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Optimized Management for Flood Control and Irrigation Demand Satisfaction for Lake Como

Author(s): Tewelde Hagos Gebremedhin; Paolo Colosio; Marco Peli; Hien Nguyen Thi; Yen Nguyen Hai; Stefano Barontini; Roberto Ranzi

Linked Author(s): Paolo Colosio, Marco Peli, Stefano Barontini, Roberto Ranzi

Keywords: Water resources management; Reservoir optimization; Flood control

Abstract: The current management of water resources is expected to be severely impacted due to climate change, rapid development of urbanization, and population growth. The management of multi-purpose reservoirs often involves several competing interests. Therefore, the need to re-evaluate the current management rules is fundamental for the optimization of the objectives, reduction of water stress and mitigation of climate change impacts. Lake Como is the third largest lake in Italy, receiving water from the upper Adda River and regulated downstream by the Olginate dam. The regulation dam has been constructed in order to manage the outflow according to the water demand of the seven downstream canals and the hydropower plants. Moreover, it regulates the water level in the Lake to prevent flooding in the town of Como and to maintain the lake level above a certain threshold to allow navigation and for environmental reasons. Here, we focus our attention in optimizing the two conflicting objectives of irrigation demand satisfaction (parametrized by α, the ratio between the actual lake outflow and the agricultural demand) and flood control (parametrized by β, the ratio between the actual and the maximum allowed water level). We apply a deterministic optimization method called min-max approach. It is based on the determination of the minimum water level required to satisfy the irrigation demand and the maximum water level to avoid flooding over the entire year. This approach is based on a set of 71 years of inflow timeseries, from 1946 (year of the construction of Olginate Dam) to 2016, to simulate the continuity equation of the reservoir to compute such minimum and maximum water levels. Accordingly, we use a set of outflows of the same reference period in order to estimate the historical efficiency of the system in terms of α and β. Among all the possible combinations of α and β, we look for the so-called efficient solutions or Pareto solutions (improving α would worsen β, and vice versa). Together with the maximum and minimum water level, we evaluate three possible operating rules based on the solutions of α and β problems with different combinations of α and α by means of a trade-off analysis. The first tends to approach historical average levels (BAUL: Business As Usual Level); the second approaches the historical average releases (BAUR: Business As Usual Release); a third one allows to modulate the releases with the parameter delta (0< δ <1), which tends to satisfy irrigation demand (δ=0) or flood control (δ=1). This study shows that the current operating rule can be substantially improved with respect to both objectives, with an improvement of 19% in terms of irrigation demand satisfaction and of 69% in terms of flood control.


Year: 2022

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