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.

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.

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.

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.

A Neutral Network based Early Eathquake Warning model in California region

NASA Astrophysics Data System (ADS)

Xiao, H.; MacAyeal, D. R.

2016-12-01

Early Earthquake Warning systems could reduce loss of lives and other economic impact resulted from natural disaster or man-made calamity. Current systems could be further enhanced by neutral network method. A 3 layer neural network model combined with onsite method was deployed in this paper to improve the recognition time and detection time for large scale earthquakes.The 3 layer neutral network early earthquake warning model adopted the vector feature design for sample events happened within 150 km radius of the epicenters. Dataset used in this paper contained both destructive events and small scale events. All the data was extracted from IRIS database to properly train the model. In the training process, backpropagation algorithm was used to adjust the weight matrices and bias matrices during each iteration. The information in all three channels of the seismometers served as the source in this model. Through designed tests, it was indicated that this model could identify approximately 90 percent of the events' scale correctly. And the early detection could provide informative evidence for public authorities to make further decisions. This indicated that neutral network model could have the potential to strengthen current early warning system, since the onsite method may greatly reduce the responding time and save more lives in such disasters.

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.

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.

Establishment of turbidity forecasting model and early-warning system for source water turbidity management using back-propagation artificial neural network algorithm and probability analysis.

PubMed

Yang, Tsung-Ming; Fan, Shu-Kai; Fan, Chihhao; Hsu, Nien-Sheng

2014-08-01

The purpose of this study is to establish a turbidity forecasting model as well as an early-warning system for turbidity management using rainfall records as the input variables. The Taipei Water Source Domain was employed as the study area, and ANOVA analysis showed that the accumulative rainfall records of 1-day Ping-lin, 2-day Ping-lin, 2-day Fei-tsui, 2-day Shi-san-gu, 2-day Tai-pin and 2-day Tong-hou were the six most significant parameters for downstream turbidity development. The artificial neural network model was developed and proven capable of predicting the turbidity concentration in the investigated catchment downstream area. The observed and model-calculated turbidity data were applied to developing the turbidity early-warning system. Using a previously determined turbidity as the threshold, the rainfall criterion, above which the downstream turbidity would possibly exceed this respective threshold turbidity, for the investigated rain gauge stations was determined. An exemplary illustration demonstrated the effectiveness of the proposed turbidity early-warning system as a precautionary alarm of possible significant increase of downstream turbidity. This study is the first report of the establishment of the turbidity early-warning system. Hopefully, this system can be applied to source water turbidity forecasting during storm events and provide a useful reference for subsequent adjustment of drinking water treatment operation.

Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil.

PubMed

Lowe, Rachel; Coelho, Caio As; Barcellos, Christovam; Carvalho, Marilia Sá; Catão, Rafael De Castro; Coelho, Giovanini E; Ramalho, Walter Massa; Bailey, Trevor C; Stephenson, David B; Rodó, Xavier

2016-02-24

Recently, a prototype dengue early warning system was developed to produce probabilistic forecasts of dengue risk three months ahead of the 2014 World Cup in Brazil. Here, we evaluate the categorical dengue forecasts across all microregions in Brazil, using dengue cases reported in June 2014 to validate the model. We also compare the forecast model framework to a null model, based on seasonal averages of previously observed dengue incidence. When considering the ability of the two models to predict high dengue risk across Brazil, the forecast model produced more hits and fewer missed events than the null model, with a hit rate of 57% for the forecast model compared to 33% for the null model. This early warning model framework may be useful to public health services, not only ahead of mass gatherings, but also before the peak dengue season each year, to control potentially explosive dengue epidemics.

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.

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.

[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.

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

Evaluating probabilistic dengue risk forecasts from a prototype early warning system for Brazil

PubMed Central

Lowe, Rachel; Coelho, Caio AS; Barcellos, Christovam; Carvalho, Marilia Sá; Catão, Rafael De Castro; Coelho, Giovanini E; Ramalho, Walter Massa; Bailey, Trevor C; Stephenson, David B; Rodó, Xavier

2016-01-01

Recently, a prototype dengue early warning system was developed to produce probabilistic forecasts of dengue risk three months ahead of the 2014 World Cup in Brazil. Here, we evaluate the categorical dengue forecasts across all microregions in Brazil, using dengue cases reported in June 2014 to validate the model. We also compare the forecast model framework to a null model, based on seasonal averages of previously observed dengue incidence. When considering the ability of the two models to predict high dengue risk across Brazil, the forecast model produced more hits and fewer missed events than the null model, with a hit rate of 57% for the forecast model compared to 33% for the null model. This early warning model framework may be useful to public health services, not only ahead of mass gatherings, but also before the peak dengue season each year, to control potentially explosive dengue epidemics. DOI: http://dx.doi.org/10.7554/eLife.11285.001 PMID:26910315

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.

An early warning indicator for atmospheric blocking events using transfer operators

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

Tantet, Alexis, E-mail: a.j.j.tantet@uu.nl; Burgt, Fiona R. van der; Dijkstra, Henk A.

The existence of persistent midlatitude atmospheric flow regimes with time-scales larger than 5–10 days and indications of preferred transitions between them motivates to develop early warning indicators for such regime transitions. In this paper, we use a hemispheric barotropic model together with estimates of transfer operators on a reduced phase space to develop an early warning indicator of the zonal to blocked flow transition in this model. It is shown that the spectrum of the transfer operators can be used to study the slow dynamics of the flow as well as the non-Markovian character of the reduction. The slowest motionsmore » are thereby found to have time scales of three to six weeks and to be associated with meta-stable regimes (and their transitions) which can be detected as almost-invariant sets of the transfer operator. From the energy budget of the model, we are able to explain the meta-stability of the regimes and the existence of preferred transition paths. Even though the model is highly simplified, the skill of the early warning indicator is promising, suggesting that the transfer operator approach can be used in parallel to an operational deterministic model for stochastic prediction or to assess forecast uncertainty.« less

[An early warning method of cucumber downy mildew in solar greenhouse based on canopy temperature and humidity modeling].

PubMed

Wang, Hui; Li, Mei-lan; Xu, Jian-ping; Chen, Mei-xiang; Li, Wen-yong; Li, Ming

2015-10-01

The greenhouse environmental parameters can be used to establish greenhouse nirco-climate model, which can combine with disease model for early warning, with aim of ecological controlling diseases to reduce pesticide usage, and protecting greenhouse ecological environment to ensure the agricultural product quality safety. Greenhouse canopy leaf temperature and air relative humidity, models were established using energy balance and moisture balance principle inside the greenhouse. The leaf temperature model considered radiation heat transfer between the greenhouse crops, wall, soil and cover, plus the heat exchange caused by indoor net radiation and crop transpiration. Furthermore, the water dynamic balance in the greenhouse including leaf transpiration, soil evaporation, cover and leaf water vapor condensation, was considered to develop a relative humidity model. The primary infection and latent period warning models for cucumber downy mildew (Pseudoperonospora cubensis) were validated using the results of the leaf temperature and relative humidity model, and then the estimated disease occurrence date of cucumber downy mildew was compared with actual disease occurrence date of field observation. Finally, the results were verified by the measured temperature and humidity data of September and October, 2014. The results showed that the root mean square deviations (RMSDs) of the measured and estimated leaf temperature were 0.016 and 0.024 °C, and the RMSDs of the measured and estimated air relative humidity were 0.15% and 0.13%, respectively. Combining the result of estimated temperature and humidity models, a cucumber disease early warning system was established to forecast the date of disease occurrence, which met with the real date. Thus, this work could provide the micro-environment data for the early warning system of cucumber diseases in solar greenhouses.

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.

Development of Laboratory Model Ecosystems as Early Warning Elements of Environmental Pollution

DTIC Science & Technology

1974-12-01

AD-AOll 851 DEVELOPMENT OF LABORATORY MODEL ECOSYSTEMS AS EARLY WARNING ELEMENTS OF ENVIRONMENTAL POLLUTION Robert L. Metcalf... ENVIRONMENTAL POLLUTION Robert L. Metcalf, Ph. D. University of Illinois Urbana-Champaign, Illinois INTRODUCTION Problems of environmental pollution with...house dust is unsafe to breathe (Ewing and Pearson, 1974). Most of the source of our concern about environmental pollution by trace substances relates

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

A holistic approach to SIM platform and its application to early-warning satellite system

NASA Astrophysics Data System (ADS)

Sun, Fuyu; Zhou, Jianping; Xu, Zheyao

2018-01-01

This study proposes a new simulation platform named Simulation Integrated Management (SIM) for the analysis of parallel and distributed systems. The platform eases the process of designing and testing both applications and architectures. The main characteristics of SIM are flexibility, scalability, and expandability. To improve the efficiency of project development, new models of early-warning satellite system were designed based on the SIM platform. Finally, through a series of experiments, the correctness of SIM platform and the aforementioned early-warning satellite models was validated, and the systematical analyses for the orbital determination precision of the ballistic missile during its entire flight process were presented, as well as the deviation of the launch/landing point. Furthermore, the causes of deviation and prevention methods will be fully explained. The simulation platform and the models will lay the foundations for further validations of autonomy technology in space attack-defense architecture research.

Changing skewness: an early warning signal of regime shifts in ecosystems.

PubMed

Guttal, Vishwesha; Jayaprakash, Ciriyam

2008-05-01

Empirical evidence for large-scale abrupt changes in ecosystems such as lakes and vegetation of semi-arid regions is growing. Such changes, called regime shifts, can lead to degradation of ecological services. We study simple ecological models that show a catastrophic transition as a control parameter is varied and propose a novel early warning signal that exploits two ubiquitous features of ecological systems: nonlinearity and large external fluctuations. Either reduced resilience or increased external fluctuations can tip ecosystems to an alternative stable state. It is shown that changes in asymmetry in the distribution of time series data, quantified by changing skewness, is a model-independent and reliable early warning signal for both routes to regime shifts. Furthermore, using model simulations that mimic field measurements and a simple analysis of real data from abrupt climate change in the Sahara, we study the feasibility of skewness calculations using data available from routine monitoring.

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.

Operational Tsunami Modelling with TsunAWI for the German-Indonesian Tsunami Early Warning System: Recent Developments

NASA Astrophysics Data System (ADS)

Rakowsky, N.; Harig, S.; Androsov, A.; Fuchs, A.; Immerz, A.; Schröter, J.; Hiller, W.

2012-04-01

Starting in 2005, the GITEWS project (German-Indonesian Tsunami Early Warning System) established from scratch a fully operational tsunami warning system at BMKG in Jakarta. Numerical simulations of prototypic tsunami scenarios play a decisive role in a priori risk assessment for coastal regions and in the early warning process itself. Repositories with currently 3470 regional tsunami scenarios for GITEWS and 1780 Indian Ocean wide scenarios in support of Indonesia as a Regional Tsunami Service Provider (RTSP) were computed with the non-linear shallow water modell TsunAWI. It is based on a finite element discretisation, employs unstructured grids with high resolution along the coast and includes inundation. This contribution gives an overview on the model itself, the enhancement of the model physics, and the experiences gained during the process of establishing an operational code suited for thousands of model runs. Technical aspects like computation time, disk space needed for each scenario in the repository, or post processing techniques have a much larger impact than they had in the beginning when TsunAWI started as a research code. Of course, careful testing on artificial benchmarks and real events remains essential, but furthermore, quality control for the large number of scenarios becomes an important issue.

On the importance of risk knowledge for an end-to-end tsunami early warning system

NASA Astrophysics Data System (ADS)

Post, Joachim; Strunz, Günter; Riedlinger, Torsten; Mück, Matthias; Wegscheider, Stephanie; Zosseder, Kai; Steinmetz, Tilmann; Gebert, Niklas; Anwar, Herryal

2010-05-01

Warning systems commonly use information provided by networks of sensors able to monitor and detect impending disasters, aggregate and condense these information to provide reliable information to a decision maker whether to warn or not, disseminates the warning message and provide this information to people at risk. Ultimate aim is to enable those in danger to make decisions (e.g. initiate protective actions for buildings) and to take action to safe their lives. This involves very complex issues when considering all four elements of early warning systems (UNISDR-PPEW), namely (1) risk knowledge, (2) monitoring and warning service, (3) dissemination and communication, (4) response capability with the ultimate aim to gain as much time as possible to empower individuals and communities to act in an appropriate manner to reduce injury, loss of life, damage to property and the environment and loss of livelihoods. Commonly most warning systems feature strengths and main attention on the technical/structural dimension (monitoring & warning service, dissemination tools) with weaknesses and less attention on social/cultural dimension (e.g. human response capabilities, defined warning chain to and knowing what to do by the people). Also, the use of risk knowledge in early warning most often is treated in a theoretical manner (knowing that it is somehow important), yet less in an operational, practical sense. Risk assessments and risk maps help to motivate people, prioritise early warning system needs and guide preparations for response and disaster prevention activities. Beyond this risk knowledge can be seen as a tie between national level early warning and community level reaction schemes. This presentation focuses on results, key findings and lessons-learnt related to tsunami risk assessment in the context of early warning within the GITEWS (German-Indonesian Tsunami Early Warning) project. Here a novel methodology reflecting risk information needs in the early warning context has been worked out. The generated results contribute significantly in the fields of (1) warning decision and warning levels, (2) warning dissemination and warning message content, (3) early warning chain planning, (4) increasing response capabilities and protective systems, (5) emergency relief and (6) enhancing communities' awareness and preparedness towards tsunami threats. Additionally examples will be given on the potentials of an operational use of risk information in early warning systems as first experiences exist for the tsunami early warning center in Jakarta, Indonesia. Beside this the importance of linking national level early warning information with tsunami risk information available at the local level (e.g. linking warning message information on expected intensity with respective tsunami hazard zone maps at community level for effective evacuation) will be demonstrated through experiences gained in three pilot areas in Indonesia. The presentation seeks to provide new insights on benefits using risk information in early warning and will provide further evidence that practical use of risk information is an important and indispensable component of end-to-end early warning.

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.

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

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…

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…

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.

Current NASA Earth Remote Sensing Observations

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey C.; Sprigg, William A.; Huete, Alfredo; Pejanovic, Goran; Nickovic, Slobodan; Ponce-Campos, Guillermo; Krapfl, Heide; Budge, Amy; Zelicoff, Alan; Myers, Orrin;

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.

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.

The Lake Victoria Intense Storm Early Warning System (VIEWS)

NASA Astrophysics Data System (ADS)

Thiery, Wim; Gudmundsson, Lukas; Bedka, Kristopher; Semazzi, Fredrick; Lhermitte, Stef; Willems, Patrick; van Lipzig, Nicole; Seneviratne, Sonia I.

2017-04-01

Weather extremes have harmful impacts on communities around Lake Victoria in East Africa. Every year, intense nighttime thunderstorms cause numerous boating accidents on the lake, resulting in thousands of deaths among fishermen. Operational storm warning systems are therefore crucial. Here we complement ongoing early warning efforts based on NWP, by presenting a new satellite data-driven storm prediction system, the prototype Lake Victoria Intense storm Early Warning System (VIEWS). VIEWS derives predictability from the correlation between afternoon land storm activity and nighttime storm intensity on Lake Victoria, and relies on logistic regression techniques to forecast extreme thunderstorms from satellite observations. Evaluation of the statistical model reveals that predictive power is high and independent of the input dataset. We then optimise the configuration and show that also false alarms contain valuable information. Our results suggest that regression-based models that are motivated through process understanding have the potential to reduce the vulnerability of local fishing communities around Lake Victoria. The experimental prediction system is publicly available under the MIT licence at http://github.com/wthiery/VIEWS.

Early warnings of hazardous thunderstorms over Lake Victoria

NASA Astrophysics Data System (ADS)

Thiery, Wim; Gudmundsson, Lukas; Bedka, Kristopher; Semazzi, Fredrick H. M.; Lhermitte, Stef; Willems, Patrick; van Lipzig, Nicole P. M.; Seneviratne, Sonia I.

2017-07-01

Weather extremes have harmful impacts on communities around Lake Victoria in East Africa. Every year, intense nighttime thunderstorms cause numerous boating accidents on the lake, resulting in thousands of deaths among fishermen. Operational storm warning systems are therefore crucial. Here we complement ongoing early warning efforts based on numerical weather prediction, by presenting a new satellite data-driven storm prediction system, the prototype Lake Victoria Intense storm Early Warning System (VIEWS). VIEWS derives predictability from the correlation between afternoon land storm activity and nighttime storm intensity on Lake Victoria, and relies on logistic regression techniques to forecast extreme thunderstorms from satellite observations. Evaluation of the statistical model reveals that predictive power is high and independent of the type of input dataset. We then optimise the configuration and show that false alarms also contain valuable information. Our results suggest that regression-based models that are motivated through process understanding have the potential to reduce the vulnerability of local fishing communities around Lake Victoria. The experimental prediction system is publicly available under the MIT licence at http://github.com/wthiery/VIEWS.

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.

Earthquake Early Warning Beta Users: Java, Modeling, and Mobile Apps

NASA Astrophysics Data System (ADS)

Strauss, J. A.; Vinci, M.; Steele, W. P.; Allen, R. M.; Hellweg, M.

2014-12-01

Earthquake Early Warning (EEW) is a system that can provide a few to tens of seconds warning prior to ground shaking at a user's location. The goal and purpose of such a system is to reduce, or minimize, the damage, costs, and casualties resulting from an earthquake. A demonstration earthquake early warning system (ShakeAlert) is undergoing testing in the United States by the UC Berkeley Seismological Laboratory, Caltech, ETH Zurich, University of Washington, the USGS, and beta users in California and the Pacific Northwest. The beta users receive earthquake information very rapidly in real-time and are providing feedback on their experiences of performance and potential uses within their organization. Beta user interactions allow the ShakeAlert team to discern: which alert delivery options are most effective, what changes would make the UserDisplay more useful in a pre-disaster situation, and most importantly, what actions users plan to take for various scenarios. Actions could include: personal safety approaches, such as drop cover, and hold on; automated processes and procedures, such as opening elevator or fire stations doors; or situational awareness. Users are beginning to determine which policy and technological changes may need to be enacted, and funding requirements to implement their automated controls. The use of models and mobile apps are beginning to augment the basic Java desktop applet. Modeling allows beta users to test their early warning responses against various scenarios without having to wait for a real event. Mobile apps are also changing the possible response landscape, providing other avenues for people to receive information. All of these combine to improve business continuity and resiliency.

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.

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…

Streamflow forecasts from WRF precipitation for flood early warning in mountain tropical areas

NASA Astrophysics Data System (ADS)

Rogelis, María Carolina; Werner, Micha

2018-02-01

Numerical weather prediction (NWP) models are fundamental to extend forecast lead times beyond the concentration time of a watershed. Particularly for flash flood forecasting in tropical mountainous watersheds, forecast precipitation is required to provide timely warnings. This paper aims to assess the potential of NWP for flood early warning purposes, and the possible improvement that bias correction can provide, in a tropical mountainous area. The paper focuses on the comparison of streamflows obtained from the post-processed precipitation forecasts, particularly the comparison of ensemble forecasts and their potential in providing skilful flood forecasts. The Weather Research and Forecasting (WRF) model is used to produce precipitation forecasts that are post-processed and used to drive a hydrologic model. Discharge forecasts obtained from the hydrological model are used to assess the skill of the WRF model. The results show that post-processed WRF precipitation adds value to the flood early warning system when compared to zero-precipitation forecasts, although the precipitation forecast used in this analysis showed little added value when compared to climatology. However, the reduction of biases obtained from the post-processed ensembles show the potential of this method and model to provide usable precipitation forecasts in tropical mountainous watersheds. The need for more detailed evaluation of the WRF model in the study area is highlighted, particularly the identification of the most suitable parameterisation, due to the inability of the model to adequately represent the convective precipitation found in the study area.

Cascade reservoir flood control operation based on risk grading and warning in the Upper Yellow River

NASA Astrophysics Data System (ADS)

Xuejiao, M.; Chang, J.; Wang, Y.

2017-12-01

Flood risk reduction with non-engineering measures has become the main idea for flood management. It is more effective for flood risk management to take various non-engineering measures. In this paper, a flood control operation model for cascade reservoirs in the Upper Yellow River was proposed to lower the flood risk of the water system with multi-reservoir by combining the reservoir flood control operation (RFCO) and flood early warning together. Specifically, a discharge control chart was employed to build the joint RFCO simulation model for cascade reservoirs in the Upper Yellow River. And entropy-weighted fuzzy comprehensive evaluation method was adopted to establish a multi-factorial risk assessment model for flood warning grade. Furthermore, after determining the implementing mode of countermeasures with future inflow, an intelligent optimization algorithm was used to solve the optimization model for applicable water release scheme. In addition, another model without any countermeasure was set to be a comparative experiment. The results show that the model developed in this paper can further decrease the flood risk of water system with cascade reservoirs. It provides a new approach to flood risk management by coupling flood control operation and flood early warning of cascade reservoirs.

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.

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

Dynamic linear models using the Kalman filter for early detection and early warning of malaria outbreaks

NASA Astrophysics Data System (ADS)

Merkord, C. L.; Liu, Y.; DeVos, M.; Wimberly, M. C.

2015-12-01

Malaria early detection and early warning systems are important tools for public health decision makers in regions where malaria transmission is seasonal and varies from year to year with fluctuations in rainfall and temperature. Here we present a new data-driven dynamic linear model based on the Kalman filter with time-varying coefficients that are used to identify malaria outbreaks as they occur (early detection) and predict the location and timing of future outbreaks (early warning). We fit linear models of malaria incidence with trend and Fourier form seasonal components using three years of weekly malaria case data from 30 districts in the Amhara Region of Ethiopia. We identified past outbreaks by comparing the modeled prediction envelopes with observed case data. Preliminary results demonstrated the potential for improved accuracy and timeliness over commonly-used methods in which thresholds are based on simpler summary statistics of historical data. Other benefits of the dynamic linear modeling approach include robustness to missing data and the ability to fit models with relatively few years of training data. To predict future outbreaks, we started with the early detection model for each district and added a regression component based on satellite-derived environmental predictor variables including precipitation data from the Tropical Rainfall Measuring Mission (TRMM) and land surface temperature (LST) and spectral indices from the Moderate Resolution Imaging Spectroradiometer (MODIS). We included lagged environmental predictors in the regression component of the model, with lags chosen based on cross-correlation of the one-step-ahead forecast errors from the first model. Our results suggest that predictions of future malaria outbreaks can be improved by incorporating lagged environmental predictors.

Surveillance of dengue fever virus: a review of epidemiological models and early warning systems.

PubMed

Racloz, Vanessa; Ramsey, Rebecca; Tong, Shilu; Hu, Wenbiao

2012-01-01

Dengue fever affects over a 100 million people annually hence is one of the world's most important vector-borne diseases. The transmission area of this disease continues to expand due to many direct and indirect factors linked to urban sprawl, increased travel and global warming. Current preventative measures include mosquito control programs, yet due to the complex nature of the disease and the increased importation risk along with the lack of efficient prophylactic measures, successful disease control and elimination is not realistic in the foreseeable future. Epidemiological models attempt to predict future outbreaks using information on the risk factors of the disease. Through a systematic literature review, this paper aims at analyzing the different modeling methods and their outputs in terms of acting as an early warning system. We found that many previous studies have not sufficiently accounted for the spatio-temporal features of the disease in the modeling process. Yet with advances in technology, the ability to incorporate such information as well as the socio-environmental aspect allowed for its use as an early warning system, albeit limited geographically to a local scale.

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 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.

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

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.

Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model.

PubMed

Wang, Jianzhou; Niu, Tong; Wang, Rui

2017-03-02

The worsening atmospheric pollution increases the necessity of air quality early warning systems (EWSs). Despite the fact that a massive amount of investigation about EWS in theory and practicality has been conducted by numerous researchers, studies concerning the quantification of uncertain information and comprehensive evaluation are still lacking, which impedes further development in the area. In this paper, firstly a comprehensive warning system is proposed, which consists of two vital indispensable modules, namely effective forecasting and scientific evaluation, respectively. For the forecasting module, a novel hybrid model combining the theory of data preprocessing and numerical optimization is first developed to implement effective forecasting for air pollutant concentration. Especially, in order to further enhance the accuracy and robustness of the warning system, interval forecasting is implemented to quantify the uncertainties generated by forecasts, which can provide significant risk signals by using point forecasting for decision-makers. For the evaluation module, a cloud model, based on probability and fuzzy set theory, is developed to perform comprehensive evaluations of air quality, which can realize the transformation between qualitative concept and quantitative data. To verify the effectiveness and efficiency of the warning system, extensive simulations based on air pollutants data from Dalian in China were effectively implemented, which illustrate that the warning system is not only remarkably high-performance, but also widely applicable.

Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model

PubMed Central

Wang, Jianzhou; Niu, Tong; Wang, Rui

2017-01-01

The worsening atmospheric pollution increases the necessity of air quality early warning systems (EWSs). Despite the fact that a massive amount of investigation about EWS in theory and practicality has been conducted by numerous researchers, studies concerning the quantification of uncertain information and comprehensive evaluation are still lacking, which impedes further development in the area. In this paper, firstly a comprehensive warning system is proposed, which consists of two vital indispensable modules, namely effective forecasting and scientific evaluation, respectively. For the forecasting module, a novel hybrid model combining the theory of data preprocessing and numerical optimization is first developed to implement effective forecasting for air pollutant concentration. Especially, in order to further enhance the accuracy and robustness of the warning system, interval forecasting is implemented to quantify the uncertainties generated by forecasts, which can provide significant risk signals by using point forecasting for decision-makers. For the evaluation module, a cloud model, based on probability and fuzzy set theory, is developed to perform comprehensive evaluations of air quality, which can realize the transformation between qualitative concept and quantitative data. To verify the effectiveness and efficiency of the warning system, extensive simulations based on air pollutants data from Dalian in China were effectively implemented, which illustrate that the warning system is not only remarkably high-performance, but also widely applicable. PMID:28257122

Early Warning Signals for Abrupt Change Raise False Alarm During Sea Ice Loss

NASA Astrophysics Data System (ADS)

Wagner, T. J. W.; Eisenman, I.

2015-12-01

Uncovering universal early warning signals for critical transitions has become a coveted goal in diverse scientific disciplines, ranging from climate science to financial mathematics. There has been a flurry of recent research proposing such signals, with increasing autocorrelation and increasing variance being among the most widely discussed candidates. A number of studies have suggested that increasing autocorrelation alone may suffice to signal an impending transition, although some others have questioned this. Here, we consider variance and autocorrelation in the context of sea ice loss in an idealized model of the global climate system. The model features no bifurcation, nor increased rate of retreat, as the ice disappears. Nonetheless, the autocorrelation of summer sea ice area is found to increase with diminishing sea ice cover in a global warming scenario. The variance, by contrast, decreases. A simple physical mechanism is proposed to explain the occurrence of increasing autocorrelation but not variance in the model when there is no approaching bifurcation. Additionally, a similar mechanism is shown to allow an increase in both indicators with no physically attainable bifurcation. This implies that relying on autocorrelation and variance as early warning signals can raise false alarms in the climate system, warning of "tipping points" that are not actually there.

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.

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.

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.

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.

False alarms: How early warning signals falsely predict abrupt sea ice loss

NASA Astrophysics Data System (ADS)

Wagner, Till J. W.; Eisenman, Ian

2016-04-01

Uncovering universal early warning signals for critical transitions has become a coveted goal in diverse scientific disciplines, ranging from climate science to financial mathematics. There has been a flurry of recent research proposing such signals, with increasing autocorrelation and increasing variance being among the most widely discussed candidates. A number of studies have suggested that increasing autocorrelation alone may suffice to signal an impending transition, although some others have questioned this. Here we consider variance and autocorrelation in the context of sea ice loss in an idealized model of the global climate system. The model features no bifurcation, nor increased rate of retreat, as the ice disappears. Nonetheless, the autocorrelation of summer sea ice area is found to increase in a global warming scenario. The variance, by contrast, decreases. A simple physical mechanism is proposed to explain the occurrence of increasing autocorrelation but not variance when there is no approaching bifurcation. Additionally, a similar mechanism is shown to allow an increase in both indicators with no physically attainable bifurcation. This implies that relying on autocorrelation and variance as early warning signals can raise false alarms in the climate system, warning of "tipping points" that are not actually there.

Early warning model based on correlated networks in global crude oil markets

NASA Astrophysics Data System (ADS)

Yu, Jia-Wei; Xie, Wen-Jie; Jiang, Zhi-Qiang

2018-01-01

Applying network tools on predicting and warning the systemic risks provides a novel avenue to manage risks in financial markets. Here, we construct a series of global crude oil correlated networks based on the historical 57 oil prices covering a period from 1993 to 2012. Two systemic risk indicators are constructed based on the density and modularity of correlated networks. The local maximums of the risk indicators are found to have the ability to predict the trends of oil prices. In our sample periods, the indicator based on the network density sends five signals and the indicator based on the modularity index sends four signals. The four signals sent by both indicators are able to warn the drop of future oil prices and the signal only sent by the network density is followed by a huge rise of oil prices. Our results deepen the application of network measures on building early warning models of systemic risks and can be applied to predict the trends of future prices in financial markets.

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.

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.

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.

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.

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.

Integrating remotely sensed fires for predicting deforestation for REDD.

PubMed

Armenteras, Dolors; Gibbes, Cerian; Anaya, Jesús A; Dávalos, Liliana M

2017-06-01

Fire is an important tool in tropical forest management, as it alters forest composition, structure, and the carbon budget. The United Nations program on Reducing Emissions from Deforestation and Forest Degradation (REDD+) aims to sustainably manage forests, as well as to conserve and enhance their carbon stocks. Despite the crucial role of fire management, decision-making on REDD+ interventions fails to systematically include fires. Here, we address this critical knowledge gap in two ways. First, we review REDD+ projects and programs to assess the inclusion of fires in monitoring, reporting, and verification (MRV) systems. Second, we model the relationship between fire and forest for a pilot site in Colombia using near-real-time (NRT) fire monitoring data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). The literature review revealed fire remains to be incorporated as a key component of MRV systems. Spatially explicit modeling of land use change showed the probability of deforestation declined sharply with increasing distance to the nearest fire the preceding year (multi-year model area under the curve [AUC] 0.82). Deforestation predictions based on the model performed better than the official REDD early-warning system. The model AUC for 2013 and 2014 was 0.81, compared to 0.52 for the early-warning system in 2013 and 0.68 in 2014. This demonstrates NRT fire monitoring is a powerful tool to predict sites of forest deforestation. Applying new, publicly available, and open-access NRT fire data should be an essential element of early-warning systems to detect and prevent deforestation. Our results provide tools for improving both the current MRV systems, and the deforestation early-warning system in Colombia. © 2017 by the Ecological Society of America.

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…

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.

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.

Early identification systems for emerging foodborne hazards.

PubMed

Marvin, H J P; Kleter, G A; Prandini, A; Dekkers, S; Bolton, D J

2009-05-01

This paper provides a non-exhausting overview of early warning systems for emerging foodborne hazards that are operating in the various places in the world. Special attention is given to endpoint-focussed early warning systems (i.e. ECDC, ISIS and GPHIN) and hazard-focussed early warning systems (i.e. FVO, RASFF and OIE) and their merit to successfully identify a food safety problem in an early stage is discussed. Besides these early warning systems which are based on monitoring of either disease symptoms or hazards, also early warning systems and/or activities that intend to predict the occurrence of a food safety hazard in its very beginning of development or before that are described. Examples are trend analysis, horizon scanning, early warning systems for mycotoxins in maize and/or wheat and information exchange networks (e.g. OIE and GIEWS). Furthermore, recent initiatives that aim to develop predictive early warning systems based on the holistic principle are discussed. The assumption of the researchers applying this principle is that developments outside the food production chain that are either directly or indirectly related to the development of a particular food safety hazard may also provide valuable information to predict the development of this hazard.

An early warning system for marine storm hazard mitigation

NASA Astrophysics Data System (ADS)

Vousdoukas, M. I.; Almeida, L. P.; Pacheco, A.; Ferreira, O.

2012-04-01

The present contribution presents efforts towards the development of an operational Early Warning System for storm hazard prediction and mitigation. The system consists of a calibrated nested-model train which consists of specially calibrated Wave Watch III, SWAN and XBeach models. The numerical simulations provide daily forecasts of the hydrodynamic conditions, morphological change and overtopping risk at the area of interest. The model predictions are processed by a 'translation' module which is based on site-specific Storm Impact Indicators (SIIs) (Ciavola et al., 2011, Storm impacts along European coastlines. Part 2: lessons learned from the MICORE project, Environmental Science & Policy, Vol 14), and warnings are issued when pre-defined threshold values are exceeded. For the present site the selected SIIs were (i) the maximum wave run-up height during the simulations; and (ii) the dune-foot horizontal retreat at the end of the simulations. Both SIIs and pre-defined thresholds were carefully selected on the grounds of existing experience and field data. Four risk levels were considered, each associated with an intervention approach, recommended to the responsible coastal protection authority. Regular updating of the topography/bathymetry is critical for the performance of the storm impact forecasting, especially when there are significant morphological changes. The system can be extended to other critical problems, like implications of global warming and adaptive management strategies, while the approach presently followed, from model calibration to the early warning system for storm hazard mitigation, can be applied to other sites worldwide, with minor adaptations.

Short National Early Warning Score - Developing a Modified Early Warning Score.

PubMed

Luís, Leandro; Nunes, Carla

2017-12-11

Early Warning Score (EWS) systems have been developed for detecting hospital patients clinical deterioration. Many studies show that a National Early Warning Score (NEWS) performs well in discriminating survival from death in acute medical and surgical hospital wards. NEWS is validated for Portugal and is available for use. A simpler EWS system may help to reduce the risk of error, as well as increase clinician compliance with the tool. The aim of the study was to evaluate whether a simplified NEWS model will improve use and data collection. We evaluated the ability of single and aggregated parameters from the NEWS model to detect patients' clinical deterioration in the 24h prior to an outcome. There were 2 possible outcomes: Survival vs Unanticipated intensive care unit admission or death. We used binary logistic regression models and Receiver Operating Characteristic Curves (ROC) to evaluate the parameters' performance in discriminating among the outcomes for a sample of patients from 6 Portuguese hospital wards. NEWS presented an excellent discriminating capability (Area under the Curve of ROC (AUCROC)=0.944). Temperature and systolic blood pressure (SBP) parameters did not contribute significantly to the model. We developed two different models, one without temperature, and the other by removing temperature and SBP (M2). Both models had an excellent discriminating capability (AUCROC: 0.965; 0.903, respectively) and a good predictive power in the optimum threshold of the ROC curve. The 3 models revealed similar discriminant capabilities. Although the use of SBP is not clearly evident in the identification of clinical deterioration, it is recognized as an important vital sign. We recommend the use of the first new model, as its simplicity may help to improve adherence and use by health care workers. Copyright © 2017 Australian College of Critical Care Nurses Ltd. Published by Elsevier Ltd. All rights reserved.

Early warning of West Nile virus mosquito vector: climate and land use models successfully explain phenology and abundance of Culex pipiens mosquitoes in north-western Italy.

PubMed

Rosà, Roberto; Marini, Giovanni; Bolzoni, Luca; Neteler, Markus; Metz, Markus; Delucchi, Luca; Chadwick, Elizabeth A; Balbo, Luca; Mosca, Andrea; Giacobini, Mario; Bertolotti, Luigi; Rizzoli, Annapaola

2014-06-12

West Nile Virus (WNV) is an emerging global health threat. Transmission risk is strongly related to the abundance of mosquito vectors, typically Culex pipiens in Europe. Early-warning predictors of mosquito population dynamics would therefore help guide entomological surveillance and thereby facilitate early warnings of transmission risk. We analysed an 11-year time series (2001 to 2011) of Cx. pipiens mosquito captures from the Piedmont region of north-western Italy to determine the principal drivers of mosquito population dynamics. Linear mixed models were implemented to examine the relationship between Cx. pipiens population dynamics and environmental predictors including temperature, precipitation, Normalized Difference Water Index (NDWI) and the proximity of mosquito traps to urban areas and rice fields. Warm temperatures early in the year were associated with an earlier start to the mosquito season and increased season length, and later in the year, with decreased abundance. Early precipitation delayed the start and shortened the length of the mosquito season, but increased total abundance. Conversely, precipitation later in the year was associated with a longer season. Finally, higher NDWI early in the year was associated with an earlier start to the season and increased season length, but was not associated with abundance. Proximity to rice fields predicted higher total abundance when included in some models, but was not a significant predictor of phenology. Proximity to urban areas was not a significant predictor in any of our models. Predicted variations in start of the season and season length ranged from one to three weeks, across the measured range of variables. Predicted mosquito abundance was highly variable, with numbers in excess of 1000 per trap per year when late season temperatures were low (average 21°C) to only 150 when late season temperatures were high (average 30°C). Climate data collected early in the year, in conjunction with local land use, can be used to provide early warning of both the timing and magnitude of mosquito outbreaks. This potentially allows targeted mosquito control measures to be implemented, with implications for prevention and control of West Nile Virus and other mosquito borne diseases.

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.

