AGWA: Integrating Climate Adaptation into Water Management Decisions Rolf Olsen, PhD Institute for Water Resources U.S. Army Corps of Engineers Alexandria, Virginia, USA

Outline Alliance for Global Water Adaptation – Background – Uncertainty of climate models – Bottom-up approaches to risk management AGWA Decision Support System (DSS) Two case studies – International Upper Great Lakes Study (IUGLS) – United States and Canada – Coralville Reservoir – U.S. Army Corps of Engineers

AGWA network alliance4water.org Development banks and capacity-building groups. The World Bank, the Asian Development Bank, European Investment Bank, KfW, the Inter-American Development Bank, GiZ, the Cooperative Programme on Water and Climate. Non-governmental Organizations Conservation International, the Delta Alliance, International Water Association, the Swedish Environmental Institute (IVL), the Global Water Partnership, Deltares, Environmental Law Institute (ELI), Stockholm Environmental Institute (SEI), Organization for European Cooperation and Development (OECD), Stockholm International Water Institute, Wetlands International, IUCN, The Nature Conservancy, ICIMOD, WWF. Governmental US Army Corps of Engineers, US State Department, NOAA, UN Water, UN Habitat, UNECE, Water Utilities Climate Alliance, WMO, CONAGUA, Seattle Public Utilities, The Private Sector Ceres, UNEP FI, World Business Council for Sustainable Development Key partners Water & Climate Coalition, the Adaptation Partnership, the Global Environment Facility, Nairobi Work Programme Development banks and capacity-building groups. The World Bank, the Asian Development Bank, European Investment Bank, KfW, the Inter-American Development Bank, GiZ, the Cooperative Programme on Water and Climate. Non-governmental Organizations Conservation International, the Delta Alliance, International Water Association, the Swedish Environmental Institute (IVL), the Global Water Partnership, Deltares, Environmental Law Institute (ELI), Stockholm Environmental Institute (SEI), Organization for European Cooperation and Development (OECD), Stockholm International Water Institute, Wetlands International, IUCN, The Nature Conservancy, ICIMOD, WWF. Governmental US Army Corps of Engineers, US State Department, NOAA, UN Water, UN Habitat, UNECE, Water Utilities Climate Alliance, WMO, CONAGUA, Seattle Public Utilities, The Private Sector Ceres, UNEP FI, World Business Council for Sustainable Development Key partners Water & Climate Coalition, the Adaptation Partnership, the Global Environment Facility, Nairobi Work Programme

AGWA: A Brief Overview The Alliance for Global Water Adaptation is a group of regional and global development banks, aid agencies and governments, a diverse set of non-governmental organizations (NGOs), and the private sector focused on how to manage water resources in way that is sustainable even as climate change alters the global hydrological cycle. Focused on how to help practitioners, investors, and water planners and managers make systematic, consistent, and resilient decisions

Current Approach to Adaptive Water Resources Management Use one or more climate models (GCMs) Generally use more than one scenario “Downscale” to watershed scale A few key air temperature, precipitation variables “Test” for vulnerability based on the constraints of the original GCMs 1. Downscale climate model projections 2. Estimate shifts in water supply 3. Determine system responses to changes in these variables Weaver et al., 2012, WIREs Climate Change

Uncertainty Models not developed for adaptation purposes but for testing hypotheses about greenhouse gas mitigation. Low confidence, especially for quantitative purposes Little agreement across models, scenarios Often result in a series of “no regret” options Stakeholders often feel disempowered by process, which is often experienced as deterministic Source: Wilby & Dessai, 2010, Weather Traditional approaches amplify or hide uncertainty Source: AGWA, “Caveat Adaptor,” 2013

Flood Frequency Estimation from Global Climate Models (GCMs) GCMs do a poor job of replicating climate conditions that often cause hydrologic extremes such as floods. Models have a general, though not universal, tendency to underestimate the magnitude of heavy precipitation events. Use of an ensemble of global climate models to derive probability distributions assumes that an ensemble of models represents the range of potential climate uncertainty – Climate models represent only a small fraction of potential future climate conditions and a small range of uncertainty. – Uncertainties that are related to the underlying science will be the same in different models.

Top-down vs. bottom-up approaches top-down approaches to risk assessment decision-scaling risk assessment 1. Define your system’s breaking points 2. Assemble multiple climate data sources and link to breaking points 3. Assess plausibility and test vulnerability 1. Downscale climate model projections 2. Estimate shifts in water supply 3. Determine system responses to changes in these variables Weaver et al., 2012, WIREs Climate Change

hydrology & climate science finance & economics ecology & engineering governance AGWA DSS World Bank, SIWI, EIB, OECD ELI, DoS, Pegasys USACE, UMass CI, IDB, USACE, WWF Software development: SEI, Hydrology.nl, UMass, ULoughborough

Establish Decision Context Identify Risks Analyze Risks Evaluate Risks Risk Mitigation Monitor, Evaluate, Modify Consult, Communicate and Collaborate Risk Assessment Adapted from ISO Risk Management—Principles and Guidelines Risk-Informed Decision Making

AGWA DSS - Define Problem Articulate goals and objectives What are potential problems and opportunities? Define spatial and temporal scale of problem Define metrics for success What are decision criteria? What are consequences of actions or non-action (economic, ecological, social, public safety)?

