Sustainable maintenance policy for infrastructure networks in the Randstad: a climate change perspective Prof.dr. Geert Dewulf and dr. I. Stipanovic, University of Twente
Project team dr. I. Stipanovic, dr. A. Hartmann, Prof. dr. G. Dewulf, University of Twente dr. H. ter Maat, dr. C. Jacobs, Prof. dr. P. Kabat, Wageningen University 2
RESEARCH OBJECTIVES Understanding the impact of climate changes on the asset performance (roads and railways) Developing local climate scenarios Analysing the relationship between maintenance renovation & reconstruction decision-making and public policies Evaluation long-term impacts caused by climate change Determining appropriate adaption strategies 3 3
Methodology: Top-down & Bottom -up Climate Change Models Policy Industry Impact Analyses Economic Analysis Adaptation Organization Infrastructure Operators Material Science Structure Design Infrastructure Roads & Railways Construction & Maintenance Costs Damage Data 4
Transport infrastructure performance relation to climate variable (e.g. temperature, rainfall, snow) Change to climate variable (Local climate scenarios, e.g. more hot days, increased precipitation) Historical data about performance and maintenance Correlation between infrastructure performance and weather conditions Baseline threshold values future incidents Impact - costs (e.g. increased incidents of washout, flooding and scour new design requirements) Risk matrix (classification and quantification of risks) Adaptation strategies (e.g. strengthening substructure) 5
Road infrastructure: The problem & question Increased road damage 90% porous asphalt, dense road network Increased winter maintenance & shorter lifespan Long-term climate change adaptation How will changes in Freeze-Thaw cycles impact porous asphalt road network? Infrastructure Planning Support System Larger body of work Precipitation, temperature Roads, buildings, bridges 6
The Approach Stressor Freeze-Thaw cycles Precipitation Temperature Traffic load Infrastructur e Roads Buildings Bridges Response Thresholds Design standards Maintenance Costs 7
Methodology: Main Inputs & Downscaling Climate Temperature Data Roadstock Conversion GCMs National Totals Latitudebased Default costs RCMs Open Source Data Regional weather data Dutch costs (external reports) RCMs 25km scale RWS-provided GIS map Localized sensor data RWS actual costs Cost 8
Methodology: Freeze-Thaw 9
Netherlands: Empirical Analysis % frost vs. #F/T for 2 winters Roadstock by Province (km) 0,25 1111 Zeeland 30 0,2 Zeeuwse meren frost damage (% of length) 2010/11 2011/12 Zeeland Service432 Life Maintenance2012/13 Costs f(x) = 0x^3-0x^2 + 0x + 0 550 A10 AmsterdamUtrecht 22 5(thousand per KM) 22 (years)r² = 0,81 550 Overijssel 0,15 A12 Haaglanden 18 5 22Width Road type Noord-Holland Right Lane Full Width 911 Right Lane Full A12 Utrecht 25 24 13764 Noord-Brabant DAB 12 18 85,500 427,500 0,1 659 Limburg A15 Arnhem&Nijmegen 30 9 36 68 IJsselmeer ZOAB 11Amsterdam 17 90,000 450,000 A44 - Haaglanden and 16 3 14 358 Groningen ZOABTW 9 0,05 13 756,000 A7 Alkmaar Gelderland 26 1099 151,200 4 23 534 Friesland A15 Twente&Achterhoek 32 9 31 252 Flevoland 0 A37 Groningen&Drenthe 461 Drenthe 24 15 4 25 3035 0 5 10 20 30 0 200 400 600 800 1000 1200 1400 1600 # of F-T Cycles # of F/T cycles 13 13
Results: Freeze-Thaw Median Average Annual Cost by Province (Million Euro) Median Average Annual Cost, National (Million Euro) 4,50 1,80 4,00 3,50 1,60 3,00 2,50 1,40 2,00 1,20 1,50 1,00 1,00 0,50 0,80 0,60 0,40 0,20 2020 2030 2040 2050 Adapt 2060 2070 2080 2090 2100 No Adapt 14 14
Scientific results The importance of regional studies Methodology for translating air temperature road temperature damage future scenarios costs Risk road performance model depending on: Type and age of asphalt Traffic intensity Climate Supporting tool for infrastructure managers visualizalisation of the risks using GIS maps and risk model 17
Lessons learned the improvement of the data collection about the failures is necessary; only local effects are stored there are often effects on other components and long-term effects; no consistent information about costs, delays and safety; database should be in accordance with the final objective development of maintenance and / or adaptation measures; 19
Thank you for your attention! STS N 49 TRA2014 Paris 14-17 avril 2014 20
Future steps Develop a risk-based tool further Improve cost model Integrate monitoring data into the existing management systems Apply the methodology for other climate stressors and potential risks (e.g. flooding, scouring of the bridges) 21
Railway infrastructure (analysis of 11 years historical events) Weather events vs. failure modes
High temperature related incidents (daily Tmax) 23
Threshold values for different weather events and the likelihood of infrastructure failures Failure occurrence Component most Weather event High temperature endangered Unlikely, Threshold 1 Threshold 2 Threshold 3 < 33 % Possible, 33 66 % Likely, 66 99 % Certain, > 99% T < 28 C 28 C < T 33 C 33 C < T 35 C T > 35 C track failure T > -5 C -9 C T < -5 C -12 C T < -9 C T < -12 C switches < 10 10 < s 22 22 < s 50 > 50 switches ( C) Low temperature ( C) Snowfall (mm/day) Different threshold values comparing to other studies with larger scale, e.g. EWENT project European level proposed for snowfall: 24 30 mm, 100 mm and 150 mm / day
Analysis winter situation for selected location 25
Analysis summer situation for selected location 26 26