addressing climate change adaptation in regional transportation plans
addressing climate change adaptation in regional transportation plans addressing climate change adaptation in regional transportation plans
Addressing Climate Change Adaptation in Regional Transportation PlansA Guide for California MPOs and RTPAsData sufficiency. Although few data sets are completely robust, some setsdo not provide sufficient information for useful assessment. Where thesedata sets can be identified prior to the inventory process, considereliminating them.Minimal climate vulnerability. Some assets are highly unlikely to bevulnerable to certain future climate hazards. Buried pipelines (which aresometimes considered through the lens of transportation) are an example ofan asset class that is not likely to be directly impacted by most climatestressors. For assessments that limit the climate hazards considered – sealevelrise only, for instance – assets that are obviously out of harm’s way (farinland or at a significant elevation) may be omitted.Collect Asset DataOnce the study boundaries are set and the list of assets has been established, datacollection can commence. Especially for inventories with many asset categoriesslated for collection, it may be advantageous to develop a data collection plan.Inventorying Assets in the San FranciscoBay AreaAn asset inventory was developed as part ofMTC’s Rising Tides project. Because MTCfaced a few challenges during the datacollection process –data was not readilyavailable nor in an accessible format – MTCtook an alternative approach to the one thatt was laid out in the FHWA conceptualmodel. This approach was iterative in naturerather than sequential, as the FHWA modeldescribes. First, GIS and spatial data, alongwith metadata, were collected for the largersubregion. Next, data related tofunctionality and asset characteristics werecollected to help select representative assets.Finally, detailed stressor data were collected.Source: MTC. (2011.)For most purposes, a multitab spreadsheet canfacilitate this exercise, listing, for example, the assettype, potential sources (Source A, Source B …),collection responsibility, and desired attributes – aframework for which is set out in the followingsection. A spreadsheet can also serve to record thecurrent status of the collection effort for each assettype, as well as the file names for GIS or nonspatialdatabase files, which can be a useful component ofthe project documentation. An example, used forthe compilation of the MTC’s “Adapting to RisingTides” report, an FHWA pilot study, is shown inTable 9.2.In some cases, multiple information sources for asingle asset might be identified. Although thesesources sometimes can exist side-by-side or, in thebest scenario, directly complement one another,generally it is good practice to designate a primarydata set which takes precedence in the instance ofconflicting information. Obviously, if one data setis known to be more accurate or reliable thananother, accuracy should take precedence. Without specific knowledge aboutaccuracy, richer data sets, containing data on the characteristics of usage such asvolumes or ridership, for example, are generally preferred, except in the instancewhere that data is proprietary (and therefore could not be viewed by otherparties or stakeholders).9-6 Cambridge Systematics, Inc.
Addressing Climate Change Adaptation in Regional Transportation PlansA Guide for California MPOs and RTPAsTable 9.2MTC’s “Potential Transportation Asset Types and Data Sources”FHWA Suggested ExampleTransportation AssetCategoriesTransportation Asset TypesConsidered for theSubregionPotential DataType/AvailabilityPotential Data SourceKey road segments Highways and State Routes TeleAtlas Road Network Caltrans and MTCSignals and traffic controlcentersEvacuation routesBack-up power,communication, fueling, andother emergency operationssystemsIntelligent TransportationSystems (ITS), signsPort and airport assetsTunnels and tubes Reports, some GIS CaltransSignals and traffic controlcentersLifeline routes, Emergencyroutes for Oakland and otherlocal jurisdictionsEmergency operationssystems, communicationITSGISReport, some GISAddressesITS Elements in GIS for StateHighwayMTC, cities and AlamedaCountyCaltrans, MTC, citiesCaltrans, MTCNot considered as part of the pilot projectCaltrans, sings not readilyavailable as a datasetSource: MTC, 2011, Adapting to Rising Tides: Transportation Vulnerability and Risk Assessment Pilot Project, November2011, extracted from Appendix A.Desirable Data Attributes for Subsequent AnalysisAn “attribute,” in this context, is a component or characteristic of a given asset(or acting on/affecting this asset) that supports the determination of how critical,vulnerable, resilient, and/or adaptable that asset, or the greater network, mightbe to the effects of climate change. Although the list of