New Jersey Department of Transportation Extreme Weather Asset Management Pilot Study Overview Prepared f d for: June 26, 2018
Introduction • Overview of Pilot Study • New Jersey’s Climate • New Jersey’s Transportation Assets • New Jersey Challenges • Summarize study approach & findings • Next Steps Hurricane Sandy approaching the New Jersey coastline on October 29, 2012
New Jer erse sey’s C s Climate • 41 emergency declarations in the last 10 years (State and Federal Declarations ) • 16 associated with flooding or tropical storms (Hurricane Sandy in 2012, and Tropical Storm Irene the most damaging) • 18 winter storm related • Average annual temperatures have increased by 3 degrees F over the past century • Highly variable precipitation with wetter than average conditions in the last decade (Average annual precipitation = 46.01 inches, projected to increase) • Sea level along New Jersey’s coast has risen by more than 16 inches since 1911, double the global average (projected to rise 1 to 4 feet by 2100) Passaic River fills street in Paterson, NJ – Hurricane Irene
New Jer erse sey’s T s Transp sportation • 8,543 lane miles of pavement in the State Highway System (35% considered good condition, 32% fair, 33% poor) • 2,676 lane miles of Interstates (61% good, 38% fair, 1% poor) • 6,702 bridges • 2,582 NJDOT owned/maintained bridges (29%,, 59%, 12%) • 6,096 minor bridges • 956 NJDOT owned/maintained minor bridges (26% good, 69% fair, 5% poor) • 4 major airports • 3 major water ports including the largest seaport in the US in Elizabeth Home of 3 rd largest commuter service provider (NJ Transit, bus, rail & light rail) with • weekday daily ridership totaling 928,494 (2015) • 981 miles of freight railroad • 360 miles of waterway New Jersey Victory Bridge over Route 35
New Jer erse sey’s C s Cha hallenges es • Coastal area presents its own unique challenges (impacts from storm surges, tidal flooding, projected sea level rise, plus Tourism and associated land use development challenges - the need to “rebuild” in flood prone areas to maintain economic stability, value of “beach front property” • Varying weather stressors • Winter storm events are growing concern • Inland flooding • How to account for extreme weather considerations in analytical tools used to predict asset performance over time (rate of deterioration)
Linking g Extrem eme Weather er a and nd Asse set M Mana nagem emen ent • NJDOT currently establishing an Asset Management Plan/Program and has identified extreme weather as an external environmental factor in assessing risks • TAMP – Risk Management Process • Identifying, assessing, evaluating risks, developing a mitigation plan and monitoring top priority risks • Extreme weather currently 3 rd highest risk in NJDOT’s Risk Register • Using results of pilot program to develop a strategy to implement in TAMP Process • 23 CFR Part 667 Evaluation
Pilot ot O Overview ew 2017 selected with 5 other states - Arizona, Kentucky, Massachusetts, Maryland, & Texas, to participate in a Pilot Program focused on extreme weather, climate risks, and asset management Aerial View of Study Area: I-80
Pilot ot O Overview ew Originally selected culverts as the “asset class” to investigate impacts of extreme weather Focused on “noncoastal” areas Could not study entire state so selected a specific study area to see what could be learned and applied state wide Study refocused on identifying “root causes” of flooding in the target area to then develop cost-effective mitigation strategies
Compile & I e & Integ egrate Da e Data Internal Sources: - Drainage Management System (DMS) - Maintenance Management System (MMS) - Culvert Inspection Reports (Bureau of Structural Evaluation and Bridge Management, SEBM) - Operations Region’s Input - Crash Data (Bureau of Transportation Data and Safety, BTDS) External Sources: - Concept Development Reports from Design Team (Louis Berger) - NOAA Other: - GIS 2016 DMS Rankings Snapshot
Case se Study A Area ea
