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Risk Analysis Of Cultural Resource4th June2
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Risk Analysis Of Cultural Resource4th June2


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  • 1. Risk Analysis of Cultural Resource within Floodplains of Snoqualmie Valley Presented By Odra Cárdenas Shweta Bhatia Gupta
  • 2. The Project The impacts of flooding in King County are far ranging and pose significant threats to public safety and regional economic viability, but it also threatens the continuity of cultural resources due to the devastating effects. The cultural heritage along the fertile Snoqualmie river valley comprise quarter of the entire county is subjected to frequent and devastating floods as recently as in year 2006 seasonal flooding.
  • 3. King County Historic preservation program has recently launched major rural preservation and the project, is a pilot for developing a model of integrated data base for a countywide assessment of historic properties leading to a management plan that will provide a more comprehensive means of treating the county’s significant historic properties during natural disasters . Sponsored By The Project
  • 4.
    • In the last 16 years, the Snoqualmie valley
    • have experienced four of the worst floods on record,
    • including November 06's record-breaking deluge.
    • Within the Snoqualmie River basin floodplain
    • there are a total of 1,880 parcels. This is approximately 40
    • percent of the total number of parcels in King County
    • floodplains (4,738).
    • There are structures at risk from flooding on 867 of these
    • parcels. The depth of flooding varies depending on
    • location.
    Why Snoqualmie River The Site
  • 5.
    • To develop a GIS model that provides a risk
    • analysis matrix that analyzes the risk exposure
    • from natural hazards for unincorporated
    • heritage properties and archeological sites in the
    • Snoqualmie River Flood Plain.
    • The model will provide finer spatial detail and
    • will be able to be used to replicate the analysis
    • for other areas of King County.
  • 6.
    • Phase I Objectives:
    • Enrich the inventory (Data sets) of the cultural resource within unincorporated King
    • County area of Snoqualmie floodplains.
    • Explore other datasets that may correlate with the mapped data.
    • Correlate data sets and map the outfalls.
    • Provide risk analysis matrix and create models to analyze risk exposure from natural
    • hazards for heritage properties.
    • Create an integrated database.
    • Phase II objectives:
    • Manipulate data so that it can be used in future modeling applications and analysis;
    • Mapping information about risk levels for each property.
    • Formulate hypotheses regarding effects of the mapped outfalls;
    • Provide report on approach and outcome of analysis.
  • 7. Research Resource identification Data Gathering Defining dataset Data accumulation Actual project plan Work breakdown structure Task Division Monitoring the process Status reports Work quality Time schedule Management Focus of today’s Presentation Methodology Definition Of Matrix Database design Creating feature set Digitization Reclassification Analysis Process Model Building Reporting
  • 8.
    • A GIS Model for analyzing risk for unincorporated historical resources in the
    • Snoqualmie River Floodplain of King County
    • A detailed Risk Analysis for the historical resources of King County (in the
    • Snoqualmie River floodplain)
    • A Instructions on how to use the model and Results report on the approach,
    • methodology and outcome of the analysis.
