Wavelet Transform Method for Synthetic Generation of Daily Streamflow
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- 作者：Wensheng Wang ; Shixiong Hu and Yueqing Li
- 关键词：Daily streamflow ; Synthetic generation ; Wavelet transform ; Decomposition and reconstruction
- 刊名：Water Resources Management
- 出版年：2011
- 出版时间：January 2011
- 年：2011
- 卷：25
- 期：1
- 页码：41-57
- 全文大小：430.6 KB
文摘
Synthetic generation of daily streamflow sequences is one of the most critical issues in stochastic hydrology. In this study, a new wavelet transform method is developed for synthetic generation of daily streamflow sequences. Firstly, daily streamflow sequences with different frequency components are decomposed into the series of wavelet coefficients W 1(t), W 2(t),...,W P (t) and scale coefficients (the residual) C P (t) at a resolution level P using wavelet decomposition algorithm. Secondly, the series of W 1(t), W 2(t),...,W P (t) and C P (t) are divided into a number of sub-series based on a yearly period. Thirdly, random sampling is performed from sub-series of W 1(t), W 2(t),...,W P (t) and C P (t), respectively. Based on these sampled sub-series, a large number of synthetic daily streamflow sequences are obtained using wavelet reconstruction algorithm. The advantages of this newly developed method include: (1) it is a nonparametric approach; (2) it is able to avoid assumptions of probability distribution types (Normal or Pearson Type III) and of dependence structure (linear or nonlinear); (3) it is not sensitive to the original data length and suitable for any hydrological sequences; and (4) the generated sequences from this method could capture the dependence structure and statistical properties presented in the data. Finally, a case study in Jinsha River, China, indicates that the new method is valid and efficient in generating daily streamflow sequences based on historical data.