New I Ini nitiatives: es: Linking E Extreme e Weather er a and nd A Asse set Managemen ent Understanding The Problem • Asset Management, Extreme Weather, and Proxy Indicators Pilot STRESSOR: PRECIPITATION • The research is aimed at identifying the WEATHER-RELATED RISK: FLOODING root cause of flooding to target the most cost-effective risk management IMPACT MOBILITY mitigation to incorporate in lifecycle SAFETY planning INFRASTRUCTURE PRESERVATION
Prel eliminary Da Data Ana nalysi sis R Resu sults: s: I I-80 M 0 MP 5 56.43 t 43 to MP 58.22 22 Total Number of 50 Incidents Recorded Westbound 41 82% Eastbound 9 18% EB WB
Number o of R Recorded F Flooding I Incidents b by Y Year Month Month 2012 2013 2014 2015 2016 2017 Total • 2014 experienced the highest January 1 0 0 0 0 0 1 number of recorded flooding February 0 0 2 0 0 0 2 incidents between the five- March 0 0 2 0 0 0 2 year period (2012-2017) April 0 0 3 0 1 0 4 May 1 0 1 0 0 0 2 • 2016 experienced the second June 0 0 3 0 0 1 4 highest number of recorded July 1 0 1 2 5 1 10 flooding incidents between August 1 2 0 0 0 0 3 the five-year period (2012- September 2 2 0 2 0 0 6 2017) October 0 0 2 3 2 0 7 November 0 0 3 0 4 0 7 December 1 0 0 1 0 0 2 Year Total 7 4 17 8 12 2
I-80 80 N Num umber er o of I Inc nciden ents vs. vs. M Mainten enanc nce A Activities es (Clea eaning) b by Year (201 2012-2017) 017) 18 16 14 12 10 8 6 4 2 0 2012 2013 2014 2015 2016 2017 Incident Maintenance Activity
Prel eliminary Da Data Ana nalysi sis R Resu sults: s: R Rt. 23 M 3 MP 4 4 to M MP 7 7 Total Number of 17 Incidents Recorded Northbound 1 6% Southbound 16 94% NB SB - One extra incident recorded (not flooding). - Number of incidents noting “clogged storm drain” = 7.
Route e 23 N 3 Num umber er o of I Inc nciden ents vs. vs. M Mainten enance A e Activities es (Clea eaning) b by Year (201 2012-2017) 017) 10 9 8 7 6 5 4 3 2 1 0 2012 2013 2014 2015 2016 2017 Incident Maintenance Activity (Cleaning)
Compariso son of Case S se Study A Area eas ( (201 2012-2017 Y 017 Yr. Period) d) I-80 Route 23 Study area location: MP. 56.43 to MP 58.22 (1.79 miles) MP. 4.0 to MP 7.0 (3 miles) DMS ranking (2016 data): #1 #14 AADT in one direction: 62,515 29,092 Number of recorded incidents: 50 17 Critical areas: WB between MP 57 – 57.5 SB between MP 6.8 – 62.82 Total number of maintenance 18 42 activities in 5-yr. period: - Cleaning activities 11 27 (inlets/manholes/channels ditches/pipes):
Ho How a about t the c culverts ts ? ?? • As builts and inspection reports noted culverts were not contributing factors to flooding, drainage issues, not culverts….inlet spacing, • Although designed and constructed some time ago without “extreme weather” considerations, function ok today, as long as they are maintained • Reaffirms need to identify possible root causes of flooding, before strategies are developed to address risks of extreme weather I-80 Culvert (located at MP 57.35 on Westbound direction)
Incorporating S Study Results i into Asset M t Management • Root cause analysis identifies a method to evaluate and develop risk mitigation actions • Better understanding of relationship between stressor, roadway system performance and cause of problem • Incorporate study’s recommendations into lifecycle planning in the planning, design/engineering, and maintenance/operations phases • Enhance/implement the use of GIS as a “Resiliency Management System” to be incorporated into NJDOT’s current process
Develo lopin ing a a “Res esil ilience M Management Tool ool/System” – How t to iden entify v vulner erabil ilit ities es GIS ca S can h help • Use various digital layers to give an indication of what areas could be subject to flooding • Project case study areas and culverts within these locations. (System can be used for any Assets) • National flood hazard layer from FEMA. • Soil hydrologic group layer. • In progress: precipitation historical data and projections, and maintenance activities. • Data shows: • Project case study areas are in low terrain (between 50’ – 200’). • Case study area soil group = low permeability. • Route 23 within 100-yr flood zone.
GIS – I-80 Digital Elevation Model
GIS – I-80 Flood Hazard Zones
GIS – I-80 Soil Groups
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