Article ID: | iaor2005329 |
Country: | United States |
Volume: | 129 |
Issue: | 3 |
Start Page Number: | 165 |
End Page Number: | 177 |
Publication Date: | May 2003 |
Journal: | Journal of Water Resources Planning and Management |
Authors: | Westphal K.S., Vogel R.M., Kirshen P., Chapra S.C. |
Keywords: | artificial intelligence: decision support |
Recent advances in computer technology and water resource modeling, availability of real-time hydroclimatic data, and improvements in our ability to develop user-friendly graphical interfaces have led to significant growth in the development and application of decision support systems (DSSs) for water resource systems. This study provides an example of the development of a real-time DSS for adaptive management of the reservoir system that provides drinking water to the Boston metropolitan region. The DSS uses a systems framework to link watershed models, reservoir hydraulic models, and a reservoir water quality model with linear and nonlinear optimization algorithms. The DSS offers the ability to optimize daily and weekly reservoir operations toward four objectives based on short-term climate forecasts: (1) maximum water quality, (2) ideal flood control levels, (3) optimum reservoir balancing, and (4) maximum hydropower revenues. Case studies document the value of the DSS as an enhancement of current rule curve operations. The study shows that simple tools, in this case, familiar spreadsheet software, can be used to improve system efficiencies.