Download International Upper Great Lakes Study (IUGLS)

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts
no text concepts found
Transcript
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
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
Source: Wilby & Dessai, 2010, Weather
Traditional approaches amplify
or hide 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: 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
1. Downscale
climate model
projections
decision-scaling risk
assessment
3. Assess plausibility and
test vulnerability
2. Estimate shifts
in water supply
3. Determine
system responses
to changes in these
variables
2. Assemble multiple
climate data sources and
link to breaking points
1. Define your system’s
breaking points
Weaver et al., 2012, WIREs Climate Change
USACE,
UMass
CI, IDB,
USACE, WWF
hydrology &
climate science
finance &
economics
World Bank, SIWI,
EIB, OECD
governance
ELI, DoS, Pegasys
ecology &
engineering
AGWA
DSS
Software development: SEI,
Hydrology.nl, UMass,
ULoughborough
Risk-Informed Decision Making
Analyze Risks
Evaluate Risks
Monitor, Evaluate, Modify
Identify Risks
Risk Assessment
Consult, Communicate and
Collaborate
Establish Decision Context
Risk Mitigation
Adapted from ISO 31000- Risk Management—Principles and Guidelines
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 1909.
• 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.
2.
3.
4.
5.
6.
Domestic, municipal and industrial water uses;
Commercial navigation;
Hydroelectric generation;
Ecosystems;
Coastal zone; and,
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
Coralville Lake
15-Day Peak Inflow
35,000
Spillway Events
30,000
25,000
Flow (cfs)
Lower Variability
Basis of Design
Increased Mean
Greater Variability
20,000
15,000
10,000
5,000
0
1900
1910
1920
1930
1940
1950
1960
1970
1980
1990
2000
2010
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
Stress Test:
100-yr Event for 15-Day Peak Flow
Non-Growing
Season
Growing
Season
Risk Assessment Part II:
Analyze Risks
Non-Growing
Season
Growing
Season
1951-1980
Risk Assessment Part II:
Analyze Risks
Non-Growing
Season
1981-2010
1951-1980
Growing
Season
Risk Assessment Part II:
Analyze Risks
2050 GCM
Projections
Non-Growing
Season
1981-2010
1951-1980
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?
[email protected]
Climate Stress Test: Prescribed Climate Changes