AGWA DSS – Identify Key Drivers Identify key drivers and stressors. Drivers are forces that can have major influences on the system of interest. Potential drivers could be of physical, biological or economic origin (i.e., climate, invasive species, population growth, etc.). Stressors are changes that occur that are brought about by the drivers. Determine the range of climate conditions under which the system of interest can acceptably meet its multiple objectives. Determine thresholds where system performance becomes marginal or fail. Method – Conduct stress test of system based on defined decision criteria. – Assess response surface and vulnerability zones of each driver. – Is system climate resilient (system is not sensitive to potential shifts in climate)?

AGWA DSS - Climate Sensitivity Questions – Are we already in a vulnerable climate state? – Are we observing shifts in the data that would suggest a transition into a vulnerable climate state? – Is there agreement between data, suggesting confidence? Small confidence intervals, Agreement in data trends/shifts – How steep is response surface? – How sensitive is your system to changes in climate mean and variance? Methods – Assess stress test with data – Robustness analysis Outputs – Understanding of sensitive climate variables – Understanding of confidence in data for decision making – Understanding system robustness

AGWA DSS - Strategies and Solutions Questions: – What type of solutions (i.e., non-structural vs. structural solutions) should be considered? – What type of economic tools are most appropriate for problem? – Did we define the problem correctly? Reiterate if necessary. Methods – Select appropriate tools and solutions based on (1) sensitive variables; (2) confidence in data for decision making; and (3) robustness of system. – Can use cost effectiveness, robustness, flexibility for future options to help select solutions.

International Upper Great Lakes Study (IUGLS)

International Joint Commission (IJC) More than a century of cooperation protecting shared waters Canada and the United States created the International Joint Commission because they recognized that each country is affected by the other's actions in lake and river systems along the border. The IJC is guided by the Boundary Waters Treaty, signed by Canada and the United States in The IJC seeks to prevent and resolve disputes regarding many of the lakes and rivers along the shared border of the two countries. This role includes approving the construction and management of works that affect levels and flows in boundary waters.

International Upper Great Lakes Study (IUGLS) The International Upper Great Lakes Study (IUGLS) examined a recurring challenge in the upper Great Lakes system: how to manage fluctuating lake levels in the face of uncertainty over future water supplies to the basin while seeking to balance the needs of those interests served by the system.

IUGLS Methods Methods to evaluate system performance – Observed record – Paleo-hydrology – Stochastic hydrology – Climate change projections: statistical downscaling and regional climate models Engagement with stakeholder groups to define coping ranges and failure thresholds 1.Domestic, municipal and industrial water uses; 2.Commercial navigation; 3.Hydroelectric generation; 4.Ecosystems; 5.Coastal zone; and, 6.Recreational boating and tourism.

IUGLS -Recommendations Best approach is to make decisions in such a way as to not overly rely on assumptions of particular future climatic and lake level conditions or specific model projections. Robustness – the capacity to meet regulation objectives under a broad range of possible future water level conditions – must be a primary attribute of any new regulation plan.

IUGLS -Recommendations An adaptive management strategy should be applied to address future extreme water levels in the Great Lakes-St. Lawrence River basin through six core initiatives: Strengthening hydroclimatic monitoring and modelling; Ongoing risk assessment; Ensuring more comprehensive information management and outreach; Improving tools and processes for decision makers to evaluate their actions; Establishing a collaborative regional adaptive management study for addressing water level extremes; and, Promoting the integration of water quality and quantity modelling and activities.

International Upper Great Lakes Study (IUGLS)

Elements of an Adaptive Management Strategy

Example: Coralville Flood Risk Management Analysis Coralville Lake

Spillway Events Lower Variability Basis of Design Increased Mean Greater Variability

Risk Assessment: Identify Risks Identify critical zones through stakeholder involvement Conduct stress test of system under various climate states Photo: Coralville Lake Dam – June 2008

Stress Tests Goal To identify system breaking points under various climate states Metrics Assessed – Flood Management: Return Period, Expected Annual Damages – Water Supply: Firm Yield, Reliability, Cost Approach Use weather generator to stochastically model rainfall occurrence, amount, and other climate fields

Stress Test: 100-yr Event for 15-Day Peak Flow

Non-Growing Season Growing Season Stress Test: 100-yr Event for 15-Day Peak Flow

Non-Growing Season Growing Season Risk Assessment Part II: Analyze Risks

Non-Growing Season Risk Assessment Part II: Analyze Risks Growing Season

2050 GCM Projections Risk Assessment Part II: Analyze Risks Non-Growing Season Growing Season

Potential Adaptation Options Buy out farmland in downstream floodplain. – Could allow increase in maximum reservoir release during the growing season to same as non-growing season, reducing summer flood risk. – Higher releases earlier during a flood event would result in more effective flood capacity. Expanded use of forecast tools in reservoir regulation. – Current regulation plans are rigid and were not designed to employ modern forecast products. – Operational flexibility would enable the system to adapt to changing and unexpected conditions.

Future AGWA Work Potential pilot studies to implement AGWA approach – Lake Oologah – water supply reservoir in United States – Thailand – Vietnam – Mongolia – CONAGUA consultation in September / DC – UNICEF consultation with 3 African countries (sub-Sahara Africa)

Thank you! Questions?

Climate Stress Test: Prescribed Climate Changes