Adaptive Water Operations and Planning Decision Support Using Reliability-Based Global Optimization and HydroGeoSphere Integrated Hydrologic Model

Project ID: 1010
Principal Investigator: George Matanga
Research Topic: Water Operation Models and Decision Support Systems
Priority Area Assignments: 2012 (Climate Adaptation), 2013 (Climate Adaptation)
Funded Fiscal Years: 2011 and 2012
Keywords: None

Research Question

The question posed in this Research and Development (R&D) project is whether decision support tools utilizing global optimization, stochastic simulations, and integrated hydrologic modeling can be developed and can help water managers objectively select the best strategy for managing water-resource system operation/planning while coping with complex hydrology, uncertainties, and regulatory/physical constraints.

Need and Benefit

Water managers traditionally make decisions on water system operations and planning based on their experience, consideration of a limited number of decision alternatives, and a few scenarios of future conditions (such as water availability, water demand, and weather). In addition, such decisions are typically made on an administrative schedule, instead of adaptively as new information is collected.

Recently, simulation-optimization tools are beginning to be available to water managers. Numerical models have increasingly been used to simulate the outcome of different water management strategies. Most of these existing tools are limited to simple hydrologic models and linear programming, and they do not have the flexibility to deal with nonlinearity of the objective functions. In addition, these tools were developed in a deterministic framework and do not consider the uncertainty in the model parameters or operational and regulatory constraints. Hydrologic systems are complex. Our knowledge of such systems is always incomplete, and our predictions of future circumstances are inherently uncertain. It is almost certain that future events will not happen exactly as assumed in these models and scenarios. An optimal solution computed for the assumed condition might not even be suboptimal in reality. Therefore, decision support tools are needed to assist water managers in assimilating water resources data, simulating the response of surface water/ground water systems, coping with uncertainties, and making optimal decisions.

The end product of the proposed research will be a robust tool for water managers to:

1. Account for uncertainties associated with model parameters, forecasting of hydrologic events, water supplies, and water demands; and

2. Reduce subjectivity in making decision under constraints and conflicting objectives.

The developed tool will provide an integrated framework for building, evaluating, and communicating the net impact of their decisions to different stakeholders.

Contributing Partners

Contact the Principal Investigator for information about partners.

Research Products

Not Reviewed

The following documents were not reviewed. Statements made in these documents are those of the authors. The findings have not been verified.

Adaptive Water Operations and Planning Decision Support Using Reliability-Based Global Optimization and Integrated-Hydrologic HydroGeoSphere Model (final, PDF, 378KB)
By George Matanga
Report completed on May 12, 2014

Recently, simulation-optimization tools have become available to water source managers for optimal and cost-effective management of the resources. Furthermore, physically-based numerical models are increasingly being applied to simulate the outcome of different water management strategies . Most of these simulation and optimization tools are limited to simple hydrologic models and linear-programming optimization models and do not have the flexibility to deal with non-linearity of the object

Adaptive Water Operations and Planning Decision Support Using Reliability-Based Global Optimization and Integrated-Hydrologic HydroGeoSphere Model (final, PDF, 378KB)
By George Matanga
Report completed on May 12, 2014

The purpose of this research project was to link HydroGeoSphere numerical model with a Differential Evolution (DE) optimization model. Tasks 1, 2, 3, 8a and 8c of the research project was contracted to AMEC GEOMATRIX, INC (AMEC) and the Principal Investigator George Matanga was responsible for Tasks 4, 5, 6). Task 7 is currently not being executed. It is also noted that Task 8c replaces Task 8b. On December 31, 2012 AMEC will submit a final report to the Principal Investigator documenting the wo


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Last Updated: 6/22/20