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

Switch of Sensitivity Dynamics Revealed with DyGloSA Toolbox for Dynamical Global Sensitivity Analysis as an Early Warning for System's Critical Transition

PubMed Central

Baumuratova, Tatiana; Dobre, Simona; Bastogne, Thierry; Sauter, Thomas

2013-01-01

Systems with bifurcations may experience abrupt irreversible and often unwanted shifts in their performance, called critical transitions. For many systems like climate, economy, ecosystems it is highly desirable to identify indicators serving as early warnings of such regime shifts. Several statistical measures were recently proposed as early warnings of critical transitions including increased variance, autocorrelation and skewness of experimental or model-generated data. The lack of automatized tool for model-based prediction of critical transitions led to designing DyGloSA – a MATLAB toolbox for dynamical global parameter sensitivity analysis (GPSA) of ordinary differential equations models. We suggest that the switch in dynamics of parameter sensitivities revealed by our toolbox is an early warning that a system is approaching a critical transition. We illustrate the efficiency of our toolbox by analyzing several models with bifurcations and predicting the time periods when systems can still avoid going to a critical transition by manipulating certain parameter values, which is not detectable with the existing SA techniques. DyGloSA is based on the SBToolbox2 and contains functions, which compute dynamically the global sensitivity indices of the system by applying four main GPSA methods: eFAST, Sobol's ANOVA, PRCC and WALS. It includes parallelized versions of the functions enabling significant reduction of the computational time (up to 12 times). DyGloSA is freely available as a set of MATLAB scripts at http://bio.uni.lu/systems_biology/software/dyglosa. It requires installation of MATLAB (versions R2008b or later) and the Systems Biology Toolbox2 available at www.sbtoolbox2.org. DyGloSA can be run on Windows and Linux systems, -32 and -64 bits. PMID:24367574

Switch of sensitivity dynamics revealed with DyGloSA toolbox for dynamical global sensitivity analysis as an early warning for system's critical transition.

PubMed

Baumuratova, Tatiana; Dobre, Simona; Bastogne, Thierry; Sauter, Thomas

2013-01-01

Systems with bifurcations may experience abrupt irreversible and often unwanted shifts in their performance, called critical transitions. For many systems like climate, economy, ecosystems it is highly desirable to identify indicators serving as early warnings of such regime shifts. Several statistical measures were recently proposed as early warnings of critical transitions including increased variance, autocorrelation and skewness of experimental or model-generated data. The lack of automatized tool for model-based prediction of critical transitions led to designing DyGloSA - a MATLAB toolbox for dynamical global parameter sensitivity analysis (GPSA) of ordinary differential equations models. We suggest that the switch in dynamics of parameter sensitivities revealed by our toolbox is an early warning that a system is approaching a critical transition. We illustrate the efficiency of our toolbox by analyzing several models with bifurcations and predicting the time periods when systems can still avoid going to a critical transition by manipulating certain parameter values, which is not detectable with the existing SA techniques. DyGloSA is based on the SBToolbox2 and contains functions, which compute dynamically the global sensitivity indices of the system by applying four main GPSA methods: eFAST, Sobol's ANOVA, PRCC and WALS. It includes parallelized versions of the functions enabling significant reduction of the computational time (up to 12 times). DyGloSA is freely available as a set of MATLAB scripts at http://bio.uni.lu/systems_biology/software/dyglosa. It requires installation of MATLAB (versions R2008b or later) and the Systems Biology Toolbox2 available at www.sbtoolbox2.org. DyGloSA can be run on Windows and Linux systems, -32 and -64 bits.

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.

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.

Demands on Intranets — Viable System Model as a Foundation for Intranet Design

NASA Astrophysics Data System (ADS)

Amcoff Nyström, Christina

2006-06-01

The number of Intranets increases in organizations but their potential to support viability is not fully exploited. The cybernetic model, the Viable System Model, has not been connected to the Intranet concept before. Characteristics of the VSM, such as highlighting the importance of production, monitoring of production units through Early Warning Systems, autonomy and empowerment, are used as patterns and a base for de-signing essential parts and/or functions of an Intranet. The result is a brief description of functions vital to the operational parts of organizations. Examples are Early Warning Systems, control systems, "gate-keepers," amplifying and damping information to and from the organization and "agents" supporting search abilities on an Intranet.

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

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.

A spatiotemporal dengue fever early warning model accounting for nonlinear associations with meteorological factors: a Bayesian maximum entropy approach

NASA Astrophysics Data System (ADS)

Lee, Chieh-Han; Yu, Hwa-Lung; Chien, Lung-Chang

2014-05-01

Dengue fever has been identified as one of the most widespread vector-borne diseases in tropical and sub-tropical. In the last decade, dengue is an emerging infectious disease epidemic in Taiwan especially in the southern area where have annually high incidences. For the purpose of disease prevention and control, an early warning system is urgently needed. Previous studies have showed significant relationships between climate variables, in particular, rainfall and temperature, and the temporal epidemic patterns of dengue cases. However, the transmission of the dengue fever is a complex interactive process that mostly understated the composite space-time effects of dengue fever. This study proposes developing a one-week ahead warning system of dengue fever epidemics in the southern Taiwan that considered nonlinear associations between weekly dengue cases and meteorological factors across space and time. The early warning system based on an integration of distributed lag nonlinear model (DLNM) and stochastic Bayesian Maximum Entropy (BME) analysis. The study identified the most significant meteorological measures including weekly minimum temperature and maximum 24-hour rainfall with continuous 15-week lagged time to dengue cases variation under condition of uncertainty. Subsequently, the combination of nonlinear lagged effects of climate variables and space-time dependence function is implemented via a Bayesian framework to predict dengue fever occurrences in the southern Taiwan during 2012. The result shows the early warning system is useful for providing potential outbreak spatio-temporal prediction of dengue fever distribution. In conclusion, the proposed approach can provide a practical disease control tool for environmental regulators seeking more effective strategies for dengue fever prevention.

Coupling a regional warning system to a semantic engine on online news for enhancing landslide prediction

NASA Astrophysics Data System (ADS)

Battistini, Alessandro; Rosi, Ascanio; Segoni, Samuele; Catani, Filippo; Casagli, Nicola

2017-04-01

Landslide inventories are basic data for large scale landslide modelling, e.g. they are needed to calibrate and validate rainfall thresholds, physically based models and early warning systems. The setting up of landslide inventories with traditional methods (e.g. remote sensing, field surveys and manual retrieval of data from technical reports and local newspapers) is time consuming. The objective of this work is to automatically set up a landslide inventory using a state-of-the art semantic engine based on data mining on online news (Battistini et al., 2013) and to evaluate if the automatically generated inventory can be used to validate a regional scale landslide warning system based on rainfall-thresholds. The semantic engine scanned internet news in real time in a 50 months test period. At the end of the process, an inventory of approximately 900 landslides was set up for the Tuscany region (23,000 km2, Italy). The inventory was compared with the outputs of the regional landslide early warning system based on rainfall thresholds, and a good correspondence was found: e.g. 84% of the events reported in the news is correctly identified by the model. In addition, the cases of not correspondence were forwarded to the rainfall threshold developers, which used these inputs to update some of the thresholds. On the basis of the results obtained, we conclude that automatic validation of landslide models using geolocalized landslide events feedback is possible. The source of data for validation can be obtained directly from the internet channel using an appropriate semantic engine. We also automated the validation procedure, which is based on a comparison between forecasts and reported events. We verified that our approach can be automatically used for a near real time validation of the warning system and for a semi-automatic update of the rainfall thresholds, which could lead to an improvement of the forecasting effectiveness of the warning system. In the near future, the proposed procedure could operate in continuous time and could allow for a periodic update of landslide hazard models and landslide early warning systems with minimum human intervention. References: Battistini, A., Segoni, S., Manzo, G., Catani, F., Casagli, N. (2013). Web data mining for automatic inventory of geohazards at national scale. Applied Geography, 43, 147-158.

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.

Challenges for operational forecasting and early warning of rainfall induced landslides

NASA Astrophysics Data System (ADS)

Guzzetti, Fausto

2017-04-01

In many areas of the world, landslides occur every year, claiming lives and producing severe economic and environmental damage. Many of the landslides with human or economic consequences are the result of intense or prolonged rainfall. For this reason, in many areas the timely forecast of rainfall-induced landslides is of both scientific interest and social relevance. In the recent years, there has been a mounting interest and an increasing demand for operational landslide forecasting, and for associated landslide early warning systems. Despite the relevance of the problem, and the increasing interest and demand, only a few systems have been designed, and are currently operated. Inspection of the - limited - literature on operational landslide forecasting, and on the associated early warning systems, reveals that common criteria and standards for the design, the implementation, the operation, and the evaluation of the performances of the systems, are lacking. This limits the possibility to compare and to evaluate the systems critically, to identify their inherent strengths and weaknesses, and to improve the performance of the systems. Lack of common criteria and of established standards can also limit the credibility of the systems, and consequently their usefulness and potential practical impact. Landslides are very diversified phenomena, and the information and the modelling tools used to attempt landslide forecasting vary largely, depending on the type and size of the landslides, the extent of the geographical area considered, the timeframe of the forecasts, and the scope of the predictions. Consequently, systems for landslide forecasting and early warning can be designed and implemented at several different geographical scales, from the local (site or slope specific) to the regional, or even national scale. The talk focuses on regional to national scale landslide forecasting systems, and specifically on operational systems based on empirical rainfall threshold models. Building on the experience gained in designing, implementing, and operating national and regional landslide forecasting systems in Italy, and on a preliminary review of the existing literature on regional landslide early warning systems, the talk discusses concepts, limitations and challenges inherent to the design of reliable forecasting and early warning systems for rainfall-triggered landslides, the evaluation of the performances of the systems, and on problems related to the use of the forecasts and the issuing of landslide warnings. Several of the typical elements of an operational landslide forecasting system are considered, including: (i) the rainfall and landslide information used to establish the threshold models, (ii) the methods and tools used to define the empirical rainfall thresholds, and their associated uncertainty, (iii) the quality (e.g., the temporal and spatial resolution) of the rainfall information used for operational forecasting, including rain gauge and radar measurements, satellite estimates, and quantitative weather forecasts, (iv) the ancillary information used to prepare the forecasts, including e.g., the terrain subdivisions and the landslide susceptibility zonations, (v) the criteria used to transform the forecasts into landslide warnings and the methods used to communicate the warnings, and (vi) the criteria and strategies adopted to evaluate the performances of the systems, and to define minimum or optimal performance levels.

Estimating millet production for famine early warning: An application of crop simulation modelling using satellite and ground-based data in Burkina Faso

USGS Publications Warehouse

Thornton, P. K.; Bowen, W. T.; Ravelo, A.C.; Wilkens, P. W.; Farmer, G.; Brock, J.; Brink, J. E.

1997-01-01

Early warning of impending poor crop harvests in highly variable environments can allow policy makers the time they need to take appropriate action to ameliorate the effects of regional food shortages on vulnerable rural and urban populations. Crop production estimates for the current season can be obtained using crop simulation models and remotely sensed estimates of rainfall in real time, embedded in a geographic information system that allows simple analysis of simulation results. A prototype yield estimation system was developed for the thirty provinces of Burkina Faso. It is based on CERES-Millet, a crop simulation model of the growth and development of millet (Pennisetum spp.). The prototype was used to estimate millet production in contrasting seasons and to derive production anomaly estimates for the 1986 season. Provincial yields simulated halfway through the growing season were generally within 15% of their final (end-of-season) values. Although more work is required to produce an operational early warning system of reasonable credibility, the methodology has considerable potential for providing timely estimates of regional production of the major food crops in countries of sub-Saharan Africa.

Spatial Models for Prediction and Early Warning of Aedes aegypti Proliferation from Data on Climate Change and Variability in Cuba.

PubMed

Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R

2015-04-01

Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for epidemiological surveillance.

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.

Early Flood Warning in Africa: Results of a Feasibility study in the JUBA, SHABELLE and ZAMBEZI

NASA Astrophysics Data System (ADS)

Pappenberger, F. P.; de Roo, A. D.; Buizza, Roberto; Bodis, Katalin; Thiemig, Vera

2009-04-01

Building on the experiences gained with the European Flood Alert System (EFAS), pilot studies are carried out in three river basins in Africa. The European Flood Alert System, pre-operational since 2003, provides early flood alerts for European rivers. At present, the experiences with the European EFAS system are used to evaluate the feasibility of flood early warning for Africa. Three case studies are carried in the Juba and Shabelle rivers (Somalia and Ethiopia), and in the Zambesi river (Southern Africa). Predictions in these data scarce regions are extremely difficult to make as records of observations are scarce and often unreliable. Meteorological and Discharge observations are used to calibrate and test the model, as well as soils, landuse and topographic data available within the JRC African Observatory. ECMWF ERA-40, ERA-Interim data and re-forecasts of flood events from January to March 1978, and in March 2001 are evaluated to examine the feasibility for early flood warning. First results will be presented.

Seasonal Water Balance Forecasts for Drought Early Warning in Ethiopia

NASA Astrophysics Data System (ADS)

Spirig, Christoph; Bhend, Jonas; Liniger, Mark

2016-04-01

Droughts severely impact Ethiopian agricultural production. Successful early warning for drought conditions in the upcoming harvest season therefore contributes to better managing food shortages arising from adverse climatic conditions. So far, however, meteorological seasonal forecasts have not been used in Ethiopia's national food security early warning system (i.e. the LEAP platform). Here we analyse the forecast quality of seasonal forecasts of total rainfall and of the meteorological water balance as a proxy for plant available water. We analyse forecast skill of June to September rainfall and water balance from dynamical seasonal forecast systems, the ECMWF System4 and EC-EARTH global forecasting systems. Rainfall forecasts outperform forecasts assuming a stationary climate mainly in north-eastern Ethiopia - an area that is particularly vulnerable to droughts. Forecasts of the water balance index seem to be even more skilful and thus more useful than pure rainfall forecasts. The results vary though for different lead times and skill measures employed. We further explore the potential added value of dynamically downscaling the forecasts through several dynamical regional climate models made available through the EU FP7 project EUPORIAS. Preliminary results suggest that dynamically downscaled seasonal forecasts are not significantly better compared with seasonal forecasts from the global models. We conclude that seasonal forecasts of a simple climate index such as the water balance have the potential to benefit drought early warning in Ethiopia, both due to its positive predictive skill and higher usefulness than seasonal mean quantities.

Preliminary Tests of a Buffet Stall-Warning Device on a 1/5-Scale Model of the Republic XP-84 Airplane

NASA Technical Reports Server (NTRS)

Tucker, Warren A.; Comisarow, Paul

1946-01-01

During the first flight tests of the Republic XP-84 airplane it was discovered that there was a complete lack of stall warning. A short series of development tests of a suitable stall-warning device for the airplane was therefore made on a 1/5-scale model in the Langley 300 MPH 7- by 10-foot tunnel. Two similar stall-warning devices, each designed to produce early root stall which would provide a buffet warning, were tested. It appeared that either device would give a satisfactory buffet warning in the flap-up configuration, at the cost of an increase of 8 or 10 miles per hour in minimum speed. Although neither device seemed to give a true buffet warning in the flaps-down configuration, it appeared that either device would improve the flaps-down stalling characteristics by lessening the severity of the stall and by maintaining better control at the stall. The flaps-down minimum-speed increase caused by the devices was only 1 or 2 miles per hour.

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

Regional Assessment of Storm-triggered Shall Landslide Risks using the SLIDE (SLope-Infiltration-Distributed Equilibrium) Model

NASA Astrophysics Data System (ADS)

Hong, Y.; Kirschbaum, D. B.; Fukuoka, H.

2011-12-01

The key to advancing the predictability of rainfall-triggered landslides is to use physically based slope-stability models that simulate the dynamical response of the subsurface moisture to spatiotemporal variability of rainfall in complex terrains. An early warning system applying such physical models has been developed to predict rainfall-induced shallow landslides over Java Island in Indonesia and Honduras. The prototyped early warning system integrates three major components: (1) a susceptibility mapping or hotspot identification component based on a land surface geospatial database (topographical information, maps of soil properties, and local landslide inventory etc.); (2) a satellite-based precipitation monitoring system (http://trmm.gsfc.nasa.gov) and a precipitation forecasting model (i.e. Weather Research Forecast); and (3) a physically-based, rainfall-induced landslide prediction model SLIDE (SLope-Infiltration-Distributed Equilibrium). The system utilizes the modified physical model to calculate a Factor of Safety (FS) that accounts for the contribution of rainfall infiltration and partial saturation to the shear strength of the soil in topographically complex terrains. The system's prediction performance has been evaluated using a local landslide inventory. In Java Island, Indonesia, evaluation of SLIDE modeling results by local news reports shows that the system successfully predicted landslides in correspondence to the time of occurrence of the real landslide events. Further study of SLIDE is implemented in Honduras where Hurricane Mitch triggered widespread landslides in 1998. Results shows within the approximately 1,200 square kilometers study areas, the values of hit rates reached as high as 78% and 75%, while the error indices were 35% and 49%. Despite positive model performance, the SLIDE model is limited in the early warning system by several assumptions including, using general parameter calibration rather than in situ tests and neglecting geologic information. Advantages and limitations of this model will be discussed with respect to future applications of landslide assessment and prediction over large scales. In conclusion, integration of spatially distributed remote sensing precipitation products and in-situ datasets and physical models in this prototype system enable us to further develop a regional early warning tool in the future for forecasting storm-induced landslides.

MAFALDA: An early warning modeling tool to forecast volcanic ash dispersal and deposition

NASA Astrophysics Data System (ADS)

Barsotti, S.; Nannipieri, L.; Neri, A.

2008-12-01

Forecasting the dispersal of ash from explosive volcanoes is a scientific challenge to modern volcanology. It also represents a fundamental step in mitigating the potential impact of volcanic ash on urban areas and transport routes near explosive volcanoes. To this end we developed a Web-based early warning modeling tool named MAFALDA (Modeling and Forecasting Ash Loading and Dispersal in the Atmosphere) able to quantitatively forecast ash concentrations in the air and on the ground. The main features of MAFALDA are the usage of (1) a dispersal model, named VOL-CALPUFF, that couples the column ascent phase with the ash cloud transport and (2) high-resolution weather forecasting data, the capability to run and merge multiple scenarios, and the Web-based structure of the procedure that makes it suitable as an early warning tool. MAFALDA produces plots for a detailed analysis of ash cloud dynamics and ground deposition, as well as synthetic 2-D maps of areas potentially affected by dangerous concentrations of ash. A first application of MAFALDA to the long-lasting weak plumes produced at Mt. Etna (Italy) is presented. A similar tool can be useful to civil protection authorities and volcanic observatories in reducing the impact of the eruptive events. MAFALDA can be accessed at http://mafalda.pi.ingv.it.

Early warning of limit-exceeding concentrations of cyanobacteria and cyanotoxins in drinking water reservoirs by inferential modelling.

PubMed

Recknagel, Friedrich; Orr, Philip T; Bartkow, Michael; Swanepoel, Annelie; Cao, Hongqing

2017-11-01

An early warning scheme is proposed that runs ensembles of inferential models for predicting the cyanobacterial population dynamics and cyanotoxin concentrations in drinking water reservoirs on a diel basis driven by in situ sonde water quality data. When the 10- to 30-day-ahead predicted concentrations of cyanobacteria cells or cyanotoxins exceed pre-defined limit values, an early warning automatically activates an action plan considering in-lake control, e.g. intermittent mixing and ad hoc water treatment in water works, respectively. Case studies of the sub-tropical Lake Wivenhoe (Australia) and the Mediterranean Vaal Reservoir (South Africa) demonstrate that ensembles of inferential models developed by the hybrid evolutionary algorithm HEA are capable of up to 30days forecasts of cyanobacteria and cyanotoxins using data collected in situ. The resulting models for Dolicospermum circinale displayed validity for up to 10days ahead, whilst concentrations of Cylindrospermopsis raciborskii and microcystins were successfully predicted up to 30days ahead. Implementing the proposed scheme for drinking water reservoirs enhances current water quality monitoring practices by solely utilising in situ monitoring data, in addition to cyanobacteria and cyanotoxin measurements. Access to routinely measured cyanotoxin data allows for development of models that predict explicitly cyanotoxin concentrations that avoid to inadvertently model and predict non-toxic cyanobacterial strains. Copyright © 2017 Elsevier B.V. All rights reserved.

Rainfall threshold calculation for debris flow early warning in areas with scarcity of data

NASA Astrophysics Data System (ADS)

Pan, Hua-Li; Jiang, Yuan-Jun; Wang, Jun; Ou, Guo-Qiang

2018-05-01

Debris flows are natural disasters that frequently occur in mountainous areas, usually accompanied by serious loss of lives and properties. One of the most commonly used approaches to mitigate the risk associated with debris flows is the implementation of early warning systems based on well-calibrated rainfall thresholds. However, many mountainous areas have little data regarding rainfall and hazards, especially in debris-flow-forming regions. Therefore, the traditional statistical analysis method that determines the empirical relationship between rainstorms and debris flow events cannot be effectively used to calculate reliable rainfall thresholds in these areas. After the severe Wenchuan earthquake, there were plenty of deposits deposited in the gullies, which resulted in several debris flow events. The triggering rainfall threshold has decreased obviously. To get a reliable and accurate rainfall threshold and improve the accuracy of debris flow early warning, this paper developed a quantitative method, which is suitable for debris flow triggering mechanisms in meizoseismal areas, to identify rainfall threshold for debris flow early warning in areas with a scarcity of data based on the initiation mechanism of hydraulic-driven debris flow. First, we studied the characteristics of the study area, including meteorology, hydrology, topography and physical characteristics of the loose solid materials. Then, the rainfall threshold was calculated by the initiation mechanism of the hydraulic debris flow. The comparison with other models and with alternate configurations demonstrates that the proposed rainfall threshold curve is a function of the antecedent precipitation index (API) and 1 h rainfall. To test the proposed method, we selected the Guojuanyan gully, a typical debris flow valley that during the 2008-2013 period experienced several debris flow events, located in the meizoseismal areas of the Wenchuan earthquake, as a case study. The comparison with other threshold models and configurations shows that the selected approach is the most promising starting point for further studies on debris flow early warning systems in areas with a scarcity of data.

Effects of forcing uncertainties in the improvement skills of assimilating satellite soil moisture retrievals into flood forecasting models

USDA-ARS?s Scientific Manuscript database

Floods have negative impacts on society, causing damages in infrastructures and industry, and in the worst cases, causing loss of human lives. Thus early and accurate warning is crucial to significantly reduce the impacts on public safety and economy. Reliable flood warning can be generated using ...

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

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.

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.

Landslide early warning based on failure forecast models: the example of Mt. de La Saxe rockslide, northern Italy

NASA Astrophysics Data System (ADS)

Manconi, A.; Giordan, D.

2015-02-01

We investigate the use of landslide failure forecast models by exploiting near-real-time monitoring data. Starting from the inverse velocity theory, we analyze landslide surface displacements on different temporal windows, and apply straightforward statistical methods to obtain confidence intervals on the estimated time of failure. Here we describe the main concepts of our method, and show an example of application to a real emergency scenario, the La Saxe rockslide, Aosta Valley region, northern Italy. Based on the herein presented case study, we identify operational thresholds based on the reliability of the forecast models, in order to support the management of early warning systems in the most critical phases of the landslide emergency.

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...

Early warning of climate tipping points from critical slowing down: comparing methods to improve robustness

PubMed Central

Lenton, T. M.; Livina, V. N.; Dakos, V.; Van Nes, E. H.; Scheffer, M.

2012-01-01

We address whether robust early warning signals can, in principle, be provided before a climate tipping point is reached, focusing on methods that seek to detect critical slowing down as a precursor of bifurcation. As a test bed, six previously analysed datasets are reconsidered, three palaeoclimate records approaching abrupt transitions at the end of the last ice age and three models of varying complexity forced through a collapse of the Atlantic thermohaline circulation. Approaches based on examining the lag-1 autocorrelation function or on detrended fluctuation analysis are applied together and compared. The effects of aggregating the data, detrending method, sliding window length and filtering bandwidth are examined. Robust indicators of critical slowing down are found prior to the abrupt warming event at the end of the Younger Dryas, but the indicators are less clear prior to the Bølling-Allerød warming, or glacial termination in Antarctica. Early warnings of thermohaline circulation collapse can be masked by inter-annual variability driven by atmospheric dynamics. However, rapidly decaying modes can be successfully filtered out by using a long bandwidth or by aggregating data. The two methods have complementary strengths and weaknesses and we recommend applying them together to improve the robustness of early warnings. PMID:22291229

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.

Earthquake Early Warning Management based on Client-Server using Primary Wave data from Vibrating Sensor

NASA Astrophysics Data System (ADS)

Laumal, F. E.; Nope, K. B. N.; Peli, Y. S.

2018-01-01

Early warning is a warning mechanism before an actual incident occurs, can be implemented on natural events such as tsunamis or earthquakes. Earthquakes are classified in tectonic and volcanic types depend on the source and nature. The tremor in the form of energy propagates in all directions as Primary and Secondary waves. Primary wave as initial earthquake vibrations propagates longitudinally, while the secondary wave propagates like as a sinusoidal wave after Primary, destructive and as a real earthquake. To process the primary vibration data captured by the earthquake sensor, a network management required client computer to receives primary data from sensors, authenticate and forward to a server computer to set up an early warning system. With the water propagation concept, a method of early warning system has been determined in which some sensors are located on the same line, sending initial vibrations as primary data on the same scale and the server recommended to the alarm sound as an early warning.

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.

A lightning-based nowcast-warning approach for short-duration rainfall events: Development and testing over Beijing during the warm seasons of 2006-2007

NASA Astrophysics Data System (ADS)

Wu, Fan; Cui, Xiaopeng; Zhang, Da-Lin

2018-06-01

Nowcasting short-duration (i.e., <6 h) rainfall (SDR) events is examined using total [i.e., cloud-to-ground (CG) and intra-cloud (IC)] lightning observations over the Beijing Metropolitan Region (BMR) during the warm seasons of 2006-2007. A total of 928 moderate and 554 intense SDR events, i.e., with the respective hourly rainfall rates (HRR) of 10-20 and ≥20 mm h-1, are utilized to estimate sharp-increasing rates in rainfall and lightning flash, termed as rainfall and lightning jumps, respectively. By optimizing the parameters in a lightning jump and a rainfall jump algorithm, their different jump intensity grades are verified for the above two categories of SDR events. Then, their corresponding graded nowcast-warning models are developed for the moderate and intense SDR events, respectively, with a low-grade warning for hitting more SDR events and a high-grade warning for reducing false alarms. Any issued warning in the nowcast-warning models is designed to last for 2 h after the occurrence of a lightning jump. It is demonstrated that the low-grade warnings can have the probability of detection (POD) of 67.8% (87.0%) and the high-grade warnings have the false alarms ratio (FAR) of 27.0% (22.2%) for the moderate (intense) SDR events, with an averaged lead time of 36.7 (52.0) min. The nowcast-warning models are further validated using three typical heavy-rain-producing storms that are independent from those used to develop the models. Results show that the nowcast-warning models can provide encouraging early warnings for the associated SDR events from the regional to meso-γ scales, indicating that they have a great potential in being applied to the other regions where high-resolution total lightning observations are available.

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.

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...

Landslide early warning based on failure forecast models: the example of the Mt. de La Saxe rockslide, northern Italy

NASA Astrophysics Data System (ADS)

Manconi, A.; Giordan, D.

2015-07-01

We apply failure forecast models by exploiting near-real-time monitoring data for the La Saxe rockslide, a large unstable slope threatening Aosta Valley in northern Italy. Starting from the inverse velocity theory, we analyze landslide surface displacements automatically and in near real time on different temporal windows and apply straightforward statistical methods to obtain confidence intervals on the estimated time of failure. Here, we present the result obtained for the La Saxe rockslide, a large unstable slope located in Aosta Valley, northern Italy. Based on this case study, we identify operational thresholds that are established on the reliability of the forecast models. Our approach is aimed at supporting the management of early warning systems in the most critical phases of the landslide emergency.

Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning

USGS Publications Warehouse

Mirus, Benjamin B.; Becker, Rachel E.; Baum, Rex L.; Smith, Joel B.

2018-01-01

Early warning for rainfall-induced shallow landsliding can help reduce fatalities and economic losses. Although these commonly occurring landslides are typically triggered by subsurface hydrological processes, most early warning criteria rely exclusively on empirical rainfall thresholds and other indirect proxies for subsurface wetness. We explore the utility of explicitly accounting for antecedent wetness by integrating real-time subsurface hydrologic measurements into landslide early warning criteria. Our efforts build on previous progress with rainfall thresholds, monitoring, and numerical modeling along the landslide-prone railway corridor between Everett and Seattle, Washington, USA. We propose a modification to a previously established recent versus antecedent (RA) cumulative rainfall thresholds by replacing the antecedent 15-day rainfall component with an average saturation observed over the same timeframe. We calculate this antecedent saturation with real-time telemetered measurements from five volumetric water content probes installed in the shallow subsurface within a steep vegetated hillslope. Our hybrid rainfall versus saturation (RS) threshold still relies on the same recent 3-day rainfall component as the existing RA thresholds, to facilitate ready integration with quantitative precipitation forecasts. During the 2015–2017 monitoring period, this RS hybrid approach has an increase of true positives and a decrease of false positives and false negatives relative to the previous RA rainfall-only thresholds. We also demonstrate that alternative hybrid threshold formats could be even more accurate, which suggests that further development and testing during future landslide seasons is needed. The positive results confirm that accounting for antecedent wetness conditions with direct subsurface hydrologic measurements can improve thresholds for alert systems and early warning of rainfall-induced shallow landsliding.

Implementation of a landslide early warning system based on near-real-time monitoring, multisensor mapping and geophysical measurements

NASA Astrophysics Data System (ADS)

Teza, Giordano; Galgaro, Antonio; Francese, Roberto; Ninfo, Andrea; Mariani, Rocco

2017-04-01

An early warning system has been implemented to monitor the Perarolo di Cadore landslide (North-Eastern Italian Alps), which is a slump whose induced risk is fairly high because a slope collapse could form a temporary dam on the underlying torrent and, therefore, could directly threaten the close village. A robotic total station (RTS) measures, with 6h returning time, the positions of 23 retro-reflectors placed on the landslide upper and middle sectors. The landslide's kinematical behavior derived from these near-real-time (NRT) surface displacements is interpreted on the basis of available geomorphological and geological information, geometrical data provided by some laser scanning and photogrammetric surveys, and a landslide model obtained by means of 3D Electrical Resistivity Tomography (3D ERT) measurements. In this way, an analysis of the time series provided by RTS and a pluviometer, which cover several years, allows the definition of some pre-alert and alert kinematical and rainfall thresholds. These thresholds, as well as the corresponding operational recommendations, are currently used for early warning purposes by Authorities involved in risk management for the Perarolo landslide. It should be noted the fact that, as new RTS and pluviometric data are available, the thresholds can be updated and, therefore, a fine tuning of the early warning system can be carried out in order to improve its performance. Although the proposed approach has been implemented in a particular case, it can be used to develop an early warning system based on NRT data in each site where a landslide threatens infrastructures and/or villages that cannot be relocated.

[Assessment and early warning of land ecological security in rapidly urbanizing coastal area: A case study of Caofeidian new district, Hebei, China].

PubMed

Zhang, Li; Chen, Ying; Wang, Shu-tao; Men, Ming-xin; Xu, Hao

2015-08-01

Assessment and early warning of land ecological security (LES) in rapidly urbanizing coastal area is an important issue to ensure sustainable land use and effective maintenance of land ecological security. In this study, an index system for the land ecological security of Caofeidian new district was established based on the Pressure-State-Response (P-S-R) model. Initial assessment units of 1 km x 1 km created with the remote sensing data and GIS methods were spatially interpolated to a fine pixel size of 30 m x 30 m, which were combined with the early warning method (using classification tree method) to evaluate the land ecological security of Caofeidian in 2005 and 2013. The early warning level was classed into four categories: security with degradation potential, sub-security with slow degradation, sub-security with rapid degradation, and insecurity. Result indicated that, from 2005 to 2013, the average LES of Caofeidian dropped from 0.55 to 0.52, indicating a degradation of land ecological security from medium security level to medium-low security level. The areas at the levels of insecurity with rapid degradation were mainly located in the rapid urbanization areas, illustrating that rapid expansion of urban construction land was the key factor to the deterioration of the regional land ecological security. Industrial District, Shilihai town and Nanpu saltern, in which the lands at the levels of insecurity and sub-security with rapid degradation or slow degradation accounted for 58.3%, 98.9% and 81.2% of their respective districts, were at the stage of high early warning. Thus, land ecological security regulation for these districts should be strengthened in near future. The study could provide a reference for land use planning and ecological protection of Caofeidian new district.

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.

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.

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.

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.

Influence of warning information changes on emergency response

NASA Astrophysics Data System (ADS)

Heisterkamp, Tobias; Ulbrich, Uwe; Glade, Thomas; Tetzlaff, Gerd

2014-05-01

Mitigation and risk reduction of natural hazards is significantly related to the possibility of predicting the actual event. Some hazards can already be forecasted several days in advance. For these hazards, early warning systems have been developed, installed and improved over the years. The formation of winter storms for example can be recognized up to one week before they pass through Central Europe. This relative long early warning time has the advantage that forecasters can concretise the warnings over time. Therefore, warnings can even be adapted to alternating conditions within the process, the observation or changes in its modelling. Emergency managers are one group of warning recipients in the civil protection sector. They have to prepare or initiate prevention or response measures at a specific point of time, depending on the required lead time of the referring actions. At this point of time already, the forecast and its equivalent warning, has to be assumed as a stage of reality, hence the decision-makers have to come to a conclusion. These decisions are based on spatial and temporal knowledge of the forecasted event and the consequential situation of risk. With incoming warning updates, the detailed status of information is permanently being alternated. Consequently, decisions can be influenced by the development of the warning situation and the inherent tendency before a certain point of time. They can also be adapted to updates later on, according to the changing 'decision reality'. The influence of these dynamic hazard situations on operational planning and response by emergency managers is investigated in case studies on winter storms for Berlin, Germany. Therefore, the issued warnings by the weather service and data of operation of Berlin Fire Brigades are analysed and compared. This presentation shows and discusses first results.

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.

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.

Using Satellite Remote Sensing Data in a Spatially Explicit Price Model

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Pinzon, Jorge E.; Prince, Stephen D.

2007-01-01

Famine early warning organizations use data from multiple disciplines to assess food insecurity of communities and regions in less-developed parts of the World. In this paper we integrate several indicators that are available to enhance the information for preparation for and responses to food security emergencies. The assessment uses a price model based on the relationship between the suitability of the growing season and market prices for coarse grain. The model is then used to create spatially continuous maps of millet prices. The model is applied to the dry central and northern areas of West Africa, using satellite-derived vegetation indices for the entire region. By coupling the model with vegetation data estimated for one to four months into the future, maps are created of a leading indicator of potential price movements. It is anticipated that these maps can be used to enable early warning of famine and for planning appropriate responses.

Famine Early Warning Systems and Their Use of Satellite Remote Sensing Data

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Essam, Timothy; Leonard, Kenneth

2011-01-01

Famine early warning organizations have experience that has much to contribute to efforts to incorporate climate and weather information into economic and political systems. Food security crises are now caused almost exclusively by problems of food access, not absolute food availability, but the role of monitoring agricultural production both locally and globally remains central. The price of food important to the understanding of food security in any region, but it needs to be understood in the context of local production. Thus remote sensing is still at the center of much food security analysis, along with an examination of markets, trade and economic policies during food security analyses. Technology including satellite remote sensing, earth science models, databases of food production and yield, and modem telecommunication systems contributed to improved food production information. Here we present an econometric approach focused on bringing together satellite remote sensing and market analysis into food security assessment in the context of early warning.

Early-warning signals for an outbreak of the influenza pandemic

NASA Astrophysics Data System (ADS)

Ren, Di; Gao, Jie

2011-12-01

Over the course of human history, influenza pandemics have been seen as major disasters, so studies on the influenza virus have become an important issue for many experts and scholars. Comprehensive research has been performed over the years on the biological properties, chemical characteristics, external environmental factors and other aspects of the virus, and some results have been achieved. Based on the chaos game representation walk model, this paper uses the time series analysis method to study the DNA sequences of the influenza virus from 1913 to 2010, and works out the early-warning signals indicator value for the outbreak of an influenza pandemic. The variances in the CGR walk sequences for the pandemic years (or + -1 to 2 years) are significantly higher than those for the adjacent years, while those in the non-pandemic years are usually smaller. In this way we can provide an influenza early-warning mechanism so that people can take precautions and be well prepared prior to a pandemic.

Synergy of Earth Observation and In-Situ Monitoring Data for Flood Hazard Early Warning System

NASA Astrophysics Data System (ADS)

Brodsky, Lukas; Kodesova, Radka; Spazierova, Katerina

2010-12-01

In this study, we demonstrate synergy of EO and in-situ monitoring data for early warning flood hazard system in the Czech Republic developed within ESA PECS project FLOREO. The development of the demonstration system is oriented to support existing monitoring activities, especially snow melt and surface water runoff contributing to flooding events. The system consists of two main parts accordingly, the first is snow cover and snow melt monitoring driven mainly by EO data and the other is surface water runoff modeling and monitoring driven by synergy of in-situ and EO data.

Source modeling and inversion with near real-time GPS: a GITEWS perspective for Indonesia

NASA Astrophysics Data System (ADS)

Babeyko, A. Y.; Hoechner, A.; Sobolev, S. V.

2010-07-01

We present the GITEWS approach to source modeling for the tsunami early warning in Indonesia. Near-field tsunami implies special requirements to both warning time and details of source characterization. To meet these requirements, we employ geophysical and geological information to predefine a maximum number of rupture parameters. We discretize the tsunamigenic Sunda plate interface into an ordered grid of patches (150×25) and employ the concept of Green's functions for forward and inverse rupture modeling. Rupture Generator, a forward modeling tool, additionally employs different scaling laws and slip shape functions to construct physically reasonable source models using basic seismic information only (magnitude and epicenter location). GITEWS runs a library of semi- and fully-synthetic scenarios to be extensively employed by system testing as well as by warning center personnel teaching and training. Near real-time GPS observations are a very valuable complement to the local tsunami warning system. Their inversion provides quick (within a few minutes on an event) estimation of the earthquake magnitude, rupture position and, in case of sufficient station coverage, details of slip distribution.

