Abstract. The problem is to find the monthly operating policy of Hydro-Qudbec's 26 large reservoirs that maximizes the utility's expected profits over a period of several years. The problem is solved in a hierarchical way. First, the optimal operating policy of the whole system, represented by an aggregate model, is found by stochastic dynamic programming (SDP). This gives not only the hydroelectric energy to produce in a month but also, as is very important in a deregulated market, the expected marginal value of the hydroelectric energy produced. At the second level the expected marginal value of the potential energy stored in each river is determined by solving a SDP problem with two state variables: one for the energy content of the river and the other for the energy content of all the other rivers combined. These marginal values are used afterward to divide the hydroelectric production among the rivers. At the third level the production assigned to each river is distributed between the reservoirs so as to minimize the spillages first, and then the square of the deviations of the reservoir levels from the target level. The targets are adjusted to maximize the expected long-term production of the river. The monthly inflows to the reservoirs are the only random variables in this problem. IntroductionThis paper tackles the problem of determining a monthly releasing policy for Hydro-Qufibec's 26 seasonal and interannual reservoirs over a period of several years. The objective is to find a policy that maximizes the utility's profits while respecting all constraints. The policy must absolutely take into account the random behavior of the reservoir inflows, since these cannot be predicted long in advance and since they vary widely throughout the year. Ideally, the randomness of electricity demand should also be taken into account, but since a probability distribution cannot be obtained for future demand, we suppose that demand is known for the whole period and equal to the most probable scenario.The problem is not stationary, even though the inflows are on an annual basis, because electricity demand increases every year and new power plants must periodically be added to meet it. Whatever the investments made, however, we cannot, in a stochastic environment, guarantee that demand will be met all the time. At best, we can guarantee that demand will be met with a certain probability. The choice of a probability is not obvious, though, because it must take into account, on the one hand, the investment that will have to be made to meet it and, on the other, the losses incurred by the customers when demand is not met. Rather than trying to determine this probability, Hydro-Qufibec has chosen to build, from information gathered from its customers, a curve representing the economic and social costs of a shortage in terms of the number of gigawatt hours (GWh) not supplied in a month. This shortage cost curve is used in our model to penalize shortages.Copyright 1998 by the American Geophysical Union. Paper number 98WR02608.00...
Food pathogenic bacteria including Listeria monocytogenes (1A1 and ATCC 19111), Staphylococcus aureus (GD13 and ATCC 13565), Escherichia coli O157:H7 (ATCC 35150), Salmonella typhimurium, Yersinia enterocolitica, Vibrio parahaemolyticus, and Campylobacter jejuni were exposed to various rates of ionizing radiation (0.78, 2.6, and 22 kGy/h) emitted by three different 60Co irradiators. D10 values (D10 is the radiation dose required to eliminate 90% of a bacterial population (one logarithmic cycle reduction)) were calculated for the various strains and growth conditions tested. A covariance analysis of these results revealed that the dose rates studied had no significant influence on the radiosensitivity of these bacteria. At all dose rates, the bacteria were more radiosensitive when irradiated in a saline solution (0.85% NaCl) than in a chicken breast meat suspension. The growth phase of the bacterial population had a variable influence on its radioresistance. For L. monocytogenes 1A1, Staphylococcus aureus ATCC 13565, E. coli O157:H7, Y. enterocolitica, and V. parahaemolyticus, radioresistance was not significantly different in the exponential and stationary phases. Populations of L. monocytogenes ATCC 19111 and Staphylococcus aureus GD13 were significantly more resistant in the stationary phase (D10 = 0.23 and 0.12 kGy, respectively) than in the exponential phase (D10 = 0.17 and 0.09 kGy, respectively). Among the pathogenic bacteria investigated in this study, the most radioresistant was L. monocytogenes (D10 = 0.16-0.38 kGy, Gram-positive bacilli) and the most radiosensitive was V. parahaemolyticus (D10 = 0.03-0.04 kGy, halophilic Gram-negative bacilli).
Because the CEQUEAU hydrophysiographic model is able to simulate natural or modified discharges simultaneously in time and space, it is suited to multiple applications. By using such a model, one can study the hydrological repercussions, all over a basin, resulting from natural or man-made modifications to its characteristics. For instance, the various effects originating from the site, type and characteristics of intended dams (flood control, diversion, storage, etc.) can be simulated with satisfaction. Moreover, the model provides the basic hydrological data required for design purposes. The effect of deforestation on floods produced by snowmelt can be simulated at any point in a basin. Flood risk mapping is also an application for which the model can be very useful. * Due to space limitation only the first part of the paper is published here. The second and third parts on Program organization and Examples of the use of the model in problems related to water resource management have been omitted. The full paper can be obtained from the authors in either English or French.
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