GAR(1)入流时水库库容均值的计算机模拟及近似表达式

N. Hung, Tran Quoc Chien
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引用次数: 1

摘要

研究了独立和一阶依赖正常流入的库容。除了正态分布外,还发现年流量遵循伽马分布[4],[11],因此考虑这种情况是有用的。在Phien[10]的工作中,假定流入遵循gamma分布,并解析导出了范围(或存储容量)的平均值,并与他早期研究中通过蒙特卡罗实验得到的经验公式进行了很好的比较。本文考虑了水库库容的分布,其中流入假定遵循gamma变量的一阶自回归模型,即GAR(1)模型。通过计算机模拟的方法,生成年流入,然后在给定的水库寿命n(以年为单位)下,得到部分和和范围的数据。通过理论分析,导出了GAR(1)变量和方差的封闭形式公式。然后将该公式与Phien[10]经验公式结合使用,得到水库库容均值的近似表达式。由近似表达式计算出的结果可以很好地与从生成数据中得到的结果进行比较。这意味着所得到的近似表达式可用于确定实际中发现的GAR(1)模型参数任意值的平均范围(或平均水库容量)。
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Computer simulation and approximate expression for the mean range of reservoir storage with GAR(1) inflows
Reservoir storage capacity has been investigated for independent and first-order dependent normal inflows. Besides the normal distribution, annual streamflows have also been found to follow the gamma distribution[4],[11] it is then useful to consider this situation. In the work of Phien[10], the inflows are assumed to follow the gamma distribution, and the mean value of the range (or the storage capacity) was derived analytically, and compared very well with the empirical formula obtained from Monte Carlo experiments in his earlier study. This paper considers the distribution of the storage capacity of reservoirs where the inflows are assumed to follow the first-order autoregressive model for gamma variables, denoted GAR(1) model. By means of computer simulation method, the annual inflows are generated, then the data for the partial sums and range are obtained for any given value of n, the life time (in years) of the reservoir under consideration. By theoretical analysis, a closed form formula for the variance of the sum of GAR(1) variables is derived. This formula is then used along with the empirical formula of Phien[10] to obtain an approximate expression for the mean value of the reservoir storage. The results computed from the approximate expression can be compared very well with those obtained from generated data. This means that the approximate expression obtained can be used to determine the mean range (or mean reservoir capacity) for any value of the parameters of the GAR(1) model found in practice.
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