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.

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).

Development of a GIS-based integrated framework for coastal seiches monitoring and forecasting: A North Jiangsu shoal case study

NASA Astrophysics Data System (ADS)

Qin, Rufu; Lin, Liangzhao

2017-06-01

Coastal seiches have become an increasingly important issue in coastal science and present many challenges, particularly when attempting to provide warning services. This paper presents the methodologies, techniques and integrated services adopted for the design and implementation of a Seiches Monitoring and Forecasting Integration Framework (SMAF-IF). The SMAF-IF is an integrated system with different types of sensors and numerical models and incorporates the Geographic Information System (GIS) and web techniques, which focuses on coastal seiche events detection and early warning in the North Jiangsu shoal, China. The in situ sensors perform automatic and continuous monitoring of the marine environment status and the numerical models provide the meteorological and physical oceanographic parameter estimates. A model outputs processing software was developed in C# language using ArcGIS Engine functions, which provides the capabilities of automatically generating visualization maps and warning information. Leveraging the ArcGIS Flex API and ASP.NET web services, a web based GIS framework was designed to facilitate quasi real-time data access, interactive visualization and analysis, and provision of early warning services for end users. The integrated framework proposed in this study enables decision-makers and the publics to quickly response to emergency coastal seiche events and allows an easy adaptation to other regional and scientific domains related to real-time monitoring and forecasting.

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.

Development and Operation of Space-Based Disease Early Warning Models

NASA Astrophysics Data System (ADS)

John, M. M.

2010-12-01

Millions of people die every year from preventable diseases such as malaria and cholera. Pandemics put the entire world population at risk and have the potential to kill thousands and cripple the global economy. In light of these dangers, it is fortunate that the data and imagery gathered by remote sensing satellites can be used to develop models that predict areas at risk for outbreaks. These warnings can help decision makers to distribute preventative medicine and other forms of aid to save lives. There are already many Earth observing satellites in orbit with the ability to provide data and imagery. Researchers have created a number of models based on this information, and some are being used in real-life situations. These capabilities should be further developed and supported by governments and international organizations to benefit as many people as possible. To understand the benefits and challenges of disease early warning models, it is useful to understand how they are developed. A number of steps must occur for satellite data and imagery to be used to prevent disease outbreaks; each requires a variety of inputs and may include a range of experts and stakeholders. This paper discusses the inputs, outputs, and basic processes involved in each of six main steps to developing models, including: identifying and validating links between a disease and environmental factors, creating and validating a software model to predict outbreaks, transitioning a model to operational use, using a model operationally, and taking action on the data provided by the model. The paper briefly overviews past research regarding the link between remote sensing data and disease, and identifies ongoing research in academic centers around the world. The activities of three currently operational models are discussed, including the U.S. Department of Defense Global Emerging Infections Surveillance and Response System (DoD-GEIS), NASA carries out its Malaria Modeling and Surveillance program, and the The Mapping Malaria Risk in Africa (MARA) program. Based on the understanding of basic processes as well as the experience of currently operational programs, the paper offers a number of recommendations to governments and researchers for future development of operational disease early warning programs.

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.

Basic features of the predictive tools of early warning systems for water-related natural hazards: examples for shallow landslides

NASA Astrophysics Data System (ADS)

Greco, Roberto; Pagano, Luca

2017-12-01

To manage natural risks, an increasing effort is being put in the development of early warning systems (EWS), namely, approaches facing catastrophic phenomena by timely forecasting and alarm spreading throughout exposed population. Research efforts aimed at the development and implementation of effective EWS should especially concern the definition and calibration of the interpretative model. This paper analyses the main features characterizing predictive models working in EWS by discussing their aims and their features in terms of model accuracy, evolutionary stage of the phenomenon at which the prediction is carried out and model architecture. Original classification criteria based on these features are developed throughout the paper and shown in their practical implementation through examples of flow-like landslides and earth flows, both of which are characterized by rapid evolution and quite representative of many applications of EWS.

Non-stationary time series modeling on caterpillars pest of palm oil for early warning system

NASA Astrophysics Data System (ADS)

Setiyowati, Susi; Nugraha, Rida F.; Mukhaiyar, Utriweni

2015-12-01

The oil palm production has an important role for the plantation and economic sector in Indonesia. One of the important problems in the cultivation of oil palm plantation is pests which causes damage to the quality of fruits. The caterpillar pest which feed palm tree's leaves will cause decline in quality of palm oil production. Early warning system is needed to minimize losses due to this pest. Here, we applied non-stationary time series modeling, especially the family of autoregressive models to predict the number of pests based on its historical data. We realized that there is some uniqueness of these pests data, i.e. the spike value that occur almost periodically. Through some simulations and case study, we obtain that the selection of constant factor has a significance influence to the model so that it can shoot the spikes value precisely.

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 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.

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.

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.

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

Developing and testing an Early Warning System for Non Indigenous Species and Ballast Water Management

NASA Astrophysics Data System (ADS)

Magaletti, Erika; Garaventa, Francesca; David, Matej; Castriota, Luca; Kraus, Romina; Luna, Gian Marco; Silvestri, Cecilia; Forte, Cosmo; Bastianini, Mauro; Falautano, Manuela; Maggio, Teresa; Rak, Giulietta; Gollasch, Stephan

2018-03-01

This paper describes the methodological approach used for the development of an Early Warning System (EWS) for Non Indigenous Species (NIS) and ballast water management and summarizes the results obtained. The specific goals of the EWS are firstly to warn vessels to prevent loading of ballast water when critical biological conditions occur in ports and surrounding areas i.e. mass development or blooms of Harmful Aquatic Organisms and Pathogens (HAOP). Secondly, to warn environmental and health authorities when NIS or pathogens are present in ports or surrounding areas to enable an early response and an implementation of remediation measures. The EWS is designed to be used for implementing various parallel obligations, by taking into consideration different legal scopes, associated information and decision-making needs. The EWS was elaborated, tested in the Adriatic Sea and illustrated by two case studies. Although the EWS was developed with an Adriatic Sea focus, it is presented in a format so that it may be used as a model when establishing similar systems in other locations. The role of the various actors is discussed and recommendations on further developments of the EWS are presented. It was concluded that the EWS is a suitable tool to reduce the spread of potentially harmful and ballast water mediated species.

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

Research on early warning of food security using a system dynamics model: evidence from Jiangsu province in China.

PubMed

Xu, Jianling; Ding, Yi

2015-01-01

Analyzing the early warning of food security, this paper sets the self-sufficiency rate as the principal indicator in a standpoint of supplement. It is common to use the quantitative methods to forecast and warning the insecurity. However, this paper considers more about the probable outcome when the government intervenes. By constructing the causal feedbacks among grain supplement, demand, productive input, and the policy factors to simulate the future food security in Jiangsu province, conclusions can be drawn as the following: (1) The situation of food security is insecure if the self-sufficiency rate is under 68.3% according to the development of system inertia. (2) it is difficult to guarantee the food security in Jiangsu just depending on the increase of grain sown area. (3) The valid solution to ensure the food security in Jiangsu is to improve the productivity. © 2015 Institute of Food Technologists®

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.

Implementation of a Global Navigation Satellite System (GNSS) Augmentation to Tsunami Early Warning Systems

NASA Astrophysics Data System (ADS)

LaBrecque, John

2016-04-01

The Global Geodetic Observing System has issued a Call for Participation to research scientists, geodetic research groups and national agencies in support of the implementation of the IUGG recommendation for a Global Navigation Satellite System (GNSS) Augmentation to Tsunami Early Warning Systems. The call seeks to establish a working group to be a catalyst and motivating force for the definition of requirements, identification of resources, and for the encouragement of international cooperation in the establishment, advancement, and utilization of GNSS for Tsunami Early Warning. During the past fifteen years the populations of the Indo-Pacific region experienced a series of mega-thrust earthquakes followed by devastating tsunamis that claimed nearly 300,000 lives. The future resiliency of the region will depend upon improvements to infrastructure and emergency response that will require very significant investments from the Indo-Pacific economies. The estimation of earthquake moment magnitude, source mechanism and the distribution of crustal deformation are critical to rapid tsunami warning. Geodetic research groups have demonstrated the use of GNSS data to estimate earthquake moment magnitude, source mechanism and the distribution of crustal deformation sufficient for the accurate and timely prediction of tsunamis generated by mega-thrust earthquakes. GNSS data have also been used to measure the formation and propagation of tsunamis via ionospheric disturbances acoustically coupled to the propagating surface waves; thereby providing a new technique to track tsunami propagation across ocean basins, opening the way for improving tsunami propagation models, and providing accurate warning to communities in the far field. These two new advancements can deliver timely and accurate tsunami warnings to coastal communities in the near and far field of mega-thrust earthquakes. This presentation will present the justification for and the details of the GGOS Call for Participation.

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.

Developing the Framework for an Early Warning System for Ebola based on Environmental Conditions

NASA Astrophysics Data System (ADS)

Dartevelle, Sebastien; Nguy-Robertson, Anthony; Bell, Jesse; Chretien, Jean-Paul

2017-04-01

The 2014-2016 Ebola outbreak in West Africa indicated that this lethal disease can become a National Security issue as it crossed boarders and taxed regional health care systems. Ebola symptoms are also similar to other endemic diseases. Thus, forewarning of its possible presence can alert local public health facilities and populations, and may thereby reduce response time. Early work by our group has identified local climate (e.g. temperature, precipitation) and vegetation health (e.g. remote sensing using normalized difference vegetation index, NDVI) variables as leading indicators to known historical Ebola outbreaks. The environmental stress placed on the system as it reaches a climatic tipping point provides optimal conditions for spillover of Ebola virus from the reservoir host (which is unknown but suspected to be bats) to humans. This work outlines a framework for an approach to provide early warning maps based on the present state of the environment. Time series data from Climate Forecast System ver. 2 and AVHRR and MODIS satellite sensors are the basis for the early warning models used. These maps can provide policy makers and local health care professionals timely information for disease surveillance and preparation for future Ebola outbreaks.

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.

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.

Prediction of line failure fault based on weighted fuzzy dynamic clustering and improved relational analysis

NASA Astrophysics Data System (ADS)

Meng, Xiaocheng; Che, Renfei; Gao, Shi; He, Juntao

2018-04-01

With the advent of large data age, power system research has entered a new stage. At present, the main application of large data in the power system is the early warning analysis of the power equipment, that is, by collecting the relevant historical fault data information, the system security is improved by predicting the early warning and failure rate of different kinds of equipment under certain relational factors. In this paper, a method of line failure rate warning is proposed. Firstly, fuzzy dynamic clustering is carried out based on the collected historical information. Considering the imbalance between the attributes, the coefficient of variation is given to the corresponding weights. And then use the weighted fuzzy clustering to deal with the data more effectively. Then, by analyzing the basic idea and basic properties of the relational analysis model theory, the gray relational model is improved by combining the slope and the Deng model. And the incremental composition and composition of the two sequences are also considered to the gray relational model to obtain the gray relational degree between the various samples. The failure rate is predicted according to the principle of weighting. Finally, the concrete process is expounded by an example, and the validity and superiority of the proposed method are verified.

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.

Vulnerability analysis for a drought Early Warning System

NASA Astrophysics Data System (ADS)

Angeluccetti, Irene; Demarchi, Alessandro; Perez, Francesca

2014-05-01

Early Warning Systems (EWS) for drought are often based on risk models that do not, or marginally, take into account the vulnerability factor. The multifaceted nature of drought (hydrological, meteorological, and agricultural) is source of coexistence for different ways to measure this phenomenon and its effects. The latter, together with the complexity of impacts generated by this hazard, causes the current underdevelopment of drought EWS compared to other hazards. In Least Developed Countries, where drought events causes the highest numbers of affected people, the importance of correct monitoring and forecasting is considered essential. Existing early warning and monitoring systems for drought produced at different geographic levels, provide only in a few cases an actual spatial model that tries to describe the cause-effect link between where the hazard is detected and where impacts occur. Integrate vulnerability information in such systems would permit to better estimate affected zones and livelihoods, improving the effectiveness of produced hazard-related datasets and maps. In fact, the need of simplification and, in general, of a direct applicability of scientific outputs is still a matter of concern for field experts and early warning products end-users. Even if the surplus of hazard related information produced right after catastrophic events has, in some cases, led to the creation of specific data-sharing platforms, the conveyed meaning and usefulness of each product has not yet been addressed. The present work is an attempt to fill this gap which is still an open issue for the scientific community as well as for the humanitarian aid world. The study aims at conceiving a simplified vulnerability model to embed into an existing EWS for drought, which is based on the monitoring of vegetation phenological parameters and the Standardized Precipitation Index, both produced using free satellite derived datasets. The proposed vulnerability model includes (i) a pure agricultural vulnerability and (ii) a systemic vulnerability. The first considers the agricultural potential of terrains, the diversity of cultivated crops and the percentage of irrigated area as main driving factors. The second vulnerability aspect consists of geographic units in which a set of socio-economic factors are modeled geographically on the basis of the physical accessibility to market centers in one case, and according to a spatial gravity model of market areas in another case. Results of the model applied to a case study (Niger) and evaluated with food insecurity data, are presented.

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.

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.

A Drought Early Warning System Using System Dynamics Model and Seasonal Climate Forecasts: a case study in Hsinchu, Taiwan.

NASA Astrophysics Data System (ADS)

Tien, Yu-Chuan; Tung, Ching-Ping; Liu, Tzu-Ming; Lin, Chia-Yu

2016-04-01

In the last twenty years, Hsinchu, a county of Taiwan, has experienced a tremendous growth in water demand due to the development of Hsinchu Science Park. In order to fulfill the water demand, the government has built the new reservoir, Baoshan second reservoir. However, short term droughts still happen. One of the reasons is that the water level of the reservoirs in Hsinchu cannot be reasonably forecasted, which sometimes even underestimates the severity of drought. The purpose of this study is to build a drought early warning system that projects the water levels of two important reservoirs, Baoshan and Baoshan second reservoir, and also the spatial distribution of water shortagewith the lead time of three months. Furthermore, this study also attempts to assist the government to improve water resources management. Hence, a system dynamics model of Touchien River, which is the most important river for public water supply in Hsinchu, is developed. The model consists of several important subsystems, including two reservoirs, water treatment plants and agricultural irrigation districts. Using the upstream flow generated by seasonal weather forecasting data, the model is able to simulate the storage of the two reservoirs and the distribution of water shortage. Moreover, the model can also provide the information under certain emergency scenarios, such as the accident or failure of a water treatment plant. At last, the performance of the proposed method and the original water resource management method that the government used were also compared. Keyword: Water Resource Management, Hydrology, Seasonal Climate Forecast, Reservoir, Early Warning, Drought

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.

Design of early warning system for nuclear preparedness case study at Serpong

NASA Astrophysics Data System (ADS)

Farid, M. M.; Prawito, Susila, I. P.; Yuniarto, A.

2017-07-01

One effort to protect the environment from the increasing of potentially environmental radiation hazards as an impact of radiation discharge around nuclear facilities is by a continuous monitoring of the environmental radiation in real time It is important to disclose the dose rate information to public or authorities for radiological protection. In this research, we have designed a nuclear preparedness early warning system around the Serpong nuclear facility. The design is based on Arduino program, general packet radio service (GPRS) shield, and radio frequencies technology to transmit environmental radiation result of the measurement and meteorological data. Data was collected at a certain location at The Center for Informatics and Nuclear Strategic Zone Utilization BATAN Serpong. The system consistency models are defined by the quality of data and the level of radiation exposure in the deployed environment. Online users can access the website which displays the radiation dose on the environment marked on Google Map. This system is capable to issue an early warning emergency when the dose reaches three times of the background radiation exposure value, 250 nSv/hour.

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 flexible hydrological warning system in Denmark for real-time surface water and groundwater simulations

NASA Astrophysics Data System (ADS)

He, Xin; Stisen, Simon; Wiese, Marianne B.; Jørgen Henriksen, Hans

2015-04-01

In Denmark, increasing focus on extreme weather events has created considerable demand for short term forecasts and early warnings in relation to groundwater and surface water flooding. The Geological Survey of Denmark and Greenland (GEUS) has setup, calibrated and applied a nationwide water resources model, the DK-Model, primarily for simulating groundwater and surface water flows and groundwater levels during the past 20 years. So far, the DK-model has only been used in offline historical and future scenario simulations. Therefore, challenges arise in operating such a model for online forecasts and early warnings, which requires access to continuously updated observed climate input data and forecast data of precipitation, temperature and global radiation for the next 48 hours or longer. GEUS has a close collaboration with the Danish Meteorological Institute in order to test and enable this data input for the DK model. Due to the comprehensive physical descriptions of the DK-Model, the simulation results can potentially be any component of the hydrological cycle within the models domain. Therefore, it is important to identify which results need to be updated and saved in the real-time mode, since it is not computationally economical to save every result considering the heavy load of data. GEUS have worked closely with the end-users and interest groups such as water planners and emergency managers from the municipalities, water supply and waste water companies, consulting companies and farmer organizations, in order to understand their possible needs for real time simulation and monitoring of the nationwide water cycle. This participatory process has been supported by a web based questionnaire survey, and a workshop that connected the model developers and the users. For qualifying the stakeholder engagement, GEUS has selected a representative catchment area (Skjern River) for testing and demonstrating a prototype of the web based hydrological warning system at the workshop, and illustrated simulated groundwater levels, streamflow and water content in the root zone. The webpages can be tailor-made to meet the requirements of the end-users and also enable flexibility to extend while the users' demand changes. The active involvement of stakeholders in the workshop provided very valuable insights and feedbacks for GEUS, relevant for the future development of the nationwide real-time modeling and water cycle monitoring system for Denmark, including possible linking to early warning and real-time forecasting systems operating at the local scale.

[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 Hidden Markov Model for Analysis of Frontline Veterinary Data for Emerging Zoonotic Disease Surveillance

PubMed Central

Robertson, Colin; Sawford, Kate; Gunawardana, Walimunige S. N.; Nelson, Trisalyn A.; Nathoo, Farouk; Stephen, Craig

2011-01-01

Surveillance systems tracking health patterns in animals have potential for early warning of infectious disease in humans, yet there are many challenges that remain before this can be realized. Specifically, there remains the challenge of detecting early warning signals for diseases that are not known or are not part of routine surveillance for named diseases. This paper reports on the development of a hidden Markov model for analysis of frontline veterinary sentinel surveillance data from Sri Lanka. Field veterinarians collected data on syndromes and diagnoses using mobile phones. A model for submission patterns accounts for both sentinel-related and disease-related variability. Models for commonly reported cattle diagnoses were estimated separately. Region-specific weekly average prevalence was estimated for each diagnoses and partitioned into normal and abnormal periods. Visualization of state probabilities was used to indicate areas and times of unusual disease prevalence. The analysis suggests that hidden Markov modelling is a useful approach for surveillance datasets from novel populations and/or having little historical baselines. PMID:21949763

Global Drought Services: Collaborations Toward an Information System for Early Warning

NASA Astrophysics Data System (ADS)

Hayes, M. J.; Pulwarty, R. S.; Svoboda, M.

2014-12-01

Drought is a hazard that lends itself well to diligent, sustained monitoring and early warning. However, unlike most hazards, the fact that droughts typically evolve slowly, can last for months or years and cover vast areas spanning multiple political boundaries/jurisdictions and economic sectors can make it a daunting task to monitor, develop plans for, and identify appropriate, proactive mitigation strategies. The National Drought Mitigation Center (NDMC) and National Integrated Drought Information System (NIDIS) have been working together to reduce societal vulnerability to drought by helping decision makers at all levels to: 1) implement drought early warning/forecasting and decision support systems; 2) support and advocate for better collection of, and understanding of drought impacts; and 3) increase long-term resilience to drought through proactive planning. The NDMC and NIDIS risk management approach has been the basis from which many partners around the world are developing a collaboration and coordination nexus with an ultimate goal of building comprehensive global drought early warning information systems (GDEWIS). The core emphasis of this model is on developing and applying useful and usable information that can be integrated and transferred freely to other regions around the globe. The High-Level Ministerial Declaration on Drought, the Integrated Drought Management Programme (IDMP) co-led by the WMO and the Global Water Partnership (GWP), and the Global Framework for Climate Services are drawing extensively from the integrated NDMC-NIDIS risk management framework. This presentation will describe, in detail, the various drought resources, tools, services, and collaborations already being provided and undertaken at the national and regional scales by the NDMC, NIDIS, and their partners. The presentation will be forward-looking, identifying improvements in existing and proposed mechanisms to help strengthen national and international drought early warning information systems to support preparedness and adaptation decisions in a changing climate.

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.

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.

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.

Design of flood early warning system with wifi network based on smartphone

NASA Astrophysics Data System (ADS)

Supani, Ahyar; Andriani, Yuli; Taqwa, Ahmad

2017-11-01

Today, the development using internet of things enables activities surrounding us to be monitored, controlled, predicted and calculated remotely through connections to the internet network such as monitoring activities of long-distance flood warning with information technology. Applying an information technology in the field of flood early warning has been developed in the world, either connected to internet network or not. The internet network that has been done in this paper is the design of WiFi network to access data of rainfall, water level and flood status at any time with a smartphone coming from flood early warning system. The results obtained when test of data accessing with smartphone are in form of rainfall and water level graphs against time and flood status indicators consisting of 3 flood states: Standby 2, Standby 1 and Flood. It is concluded that data are from flood early warning system has been able to accessed and displayed on smartphone via WiFi network in any time and real time.

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.

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.

The Applicability of Herman's and Chomsky's Propaganda Model Today

ERIC Educational Resources Information Center

Model, David

2005-01-01

Since the early twentieth century, there have been numerous warnings about the dangers of the growing concentration of corporate ownership of the mass media. As early as 1920, Walter Lippmann claimed that propaganda was already "...a regular organ of popular government." He referred to the propaganda in the media as the…

Climate related natural hazards management in the vulnerable regions of Uzbekistan - experiences in the frame of projects Climate Risk Management in Uzbekistan (CRM-Uz) and Water in Central Asia (CAWa)

NASA Astrophysics Data System (ADS)

Merkushkin, Alexander; Gafurov, Abror; Agaltseva, Natalya; Pak, Alexander; Mannig, Birgit; Paeth, Heiko; Vorogushyn, Sergiy; Unger-Shayesteh, Katy

2014-05-01

Increased frequency of natural hazards under conditions of observed climate change in Uzbekistan has become challenging concern and shows the need to develop more effective climate risk mechanisms towards improving the security of society and sustainable development. In the framework of presented study, the importance of drought monitoring and methodologies for early warning for such purposes in Uzbekistan are demonstrated. For the conditions of Uzbekistan, droughts are most dangerous climate related natural phenomenon. Therefore, the CRM-Uz Project on Climate Risk Management was established with focus on reducing climate risks, strengthening adaptive capacity for stimulating the development of early warning mechanisms, as well as to build up the basis for long-term investments. This serves to increase resilience to climate impacts in the country. In the frame of the CRM-Uz Project, Drought Early Warning System (DEWS), has been developed and implemented in one of the southern provinces of Uzbekistan (Kashkadarya). The main task of DEWS is to provide population with information on the possibility of upcoming drought season in advance. DEWS is used for the assessment, monitoring, prevention, early warning and decision making in this region. Such early warning system provides the required information to undertake appropriate measures against drought and to mitigate its adverse effects to society. It is clear that during years with expected drought the hydrological forecasts become much more important. Complex mathematical model which simulates of run-off formation as a basis of DEWS provides the seasonal hydrological forecasts that are used to inform all concerned sectors, especially the agricultural sector on water availability during the vegetation period. In the frame of cooperation with German Research Centre for Geosciences (GFZ) within the CAWa Project, the DEWS was extended through implementation of MODSNOW - the operational tool for snow cover monitoring at the Drought Monitoring Centre at UzHydromet. The upgrade of the DEWS withMODSNOW strengthens DEWS's capacity in terms of improvement the hydrological forecasting. Moreover, based on climate scenarios provided within the CAWa project by the University of Würzburg, the regional hydrological model AISHF was used to asses medium and long term water availability in the Kashkadarya River which indicates a reduction of water resources in the selected basin in the future.

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)

Early Warning Signals of Social Transformation: A Case Study from the US Southwest.

PubMed

Spielmann, Katherine A; Peeples, Matthew A; Glowacki, Donna M; Dugmore, Andrew

2016-01-01

Recent research in ecology suggests that generic indicators, referred to as early warning signals (EWS), may occur before significant transformations, both critical and non-critical, in complex systems. Up to this point, research on EWS has largely focused on simple models and controlled experiments in ecology and climate science. When humans are considered in these arenas they are invariably seen as external sources of disturbance or management. In this article we explore ways to include societal components of socio-ecological systems directly in EWS analysis. Given the growing archaeological literature on 'collapses,' or transformations, in social systems, we investigate whether any early warning signals are apparent in the archaeological records of the build-up to two contemporaneous cases of social transformation in the prehistoric US Southwest, Mesa Verde and Zuni. The social transformations in these two cases differ in scope and severity, thus allowing us to explore the contexts under which warning signals may (or may not) emerge. In both cases our results show increasing variance in settlement size before the transformation, but increasing variance in social institutions only before the critical transformation in Mesa Verde. In the Zuni case, social institutions appear to have managed the process of significant social change. We conclude that variance is of broad relevance in anticipating social change, and the capacity of social institutions to mitigate transformation is critical to consider in EWS research on socio-ecological systems.

The Early-Warning System for incoming storm surge and tide in the Republic of Mauritius

NASA Astrophysics Data System (ADS)

Bogaard, Tom; de Lima Rego, Joao; Vatvani, Deepak; Virasami, Renganaden; Verlaan, Martin

2016-04-01

The Republic of Mauritius (ROM) is a group of islands in the South West of the Indian Ocean, consisting of the main islands of Mauritius, Rodrigues and Agalega and the archipelago of Saint Brandon. The ROM is particularly vulnerable to the adverse effects of climate change, especially in the coastal zone, where a convergence of accelerating sea level rise and increasing intensity of tropical cyclones is expected to result in considerable economic loss, humanitarian stresses, and environmental degradation. Storm surges and swell waves are expected to be aggravated through sea level rise and climate change effects on weather patterns. Adaptation to increased vulnerability requires a re-evaluation of existing preparedness measures. The focus of this project is on more effective preparedness and issuing of alerts developing a fully-automated Early-Warning System for incoming storm surge and tide, together with the Mauritius Meteorological Services and the National Disaster Risk Reduction and Management Centre (NDRRMC), such that coastal communities in Mauritius, Rodrigues and Agalega Islands are able to evacuate timely and safely in case of predicted extreme water levels. The Mauritius Early-Warning System for storm surge and tide was implemented using software from Deltares' Open-Source and free software Community. A set of five depth-averaged Delft3D-FLOW hydrodynamic models are run every six-hours with a forecast horizon of three days, simulating water levels along the coast of the three main islands. Two regional models of horizontal resolution 5km force the three detailed models of 500m resolution; all models are forced at the surface by the 0.25° NOAA/GFS meteorological forecasts. In addition, our Wind-Enhancement Scheme is used to blend detailed cyclone track bulletin's info with the larger-scale Numerical Weather Predictions. Measured data is retrieved near real-time from available Automatic Weather Stations. All these workflows are managed by the operational platform software, Delft-FEWS. The presently operational Mauritius Early-Warning System produces a set of intuitive tables for each island, containing time- and space-varying information on threshold crossings by predicted water levels. At multiple locations for each island of the ROM, the operator is informed in one glance about the recommended preparedness level, from "Safe" to "Watch", "Alert" or "Warning" based on water level forecasts. The HTML page was designed together with the MMS and the NDRRMC, in order to be easy to interpret and disseminate by local authorities.

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.

Establishing an early warning alert and response network following the Solomon Islands tsunami in 2013.

PubMed

Bilve, Augustine; Nogareda, Francisco; Joshua, Cynthia; Ross, Lester; Betcha, Christopher; Durski, Kara; Fleischl, Juliet; Nilles, Eric

2014-11-01

On 6 February 2013, an 8.0 magnitude earthquake generated a tsunami that struck the Santa Cruz Islands, Solomon Islands, killing 10 people and displacing over 4700. A post-disaster assessment of the risk of epidemic disease transmission recommended the implementation of an early warning alert and response network (EWARN) to rapidly detect, assess and respond to potential outbreaks in the aftermath of the tsunami. Almost 40% of the Santa Cruz Islands' population were displaced by the disaster, and living in cramped temporary camps with poor or absent sanitation facilities and insufficient access to clean water. There was no early warning disease surveillance system. By 25 February, an EWARN was operational in five health facilities that served 90% of the displaced population. Eight priority diseases or syndromes were reported weekly; unexpected health events were reported immediately. Between 25 February and 19 May, 1177 target diseases or syndrome cases were reported. Seven alerts were investigated. No sustained transmission or epidemics were identified. Reporting compliance was 85%. The EWARN was then transitioned to the routine four-syndrome early warning disease surveillance system. It was necessary to conduct a detailed assessment to evaluate the risk and potential impact of serious infectious disease outbreaks, to assess whether and how enhanced early warning disease surveillance should be implemented. Local capacities and available resources should be considered in planning EWARN implementation. An EWARN can be an opportunity to establish or strengthen early warning disease surveillance capabilities.

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;

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.

Implementation of the Geological Hazard Monitoring and Early Warning System Based on Multi - source Data -A Case Study of Deqin Tibetan County, Yunnan Province

NASA Astrophysics Data System (ADS)

Zhao, Junsan; Chen, Guoping; Yuan, Lei

2017-04-01

The new technologies, such as 3D laser scanning, InSAR, GNSS, unmanned aerial vehicle and Internet of things, will provide much more data resources for the surveying and monitoring, as well as the development of Early Warning System (EWS). This paper provides the solutions of the design and implementation of a geological disaster monitoring and early warning system (GDMEWS), which includes landslides and debris flows hazard, based on the multi-sources of the date by use of technologies above mentioned. The complex and changeable characteristics of the GDMEWS are described. The architecture of the system, composition of the multi-source database, development mode and service logic, the methods and key technologies of system development are also analyzed. To elaborate the process of the implementation of the GDMEWS, Deqin Tibetan County is selected as a case study area, which has the unique terrain and diverse types of typical landslides and debris flows. Firstly, the system functional requirements, monitoring and forecasting models of the system are discussed. Secondly, the logic relationships of the whole process of disaster including pre-disaster, disaster rescue and post-disaster reconstruction are studied, and the support tool for disaster prevention, disaster reduction and geological disaster management are developed. Thirdly, the methods of the multi - source monitoring data integration and the generation of the mechanism model of Geological hazards and simulation are expressed. Finally, the construction of the GDMEWS is issued, which will be applied to management, monitoring and forecasting of whole disaster process in real-time and dynamically in Deqin Tibetan County. Keywords: multi-source spatial data; geological disaster; monitoring and warning system; Deqin Tibetan County

Regional early flood warning system: design and implementation

NASA Astrophysics Data System (ADS)

Chang, L. C.; Yang, S. N.; Kuo, C. L.; Wang, Y. F.

2017-12-01

This study proposes a prototype of the regional early flood inundation warning system in Tainan City, Taiwan. The AI technology is used to forecast multi-step-ahead regional flood inundation maps during storm events. The computing time is only few seconds that leads to real-time regional flood inundation forecasting. A database is built to organize data and information for building real-time forecasting models, maintaining the relations of forecasted points, and displaying forecasted results, while real-time data acquisition is another key task where the model requires immediately accessing rain gauge information to provide forecast services. All programs related database are constructed in Microsoft SQL Server by using Visual C# to extracting real-time hydrological data, managing data, storing the forecasted data and providing the information to the visual map-based display. The regional early flood inundation warning system use the up-to-date Web technologies driven by the database and real-time data acquisition to display the on-line forecasting flood inundation depths in the study area. The friendly interface includes on-line sequentially showing inundation area by Google Map, maximum inundation depth and its location, and providing KMZ file download of the results which can be watched on Google Earth. The developed system can provide all the relevant information and on-line forecast results that helps city authorities to make decisions during typhoon events and make actions to mitigate the losses.

Experiences from coordinated national-level landslide and flood forecasting in Norway

NASA Astrophysics Data System (ADS)

Krøgli, Ingeborg; Fleig, Anne; Glad, Per; Dahl, Mads-Peter; Devoli, Graziella; Colleuille, Hervé

2015-04-01

While flood forecasting at national level is quite well established and operational in many countries worldwide, landslide forecasting at national level is still seldom. Examples of coordinated flood and landslide forecasting are even rarer. Most of the time flood and landslide forecasters work separately (investigating, defining thresholds, and developing models) and most of the time without communication with each other. One example of coordinated operational early warning systems (EWS) for flooding and shallow landslides is found at the Norwegian Water Resources and Energy Directorate (NVE) in Norway. In this presentation we give an introduction to the two separate but tightly collaborative EWSs and to the coordination of these. The two EWSs are being operated from the same office, every day using similar hydro-meteorological prognosis and hydrological models. Prognosis and model outputs on e.g. discharge, snow melt, soil water content and exceeded landslide thresholds are evaluated in a web based decision-making tool (xgeo.no). The experts performing forecasts are hydrologists, geologists and physical geographers. A similar warning scale, based on colors (green, yellow, orange and red) is used for both EWSs, however thresholds for flood and landslide warning levels are defined differently. Also warning areas may not necessary be the same for both hazards and depending on the specific meteorological event, duration of the warning periods can differ. We present how knowledge, models and tools, but also human and economic resources are being shared between the two EWSs. Moreover, we discuss challenges faced in the communication of warning messages using recent flood and landslide events as examples.

Research on Climate and Dengue in Malaysia: A Systematic Review.

PubMed

Hii, Yien Ling; Zaki, Rafdzah Ahmad; Aghamohammadi, Nasrin; Rocklöv, Joacim

2016-03-01

Dengue is a climate-sensitive infectious disease. Climate-based dengue early warning may be a simple, low-cost, and effective tool for enhancing surveillance and control. Scientific studies on climate and dengue in local context form the basis for advancing the development of a climate-based early warning system. This study aims to review the current status of scientific studies in climate and dengue and the prospect or challenges of such research on a climate-based dengue early warning system in a dengue-endemic country, taking Malaysia as a case study. We reviewed the relationship between climate and dengue derived from statistical modeling, laboratory tests, and field studies. We searched electronic databases including PubMed, Scopus, EBSCO (MEDLINE), Web of Science, and the World Health Organization publications, and assessed climate factors and their influence on dengue cases, mosquitoes, and virus and recent development in the field of climate and dengue. Few studies in Malaysia have emphasized the relationship between climate and dengue. Climatic factors such as temperature, rainfall, and humidity are associated with dengue; however, these relationships were not consistent. Climate change projections for Malaysia show a mounting risk for dengue in the future. Scientific studies on climate and dengue enhance dengue surveillance in the long run. It is essential for institutions in Malaysia to promote research on climate and vector-borne diseases to advance the development of climate-based early warning systems. Together, effective strategies that improve existing research capacity, maximize the use of limited resources, and promote local-international partnership are crucial for sustaining research on climate and health.

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.

Bridging Empirical and Physical Approaches for Landslide Monitoring and Early Warning

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia; Peters-Lidard, Christa; Adler, Robert; Kumar, Sujay; Harrison, Ken

2011-01-01

Rainfall-triggered landslides typically occur and are evaluated at local scales, using slope-stability models to calculate coincident changes in driving and resisting forces at the hillslope level in order to anticipate slope failures. Over larger areas, detailed high resolution landslide modeling is often infeasible due to difficulties in quantifying the complex interaction between rainfall infiltration and surface materials as well as the dearth of available in situ soil and rainfall estimates and accurate landslide validation data. This presentation will discuss how satellite precipitation and surface information can be applied within a landslide hazard assessment framework to improve landslide monitoring and early warning by considering two disparate approaches to landslide hazard assessment: an empirical landslide forecasting algorithm and a physical slope-stability model. The goal of this research is to advance near real-time landslide hazard assessment and early warning at larger spatial scales. This is done by employing high resolution surface and precipitation information within a probabilistic framework to provide more physically-based grounding to empirical landslide triggering thresholds. The empirical landslide forecasting tool, running in near real-time at http://trmm.nasa.gov, considers potential landslide activity at the global scale and relies on Tropical Rainfall Measuring Mission (TRMM) precipitation data and surface products to provide a near real-time picture of where landslides may be triggered. The physical approach considers how rainfall infiltration on a hillslope affects the in situ hydro-mechanical processes that may lead to slope failure. Evaluation of these empirical and physical approaches are performed within the Land Information System (LIS), a high performance land surface model processing and data assimilation system developed within the Hydrological Sciences Branch at NASA's Goddard Space Flight Center. LIS provides the capabilities to quantify uncertainty from model inputs and calculate probabilistic estimates for slope failures. Results indicate that remote sensing data can provide many of the spatiotemporal requirements for accurate landslide monitoring and early warning; however, higher resolution precipitation inputs will help to better identify small-scale precipitation forcings that contribute to significant landslide triggering. Future missions, such as the Global Precipitation Measurement (GPM) mission will provide more frequent and extensive estimates of precipitation at the global scale, which will serve as key inputs to significantly advance the accuracy of landslide hazard assessment, particularly over larger spatial scales.

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.

Autonomic nervous system activity as risk predictor in the medical emergency department: a prospective cohort study.

