Swiss early warning system for natural hazards

537 views

Published on

M. Sättele, WSL Institute for Snow and Avalanche Research

Published in: Education, Technology
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
537
On SlideShare
0
From Embeds
0
Number of Embeds
15
Actions
Shares
0
Downloads
0
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

Swiss early warning system for natural hazards

  1. 1. Dissertation REWARNA Classification of Warning Systems for Natural Hazards Martina Sättele FOCP Swiss Federal Office for Civil Protection & SLF WSL Institute for Snow and Avalanche Research SLF
  2. 2. Dissertation Content of presentation REWARNResearch goal • Research goal and objectiveand objective Warning systems for natural hazards - Application of a generic classificationHazardprocesses • Hazard processesMonitoringpossibilities • Monitoring possibilitiesSystemclassification • System classificationReliabilitycriteria • Reliability criteriaConclusion • Conclusion
  3. 3. Dissertation Role of warning systems in „Integrated Risk Management“ REWARN • Mitigate the risk to an object in a scenario by reducing:Research goaland objective Warning systems for natural hazards - Application of a generic classificationHazardprocesses • probability of occurrenceMonitoringpossibilities • presence probability of object • vulnerability of objectSystemclassification • value of objectReliabilitycriteria Source: FOCP Swiss Federal Office forConclusion Civil Protection • Warning systems mitigate the risk by reducing the presence probability • To be able to incorporate warning systems as standard measures in the integrated risk management their reliability must be quantifiable 3
  4. 4. Dissertation Research goal and objectives REWARN 1. Objective: • Provide an overview of warning systemsResearch goal • Derive a classification of warning systemsand objective Warning systems for natural hazards - Application of a generic classificationHazardprocesses 2. Objective: • Summarize reliability methods applied in industryMonitoringpossibilities • Identify methods for the required fieldSystemclassification 3. Objective: • Verify reliability methods in case studiesReliabilitycriteria • Document relevant findings in a guidelineConclusion Research goal Development of a method to quantify the reliability of warning systems for natural hazards 4
  5. 5. Dissertation Classification of warning systems REWARN • A recognized classification does not exist at present • Allows the identification of system reliability criteriaResearch goaland objective • Requires an holistic approach Warning systems for natural hazards - Application of a generic classificationHazardprocessesMonitoring Human Environmentpossibilities Material EnergySystem Informationclassification Material Material Energy EnergyReliability Information Informationcriteria Technical systemConclusion Material Energy Information Input Technical Process Output 5
  6. 6. Hazards processes and warning systems in Switzerland Dissertation REWARN • Main property damages since 1990: flood, hail and storm (IRV, 2012) • Statistics are influenced by major events (WSL, Swiss flood and landslide damage database,2009)Research goaland objective • Historical events show processes with hazard potential (PLANAT homepage, 2012) Warning systems for natural hazards - Application of a generic classificationHazardprocessesMonitoring • 52 systems in four Cantons were identifiedpossibilities atmospheric – meteorologicalSystemclassification hydrological – glaciological Nr. of systems identified/ hazard process geological – geomorphologicalReliability 16 biologicalcriteria 14 12 10 FireLess Schweiz Meteo System SED – Swiss Snow avalanche HydrologicalConclusion 8 Seismological WSL bulletin SLF 6 4 Service (FOEN) 2 0 6
  7. 7. Natural hazards processes characteristics Dissertation REWARN trigger events damaging hazard event event dynamic process parametersResearch goal variable dispositionand objective Warning systemsdisposition basic for natural hazards - Application of a generic classificationHazardprocesses (aligned to: Zimmermann, 1997)Monitoringpossibilities Example: Debris flow process characteristics:Systemclassification • Basic disposition: steep slope and curvature, glacierReliability • Variable disposition: availability of loose debris materialcriteriaConclusion • Trigger events: rain, snow and ice melting • Dynamic process parameters: frontal speed, height, volume, discharge, density 7
  8. 8. Hazard process characteristics and system monitoring parameters Dissertation REWARN trigger events damaging hazard event eventResearch goaland objective dynamic process parameters variable disposition Warning systems for natural hazards - Application of a generic classificationHazard basic dispositionprocessesMonitoring warning time alarm timepossibilities system lead time system lead timeSystemclassificationReliability Two situations can be distinguished:criteriaConclusion • System lead time = alarm time  dynamic process parameters (direct) • System lead time = warning + alarm time  variable disposition, triggers (direct/ indirect) 8
