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A Procedure for Combining Improved Correlated Sampling Methods and a Resampling Strategy to Generate a Multi-Site Conditioned Streamflow Process
- Source :
- Water Resources Management. 35:1011-1027
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- In this study, a new method is developed to generate multi-site streamflow series. First, a correlated sampling method based on spectral decomposition is employed to simulate a large number of individual years of multi-site streamflow series. Then, combined with historical design flood data, flood characteristic series considering historical floods are generated. Finally, a subset of the streamflow series corresponding to these flood characteristics is selected from the pool of multi-site simulated streamflow series. The proposed model is applied to multi-site streamflow simulations in the upper Yangtze River basin. Experimental results show that the simulated data not only ensure the fundamental statistical characteristics of the observed data, but also provide good preservation of high order self-dependent, cross-dependent at finer and coarser time scales with any marginal distributions and any correlation structures. In addition, the simulated extreme situations are more reliable for risk and vulnerability analysis of multi-reservoir joint operation systems due to the consideration of the historical design flood data.
- Subjects :
- Hydrogeology
010504 meteorology & atmospheric sciences
Series (mathematics)
Flood myth
0208 environmental biotechnology
02 engineering and technology
Structural basin
01 natural sciences
020801 environmental engineering
Matrix decomposition
Streamflow
Resampling
Statistics
Environmental science
Marginal distribution
0105 earth and related environmental sciences
Water Science and Technology
Civil and Structural Engineering
Subjects
Details
- ISSN :
- 15731650 and 09204741
- Volume :
- 35
- Database :
- OpenAIRE
- Journal :
- Water Resources Management
- Accession number :
- edsair.doi...........889d454a98061c7f4ca01fd1500fae7d