PubMed

Eick, Christian; Rizas, Konstantinos D; Meyer-Zürn, Christine S; Groga-Bada, Patrick; Hamm, Wolfgang; Kreth, Florian; Overkamp, Dietrich; Weyrich, Peter; Gawaz, Meinrad; Bauer, Axel

2015-05-01

To evaluate heart rate deceleration capacity, an electrocardiogram-based marker of autonomic nervous system activity, as risk predictor in a medical emergency department and to test its incremental predictive value to the modified early warning score. Prospective cohort study. Medical emergency department of a large university hospital. Five thousand seven hundred thirty consecutive patients of either sex in sinus rhythm, who were admitted to the medical emergency department of the University of Tübingen, Germany, between November 2010 and March 2012. None. Deceleration capacity of heart rate was calculated within the first minutes after emergency department admission. The modified early warning score was assessed from respiratory rate, heart rate, systolic blood pressure, body temperature, and level of consciousness as previously described. Primary endpoint was intrahospital mortality; secondary endpoints included transfer to the ICU as well as 30-day and 180-day mortality. One hundred forty-two patients (2.5%) reached the primary endpoint. Deceleration capacity was highly significantly lower in nonsurvivors than survivors (2.9 ± 2.1 ms vs 5.6 ± 2.9 ms; p < 0.001) and yielded an area under the receiver-operator characteristic curve of 0.780 (95% CI, 0.745-0.813). The modified early warning score model yielded an area under the receiver-operator characteristic curve of 0.706 (0.667-0.750). Implementing deceleration capacity into the modified early warning score model led to a highly significant increase of the area under the receiver-operator characteristic curve to 0.804 (0.770-0.835; p < 0.001 for difference). Deceleration capacity was also a highly significant predictor of 30-day and 180-day mortality as well as transfer to the ICU. Deceleration capacity is a strong and independent predictor of short-term mortality among patients admitted to a medical emergency department.

Development of a flood-induced health risk prediction model for Africa

NASA Astrophysics Data System (ADS)

Lee, D.; Block, P. J.

2017-12-01

Globally, many floods occur in developing or tropical regions where the impact on public health is substantial, including death and injury, drinking water, endemic disease, and so on. Although these flood impacts on public health have been investigated, integrated management of floods and flood-induced health risks is technically and institutionally limited. Specifically, while the use of climatic and hydrologic forecasts for disaster management has been highlighted, analogous predictions for forecasting the magnitude and impact of health risks are lacking, as is the infrastructure for health early warning systems, particularly in developing countries. In this study, we develop flood-induced health risk prediction model for African regions using season-ahead flood predictions with climate drivers and a variety of physical and socio-economic information, such as local hazard, exposure, resilience, and health vulnerability indicators. Skillful prediction of flood and flood-induced health risks can contribute to practical pre- and post-disaster responses in both local- and global-scales, and may eventually be integrated into multi-hazard early warning systems for informed advanced planning and management. This is especially attractive for areas with limited observations and/or little capacity to develop flood-induced health risk warning systems.

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.

Real-time 3-D space numerical shake prediction for earthquake early warning

NASA Astrophysics Data System (ADS)

Wang, Tianyun; Jin, Xing; Huang, Yandan; Wei, Yongxiang

2017-12-01

In earthquake early warning systems, real-time shake prediction through wave propagation simulation is a promising approach. Compared with traditional methods, it does not suffer from the inaccurate estimation of source parameters. For computation efficiency, wave direction is assumed to propagate on the 2-D surface of the earth in these methods. In fact, since the seismic wave propagates in the 3-D sphere of the earth, the 2-D space modeling of wave direction results in inaccurate wave estimation. In this paper, we propose a 3-D space numerical shake prediction method, which simulates the wave propagation in 3-D space using radiative transfer theory, and incorporate data assimilation technique to estimate the distribution of wave energy. 2011 Tohoku earthquake is studied as an example to show the validity of the proposed model. 2-D space model and 3-D space model are compared in this article, and the prediction results show that numerical shake prediction based on 3-D space model can estimate the real-time ground motion precisely, and overprediction is alleviated when using 3-D space model.

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.

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.

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.

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.

Future of Earthquake Early Warning: Quantifying Uncertainty and Making Fast Automated Decisions for Applications

NASA Astrophysics Data System (ADS)

Wu, Stephen

Earthquake early warning (EEW) systems have been rapidly developing over the past decade. Japan Meteorological Agency (JMA) has an EEW system that was operating during the 2011 M9 Tohoku earthquake in Japan, and this increased the awareness of EEW systems around the world. While longer-time earthquake prediction still faces many challenges to be practical, the availability of shorter-time EEW opens up a new door for earthquake loss mitigation. After an earthquake fault begins rupturing, an EEW system utilizes the first few seconds of recorded seismic waveform data to quickly predict the hypocenter location, magnitude, origin time and the expected shaking intensity level around the region. This early warning information is broadcast to different sites before the strong shaking arrives. The warning lead time of such a system is short, typically a few seconds to a minute or so, and the information is uncertain. These factors limit human intervention to activate mitigation actions and this must be addressed for engineering applications of EEW. This study applies a Bayesian probabilistic approach along with machine learning techniques and decision theories from economics to improve different aspects of EEW operation, including extending it to engineering applications. Existing EEW systems are often based on a deterministic approach. Often, they assume that only a single event occurs within a short period of time, which led to many false alarms after the Tohoku earthquake in Japan. This study develops a probability-based EEW algorithm based on an existing deterministic model to extend the EEW system to the case of concurrent events, which are often observed during the aftershock sequence after a large earthquake. To overcome the challenge of uncertain information and short lead time of EEW, this study also develops an earthquake probability-based automated decision-making (ePAD) framework to make robust decision for EEW mitigation applications. A cost-benefit model that can capture the uncertainties in EEW information and the decision process is used. This approach is called the Performance-Based Earthquake Early Warning, which is based on the PEER Performance-Based Earthquake Engineering method. Use of surrogate models is suggested to improve computational efficiency. Also, new models are proposed to add the influence of lead time into the cost-benefit analysis. For example, a value of information model is used to quantify the potential value of delaying the activation of a mitigation action for a possible reduction of the uncertainty of EEW information in the next update. Two practical examples, evacuation alert and elevator control, are studied to illustrate the ePAD framework. Potential advanced EEW applications, such as the case of multiple-action decisions and the synergy of EEW and structural health monitoring systems, are also discussed.

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…

Early-warning signals of critical transition: Effect of extrinsic noise

NASA Astrophysics Data System (ADS)

Qin, Shanshan; Tang, Chao

2018-03-01

Complex dynamical systems often have tipping points and exhibit catastrophic regime shift. Despite the notorious difficulty of predicting such transitions, accumulating studies have suggested the existence of generic early-warning signals (EWSs) preceding upcoming transitions. However, previous theories and models were based on the effect of the intrinsic noise (IN) when a system is approaching a critical point, and did not consider the pervasive environmental fluctuations or the extrinsic noise (EN). Here, we extend previous theory to investigate how the interplay of EN and IN affects EWSs. Stochastic simulations of model systems subject to both IN and EN have verified our theory and demonstrated that EN can dramatically alter and diminish the EWS. This effect is stronger with increasing amplitude and correlation time scale of the EN. In the presence of EN, the EWS can fail to predict or even give a false alarm of critical transitions.

Establishing an early warning alert and response network following the Solomon Islands tsunami in 2013

PubMed Central

Bilve, Augustine; Nogareda, Francisco; Joshua, Cynthia; Ross, Lester; Betcha, Christopher; Durski, Kara; Fleischl, Juliet

2014-01-01

Abstract Problem On 6 February 2013, an 8.0 magnitude earthquake generated a tsunami that struck the Santa Cruz Islands, Solomon Islands, killing 10 people and displacing over 4700. Approach A post-disaster assessment of the risk of epidemic disease transmission recommended the implementation of an early warning alert and response network (EWARN) to rapidly detect, assess and respond to potential outbreaks in the aftermath of the tsunami. Local setting Almost 40% of the Santa Cruz Islands’ population were displaced by the disaster, and living in cramped temporary camps with poor or absent sanitation facilities and insufficient access to clean water. There was no early warning disease surveillance system. Relevant changes By 25 February, an EWARN was operational in five health facilities that served 90% of the displaced population. Eight priority diseases or syndromes were reported weekly; unexpected health events were reported immediately. Between 25 February and 19 May, 1177 target diseases or syndrome cases were reported. Seven alerts were investigated. No sustained transmission or epidemics were identified. Reporting compliance was 85%. The EWARN was then transitioned to the routine four-syndrome early warning disease surveillance system. Lesson learnt It was necessary to conduct a detailed assessment to evaluate the risk and potential impact of serious infectious disease outbreaks, to assess whether and how enhanced early warning disease surveillance should be implemented. Local capacities and available resources should be considered in planning EWARN implementation. An EWARN can be an opportunity to establish or strengthen early warning disease surveillance capabilities. PMID:25378746

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.

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...

Control strategy to limit duty cycle impact of earthquakes on the LIGO gravitational-wave detectors

NASA Astrophysics Data System (ADS)

Biscans, S.; Warner, J.; Mittleman, R.; Buchanan, C.; Coughlin, M.; Evans, M.; Gabbard, H.; Harms, J.; Lantz, B.; Mukund, N.; Pele, A.; Pezerat, C.; Picart, P.; Radkins, H.; Shaffer, T.

2018-03-01

Advanced gravitational-wave detectors such as the laser interferometer gravitational-wave observatories (LIGO) require an unprecedented level of isolation from the ground. When in operation, they measure motion of less than 10‑19 m. Strong teleseismic events like earthquakes disrupt the proper functioning of the detectors, and result in a loss of data. An earthquake early-warning system, as well as a prediction model, have been developed to understand the impact of earthquakes on LIGO. This paper describes a control strategy to use this early-warning system to reduce the LIGO downtime by  ∼30%. It also presents a plan to implement this new earthquake configuration in the LIGO automation system.

Applying temporal abstraction and case-based reasoning to predict approaching influenza waves.

PubMed

Schmidt, Rainer; Gierl, Lothar

2002-01-01

The goal of the TeCoMed project is to send early warnings against forthcoming waves or even epidemics of infectious diseases, especially of influenza, to interested practitioners, pharmacists etc. in the German federal state Mecklenburg-Western Pomerania. The forecast of these waves is based on written confirmations of unfitness for work of the main German health insurance company. Since influenza waves are difficult to predict because of their cyclic but not regular behaviour, statistical methods based on the computation of mean values are not helpful. Instead, we have developed a prognostic model that makes use of similar former courses. Our method combines Case-based Reasoning with Temporal Abstraction to decide whether early warning is appropriate.

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.

Implementation of Malaria Dynamic Models in Municipality Level Early Warning Systems in Colombia. Part I: Description of Study Sites

PubMed Central

Ruiz, Daniel; Cerón, Viviana; Molina, Adriana M.; Quiñónes, Martha L.; Jiménez, Mónica M.; Ahumada, Martha; Gutiérrez, Patricia; Osorio, Salua; Mantilla, Gilma; Connor, Stephen J.; Thomson, Madeleine C.

2014-01-01

As part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System, the Colombian National Institute of Health is working on the design and implementation of a Malaria Early Warning System framework, supported by seasonal climate forecasting capabilities, weather and environmental monitoring, and malaria statistical and dynamic models. In this report, we provide an overview of the local ecoepidemiologic settings where four malaria process-based mathematical models are currently being implemented at a municipal level. The description includes general characteristics, malaria situation (predominant type of infection, malaria-positive cases data, malaria incidence, and seasonality), entomologic conditions (primary and secondary vectors, mosquito densities, and feeding frequencies), climatic conditions (climatology and long-term trends), key drivers of epidemic outbreaks, and non-climatic factors (populations at risk, control campaigns, and socioeconomic conditions). Selected pilot sites exhibit different ecoepidemiologic settings that must be taken into account in the development of the integrated surveillance and control system. PMID:24891460

Early warning and crop condition assessment research

NASA Technical Reports Server (NTRS)

Boatwright, G. O.; Whitehead, V. S.

1986-01-01

The Early Warning Crop Condition Assessment Project of AgRISTARS was a multiagency and multidisciplinary effort. Its mission and objectives were centered around development and testing of remote-sensing techniques that enhance operational methodologies for global crop-condition assessments. The project developed crop stress indicators models that provide data filter and alert capabilities for monitoring global agricultural conditions. The project developed a technique for using NOAA-n satellite advanced very-high-resolution radiometer (AVHRR) data for operational crop-condition assessments. This technology was transferred to the Foreign Agricultural Service of the USDA. The project developed a U.S. Great Plains data base that contains various meteorological parameters and vegetative index numbers (VIN) derived from AVHRR satellite data. It developed cloud screening techniques and scan angle correction models for AVHRR data. It also developed technology for using remotely acquired thermal data for crop water stress indicator modeling. The project provided basic technology including spectral characteristics of soils, water, stressed and nonstressed crop and range vegetation, solar zenith angle, and atmospheric and canopy structure effects.

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.

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.

Variability in soil-water retention properties and implications for physics-based simulation of landslide early warning criteria

USGS Publications Warehouse

Thomas, Matthew A.; Mirus, Benjamin B.; Collins, Brian D.; Lu, Ning; Godt, Jonathan W.

2018-01-01

Rainfall-induced shallow landsliding is a persistent hazard to human life and property. Despite the observed connection between infiltration through the unsaturated zone and shallow landslide initiation, there is considerable uncertainty in how estimates of unsaturated soil-water retention properties affect slope stability assessment. This source of uncertainty is critical to evaluating the utility of physics-based hydrologic modeling as a tool for landslide early warning. We employ a numerical model of variably saturated groundwater flow parameterized with an ensemble of texture-, laboratory-, and field-based estimates of soil-water retention properties for an extensively monitored landslide-prone site in the San Francisco Bay Area, CA, USA. Simulations of soil-water content, pore-water pressure, and the resultant factor of safety show considerable variability across and within these different parameter estimation techniques. In particular, we demonstrate that with the same permeability structure imposed across all simulations, the variability in soil-water retention properties strongly influences predictions of positive pore-water pressure coincident with widespread shallow landsliding. We also find that the ensemble of soil-water retention properties imposes an order-of-magnitude and nearly two-fold variability in seasonal and event-scale landslide susceptibility, respectively. Despite the reduced factor of safety uncertainty during wet conditions, parameters that control the dry end of the soil-water retention function markedly impact the ability of a hydrologic model to capture soil-water content dynamics observed in the field. These results suggest that variability in soil-water retention properties should be considered for objective physics-based simulation of landslide early warning criteria.

Development of Water Resources Drought Early Warning System

NASA Astrophysics Data System (ADS)

Chen, B. P. T.; Chen, C. H.

2017-12-01

Signs of impending drought are often vague and result from hydrologic uncertainty. Because of this, determining the appropriate time to enforce water supply restrictions is difficult. This study proposes a drought early warning index (DEWI) that can help water resource managers to anticipate droughts so that preparations can be made to mitigate the impact of water shortages. This study employs the expected-deficit-rate of normal water supply conditions as the drought early warning index. An annual-use-reservoir-based water supply system in southern Taiwan was selected as the case study. The water supply simulation was based on reservoir storage at the evaluation time and the reservoir inflow series to cope with the actual water supply process until the end of the hydrologic year. A variety of deficits could be realized during different hydrologic years of records and assumptions of initial reservoir storage. These deficits are illustrated using the Average Shortage Rate (ASR) and the value of the ASR, namely the DEWI. The ASR is divided into 5 levels according to 5 deficit-tolerance combinations of each kind of annual demand. A linear regression model and a Neuro-Fuzzy Computing Technique model were employed to estimate the DEWI using selected factors deduced from supply-demand traits and available information, including: rainfall, reservoir inflow and storage data. The chosen methods mentioned above are used to explain a significant index is useful for both model development and decision making. Tests in the Tsengwen-Wushantou reservoir system showed this DEWI to perform very well in adopting the proper mitigation policy at the end of the wet season.

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.

Evaluation of the effects of implementing an electronic early warning score system: protocol for a stepped wedge study.

PubMed

Bonnici, Timothy; Gerry, Stephen; Wong, David; Knight, Julia; Watkinson, Peter

2016-02-09

An Early Warning Score is a clinical risk score based upon vital signs intended to aid recognition of patients in need of urgent medical attention. The use of an escalation of care policy based upon an Early Warning Score is mandated as the standard of practice in British hospitals. Electronic systems for recording vital sign observations and Early Warning Score calculation offer theoretical benefits over paper-based systems. However, the evidence for their clinical benefit is limited. Previous studies have shown inconsistent results. The majority have employed a "before and after" study design, which may be strongly confounded by simultaneously occurring events. This study aims to examine how the implementation of an electronic early warning score system, System for Notification and Documentation (SEND), affects the recognition of clinical deterioration occurring in hospitalised adult patients. This study is a non-randomised stepped wedge evaluation carried out across the four hospitals of the Oxford University Hospitals NHS Trust, comparing charting on paper and charting using SEND. We assume that more frequent monitoring of acutely ill patients is associated with better recognition of patient deterioration. The primary outcome measure is the time between a patient's first observations set with an Early Warning Score above the alerting threshold and their subsequent set of observations. Secondary outcome measures are in-hospital mortality, cardiac arrest and Intensive Care admission rates, hospital length of stay and system usability measured using the System Usability Scale. We will also measure Intensive Care length of stay, Intensive Care mortality, Acute Physiology and Chronic Health Evaluation (APACHE) II acute physiology score on admission, to examine whether the introduction of SEND has any effect on Intensive Care-related outcomes. The development of this protocol has been informed by guidance from the Agency for Healthcare Research and Quality (AHRQ) Health Information Technology Evaluation Toolkit and Delone and McLeans's Model of Information System Success. Our chosen trial design, a stepped wedge study, is well suited to the study of a phased roll out. The choice of primary endpoint is challenging. We have selected the time from the first triggering observation set to the subsequent observation set. This has the benefit of being easy to measure on both paper and electronic charting and having a straightforward interpretation. We have collected qualitative measures of system quality via a user questionnaire and organisational descriptors to help readers understand the context in which SEND has been implemented.

Early Warning Signals of Social Transformation: A Case Study from the US Southwest

PubMed Central

2016-01-01

Recent research in ecology suggests that generic indicators, referred to as early warning signals (EWS), may occur before significant transformations, both critical and non-critical, in complex systems. Up to this point, research on EWS has largely focused on simple models and controlled experiments in ecology and climate science. When humans are considered in these arenas they are invariably seen as external sources of disturbance or management. In this article we explore ways to include societal components of socio-ecological systems directly in EWS analysis. Given the growing archaeological literature on ‘collapses,’ or transformations, in social systems, we investigate whether any early warning signals are apparent in the archaeological records of the build-up to two contemporaneous cases of social transformation in the prehistoric US Southwest, Mesa Verde and Zuni. The social transformations in these two cases differ in scope and severity, thus allowing us to explore the contexts under which warning signals may (or may not) emerge. In both cases our results show increasing variance in settlement size before the transformation, but increasing variance in social institutions only before the critical transformation in Mesa Verde. In the Zuni case, social institutions appear to have managed the process of significant social change. We conclude that variance is of broad relevance in anticipating social change, and the capacity of social institutions to mitigate transformation is critical to consider in EWS research on socio-ecological systems. PMID:27706200

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.

A Case Study of Array-based Early Warning System for Tsunami Offshore Ventura, California

NASA Astrophysics Data System (ADS)

Xie, Y.; Meng, L.

2017-12-01

Extreme scenarios of M 7.5+ earthquakes on the Red Mountain and Pitas Point faults can potentially generate significant local tsunamis in southern California. The maximum water elevation could be as large as 10 m in the nearshore region of Oxnard and Santa Barbara. Recent development in seismic array processing enables rapid tsunami prediction and early warning based on the back-projection approach (BP). The idea is to estimate the rupture size by back-tracing the seismic body waves recorded by stations at local and regional distances. A simplified source model of uniform slip is constructed and used as an input for tsunami simulations that predict the tsunami wave height and arrival time. We demonstrate the feasibility of this approach in southern California by implementing it in a simulated real-time environment and applying to a hypothetical M 7.7 Dip-slip earthquake scenario on the Pitas Point fault. Synthetic seismograms are produced using the SCEC broadband platform based on the 3D SoCal community velocity model. We use S-wave instead of P-wave to avoid S-minus-P travel times shorter than rupture duration. Two clusters of strong-motion stations near Bakersfield and Palmdale are selected to determine the back-azimuth of the strongest high-frequency radiations (0.5-1 Hz). The back-azimuths of the two clusters are then intersected to locate the source positions. The rupture area is then approximated by enclosing these BP radiators with an ellipse or a polygon. Our preliminary results show that the extent of 1294 square kilometers rupture area and magnitude of 7.6 obtained by this approach is reasonably close to the 1849 square kilometers and 7.7 of the input model. The average slip of 7.3 m is then estimated according to the scaling relation between slip and rupture area, which is close to the actual average dislocation amount, 8.3 m. Finally, a tsunami simulation is conducted to assess the wave height and arrival time. The errors of -3 to +9 s in arrival time and 0.4 m in wave amplitude are reasonably small for early warning purpose. The blind zone for early warning is the region north of the outcrop of Pitas Point faults and has a scale close to the length of the fault, 43 km. The warning time is above 15 min in the nearshore region west of Cojo Bay Beach and south of Oxnard.

Forecast of dengue incidence using temperature and rainfall.

PubMed

Hii, Yien Ling; Zhu, Huaiping; Ng, Nawi; Ng, Lee Ching; Rocklöv, Joacim

2012-01-01

An accurate early warning system to predict impending epidemics enhances the effectiveness of preventive measures against dengue fever. The aim of this study was to develop and validate a forecasting model that could predict dengue cases and provide timely early warning in Singapore. We developed a time series Poisson multivariate regression model using weekly mean temperature and cumulative rainfall over the period 2000-2010. Weather data were modeled using piecewise linear spline functions. We analyzed various lag times between dengue and weather variables to identify the optimal dengue forecasting period. Autoregression, seasonality and trend were considered in the model. We validated the model by forecasting dengue cases for week 1 of 2011 up to week 16 of 2012 using weather data alone. Model selection and validation were based on Akaike's Information Criterion, standardized Root Mean Square Error, and residuals diagnoses. A Receiver Operating Characteristics curve was used to analyze the sensitivity of the forecast of epidemics. The optimal period for dengue forecast was 16 weeks. Our model forecasted correctly with errors of 0.3 and 0.32 of the standard deviation of reported cases during the model training and validation periods, respectively. It was sensitive enough to distinguish between outbreak and non-outbreak to a 96% (CI = 93-98%) in 2004-2010 and 98% (CI = 95%-100%) in 2011. The model predicted the outbreak in 2011 accurately with less than 3% possibility of false alarm. We have developed a weather-based dengue forecasting model that allows warning 16 weeks in advance of dengue epidemics with high sensitivity and specificity. We demonstrate that models using temperature and rainfall could be simple, precise, and low cost tools for dengue forecasting which could be used to enhance decision making on the timing, scale of vector control operations, and utilization of limited resources.

Linking Research to Practice: FEWS NET and Its Use of Satellite Remote Sensing Data

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Brickley, Elizabeth B.

2011-01-01

The purpose of the Famine Early Warning Systems Network (FEWS NET) is to collaborate with international, regional and national partners to provide timely and rigorous early warning and vulnerability information on emerging and evolving food security issues

[Early detection on the onset of scarlet fever epidemics in Beijing, using the Cumulative Sum].

PubMed

Li, Jing; Yang, Peng; Wu, Shuang-sheng; Wang, Xiao-li; Liu, Shuang; Wang, Quan-yi

2013-05-01

Based on data related to scarlet fever which was collected from the Disease Surveillance Information Reporting System in Beijing from 2005 to 2011, to explore the efficiency of Cumulative Sum (CUSUM) in detecting the onset of scarlet fever epidemics. Models as C1-MILD (C1), C2-MEDIUM (C2) and C3-ULTRA (C3) were used. Tools for evaluation as Youden's index and detection time were calculated to optimize the parameters and optimal model. Data on 2011 scarlet fever surveillance was used to verify the efficacy of these models. C1 (k = 0.5, H = 2σ), C2 (k = 0.7, H = 2σ), C3 (k = 1.1, H = 2σ) appeared to be the optimal parameters among these models. Youden's index of C1 was 83.0% and detection time being 0.64 weeks, Youden's index of C2 was 85.4% and detection time being 1.27 weeks, Youden's index of C1 was 85.1% and detection time being 1.36 weeks. Among the three early warning detection models, C1 had the highest efficacy. Three models all triggered the signals within 4 weeks after the onset of scarlet fever epidemics. The early warning detection model of CUSUM could be used to detect the onset of scarlet fever epidemics, with good efficacy.

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.

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.

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

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.

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%.

Debris flow early warning systems in Norway: organization and tools

NASA Astrophysics Data System (ADS)

Kleivane, I.; Colleuille, H.; Haugen, L. E.; Alve Glad, P.; Devoli, G.

2012-04-01

In Norway, shallow slides and debris flows occur as a combination of high-intensity precipitation, snowmelt, high groundwater level and saturated soil. Many events have occurred in the last decades and are often associated with (or related to) floods events, especially in the Southern of Norway, causing significant damages to roads, railway lines, buildings, and other infrastructures (i.e November 2000; August 2003; September 2005; November 2005; Mai 2008; June and Desember 2011). Since 1989 the Norwegian Water Resources and Energy Directorate (NVE) has had an operational 24 hour flood forecasting system for the entire country. From 2009 NVE is also responsible to assist regions and municipalities in the prevention of disasters posed by landslides and snow avalanches. Besides assisting the municipalities through implementation of digital landslides inventories, susceptibility and hazard mapping, areal planning, preparation of guidelines, realization of mitigation measures and helping during emergencies, NVE is developing a regional scale debris flow warning system that use hydrological models that are already available in the flood warning systems. It is well known that the application of rainfall thresholds is not sufficient to evaluate the hazard for debris flows and shallow slides, and soil moisture conditions play a crucial role in the triggering conditions. The information on simulated soil and groundwater conditions and water supply (rain and snowmelt) based on weather forecast, have proved to be useful variables that indicate the potential occurrence of debris flows and shallow slides. Forecasts of runoff and freezing-thawing are also valuable information. The early warning system is using real-time measurements (Discharge; Groundwater level; Soil water content and soil temperature; Snow water equivalent; Meteorological data) and model simulations (a spatially distributed version of the HBV-model and an adapted version of 1-D soil water and energy balance model COUP). The data are presented in a web- and GIS-based system with daily nationwide maps showing the meteorological and hydrological conditions for the present and the near future from quantitative weather prognosis. In addition a division of the country in homogenous debris flow-prone regions is also under progress based on geomorfological, topographic parameters and loose quaternary deposits distribution. Threshold-levels are being investigated by using statistical analyses of historical debris flows events and measured hydro-meteorological parameters. The debris flow early warning system is currently being tested and is expected to be operational in 2013. Final products will be warning messages and a map showing the different hazard levels, from low to high, indicating the landslide probability and the type of expected damages in a certain area. Many activities are realized in strong collaboration with the road and railway authorities, the geological survey and private consultant companies.

The 2014 Mw 6.0 Napa Earthquake, California: Observations from Real-time GPS-enhanced Earthquake Early Warning

NASA Astrophysics Data System (ADS)

Johanson, I. A.; Grapenthin, R.; Allen, R. M.

2014-12-01

Recently, progress has been made to demonstrate feasibility and benefits of including real-time GPS (rtGPS) in earthquake early warning and rapid response systems. While most concepts have yet to be integrated into operational environments, the Berkeley Seismological Laboratory is currently running an rtGPS based finite fault inversion scheme in true real-time, which is triggered by the seismic-based ShakeAlert system and then sends updated earthquake alerts to a test receiver. The Geodetic Alarm System (G-larmS) was online and responded to the 2014 Mw6.0 South Napa earthquake in California. We review G-larmS' performance during this event and for 13 aftershocks, and we present rtGPS observations and real-time modeling results for the main shock. The first distributed slip model and a magnitude estimate of Mw5.5 were available 24 s after the event origin time, which could be reduced to 14 s after a bug fix (~8 s S-wave travel time, ~6 s data latency). The system continued to re-estimate the magnitude once every second: it increased to Mw5.9 3 s after the first alert and stabilized at Mw5.8 after 15 s. G-larmS' solutions for the subsequent small magnitude aftershocks demonstrate that Mw~6.0 is the current limit for alert updates to contribute back to the seismic-based early warning system.

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 ...

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.

[Early warning on measles through the neural networks].

PubMed

Yu, Bin; Ding, Chun; Wei, Shan-bo; Chen, Bang-hua; Liu, Pu-lin; Luo, Tong-yong; Wang, Jia-gang; Pan, Zhi-wei; Lu, Jun-an

2011-01-01

To discuss the effects on early warning of measles, using the neural networks. Based on the available data through monthly and weekly reports on measles from January 1986 to August 2006 in Wuhan city. The modal was developed using the neural networks to predict and analyze the prevalence and incidence of measles. When the dynamic time series modal was established with back propagation (BP) networks consisting of two layers, if p was assigned as 9, the convergence speed was acceptable and the correlation coefficient was equal to 0.85. It was more acceptable for monthly forecasting the specific value, but better for weekly forecasting the classification under probabilistic neural networks (PNN). When data was big enough to serve the purpose, it seemed more feasible for early warning using the two-layer BP networks. However, when data was not enough, then PNN could be used for the purpose of prediction. This method seemed feasible to be used in the system for early warning.

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.

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.

Tsunami prevention and mitigation necessities and options derived from tsunami risk assessment in Indonesia

NASA Astrophysics Data System (ADS)

Post, J.; Zosseder, K.; Wegscheider, S.; Steinmetz, T.; Mück, M.; Strunz, G.; Riedlinger, T.; Anwar, H. Z.; Birkmann, J.; Gebert, N.

2009-04-01

Risk and vulnerability assessment is an important component of an effective End-to-End Tsunami Early Warning System and therefore contributes significantly to disaster risk reduction. Risk assessment is a key strategy to implement and design adequate disaster prevention and mitigation measures. The knowledge about expected tsunami hazard impacts, exposed elements, their susceptibility, coping and adaptation mechanisms is a precondition for the development of people-centred warning structures, local specific response and recovery policy planning. The developed risk assessment and its components reflect the disaster management cycle (disaster time line) and cover the early warning as well as the emergency response phase. Consequently the components hazard assessment, exposure (e.g. how many people/ critical facilities are affected?), susceptibility (e.g. are the people able to receive a tsunami warning?), coping capacity (are the people able to evacuate in time?) and recovery (are the people able to restore their livelihoods?) are addressed and quantified. Thereby the risk assessment encompasses three steps: (i) identifying the nature, location, intensity and probability of potential tsunami threats (hazard assessment); (ii) determining the existence and degree of exposure and susceptibility to those threats; and (iii) identifying the coping capacities and resources available to address or manage these threats. The paper presents results of the research work, which is conducted in the framework of the GITEWS project and the Joint Indonesian-German Working Group on Risk Modelling and Vulnerability Assessment. The assessment methodology applied follows a people-centred approach to deliver relevant risk and vulnerability information for the purposes of early warning and disaster management. The analyses are considering the entire coastal areas of Sumatra, Java and Bali facing the Sunda trench. Selected results and products like risk maps, guidelines, decision support information and other GIS products will be presented. The focus of the products is on the one hand to provide relevant risk assessment products as decision support to issue a tsunami warning within the early warning stage. On the other hand the maps and GIS products shall provide relevant information to enable local decision makers to act adequately concerning their local risks. It is shown that effective prevention and mitigation measures can be designed based on risk assessment results and information especially when used pro-active and beforehand a disaster strikes. The conducted hazard assessment provides the probability of an area to be affected by a tsunami threat divided into two ranked impact zones. The two divided impact zones directly relate to tsunami warning levels issued by the Early Warning Center and consequently enable the local decision maker to base their planning (e.g. evacuation) accordingly. Within the tsunami hazard assessment several hundred pre-computed tsunami scenarios are analysed. This is combined with statistical analysis of historical event data. Probabilities of tsunami occurrence considering probabilities of different earthquake magnitudes, occurrences of specific wave heights at coast and spatial inundation probability are computed. Hazard assessment is then combined with a comprehensive vulnerability assessment. Here deficits in e.g. people's ability to receive and understand a tsunami warning and deficits in their ability to respond adequately (evacuate on time) are quantified and are visualized for the respective coastal areas. Hereby socio-economic properties (determining peoples ability to understand a warning and to react) are combined with environmental conditions (land cover, slope, population density) to calculate the time needed to evacuate (reach a tsunami safe area derived through the hazard assessment). This is implemented using a newly developed GIS cost-distance weighting approach. For example, the amount of people affected in a certain area is dependent on expected tsunami intensity, inundated area, estimated tsunami arrival time and available time for evacuation. Referring to the Aceh 2004 Tsunami, an estimated amount of people affected (dead/injured) of 21000 for Kabubaten Aceh Jaya and 85000 for Kab. Banda Aceh is in a comparable range with reported values of 19661 and 78417 (JICA 2005) respectively. Hence the established methodology provides reliable estimates of people affected and people's ability to reach a safe area. Based on the spatial explicit detection of e.g. high tsunami risk areas (and the assessed root causes therefore), specific disaster risk reduction and early warning strategies can be designed. For example additional installation of technical warning dissemination device, community based preparedness and awareness programmes (education), structural and non-structural measures (e.g. land use conversion, coastal engineering), effective evacuation, contingency and household recovery aid planning can be employed and/or optimized within high tsunami risk areas as a first priority. In the context of early warning, spatially distributed information like degree of expected hazard impact, exposure of critical facilities (e.g. hospitals, schools), potential people dead/injured depending on available response times, location of safe and shelter areas can be disseminated and used for decision making. Keywords: Tsunami risk, hazard and vulnerability assessment, early warning, tsunami mitigation and prevention, Indonesia

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.

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.

A Prototype Flood Early Warning SensorWeb System for Namibia

NASA Astrophysics Data System (ADS)

Sohlberg, R. A.; Mandl, D.; Frye, S. W.; Cappelaere, P. G.; Szarzynski, J.; Policelli, F.; van Langenhove, G.

2010-12-01

During the past two years, there have been extensive floods in the country of Namibia, Africa which have affected up to a quarter of the population. Via a collaboration between a group funded by the Earth Science Technology Office (ESTO) at NASA that has been performing various SensorWeb prototyping activities for disasters, the Department of Hydrology in Namibia and the United Nations Space-based Information for Disaster and Emergency Response (UN-SPIDER) , experiments were conducted on how to apply various satellite resources integrated into a SensorWeb architecture along with in-situ sensors such as river gauges and rain gauges into a flood early warning system. The SensorWeb includes a global flood model and a higher resolution basin specific flood model. Furthermore, flood extent and status is monitored by optical and radar types of satellites and integrated via some automation. We have taken a practical approach to find out how to create a working system by selectively using the components that provide good results. The vision for the future is to combine this with the country side dwelling unit data base to create risk maps that provide specific warnings to houses within high risk areas based on near term predictions. This presentation will show some of the highlights of the effort thus far plus our future plans.

Three-Month Real-Time Dengue Forecast Models: An Early Warning System for Outbreak Alerts and Policy Decision Support in Singapore.

PubMed

Shi, Yuan; Liu, Xu; Kok, Suet-Yheng; Rajarethinam, Jayanthi; Liang, Shaohong; Yap, Grace; Chong, Chee-Seng; Lee, Kim-Sung; Tan, Sharon S Y; Chin, Christopher Kuan Yew; Lo, Andrew; Kong, Waiming; Ng, Lee Ching; Cook, Alex R

2016-09-01

With its tropical rainforest climate, rapid urbanization, and changing demography and ecology, Singapore experiences endemic dengue; the last large outbreak in 2013 culminated in 22,170 cases. In the absence of a vaccine on the market, vector control is the key approach for prevention. We sought to forecast the evolution of dengue epidemics in Singapore to provide early warning of outbreaks and to facilitate the public health response to moderate an impending outbreak. We developed a set of statistical models using least absolute shrinkage and selection operator (LASSO) methods to forecast the weekly incidence of dengue notifications over a 3-month time horizon. This forecasting tool used a variety of data streams and was updated weekly, including recent case data, meteorological data, vector surveillance data, and population-based national statistics. The forecasting methodology was compared with alternative approaches that have been proposed to model dengue case data (seasonal autoregressive integrated moving average and step-down linear regression) by fielding them on the 2013 dengue epidemic, the largest on record in Singapore. Operationally useful forecasts were obtained at a 3-month lag using the LASSO-derived models. Based on the mean average percentage error, the LASSO approach provided more accurate forecasts than the other methods we assessed. We demonstrate its utility in Singapore's dengue control program by providing a forecast of the 2013 outbreak for advance preparation of outbreak response. Statistical models built using machine learning methods such as LASSO have the potential to markedly improve forecasting techniques for recurrent infectious disease outbreaks such as dengue. Shi Y, Liu X, Kok SY, Rajarethinam J, Liang S, Yap G, Chong CS, Lee KS, Tan SS, Chin CK, Lo A, Kong W, Ng LC, Cook AR. 2016. Three-month real-time dengue forecast models: an early warning system for outbreak alerts and policy decision support in Singapore. Environ Health Perspect 124:1369-1375; http://dx.doi.org/10.1289/ehp.1509981.

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.

CoopEUS Case Study: Tsunami Modelling and Early Warning Systems for Near Source Areas (Mediterranean, Juan de Fuca).

