uncertainty and changing risk profiles? Dr Dr Ju Judy La Lawren - PowerPoint PPT Presentation

Can we provide dynamic adaptive policy to address uncertainty and changing risk profiles? Dr Dr Ju Judy La Lawren ence Senior Research Fellow Climate Change Research Institute Victoria University Of Wellington Managin ing th the e unavoidable le and avoi oiding g th the e unmanageable

Events Response Climate is changing in an undesired direction — we do not know how fast and how much. How do we start to adapt? Infrastructure and institutional investments are being made now. How should decisions be modified to cope with changing conditions? Source picture: http://www.ideachampions.com

Scope and scale of impacts From what? What is exposed?  Drought  Low-lying land-reclaimed land, ports, airports, cities, towns  Fire  Transport networks  Biosecurity threats- pests and diseases  Underground infrastructure  Indigenous biodiversity  Human activities  Sea-level rise-erosion and inundation, rising groundwater and liquefaction risk  Rural investments  Shift in rainfall patterns  Tourism  Increased rainfall intensity- storm water  Water availability and ponding  More frequent extreme events  Water quality  Increased flood risk- rivers and surface  Endangered habitats water  Health  Increased wind strength  Forestry  Snowfall accumulation decrease  Oceans  Fisheries

What is at stake? Flora and fauna and human habitats, mobility, infrastructure, economic activity, lost earnings, recovery costs, adjustment costs

Costs

Inter-connected and compounding risks

Increase in extremes hot days ↑ cold days/frosts ↓ heavy rain ↑ drought ↑ fire risk ↑ severe storms ± ( ↑ ) Source: Reisinger, A. (2009) Figure 3.5. Based on IPCC AR4 WGI Box TS.5

Increase in frequency 1 in in 100yr event today becomes an annual l affair wit ith modest sea le level l ris ise (by y around 2050-60s): lo low uncertainty 2.9m sp 2.9 spri ring-tid ide ran ange 1.4 1.4m sp spri ring-tid ide ran ange PCE 2015

Threshold effects (After Scheffer 2009)

Climate change risk is more than change in the hazard. Exposure + vulnerability(sensitivity) of people and systems (natural or physical) affects adaptive capacity & consequences

Exposure-sensitivity and adaptive capacity Vulnerability as a function of exposure-sensitivity and adaptive capacity (after Nelson et al 2010) As adaptive capacity increases, exposure-sensitivity decreases and vice-versa. There is greater vulnerability where adaptive capacity is low and there is greater exposure to risk

Uncertainty • People can’t imagine the impacts 2100 and beyond…but climate science and our law asks us to • Difficult for people to accept incurring costs for a future they can’t even imagine • Communities prefer small, incremental change that doesn’t threaten our way of life and sense of place • There is no one ‘owner’ of the issue— ”others should solve it”

Are our r decision frameworks fit for purpose? It is a challenge managing uncertainty and change over long timeframes, across organisations and actors, and across scales of governance. This requires practice that is fit for this problem AND adaptive governance based on the values and preferences of the actors today and in the future

Adequacy of frameworks and practice • Statutory frameworks are designed to deliver certainty of outcome for the actors • BUT they are poorly integrated using static response measures (hazard lines on maps, sea walls and levees …snapshots or are fixed in time and space) …. that lock-in investment, limit future options, affordability and physical limits • AND investments last a long time, existing uses prevail, disruptive to change infrastructure design or location • The dominant economic assessment tools use snapshots in time, discount future risk, raise expectations of protection, reduce flexibility Reference: Lawrence, J., 2015. The adequacy of institutional frameworks and practice for climate change adaptation decision making. Doctor of Philosophy in Public Policy School of Government. Victoria University of Wellington, Wellington, New Zealand, p. 263.

Time-inconsistency 2114 Infrastructure Urban settlements T he lead-in time and Coastal hazard zones the life-time of the adaptation decision Residential housing life Time is KEY in determining Long term plans the type of response Resource consent Regional & district plans Election cycles 2014

Complexity • Complex-many dimensions (time/magnitude/timeframe/rate of change) • Contested problem and values (science/different values/regulatory responsibilities • Many players with divergence ideas for solutions • Fragmented governance • Solutions and problem formulation are intertwined • Decision making can ill-afford to be wrong because consequences can be profound • ‘lock - in’ of development creates path dependency and future high adjustment costs • irreversibility of impact e.g. from ongoing sea level rise or biological systems having nowhere to go (the coast or mountains)

What does decision making demand? • Evidence base clear and certain • ‘Predict and Act’ approach to policy making • Certainty of outcome • Systematic analytics • Clear cause and effect • Transparency of effect

Most approaches for dealing with uncertainty about the future are problematic • Ignore uncertainty • Assume the future is knowable (‘predict -and- act’  ‘optimal’ policy) • Assume the future will (probabilistically) look like the past (  ‘trend - based’ policy ) • Look for a policy that will do well in a few scenarios (  ‘static robust’ policy) • What if the experts do not know and stakeholders cannot agree on what the future might bring = “ deep uncertainty ” where surprises are possible

Decisions must deal with several levels of uncertainty at each location LEVEL Level 1 Level 2 Level 3 Level 4 Context A clear enough Alternate futures A multiplicity of Unknown future (X) future (with probabilities) plausible futures Complete Certainty LOCATION Total ignorance System A single A single Several system Unknown system Model (R) (deterministic) (stochastic) system models, with model; know we don’t know system model model different structures System A point A confidence A known range Unknown Outcomes estimate for interval for each of outcomes outcomes; know we don’t know (O) each outcome outcome Weights A single set of Several sets of A known range Unknown weights; know we don’t on weights weights, with a of weights outcomes probability know (W) attached to each set Source: Walker et al 2013

Definition of deep uncertainty A situation in which the relevant actors do not know, or cannot agree upon: • how the system works • how likely or plausible various future states are • how to value the various outcomes of interest Source: Walker et al 2013 Climate change impacts exhibit such characteristics

Where does climate change sit in the uncertainty typology • Some impact evidence is clear (e.g. sea level is rising, drought and rainfall intensity is increasing, more populations are exposed to impacts) • We know that the sea levels are rising BUT we do not know the rate of change nor the magnitude of change over the longer-term • This implies there are knowns, known unknowns and unknown unknowns (surprises) that require attention. A mix of Types across impacts and time Addressing uncertainty matters because the consequences can be profound

Iteration and learning-based approaches • Wicked characteristics and deep uncertainty mean learning-based approaches are most helpful that: • Demonstrate iterative processes • Build shared understanding of system functioning and how it gives rise to the problem • Develop promising solutions that are flexible and adaptive over time • Generate emergence of solutions through debate amongst decision makers and stakeholders • Are ongoing processes as conditions change

Four Approaches for Dealing with Deep (Level 4) Uncertainty • Resistance: plan for the worst possible case or future situation • Likely to be very costly • Resilience: whatever happens in the future, make sure that the system can recover quickly • Accepts short-term pain; focuses on recovery • Static robustness: aim at reducing vulnerability in the largest possible range of conditions • May be difficult to change when conditions change • Planned adaptation: plan to change over time, in case conditions change

Adaptation: incremental to transformational Incremental: doing better/more of what we do now Ok for some decisions …… for a while…… Limits for others – physical and affordability Risk of lock-in and high future costs Transformational: accept that something has to give; re-assess objectives and change course Mix of protection / accommodation / retreat Relocation of industries, diversification Consider social, environmental, economic objectives Enablers Co-ordination across levels of government Attention to vulnerable groups in society Building stable consensus which takes time and ongoing attention