Improved disaster management with use of Statistics Netherlands Data

1. Improved disaster management with use of Statistics Netherlands Data Jos Kuilboer

2. Goal Quantitatively and Qualitatively optimize and enhance the current flood management in The Netherlands by use of register data.

3. 1. Introduction • Introduction • Models characteristics • Stakeholders • SN data • Newly developed framework • Model, test-case • Conclusions and Recommendations

4. New Orleans 2005

5. Dutch Situation Rising sea level; Increasing river discharges; Subsidence; Increasing pressure on Dutch Delta; More than 50% of the Dutch population lives below sea level; 70% of the gross national income is earned below sea level. Importance of detailed flood management

6. How can register data form an additional value in the field of flood risk management, and in what way can this be modeled? Research question

7. 2. Models • Introduction • Model characteristics • Stakeholders • SN data • Newly developed framework • Model, test-case • Conclusions and Recommendations

8. Characteristics/ focus Damage categories

9. Characteristics/ focus Damage calculation using “postcode level”

10. Characteristics/ focus Damage calculations using object data

11. Characteristics/ focus Scale level • Preferred scale level; • Research area; • Homogeneity of ground use; • Included number of parameters. Macro Meso Micro Micro

12. Models Challenges for future research and use • International models • Inclusion of non-monetary damage parameters; • Damage interpretation in time; • Dutch situation in detail • Inclusion of object databases; • Increased level of detail; • Update databases; • Inclusion of evacuation aid, social disruption, ecologics and cultural damage.

13. 3. Stakeholders • Introduction • Model characteristics • Stakeholders • SN data • Newly developed framework • Model, test-case • Conclusions and Recommendations

14. Stakeholders Stakeholders Fire brigade; Municipality; First aid teams; Ministries; Police; Safety regions; Water boards A broad range of different stakeholders

15. Stakeholders/ focus Challenges/ focus Detailed information supply; Demographic information; Information on pollution sources; Increased level of detail; Updating databases; Information supply per moment in time. Challenges for future use

16. 4. Statistics Netherlands data • Introduction • Model characteristics • Stakeholders • SN data • Newly developed framework • Model, test-case • Conclusions and Recommendations

17. CBS data 14 applicable databases; Over 300 parameters; 4 themes: Cultural damage; Ecologic damage; Evacuation and emergency aid; Public services. SN data Overview of applicable SN databases

18. How can register data form an additional value in the field of flood risk management, and in what way can this be modeled?

19. 5. Newly developed framework • Introduction • Models • Stakeholders • SN data • Newly developed framework • Model, test-case • Conclusions and Recommendations

20. Newly developed framework Based on safety chain

21. Newly developed framework Result

22. 6. Model, test-case • Introduction • Models • Stakeholders • SN data • Newly developed framework • Model, test-case • Conclusions and Recommendations

23. Model Newly developed flood risk model • Goal • Point out qualitative and quantitative advantages of using register data within flood management. • Approach • Develop model; • Test-case focused on evacuation management.

24. Model Location test-case

25. Model Structuur van model

26. Model Test-case: Bijlmermeer polder • Test-case: • 8 polders; • 3 000 hectare; • 40 000 residents; • Belt system: -0.4 m NAP; • Polder: -6.0 m NAP; • High diversity of vulnerable objects; • Densely populated [7 000 residents/km2]; • Sparsely populated[18 residents/km2].

27. Model Overview of simulated scenarios • Quantitative: • Secondary dike breach for densely populated areas (small postcode areas); • Secondary dike breach for sparsely populated area (large postcode areas). • Qualitative: • Vulnerable objects in time.

28. Model Dike breach for densely populated area

29. Model Affected population in place and time

30. Model Quantitative results: dike breach for densely populated area Affected residents [-] Flooded population in time Time [hours]

31. Model Quantitative results: dike breach for sparsely populated area Affeted resident in time [-] Getroffen bevolking in de tijd Flooded population in time Time [hours]

32. Model Verklaring resultaten

33. Model Quantitative results: vulnerable objects in time Flooded primary schools in time for densely populated area Flooded primary schools [-] Time [hours]

34. Model Flooded primary schools in time

35. How can register data form an additional value in the field of flood risk management, and in what way can this be modeled?

36. 7. Conclusions and Recommendations • Introduction • Models • Stakeholders • SN data • Newly developed framework • Model, test-case • Conclusions and Recommendations

37. Conclusions [1/2] Qualitative advantages of using register data • Application of register data: • Increased level of detail; • Vulnerable objects; • Flooded risks in time; • Taylor made solutions; • Yearly updates of databases.

38. Conclusions [2/2] Quantitative advantages of using register data • Applications of register data: • Object databases; • Small scale flooding; • Sparsely populated areas; • Enhanced capacity predicting flood risks.

39. Recommendations Using SN data within flood management • Application of SN data • Preventive evacuation; • Mobility residents; • Z-component; • Compute all possible scenarios in advance; • Online publications for selected users; • Stimulate use of object data within SN; • Elaborate model for multiple damage scenarios; • Multidisciplinary approach.

40. Questions? • Contact: • n.vanleeuwen@cbs.nl • joskuilboer@hotmail.com