Improving multi-objective ecological flow management …€¦ · Improving multi-objective...
Transcript of Improving multi-objective ecological flow management …€¦ · Improving multi-objective...
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Improving multi-objective ecological flow management with flexible priorities and turn-taking
February 9, 2017
Clint Alexander
Technologies
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BalancingMultiple Objectives
Coupled Flow‐ecology
Modelling
Turn‐taking to Boost Solution Space
Real‐Time Decision‐Support
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You can’t always get
what you want!
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Sacramento River Basin & San Francisco Bay-Delta “Family”
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Sacramento River Basin and San Francisco
Bay-Delta estuary
California
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• Limited flexibility• Complex layers of rules and regulations• ESA & BiOps generate “winners and losers”
• Sacramento River - simplistic flow targets• Min. flow targets; no high flow targets• Few ramping rate targets• Flow as proxy for desired outcome (e.g. spawning habitat)
• Considers only a few solutions• Effects analysis modelling, State Water Board hearings, law suits• Establishes set of relatively static priorities, decided in advance• No one really evaluating larger number of alternative flow mgmt. regimes • Disconnected tools brought together in somewhat ‘Rube Goldberg’ fashion• Many trade-offs are poorly balanced through time
The Problem:Rigid Water Management Regimes
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Coupled Flow-Ecology Modelling – The Ecological Flows Tool
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1 decision support platform
13 Species 25 indicators
Spawning Success
Index
Habitat Suitability
Index
Entrainment Risk Index
Delta Smelt
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Applications “EFT captures current knowledge in one place,
builds community knowledge and is a great
example of a decision support tool to reflect trade-
offs in a very transparent manner. EFT is a great
example tool for collaborative science”
~ Dr. Peter Goodwin, former Lead Scientist of the Delta
Science Program
Google ‘Research Gate Clint Alexander’
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Coupled modelling
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Input data (e.g. temperature, salinity) drive models at representativelocations and dailytimescale
Model content and complexity depend on state of scientific knowledge (e.g. peer literature, expert input)
Conceptual Models linked to driving variables
• 70 locations defined in the Sacramento River ecoregion; representing points, segments and bends, depending on the Indicator.
• Additional 67 locations defined in the Delta ecoregion, representing points, segments, routes and regions, depending on the Indicator.
• Indicator models at these locations are driven by daily or sub‐daily data: flow, temperature, salinity, and stage, depending on the Indicator.
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Persistent conflicting trade-offs…
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From “What-if” to Turn-Taking Optimization (TTO)
Boosting solution space
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What Does Turn-Taking Look Like?Tu
rn-T
akin
g Op
timiza
tion
Busin
ess A
s Usu
al
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Business As Usual
Year
Management Priority Species Status
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Turn-Taking Optimization
Year
Management Priority Species Status
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Commercial Cloud Cost-Effective
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Ecological Results ofTurn-Taking
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Insufficient emphasis on real-
time decision support tools for
ecosystems
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Real-time Decision Making Requiredto Achieve these Benefits
• Multi-species benefits requires real-time decision support• Mental arithmetic too tough• Need automated real-time tools
…that track recent history & conditions…w automated TTO computation to narrow solutions …w data visualizations that clearly present equally ‘optimal’ trade-offs
• Pair with adaptive management experiments to continuously learn
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Take Home Points
No single best way to operate a
water system
New TTO approach brings more flexibility, more solutions
Move away from winners/losers
approach
Need greater emphasis on
real-time operational tools
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More Information• Publication coming soon!Improving multi-objective ecological flow management with flexible priorities and turn-taking: a case study from the Sacramento River Basin and San Francisco Bay‒Delta estuary, San Francisco Estuary and Watershed Science, in prep.
• EFT tech. report & software: essa.com/tools/ecological-flows-tool/
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Clint Alexander Ryan [email protected] [email protected](250) 808-2654 (530) 518-4490