Enhancing the Quality of Hazus-MH Loss Estimation

Transcription

1 Innovations with integrity competency responsiveness Enhancing the Quality of Hazus-MH Loss Estimation Doug Bausch, Nikolay Todorov & Suman Biswas Hazus Conference, Charleston, SC

2 Hazus Extended Family User Community, Stakeholders, Sponsors Use Case #1 Use Case #1 Use Case #n External Entities (USGS, NOAA) Documentation Hazus Software Management Hazus Software Architecture & Design Outreach Infrastructure Management ArcGIS 10.4 Windows Platform Help Desk Training 2

3 Hazus Future User Community, Stakeholders, Sponsors Use Case #1 Use Case #1 Use Case #n External Entities (USGS, NOAA) Documentation Hazus Software Management Hazus Software Architecture & Design Outreach Infrastructure Management ArcGIS 10.4 Windows Platform Help Desk Training 3

4 Success Story #1 Risk MAP CDS Program re-architected its GIS Platform and re-wrote NFHL Services July, 2013 In September 2016 NFHL Services got over 26 Million Hits 423% increase in volume since July, 2013 Not a single Server/Hardware has been added Infrastructure capacity remained the same 4

5 Success Story #2 Risk MAP hosts over 140+ TB of Production Data Structured and Unstructured data A Search Engine is developed (called Flood Risk Study Engineering Library FRiSEL) If you search by any random keyword you may get ~700k results < 2 seconds No Hardware or Software has been procured for this solution Note: : Tools & Links 5

6 Believe in Fundamentals Separation of concerns develop specific software components that do only one specific thing Interoperability is key Service driven architecture is the mantra Better/Improved technologies a) For FRiSEL: Used a scalable big-data solution b) ElasticSearch based solution Saves your maintenance cost 6

7 IT Guiding Principles FEMA Mission To support our citizens and first responders to ensure that as a nation we work together to build, sustain, and improve our capability to prepare for, protect against, respond to, recover from, and mitigate all hazards. Risk MAP Vision To deliver quality data that increases public awareness and leads to action that reduces risk to life and property. IT Guiding Principles Consider Customer and User Needs First IT investments should provide clear benefit to customers and/or users IT Vision IT Mission Making it easy to create, analyze, share, and understand our programs data. To provide the IT infrastructure needed to manage projects, deliver products and services, create quality data, and make our programs information accessible to our customers. Manage Data as Our Asset Our business is dependent on the ability to create quality data and make it accessible to anyone that needs it Integrate, don t Duplicate Solutions should not introduce duplicate data sets or information systems Buy before Build Custom IT solutions should be avoided when possible; COTS customization should be minimal Design for Compliance IT solutions should further our alignment with federal mandates and standards Goal 1 Effective IT Governance Strategies 1.1 Define and execute approach for selecting IT projects that meet business need (i.e. - IT Governance Framework) 1.2 Define and implement approach for executing and controlling IT investments (ex: SELC, agile development) 1.3 Implement mechanisms to ensure compliance with Federal Standards (i.e. - Security, Data, etc) Goal 2 Mission-Enabling IT Solutions Strategies 2.1 Align IT solutions to Risk MAP production processes 2.2 Enhance program reporting 2.3 Upgrade system/tools to align with geospatial specifications Goal 3 Managed Data, Available Information Strategies 3.1 Define FEMA Risk MAP data management policies and standards 3.2 Implement IT solutions to align with data management policies and standards 3.3 Facilitate information sharing across enterprise Goal 4 Service-Focused, Efficient IT Operations Strategies 4.1 Define and implement approach for communicating IT processes, plans, progress, and performance 4.2 Adjust IT Services and Service Level Agreements (SLAs) based on customer feedback and program constraints 4.3 Identify and implement IT operational and cost efficiencies 7 Activities Measures Version 0.11 April 2012

