Evaluation for Oil accident Warning In River Belaya

Valeriy Klenov State Institute for Applied Ecology, Moscow

Objectives

 RiverNet Simulation has two objectives: Quick Response systems for emergency warning, Monitoring support - by vivid pollution spread follow up.

 Used was method for Genetic Coding (GC) of River Net.

 Case study for: Education on Accident Monitoring and treatment in the River Belaya.

Method - String Genetic Coding (GC)

 Balance estimation of pollution move along RiverNet of any structure is ordered by multiple string GC (1500 -2500 sections of net)  Generalised parameters are: Pollution delay, Pollution decay, Danger  Primary - Quick Responce with strong uncertainty. Calibration - in process of pollution follow up. Further - monitoring

1. EDUCATION: Estimation for Waste monitoring and cleaning up (Tobol basin)



Clean up of Rivernet

 Initial map Warning for

1 300 000

(2 balls)  Final map Warning for 0 (5 balls)

Winter Oil Pipeline Accident (River Belaya)

2. Oil Forecasting after Pipeline Accident (r. Belaya)

 Monitoring for oils spreading downstream  Warning for exposed towns on 45, 75, and 110 days.

 Mapping of oil threat in colors (Red and Black exceed PLC)

Other simultaneous Layers



Summary Oil in the water on 130 day



View for Water Discharge

Scenarios of nuclides spread over River Net

 Import of simulated (or observed) data for Radio Nuclides (RN) spatial distribution (scenario) .

 Runoff RN from watersheds to rivers and spill along its. Scenario prognosis: 5 chosen slides show the Move of Radio Nuclides along River

Net

 Warning system - exposed population in the region simultaneously the spill.

3.Scenario for Nuclear Accident spread along Rivernet



Watershed of three Seas (Baltic Sea, Black sea, Caspean sea)

Conclusion

 Now: if needs for Rapid assessment of accident spread for urgent forecasting. River Net is drawn directly on the screen. Input of Accident situation from keyboard.

 Then:Urgent follow up and prognosis with data and parameters uncertainty for further model controlled calibration by field checking.

 Later: For accident monitoring and emergency warning all data (with Population sites and pollution sources by imported from Data Bases)