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Estrategias para evaluar Cambio Climático en Infraestructuras Críticas - Juan Gutiérrez

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Estrategias para evaluar Cambio Climático en Infraestructuras Críticas - Juan Gutiérrez

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Estrategias para evaluar Cambio Climático en Infraestructuras Críticas - Juan Gutiérrez

  1. 1. Estrategias para Evaluar Cambio Climático en Infraestructuras Críticas Juan Gutiérrez Andrés 13 Julio 2017
  2. 2. © HR Wallingford 2017 Climate change and critical infrastructure July 2017 Page 2
  3. 3. © HR Wallingford 2017 International Climate Agreement COP21, Paris, December 2015 Intended Nationally Determined Contributions (INDCs). International agreement with countries post-2020 climate actions July 2017 Page 3
  4. 4. © HR Wallingford 2017 Resilient and adaptive intervention Pillars for resilience and adaptability of projects July 2017 Page 4
  5. 5. © HR Wallingford 2017 Climate change risk assessment and adaptation July 2017 Page 5 UK context
  6. 6. © HR Wallingford 2017 National Adaptation Programme Climate Change Act UK Climate Projections (UKCP09) Adaptation Reporting Powers (ARP) Climate Change Risk Assessment (CCRA) Economics of Climate Resilience (ECR) National Adaptation Programme (NAP) July 2017 2008 2009 2010-11 2012 2013 2013 Page 6
  7. 7. © HR Wallingford 2017 • 5 year cycle • Compares different sectors • Single set of outputs • Transparency • Learning process UK Climate change risk assessment process
  8. 8. © HR Wallingford 2017 Climate Change Risk Assessment (CCRA) Assessing climate change risks to 2100 for 11 sectors in 5 themes October 2013
  9. 9. © HR Wallingford 2017 Mitigation is vital, but we need to prepare for inevitable climate change 9
  10. 10. © HR Wallingford 2017 Climate Change Risk Assessment (CCRA) October 2013
  11. 11. © HR Wallingford 2017 Climate Change Risk Assessment (CCRA) October 2013
  12. 12. © HR Wallingford 2017 Headline Findings for the UK * This estimate takes into account population growth as well as climate change, and includes costs from fluvial and tidal flooding (not surface water flooding) Flooding • Annual damage to properties could rise from the current figure of £1.2 billion for England and Wales alone to £2-12 billion* by the 2080s. Health risks • Premature deaths due to cold winters are projected to decrease significantly (e.g. by between 3900 and 24,000 by the 2050s) whilst premature deaths due to hotter summers are projected to increase (e.g. by between 580 and 5900 by the 2050s). Water scarcity • By the 2050s, between 27 million and 59 million people in the UK may be living in areas affected by water supply- demand deficits. Ecosystem risks • Some species could benefit, but many more would be negatively impacted, having knock-on effects on habitats and on the goods and services that ecosystems provide.
  13. 13. © HR Wallingford 2013 Principles of adaptation decision-making July 2017 Thames Estuary 2100 Page 13
  14. 14. © HR Wallingford 2017 The Thames Estuary July 2017 Thames Barrier Teddington Weir River Thames Southend River Medway River Darent River Roding River Lee Primary defences Secondary defences Barking Barrier Canvey barriers Dartford Barrier Erith GREATER LONDON Westminster Floodplain area: 350 km2 Length of estuary: About 100km Length of defences: About 350km Number of properties in floodplains: About 540,000 Page 14
  15. 15. © HR Wallingford 2017 The challenges (1) Climate change  Sea level rise (currently 3mm/year)  Increases in river flood flows  Is London sustainable in the long-term? Thames Barrier originally designed for climate change up to 2030  Is this still correct? Deterioration of defences  Defences will require repair and/or replacement in the next 100 years July 2017 Page 15
  16. 16. © HR Wallingford 2017 The challenges (2) Development  Major developments on the floodplains in the last 50 years  Olympics; new port; Canary Wharf  Future developments also planned  Can this be protected? The environment  Need for habitat creation  Improvement of the urban environment July 2017 Page 16
  17. 17. © HR Wallingford 2017 Sea level rise scenarios 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 2000 2020 2040 2060 2080 2100 2120 Increaseinsealevel(m) Date Increases in Mean Sea Level (MSL) and 1000-year tidal surge components Defra MSL rise Defra total (=SL rise) Medium High MSL rise Medium High total High+ MSL rise High+ total High++ MSL rise High++ total Defra06 Peak Level and MSL in 2100 July 2017 Page 17