NASA Astrophysics Data System (ADS)

Beranzoli, Laura; Best, Mairi; Chierici, Francesco; Embriaco, Davide; Galbraith, Nan; Heeseman, Martin; Kelley, Deborah; Pirenne, Benoit; Scofield, Oscar; Weller, Robert

2015-04-01

There is a need for tsunami modeling and early warning systems for near-source areas. For example this is a common public safety threat in the Mediterranean and Juan de Fuca/NE Pacific Coast of N.A.; Regions covered by the EMSO, OOI, and ONC ocean observatories. Through the CoopEUS international cooperation project, a number of environmental research infrastructures have come together to coordinate efforts on environmental challenges; this tsunami case study tackles one such challenge. There is a mutual need of tsunami event field data and modeling to deepen our experience in testing methodology and developing real-time data processing. Tsunami field data are already available for past events, part of this use case compares these for compatibility, gap analysis, and model groundtruthing. It also reviews sensors needed and harmonizes instrument settings. Sensor metadata and registries are compared, harmonized, and aligned. Data policies and access are also compared and assessed for gap analysis. Modelling algorithms are compared and tested against archived and real-time data. This case study will then be extended to other related tsunami data and model sources globally with similar geographic and seismic scenarios.

Monsoon Rainfall and Landslides in Nepal

NASA Astrophysics Data System (ADS)

Dahal, R. K.; Hasegawa, S.; Bhandary, N. P.; Yatabe, R.

2009-12-01

A large number of human settlements on the Nepal Himalayas are situated either on old landslide mass or on landslide-prone areas. As a result, a great number of people are affected by large- and small-scale landslides all over the Himalayas especially during monsoon periods. In Nepal, only in the half monsoon period (June 10 to August 15), 70, 50 and 68 people were killed from landslides in 2007, 2008 and 2009, respectively. In this context, this paper highlights monsoon rainfall and their implications in the Nepal Himalaya. In Nepal, monsoon is major source of rainfall in summer and approximately 80% of the annual total rainfall occurs from June to September. The measured values of mean annual precipitation in Nepal range from a low of approximately 250 mm at area north of the Himalaya to many areas exceeding 6,000 mm. The mean annual rainfall varying between 1500 mm and 2500 mm predominate over most of the country. In Nepal, the daily distribution of precipitation during rainy season is also uneven. Sometime 10% of the total annual precipitation can occur in a single day. Similarly, 50% total annual rainfall also can occur within 10 days of monsoon. This type of uneven distribution plays an important role in triggering many landslides in Nepal. When spatial distribution of landslides was evaluated from record of more than 650 landslides, it is found that more landslides events were concentrated at central Nepal in the area of high mean annual rainfall. When monsoon rainfall and landslide relationship was taken into consideration, it was noticed that a considerable number of landslides were triggered in the Himalaya by continuous rainfall of 3 to 90 days. It has been noticed that continuous rainfall of few days (5 days or 7 days or 10 days) are usually responsible for landsliding in the Nepal Himalaya. Monsoon rains usually fall with interruptions of 2-3 days and are generally characterized by low intensity and long duration. Thus, there is a strong role of antecedent rainfall in triggering landslides. It is noticed that a moderate correlation exists between the antecedent rainfalls of 3 to 10 days and the daily rainfall at failure in the Nepal Himalaya. The rainfall thresholds are utilized to develop early warning systems. Taking reference of the intensity-duration threshold and normalized rainfall intensity threshold, two proto-type models of early warning systems (RIEWS and N-RIEWS) are proposed. Early warning models show less time for evacuation in the case of short duration and high intensity rainfall, whereas for long duration rainfall, warning time is enough and when warning information disseminate to the people, people will aware to possible landslide risk. In the meantime, they will be mentally ready to tackle with possible disaster of coming hours or days and will avoid the consequences. On the basis of coarse hydro-meteorological data of developing country like Nepal, this simple and rather easy model of early warning will certainly help to reduce fatalities from landslides.

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.

Determination of early warning signs for photocatalytic degradation of titanium white oil paints by means of surface analysis

NASA Astrophysics Data System (ADS)

van Driel, B. A.; Wezendonk, T. A.; van den Berg, K. J.; Kooyman, P. J.; Gascon, J.; Dik, J.

2017-02-01

Titanium white (TiO2) has been widely used as a pigment in the 20th century. However, its most photocatalytic form (anatase) can cause severe degradation of the oil paint in which it is contained. UV light initiates TiO2-photocatalyzed processes in the paint film, degrading the oil binder into volatile components resulting in chalking of the paint. This will eventually lead to severe changes in the appearance of a painting. To date, limited examples of degraded works of art containing titanium white are known due to the relatively short existence of the paintings in question and the slow progress of the degradation process. However, UV light will inevitably cause degradation of paint in works of art containing photocatalytic titanium white. In this work, a method to detect early warning signs of photocatalytic degradation of unvarnished oil paint is proposed, using atomic force microscopy (AFM) and X-ray photoelectron spectroscopy (XPS). Consequently, a four-stage degradation model was developed through in-depth study of TiO2-containing paint films in various stages of degradation. The XPS surface analysis proved very valuable for detecting early warning signs of paint degradation, whereas the AFM results provide additional confirmation and are in good agreement with bulk gloss reduction.

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…

PROPOSED WATER QUALITY SURVEILLANCE NETWORK USING PHYSICAL, CHEMICAL AND BIOLOGICAL EARLY WARNING SYSTEMS (CBEWS)

EPA Science Inventory

The Homeland Protection Act of 2002 specifically calls for the investigation and use of Early Warning Systems (EWS) for water security reasons. The EWS is a screening tool for detecting changes in source water and distribution system water quality. A suite of time-relevant biol...

PROPOSED WATER QUALITY SURVEILLANCE NETWORK USING PHYSICAL, CHEMICAL AND BIOLOGICAL EARLY WARNING SYSTEMS (BEWS)

EPA Science Inventory

The Homeland Protection Act of 2002 specifically calls for the investigation and use of Early Warning Systems (EWS) for water security reasons. The EWS is a screening tool for detecting changes in source water and distribution system water quality. A suite of time-relevant biol...

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.

Assessing the performance of remotely-sensed flooding indicators and their potential contribution to early warning for leptospirosis in Cambodia

PubMed Central

Ledien, Julia; Sorn, Sopheak; Hem, Sopheak; Huy, Rekol; Buchy, Philippe

2017-01-01

Remote sensing can contribute to early warning for diseases with environmental drivers, such as flooding for leptospirosis. In this study we assessed whether and which remotely-sensed flooding indicator could be used in Cambodia to study any disease for which flooding has already been identified as an important driver, using leptospirosis as a case study. The performance of six potential flooding indicators was assessed by ground truthing. The Modified Normalized Difference Water Index (MNDWI) was used to estimate the Risk Ratio (RR) of being infected by leptospirosis when exposed to floods it detected, in particular during the rainy season. Chi-square tests were also calculated. Another variable—the time elapsed since the first flooding of the year—was created using MNDWI values and was also included as explanatory variable in a generalized linear model (GLM) and in a boosted regression tree model (BRT) of leptospirosis infections, along with other explanatory variables. Interestingly, MNDWI thresholds for both detecting water and predicting the risk of leptospirosis seroconversion were independently evaluated at -0.3. Value of MNDWI greater than -0.3 was significantly related to leptospirosis infection (RR = 1.61 [1.10–1.52]; χ2 = 5.64, p-value = 0.02, especially during the rainy season (RR = 2.03 [1.25–3.28]; χ2 = 8.15, p-value = 0.004). Time since the first flooding of the year was a significant risk factor in our GLM model (p-value = 0.042). These results suggest that MNDWI may be useful as a risk indicator in an early warning remote sensing tool for flood-driven diseases like leptospirosis in South East Asia. PMID:28704461

Assessing the performance of remotely-sensed flooding indicators and their potential contribution to early warning for leptospirosis in Cambodia.

PubMed

Ledien, Julia; Sorn, Sopheak; Hem, Sopheak; Huy, Rekol; Buchy, Philippe; Tarantola, Arnaud; Cappelle, Julien

2017-01-01

Remote sensing can contribute to early warning for diseases with environmental drivers, such as flooding for leptospirosis. In this study we assessed whether and which remotely-sensed flooding indicator could be used in Cambodia to study any disease for which flooding has already been identified as an important driver, using leptospirosis as a case study. The performance of six potential flooding indicators was assessed by ground truthing. The Modified Normalized Difference Water Index (MNDWI) was used to estimate the Risk Ratio (RR) of being infected by leptospirosis when exposed to floods it detected, in particular during the rainy season. Chi-square tests were also calculated. Another variable-the time elapsed since the first flooding of the year-was created using MNDWI values and was also included as explanatory variable in a generalized linear model (GLM) and in a boosted regression tree model (BRT) of leptospirosis infections, along with other explanatory variables. Interestingly, MNDWI thresholds for both detecting water and predicting the risk of leptospirosis seroconversion were independently evaluated at -0.3. Value of MNDWI greater than -0.3 was significantly related to leptospirosis infection (RR = 1.61 [1.10-1.52]; χ2 = 5.64, p-value = 0.02, especially during the rainy season (RR = 2.03 [1.25-3.28]; χ2 = 8.15, p-value = 0.004). Time since the first flooding of the year was a significant risk factor in our GLM model (p-value = 0.042). These results suggest that MNDWI may be useful as a risk indicator in an early warning remote sensing tool for flood-driven diseases like leptospirosis in South East Asia.

Limits to Forecasting Precision for Outbreaks of Directly Transmitted Diseases

PubMed Central

Drake, John M

2006-01-01

Background Early warning systems for outbreaks of infectious diseases are an important application of the ecological theory of epidemics. A key variable predicted by early warning systems is the final outbreak size. However, for directly transmitted diseases, the stochastic contact process by which outbreaks develop entails fundamental limits to the precision with which the final size can be predicted. Methods and Findings I studied how the expected final outbreak size and the coefficient of variation in the final size of outbreaks scale with control effectiveness and the rate of infectious contacts in the simple stochastic epidemic. As examples, I parameterized this model with data on observed ranges for the basic reproductive ratio (R 0) of nine directly transmitted diseases. I also present results from a new model, the simple stochastic epidemic with delayed-onset intervention, in which an initially supercritical outbreak (R 0 > 1) is brought under control after a delay. Conclusion The coefficient of variation of final outbreak size in the subcritical case (R 0 < 1) will be greater than one for any outbreak in which the removal rate is less than approximately 2.41 times the rate of infectious contacts, implying that for many transmissible diseases precise forecasts of the final outbreak size will be unattainable. In the delayed-onset model, the coefficient of variation (CV) was generally large (CV > 1) and increased with the delay between the start of the epidemic and intervention, and with the average outbreak size. These results suggest that early warning systems for infectious diseases should not focus exclusively on predicting outbreak size but should consider other characteristics of outbreaks such as the timing of disease emergence. PMID:16435887

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.

Developing an early warning system for storm surge inundation in the Philippines

NASA Astrophysics Data System (ADS)

Tablazon, Judd; Mahar Francisco Lagmay, Alfredo; Francia Mungcal, Ma. Theresa; Gonzalo, Lia Anne; Dasallas, Lea; Briones, Jo Brianne Louise; Santiago, Joy; Suarez, John Kenneth; Lapidez, John Phillip; Caro, Carl Vincent; Ladiero, Christine; Malano, Vicente

2014-05-01

A storm surge is the sudden rise of sea water generated by an approaching storm, over and above the astronomical tides. This event imposes a major threat in the Philippine coastal areas, as manifested by Typhoon Haiyan on 08 November 2013 where more than 6,000 people lost their lives. It has become evident that the need to develop an early warning system for storm surges is of utmost importance. To provide forecasts of the possible storm surge heights of an approaching typhoon, the Nationwide Operational Assessment of Hazards under the Department of Science and Technology (DOST-Project NOAH) simulated historical tropical cyclones that entered the Philippine Area of Responsibility. Bathymetric data, storm track, central atmospheric pressure, and maximum wind speed were used as parameters for the Japan Meteorological Agency (JMA) Storm Surge Model. The researchers calculated the frequency distribution of maximum storm surge heights of all typhoons under a specific Public Storm Warning Signal (PSWS) that passed through a particular coastal area. This determines the storm surge height corresponding to a given probability of occurrence. The storm surge heights from the model were added to the maximum astronomical tide data from WXTide software. The team then created maps of probable area inundation and flood levels of storm surges along coastal areas for a specific PSWS using the results of the frequency distribution. These maps were developed from the time series data of the storm tide at 10-minute intervals of all observation points in the Philippines. This information will be beneficial in developing early warnings systems, static maps, disaster mitigation and preparedness plans, vulnerability assessments, risk-sensitive land use plans, shoreline defense efforts, and coastal protection measures. Moreover, these will support the local government units' mandate to raise public awareness, disseminate information about storm surge hazards, and implement appropriate counter-measures for a given PSWS.

Developing an early warning system for storm surge inundation in the Philippines

NASA Astrophysics Data System (ADS)

Tablazon, J.; Caro, C. V.; Lagmay, A. M. F.; Briones, J. B. L.; Dasallas, L.; Lapidez, J. P.; Santiago, J.; Suarez, J. K.; Ladiero, C.; Gonzalo, L. A.; Mungcal, M. T. F.; Malano, V.

2014-10-01

A storm surge is the sudden rise of sea water generated by an approaching storm, over and above the astronomical tides. This event imposes a major threat in the Philippine coastal areas, as manifested by Typhoon Haiyan on 8 November 2013 where more than 6000 people lost their lives. It has become evident that the need to develop an early warning system for storm surges is of utmost importance. To provide forecasts of the possible storm surge heights of an approaching typhoon, the Nationwide Operational Assessment of Hazards under the Department of Science and Technology (DOST-Project NOAH) simulated historical tropical cyclones that entered the Philippine Area of Responsibility. Bathymetric data, storm track, central atmospheric pressure, and maximum wind speed were used as parameters for the Japan Meteorological Agency Storm Surge Model. The researchers calculated the frequency distribution of maximum storm surge heights of all typhoons under a specific Public Storm Warning Signal (PSWS) that passed through a particular coastal area. This determines the storm surge height corresponding to a given probability of occurrence. The storm surge heights from the model were added to the maximum astronomical tide data from WXTide software. The team then created maps of probable area inundation and flood levels of storm surges along coastal areas for a specific PSWS using the results of the frequency distribution. These maps were developed from the time series data of the storm tide at 10 min intervals of all observation points in the Philippines. This information will be beneficial in developing early warnings systems, static maps, disaster mitigation and preparedness plans, vulnerability assessments, risk-sensitive land use plans, shoreline defense efforts, and coastal protection measures. Moreover, these will support the local government units' mandate to raise public awareness, disseminate information about storm surge hazards, and implement appropriate counter-measures for a given PSWS.

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).

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.

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.

[Intervention effect assessment of response to heatwave in communities of four cities, China].

PubMed

Li, Y H; Wang, Q Q; Lan, L; Luo, S Q; Fang, D K; He, J Y; Yang, C; Ding, Z; Cheng, Y B; Li, C C; Wu, Z; Yu, S Y; Jin, Y L

2018-04-06

Objective: To evaluate the intervention effects of response to heatwave in communities of four cities, China. Methods: Baseline survey on heatwave and climate change related knowledge, attitude and practice (KAP) was conducted in the pilot communities in Harbin, Nanjing, Shenzhen and Chongqing, using face-to-face questionnaire interview in November, 2011 to November, 2013. Finally, 1 604 residents were interviewed. Intervention measures were implemented in summers of 2013 and 2014, including delivering early warning information of heatwave health risk and launching health education and promotion. The second survey was conducted in same communities using the same questionnaire and sampling method as baseline survey in November, 2014, and 1 640 residents were interviewed. The Chi-square test was used to compare the demographic characteristics and KAP of community residents between before and after intervention, and the factors that affected the intervention effect were selected by logistic multiple stepwise regression model. Results: The age of the residents interviewed before and after intervention was (46.4 ± 15.5) years and (45.0 ± 15.9) years, respectively. Overall, the residents' awareness rates of heatwave before and after intervention were 70.5% (1 131/1 604) and 82.9% (1 359/1 640) (χ 2 =69.40, P< 0.001). The rate of residents who had wished to receive early warning information increased 6.3% (χ 2 =41.11, P< 0.001), which reached 94.6% (1 551/1 604) after intervention from 88.3% (1 416/1 604) in baseline survey. Both heatwave health risk early warning and health education had big impacts to residents. There were 92.7% (1 105 residents) among the 1 192 residents who had received the early warning information arrange work and rest time according to the early warning information and 93.0% (1 231 residents) among the 1 323 residents who knew about health education activities being conducted in community thought that the community health education activities had made active role in protecting health from heatwaves. After a series of intervention, male had a effect on attitude about hot wave than female in Nanjing and Chongqing, OR (95 %CI ) were 1.48(1.02-2.16) and 1.45 (1.18-2.05) , respectively; compared with subjects below primary school education, people with college degree or above had higer KAP in all cities ( ORs range from 1.18 to 2.05), P< 0.05; regular physical exercise ( ORs range from 1.39 to 2.70) also had profound impacts on KAP in all cities ( P< 0.05). Conclusion: s Early warning and health education were effective measures to enhance residents' response capacity to climate change.

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

Implementation of malaria dynamic models in municipality level early warning systems in Colombia. Part I: description of study sites.

PubMed

Ruiz, Daniel; Cerón, Viviana; Molina, Adriana M; Quiñónes, Martha L; Jiménez, Mónica M; Ahumada, Martha; Gutiérrez, Patricia; Osorio, Salua; Mantilla, Gilma; Connor, Stephen J; Thomson, Madeleine C

2014-07-01

As part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System, the Colombian National Institute of Health is working on the design and implementation of a Malaria Early Warning System framework, supported by seasonal climate forecasting capabilities, weather and environmental monitoring, and malaria statistical and dynamic models. In this report, we provide an overview of the local ecoepidemiologic settings where four malaria process-based mathematical models are currently being implemented at a municipal level. The description includes general characteristics, malaria situation (predominant type of infection, malaria-positive cases data, malaria incidence, and seasonality), entomologic conditions (primary and secondary vectors, mosquito densities, and feeding frequencies), climatic conditions (climatology and long-term trends), key drivers of epidemic outbreaks, and non-climatic factors (populations at risk, control campaigns, and socioeconomic conditions). Selected pilot sites exhibit different ecoepidemiologic settings that must be taken into account in the development of the integrated surveillance and control system. © The American Society of Tropical Medicine and Hygiene.

Combining multiple earthquake models in real time for earthquake early warning

USGS Publications Warehouse

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

2017-01-01

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

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.

Physically based approaches incorporating evaporation for early warning predictions of rainfall-induced landslides

NASA Astrophysics Data System (ADS)

Reder, Alfredo; Rianna, Guido; Pagano, Luca

2018-02-01

In the field of rainfall-induced landslides on sloping covers, models for early warning predictions require an adequate trade-off between two aspects: prediction accuracy and timeliness. When a cover's initial hydrological state is a determining factor in triggering landslides, taking evaporative losses into account (or not) could significantly affect both aspects. This study evaluates the performance of three physically based predictive models, converting precipitation and evaporative fluxes into hydrological variables useful in assessing slope safety conditions. Two of the models incorporate evaporation, with one representing evaporation as both a boundary and internal phenomenon, and the other only a boundary phenomenon. The third model totally disregards evaporation. Model performances are assessed by analysing a well-documented case study involving a 2 m thick sloping volcanic cover. The large amount of monitoring data collected for the soil involved in the case study, reconstituted in a suitably equipped lysimeter, makes it possible to propose procedures for calibrating and validating the parameters of the models. All predictions indicate a hydrological singularity at the landslide time (alarm). A comparison of the models' predictions also indicates that the greater the complexity and completeness of the model, the lower the number of predicted hydrological singularities when no landslides occur (false alarms).

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.

Performance evaluation of the national early warning system for shallow landslides in Norway

NASA Astrophysics Data System (ADS)

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

2017-04-01

As a consequence of the increased number of rainfall-and snowmelt-induced landslides (debris flows, debris slides, debris avalanches and slush flows) occurring in Norway, a national landslide early warning system (EWS) has been developed for monitoring and forecasting the hydro-meteorological conditions potentially necessary of triggering slope failures. The system, operational since 2013, is managed by the Norwegian Water Resources and Energy Directorate (NVE) and has been designed in cooperation with the Norwegian Public Road Administration (SVV), the Norwegian National Rail Administration (JBV) and the Norwegian Meteorological Institute (MET). Decision-making in the EWS is based upon hazard threshold levels, hydro-meteorological and real-time landslide observations as well as landslide inventory and susceptibility maps. Hazard threshold levels have been obtained through statistical analyses of historical landslides and modelled hydro-meteorological parameters. Daily hydro-meteorological conditions such as rainfall, snowmelt, runoff, soil saturation, groundwater level and frost depth have been derived from a distributed version of the hydrological HBV-model. Two different landslide susceptibility maps are used as supportive data in deciding daily warning levels. Daily alerts are issued throughout the country considering variable warning zones. Warnings are issued once per day for the following 3 days with an update possibility later during the day according to the information gathered by the monitoring variables. The performance of the EWS has been evaluated applying the EDuMaP method. In particular, the performance of warnings issued in Western Norway, in the period 2013-2014 has been evaluated using two different landslide datasets. The best performance is obtained for the smallest and more accurate dataset. Different performance results may be observed as a function of changing the landslide density criterion, Lden(k), (i.e., thresholds considered to differentiate among classes of landslide events) used as an input parameter within the EDuMaP method. To investigate this issue, a parametric analysis has been conducted; the results of the analysis show clear differences among computed performances when absolute or relative landslide density criteria are considered.

Visual attention to health warnings on plain tobacco packaging in adolescent smokers and non-smokers.

PubMed

Maynard, Olivia M; Munafò, Marcus R; Leonards, Ute

2013-02-01

Previous research with adults indicates that plain packaging increases visual attention to health warnings in adult non-smokers and weekly smokers, but not daily smokers. The present research extends this study to adolescents aged 14-19 years. Mixed-model experimental design, with smoking status as a between-subjects factor and pack type (branded or plain pack) and eye gaze location (health warning or branding) as within-subjects factors. Three secondary schools in Bristol, UK. A convenience sample of adolescents comprising never-smokers (n = 26), experimenters (n = 34), weekly smokers (n = 13) and daily smokers (n = 14). Number of eye movements to health warnings and branding on plain and branded packs. Analysis of variance, irrespective of smoking status revealed more eye movements to health warnings than branding on plain packs, but an equal number of eye movements to both regions on branded packs (P = 0.033). This was observed among experimenters (P < 0.001) and weekly smokers (P = 0.047), but not among never-smokers or daily smokers. Among experimenters and weekly smokers, plain packaging increases visual attention to health warnings and away from branding. Daily smokers, even relatively early in their smoking careers, seem to avoid the health warnings on cigarette packs. Adolescent never-smokers attend the health warnings preferentially on both types of packs, a finding which may reflect their decision not to smoke. © 2012 The Authors, Addiction © 2012 Society for the Study of Addiction.

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.

An analysis of an early-warning system to reduce abortions in dairy cattle in Denmark incorporating both financial and epidemiologic aspects.

PubMed

Carpenter, Tim E; Chrièl, Mariann; Greiner, Matthias

2007-01-16

Emergency preparedness relies on the ability to detect patterns in rare incidents in an early stage of an outbreak in order to implement relevant actions. Early warning of an abortion storm as a result of infection with a notifiable disease, e.g. brucellosis, bovine viral diarrhea (BVD) or infectious bovine rhinotracheitis (IBR), is a significant surveillance tool. This study used data from 507 large Danish dairy herds. A modified two-stage method for detecting an unusual increase in the abortion incidence was applied to the data. An alarm was considered true if an abortion were detected in the month following the alarm month, otherwise false. The total number of abortions that could potentially be avoided if effective action were taken ranged from 769 (22.9%) to 10 (0.3%), as the number of abortions required to set the alarm increased from 1 to 6. The vast majority of abortions could, however, not be predicted, much less prevented, given this early-warning system. The false to true alarm ratio was reduced when the number of abortions that set the alarm increased. The financial scenarios evaluated demonstrated that the value of an abortion, the cost of responding to an alarm and the efficiency of the actions are important for decision making when reporting an alarm. The presented model can readily be extended to other disease problems and multiple-time periods.

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

Developing an automatic classification system of vegetation anomalies for early warning with the ASAP (Anomaly hot Spots of Agricultural Production) system

NASA Astrophysics Data System (ADS)

Meroni, M.; Rembold, F.; Urbano, F.; Lemoine, G.

2016-12-01

Anomaly maps and time profiles of remote sensing derived indicators relevant to monitor crop and vegetation stress can be accessed online thanks to a rapidly growing number of web based portals. However, timely and systematic global analysis and coherent interpretation of such information, as it is needed for example for SDG 2 related monitoring, remains challenging. With the ASAP system (Anomaly hot Spots of Agricultural Production) we propose a two-step analysis to provide monthly warning of production deficits in water-limited agriculture worldwide. The first step is fully automated and aims at classifying each administrative unit (1st sub-national level) into a number of possible warning levels, ranging from "none" to "watch" and up to "extended alarm". The second step involves the verification of the automatic warnings and integration into a short national level analysis by agricultural analysts. In this paper we describe the methodological development of the automatic vegetation anomaly classification system. Warnings are triggered only during the crop growing season, defined by a remote sensing based phenology. The classification takes into consideration the fraction of the agricultural and rangelands area for each administrative unit that is affected by a severe anomaly of two rainfall-based indicators (the Standardized Precipitation Index (SPI), computed at 1 and 3-month scale) and one biophysical indicator (the cumulative NDVI from the start of the growing season). The severity of the warning thus depends on the timing, the nature and the number of indicators for which an anomaly is detected. The prototype system is using global NDVI images of the METOP sensor, while a second version is being developed based on 1km Modis NDVI with temporal smoothing and near real time filtering. Also a specific water balance model is under development to include agriculture water stress information in addition to the SPI. The monthly warning classification and crop condition assessment will be made available on a website and will strengthen the JRC support to information products based on consensus assessment such as the GEOGLAM Crop Monitor for Early Warning.

Learning by teaching: undergraduate engineering students improving a community's response capability to an early warning system

NASA Astrophysics Data System (ADS)

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 in the event of a landslide. Participants were four undergraduate students in a civil engineering programme at a university in Thailand, as well as nine community members and three external evaluators. Results illustrate project and problem-based, experiential learning and highlight the real-world applications and development of knowledge and of hard and soft skills. The discussion raises issues of scalability and feasibility for implementation of these types of projects in large undergraduate engineering classes.

INSAR For Early Warning Of Possible Highway Instability Over Undermined Area Of Ostrava

NASA Astrophysics Data System (ADS)

Lazecky, Milan; Kacmarik, Michal; Rapant, Petr

2012-01-01

A part of czech highway D1 connecting Ostrava with Prague and Poland, is built over an undermined area of Ostrava-Svinov. Since the end of 2010, this part of the highway is fully operational. Because of undermining, a subsidence can be expected, however with a very slow rate since the mines are no more active in this area. Several TerraSAR-X images from 2011 are investigated interferometrically in order to estimate a precise deformation model. Subjects of interest are movements of newly built highway bridges, banks and close neighbourhood. Existing C-band multitemporal InSAR processing results of ERS and Envisat are available from an earlier period that reveil a slow trend of residual subsidence. In this project, InSAR will be investigated as a tool for an early warning for highway stability.

Operational Remote Sensing Services in North Eastern Region of India for Natural Resources Management, Early Warning for Disaster Risk Reduction and Dissemination of Information and Services

NASA Astrophysics Data System (ADS)

Raju, P. L. N.; Sarma, K. K.; Barman, D.; Handique, B. K.; Chutia, D.; Kundu, S. S.; Das, R. Kr.; Chakraborty, K.; Das, R.; Goswami, J.; Das, P.; Devi, H. S.; Nongkynrih, J. M.; Bhusan, K.; Singh, M. S.; Singh, P. S.; Saikhom, V.; Goswami, C.; Pebam, R.; Borgohain, A.; Gogoi, R. B.; Singh, N. R.; Bharali, A.; Sarma, D.; Lyngdoh, R. B.; Mandal, P. P.; Chabukdhara, M.

2016-06-01

North Eastern Region (NER) of India comprising of eight states considered to be most unique and one of the most challenging regions to govern due to its unique physiographic condition, rich biodiversity, disaster prone and diverse socio-economic characteristics. Operational Remote Sensing services increased manifolds in the region with the establishment of North Eastern Space Applications Centre (NESAC) in the year 2000. Since inception, NESAC has been providing remote sensing services in generating inventory, planning and developmental activities, and management of natural resources, disasters and dissemination of information and services through geo-web services for NER. The operational remote sensing services provided by NESAC can be broadly divided into three categories viz. natural resource planning and developmental services, disaster risk reduction and early warning services and information dissemination through geo-portal services. As a apart of natural resources planning and developmental services NESAC supports the state forest departments in preparing the forest working plans by providing geospatial inputs covering entire NER, identifying the suitable culturable wastelands for cultivation of silkworm food plants, mapping of natural resources such as land use/land cover, wastelands, land degradation etc. on temporal basis. In the area of disaster risk reduction, NESAC has initiated operational services for early warning and post disaster assessment inputs for flood early warning system (FLEWS) using satellite remote sensing, numerical weather prediction, hydrological modeling etc.; forest fire alert system with actionable attribute information; Japanese Encephalitis Early Warning System (JEWS) based on mosquito vector abundance, pig population and historical disease intensity and agriculture drought monitoring for the region. The large volumes of geo-spatial databases generated as part of operational services are made available to the administrators and local government bodies for better management, preparing prospective planning, and sustainable use of available resources. The knowledge dissemination is being done through online web portals wherever the internet access is available and as well as offline space based information kiosks, where the internet access is not available or having limited bandwidth availability. This paper presents a systematic and comprehensive study on the remote sensing services operational in NER of India for natural resources management, disaster risk reduction and dissemination of information and services, in addition to outlining future areas and direction of space applications for the region.

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.

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.

An early warning system for incursions of Bluetongue disease to the UK

NASA Astrophysics Data System (ADS)

Burgin, Laura; Sanders, Christopher; Carpenter, Simon; Mellor, Philip; Gloster, John

2010-05-01

Since 2006 northern Europe has been in the midst of an extensive epidemic of the animal disease, Bluetongue, which has cost the European economy hundreds of millions of euros due to death, sickness and movement restrictions of livestock. Bluetongue is spread by biting midges which can be carried for hundreds of kilometers on the wind. A scheme within the UK Met Office's dispersion model, the Numerical Atmospheric-dispersion Modelling Environment (NAME), has been developed to reflect the effects of meteorology on the long-distance transport of these midge vectors. The scheme is based on data from field and laboratory experiments carried out at the Institute for Animal Health, Pirbright. From these experiments, certain threshold values which define when midges do not become airborne have been obtained for several meteorological variables. Within NAME, particles representing midges are removed from the model atmosphere if these thresholds are exceeded. Following outbreaks of the disease in Belgium and the Netherlands in 2006, an early-warning website was developed based on the model, to provide the UK Department for Environment, Food and Rural Affairs (Defra) advance knowledge of potential disease incursions by infected midges carried on the wind across the English Channel. The service has been in daily operation since April 2007 and correctly warned of the high risk of an incursion of infected midges causing the first UK outbreak in Suffolk on 4 August 2007. The website has since been expanded to predict potential incursions of disease into the Channel Islands and Northern Ireland and was used to inform on vaccination policy decisions by Defra and the Scottish government.

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.

Applying the zero-inflated Poisson model with random effects to detect abnormal rises in school absenteeism indicating infectious diseases outbreak.

PubMed

Song, X X; Zhao, Q; Tao, T; Zhou, C M; Diwan, V K; Xu, B

2018-05-30

Records of absenteeism from primary schools are valuable data for infectious diseases surveillance. However, the analysis of the absenteeism is complicated by the data features of clustering at zero, non-independence and overdispersion. This study aimed to generate an appropriate model to handle the absenteeism data collected in a European Commission granted project for infectious disease surveillance in rural China and to evaluate the validity and timeliness of the resulting model for early warnings of infectious disease outbreak. Four steps were taken: (1) building a 'well-fitting' model by the zero-inflated Poisson model with random effects (ZIP-RE) using the absenteeism data from the first implementation year; (2) applying the resulting model to predict the 'expected' number of absenteeism events in the second implementation year; (3) computing the differences between the observations and the expected values (O-E values) to generate an alternative series of data; (4) evaluating the early warning validity and timeliness of the observational data and model-based O-E values via the EARS-3C algorithms with regard to the detection of real cluster events. The results indicate that ZIP-RE and its corresponding O-E values could improve the detection of aberrations, reduce the false-positive signals and are applicable to the zero-inflated data.

Early-warning signals for catastrophic soil degradation

NASA Astrophysics Data System (ADS)

Karssenberg, Derek

2010-05-01

Many earth systems have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been described, among others, for climate, vegetation, animal populations, and geomorphology. Predicting the timing of critical transitions before they are reached is of importance because of the large impact on nature and society associated with the transition. However, it is notably difficult to predict the timing of a transition. This is because the state variables of the system show little change before the threshold is reached. As a result, the precision of field observations is often too low to provide predictions of the timing of a transition. A possible solution is the use of spatio-temporal patterns in state variables as leading indicators of a transition. It is becoming clear that the critically slowing down of a system causes spatio-temporal autocorrelation and variance to increase before the transition. Thus, spatio-temporal patterns are important candidates for early-warning signals. In this research we will show that these early-warning signals also exist in geomorphological systems. We consider a modelled vegetation-soil system under a gradually increasing grazing pressure causing an abrupt shift towards extensive soil degradation. It is shown that changes in spatio-temporal patterns occur well ahead of this catastrophic transition. A distributed model describing the coupled processes of vegetation growth and geomorphological denudation is adapted. The model uses well-studied simple process representations for vegetation and geomorphology. A logistic growth model calculates vegetation cover as a function of grazing pressure and vegetation growth rate. Evolution of the soil thickness is modelled by soil creep and wash processes, as a function of net rain reaching the surface. The vegetation and soil system are coupled by 1) decreasing vegetation growth with decreasing soil thickness and 2) increasing soil wash with decreasing vegetation cover. The model describes a critical, catastrophic transition of an underexploited system with low grazing pressure towards an overexploited system. The underexploited state has high vegetation cover and well developed soils, while the overexploited state has low vegetation cover and largely degraded soils. We first show why spatio-temporal patterns in vegetation cover, morphology, erosion rate, and sediment load should be expected to change well before the critical transition towards the overexploited state. Subsequently, spatio-temporal patterns are quantified by calculating statistics, in particular first order statistics and autocorrelation in space and time. It is shown that these statistics gradually change before the transition is reached. This indicates that the statistics may serve as early-warning signals in real-world applications. We also discuss the potential use of remote sensing to predict the critical transition in real-world landscapes.

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

Developing a dengue early warning system using time series model: Case study in Tainan, Taiwan

NASA Astrophysics Data System (ADS)

Chen, Xiao-Wei; Jan, Chyan-Deng; Wang, Ji-Shang

2017-04-01

Dengue fever (DF) is a climate-sensitive disease that has been emerging in southern regions of Taiwan over the past few decades, causing a significant health burden to affected areas. This study aims to propose a predictive model to implement an early warning system so as to enhance dengue surveillance and control in Tainan, Taiwan. The Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used herein to forecast dengue cases. Temporal correlation between dengue incidences and climate variables were examined by Pearson correlation analysis and Cross-correlation tests in order to identify key determinants to be included as predictors. The dengue surveillance data between 2000 and 2009, as well as their respective climate variables were then used as inputs for the model. We validated the model by forecasting the number of dengue cases expected to occur each week between January 1, 2010 and December 31, 2015. In addition, we analyzed historical dengue trends and found that 25 cases occurring in one week was a trigger point that often led to a dengue outbreak. This threshold point was combined with the season-based framework put forth by the World Health Organization to create a more accurate epidemic threshold for a Tainan-specific warning system. A Seasonal ARIMA model with the general form: (1,0,5)(1,1,1)52 is identified as the most appropriate model based on lowest AIC, and was proven significant in the prediction of observed dengue cases. Based on the correlation coefficient, Lag-11 maximum 1-hr rainfall (r=0.319, P<0.05) and Lag-11 minimum temperature (r=0.416, P<0.05) are found to be the most positively correlated climate variables. Comparing the four multivariate models(i.e.1, 4, 9 and 13 weeks ahead), we found that including the climate variables improves the prediction RMSE as high as 3.24%, 10.39%, 17.96%, 21.81% respectively, in contrast to univariate models. Furthermore, the ability of the four multivariate models to determine whether the epidemic threshold would be exceeded in any given week during the forecasting period of 2010-2015 was analyzed using a contingency table. The 4 weeks-ahead approach was the most appropriate for an operational public health response with a 78.7% hit rate and 0.7% false alarm rate. Our findings indicate that SARIMA model is an ideal model for detecting outbreaks as it has high sensitivity and low risk of false alarms. Accurately forecasting future trends will provide valuable time to activate dengue surveillance and control in Tainan, Taiwan. We conclude that this timely dengue early warning system will enable public health services to allocate limited resources more effectively, and public health officials to adjust dengue emergency response plans to their maximum capabilities.

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.

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.

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,…

Forecasting the Incidence of Mumps in Zibo City Based on a SARIMA Model.

PubMed

Xu, Qinqin; Li, Runzi; Liu, Yafei; Luo, Cheng; Xu, Aiqiang; Xue, Fuzhong; Xu, Qing; Li, Xiujun

2017-08-17

This study aimed to predict the incidence of mumps using a seasonal autoregressive integrated moving average (SARIMA) model, and provide theoretical evidence for early warning prevention and control in Zibo City, Shandong Province, China. Monthly mumps data from Zibo City gathered between 2005 and 2013 were used as a training set to construct a SARIMA model, and the monthly mumps in 2014 were defined as a test set for the model. From 2005 to 2014, a total of 8722 cases of mumps were reported in Zibo City; the male-to-female ratio of cases was 1.85:1, the age group of 1-20 years old accounted for 94.05% of all reported cases, and students made up the largest proportion (65.89%). The main serious endemic areas of mumps were located in Huantai County, Linzi District, and Boshan District of Zibo City. There were two epidemic peaks from April to July and from October to January in next year. The fitted model SARIMA (0, 1, 1) (0, 1, 1) 12 was established (AIC = 157.528), which has high validity and reasonability. The SARIMA model fitted dynamic changes of mumps in Zibo City well. It can be used for short-term forecasting and early warning of mumps.