8 Architectural Decisions Separation of Concerns Before After Business Logic Layer Data Access Layer 8

9 Hazus Software Good News So Far (still more to achieve) Before Now (Hazus 3.2) For Charleston, SC in 3.1 the ShakeMap Analysis 1 Hr 43 Min 10 Min For Greater Los Angeles the ShakeMap Analysis 1 Hr 58 Min 58 Min In terms of Aggregation, for Earthquake 20+ Minutes on average 2 minutes on average The aggregation of Watershed was improved - 3x improvement at-least Large scale dataset importing for AEBM Didn t work Re-architected scales better Hazus 3.1 downloads in first 2 weeks: ~2000 Reduced cost for future enhancements Tsunami model go live target: March, 2016 Reduced cost for ArcGIS Platform upgrade in future Pave the path for Hazus Web, introduce other model etc. 9

10 A little Hazus-MH history Hazus-MH 1.0 Level 1 hazard was based on Static gage data (FL) No Depth grid import (FL) Manual ShakeMap conversion & import (EQ) Static historic storm tracks (HU) In 2001 a requirement to include the capability to generate flood, earthquake and hurricane hazard information, since it rarely existed in the GIS data formats were required for loss estimation 10

11 A little Hazus-MH history (contd.) In 2016 this is no longer the case and authoritative sources (NOAA, USGS, USACE, FEMA Map Modernization, and Risk MAP, etc.) have produced high quality hazard data that Hazus-MH modelers should use over continuing to model these hazards within Hazus-MH 11

12 A little Hazus-MH history (contd.) Hazus-MH 3.2 hazard can be based on HEC-RAS and Depth grid import (FL) Direct USGS ShakeMap XML import (EQ) Direct Hurrevac historic storm import (HU) Hazus-MH 3.2 capable of modeling Earthquake Flood Hurricane Coastal Surge (hurricane-induced flood) Hazus-MH 4.0 will add Tsunami model 12

13 A little Hazus-MH history (contd.) Hazus-MH 1.0 released in 2003 was based on Hazus-MH 3.2 released in 2016 is based on MSDE 2000 / pgdb SQL Server 2014 Express Spatial ArcGIS 8.0 ArcGIS 10.4 Embracing ArcObjects COM (C++, VB6) GP tools; Spatial SQL; moving away from ArcObjects Mostly.NET, some C++ COM (no more VB6!) old Avenue code converted to VB6 13

14 Inventory Kenai peninsula, AK UDF Economic Loss benchmark Tract County UDF facilities 1,839 28,512 TS UDF Analysis 0:40 2:44 TS UDFs per sec C# recordsets process linearly in O(n) DB sets process much faster in O(log(n)) O (log(n)) much better than O(n) for large n Troy (EQ), John (FL) confirm the above 27,371 FL UDFs in 3:19 min (Python) 14

15 Inventory User-Defined Facilities (UDFs) are now a part of study region aggregation process Hint: clean up, verify external UDF attribute data & insert to StateDB for seamless repetitive use in study regions 15

16 Hazard New ShakeMap Interface: Observed vs Modeled Ground Motions 16

17 USGS ShakeMap Integration 17

18 USGS ShakeMap integration Rapid online query 18

19 M5.0 Cushing, Oklahoma $29M nonstructural and content loss 0 casualties 19

20 M5.0 Cushing, Oklahoma 20

21 M5.0 Cushing, Oklahoma 21

22 M5.0 Cushing, Oklahoma 22

23 M5.0 Cushing, Oklahoma 23

24 M5.0 Cushing, Oklahoma Based on epicenter non ShakeMap method $298M 161 complete 115 casualties 24

25 Hazard Conclusion Hazus-MH (FEMA) collaboration & integration with HEC-RAS (USACE) HEC-FIA (USACE) Hurrevac Shakemap (USGS) National Water Model (NOAA)... is a win-win! 25

26 Questions Doug Bausch: Nikolay Todorov: Suman Biswas: ISO 9001:2015 US SBA 8(a) Certified 26