  18. 18. © HR Wallingford 2017 Flood risk management options 2005 Flood risk Target level of flood risk Introduction of portfolios of responses to reduce flood risk Time Baseline flood risk 2100 AN OPTION Target level of flood risk varies depending on FRM policy July 2017 Page 18
  19. 19. © HR Wallingford 2017 Development of final options • Ten options considered in detail • Use of latest Government climate change projections • Appraisal to identify ‘preferred’ option(s) • Consultation with stakeholders and feedback • Management plan for the flood defences (deterioration, repair, replace) July 2017 Page 19
  20. 20. © HR Wallingford 2017 Preferred options • Now: maintain and improve existing system • When sea level rise 0.21m from 2000: raise some primary defences • When sea level rise 0.46m from 2000: raise secondary defences • When sea level rise 0.52m from 2000: Either:  Major improvement to Thames Barrier plus defence raising Or  New barrier at Long Reach (17km downstream) plus defence raising July 2017 Page 20
  21. 21. © HR Wallingford 2017 Indicator value (e.g. sea level rise) Time Threshold value of indicator when intervention is needed Lead time for planning and construction Recorded values of indicator Date of review Predicted values of indicator based on rate of change Decision point based on best estimate The Plan is based on assumptions about future change….. July 2017 Page 21
  22. 22. © HR Wallingford 2017 Indicator value (e.g. sea level rise) Time Threshold value of indicator when intervention is needed Lead time for planning and construction Recorded values of indicator Date of review Assumed values of indicator in Plan New Decision Point based on best estimate Predicted values of indicator based on rate of change Decision Point in Plan Change in date of Decision Point New Decision Point based on best estimate Rates of change will differ from assumptions: Need to monitor indicators July 2017 Page 22
  23. 23. © HR Wallingford 2017 TE2100: Lessons learned • Start by understanding your extreme scenario (i.e. what’s the worst that could happen?) • Understand your constraints (i.e. what you can/cannot do?) • Consider your long-term intervention options and then develop your near-term options that can be adapted to the long-term • Appraisal must be based on agreed projections with sensitivity testing (robustness of decisions) • Allow time for the development of new concepts and their acceptance • Making something too big is a small cost to bear compared to making something too small July 2017 Page 23
  24. 24. © HR Wallingford 2017 Climate proofing principles July 2017 Page 24 Sandy Bay water service improvement project, St. Vincent
  25. 25. © HR Wallingford 2017 Climate proofing the Sandy Bay water service improvement project, St. Vincent Problem: Reduced reliability and quality of the potable water supply to the residents of the Sandy Bay Village and neighbouring communities due to extreme rainfall events. Approach: • Sandy bay risk assessment • Identification of possible interventions • prioritisation and selection of interventions using the risk assessment and social and economic criteria July 2017 Page 25
  26. 26. © HR Wallingford 2017 Identify and assess baseline risks July 2017 Assess baseline climate risks Prepare climate change and socio-economic projections Assess future climate risks Likelihood Likelihood comment Severity Severity comment Risk score Risk 1 – Heavy rainfall induced turbidity Very frequent occurrence Occurs 10 times per month in dry season Moderate Health impacts unknown, disruption usually lasts <1 day Extreme risk Risk 2 – Landslides and high river flow damage to infrastructure Occasional occurrence Has occurred in 2013 Major Caused disruption for 1 week High risk Risk 3 – Bacterial and chemical pollution of raw water during heavy rainfall Occasional occurrence Not known to occur, but uncertainty is high. Low likelihood assumes chlorination is effective Low if chlorination is effective Potential for health impact if chlorination fails or chemical contamination occurs Low risk Risk 4 – Bacterial and chemical pollution of raw water during dry season low flows Very unlikely to occur Not known to occurred in historical period Low if chlorination is effective Potential for health impact if chlorination fails or chemical contamination occurs Low risk Risk 5 – Drought induced reduction in source yield Very unlikely to occur Not known to occurred in historical period Major Potential for service interruptions of long duration, health risks of alternative sources Moderate risk Risk 6 – High water demand during dry periods leading to low pressure and shortages Very unlikely to occur Not known to occurred in historical period Moderate Potential for service interruptions Low risk Risk 7 – Loss of electrical supply at Sandy Bay treatment plant (proposed N/A Not applicable as existing system does not require electrical power N/A No impact possible No risk Page 26
