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The Upper Rio Grande. 1 2 5 3 6 4 8 7. 23.55 19.34 16.2 326.9 4.1 9.8 0.34 101.9. Weights/Penalties. Multi-objective River and Reservoir System Modeling. Water Supply. Navigation. Priorities. Water Quality. Flood Control. Aquatic/Riparian Habitat. Recreational Flows.
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1 2 5 3 6 4 8 7 23.55 19.34 16.2 326.9 4.1 9.8 0.34 101.9 Weights/Penalties Multi-objective River and Reservoir System Modeling Water Supply Navigation Priorities Water Quality Flood Control Aquatic/Riparian Habitat Recreational Flows Recreational Lake Levels Hydropower
RiverWare is a General River and Reservoir System Modeling Tool that Meets These Requirements: • Multiple Uses - operational scheduling, forecasting, planning • Multiple solution methodologies - simulation, rulebased simulation, optimization • Operating policy expressed as data – create, view, change policies; see effects of policy on operations
RiverWare is a General Reservoir and River System Modeling Tool that Meets These Requirements: • Easy to use – create complex physical process and policy models without writing computer code; point and click interface; Analyze results of model runs through GUI • Automatic Data Management Interface – import/export data from any source quickly • Extensible – add new features easily, reproduce results of old models • Supported / Maintained – new releases, user support, training
Object-Oriented Modeling Approach • Objects on Workspace Represent Features of the River and Reservoir System • Objects contain their own data • Objects contain their own physical process models • Objects know only about themselves - when they get a new value - how to use their data to simulate
Objects on the Palette and Their Methods • ReservoirsStorage (mass balance, release, spill) Power Reservoirs Level (+ tailwater, power, energy, eis) Sloped ( + wedge storage) Pumped Storage (+ pump/generators) • Confluence - mass balance • Canal - bi-directional gravity flow • River Reach - routing, water quality • AggDiversion Site - demands, consumption, return flow, available water • Water User - demands, consumption, return flow • Diversion - pumped or gravity diversion structure • Groundwater Storage - gw interaction for return flows, seepage, conjunctive use • AggDistribution Canal - calculates diversion schedules, routes flows • Stream Gage - input for river gage data; propagates flow value u.s. and d.s. • Thermal Object - economics of thermal power system • Data Object - user-specified data
Three Solution Approaches 1. Simulation models physical processes for a variety of input/output combinations (upstream/downstream; forward/backward in time) 2. Rulebased Simulation simulation driven by user-specified operating rules (policy) expressed through an interpreted language 3. Optimization linear goal programming solution
USBR Applications of RiverWare • Colorado River – CRSS, 24-month study (stakeholders) • Lower Colorado EIS • San Juan – daily operations, EIS with USGS, BIA • Yakima – planning model • Upper Rio Grande – URGWOM with COE, USGS • Pecos – EIS with NMISC • Gunnison – policy analysis for environmental issues with NPS • Truckee River – accounting and daily operations • Umatilla – with BIA
Areas of Ongoing USBR-funded R&D • Water Accounting/Water Rights modeling • Enhancement to Rulebased Simulation to facilitate developing policy sets • Continued new physical processes and basin features modeled • Post processing and data connections
Sharing Water: Towards a Transboundary Consensus on the Management of the Okavango Basin • Joint proposal by NHI and IUCN to develop and test a transparent decision-making model (WEAP) in the context of the Okavango Basin • Build regional capacity to manage complex transboundary river systems and apply conflict management tools • Develop a set of key parameters necessary to monitor ecological trends in the basin
Adaptive Management • Acting without knowing enough, and learning. • Important management tool • Acknowledges incomplete understanding • Iterative process
Adaptive Management: the Process • Define measurable goals and objectives • Develop a conceptual model • Generate hypotheses • Explicitly disclose assumptions and uncertainties • Develop numerical model(s) • Design management interventions • Implement interventionsMonitor, and analyze results • Adjust management interventions accordingly • Design new interventions
Lessons Learned • · Desired end conditions need to be clearly defined • ·Monitoring needs to be tied to specific goals • ·Our ignorance of ecosystems is uneven • ·Pragmatism is fundamental • ·“Battle of the Models” • ·Institutional Issues
Restoring Aquatic Ecosystems: Delivering on the Promise of Adaptive Management • Analyze successes and pitfalls associated with adaptive management • Provide focused attention to further adaptive management practices - Yolo By-Pass, San Joaquin Basin, the Guadalupe River, and the Russian River • Advance the ability of NHI to assist in implementing adaptive management approaches in aquatic restoration