  9. 9. Dissertation Illgraben: Debris flow warning system Canton Valais REWARNResearch goaland objective Warning systems for natural hazards - Application of a generic classificationHazardprocessesMonitoringpossibilitiesSystemclassificationReliabilitycriteriaConclusion Source: Christoph Graf, WSL 9
  10. 10. Dissertation Preonzo: Rock avalanche warning system Canton Ticino REWARNResearch goaland objective Warning systems for natural hazards - Application of a generic classificationHazardprocessesMonitoringpossibilitiesSystemclassificationReliabilitycriteriaConclusion 10
  11. 11. Dissertation SLF Snow avalanche system REWARNResearch goaland objective Warning systems for natural hazards - Application of a generic classificationHazardprocessesMonitoringpossibilitiesSystemclassificationReliabilitycriteriaConclusion Source: SLF, MeteoSchweiz 11
  12. 12. Dissertation Classification of warning system for natural hazards REWARN Type Threshold Expert Model based system system expert system Characteristics (34) (14) (4) Lead time alarm (34) warning (13) warning (4)Research goal alarm (1)and objective Geographical Warning systems for natural hazards - Application of national (4) classification national (2) national (1) a genericHazard Coverage regional (1) local (13) regional (1)processes local (31) Geographical local (34) local (14) regional (5)Monitoringpossibilities resolution Type of monitoring direct (33) direct (14) indirect (5)System indirect (13)classification First decision instance threshold (33) threshold (14) threshold (1)Reliability no (3)criteria Final decision instance threshold (33) expert (14) experts (4)Conclusion Model based decision no (33) simple model (14) complex models (5) complex models (1) Automated actions yes (34) no (14) no (4) Warning levels one (21) one (6) multiple (5) multiple (13) multiple (8) Information receiver endangered objects (33) endangered objects (14) interest groups (5) public (1) public (6) public (5) authorities (31) authorities (5) system operator (33) 12
  13. 13. Dissertation General influences on the system reliability REWARN Degree ofResearch goal influenceand objective Warning systems for natural hazards - Application of a generic classificationHazardprocessesMonitoringpossibilities Threshold & Human , models &System automated actions technical complexityclassificationReliabilitycriteriaConclusion System Threshold Expert Model based class system system expert system 13
  14. 14. Dissertation Threshold system - reliability criteria REWARN • Choice of sensor type, redundancies, position and fixation • Choice of threshold valueResearch goaland objective • Functionality and control of the logger and power supply Warning systems for natural hazards - Application of a generic classificationHazardprocesses • Functionality and control of alarm transmissionMonitoringpossibilities • Functionality and control of alarm facilities/ equipmentSystem • Reduced technical complexity/ number of interfacesclassificationReliabilitycriteria  Uncertain parameters are technical and data related factorsConclusion 14
  15. 15. Dissertation Expert system - reliability criteria REWARN • Availability of measured data on server • Degree of experts experience and risk attitudeResearch goaland objective • Quality of models and the natural hazards -of indirect datageneric classification Warning systems for interpretation Application of aHazardprocesses • Conduction of preventive and active actionsMonitoringpossibilities • Achievement of endangered objectivesSystemclassificationReliability  Uncertain parameters are technical, human, data related andcriteria organisational factorsConclusion 15
  16. 16. Dissertation Model based expert system - reliability criteria REWARN • Handling of complex data management e.g. redundant servers • Definition of clear work and decision processesResearch goaland objective • Standardisation systemsmeasuringhazards - Application of a generic classification Warning of the for natural stationsHazardprocessesMonitoringpossibilities  Uncertain parameters are technical, human, data related, organisationalSystemclassification and standardisation related factorsReliabilitycriteriaConclusion 16
  17. 17. Dissertation Conclusion REWARN • Warning systems can be classified in • i) threshold, ii) expert and iii) model based expert systemsResearch goaland objective • Each class incorporates for natural hazards - Application of a generic classification Warning systems typical system characteristicsHazardprocesses • The monitored hazard process characteristics determine the systemMonitoringpossibilities lead time, the system design and the system reliability criteriaSystem • The classification allows the derivation of reliability criteriaclassificationReliability • The classification and the derived reliability criteria are an essentialcriteria input for the development of a reliability methodConclusion 17
  18. 18. Dissertation REWARNResearch goaland objectiveHazard Thank you for your Warning systems for natural hazards - Application of a generic classificationprocessesMonitoringpossibilities attention!SystemclassificationReliabilitycriteriaConclusion Questions??? 18

×