Key Laboratory of Northwest Water Resources and Environmental Ecology of MOE at XAUT

Fengcheng, China

Key Laboratory of Northwest Water Resources and Environmental Ecology of MOE at XAUT

Fengcheng, China
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Qi Q.,Key Laboratory of Northwest Water Resources and Environmental Ecology of MOE at XAUT | Qi Q.,North China University of Water Conservancy and Electric Power | Shen B.,Key Laboratory of Northwest Water Resources and Environmental Ecology of MOE at XAUT | Lv J.,Key Laboratory of Northwest Water Resources and Environmental Ecology of MOE at XAUT | Zhang Z.,North China University of Water Conservancy and Electric Power
Shuili Fadian Xuebao/Journal of Hydroelectric Engineering | Year: 2013

Affected by climate changing, the hydrological time series in the upper Yellow River high cold region demonstrate persistent, volatility and other non-stationary features. Conditional heteroskedasticity (ARCH effect) exists in these hydrological time series, which leads to an increase in the risk and uncertainty of modern water resources management. In this paper, we use 54-years time series of monthly runoff data recorded at the Jimai hydrological station to study the characteristics and origin of such heteroscedasticity and its effect on regional water resources management. And we develop a hydrological process prediction model that can reduce the ARCH effects and improve prediction accuracy. This model would provide a reliable basis for regional water resources management. © right.


Lv J.,Key Laboratory of Northwest Water Resources and Environmental Ecology of MOE at XAUT | Shen B.,Key Laboratory of Northwest Water Resources and Environmental Ecology of MOE at XAUT | Shao N.,Key Laboratory of Northwest Water Resources and Environmental Ecology of MOE at XAUT | Dong K.,Hotan Survey Bureau of Hydrology and Water Resources | Li K.,Key Laboratory of Northwest Water Resources and Environmental Ecology of MOE at XAUT
Shuili Fadian Xuebao/Journal of Hydroelectric Engineering | Year: 2012

To better understand the evolution modes and self-memory characteristics of the Yellow River annual runoff, a gray self-memory prediction model is developed by using empirical mode decomposition theory. A auto-correlation function is adopted to define the backdate orders of this model to improve its accuracy. The results show that the runoff series at Huayuankou gauge can be decomposed into seven intrinsic mode functions (IMF) and a tendency function. Since 1965 the evolution modes and periodicity of runoff series has changed under the influences by water resources development and climate change in this river basin. © right.


Lv J.,Key Laboratory of Northwest Water Resources and Environmental Ecology of MOE at XAUT | Zhang X.,Key Laboratory of Northwest Water Resources and Environmental Ecology of MOE at XAUT | Zhang X.,China Water Resources Pearl River Planning Surveying and Designing Co. | Shen B.,Key Laboratory of Northwest Water Resources and Environmental Ecology of MOE at XAUT | Huang L.,Key Laboratory of Northwest Water Resources and Environmental Ecology of MOE at XAUT
Shuili Fadian Xuebao/Journal of Hydroelectric Engineering | Year: 2010

This paper analyzes the variation trend and primary driving factors of the annual runoffs in the Hotan oasis by adopting the moving average method, progressive average method, Spearman rank correlation coefficient method, de-trended fluctuation analysis (DFA), rescaled range (R/S) analysis and Husdorsff fractal dimension method. Results indicate a fractal dimension and a trend of no significant increasing in the Hotan oasis runoff sequence. During the period of 2000-2007, the runoff showed a short-term increase that is primarily resulted from temperature rising. © Tsinghua University Press.

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