Forecasting the Incidence of Mumps in Zibo City Based on a SARIMA Model

PubMed Central

Xu, Qinqin; Li, Runzi; Liu, Yafei; Luo, Cheng; Xu, Aiqiang; Xue, Fuzhong; Xu, Qing; Li, Xiujun

2017-01-01

This study aimed to predict the incidence of mumps using a seasonal autoregressive integrated moving average (SARIMA) model, and provide theoretical evidence for early warning prevention and control in Zibo City, Shandong Province, China. Monthly mumps data from Zibo City gathered between 2005 and 2013 were used as a training set to construct a SARIMA model, and the monthly mumps in 2014 were defined as a test set for the model. From 2005 to 2014, a total of 8722 cases of mumps were reported in Zibo City; the male-to-female ratio of cases was 1.85:1, the age group of 1–20 years old accounted for 94.05% of all reported cases, and students made up the largest proportion (65.89%). The main serious endemic areas of mumps were located in Huantai County, Linzi District, and Boshan District of Zibo City. There were two epidemic peaks from April to July and from October to January in next year. The fitted model SARIMA (0, 1, 1) (0, 1, 1)12 was established (AIC = 157.528), which has high validity and reasonability. The SARIMA model fitted dynamic changes of mumps in Zibo City well. It can be used for short-term forecasting and early warning of mumps. PMID:28817101

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.

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

Determination of early warning signs for photocatalytic degradation of titanium white oil paints by means of surface analysis.

PubMed

van Driel, B A; Wezendonk, T A; van den Berg, K J; Kooyman, P J; Gascon, J; Dik, J

2017-02-05

Titanium white (TiO 2 ) has been widely used as a pigment in the 20th century. However, its most photocatalytic form (anatase) can cause severe degradation of the oil paint in which it is contained. UV light initiates TiO 2 -photocatalyzed processes in the paint film, degrading the oil binder into volatile components resulting in chalking of the paint. This will eventually lead to severe changes in the appearance of a painting. To date, limited examples of degraded works of art containing titanium white are known due to the relatively short existence of the paintings in question and the slow progress of the degradation process. However, UV light will inevitably cause degradation of paint in works of art containing photocatalytic titanium white. In this work, a method to detect early warning signs of photocatalytic degradation of unvarnished oil paint is proposed, using atomic force microscopy (AFM) and X-ray photoelectron spectroscopy (XPS). Consequently, a four-stage degradation model was developed through in-depth study of TiO 2 -containing paint films in various stages of degradation. The XPS surface analysis proved very valuable for detecting early warning signs of paint degradation, whereas the AFM results provide additional confirmation and are in good agreement with bulk gloss reduction. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

A max-to-min technique for making projections of NDVI change in semi-arid Africa for food security early warning

NASA Astrophysics Data System (ADS)

Brown, M. E.; Funk, C. C.

2005-12-01

Climatic hazards such as droughts and floods often result in a decline in food production in economically vulnerable pre-industrial economies such as those in Africa. Early warning systems (EWS) have been developed to identify slow onset disasters such famine and epidemic disease that may result from hazardous environmental conditions. These conditions often precede food crises by many months, thus effective monitoring via satellite and in situ observations can allow for successful mitigation activities. Accurate forecasts of NDVI could increase monitoring lead times and allow for effective institutional planning of intervention, making early warning earlier. This paper presents a simple empirical max-to-min model for making 1 to 4 month NDVI projections. These statistical projections are based on parameterized satellite rainfall estimates (RFE) and relative humidity demand (RHD). A heuristic example in central Zimbabwe introduces the RFE growth and RHD loss terms. A quasi-global, one month ahead, 1 degree study then demonstrates reasonable accuracies in many semi-arid regions. In Africa, a 0.1 degree cross-validated skill assessment quantifies the technique's applicability at 1 to 4 month forecast intervals. These results suggest that useful projections can be made over many semi-arid, food insecure regions of Africa, with plausible extensions to drought prone areas of Asia, Australia and South America.

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/

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.

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

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.

Urban flood early warning systems: approaches to hydrometeorological forecasting and communicating risk

NASA Astrophysics Data System (ADS)

Cranston, Michael; Speight, Linda; Maxey, Richard; Tavendale, Amy; Buchanan, Peter

2015-04-01

One of the main challenges for the flood forecasting community remains the provision of reliable early warnings of surface (or pluvial) flooding. The Scottish Flood Forecasting Service has been developing approaches for forecasting the risk of surface water flooding including capitalising on the latest developments in quantitative precipitation forecasting from the Met Office. A probabilistic Heavy Rainfall Alert decision support tool helps operational forecasters assess the likelihood of surface water flooding against regional rainfall depth-duration estimates from MOGREPS-UK linked to historical short-duration flooding in Scotland. The surface water flood risk is communicated through the daily Flood Guidance Statement to emergency responders. A more recent development is an innovative risk-based hydrometeorological approach that links 24-hour ensemble rainfall forecasts through a hydrological model (Grid-to-Grid) to a library of impact assessments (Speight et al., 2015). The early warning tool - FEWS Glasgow - presents the risk of flooding to people, property and transport across a 1km grid over the city of Glasgow with a lead time of 24 hours. Communication of the risk was presented in a bespoke surface water flood forecast product designed based on emergency responder requirements and trialled during the 2014 Commonwealth Games in Glasgow. The development of new approaches to surface water flood forecasting are leading to improved methods of communicating the risk and better performance in early warning with a reduction in false alarm rates with summer flood guidance in 2014 (67%) compared to 2013 (81%) - although verification of instances of surface water flooding remains difficult. However the introduction of more demanding hydrometeorological capabilities with associated greater levels of uncertainty does lead to an increased demand on operational flood forecasting skills and resources. Speight, L., Cole, S.J., Moore, R.J., Pierce, C., Wright, B., Golding, B., Cranston, M., Tavendale, A., Ghimire, S., and Dhondia, J. (2015) Developing surface water flood forecasting capabilities in Scotland: an operational pilot for the 2014 Commonwealth Games in Glasgow. Journal of Flood Risk Management, In Press.

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.

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).

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.

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.

Forecasting of wet snow avalanche activity: Proof of concept and operational implementation

NASA Astrophysics Data System (ADS)

Gobiet, Andreas; Jöbstl, Lisa; Rieder, Hannes; Bellaire, Sascha; Mitterer, Christoph

2017-04-01

State-of-the-art tools for the operational assessment of avalanche danger include field observations, recordings from automatic weather stations, meteorological analyses and forecasts, and recently also indices derived from snowpack models. In particular, an index for identifying the onset of wet-snow avalanche cycles (LWCindex), has been demonstrated to be useful. However, its value for operational avalanche forecasting is currently limited, since detailed, physically based snowpack models are usually driven by meteorological data from automatic weather stations only and have therefore no prognostic ability. Since avalanche risk management heavily relies on timely information and early warnings, many avalanche services in Europe nowadays start issuing forecasts for the following days, instead of the traditional assessment of the current avalanche danger. In this context, the prognostic operation of detailed snowpack models has recently been objective of extensive research. In this study a new, observationally constrained setup for forecasting the onset of wet-snow avalanche cycles with the detailed snow cover model SNOWPACK is presented and evaluated. Based on data from weather stations and different numerical weather prediction models, we demonstrate that forecasts of the LWCindex as indicator for wet-snow avalanche cycles can be useful for operational warning services, but is so far not reliable enough to be used as single warning tool without considering other factors. Therefore, further development currently focuses on the improvement of the forecasts by applying ensemble techniques and suitable post processing approaches to the output of numerical weather prediction models. In parallel, the prognostic meteo-snow model chain is operationally used by two regional avalanche warning services in Austria since winter 2016/2017 for the first time. Experiences from the first operational season and first results from current model developments will be reported.

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...

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…

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...

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.

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.

CyberShake-derived ground-motion prediction models for the Los Angeles region with application to earthquake early warning

USGS Publications Warehouse

Bose, Maren; Graves, Robert; Gill, David; Callaghan, Scott; Maechling, Phillip J.

2014-01-01

Real-time applications such as earthquake early warning (EEW) typically use empirical ground-motion prediction equations (GMPEs) along with event magnitude and source-to-site distances to estimate expected shaking levels. In this simplified approach, effects due to finite-fault geometry, directivity and site and basin response are often generalized, which may lead to a significant under- or overestimation of shaking from large earthquakes (M > 6.5) in some locations. For enhanced site-specific ground-motion predictions considering 3-D wave-propagation effects, we develop support vector regression (SVR) models from the SCEC CyberShake low-frequency (<0.5 Hz) and broad-band (0–10 Hz) data sets. CyberShake encompasses 3-D wave-propagation simulations of >415 000 finite-fault rupture scenarios (6.5 ≤ M ≤ 8.5) for southern California defined in UCERF 2.0. We use CyberShake to demonstrate the application of synthetic waveform data to EEW as a ‘proof of concept’, being aware that these simulations are not yet fully validated and might not appropriately sample the range of rupture uncertainty. Our regression models predict the maximum and the temporal evolution of instrumental intensity (MMI) at 71 selected test sites using only the hypocentre, magnitude and rupture ratio, which characterizes uni- and bilateral rupture propagation. Our regression approach is completely data-driven (where here the CyberShake simulations are considered data) and does not enforce pre-defined functional forms or dependencies among input parameters. The models were established from a subset (∼20 per cent) of CyberShake simulations, but can explain MMI values of all >400 k rupture scenarios with a standard deviation of about 0.4 intensity units. We apply our models to determine threshold magnitudes (and warning times) for various active faults in southern California that earthquakes need to exceed to cause at least ‘moderate’, ‘strong’ or ‘very strong’ shaking in the Los Angeles (LA) basin. These thresholds are used to construct a simple and robust EEW algorithm: to declare a warning, the algorithm only needs to locate the earthquake and to verify that the corresponding magnitude threshold is exceeded. The models predict that a relatively moderate M6.5–7 earthquake along the Palos Verdes, Newport-Inglewood/Rose Canyon, Elsinore or San Jacinto faults with a rupture propagating towards LA could cause ‘very strong’ to ‘severe’ shaking in the LA basin; however, warning times for these events could exceed 30 s.

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.

Early warning and response system (EWARS) for dengue outbreaks: Recent advancements towards widespread applications in critical settings

PubMed Central

Kroeger, Axel; Olliaro, Piero; Rocklöv, Joacim; Sewe, Maquins Odhiambo; Tejeda, Gustavo; Benitez, David; Gill, Balvinder; Hakim, S. Lokman; Gomes Carvalho, Roberta; Bowman, Leigh; Petzold, Max

2018-01-01

Background Dengue outbreaks are increasing in frequency over space and time, affecting people’s health and burdening resource-constrained health systems. The ability to detect early emerging outbreaks is key to mounting an effective response. The early warning and response system (EWARS) is a toolkit that provides countries with early-warning systems for efficient and cost-effective local responses. EWARS uses outbreak and alarm indicators to derive prediction models that can be used prospectively to predict a forthcoming dengue outbreak at district level. Methods We report on the development of the EWARS tool, based on users’ recommendations into a convenient, user-friendly and reliable software aided by a user’s workbook and its field testing in 30 health districts in Brazil, Malaysia and Mexico. Findings 34 Health officers from the 30 study districts who had used the original EWARS for 7 to 10 months responded to a questionnaire with mainly open-ended questions. Qualitative content analysis showed that participants were generally satisfied with the tool but preferred open-access vs. commercial software. EWARS users also stated that the geographical unit should be the district, while access to meteorological information should be improved. These recommendations were incorporated into the second-generation EWARS-R, using the free R software, combined with recent surveillance data and resulted in higher sensitivities and positive predictive values of alarm signals compared to the first-generation EWARS. Currently the use of satellite data for meteorological information is being tested and a dashboard is being developed to increase user-friendliness of the tool. The inclusion of other Aedes borne viral diseases is under discussion. Conclusion EWARS is a pragmatic and useful tool for detecting imminent dengue outbreaks to trigger early response activities. PMID:29727447

Application of the National Early Warning Score (NEWS) as a stratification tool on admission in an Italian acute medical ward: A perspective study.

PubMed

Spagnolli, Walter; Rigoni, Marta; Torri, Emanuele; Cozzio, Susanna; Vettorato, Elisa; Nollo, Giandomenico

2017-03-01

We aimed to assess the performance of the National Early Warning Score (NEWS) as tool for patient risk stratification at admission in an acute Internal Medicine ward and to ensure patient placement in ward areas with the required and most appropriate intensity of care. As secondary objective, we considered NEWS performance in two subgroups of patients: sudden cardiac events (acute coronary syndromes and arrhythmic events), and chronic respiratory insufficiency. We conducted a perspective cohort single centre study on 2,677 unselected patients consecutively admitted from July 2013 to March 2015 in the Internal Medicine ward of the hospital of Trento, Italy. The NEWS was mandatory collected on ward admission. We defined three risk categories for clinical deterioration: low score (NEWS 0-4), medium score (NEWS 5-6), and high score (NEWS≥7). Following adverse outcomes were considered: total and early (<72 hours) in-hospital mortality, urgent transfers to a higher intensity of care. A logistic regression model quantified the association between outcomes and NEWS. For patients with NEWS >4 vs patients with NEWS <4, the risk of early death increased from 12 to 36 times, total mortality from 3.5 to 9, and urgent transfers from 3.5 to 7. In patients with sudden cardiac events, lower scores were significantly associated with higher risk of transfer to a higher intensity of care. In patients affected by chronic hypoxaemia, adverse outcomes occurred less in medium and high score categories of NEWS. National Early Warning Score assessed on ward admission may enable risk stratification of clinical deterioration and can be a good predictor of in-hospital serious adverse outcomes, although sudden cardiac events and chronic hypoxaemia could constitute some limits. © 2017 John Wiley & Sons Ltd.

Early warning and response system (EWARS) for dengue outbreaks: Recent advancements towards widespread applications in critical settings.

PubMed

Hussain-Alkhateeb, Laith; Kroeger, Axel; Olliaro, Piero; Rocklöv, Joacim; Sewe, Maquins Odhiambo; Tejeda, Gustavo; Benitez, David; Gill, Balvinder; Hakim, S Lokman; Gomes Carvalho, Roberta; Bowman, Leigh; Petzold, Max

2018-01-01

Dengue outbreaks are increasing in frequency over space and time, affecting people's health and burdening resource-constrained health systems. The ability to detect early emerging outbreaks is key to mounting an effective response. The early warning and response system (EWARS) is a toolkit that provides countries with early-warning systems for efficient and cost-effective local responses. EWARS uses outbreak and alarm indicators to derive prediction models that can be used prospectively to predict a forthcoming dengue outbreak at district level. We report on the development of the EWARS tool, based on users' recommendations into a convenient, user-friendly and reliable software aided by a user's workbook and its field testing in 30 health districts in Brazil, Malaysia and Mexico. 34 Health officers from the 30 study districts who had used the original EWARS for 7 to 10 months responded to a questionnaire with mainly open-ended questions. Qualitative content analysis showed that participants were generally satisfied with the tool but preferred open-access vs. commercial software. EWARS users also stated that the geographical unit should be the district, while access to meteorological information should be improved. These recommendations were incorporated into the second-generation EWARS-R, using the free R software, combined with recent surveillance data and resulted in higher sensitivities and positive predictive values of alarm signals compared to the first-generation EWARS. Currently the use of satellite data for meteorological information is being tested and a dashboard is being developed to increase user-friendliness of the tool. The inclusion of other Aedes borne viral diseases is under discussion. EWARS is a pragmatic and useful tool for detecting imminent dengue outbreaks to trigger early response activities.

Towards Actionable Waterborne and Vector-borne Disease Forecasts

NASA Astrophysics Data System (ADS)

Zaitchik, B. F.

2015-12-01

Numerous studies have shown that remote sensing (RS) and Earth System Models (ESM) can make important contributions to the analysis, monitoring and prediction of waterborne and vector-borne illnesses. Unsurprisingly, however, the great majority of these studies have been proof-of-concept investigations, and vanishingly few have been translated into operational and utilized disease early warning systems. To some extent this is simply an example of the general challenge of translating research findings into decision-relevant operations. Disease early warning, however, entails specific challenges that distinguish it from many other fields of environmental monitoring and prediction. Some of these challenges stem from predictability and data constraints, while others relate to the difficulty of communicating predictions and the particularly high price of false alarms. This presentation will review progress on the translation of analysis to decision making, identify avenues for enhancing forecast utility, and propose priorities for future RS and ESM investments in disease monitoring and prediction.

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.

Intra-seasonal NDVI change projections in semi-arid Africa

USGS Publications Warehouse

Funk, Christopher C.; Brown, Molly E.

2006-01-01

Early warning systems (EWS) tend to focus on the identification of slow onset disasters such famine and epidemic disease. Since hazardous environmental conditions often precede disastrous outcomes by many months, effective monitoring via satellite and in situ observations can successfully guide mitigation activities. Accurate short term forecasts of NDVI could increase lead times, making early warning earlier. This paper presents a simple empirical model for making 1 to 4 month NDVI projections. These statistical projections are based on parameterized satellite rainfall estimates (RFE) and relative humidity demand (RHD). A quasi-global, 1 month ahead, 1° study demonstrates reasonable accuracies in many semi-arid regions. In Africa, a 0.1° cross-validated skill assessment quantifies the technique's applicability at 1 to 4 month forecast intervals. These results suggest that useful projections can be made over many semi-arid, food insecure regions of Africa, with plausible extensions to drought prone areas of Asia, Australia and South America.

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

TRMM Applications for Rainfall-Induced Landslide Early Warning

NASA Astrophysics Data System (ADS)

Dok, A.; Fukuoka, H.; Hong, Y.

2012-04-01

Early warning system (EWS) is the most effective method in saving lives and reducing property damages resulted from the catastrophic landslides if properly implemented in populated areas of landslide-prone nations. For predicting the occurrence of landslides, it requires examination of empirical relationship between rainfall characteristics and past landslide occurrence. In developed countries like Japan and the US, precipitation is monitored by rain radars and ground-based rain gauge matrix. However, in developing regions like Southeast Asian countries, very limited number of rain gauges is available, and there is no implemented methodology for issuing effective warming of landslides yet. Correspondingly, satellite precipitation monitoring could be therefore a possible and promising solution for launching landslide quasi-real-time early warning system in those countries. It is due to the fact that TMPA (TRMM Multi-satellite Precipitation Analysis) can provides a globally calibration-based sequential scheme for combining precipitation estimates from multiple satellites, and gauge analyses where feasible, at fine scales (3-hourly with 0.25°x0.25° spatial resolution). It is available both after and in quasi-real time, calibrated by TRMM Combined Instrument and TRMM Microwave Imager precipitation product. However, validation of ground based rain gauge and TRMM satellite data in the vulnerable regions is still not yet operative. Snake-line/Critical-line and Soil Water Index (SWI) are used for issuing warning of landslide occurrence in Japan; whereas, Caine criterion is preferable in Europe and western nations. Herewith, it presents rainfall behavior which took place in Beichuan city (located on the 2008 Chinese Wenchuan earthquake fault), Hofu and Shobara cities in Japan where localized heavy rainfall attacked in 2009 and 2010, respectively, from TRMM 3B42RT correlated with ground based rain gauge data. The 1-day rainfall intensity and 15-day cumulative rainfall (snake line) were independently plotted to investigate the impact of short-term rainfall intensity and accumulated effective rainfall volume respectively for obtaining some probabilistic threshold. Japanese SWI was also tested to distribute threshold regarding to highly nonlinear rainfall patterns in predicting the landslide occurrence through the plot of total water of 3 serial tank models and daily precipitation. As a result, the snake line plots using TMPA work well for landslide warning in the selected cities; while SWI plots shows unusual peak value on the day of the debris flow occurrence. Graph of daily precipitation vs SWI implies possible zone of critical line, and second peak appearance 1 day before, indicating possibility of early warning.

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.

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

Safe and Effective Secondary Schools: The Boys Town Model. Preventing Violence, Building Respect, and Promoting Learning in the Classroom and Beyond.

ERIC Educational Resources Information Center

Davis, Jerry L., Ed.; Nelson, Cathy S., Ed.; Gauger, Elizabeth S., Ed.

This book presents useful information on types and levels of aggression, how conflicts escalate, early warning signs of violence, and characteristics of a safe school. Violence prevention techniques, many based on principles that form the foundation of the Boys Town Education Model, show educators and administrators how to calm an angry or…

Near Real Time Flood Warning System for National Capital Territory of Delhi

NASA Astrophysics Data System (ADS)

Goyal, A.; Yadav, H.; Tyagi, H.; Gosain, A. K.

2017-12-01

Extreme floods are common phenomena during Indian Monsoons. The National Capital Territory area of India, Delhi, frequently experiences fluvial as well as pluvial inundation due to its proximity to river Yamuna and poor functioning of its stormwater drainage system. The urban floods result in severe waterlogging and heavy traffic snarls, bringing life in this megapolis to a halt. The city has witnessed six major floods since 1900 and thus its residents are well conscious of potential flood risks but the city still lacks a flood warning system. The flood related risks can be considerably reduced, if not eliminated, by issuing timely warnings and implementing adaptive measures. Therefore, the present study attempts to develop a web based platform that integrates Web-GIS technology and mathematical simulation modelling to provide an effective and reliable early flood warning service for Delhi. The study makes use of India Metorological Department's Doppler radar-derived near real time rainfall estimates of 15 minutes time step. The developed SWMM model has been validated using information from gauges, monitoring sensors and crowd sourcing techniques and utilises capabilities of cloud computing on server side for fast processing. This study also recommends safe evacuation policy and remedial measures for flooding hotspots as part of flood risk management plan. With heightened risk of floods in fast urbanizing areas, this work becomes highly pertinent as flood warning system with adequate lead time can not only save precious lives but can also substantially reduce flood damages.

Prototyping an Early-warning System for Rainfall-triggered Landslides on a Regional Scale Using a Physically-based Model and Remote Sensing Datasets

NASA Astrophysics Data System (ADS)

Liao, Z.; Hong, Y.; Kirschbaum, D. B.; Fukuoka, H.; Sassa, K.; Karnawati, D.; Fathani, F.

2010-12-01

Recent advancements in the availability of remotely sensed datasets provide an opportunity to advance the predictability of rainfall-triggered landslides at larger spatial scales. An early-warning system based on a physical landslide model and remote sensing information is used to simulate the dynamical response of the soil water content to the spatiotemporal variability of rainfall in complex terrain. The system utilizes geomorphologic datasets including a 30-meter ASTER DEM, a 1-km downscaled FAO soil map, and satellite-based Tropical Rainfall Measuring Mission (TRMM) precipitation. The applied physical model SLIDE (SLope-Infiltration-Distributed Equilibrium) defines a direct relationship between a factor of safety and the rainfall depth on an infinite slope. This prototype model is applied to a case study in Honduras during Hurricane Mitch in 1998 and a secondary case of typhoon-induced shallow landslides over Java Island, Indonesia. In Honduras, two study areas were selected which cover approximately 1,200 square kilometers and where a high density of shallow landslides occurred. The results were quantitatively evaluated using landslide inventory data compiled by the United States Geological Survey (USGS) following Hurricane Mitch, and show a good agreement between the modeling results and observations. The success rate for accurately estimating slope failure locations reached as high as 78% and 75%, while the error indices were 35% and 49%, respectively for each of the two selected study areas. Advantages and limitations of this application are discussed with respect to future assessment and challenges of performing a slope-stability estimation using coarse data at 1200 square kilometers. In Indonesia, the system has been applied over the whole Java Island. The prototyped early-warning system has been enhanced by integration of a susceptibility mapping and a precipitation forecasting model (i.e. Weather Research Forecast). The performance has been evaluated using a local landslide inventory, and results show that the system successfully predicted landslides in correspondence to the time of occurrence of the real landslide events in this case.

Estimating root-zone soil moisture in the West Africa Sahel using remotely sensed rainfall and vegetation

NASA Astrophysics Data System (ADS)

McNally, Amy L.

Agricultural drought is characterized by shortages in precipitation, large differences between actual and potential evapotranspiration, and soil water deficits that impact crop growth and pasture productivity. Rainfall and other agrometeorological gauge networks in Sub-Saharan Africa are inadequate for drought early warning systems and hence, satellite-based estimates of rainfall and vegetation greenness provide the main sources of information. While a number of studies have described the empirical relationship between rainfall and vegetation greenness, these studies lack a process based approach that includes soil moisture storage. In Chapters I and II, I modeled soil moisture using satellite rainfall inputs and developed a new method for estimating soil moisture with NDVI calibrated to in situ and microwave soil moisture observations. By transforming both NDVI and rainfall into estimates of soil moisture I was able to easily compare these two datasets in a physically meaningful way. In Chapter II, I also show how the new NDVI derived soil moisture can be assimilated into a water balance model that calculates an index of crop water stress. Compared to the analogous rainfall derived estimates of soil moisture and crop stress the NDVI derived estimates were better correlated with millet yields. In Chapter III, I developed a metric for defining growing season drought events that negatively impact millet yields. This metric is based on the data and models used in the Chapters I and II. I then use this metric to evaluate the ability of a sophisticated land surface model to detect drought events. The analysis showed that this particular land surface model's soil moisture estimates do have the potential to benefit the food security and drought early warning communities. With a focus on soil moisture, this dissertation introduced new methods that utilized a variety of data and models for agricultural drought monitoring applications. These new methods facilitate a more quantitative, transparent `convergence of evidence' approach to identifying agricultural drought events that lead to food insecurity. Ideally, these new methods will contribute to better famine early warning and the timely delivery of food aid to reduce the human suffering caused by drought.

Three-Month Real-Time Dengue Forecast Models: An Early Warning System for Outbreak Alerts and Policy Decision Support in Singapore

PubMed Central

Shi, Yuan; Liu, Xu; Kok, Suet-Yheng; Rajarethinam, Jayanthi; Liang, Shaohong; Yap, Grace; Chong, Chee-Seng; Lee, Kim-Sung; Tan, Sharon S.Y.; Chin, Christopher Kuan Yew; Lo, Andrew; Kong, Waiming; Ng, Lee Ching; Cook, Alex R.

2015-01-01

Background: With its tropical rainforest climate, rapid urbanization, and changing demography and ecology, Singapore experiences endemic dengue; the last large outbreak in 2013 culminated in 22,170 cases. In the absence of a vaccine on the market, vector control is the key approach for prevention. Objectives: We sought to forecast the evolution of dengue epidemics in Singapore to provide early warning of outbreaks and to facilitate the public health response to moderate an impending outbreak. Methods: We developed a set of statistical models using least absolute shrinkage and selection operator (LASSO) methods to forecast the weekly incidence of dengue notifications over a 3-month time horizon. This forecasting tool used a variety of data streams and was updated weekly, including recent case data, meteorological data, vector surveillance data, and population-based national statistics. The forecasting methodology was compared with alternative approaches that have been proposed to model dengue case data (seasonal autoregressive integrated moving average and step-down linear regression) by fielding them on the 2013 dengue epidemic, the largest on record in Singapore. Results: Operationally useful forecasts were obtained at a 3-month lag using the LASSO-derived models. Based on the mean average percentage error, the LASSO approach provided more accurate forecasts than the other methods we assessed. We demonstrate its utility in Singapore’s dengue control program by providing a forecast of the 2013 outbreak for advance preparation of outbreak response. Conclusions: Statistical models built using machine learning methods such as LASSO have the potential to markedly improve forecasting techniques for recurrent infectious disease outbreaks such as dengue. Citation: Shi Y, Liu X, Kok SY, Rajarethinam J, Liang S, Yap G, Chong CS, Lee KS, Tan SS, Chin CK, Lo A, Kong W, Ng LC, Cook AR. 2016. Three-month real-time dengue forecast models: an early warning system for outbreak alerts and policy decision support in Singapore. Environ Health Perspect 124:1369–1375; http://dx.doi.org/10.1289/ehp.1509981 PMID:26662617

Prediction of shallow landslide occurrence: Validation of a physically-based approach through a real case study.

PubMed

Schilirò, Luca; Montrasio, Lorella; Scarascia Mugnozza, Gabriele

2016-11-01

In recent years, physically-based numerical models have frequently been used in the framework of early-warning systems devoted to rainfall-induced landslide hazard monitoring and mitigation. For this reason, in this work we describe the potential of SLIP (Shallow Landslides Instability Prediction), a simplified physically-based model for the analysis of shallow landslide occurrence. In order to test the reliability of this model, a back analysis of recent landslide events occurred in the study area (located SW of Messina, northeastern Sicily, Italy) on October 1st, 2009 was performed. The simulation results have been compared with those obtained for the same event by using TRIGRS, another well-established model for shallow landslide prediction. Afterwards, a simulation over a 2-year span period has been performed for the same area, with the aim of evaluating the performance of SLIP as early warning tool. The results confirm the good predictive capability of the model, both in terms of spatial and temporal prediction of the instability phenomena. For this reason, we recommend an operating procedure for the real-time definition of shallow landslide triggering scenarios at the catchment scale, which is based on the use of SLIP calibrated through a specific multi-methodological approach. Copyright © 2016 Elsevier B.V. All rights reserved.

Strengthening community participation in reducing GHG emission from forest and peatland fire

NASA Astrophysics Data System (ADS)

Thoha, A. S.; Saharjo, B. H.; Boer, R.; Ardiansyah, M.

2018-02-01

Strengthening community participation is needed to find solutions to encourage community more participate in reducing Green House Gas (GHG) from forest and peatland fire. This research aimed to identify stakeholders that have the role in forest and peatland fire control and to formulate strengthening model of community participation through community-based early warning fire. Stakeholder mapping and action research were used to determine stakeholders that had potential influence and interest and to formulate strengthening model of community participation in reducing GHG from forest and peatland fire. There was found that position of key players in the mapping of stakeholders came from the government institution. The existence of community-based fire control group can strengthen government institution through collaborating with stakeholders having strong interest and influence. Moreover, it was found several local knowledge in Kapuas District about how communities predict drought that have potential value for developing the community-based early warning fire system. Formulated institutional model in this research also can be further developed as a model institution in the preservation of natural resources based on local knowledge. In conclusion, local knowledge and community-based fire groups can be integrated within strengthening model of community participation in reducing GHG from forest and peatland fire.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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.

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.

Early warning signal for dengue outbreaks and identification of high risk areas for dengue fever in Colombia using climate and non-climate datasets.

PubMed

Lee, Jung-Seok; Carabali, Mabel; Lim, Jacqueline K; Herrera, Victor M; Park, Il-Yeon; Villar, Luis; Farlow, Andrew

2017-07-10

Dengue has been prevalent in Colombia with high risk of outbreaks in various locations. While the prediction of dengue epidemics will bring significant benefits to the society, accurate forecasts have been a challenge. Given competing health demands in Colombia, it is critical to consider the effective use of the limited healthcare resources by identifying high risk areas for dengue fever. The Climate Risk Factor (CRF) index was constructed based upon temperature, precipitation, and humidity. Considering the conditions necessary for vector survival and transmission behavior, elevation and population density were taken into account. An Early Warning Signal (EWS) model was developed by estimating the elasticity of the climate risk factor function to detect dengue epidemics. The climate risk factor index was further estimated at the smaller geographical unit (5 km by 5 km resolution) to identify populations at high risk. From January 2007 to December 2015, the Early Warning Signal model successfully detected 75% of the total number of outbreaks 1 ~ 5 months ahead of time, 12.5% in the same month, and missed 12.5% of all outbreaks. The climate risk factors showed that populations at high risk are concentrated in the Western part of Colombia where more suitable climate conditions for vector mosquitoes and the high population level were observed compared to the East. This study concludes that it is possible to detect dengue outbreaks ahead of time and identify populations at high risk for various disease prevention activities based upon observed climate and non-climate information. The study outcomes can be used to minimize potential societal losses by prioritizing limited healthcare services and resources, as well as by conducting vector control activities prior to experiencing epidemics.

Specification of parameters for development of a spatial database for drought monitoring and famine early warning in the African Sahel

NASA Technical Reports Server (NTRS)

Rochon, Gilbert L.

1989-01-01

Parameters were described for spatial database to facilitate drought monitoring and famine early warning in the African Sahel. The proposed system, referred to as the African Drought and Famine Information System (ADFIS) is ultimately recommended for implementation with the NASA/FEMA Spatial Analysis and Modeling System (SAMS), a GIS/Dymanic Modeling software package, currently under development. SAMS is derived from FEMA'S Integration Emergency Management Information System (IEMIS) and the Pacific Northwest Laborotory's/Engineering Topographic Laboratory's Airland Battlefield Environment (ALBE) GIS. SAMS is primarily intended for disaster planning and resource management applications with the developing countries. Sources of data for the system would include the Developing Economics Branch of the U.S. Dept. of Agriculture, the World Bank, Tulane University School of Public Health and Tropical Medicine's Famine Early Warning Systems (FEWS) Project, the USAID's Foreign Disaster Assistance Section, the World Resources Institute, the World Meterological Institute, the USGS, the UNFAO, UNICEF, and the United Nations Disaster Relief Organization (UNDRO). Satellite imagery would include decadal AVHRR imagery and Normalized Difference Vegetation Index (NDVI) values from 1981 to the present for the African continent and selected Landsat scenes for the Sudan pilot study. The system is initially conceived for the MicroVAX 2/GPX, running VMS. To facilitate comparative analysis, a global time-series database (1950 to 1987) is included for a basic set of 125 socio-economic variables per country per year. A more detailed database for the Sahelian countries includes soil type, water resources, agricultural production, agricultural import and export, food aid, and consumption. A pilot dataset for the Sudan with over 2,500 variables from the World Bank's ANDREX system, also includes epidemiological data on incidence of kwashiorkor, marasmus, other nutritional deficiencies, and synergistically-related infectious diseases.

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.

An early warning system for flash floods in Egypt

NASA Astrophysics Data System (ADS)

Cools, J.; Abdelkhalek, A.; El Sammany, M.; Fahmi, A. H.; Bauwens, W.; Huygens, M.

2009-09-01

This paper describes the development of the Flash Flood Manager, abbreviated as FlaFloM. The Flash Flood Manager is an early warning system for flash floods which is developed under the EU LIFE project FlaFloM. It is applied to Wadi Watier located in the Sinai peninsula (Egypt) and discharges in the Red Sea at the local economic and tourist hub of Nuweiba city. FlaFloM consists of a chain of four modules: 1) Data gathering module, 2) Forecasting module, 3) Decision support module or DSS and 4) Warning module. Each module processes input data and consequently send the output to the following module. In case of a flash flood emergency, the final outcome of FlaFloM is a flood warning which is sent out to decision-makers. The ‘data gathering module’ collects input data from different sources, validates the input, visualise data and exports it to other modules. Input data is provided ideally as water stage (h), discharge (Q) and rainfall (R) through real-time field measurements and external forecasts. This project, however, as occurs in many arid flash flood prone areas, was confronted with a scarcity of data, and insufficient insight in the characteristics that release a flash flood. Hence, discharge and water stage data were not available. Although rainfall measurements are available through classical off line rain gauges, the sparse rain gauges network couldn’t catch the spatial and temporal characteristics of rainfall events. To overcome this bottleneck, we developed rainfall intensity raster maps (mm/hr) with an hourly time step and raster cell of 1*1km. These maps are derived through downscaling from two sources of global instruments: the weather research and forecasting model (WRF) and satellite estimates from the Tropical Rainfall Measuring Mission (TRMM). The ‘forecast module’ comprises three numerical models that, using data from the gathering module performs simulations on command: a rainfall-runoff model, a river flow model, and a flood model. A rainfall-runoff model transforms the (forecasted) rainfall into a runoff volume (m³) and consequently a time-dependent discharge (m³/s) for each of the subwadis which is then routed through the main channel. The flood model then converts the discharges into water stages and generates a spatially-distributed flood map. The rainfall-runoff model is developed in Matlab-Simulink. The latter two models are implemented in Infoworks and Floodworks (both Wallingford Software), which allows an automatic feed into the warning module. The ‘warning module’ has two tasks: 1) to generate specific flags when modelling results exceed pre-established thresholds for rainfall, discharge, water stage, volumes, etc… 2) to communicate the given flags as warning signals to operators and/or stakeholders. The ‘decision support module’ or DSS finally gives to the user the capability of performing alternative analysis in order to have a better idea of the reliability of the forecasts by means of the comparison of already made forecasts with new data and a sensitivity analysis. Although FlaFloM is now able to send out warnings, the forecasts of this first version are expected to be insufficiently accurate which may lead to false warnings and loss of trust with decision-makers if not communicated well. When new insights and data are available, the model will be updated which improves the forecast accuracy. At this moment, we see two major fields of improvement: 1) better rainfall forecasts and 2) better insights of the response of an arid area to storm events. Firstly, the rainfall maps provided better insights in the spatial and temporal extent of a rainfall event, though absolute rainfall values are not considered accurate. The major reason behind is the fact that both global systems are insufficiently parameterized for arid areas. New data from an improved rain gauge network is expected to add value. Secondly, better insights need to be gained on the response of the Wadi to rainfall. The calibration of the hydrological models is currently based on literature and a geological surface map from which we derived infiltration rates. Modelled discharges or flood volumes can only be assessed qualitatively based on the field knowledge of local Bedouins inhabitants. To reduce uncertainty on forecasts and to guide on new data to be collected, a sensitivity analysis with rainfall scenarios is performed.