potentially desirable assetattributes will be specific to each region and/or agency – and, in any case wouldbe too exhaustive to include in this overview – potential broad attributecategories are included below, along with possible examples.Location and Extent. At the most basic level, knowledge of the location of agiven asset supports identification of possible exposure to geospatial climatehazards, such as inland flooding and sea-level rise. Location may be expressedas a latitude/longitude “point,” especially for smaller assets (signs or signals, forexample); as a “line,” showing, for instance, the extent or spatial path traveled bya roadway or rail line; or, as a two-dimensional shape, called a “polygon,” thatrepresents the geographically-specific area of a facility, such as the boundaries ofa harbor or airport. Figure 9.2 shows the point, line and polygon assetsassembled for the Honolulu Harbor for the Oahu MPO.Cambridge Systematics, Inc. 9-7
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Address<strong>in</strong>g Climate Change Adaptation <strong>in</strong> Regional Transportation PlansA Guide for California MPOs and RTPAsData sufficiency. Although few data sets are completely robust, some setsdo not provide sufficient <strong>in</strong>formation for useful assessment. Where thesedata sets can be identified prior to the <strong>in</strong>ventory process, considerelim<strong>in</strong>at<strong>in</strong>g them.M<strong>in</strong>imal <strong>climate</strong> vulnerability. Some assets are highly unlikely to bevulnerable to certa<strong>in</strong> future <strong>climate</strong> hazards. Buried pipel<strong>in</strong>es (which aresometimes considered through the lens of <strong>transportation</strong>) are an example ofan asset class that is not likely to be directly impacted by most <strong>climate</strong>stressors. For assessments that limit the <strong>climate</strong> hazards considered – sealevelrise only, for <strong>in</strong>stance – assets that are obviously out of harm’s way (far<strong>in</strong>land or at a significant elevation) may be omitted.Collect Asset DataOnce the study boundaries are set and the list of assets has been established, datacollection can commence. Especially for <strong>in</strong>ventories with many asset categoriesslated for collection, it may be advantageous to develop a data collection plan.Inventory<strong>in</strong>g Assets <strong>in</strong> the San FranciscoBay AreaAn asset <strong>in</strong>ventory was developed as part ofMTC’s Ris<strong>in</strong>g Tides project. Because MTCfaced a few challenges dur<strong>in</strong>g the datacollection process –data was not readilyavailable nor <strong>in</strong> an accessible format – MTCtook an alternative approach to the one thatt was laid out <strong>in</strong> the FHWA conceptualmodel. This approach was iterative <strong>in</strong> naturerather than sequential, as the FHWA modeldescribes. First, GIS and spatial data, alongwith metadata, were collected for the largersubregion. Next, data related tofunctionality and asset characteristics werecollected to help select representative assets.F<strong>in</strong>ally, detailed stressor data were collected.Source: MTC. (2011.)For most purposes, a multitab spreadsheet canfacilitate this exercise, list<strong>in</strong>g, for example, the assettype, potential sources (Source A, Source B …),collection responsibility, and desired attributes – aframework for which is set out <strong>in</strong> the follow<strong>in</strong>gsection. A spreadsheet can also serve to record thecurrent status of the collection effort for each assettype, as well as the file names for GIS or nonspatialdatabase files, which can be a useful component ofthe project documentation. An example, used forthe compilation of the MTC’s “Adapt<strong>in</strong>g to Ris<strong>in</strong>gTides” report, an FHWA pilot study, is shown <strong>in</strong>Table 9.2.In some cases, multiple <strong>in</strong>formation sources for as<strong>in</strong>gle asset might be identified. Although thesesources sometimes can exist side-by-side or, <strong>in</strong> thebest scenario, directly complement one another,generally it is good practice to designate a primarydata set which takes precedence <strong>in</strong> the <strong>in</strong>stance ofconflict<strong>in</strong>g <strong>in</strong>formation. Obviously, if one data setis known to be more accurate or reliable thananother, accuracy should take precedence. Without specific knowledge aboutaccuracy, richer data sets, conta<strong>in</strong><strong>in</strong>g data on the characteristics of usage such asvolumes or ridership, for example, are generally preferred, except <strong>in</strong> the <strong>in</strong>stancewhere that data is proprietary (and therefore could not be viewed by otherparties or stakeholders).9-6 Cambridge Systematics, Inc.