Optimization of storage reservoir considering water quantity and quality

• Published in: Hydrological processes Vol. 17; no. 14; pp. 2769 - 2793
• Main Authors: Chaves, Paulo, Kojiri, Toshiharu, Yamashiki, Yosuke
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 15.10.2003
• Subjects: Barra Bonita reservoir; dynamic programming; fuzzy theory; genetic algorithm; multiobjective optimization; water quality model; UNEP
• ISSN: 0885-6087; 1099-1085
• DOI: 10.1002/hyp.1433

Many factors influence water quality within a reservoir. Deforestation, excessive erosion, introduction of new species, domestic and industrial waste disposal and agricultural runoff are only a few examples. It is well known by specialists in water resources management that water levels in a reservoir may also affect its quality. But how these processes occur and how appropriate water levels can be maintained are very hard questions to answer. This is because of the physical and biological processes occurring inside the water body, and also due to the various demands from society concerning water uses. Nowadays, through the use of models, knowledge of some of the conditions can enable us to predict future conditions. In many cases, reservoir models, such as physical models for water quality, may predict the future water quality situation. These models have been used successfully to enhance knowledge about the interactions among the different parts inherent to the water systems. Through the combination of water quality and optimization models, this study proposes a suitable methodology for the assessment of planning operations of a storage reservoir. The purpose of this paper is to consider a multipurpose reservoir, under different water demands and uses from societies, concerning reservoir water quality. The proposed optimization is realized through the use of dynamic programming combined with stochastic techniques that can handle the probabilistic characteristics of inflow quantity and quality. For the water quality assessment, the UNEP/ILEC one‐dimensional model with two layers called PAMOLARE is applied. Finally, sensitivity analysis is carried out using a genetic algorithm model. Copyright © 2003 John Wiley & Sons, Ltd.