  27. 27. © HR Wallingford 2017 Identify and assess baseline risks July 2017 Assess baseline climate risks Prepare climate change and socio-economic projections Assess future climate risks Likelihood Likelihood comment Severity Severity comment Risk score Risk 1 – Heavy rainfall induced turbidity Very frequent occurrence Occurs 10 times per month in dry season Moderate Health impacts unknown, disruption usually lasts <1 day Extreme risk Risk 2 – Landslides and high river flow damage to infrastructure Occasional occurrence Has occurred in 2013 Major Caused disruption for 1 week High risk Risk 3 – Bacterial and chemical pollution of raw water during heavy rainfall Occasional occurrence Not known to occur, but uncertainty is high. Low likelihood assumes chlorination is effective Low if chlorination is effective Potential for health impact if chlorination fails or chemical contamination occurs Low risk Risk 4 – Bacterial and chemical pollution of raw water during dry season low flows Very unlikely to occur Not known to occurred in historical period Low if chlorination is effective Potential for health impact if chlorination fails or chemical contamination occurs Low risk Risk 5 – Drought induced reduction in source yield Very unlikely to occur Not known to occurred in historical period Major Potential for service interruptions of long duration, health risks of alternative sources Moderate risk Risk 6 – High water demand during dry periods leading to low pressure and shortages Very unlikely to occur Not known to occurred in historical period Moderate Potential for service interruptions Low risk Risk 7 – Loss of electrical supply at Sandy Bay treatment plant (proposed N/A Not applicable as existing system does not require electrical power N/A No impact possible No risk Page 27
  28. 28. © HR Wallingford 2017 Assess baseline climate risks Prepare climate change and socio-economic projections Assess future climate risks Future projections Examples from SVG July 2017 Consistently warmer temperatures • Observed warming trend (0.15 degC / decade) • Climate models indicate warming (~2-3 degC by 2080s) Less rainfall on average • Observed drying trend (1960-2006) (-5% per decade) • Climate models indicate drying (-15% to -30% by 2080s, could be more or less) Changing storm intensity / heavy rainfall • Difficult to measure trends, although a slew of notable events in recent years • Climate models struggle to represent extreme rainfall, but could increase Rising sea levels Caribbean sea levels rising in line with global trends (1.8mm / year accelerating) Lots of climate model uncertainties, but could be up to ~1.5m by 2080s (Ramsdorf, 2007) Page 28
  29. 29. © HR Wallingford 2017 Assess future risks July 2017 Assess baseline climate risks Prepare climate change and socio-economic projections Assess future climate risks Risk Climate change drivers Direction of change Impacts on system Non-climate compounding factors Risk 1 – Heavy rainfall induced turbidity Increase / decrease in heavy rainfall Increase / decrease in hurricane activity Direction of change uncertain Increased / decreased frequency of raw water turbidity incidents Deforestation and farming in upper catchment could increase risk Risk 2 – Landslides and high river flow damage to infrastructure Increase / decrease in heavy rainfall Increase / decrease in hurricane activity Direction of change uncertain Increased / decreased frequency of damage to infrastructure Deforestation and farming in upper catchment could increase risk Risk 3 – Bacterial and chemical pollution of raw water during heavy rainfall Increase / decrease in heavy rainfall Direction of change uncertain Increased / decreased frequency and / or severity of raw water storm runoff contaminated with microbes / chemicals Deforestation, farming in upper catchment (animal waste / chemicals) could increase risk Risk 4 – Bacterial and chemical pollution of raw water during dry season low flows Decrease in seasonal rainfall / Increase in temperature Decrease in rainfall likely, increase in temperature very likely Increased frequency and / or severity droughts, reducing river flows and the dilution of contaminants Farming in upper catchment (animal waste / chemicals) could increase risk Risk 5 – Drought induced reduction in source yield