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.

Arbovirus models to provide practical management tools for mosquito control and disease prevention in the Northern Territory, Australia.

PubMed

Jacups, Susan P; Whelan, Peter I; Harley, David

2011-03-01

Ross River virus (RRV) causes the most common human arbovirus disease in Australia. Although the disease is nonfatal, the associated arthritis and postinfection fatigue can be debilitating for many months, impacting on workforce participation. We sought to create an early-warning system to notify of approaching RRV disease outbreak conditions for major townships in the Northern Territory. By applying a logistic regression model to meteorologic factors, including rainfall, a postestimation analysis of sensitivity and specificity can create rainfall cut-points. These rainfall cut-points indicate the rainfall level above which previous epidemic conditions have occurred. Furthermore, rainfall cut-points indirectly adjust for vertebrate host data from the agile wallaby (Macropus agilis) as the life cycle of the agile wallaby is intricately meshed with the wet season. Once generated, cut-points can thus be used prospectively to allow timely implementation of larval survey and control measures and public health warnings to preemptively reduce RRV disease incidence. Cut-points are location specific and have the capacity to replace previously used models, which require data management and input, and rarely provide timely notification for vector control requirements and public health warnings. These methods can be adapted for use elsewhere.

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...

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.…

The Law Enforcement Officer Stress Survey (LEOSS): Evaluation of Psychometric Properties

ERIC Educational Resources Information Center

Van Hasselt, Vincent B.; Sheehan, Donald C.; Malcolm, Abigail S.; Sellers, Alfred H.; Baker, Monty T.; Couwels, Judy

2008-01-01

This study establishes the reliability and validity of the Law Enforcement Officer Stress Survey (LEOSS), a short early-warning stress-screening measure for law enforcement officers. The initial phase of LEOSS development employed the behavioral-analytic model to construct a 25-item instrument specifically geared toward evaluation of stress in…

Perception or Fact: Measuring the Effectiveness of the Terrorism Early Warning (TEW) Group

DTIC Science & Technology

2005-09-01

alternatives ” (Campbell 2005). The logic model process is a tool that has been used by evaluators for many years to identify performance measures and...pertinent information is obtained, this cell is responsible for the development (pre-event) and use (trans- and post-event) of playbooks and...

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…

Response Characteristics of an Aquatic Biomonitor Used for Rapid Toxicity Detection

DTIC Science & Technology

2004-05-15

for drinking water protection. 14. SUBJECT TERMS 15. NUMBER OF PAGES biological early warning system; Lepomis macrochirus; bluegill; aquatic toxicity...Fort Detrick, MD 21702-5010, USA Key words: biomonitor; biological early warning system; Lepomis macrochirus; bluegill; aquatic toxicity; water ...narcosis are most likely to cause rapid aquatic biomonitor depth related to variations in water quality (primarily responses. Other modes of action may

Understanding the High School Proficiency Test and the Early Warning Test in Relation to HCCC Enrollment Trends.

ERIC Educational Resources Information Center

Taffy, Fred

The Grade 11 High School Proficiency Test (HSPT) and the New Jersey Early Warning Test (EWT) are two key standardized tests that indicate academic ability of county high school graduates which colleges will need to address. While HSPT scores for county high school districts reflect a range of competency in reading, math, and writing, the majority…

Delivery of State-Provided Predictive Analytics to Schools: Wisconsin's DEWS and the Proposed EWIMS Dashboard. WCER Working Paper No. 2016-3

ERIC Educational Resources Information Center

Clune, Bill; Knowles, Jared

2016-01-01

Since 2012, the Wisconsin Department of Public Instruction (DPI) has maintained a statewide predictive analytics system providing schools with an early warning in middle grades of students at risk for not completing high school. DPI is considering extending and enhancing this system, known as the Dropout Early Warning System (DEWS). The proposed…

Looking beyond the destruction of the GLOF-Early Warning System of the Lake 513 in the Peruvian Andes by the local rural population

NASA Astrophysics Data System (ADS)

Christine, Jurt; Vicuña, Luis; Dulce Burga, María; Huggel, Christian; Frey, Holger

2017-04-01

The news about the destruction of the early warning system of the glacial Lake 513 at the headwaters of the Chucchún catchment in Peru's Cordillera Blanca left many people perplexed. The early warning system was installed after around 40 years of glacier hazard management in the region. It was developed within a project that is widely considered as particularly successful with a close cooperation of several Peruvian institutions, the local municipality, the community and Swiss scientists. From a risk reduction point of view, the early warning system is a critical factor and its destruction by local people themselves is hardly comprehensible. Three month of fieldwork on site in the local communities of the Chucchún catchment during and after the installation of the system, including semi-structured interviews, group discussions and participatory observations as well the participation in the project allowed us to get deeper insights into the context and background of what has occurred. Here, we approach the destruction of the early warning system by analyzing different perspectives on encounters between different actors involved - local groups, scientists from Peru and Switzerland, technical staff, NGO in the field of development, representatives of governmental institutions. Such encounters between the different actors during the practice of science (e.g. doing fieldwork) or during the installation of the early warning system (as for instance in meetings on site) are crucial for overcoming gaps between scientific and local knowledge as well as between knowledge and practice. This led to new insights into the discussion of the case of destruction in Chucchún. Mutual perceptions among the groups, self-perceptions and perceptions of both visible and invisible risks shape the discourses about risks and measures in specific situations of encounters during the project. Particularly striking, however, are different perspectives on encounters in the past between representatives of groups which are now involved in the project, and how these encounters are analyzed in the actual in terms of the present and future.

Establishing the fundamentals for an elephant early warning and monitoring system.

PubMed

Zeppelzauer, Matthias; Stoeger, Angela S

2015-09-04

The decline of habitat for elephants due to expanding human activity is a serious conservation problem. This has continuously escalated the human-elephant conflict in Africa and Asia. Elephants make extensive use of powerful infrasonic calls (rumbles) that travel distances of up to several kilometers. This makes elephants well-suited for acoustic monitoring because it enables detecting elephants even if they are out of sight. In sight, their distinct visual appearance makes them a good candidate for visual monitoring. We provide an integrated overview of our interdisciplinary project that established the scientific fundamentals for a future early warning and monitoring system for humans who regularly experience serious conflict with elephants. We first draw the big picture of an early warning and monitoring system, then review the developed solutions for automatic acoustic and visual detection, discuss specific challenges and present open future work necessary to build a robust and reliable early warning and monitoring system that is able to operate in situ. We present a method for the automated detection of elephant rumbles that is robust to the diverse noise sources present in situ. We evaluated the method on an extensive set of audio data recorded under natural field conditions. Results show that the proposed method outperforms existing approaches and accurately detects elephant rumbles. Our visual detection method shows that tracking elephants in wildlife videos (of different sizes and postures) is feasible and particularly robust at near distances. From our project results we draw a number of conclusions that are discussed and summarized. We clearly identified the most critical challenges and necessary improvements of the proposed detection methods and conclude that our findings have the potential to form the basis for a future automated early warning system for elephants. We discuss challenges that need to be solved and summarize open topics in the context of a future early warning and monitoring system. We conclude that a long-term evaluation of the presented methods in situ using real-time prototypes is the most important next step to transfer the developed methods into practical implementation.

Drought early warning and risk management in a changing environment

NASA Astrophysics Data System (ADS)

Pulwarty, R. S.

2011-12-01

Drought has long been recognized as falling into the category of incremental but long-term and cumulative environmental changes, also termed slow-onset or creeping events. These event types would include: air and water quality decline, desertification processes, deforestation and forest fragmentation, loss of biodiversity and habitats, and nitrogen overloading, among others. Climate scientists continue to struggle with recognizing the onset of drought and scientists and policy makers continue to debate the basis (i.e., criteria) for declaring an end to a drought. Risk-based management approaches to drought planning at the national and regional levels have been recommended repeatedly over the years but their prototyping, testing and operational implementation have been limited. This presentation will outline two avenues for disaster risk reduction in the context of drought (1) integrated early warning information systems, and (2) linking disaster risk reduction to climate change adaptation strategies. Adaptation involves not only using operational facilities and infrastructure to cope with the immediate problems but also leaving slack or reserve for coping with multiple stress problems that produce extreme impacts and surprise. Increasing the 'anticipatability' of an event, involves both monitoring of key indicators from appropriate baseline data, and observing early warning signs that assumptions in risk management plans are failing and critical transitions are occurring. Illustrative cases will be drawn from the IPCC Special Report on Managing the Risks of Extreme Events and Disasters (2011), the UN Global Assessment of Disaster Risk Reduction (2011) and implementation activities in which the author has been engaged. Most drought early warning systems have tended to focus on the development and use of physical system indicators and forecasts of trends and thresholds. We show that successful early warning systems that meet expectations of risk management also have explicit foci on (1) integrating physical and social vulnerability indicators across timescales, (2) analytical capacity to generate local scenarios of risk using both analogs and projections, (3) the communication of risk-based information, and (4) the support and governance of a collaborative framework for early warning structures across spatial scales.

Coronal Mass Ejection early-warning mission by solar-photon sailcraft

NASA Astrophysics Data System (ADS)

Vulpetti, Giovanni; Circi, Christian; Pino, Tommaso

2017-11-01

A preliminary investigation of the early warning of solar storms caused by Coronal Mass Ejection has been carried out. A long warning time could be obtained with a sailcraft synchronous with the Earth-Moon barycenter, and stationed well below the L1 point. In this paper, the theory of heliocentric synchronous sailcraft is set up, its perturbed orbit is analyzed, and a potential solution capable of providing an annual synchrony is carried out. A simple analysis of the response from a low-mass electrochromic actuator for the realization of station-keeping attitude maneuvers is put forwards, and an example of propellantless re-orientation maneuver is studied.

Heterogeneous population dynamics and scaling laws near epidemic outbreaks.

PubMed

Widder, Andreas; Kuehn, Christian

2016-10-01

In this paper, we focus on the influence of heterogeneity and stochasticity of the population on the dynamical structure of a basic susceptible-infected-susceptible (SIS) model. First we prove that, upon a suitable mathematical reformulation of the basic reproduction number, the homogeneous system and the heterogeneous system exhibit a completely analogous global behaviour. Then we consider noise terms to incorporate the fluctuation effects and the random import of the disease into the population and analyse the influence of heterogeneity on warning signs for critical transitions (or tipping points). This theory shows that one may be able to anticipate whether a bifurcation point is close before it happens. We use numerical simulations of a stochastic fast-slow heterogeneous population SIS model and show various aspects of heterogeneity have crucial influences on the scaling laws that are used as early-warning signs for the homogeneous system. Thus, although the basic structural qualitative dynamical properties are the same for both systems, the quantitative features for epidemic prediction are expected to change and care has to be taken to interpret potential warning signs for disease outbreaks correctly.

Flash flood warnings for ungauged basins based on high-resolution precipitation forecasts

NASA Astrophysics Data System (ADS)

Demargne, Julie; Javelle, Pierre; Organde, Didier; de Saint Aubin, Céline; Janet, Bruno

2016-04-01

Early detection of flash floods, which are typically triggered by severe rainfall events, is still challenging due to large meteorological and hydrologic uncertainties at the spatial and temporal scales of interest. Also the rapid rising of waters necessarily limits the lead time of warnings to alert communities and activate effective emergency procedures. To better anticipate such events and mitigate their impacts, the French national service in charge of flood forecasting (SCHAPI) is implementing a national flash flood warning system for small-to-medium (up to 1000 km²) ungauged basins based on a discharge-threshold flood warning method called AIGA (Javelle et al. 2014). The current deterministic AIGA system has been run in real-time in the South of France since 2005 and has been tested in the RHYTMME project (rhytmme.irstea.fr/). It ingests the operational radar-gauge QPE grids from Météo-France to run a simplified hourly distributed hydrologic model at a 1-km² resolution every 15 minutes. This produces real-time peak discharge estimates along the river network, which are subsequently compared to regionalized flood frequency estimates to provide warnings according to the AIGA-estimated return period of the ongoing event. The calibration and regionalization of the hydrologic model has been recently enhanced for implementing the national flash flood warning system for the entire French territory by 2016. To further extend the effective warning lead time, the flash flood warning system is being enhanced to ingest Météo-France's AROME-NWC high-resolution precipitation nowcasts. The AROME-NWC system combines the most recent available observations with forecasts from the nowcasting version of the AROME convection-permitting model (Auger et al. 2015). AROME-NWC pre-operational deterministic precipitation forecasts, produced every hour at a 2.5-km resolution for a 6-hr forecast horizon, were provided for 3 significant rain events in September and November 2014 and ingested as time-lagged ensembles. The time-lagged approach is a practical choice of accounting for the atmospheric forecast uncertainty when no extensive forecast archive is available for statistical modelling. The evaluation on 185 basins in the South of France showed significant improvements in terms of flash flood event detection and effective warning lead-time, compared to warnings from the current AIGA setup (without any future precipitation). Various verification metrics (e.g., Relative Mean Error, Brier Skill Score) show the skill of ensemble precipitation and flow forecasts compared to single-valued persistency benchmarks. Planned enhancements include integrating additional probabilistic NWP products (e.g., AROME precipitation ensembles on longer forecast horizon), accounting for and reducing hydrologic uncertainties from the model parameters and initial conditions via data assimilation, and developing a comprehensive observational and post-event damage database to determine decision-relevant warning thresholds for flood magnitude and probability. Javelle, P., Demargne, J., Defrance, D., Arnaud, P., 2014. Evaluating flash flood warnings at ungauged locations using post-event surveys: a case study with the AIGA warning system. Hydrological Sciences Journal, doi: 10.1080/02626667.2014.923970 Auger, L., Dupont, O., Hagelin, S., Brousseau, P., Brovelli, P., 2015. AROME-NWC: a new nowcasting tool based on an operational mesoscale forecasting system. Quarterly Journal of the Royal Meteorological Society, 141: 1603-1611, doi: 10.1002/qj.2463

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

Earthquake magnitude estimation using the τ c and P d method for earthquake early warning systems

NASA Astrophysics Data System (ADS)

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

2013-10-01

Earthquake early warning (EEW) systems are one of the most effective ways to reduce earthquake disaster. Earthquake magnitude estimation is one of the most important and also the most difficult parts of the entire EEW system. In this paper, based on 142 earthquake events and 253 seismic records that were recorded by the KiK-net in Japan, and aftershocks of the large Wenchuan earthquake in Sichuan, we obtained earthquake magnitude estimation relationships using the τ c and P d methods. The standard variances of magnitude calculation of these two formulas are ±0.65 and ±0.56, respectively. The P d value can also be used to estimate the peak ground motion of velocity, then warning information can be released to the public rapidly, according to the estimation results. In order to insure the stability and reliability of magnitude estimation results, we propose a compatibility test according to the natures of these two parameters. The reliability of the early warning information is significantly improved though this test.

Solar Energetic Particle Warnings from a Coronagraph

NASA Technical Reports Server (NTRS)

St Cyr, O. C.; Posner, A.; Burkepile, J. T.

2017-01-01

We report here the concept of using near-real time observations from a coronagraph to provide early warning of a fast coronal mass ejection (CME) and the possible onset of a solar energetic particle (SEP) event. The 1 January 2016, fast CME, and its associated SEP event are cited as an example. The CME was detected by the ground-based K-Cor coronagraph at Mauna Loa Solar Observatory and by the SOHO Large Angle and Spectrometric Coronagraph. The near-real-time availability of the high-cadence K-Cor observations in the low corona leads to an obvious question: Why has no one attempted to use a coronagraph as an early warning device for SEP events? The answer is that the low image cadence and the long latency of existing spaceborne coronagraphs make them valid for archival studies but typically unsuitable for near-real-time forecasting. The January 2016 event provided favorable CME viewing geometry and demonstrated that the primary component of a prototype ground-based system for SEP warnings is available several hours on most days. We discuss how a conceptual CME-based warning system relates to other techniques, including an estimate of the relative SEP warning times, and how such a system might be realized.

Operational tsunami modeling with TsunAWI - Examples for Indonesia and Chile

NASA Astrophysics Data System (ADS)

Rakowsky, Natalja; Androsov, Alexey; Harig, Sven; Immerz, Antonia; Fuchs, Annika; Behrens, Jörn; Danilov, Sergey; Hiller, Wolfgang; Schröter, Jens

2014-05-01

The numerical simulation code TsunAWI was developed in the framework of the German-Indonesian Tsunami Early Warning System (GITEWS). The numerical simulation of prototypical tsunami scenarios plays a decisive role in the a priory risk assessment for coastal regions and in the early warning process itself. TsunAWI is based on a finite element discretization, employs unstructured grids with high resolution along the coast, and includes inundation. This contribution gives an overview of the model itself and presents two applications. For GITEWS, the existing scenario database covering 528 epicenters / 3450 scenarios from Sumatra to Bali was extended by 187 epicenters / 1100 scenarios in the Eastern Sunda Arc. Furthermore, about 1100 scenarios for the Western Sunda Arc were recomputed on the new model domain covering the whole Indonesian Seas. These computations would not have been feasible in the beginning of the project. The unstructured computational grid contains 7 million nodes and resolves all coastal regions with 150m, some project regions and the surrounding of tide gauges with 50m, and the deep ocean with 12km edge length. While in the Western Sunda Arc, the large islands of Sumatra and Java shield the Northern Indonesian Archipelago, tsunamis in the Eastern Sunda Arc can propagate to the North. The unstructured grid approach allows TsunAWI to easily simulate the complex propagation patterns with the self-interactions and the reflections at the coastal regions of myriads of islands. For the Hydrographic and Oceanographic Service of the Chilean Navy (SHOA), we calculated a small scenario database of 100 scenarios (sources by Universidad de Chile) to provide data for a lightweight decision support system prototype (built by DLR). This work is part of the initiation project "Multi hazard information and early warning system in cooperation with Chile" and aims at sharing our experience from GITEWS with the Chilean partners.

Role of remote sensing in desert locust early warning

NASA Astrophysics Data System (ADS)

Cressman, Keith

2013-01-01

Desert locust (Schistocerca gregaria, Forskål) plagues have historically had devastating consequences on food security in Africa and Asia. The current strategy to reduce the frequency of plagues and manage desert locust infestations is early warning and preventive control. To achieve this, the Food and Agriculture Organization of the United Nations operates one of the oldest, largest, and best-known migratory pest monitoring systems in the world. Within this system, remote sensing plays an important role in detecting rainfall and green vegetation. Despite recent technological advances in data management and analysis, communications, and remote sensing, monitoring desert locusts and preventing plagues in the years ahead will continue to be a challenge from a geopolitical and financial standpoint for affected countries and the international donor community. We present an overview of the use of remote sensing in desert locust early warning.

Tsunami Early Warning via a Physics-Based Simulation Pipeline

NASA Astrophysics Data System (ADS)

Wilson, J. M.; Rundle, J. B.; Donnellan, A.; Ward, S. N.; Komjathy, A.

2017-12-01

Through independent efforts, physics-based simulations of earthquakes, tsunamis, and atmospheric signatures of these phenomenon have been developed. With the goal of producing tsunami forecasts and early warning tools for at-risk regions, we join these three spheres to create a simulation pipeline. The Virtual Quake simulator can produce thousands of years of synthetic seismicity on large, complex fault geometries, as well as the expected surface displacement in tsunamigenic regions. These displacements are used as initial conditions for tsunami simulators, such as Tsunami Squares, to produce catalogs of potential tsunami scenarios with probabilities. Finally, these tsunami scenarios can act as input for simulations of associated ionospheric total electron content, signals which can be detected by GNSS satellites for purposes of early warning in the event of a real tsunami. We present the most recent developments in this project.

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.

98. View of IBM digital computer model 7090 magnet core ...

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

98. View of IBM digital computer model 7090 magnet core installation. ITT Artic Services, Inc., Official photograph BMEWS Site II, Clear, AK, by unknown photographer, 17 September 1965. BMEWS, clear as negative no. A-6606. - 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

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.

Using natural archives to detect climate and environmental tipping points in the Earth System

NASA Astrophysics Data System (ADS)

Thomas, Zoë A.

2016-11-01

'Tipping points' in the Earth system are characterised by a nonlinear response to gradual forcing, and may have severe and wide-ranging impacts. Many abrupt events result from simple underlying system dynamics termed 'critical transitions' or 'bifurcations'. One of the best ways to identify and potentially predict threshold behaviour in the climate system is through analysis of natural ('palaeo') archives. Specifically, on the approach to a tipping point, early warning signals can be detected as characteristic fluctuations in a time series as a system loses stability. Testing whether these early warning signals can be detected in highly complex real systems is a key challenge, since much work is either theoretical or only tested with simple models. This is particularly problematic in palaeoclimate and palaeoenvironmental records with low resolution, non-equidistant data, which can limit accurate analysis. Here, a range of different datasets are examined to explore generic rules that can be used to detect such dramatic events. A number of key criteria are identified to be necessary for the reliable identification of early warning signals in natural archives, most crucially, the need for a low-noise record of sufficient data length, resolution and accuracy. A deeper understanding of the underlying system dynamics is required to inform the development of more robust system-specific indicators, or to indicate the temporal resolution required, given a known forcing. This review demonstrates that time series precursors from natural archives provide a powerful means of forewarning tipping points within the Earth System.

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.

Seismic instrumentation plan for the Hawaiian Volcano Observatory

USGS Publications Warehouse

Thelen, Weston A.

2014-01-01

The installation of new seismic stations is only the first part of building a volcanic early warning capability for seismicity in the State of Hawaii. Additional personnel will likely be required to study the volcanic processes at work under each volcano, analyze the current seismic activity at a level sufficient for early warning, build new tools for monitoring, maintain seismic computing resources, and maintain the new seismic stations.

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.

Are Two Commonly Used Early Warning Indicators Accurate Predictors of Dropout for English Learner Students? Evidence from Six Districts in Washington State. REL 2017-261

ERIC Educational Resources Information Center

Deussen, Theresa; Hanson, Havala; Bisht, Biraj

2017-01-01

Students who drop out of high school are at increased risk of a range of negative social and economic consequences, including lower earnings and poorer health. To reduce dropout rates and lessen these negative consequences, districts around the country are using early warning indicators to identify and provide supports for students at risk of…

Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data

PubMed Central

Dakos, Vasilis; Carpenter, Stephen R.; Brock, William A.; Ellison, Aaron M.; Guttal, Vishwesha; Ives, Anthony R.; Kéfi, Sonia; Livina, Valerie; Seekell, David A.; van Nes, Egbert H.; Scheffer, Marten

2012-01-01

Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called ‘early warning signals’, and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data. PMID:22815897

Advances in the mechanisms and early warning indicators of the postoperative cognitive dysfunction after the extracorporeal circulation.

PubMed

Liu, Chao; Han, Jian-ge

2015-02-01

The high incidence of postoperative cognitive dysfunction (POCD) after extracorporeal circulation has seriously affected the prognosis and quality of life. Its mechanism may involve the inflammatory response and oxidative stress,the excessive phosphorylation of tau protein, the decreased blood volume and oxygen in the cerebral cortex. Appropriate early warning indicators of POCD after the extracorporeal circulation should be chosen to facilitate the cross validation of the results obtained different technical approaches and thus promote the early diagnosis and treatment of POCD.

Dengue Baidu Search Index data can improve the prediction of local dengue epidemic: A case study in Guangzhou, China

PubMed Central

Liu, Tao; Zhu, Guanghu; Lin, Hualiang; Zhang, Yonghui; He, Jianfeng; Deng, Aiping; Peng, Zhiqiang; Xiao, Jianpeng; Rutherford, Shannon; Xie, Runsheng; Zeng, Weilin; Li, Xing; Ma, Wenjun

2017-01-01

Background Dengue fever (DF) in Guangzhou, Guangdong province in China is an important public health issue. The problem was highlighted in 2014 by a large, unprecedented outbreak. In order to respond in a more timely manner and hence better control such potential outbreaks in the future, this study develops an early warning model that integrates internet-based query data into traditional surveillance data. Methodology and principal findings A Dengue Baidu Search Index (DBSI) was collected from the Baidu website for developing a predictive model of dengue fever in combination with meteorological and demographic factors. Generalized additive models (GAM) with or without DBSI were established. The generalized cross validation (GCV) score and deviance explained indexes, intraclass correlation coefficient (ICC) and root mean squared error (RMSE), were respectively applied to measure the fitness and the prediction capability of the models. Our results show that the DBSI with one-week lag has a positive linear relationship with the local DF occurrence, and the model with DBSI (ICC:0.94 and RMSE:59.86) has a better prediction capability than the model without DBSI (ICC:0.72 and RMSE:203.29). Conclusions Our study suggests that a DSBI combined with traditional disease surveillance and meteorological data can improve the dengue early warning system in Guangzhou. PMID:28263988

SPIRALE: early warning optical space demonstrator

NASA Astrophysics Data System (ADS)

Galindo, D.; Carucci, A.

2004-11-01

Thanks to its global coverage, its peacetime capabilities and its availability, ballistic missiles Early Warning (EW) space systems are identified as a key node of a global missile defence system. Since the Gulf war in 1991, several feasibility studies of such an Early Warning system have been conducted in France. The main conclusions are first that the most appropriate concept is to use infra-red (IR) sensors on geo- stationary orbit satellites and second that the required satellite performances are achievable and accessible to European industries, even if technological developments are necessary. Besides that, it was recommended to prepare the development of the EW operational system, by demonstrating its achievable performances on the basis of collected background images and available target IR signatures. This is the objective of the "EW optical space demonstrator", also named SPIRALE (this a French acronym which stands for "Preparatory IR Program for EW"). A contract has been awarded early 2004, by DGA/SPOTI (French Armament Procurement Agency), to EADS Astrium France, with a significant participation of Alcatel Space, to perform this demonstration.

The value of vital sign trends for detecting clinical deterioration on the wards

PubMed Central

Churpek, Matthew M; Adhikari, Richa; Edelson, Dana P

2016-01-01

Aim Early detection of clinical deterioration on the wards may improve outcomes, and most early warning scores only utilize a patient’s current vital signs. The added value of vital sign trends over time is poorly characterized. We investigated whether adding trends improves accuracy and which methods are optimal for modelling trends. Methods Patients admitted to five hospitals over a five-year period were included in this observational cohort study, with 60% of the data used for model derivation and 40% for validation. Vital signs were utilized to predict the combined outcome of cardiac arrest, intensive care unit transfer, and death. The accuracy of models utilizing both the current value and different trend methods were compared using the area under the receiver operating characteristic curve (AUC). Results A total of 269,999 patient admissions were included, which resulted in 16,452 outcomes. Overall, trends increased accuracy compared to a model containing only current vital signs (AUC 0.78 vs. 0.74; p<0.001). The methods that resulted in the greatest average increase in accuracy were the vital sign slope (AUC improvement 0.013) and minimum value (AUC improvement 0.012), while the change from the previous value resulted in an average worsening of the AUC (change in AUC −0.002). The AUC increased most for systolic blood pressure when trends were added (AUC improvement 0.05). Conclusion Vital sign trends increased the accuracy of models designed to detect critical illness on the wards. Our findings have important implications for clinicians at the bedside and for the development of early warning scores. PMID:26898412

The value of vital sign trends for detecting clinical deterioration on the wards.

PubMed

Churpek, Matthew M; Adhikari, Richa; Edelson, Dana P

2016-05-01

Early detection of clinical deterioration on the wards may improve outcomes, and most early warning scores only utilize a patient's current vital signs. The added value of vital sign trends over time is poorly characterized. We investigated whether adding trends improves accuracy and which methods are optimal for modelling trends. Patients admitted to five hospitals over a five-year period were included in this observational cohort study, with 60% of the data used for model derivation and 40% for validation. Vital signs were utilized to predict the combined outcome of cardiac arrest, intensive care unit transfer, and death. The accuracy of models utilizing both the current value and different trend methods were compared using the area under the receiver operating characteristic curve (AUC). A total of 269,999 patient admissions were included, which resulted in 16,452 outcomes. Overall, trends increased accuracy compared to a model containing only current vital signs (AUC 0.78 vs. 0.74; p<0.001). The methods that resulted in the greatest average increase in accuracy were the vital sign slope (AUC improvement 0.013) and minimum value (AUC improvement 0.012), while the change from the previous value resulted in an average worsening of the AUC (change in AUC -0.002). The AUC increased most for systolic blood pressure when trends were added (AUC improvement 0.05). Vital sign trends increased the accuracy of models designed to detect critical illness on the wards. Our findings have important implications for clinicians at the bedside and for the development of early warning scores. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Integrating Remote Sensing and Disease Surveillance to Forecast Malaria Epidemics

NASA Astrophysics Data System (ADS)

Wimberly, M. C.; Beyane, B.; DeVos, M.; Liu, Y.; Merkord, C. L.; Mihretie, A.

2015-12-01

Advance information about the timing and locations of malaria epidemics can facilitate the targeting of resources for prevention and emergency response. Early detection methods can detect incipient outbreaks by identifying deviations from expected seasonal patterns, whereas early warning approaches typically forecast future malaria risk based on lagged responses to meteorological factors. A critical limiting factor for implementing either of these approaches is the need for timely and consistent acquisition, processing and analysis of both environmental and epidemiological data. To address this need, we have developed EPIDEMIA - an integrated system for surveillance and forecasting of malaria epidemics. The EPIDEMIA system includes a public health interface for uploading and querying weekly surveillance reports as well as algorithms for automatically validating incoming data and updating the epidemiological surveillance database. The newly released EASTWeb 2.0 software application automatically downloads, processes, and summaries remotely-sensed environmental data from multiple earth science data archives. EASTWeb was implemented as a component of the EPIDEMIA system, which combines the environmental monitoring data and epidemiological surveillance data into a unified database that supports both early detection and early warning models. Dynamic linear models implemented with Kalman filtering were used to carry out forecasting and model updating. Preliminary forecasts have been disseminated to public health partners in the Amhara Region of Ethiopia and will be validated and refined as the EPIDEMIA system ingests new data. In addition to continued model development and testing, future work will involve updating the public health interface to provide a broader suite of outbreak alerts and data visualization tools that are useful to our public health partners. The EPIDEMIA system demonstrates a feasible approach to synthesizing the information from epidemiological surveillance systems and remotely-sensed environmental monitoring systems to improve malaria epidemic detection and forecasting.

Integrated Land- and Underwater-Based Sensors for a Subduction Zone Earthquake Early Warning System

NASA Astrophysics Data System (ADS)

Pirenne, B.; Rosenberger, A.; Rogers, G. C.; Henton, J.; Lu, Y.; Moore, T.

2016-12-01

Ocean Networks Canada (ONC — oceannetworks.ca/ ) operates cabled ocean observatories off the coast of British Columbia (BC) to support research and operational oceanography. Recently, ONC has been funded by the Province of BC to deliver an earthquake early warning (EEW) system that integrates offshore and land-based sensors to deliver alerts of incoming ground shaking from the Cascadia Subduction Zone. ONC's cabled seismic network has the unique advantage of being located offshore on either side of the surface expression of the subduction zone. The proximity of ONC's sensors to the fault can result in faster, more effective warnings, which translates into more lives saved, injuries avoided and more ability for mitigative actions to take place.ONC delivers near real-time data from various instrument types simultaneously, providing distinct advantages to seismic monitoring and earthquake early warning. The EEW system consists of a network of sensors, located on the ocean floor and on land, that detect and analyze the initial p-wave of an earthquake as well as the crustal deformation on land during the earthquake sequence. Once the p-wave is detected and characterized, software systems correlate the data streams of the various sensors and deliver alerts to clients through a Common Alerting Protocol-compliant data package. This presentation will focus on the development of the earthquake early warning capacity at ONC. It will describe the seismic sensors and their distribution, the p-wave detection algorithms selected and the overall architecture of the system. It will further overview the plan to achieve operational readiness at project completion.

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

Incorporating the Wind Erosion Prediction System (WEPS) Into a Regional Air Quality Modeling System for the Pacific Northwest

USDA-ARS?s Scientific Manuscript database

In the Pacific Northwest, wind storms intermittently cause massive dust events that reduce visibility along roadways and jeopardize health as a result of extremely high concentrations of PM10 (particulate matter less than or equal to 10µm in diameter). An early warning dust forecast system is needed...

The Example of Eastern Africa: the dynamic of Rift Valley fever and tools for monitoring virus activity

USDA-ARS?s Scientific Manuscript database

Rift Valley fever is a mosquito-borne viral zoonosis that primarily affects animals but also has the capacity to infect humans. Outbreaks of this disease in eastern Africa are closely associated with periods of heavy rainfall and forecasting models and early warning systems have been developed to en...

Predicting Student Success by Modeling Student Interaction in Asynchronous Online Courses

ERIC Educational Resources Information Center

Shelton, Brett E.; Hung, Jui-Long; Lowenthal, Patrick R.

2017-01-01

Early-warning intervention for students at risk of failing their online courses is increasingly important for higher education institutions. Students who show high levels of engagement appear less likely to be at risk of failing, and how engaged a student is in their online experience can be characterized as factors contributing to their social…

The Trend of Voluntary Warnings in Electronic Nicotine Delivery System Magazine Advertisements.

PubMed

Shang, Ce; Chaloupka, Frank J

2017-01-10

Some manufacturers of electronic nicotine delivery systems (ENDS) voluntarily carried health warnings in their advertisements. This study examined these voluntary warnings in magazine ads and plotted their trends between 2012 and early 2015. ENDS magazine ads were obtained through Kantar media and warnings were collected from the Chicago Public Library or the Trinkets and Trash surveillance system. The prevalence of voluntary warnings, warnings with the specific capitalized word "WARNING", and MarkTen warnings were examined after being weighted using factors related to exposure between January 2012 and March 2015. Five brands (MarkTen, NJOY, MISTIC, and some Blu) carried warnings during the study period. The prevalence of warnings post 2012 that contained a description of nicotine did not significantly increase until the launch of MarkTen, which also happened several months before April 2014 when the U.S. food and drug administration (FDA) published its proposed deeming rule. In addition, none of these warnings met the criteria required by the FDA in the final rules. Voluntary warnings, particularly MarkTen warnings, significantly increased in ENDS magazine ads between 2014 and 2015. It is important to monitor how ENDS manufacturers will comply with the FDA regulation related to warnings and how this regulation will ultimately impact ENDS risk perceptions and use.

Aerial Refueling For NATO’s Smart Defence Initiative

DTIC Science & Technology

2012-04-01

Rome: NATO Defense College, 2012, 148. 40 David A. Brown , "NATO Studying Development of Dedicated Refueling Unit Similar to Early Warning Force...accessed March 1, 2012). Brown , David A. "NATO Studying Development of Dedicated Refueling Unit Similar to Early Warning Force." Aviation Week...Aircraft. Coulsdon, Surrey: IHS Global Limited, 2011. Jennings, Gareth . "Nations Pool for NATO C-17A Fleet." Jane’s Defence Weekly, October 2008

Getting Students on Track for Graduation: Impacts of the Early Warning Intervention and Monitoring System after One Year. REL 2017-272

ERIC Educational Resources Information Center

Faria, Ann-Marie; Sorensen, Nicholas; Heppen, Jessica; Bowdon, Jill; Taylor, Suzanne; Eisner, Ryan; Foster, Shandu

2017-01-01

Although high school graduation rates are rising--the national rate was 82 percent during the 2013/14 school year (U.S. Department of Education, 2015)--dropping out remains a persistent problem in the Midwest and nationally. Many schools now use early warning systems to identify students who are at risk of not graduating, with the goal of…

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

Efficient Flame Detection and Early Warning Sensors on Combustible Materials Using Hierarchical Graphene Oxide/Silicone Coatings.

PubMed

Wu, Qian; Gong, Li-Xiu; Li, Yang; Cao, Cheng-Fei; Tang, Long-Cheng; Wu, Lianbin; Zhao, Li; Zhang, Guo-Dong; Li, Shi-Neng; Gao, Jiefeng; Li, Yongjin; Mai, Yiu-Wing

2018-01-23

Design and development of smart sensors for rapid flame detection in postcombustion and early fire warning in precombustion situations are critically needed to improve the fire safety of combustible materials in many applications. Herein, we describe the fabrication of hierarchical coatings created by assembling a multilayered graphene oxide (GO)/silicone structure onto different combustible substrate materials. The resulting coatings exhibit distinct temperature-responsive electrical resistance change as efficient early warning sensors for detecting abnormal high environmental temperature, thus enabling fire prevention below the ignition temperature of combustible materials. After encountering a flame attack, we demonstrate extremely rapid flame detection response in 2-3 s and excellent flame self-extinguishing retardancy for the multilayered GO/silicone structure that can be synergistically transformed to a multiscale graphene/nanosilica protection layer. The hierarchical coatings developed are promising for fire prevention and protection applications in various critical fire risk and related perilous circumstances.

The Self-Organising Seismic Early Warning Information Network: Scenarios

NASA Astrophysics Data System (ADS)

Kühnlenz, F.; Fischer, J.; Eveslage, I.

2009-04-01

SAFER and EDIM working groups, the Department of Computer Science, Humboldt-Universität zu Berlin, Berlin, Germany, and Section 2.1 Earthquake Risk and Early Warning, GFZ German Research Centre for Geosciences, Germany Contact: Frank Kühnlenz, kuehnlenz@informatik.hu-berlin.de 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). It uses SEEDLink to store and provide access to the sensor data. 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 should be of great value to do this job in a shorter time and with less manpower compared to using common seismic stations. 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 network and finally a scenario deals with the visualization of the alarming protocol detecting an earthquake event and issuing an early warning.

