participated as partner, to the cross-border project "Set-up and implementation of key core components of a regional early-warning system for marine geohazards of risk to the Romanian-Bulgarian Black Sea coastal area - MARINEGEOHAZARDS", coordinated by GeoEcoMar. The main purpose of the project was the implementation of an integrated early-warning system accompanied by a common decision-support tool, and enhancement of regional technical capability, for the adequate detection, assessment, forecasting and rapid notification of natural marine geohazards for the Romanian-Bulgarian Black Sea cross-border area. In the last years, NIEP has increased its interest on the marine related hazards, such as tsunamis and, in collaboration with other institutions of Romania, is acting to strengthen the cooperation and data exchanges with institutions from the Black Sea surrounding countries which already have tsunami monitoring infrastructures. In this respect, NIEP has developed a coastal network for marine seismicity, by installing three new seismic stations in the coastal area of the Black Sea, Sea Level Sensors, Radar and Pressure sensors, Meteorological and GNSS stations at every site, providing tide gauges and seismic data exchange with the Black Sea countries. At the same time, the Tsunami Analysis Tool (TAT) software, for inundation modelling, along with it's RedPhone application, were also installed at the National Data Centre in Magurele city, and also at Dobrogea Seismic Observatory in the city of Eforie Nord, close to the Black Sea shore.

Evaluation of Intersection Collision Warning Systems in Minnesota

DOT National Transportation Integrated Search

2017-10-01

The Minnesota Department of Transportation (MnDOT) is investing significant resources in intersection collision warning systems (ICWS) based on early indications of effectiveness. However, the effectiveness is not well documented, and negative change...

Early Warning System for reducing disaster risk: the technological platform DEWETRA for the Republic of Serbia

NASA Astrophysics Data System (ADS)

Massabo, Marco; Molini, Luca; Kostic, Bojan; Campanella, Paolo; Stevanovic, Slavimir

2015-04-01

Disaster risk reduction has long been recognized for its role in mitigating the negative environmental, social and economic impacts of natural hazards. Flood Early Warning System is a disaster risk reduction measure based on the capacities of institutions to observe and predict extreme hydro-meteorological events and to disseminate timely and meaningful warning information; it is furthermore based on the capacities of individuals, communities and organizations to prepare and to act appropriately and in sufficient time to reduce the possibility of harm or loss. An operational definition of an Early Warning System has been suggested by ISDR - UN Office for DRR [15 January 2009]: "EWS is the set of capacities needed to generate and disseminate timely and meaningful warning information to enable individuals, communities and organizations threatened by a hazard to prepare and to act appropriately and in sufficient time to reduce the possibility of harm or loss.". ISDR continues by commenting that a people-centered early warning system necessarily comprises four key elements: 1-knowledge of the risks; 2-monitoring, analysis and forecasting of the hazards; 3-communication or dissemination of alerts and warnings; and 4- local capabilities to respond to the warnings received." The technological platform DEWETRA supports the strengthening of the first three key elements of EWS suggested by ISDR definition, hence to improve the capacities to build real-time risk scenarios and to inform and warn the population in advance The technological platform DEWETRA has been implemented for the Republic of Serbia. DEWETRA is a real time-integrate system that supports decision makers for risk forecasting and monitoring and for distributing warnings to end-user and to the general public. The system is based on the rapid availability of different data that helps to establish up-to-date and reliable risk scenarios. The integration of all relevant data for risk management significantly increases the value of available information and the level of knowledge of forecasters and disaster managers. Different data, forecast and monitoring products, which are generated by different national and international institution and organizations, can be visualized and processed in real-time within the platform. DEWETRA is a web application ensuring the capillary distribution of information among institutions. The system is used as an infrastructure for exchanging and sharing data, procedures, models and expertise among the Sector of Emergency Management (SEM), the Republic Hydro-Meteorological Service of Serbia (RHMSS) and the Serbian Public Water Companies (PWCs): Serbia Waters, Vojvodina Waters and Belgrade Waters.

National High School Center Early Warning System Tool v2.0: Technical Manual

ERIC Educational Resources Information Center

National High School Center, 2011

2011-01-01

The Early Warning System (EWS) Tool v2.0 is a Microsoft Excel-based tool developed by the National High School Center at the American Institutes for Research in collaboration with Matrix Knowledge Group. The tool enables schools, districts, and states to identify students who may be at risk of dropping out of high school and to monitor these…

Bistatic Space Borne Radar for Early Warning

DTIC Science & Technology

2006-08-01

bandwidth of about 1.2 MHz. hr ht RX TX z x α α α α αr αt y R30 R10 R31 R11 vRx vTx P Bistatic Space Borne Radar for Early Warning...B V R == (12) where VRX is the receiver velocity and BA is the Doppler chirp bandwidth defined by equation (5). The time necessary to obtain

Does the Computer-Assisted Remedial Mathematics Program at Kearny High School Lead to Improved Scores on the N.J. Early Warning Test?

ERIC Educational Resources Information Center

Schalago-Schirm, Cynthia

Eighth-grade students in New Jersey take the Early Warning Test (EWT), which involves reading, writing, and mathematics. Students with EWT scores below the state level of competency take a remedial mathematics course that provides students with computer-assisted instruction (2 days per week) as well as regular classroom instruction (3 days per…

Learning by Teaching: Undergraduate Engineering Students Improving a Community's Response Capability to an Early Warning System

ERIC Educational Resources Information Center

Suvannatsiri, Ratchasak; Santichaianant, Kitidech; Murphy, Elizabeth

2015-01-01

This paper reports on a project in which students designed, constructed and tested a model of an existing early warning system with simulation of debris flow in a context of a landslide. Students also assessed rural community members' knowledge of this system and subsequently taught them to estimate the time needed for evacuation of the community…