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Early Warning Alarm System (EWAS)

Early Warning Alarm System (EWAS). Meir Rom, D.Sc. Statistician and System Analyzer. Facts and Figures. Supplies 80% of Drinking water in Israel. Supplies 70% of total water consumption. Reuses 60% of Israel’s treated wastewater. 3,000 Facilities. 1,070 Water well drillings.

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Early Warning Alarm System (EWAS)

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  1. Early Warning Alarm System (EWAS) Meir Rom, D.Sc. Statistician and System Analyzer

  2. Facts and Figures Supplies 80%of Drinking water in Israel Supplies 70%of total water consumption Reuses 60% of Israel’s treated wastewater 3,000Facilities 1,070Water well drillings 12,000km of water lines Employees 2200 Investments $350 million per annum Revenue $1 billion per annum

  3. The Challenge:Integrative Real-Time Water Management Water Treatment Water Security Desalination Hydrology & Drillings Rain Enhancement Operational Models Command & Control Water Supply Watershed Monitoring & Management Water Quality Wastewater Treatment & Reclamation Flood Catchment

  4. Early Warning Alarm System (EWAS) Detection & Identification of Water Quality Changes in Watersheds and Rivers, based on an Integrated Multi-Sensor Real-Time Water Quality Index Dr. Meir Rom, Dr. Diego Berger, Dr. Ram Porat

  5. Motivation: Prevention Is Not Enough

  6. We Don’t Want To Be There…

  7. Objectives • Detect and identify changes in water quality • Produce alerts with high sensitivity and small rate of false-alarms • Developed water quality index based on multiple sensors • Assemble in real-time modular EWA system • Reliable and low cost system

  8. Usages (Already Operational) • The system is already operated near the northern Israeli border • Integrated with other remote equipment in a 24/7 control room environment. Sampling Point Monitoring Station

  9. Automatic Monitoring Station

  10. Soaked Sensors in bath UV Redox Turbidity Ammonia PH EC

  11. Turbidity Redox pH System works:Broadcasting and processing the data Communication Center

  12. Real-Time Integrated Multi-Channel Index EC EC Sensors Sensor Indexes Thresholds Redox Redox Jumps Integrated Weighted Index pH pH Trend

  13. Online Integrated Multi-Channel System Detection of Real Event ~22:15

  14. Summary and Future Developments • Operational EWA system was described, based on index which is highly sensitive to changes in water quality • Algorithm is optimized to produce preset false-alarm rate • System is based on multiple sensors. New sensors can be added. • This year, the system will be applied to five monitoring stations located in Lake Kinneret watershed. • Alerts will be sent directly to authorized people using the mobile system and a remote retrospective study can be done in field, in case of suspected event.

  15. EWA Algorithm: baseline “Jumps” and “Trend” detection • For each sensor and time unit (minute), define a moving window (say, of the preceded 3 hours). Save the data contained in this time range • Process the historical saved data. Fit robust regression line and predict the value associate with the next time point.. Compare to the next value obtained by the sensor by taking the difference between values. Use the significant slope value for “Trend” detection. • Continue using the “CUSUM” algorithm to detect “Jumps”

  16. Thresholds

  17. Jumps

  18. Trends

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