An assessment of a North American Multi-Model Ensemble (NMME) based global drought early warning forecast system

NASA Astrophysics Data System (ADS)

Wood, E. F.; Yuan, X.; Sheffield, J.; Pan, M.; Roundy, J.

2013-12-01

One of the key recommendations of the WCRP Global Drought Information System (GDIS) workshop is to develop an experimental real-time global monitoring and prediction system. While great advances has been made in global drought monitoring based on satellite observations and model reanalysis data, global drought forecasting has been stranded in part due to the limited skill both in climate forecast models and global hydrologic predictions. Having been working on drought monitoring and forecasting over USA for more than a decade, the Princeton land surface hydrology group is now developing an experimental global drought early warning system that is based on multiple climate forecast models and a calibrated global hydrologic model. In this presentation, we will test its capability in seasonal forecasting of meteorological, agricultural and hydrologic droughts over global major river basins, using precipitation, soil moisture and streamflow forecasts respectively. Based on the joint probability distribution between observations using Princeton's global drought monitoring system and model hindcasts and real-time forecasts from North American Multi-Model Ensemble (NMME) project, we (i) bias correct the monthly precipitation and temperature forecasts from multiple climate forecast models, (ii) downscale them to a daily time scale, and (iii) use them to drive the calibrated VIC model to produce global drought forecasts at a 1-degree resolution. A parallel run using the ESP forecast method, which is based on resampling historical forcings, is also carried out for comparison. Analysis is being conducted over global major river basins, with multiple drought indices that have different time scales and characteristics. The meteorological drought forecast does not have uncertainty from hydrologic models and can be validated directly against observations - making the validation an 'apples-to-apples' comparison. Preliminary results for the evaluation of meteorological drought onset hindcasts indicate that climate models increase drought detectability over ESP by 31%-81%. However, less than 30% of the global drought onsets can be detected by climate models. The missed drought events are associated with weak ENSO signals and lower potential predictability. Due to the high false alarms from climate models, the reliability is more important than sharpness for a skillful probabilistic drought onset forecast. Validations and skill assessments for agricultural and hydrologic drought forecasts are carried out using soil moisture and streamflow output from the VIC land surface model (LSM) forced by a global forcing data set. Given our previous drought forecasting experiences over USA and Africa, validating the hydrologic drought forecasting is a significant challenge for a global drought early warning system.

A comparison of large-scale climate signals and the North American Multi-Model Ensemble (NMME) for drought prediction in China

NASA Astrophysics Data System (ADS)

Xu, Lei; Chen, Nengcheng; Zhang, Xiang

2018-02-01

Drought is an extreme natural disaster that can lead to huge socioeconomic losses. Drought prediction ahead of months is helpful for early drought warning and preparations. In this study, we developed a statistical model, two weighted dynamic models and a statistical-dynamic (hybrid) model for 1-6 month lead drought prediction in China. Specifically, statistical component refers to climate signals weighting by support vector regression (SVR), dynamic components consist of the ensemble mean (EM) and Bayesian model averaging (BMA) of the North American Multi-Model Ensemble (NMME) climatic models, and the hybrid part denotes a combination of statistical and dynamic components by assigning weights based on their historical performances. The results indicate that the statistical and hybrid models show better rainfall predictions than NMME-EM and NMME-BMA models, which have good predictability only in southern China. In the 2011 China winter-spring drought event, the statistical model well predicted the spatial extent and severity of drought nationwide, although the severity was underestimated in the mid-lower reaches of Yangtze River (MLRYR) region. The NMME-EM and NMME-BMA models largely overestimated rainfall in northern and western China in 2011 drought. In the 2013 China summer drought, the NMME-EM model forecasted the drought extent and severity in eastern China well, while the statistical and hybrid models falsely detected negative precipitation anomaly (NPA) in some areas. Model ensembles such as multiple statistical approaches, multiple dynamic models or multiple hybrid models for drought predictions were highlighted. These conclusions may be helpful for drought prediction and early drought warnings in China.

Main components and characteristics of landslide early warning systems operational worldwide

NASA Astrophysics Data System (ADS)

Piciullo, Luca; Cepeda, José

2017-04-01

During the last decades the number of victims and economic losses due to natural hazards are dramatically increased worldwide. The reason can be mainly ascribed to climate changes and urbanization in areas exposed at high level of risk. Among the many mitigation measures available for reducing the risk to life related to natural hazards, early warning systems certainly constitute a significant cost-effective option available to the authorities in charge of risk management and governance. The aim is to help and protect populations exposed to natural hazards, reducing fatalities when major events occur. Landslide is one of the natural hazards addressed by early warning systems. Landslide early warning systems (LEWSs) are mainly composed by the following four components: set-up, correlation laws, decisional algorithm and warning management. Within this framework, the set-up includes all the preliminary actions and choices necessary for designing a LEWS, such as: the area covered by the system, the types of landslides and the monitoring instruments. The monitoring phase provides a series of important information on different variables, considered as triggering factors for landslides, in order to define correlation laws and thresholds. Then, a decisional algorithm is necessary for defining the: number of warning levels to be employed in the system, decision making procedures, and everything else system managers may need for issuing warnings in different warning zones. Finally the warning management is composed by: monitoring and warning strategy; communication strategy; emergency plan and, everything connected to the social sphere. Among LEWSs operational worldwide, two categories can be defined as a function of the scale of analysis: "local" and "territorial" systems. The scale of analysis influences several actions and aspects connected to the design and employment of the system, such as: the actors involved, the monitoring systems, type of landslide phenomena addressed and variables to be considered for correlations. The characteristics of LEWSs at local scale are strongly affected by numerous constraints and factors, from time to time different, related to the characteristics of the problem they address. Monitoring measures, variables and correlation laws considered for the design and employment of local LEWSs, strongly depends on the type of landslide to be addressed. On the other hand, territorial LEWSs mainly deals with rainfall-induced landslides characterized by fast slope movement. These systems have become a risk management approach, employed worldwide over areas of relevant extension. Before 2005 only few experiences of LEWSs at a regional scale were carried out, such as in: Hong Kong, China; Zhejiang Province, China; San Francisco Bay, California, USA; Appalachians, USA; Oregon, USA; Rio de Janeiro, Brazil. Since the beginning of the XXI century, increased knowledge on rainfall-landslide correlations and upgraded technologies in weather forecast have promoted the development and improvement of territorial LEWSs around the world.

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?

Earthquake Early Warning ShakeAlert System: Testing and certification platform

USGS Publications Warehouse

Cochran, Elizabeth S.; Kohler, Monica D.; Given, Douglas; Guiwits, Stephen; Andrews, Jennifer; Meier, Men-Andrin; Ahmad, Mohammad; Henson, Ivan; Hartog, Renate; Smith, Deborah

2017-01-01

Earthquake early warning systems provide warnings to end users of incoming moderate to strong ground shaking from earthquakes. An earthquake early warning system, ShakeAlert, is providing alerts to beta end users in the western United States, specifically California, Oregon, and Washington. An essential aspect of the earthquake early warning system is the development of a framework to test modifications to code to ensure functionality and assess performance. In 2016, a Testing and Certification Platform (TCP) was included in the development of the Production Prototype version of ShakeAlert. The purpose of the TCP is to evaluate the robustness of candidate code that is proposed for deployment on ShakeAlert Production Prototype servers. TCP consists of two main components: a real‐time in situ test that replicates the real‐time production system and an offline playback system to replay test suites. The real‐time tests of system performance assess code optimization and stability. The offline tests comprise a stress test of candidate code to assess if the code is production ready. The test suite includes over 120 events including local, regional, and teleseismic historic earthquakes, recentering and calibration events, and other anomalous and potentially problematic signals. Two assessments of alert performance are conducted. First, point‐source assessments are undertaken to compare magnitude, epicentral location, and origin time with the Advanced National Seismic System Comprehensive Catalog, as well as to evaluate alert latency. Second, we describe assessment of the quality of ground‐motion predictions at end‐user sites by comparing predicted shaking intensities to ShakeMaps for historic events and implement a threshold‐based approach that assesses how often end users initiate the appropriate action, based on their ground‐shaking threshold. TCP has been developed to be a convenient streamlined procedure for objectively testing algorithms, and it has been designed with flexibility to accommodate significant changes in development of new or modified system code. It is expected that the TCP will continue to evolve along with the ShakeAlert system, and the framework we describe here provides one example of how earthquake early warning systems can be evaluated.

Canadian crop calendars in support of the early warning project

NASA Technical Reports Server (NTRS)

Trenchard, M. H.; Hodges, T. (Principal Investigator)

1980-01-01

The Canadian crop calendars for LACIE are presented. Long term monthly averages of daily maximum and daily minimum temperatures for subregions of provinces were used to simulate normal daily maximum and minimum temperatures. The Robertson (1968) spring wheat and Williams (1974) spring barley phenology models were run using the simulated daily temperatures and daylengths for appropriate latitudes. Simulated daily temperatures and phenology model outputs for spring wheat and spring barley are given.

97. View of International Business Machine (IBM) digital computer model ...

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

97. View of International Business Machine (IBM) digital computer model 7090 magnetic core installation, international telephone and telegraph (ITT) Artic Services Inc., Official photograph BMEWS site II, Clear, AK, by unknown photographer, 17 September 1965, BMEWS, clear as negative no. A-6604. - 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 web-based Tamsui River flood early-warning system with correction of real-time water stage using monitoring data

NASA Astrophysics Data System (ADS)

Liao, H. Y.; Lin, Y. J.; Chang, H. K.; Shang, R. K.; Kuo, H. C.; Lai, J. S.; Tan, Y. C.

2017-12-01

Taiwan encounters heavy rainfalls frequently. There are three to four typhoons striking Taiwan every year. To provide lead time for reducing flood damage, this study attempt to build a flood early-warning system (FEWS) in Tanshui River using time series correction techniques. The predicted rainfall is used as the input for the rainfall-runoff model. Then, the discharges calculated by the rainfall-runoff model is converted to the 1-D river routing model. The 1-D river routing model will output the simulating water stages in 487 cross sections for the future 48-hr. The downstream water stage at the estuary in 1-D river routing model is provided by storm surge simulation. Next, the water stages of 487 cross sections are corrected by time series model such as autoregressive (AR) model using real-time water stage measurements to improve the predicted accuracy. The results of simulated water stages are displayed on a web-based platform. In addition, the models can be performed remotely by any users with web browsers through a user interface. The on-line video surveillance images, real-time monitoring water stages, and rainfalls can also be shown on this platform. If the simulated water stage exceeds the embankments of Tanshui River, the alerting lights of FEWS will be flashing on the screen. This platform runs periodically and automatically to generate the simulation graphic data of flood water stages for flood disaster prevention and decision making.

Global Environmental Alert Service

NASA Astrophysics Data System (ADS)

Grasso, V. F.; Cervone, G.; Singh, A.; Kafatos, M.

2006-12-01

Every year natural disasters such as earthquakes, floods, hurricanes, tsunamis, etc. occur around the world, causing hundreds of thousands of deaths and injuries, billions of dollars in economic losses, and destroying natural landmarks and adveresely affecting ecosystems. Due to increasing urbanization, and increasingly higher percentage of the world's population living in megacities, the existence of nuclear power plants and other facilities whose potential destruction poses unacceptable high risks, natural hazards represent an increasing threat for economic losses, as well as risk to people and property. Warning systems represent an innovative and effective approach to mitigate the risks associated with natural hazards. Several state-of-the-art analyses show that early warning technologies are now available for most natural hazards and systems are already in operation in some parts of the world. Nevertheless, recent disasters such as the 2004 Indian Ocean tsunami, the 2005 Kashmir earthquake and the 2005 Katrina hurricane, highlighted inadequacies in early warning system technologies. Furthermore, not all available technologies are deployed in every part of the world, due to the lack of awareness and resources in the poorer countries, leaving very large and densely populated areas at risk. Efforts towards the development of a global warning system are necessary for filling the gaps of existing technologies. A globally comprehensive early warning system based on existing technologies will be a means to consolidate scientific knowledge, package it in a form usable to international and national decision makers and actively disseminate this information to protect people and properties. There is not a single information broker who searches and packages the policy relevant material and delivers it in an understandable format to the public and decision makers. A critical review of existing systems reveals the need for the innovative service. We propose here a Global Environmental Alert Service (GEAS) that could provide information from monitoring, Earth observing and early warning systems to users in a near real time mode and bridge the gap between the scientific community and policy makers. Characteristics and operational aspects of GEAS are discussed.

Financial Distress Prediction using Linear Discriminant Analysis and Support Vector Machine

NASA Astrophysics Data System (ADS)

Santoso, Noviyanti; Wibowo, Wahyu

2018-03-01

A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.

Probabilistic flood warning using grand ensemble weather forecasts

NASA Astrophysics Data System (ADS)

He, Y.; Wetterhall, F.; Cloke, H.; Pappenberger, F.; Wilson, M.; Freer, J.; McGregor, G.

2009-04-01

As the severity of floods increases, possibly due to climate and landuse change, there is urgent need for more effective and reliable warning systems. The incorporation of numerical weather predictions (NWP) into a flood warning system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and can lead to a high number of false or missed warnings. An ensemble of weather forecasts from one Ensemble Prediction System (EPS), when used on catchment hydrology, can provide improved early flood warning as some of the uncertainties can be quantified. EPS forecasts from a single weather centre only account for part of the uncertainties originating from initial conditions and stochastic physics. Other sources of uncertainties, including numerical implementations and/or data assimilation, can only be assessed if a grand ensemble of EPSs from different weather centres is used. When various models that produce EPS from different weather centres are aggregated, the probabilistic nature of the ensemble precipitation forecasts can be better retained and accounted for. The availability of twelve global EPSs through the 'THORPEX Interactive Grand Global Ensemble' (TIGGE) offers a new opportunity for the design of an improved probabilistic flood forecasting framework. This work presents a case study using the TIGGE database for flood warning on a meso-scale catchment. The upper reach of the River Severn catchment located in the Midlands Region of England is selected due to its abundant data for investigation and its relatively small size (4062 km2) (compared to the resolution of the NWPs). This choice was deliberate as we hypothesize that the uncertainty in the forcing of smaller catchments cannot be represented by a single EPS with a very limited number of ensemble members, but only through the variance given by a large number ensembles and ensemble system. A coupled atmospheric-hydrologic-hydraulic cascade system driven by the TIGGE ensemble forecasts is set up to study the potential benefits of using the TIGGE database in early flood warning. Physically based and fully distributed LISFLOOD suite of models is selected to simulate discharge and flood inundation consecutively. The results show the TIGGE database is a promising tool to produce forecasts of discharge and flood inundation comparable with the observed discharge and simulated inundation driven by the observed discharge. The spread of discharge forecasts varies from centre to centre, but it is generally large, implying a significant level of uncertainties. Precipitation input uncertainties dominate and propagate through the cascade chain. The current NWPs fall short of representing the spatial variability of precipitation on a comparatively small catchment. This perhaps indicates the need to improve NWPs resolution and/or disaggregation techniques to narrow down the spatial gap between meteorology and hydrology. It is not necessarily true that early flood warning becomes more reliable when more ensemble forecasts are employed. It is difficult to identify the best forecast centre(s), but in general the chance of detecting floods is increased by using the TIGGE database. Only one flood event was studied because most of the TIGGE data became available after October 2007. It is necessary to test the TIGGE ensemble forecasts with other flood events in other catchments with different hydrological and climatic regimes before general conclusions can be made on its robustness and applicability.

Detection of Deteriorating Patients on Surgical Wards Outside the ICU by an Automated MEWS-Based Early Warning System With Paging Functionality.

PubMed

Heller, Axel R; Mees, Sören T; Lauterwald, Benjamin; Reeps, Christian; Koch, Thea; Weitz, Jürgen

2018-05-16

The establishment of early warning systems in hospitals was strongly recommended in recent guidelines to detect deteriorating patients early and direct them to adequate care. Upon reaching predefined trigger criteria, Medical Emergency Teams (MET) should be notified and directed to these patients. The present study analyses the effect of introducing an automated multiparameter early warning score (MEWS)-based early warning system with paging functionality on 2 wards hosting patients recovering from highly complex surgical interventions. The deployment of the system was accompanied by retrospective data acquisition during 12 months (intervention) using 4 routine databases: Hospital patient data management, anesthesia database, local data of the German Resuscitation Registry, and measurement logs of the deployed system (intervention period only). A retrospective 12-month data review using the same aforementioned databases before the deployment of the system served as control. Control and intervention phases were separated by a 6-month washout period for the installation of the system and for training. Data from 3827 patients could be acquired from 2 surgical wards during the two 12-month periods, 1896 patients in the control and 1931 in the intervention cohorts. Patient characteristics differed between the 2 observation phases. American Society of Anesthesiologists risk classification and duration of surgery as well as German DRG case-weight were significantly higher in the intervention period. However, the rate of cardiac arrests significantly dropped from 5.3 to 2.1 per 1000 admissions in the intervention period (P < 0.001). This observation was paralleled by a reduction of unplanned ICU admissions from 3.6% to 3.0% (P < 0.001), and an increase of notifications of critical conditions to the ward surgeon. The primary triggers for MET activation were abnormal ECG alerts, specifically asystole (n = 5), and pulseless electric activity (n = 8). In concert with a well-trained and organized MET, the early deterioration detection of patients on surgical wards outside the ICU may be improved by introducing an automated MEWS-based early warning system with paging functionality.

Design and field test equipment of river water level detection based on ultrasonic sensor and SMS gateway as flood early warning

NASA Astrophysics Data System (ADS)

Sulistyowati, Riny; Sujono, Hari Agus; Musthofa, Ahmad Khamdi

2017-06-01

Due to the high rainfall, flood often occurs in some regions, especially in the area adjacent to the river banks that led to the idea to make the river water level detection system as a flood early warning. Several researches have produced flood detection equipment based on ultrasonic sensors and android as flood early warning system. This paper reported the results of a field test detection equipment to measure the river water level of the Bengawansolo River that was conducted in three villages in the district of Bungah, Dukun, and Manyar in Gresik regency. Tests were conducted simultaneously for 21 hours during heavy rainfall. The test results demonstrated the accuracy of the equipment of 97.28% for all categories of observation. The application of AFD (Android Flood Detection) via android smartphone demonstrated its precision in conveying the information of water level as represented by the status of SAFE, STAND, WARNING, and DANGER. Some charts presented from the analysis of data was derived from the data acquisition time of testing that can be used as an evaluation of flooding at some points prone to flood.

Potential economic value of drought information to support early warning in Africa

NASA Astrophysics Data System (ADS)

Quiroga, S.; Iglesias, A.; Diz, A.; Garrote, L.

2012-04-01

We present a methodology to estimate the economic value of advanced climate information for food production in Africa under climate change scenarios. The results aim to facilitate better choices in water resources management. The methodology includes 4 sequential steps. First two contrasting management strategies (with and without early warning) are defined. Second, the associated impacts of the management actions are estimated by calculating the effect of drought in crop productivity under climate change scenarios. Third, the optimal management option is calculated as a function of the drought information and risk aversion of potential information users. Finally we use these optimal management simulations to compute the economic value of enhanced water allocation rules to support stable food production in Africa. Our results show how a timely response to climate variations can help reduce loses in food production. The proposed framework is developed within the Dewfora project (Early warning and forecasting systems to predict climate related drought vulnerability and risk in Africa) that aims to improve the knowledge on drought forecasting, warning and mitigation, and advance the understanding of climate related vulnerability to drought and to develop a prototype operational forecasting.

Tsunami Early Warning Within Five Minutes

NASA Astrophysics Data System (ADS)

Lomax, Anthony; Michelini, Alberto

2013-09-01

Tsunamis are most destructive at near to regional distances, arriving within 20-30 min after a causative earthquake; effective early warning at these distances requires notification within 15 min or less. The size and impact of a tsunami also depend on sea floor displacement, which is related to the length, L, width, W, mean slip, D, and depth, z, of the earthquake rupture. Currently, the primary seismic discriminant for tsunami potential is the centroid-moment tensor magnitude, M {w/CMT}, representing the product LWD and estimated via an indirect inversion procedure. However, the obtained M {w/CMT} and the implied LWD value vary with rupture depth, earth model, and other factors, and are only available 20-30 min or more after an earthquake. The use of more direct discriminants for tsunami potential could avoid these problems and aid in effective early warning, especially for near to regional distances. Previously, we presented a direct procedure for rapid assessment of earthquake tsunami potential using two, simple measurements on P-wave seismograms—the predominant period on velocity records, T d , and the likelihood, T {50/Ex}, that the high-frequency, apparent rupture-duration, T 0, exceeds 50-55 s. We have shown that T d and T 0 are related to the critical rupture parameters L, W, D, and z, and that either of the period-duration products T d T 0 or T d T {50/Ex} gives more information on tsunami impact and size than M {w/CMT}, M wp, and other currently used discriminants. These results imply that tsunami potential is not directly related to the product LWD from the "seismic" faulting model, as is assumed with the use of the M {w/CMT} discriminant. Instead, information on rupture length, L, and depth, z, as provided by T d T 0 or T d T {50/Ex}, can constrain well the tsunami potential of an earthquake. We introduce here special treatment of the signal around the S arrival at close stations, a modified, real-time, M wpd(RT) magnitude, and other procedures to enable early estimation of event parameters and tsunami discriminants. We show that with real-time data currently available in most regions of tsunami hazard, event locations, m b and M wp magnitudes, and the direct, period-duration discriminant, T d T {50/Ex} can be determined within 5 min after an earthquake occurs, and T 0, T d T 0, and M wpd(RT) within approximately 10 min. This processing is implemented and running continuously in real-time within the Early-est earthquake monitor at INGV-Rome (http://early-est.rm.ingv.it). We also show that the difference m b - log10( T d T 0) forms a rapid discriminant for slow, tsunami earthquakes. The rapid availability of these measurements can aid in faster and more reliable tsunami early warning for near to regional distances.

The Trend of Voluntary Warnings in Electronic Nicotine Delivery System Magazine Advertisements

PubMed Central

Shang, Ce; Chaloupka, Frank J.

2017-01-01

Some manufacturers of electronic nicotine delivery systems (ENDS) voluntarily carried health warnings in their advertisements. This study examined these voluntary warnings in magazine ads and plotted their trends between 2012 and early 2015. ENDS magazine ads were obtained through Kantar media and warnings were collected from the Chicago Public Library or the Trinkets and Trash surveillance system. The prevalence of voluntary warnings, warnings with the specific capitalized word “WARNING”, and MarkTen warnings were examined after being weighted using factors related to exposure between January 2012 and March 2015. Five brands (MarkTen, NJOY, MISTIC, and some Blu) carried warnings during the study period. The prevalence of warnings post 2012 that contained a description of nicotine did not significantly increase until the launch of MarkTen, which also happened several months before April 2014 when the U.S. food and drug administration (FDA) published its proposed deeming rule. In addition, none of these warnings met the criteria required by the FDA in the final rules. Voluntary warnings, particularly MarkTen warnings, significantly increased in ENDS magazine ads between 2014 and 2015. It is important to monitor how ENDS manufacturers will comply with the FDA regulation related to warnings and how this regulation will ultimately impact ENDS risk perceptions and use. PMID:28075420

Analysis of meteorology and emission in haze episode prevalence over mountain-bounded region for early warning.

PubMed

Kim Oanh, Nguyen Thi; Leelasakultum, Ketsiri

2011-05-01

This study investigated the main causes of haze episodes in the northwestern Thailand to provide early warning and prediction. In an absence of emission input data required for chemical transport modeling to predict the haze, the climatological approach in combination with statistical analysis was used. An automatic meteorological classification scheme was developed using regional meteorological station data of 8years (2001-2008) which classified the prevailing synoptic patterns over Northern Thailand into 4 patterns. Pattern 2, occurring with high frequency in March, was found to associate with the highest levels of 24h PM(10) in Chiangmai, the largest city in Northern Thailand. Typical features of this pattern were the dominance of thermal lows over India, Western China and Northern Thailand with hot, dry and stagnant air in Northern Thailand. March 2007, the month with the most severe haze episode in Chiangmai, was found to have a high frequency of occurrence of pattern 2 coupled with the highest emission intensities from biomass open burning. Backward trajectories showed that, on haze episode days, air masses passed over the region of dense biomass fire hotspots before arriving at Chiangmai. A stepwise regression model was developed to predict 24h PM(10) for days of meteorology pattern 2 using February-April data of 2007-2009 and tested with 2004-2010 data. The model performed satisfactorily for the model development dataset (R(2)=87%) and test dataset (R(2)=81%), which appeared to be superior over a simple persistence regression of 24h PM(10) (R(2)=76%). Our developed model had an accuracy over 90% for the categorical forecast of PM(10)>120μg/m(3). The episode warning procedure would identify synoptic pattern 2 and predict 24h PM(10) in Chiangmai 24h in advance. This approach would be applicable for air pollution episode management in other areas with complex terrain where similar conditions exist. Copyright © 2011 Elsevier B.V. All rights reserved.

Global integrated drought monitoring and prediction system

PubMed Central

Hao, Zengchao; AghaKouchak, Amir; Nakhjiri, Navid; Farahmand, Alireza

2014-01-01

Drought is by far the most costly natural disaster that can lead to widespread impacts, including water and food crises. Here we present data sets available from the Global Integrated Drought Monitoring and Prediction System (GIDMaPS), which provides drought information based on multiple drought indicators. The system provides meteorological and agricultural drought information based on multiple satellite-, and model-based precipitation and soil moisture data sets. GIDMaPS includes a near real-time monitoring component and a seasonal probabilistic prediction module. The data sets include historical drought severity data from the monitoring component, and probabilistic seasonal forecasts from the prediction module. The probabilistic forecasts provide essential information for early warning, taking preventive measures, and planning mitigation strategies. GIDMaPS data sets are a significant extension to current capabilities and data sets for global drought assessment and early warning. The presented data sets would be instrumental in reducing drought impacts especially in developing countries. Our results indicate that GIDMaPS data sets reliably captured several major droughts from across the globe. PMID:25977759

Global integrated drought monitoring and prediction system.

PubMed

Hao, Zengchao; AghaKouchak, Amir; Nakhjiri, Navid; Farahmand, Alireza

2014-01-01

Drought is by far the most costly natural disaster that can lead to widespread impacts, including water and food crises. Here we present data sets available from the Global Integrated Drought Monitoring and Prediction System (GIDMaPS), which provides drought information based on multiple drought indicators. The system provides meteorological and agricultural drought information based on multiple satellite-, and model-based precipitation and soil moisture data sets. GIDMaPS includes a near real-time monitoring component and a seasonal probabilistic prediction module. The data sets include historical drought severity data from the monitoring component, and probabilistic seasonal forecasts from the prediction module. The probabilistic forecasts provide essential information for early warning, taking preventive measures, and planning mitigation strategies. GIDMaPS data sets are a significant extension to current capabilities and data sets for global drought assessment and early warning. The presented data sets would be instrumental in reducing drought impacts especially in developing countries. Our results indicate that GIDMaPS data sets reliably captured several major droughts from across the globe.

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.

Early Warning System for West Nile Virus Risk Areas, California, USA

PubMed Central

Ahearn, Sean C.; McConchie, Alan; Glaser, Carol; Jean, Cynthia; Barker, Chris; Park, Bborie; Padgett, Kerry; Parker, Erin; Aquino, Ervic; Kramer, Vicki

2011-01-01

The Dynamic Continuous-Area Space-Time (DYCAST) system is a biologically based spatiotemporal model that uses public reports of dead birds to identify areas at high risk for West Nile virus (WNV) transmission to humans. In 2005, during a statewide epidemic of WNV (880 cases), the California Department of Public Health prospectively implemented DYCAST over 32,517 km2 in California. Daily risk maps were made available online and used by local agencies to target public education campaigns, surveillance, and mosquito control. DYCAST had 80.8% sensitivity and 90.6% specificity for predicting human cases, and κ analysis indicated moderate strength of chance-adjusted agreement for >4 weeks. High-risk grid cells (populations) were identified an average of 37.2 days before onset of human illness; relative risk for disease was >39× higher than for low-risk cells. Although prediction rates declined in subsequent years, results indicate DYCAST was a timely and effective early warning system during the severe 2005 epidemic. PMID:21801622

Information dissipation as an early-warning signal for the Lehman Brothers collapse in financial time series

PubMed Central

Quax, Rick; Kandhai, Drona; Sloot, Peter M. A.

2013-01-01

In financial markets, participants locally optimize their profit which can result in a globally unstable state leading to a catastrophic change. The largest crash in the past decades is the bankruptcy of Lehman Brothers which was followed by a trust-based crisis between banks due to high-risk trading in complex products. We introduce information dissipation length (IDL) as a leading indicator of global instability of dynamical systems based on the transmission of Shannon information, and apply it to the time series of USD and EUR interest rate swaps (IRS). We find in both markets that the IDL steadily increases toward the bankruptcy, then peaks at the time of bankruptcy, and decreases afterwards. Previously introduced indicators such as ‘critical slowing down' do not provide a clear leading indicator. Our results suggest that the IDL may be used as an early-warning signal for critical transitions even in the absence of a predictive model. PMID:23719567

Information dissipation as an early-warning signal for the Lehman Brothers collapse in financial time series

NASA Astrophysics Data System (ADS)

Quax, Rick; Kandhai, Drona; Sloot, Peter M. A.

2013-05-01

In financial markets, participants locally optimize their profit which can result in a globally unstable state leading to a catastrophic change. The largest crash in the past decades is the bankruptcy of Lehman Brothers which was followed by a trust-based crisis between banks due to high-risk trading in complex products. We introduce information dissipation length (IDL) as a leading indicator of global instability of dynamical systems based on the transmission of Shannon information, and apply it to the time series of USD and EUR interest rate swaps (IRS). We find in both markets that the IDL steadily increases toward the bankruptcy, then peaks at the time of bankruptcy, and decreases afterwards. Previously introduced indicators such as `critical slowing down' do not provide a clear leading indicator. Our results suggest that the IDL may be used as an early-warning signal for critical transitions even in the absence of a predictive model.

Predicting the timing and potential of the spring emergence of overwintered populations of Heliothis spp

NASA Technical Reports Server (NTRS)

Hartstack, A. W.; Witz, J. A.; Lopez, J. D. (Principal Investigator)

1981-01-01

The current state of knowledge dealing with the prediction of the overwintering population and spring emergence of Heliothis spp., a serious pest of numerous crops is surveyed. Current literature is reviewed in detail. Temperature and day length are the primary factors which program H. spp. larva for possible diapause. Although studies on the interaction of temperature and day length are reported, the complete diapause induction process is not identified sufficiently to allow accurate prediction of diapause timing. Mortality during diapause is reported as highly variable. The factors causing mortality are identified, but only a few are quantified. The spring emergence of overwintering H. spp. adults and mathematical models which predict the timing of emergence are reviewed. Timing predictions compare favorably to observed field data; however, prediction of actual numbers of emerging moths is not possible. The potential for use of spring emergence predictions in pest management applications, as an early warning of potential crop damage, are excellent. Research requirements to develop such an early warning system are discussed.

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.

Flood Monitoring and Early Warning System Using Ultrasonic Sensor

NASA Astrophysics Data System (ADS)

Natividad, J. G.; Mendez, J. M.

2018-03-01

The purpose of this study is to develop a real-time flood monitoring and early warning system in the northern portion of the province of Isabela, particularly the municipalities near Cagayan River. Ultrasonic sensing techniques have become mature and are widely used in the various fields of engineering and basic science. One of advantage of ultrasonic sensing is its outstanding capability to probe inside objective non-destructively because ultrasound can propagate through any kinds of media including solids, liquids and gases. This study focuses only on the water level detection and early warning system (via website and/or SMS) that alerts concern agencies and individuals for a potential flood event. Furthermore, inquiry system is also included in this study to become more interactive wherein individuals in the community could inquire the actual water level and status of the desired area or location affected by flood thru SMS keyword. The study aims in helping citizens to be prepared and knowledgeable whenever there is a flood. The novelty of this work falls under the utilization of the Arduino, ultrasonic sensors, GSM module, web-monitoring and SMS early warning system in helping stakeholders to mitigate casualties related to flood. The paper envisions helping flood-prone areas which are common in the Philippines particularly to the local communities in the province. Indeed, it is relevant and important as per needs for safety and welfare of the community.

Assessing earthquake early warning using sparse networks in developing countries: Case study of the Kyrgyz Republic

NASA Astrophysics Data System (ADS)

Parolai, Stefano; Boxberger, Tobias; Pilz, Marco; Fleming, Kevin; Haas, Michael; Pittore, Massimiliano; Petrovic, Bojana; Moldobekov, Bolot; Zubovich, Alexander; Lauterjung, Joern

2017-09-01

The first real-time digital strong-motion network in Central Asia has been installed in the Kyrgyz Republic since 2014. Although this network consists of only 19 strong-motion stations, they are located in near-optimal locations for earthquake early warning and rapid response purposes. In fact, it is expected that this network, which utilizes the GFZ-Sentry software, allowing decentralized event assessment calculations, not only will provide useful strong motion data useful for improving future seismic hazard and risk assessment, but will serve as the backbone for regional and on-site earthquake early warning operations. Based on the location of these stations, and travel-time estimates for P- and S-waves, we have determined potential lead times for several major urban areas in Kyrgyzstan (i.e., Bishkek, Osh, and Karakol) and Kazakhstan (Almaty), where we find the implementation of an efficient earthquake early warning system would provide lead times outside the blind zone ranging from several seconds up to several tens of seconds. This was confirmed by the simulation of the possible shaking (and intensity) that would arise considering a series of scenarios based on historical and expected events, and how they affect the major urban centres. Such lead times would allow the instigation of automatic mitigation procedures, while the system as a whole would support prompt and efficient actions to be undertaken over large areas.

Use of cyanopigment determination as an indicator of cyanotoxins in drinking water.

PubMed

Schmidt, Wido; Petzoldt, Heike; Bornmann, Katrin; Imhof, Lutz; Moldaenke, Christian

2009-01-01

The indicator function of the fluorescence signals of the cyanopigments phycocyanin and phycoerythrin as early warning parameters against the microcystins in drinking water was investigated by lab- and pilot-scale studies. The early warning function of the fluorescence signals was examined with regard to the signals' real-time character, their sensitivity and the behaviour of the cyanopigments in different treatment stages in comparison to microcystins. Fluorescence measurements confirmed the real-time character, since they can be carried out on-site without the pre-concentration of pigments. The limit of detection of phycoerythrin is determined at 0.7 microg/L and of phycocyanin at 5.3 microg/L respectively. If the pigment/microcystin ratio is known and calculated to be higher than 1, very low microcystin concentrations can be estimated by the fluorescence signals. The compared behaviour of both pigments and selected microcystins (MC-LR and MC-RR) during water treatment shows that pigments have an early warning function against microcystins in conventional treatment stages using pre-oxidation with permanganate, powdered-activated carbon and chlorination. In contrast, cyanopigments do not have an early warning function if chlorine dioxide is used as a pre-oxidant or final disinfection agent. In order to use pigment control measurements in drinking water treatment the initial pigment/toxin ratio of the raw water must be known.

Towards the use of Structural Loop Analysis to Study System Behaviour of Socio-Ecological Systems.

NASA Astrophysics Data System (ADS)

Abram, Joseph; Dyke, James

2016-04-01

Maintaining socio-ecological systems in desirable states is key to developing a growing economy, alleviating poverty and achieving a sustainable future. While the driving forces of an environmental system are often well known, the dynamics impacting these drivers can be hidden within a tangled structure of causal chains and feedback loops. A lack of understanding of a system's dynamic structure and its influence on a system's behaviour can cause unforeseen side-effects during model scenario testing and policy implementation. Structural Loop analysis of socio-ecological system models identifies dominant feedback structures during times of behavioural shift, allowing the user to monitor key influential drivers during model simulation. This work carries out Loop Eigenvalue Elasticity Analysis (LEEA) on three system dynamic models, exploring tipping points in lake systems undergoing eutrophication. The purpose is to explore the potential benefits and limitations of the technique in the field of socio-ecology. The LEEA technique shows promise for socio-ecological systems which undergo regime shifts or express oscillatory trends, but shows limited usefulness with large models. The results of this work highlight changes in feedback loop dominance, years prior to eutrophic tipping events in lake systems. LEEA could be used as an early warning signal to impending system changes, complementary to other known early warning signals. This approach could improve our understanding during critical times of a system's behaviour, changing how we approach model analysis and the way scenario testing and policy implementation are addressed in socio-ecological system models.

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.

Resilience of the Nexus of Competitive Water Consumption between Human Society and Environment Development: Regime Shifts and Early Warning Signals

NASA Astrophysics Data System (ADS)

Li, Z.; Liu, P.; Feng, M.; Zhang, J.

2017-12-01

Based on the modeling of the water supply, power generation and environment (WPE) nexus by Feng et al. (2016), a refined theoretical model of competitive water consumption between human society and environment has been presented in this study, examining the role of technology advancement and social environmental awareness growth-induced pollution mitigation to the environment as a mechanism for the establishment and maintenance of the coexistence of both higher social water consumption and improved environment condition. By coupling environmental and social dynamics, both of which are represented by water consumption quantity, this study shows the possibility of sustainable situation of the social-environmental system when the benefit of technology offsets the side effect (pollution) of social development to the environment. Additionally, regime shifts could be triggered by gradually increased pollution rate, climate change-induced natural resources reduction and breakdown of the social environmental awareness. Therefore, in order to foresee the pending abrupt regime shifts of the system, early warning signals, including increasing variance and autocorrelation, have been examined when the system is undergoing stochastic disturbance. ADDIN EN.REFLIST Feng, M. et al., 2016. Modeling the nexus across water supply, power generation and environment systems using the system dynamics approach: Hehuang Region, China. J. Hydrol., 543: 344-359.

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.