Decrease in seasonal rainfall / increase in temperature Decrease in rainfall likely, increase in temperature very likely Decrease in source dry weather flow in average and drought years Land use change in upper catchment reducing groundwater infiltration could increase risk Risk 6 – High water demand during dry periods leading to low pressure and shortages Increase in temperature Increase in temperature very likely Increased dry weather demand from consumers places strain on source and system capacity Consumer behaviour and socio- demographic changes leading to higher demand could increase risk Risk 7 – Loss of electrical supply at Sandy Bay treatment plant (proposed option only) Increase / decrease in heavy rainfall Increase / decrease in hurricane activity Direction of change uncertain Increased / decreased frequency of power outages Upgrading of electricity systems could improve resilience and reliability to offset this riskPage 29
  30. 30. © HR Wallingford 2017 Identifying resilience measures  Solar PV as a back up.  Improving accessibility of water intake.  Back up groundwater supply for disaster situation.  Increase water storage volume to maintain supply.  Reforestation to maintain water quality.  Awareness raising in community.  Training farmers in techniques to minimise erosion.  Partnership between utility, forestry and agriculture agencies  Training communities in water purification.  Working on contingency plans.  Strengthening community disaster response.  Regional knowledge sharing and capacity development  Install monitoring equipment on water supply system.  Specific staff training needs. July 2017 Page 30
  31. 31. © HR Wallingford 2017 Impacts from violent wave overtopping July 2017 Page 31 Dawlish rail line
  32. 32. © HR Wallingford 2016 The infrastructure Page 32 Exeter Newton Abbot Dawlish
  33. 33. © HR Wallingford 2016 The infrastructure Page 33 From Mott MacDonald (2013)
  34. 34. © HR Wallingford 2016 The problems Page 34 1855 2014 • Sea level rise • Local land levels falling
  35. 35. © HR Wallingford 2016 The approach Page 35 Modelling approach to support the decision-making process Method for coast & estuaries Hindcasting analysis Assessment of scenarios • Present day • Climate change CC + adaptation measures
  36. 36. © HR Wallingford 2016 Estuaries Page 36 Impacts of climate change: • On river flows • On boundary conditions downstream Exeter Newton Abbot Dawlish Exe Teign Water levels on the track
  37. 37. © HR Wallingford 2016 Coastal frontage Page 37 Overtopping Impact of climate change: • sea level rise considering storm surges
  38. 38. © HR Wallingford 2016 Coastal frontage Page 38 Offshore multivariate extreme value analysis  Concurrent observations of waves, winds and water levels  Monte Carlo simulation of joint parameters  10,000 years
  39. 39. © HR Wallingford 2016 Coastal frontage Insert Date ('Insert - Header & Footer') Insert footer for all slides with 'Insert - Header & Footer' Page 39 Wave transformation modelling  Transform offshore Monte Carlo simulations through the near shore  2D SWAN model + emulator
  40. 40. © HR Wallingford 2016 Coastal frontage Page 40 Analysis of wave overtopping rates  Definition of protection geometry and beach profiles  1D SWAN model + overtopping equations
  41. 41. © HR Wallingford 2016 Hindcasting analysis Page 41 • Simulation of 35 years (1980-2014) – overtopping rates • Difficulties interpreting historical data 0 1,000 2,000 3,000 4,000 5,000 6,000 Delaytime(inminutes) Date Quotes: 11/01/2001: “Very rough sea…stones thrown against train” 1/12/2005: “Atrocious conditions…over-wash…debris”
  42. 42. © HR Wallingford 2016 Climate change and adaptation measures Page 42 Structural measures • Raise of crest levels • Creation of a revetment slope • Consideration of a detached defence Climate change conditions • Years 2065 and 2115 • Low, Medium and High emissions
  43. 43. © HR Wallingford 2016 Results Page 43 Exe Estuary Water levels (in mAOD) Coastal frontage
  44. 44. © HR Wallingford 2017July 2017 Page 44 Final thoughts
  45. 45. © HR Wallingford 2017 How to tackle climate change and uncertainties when planning critical infrastructure We need to plan and implement interventions that reduce vulnerability and build resilience Interventions need to be resilient and adaptive Climate change uncertainties Long life critical infrastructure Climate change and uncertainties need to be incorporated through the project cycle Prioritise climate resilient interventions in sectoral, regional and national policies July 2017 Page 45

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