Cyclone Web -DCRA & DSS: A Tool for Disaster Risk Mitigation and Response Planning

1. Cyclone Web-DCRA & DSS: A Tool for Disaster Risk Mitigation and Response Planning Dr. Sushil Gupta, Assistant Vice President, Risk Modeling and Insurance RMSI, India Sushil.Gupta@rmsi.com Global inclusive Disaster Management Conference (GiDMC 2019), New Delhi Plenary Session 4: Smart Technologies for Disaster Risk Reduction and Response July 02 , 2019

2. Objective(s) Development of a Cyclone Web-GIS based Dynamic CompositeRisk Atlas (DCRA) & Decision Support System (DSS) for the area up to 10-m above mean sea level for all the 13 coastal States/UTs of India • Sub Objectives: - Probabilistic Hazard and Risk Assessment Maps - Real-time Decision Support Tool • Web-DCRA App (Android) • Offline Web-CRA (Desktop version) for exposure data management • Training and Capacity building support on the Decision Support Tool Tracks of major historical cyclonic storms (1891 – 2018)

3. Data Sets ‒Hazard Modeling • NHO , INCOIS/GEBCO • FES2004 Global Ocean Tidal Model • INCOIS • SOI • NRS C 10 m • IMD Data (period 1990-2014) • IMD Atlas (period 1891-2007) • NOAA- IBTraCS (1877-2012) • NDC, IMD Pune (period 1901-2007) • WRIS and CWC (period 1964-2013)

4. Exposure database

6. Stochastic Cyclone Tracks ‒ India INDIA

7. Automatic Execution for Cyclonic Wind, Storm Surge and Flood modelling using software application Cyclone Tracks (Input.dat) Wind Distribution (fort.22) Cyclone Induced Rainfall Model Wind Model(wind.exe) Hydrologic Model (HEC-HMS) HECHMSCALL.exe Storm Surge Model (ADCIRC.exe, fort.14, fort.15) Rainfall.dss Surge inundation, Water levels and Current velocity Hydraulic Model (HEC-RAS) HECRASCALL.exe Surge.dss HEC-RAS output (Discharge Output.dss, Flood Depth map, velocity, Water surface Elevation)

8. Methodology for Cyclonic Wind Hazard Assessment • Surface winds associated with a tropical cyclone are derived using dynamic storm model of Jelesnianski and Taylor • The key output of the wind model is a wind speed that provides maximum wind at every grid point covering the area of impact • This output is used to develop wind hazard maps at village level

9. Cyclonic Wind Model – Validation • Performance of dynamic storm model assessed against several historical events • The percentage error between computed and observed wind speed varies between 0.5% - 5% • indicates that the numerical solutions represent a realistic distribution of wind fields in the study region Validation of modelledwind speeds for major cyclones

10. Model Validation ‒ Wind Hazard Modeled wind field of 1999 SuCSOdisha (left) & 2013 VSCS Phailin (right) www.rmsi.com | 10

11. Wind hazard map of Odisha for 50-year return period

12. Wind hazard map of Odisha for 100-year return period

13. Wind hazard map of Odisha for 250-year return period

14. Wind hazard map of Odisha for 500-year return period

15. Storm Surge Hazard Modelling

16. ADCIRC finite-element grid of the model domain

17. Zoomed portion of the ADCIRC finite-element grid of the model domain

18. Bathymetry/Topography (m) of the model domain for Odisha

19. Storm Surge Model – Validation • Performance of dynamic storm model assessed against several historical events • Error between the observed and computed maximum surge heights varies between 0.5% - 3.3% • indicates that the numerical solutions represent a realistic distribution of surge in the study region Validation of modelledsurge heights for major cyclones

20. Model Validation ‒ Storm Surge Hazard Storm surge flood hazard map associated with October 1999 Super cyclone

21. Storm Surge Map of Odisha for 100 year return period www.rmsi.com | 21

22. Methodology‒Flood Modelling Two Modules used in flood modelling: • Hydrologic Model: HEC-HMS(Hydrologic Engineering Center-Hydrologic Modelling System) -Generation of Runoff from Rainfall and other catchment inputs • Hydraulic cum Flood Inundation Modelling: HEC-RAS(Hydrologic Engineering Center -River Analysis System) -Generates flood inundation maps using Hydraulic parameters

23. Flood Modelling

24. Hydraulic Models Comparison of observed and simulated water levels (m) for various gauge station for 14-Sept-2005 cyclonic depression • Cyclone induced rainfall flooding utilizes the HEC HMS and HEC RAS suites from the USACE • Data used: • The Gauge-Discharge data downloaded from India WRIS (Water Resource Information System) • Water level data available from CWC WRIS Comparison of observed and simulated water levels (m) for various gauge station for 30-Sept-2004 severe cyclonic storm Onil