  • 9. Feature Historic DistrictID Location Info Characteristics HistPropretyID HistoricDistrict Polygon HistPropretyID HistDistrictID HistMunicipleID Characteristics Summary CharacteristicDetail HistoricProperty Point HistPropPolygon HistPropretyID HistMunicipality Polygon Polygon HistPropretyID HistStructureID Characteristics Summary CharacteristicDetail HistStructure Polygon Polygon Polygon Point Polygon Object Feature Historic Architecture Feature Feature Archaeological Site GIS Model HistElementID HistPropretyID Location Info HistElemPoint HistElementID HistPropretyID Location Info HistElemPolygon HasSites ArchSite Grid ¼ Mile grid ArchPropertyID Location Info Characteristics Archaeological District Polygon ArchPropertyID ArchProperty Polygon Polygon ArchPropertyID SmithsodianID ArchDistrictID Property Name Location Info Characteristics Summary CharacteristicDetail SiteDetails Archaeological Property Point
  • 10. Project Scope 1 2 3 4 5
    • MATRIX
    • MODELS
  • 11. Data Base 1 Flood Data Set Flood Plain Flood Way Water Bodies Contour Data 5ft Contour 2ft Contour Contour TIN Contour _ Merge Historic Site Point Historic Site Structure Parcel KC Zoning Admin Data Models Flood Plain Raster General Analysis Parcel Analysis Modelwoflood Analysis Structure Analysis Result Raster Set Parcel Flood Parcel Soil Parcel Slope Flood Plain uni Soil 15 Slope Flood pl reclass Soil reclass Slope reclass Final Result Zone st –Par Zonal St- Min Zonal St- Mean Project Scope
  • 12. Digitization 2 A polygon shapefile replaced the existing point shapefile indicating the historic site, but not individual structure within the site. The fields were decided on the bases of inventory documents provided for each site. Point Feature Polygon Feature Project Scope
  • 13. Matrix 3 Structural Risk Percentage Breakup 40% ,5% Status Architectural Style 20% Structural system And Material 20% Structural Condition 15% Site Condition Foundation Type 40% Cladding Type 20% Roof Type 20% Roof Material 20% Accessibility 30% Extant 30% Change in Use 40% Project Scope
  • 14. Matrix 3 The Matrix was prepared based on the consequence and likelihood for each contributor, i.e. structural material (20%), This in turn provided a ranking defining the score of each sub-set i.e. foundation and cladding material . Project Scope Structural Material and Construction Type 20 % Contribute Ranking Score Foundation Type (50%) Conc. Poured 1 10 Post & Pier 2 20 Conc. Block 3 30 Log 4 40 Stone 5 50 Cladding(30%) Stucco 1 6 Brick, Stone 2 12 Log, Hr.Wood siding, Rustic drop,Wood Shingles 3 18 Board and Batten, Vertical Board, Asbestos/Asphalt 4 24 Vinyl/Aluminium Siding,Metal 5 30
  • 15.  
  • 16. Model 4 Mapped Results Analysis Model With/without Floodplain consideration Analysis Model At Parcel Level Analysis Model At Structural Level Mapped Results Mapped Results Project Scope
  • 17. Detailed slope map Detailed soil map Detailed flood elevation map Detailed results map Back To Model
  • 18. Results Maps 5
  • 19. Results Maps 5
  • 20. HEC2 HEC1 Results Maps 5
  • 21. Results Maps 5
  • 22.  
  • 23. Model developed by the US Corps of Engineers Hydrologic Engineering Center (HEC) River Analysis Systems (RAS) TIN Flood elevation Detailed survey information Use of HEC RAS Replicate information to verify data HEC1 Flood information HEC RAS
  • 24. HEC GeoRAS ( extension for ArcMap ) HEC2 Flood information Geo RAS
  • 25. John and Joyce Place HRI # 0937 Results Maps 5
  • 26. Risk Impact Prob. Mitigation Contingency Field population must be done manually and is time consuming High Low Distribute the work between members. Reduce study area. It is necessary to digitize polygons of the historic resources since they are currently in point form. To digitize we need reliable aerial photographs. High Low Contact different resources to get aerial photographs. Use the point dataset or parcel dataset, but the results will be less accurate. The results might not be significant Low High Try to include a variety of historical resources. Talk to sponsor on the probability of this risk (the importance of the project resides on the methodology and model, not so much on the results) The sponsor shows little interest in the project. Low High Constant communication with the sponsor. The team will look for other sources of information aside the sponsor and will make own decisions on the project. Not finishing on time the phases of the critical path Very High Low Use Microsoft Project. Leave slack on the programmed activities. Reduce study area. Risk And Challenges
  • 27.
    • Data Formats
    • Data Conversion
    • Data Generation
    • The Process
    • Keeping up with the Critical Path
    • Scale of the Analysis
    • Loosing a team mate !
    • Communication – Inside and Out
    Risk And Challenges
  • 28.
    • Combination: GIS – Other Tools
    • High Data dependency: But better the data does not
    • guarantee better results
    • Data Verification
    • Importance of the Team……..
    Lesson Learned