25. Flood Modelling- Flood depths and extent Cyclonic rainfall induced flood map for October 1999 Odisha Super Cyclone

26. Flood Modelling- Flood depths and extent Cyclonic rainfall induced flood map for 16 Sept. 2008 deep depression

27. Infrastructure Exposure Map – Odisha Road Network

28. Infrastructure Exposure Map – Odisha Railway Network

29. Infrastructure Exposure Map – Odisha Bridges

30. Infrastructure Exposure Map – Odisha Airports and Seaports

31. Infrastructure Exposure Map – Odisha Electricity Network

32. Odisha Railway Network – Flood affected Railway Network

33. Risk Modeling Output – Cyclonic wind PML 100 years RP

34. Hotspot map for Odisha

35. Web-based DCRA • Developed over World Bank’s GeoNode platform • GeoNode is a open source GIS-based web platform designed to present and share geospatial data (www.geonode.org)

36. Web-DCRA Login Screen rmsiod ……

37. Web-DCRA Dashboard Screen • Risk Status, Cyclone History, Exposure and Population at Risk • Risk Atlas (Pre-compiled), 2. Risk Analyzer, 3. Hotspot Analyzer

38. Web-DCRA Cyclone History Screen

39. Web-DCRA Exposure At Risk Screen

40. Web-DCRA Population At Risk Screen

41. Real time cyclone impact forecasting Sample - Details screen of maximum wind speed

42. Exposure and Risk Analyzer • Capability to generate exposure and risk, summary and detail reports on a single click of a button • Capability to update exposure and vulnerability and update risk

43. Desktop smart client application Layout of proposed WEB-CRA desktop smart client application

44. “I AM SAFE” ‒ WEB-DCRA App • “I AM SAFE” feature • Registration with facility to upload photograph, specify the people to be alerted etc. • Geotagged SMS alert to predefined numbers. • 2. Crowd Sourcing feature: to get feedback from people who want to submit information related to events such as: • • Status of flooding • • Approximate wind speed, surge height • • Damage descriptions • • Need to be evacuated • • Need Emergency Medical help” etc. Sample user interface (Android based mobile phone application) for WEB-DCRA App

45. Real time cyclone impact forecasting – As an early warning system Analysis on real-time basis- run on automatic mode • Fetching cyclone and rainfall information from IMD/JAXA in automatic mode • Running hazard models viz. – Flood, Cyclone and Storm • Running exposure, vulnerability and loss module • Dissemination of hazard and risk information • Web-app have the feature to update forecast scenario in real time based on IMD’s forecast available at regular time intervals Process flow of WEB-based dynamic analysis engine

46. Real Time Cyclone Risk Forecast module Sample - A detailed view of the event FANI

47. Real Time Cyclone Risk Forecast module • Hazard event scenario generation based on IMD bulletin • Assets/exposure at risk • Composite losses aggregated at administrative level (village/city/tehsil/ district/ state) • Suggested action/advice • Detailed event report with maps

48. Real Time Cyclone Risk Forecast module The top panel highlighted by a red colored rectangle helps provide: • Event Info – information about the event like name, category, location etc. is provided under Event Info Section • Most Affected Areas – Using the above information and the exposure data, the model will run an analysis and provide the percentage of the areas affected due to the event (Figure 6) • Available Safe Shelters- analysis using the affected area information and the population in these areas will be run and provide the details like available safe shelters, how much population is impacted and potentially undamaged shelters The right panel, highlighted in a black colored rectangle helps provide: • Weather Forecast – provides the visualization of the real time rainfall data as well as three days of forecasted data from IMD • Damage Potential – Based on analysis, it gives the information on total damage expected financially, details like household damage, damage to the standing crops and affected villages The middle panel, highlighted by an orange colored rectangle consists of: • the map window which provides the track of the real time cyclone event with sustained winds and surge details which could be overlayed with Exposure and Loss Layers for visualization Similarly, the left panel, highlighted by a green colored rectangle, consists of: • collapsible Exposure and Loss Layers The bottom panel provides • link to other sites such as the INCOIS Cyclone and Surge warning web-site

49. Real time simulation of ESCS FANI through the Web-Application Estimated Wind Profile of Cyclone FANI RMSI analyzed extremely severe cyclonic storm ‘FANI’: • the extent of maximum winds which could have devastating effects on coastal areas based on IMD bulletin issued at 03 May 0830 IST • Map depicting landfall location and the range of estimated wind speeds under the influence of ‘FANI’ • Maximum wind speed 203 km/h

50. Real time simulation of ESCS FANI through the Web-Application Model Output Analysis: Maximum surge height 2.2 m above the astronomical tides Modeled Maximum sustained wind =203 km/h District: Ganjam IMD forecasted MSW wind about 200 km/h Districts affected with maximum wind speed and surge height Estimated surge height under the influence of ‘FANI’