scholarly journals Annual runoff prediction in the source area of the Yellow River based on structure change co-integration theory

2020 ◽  
Vol 20 (5) ◽  
pp. 1664-1677
Author(s):  
Jinping Zhang ◽  
Hongbin Li ◽  
Bin Sun ◽  
Hongyuan Fang

Abstract Aiming at revealing the co-integration under structural change in the long-run relationship between rainfall and runoff time series at Tangnaihai Hydrological Station in the source area of the Yellow River, and improving the accuracy of annual runoff prediction, co-integration theory and structure change co-integration theory are introduced respectively. The error correction models of rainfall and runoff in these two cases are constructed. The results show that reservoir construction and climate change can cause structure change in the long-run relationship between rainfall and runoff in the source area of the Yellow River. The breakpoints appeared in 1989 and 2002, in which the breakpoint in 1989 is mainly effected by reservoir construction while in 2002 it is effected by rainfall changes. Meanwhile, the error correction model with structural change shows that the impact of rainfall on runoff decreases from 1989 but increases from 2002. Finally, for the prediction of runoff in the next five years, the mean absolute percentage errors of the prediction models without and with breakpoints are 11.04% and 7.08% respectively, and this shows that the error correction model with structural change has the higher runoff prediction accuracy.

Author(s):  
Jinping Zhang ◽  
Hongbin Li ◽  
Bin Sun ◽  
Hongyuan Fang

Abstract In order to reveal the multi-time scale of rainfall, runoff and sediment in the source area of the Yellow River and improve the accuracy of annual runoff forecast, the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) method is introduced to decompose the measured rainfall, runoff and sediment data series of the Tangnahai hydrological station in the source area of the Yellow River of China. With the co-integration theory, two new error correction models (ECMs) for the forecast of annual runoff in the source area of the Yellow River are constructed. The application of these two methods solves the problem of pseudo-regression caused by nonlinearity and non-stationary of hydrological time series. The results show that rainfall, runoff and sediment in the source area of the Yellow River have multi-time scales and the component sequences have co-integration relationships. For two new ECMs, the CEEMDAN component ECM has better forecast accuracy than the original sequence one. The relative error of all forecasted values is less than 15% except 2009, and the accuracy has reached level A.


Author(s):  
Dongying Yi ◽  
Yue Xu ◽  
Nan Wang ◽  
Xiaoyi Ma

The primary approach to realizing long-term runoff prediction involves combining a hydrological model with general circulation model. Previous studies on the Source area of the Yellow River were all based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) data sets with defects in physical mechanisms. In this paper, the Beijing Climate Center Climate System Model (BCC-CSM2-MR) of CMIP6, which proved to perform well in arid and semi-arid regions, will be used to drive the Soil & Water Assessment Tool (SWAT) model and evaluate its applicability in runoff simulation at Tang Nahai Hydrological Station from 2011 to 2019. The occurrence of the extreme value of runoff, its change trend, and the year of abrupt change of runoff in the four Shared Socio-economic Pathway (SSP) scenarios (SSP1-2.6, 2-4.5, 3-7.0, and 5-8.5) during 2021-2100 were analyzed. The results show that: (1) the runoff simulation evaluation index of SWAT driven by BCC-CSM2-MR in the research area from 2011 to 2019 is excellent, and the runoff simulation in the future is reliable and effective. (2) only the average annual runoff in scenario 5-8.5 (708.5m /s) from 2021 to 2100 was significantly higher than that in 2011-2019. Other scenarios are close to or less than the annual runoff observed. Most importantly, the maximum and minimum annual runoff values under the four scenarios all occurred during 2060-2080, so the attribution analysis of runoff extremum during 2060-2080 is worth further study. (3) it is necessary to evaluate whether the existing reservoirs and hydropower stations in the Yellow River basin can reasonably regulate and utilize the annual runoff under scenario 5-8.5.


Authorea ◽  
2019 ◽  
Author(s):  
Jinping Zhang ◽  
Hongbin Li ◽  
Qiting Zuo ◽  
Hongyuan Fang ◽  
Yang Hong

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 509
Author(s):  
Jingwen Wu ◽  
Haiyan Zheng ◽  
Yang Xi

Runoff in snowy alpine regions is sensitive to climate change in the context of global warming. Exploring the impact of climate change on the runoff in these regions is critical to understand the dynamics of the water cycle and for the improvement of water resources management. In this study, we analyzed the long-term variations in annual runoff in the headwaters region of the Yellow River (HRYR) (a typical snowy mountain region) during the period of 1956–2012. The Soil and Water Assessment Tool (SWAT) with different elevation bands was employed to assess the performance of monthly runoff simulations, and then to evaluate the impacts of climate change on runoff. The results show that the observed runoff for the hydrological stations at lower relative elevations (i.e., Maqu and Tangnaihai stations) had a downward trend, with rates of 1.91 and 1.55 mm/10 years, while a slight upward trend with a rate of 0.26 mm/10 years was observed for the hydrological station at higher elevation (i.e., Huangheyan station). We also found that the inclusion of five elevation bands could lead to more accurate runoff estimates as compared to simulation without elevation bands at monthly time steps. In addition, the dominant cause of the runoff decline across the whole HRYR was precipitation (which explained 64.2% of the decrease), rather than temperature (25.93%).


2019 ◽  
Vol 11 (3) ◽  
pp. 865-876 ◽  
Author(s):  
Xianqi Zhang ◽  
Wei Tuo ◽  
Chao Song

Abstract The prediction of annual runoff in the Lower Yellow River can provide an important theoretical basis for effective reservoir management, flood control and disaster reduction, river and beach management, rational utilization of regional water and sediment resources. To solve this problem and improve the prediction accuracy, permutation entropy (PE) was used to extract the pseudo-components of modified ensemble empirical mode decomposition (MEEMD) to decompose time series to reduce the non-stationarity of time series. However, the pseudo-component was disordered and difficult to predict, therefore, the pseudo-component was decomposed by ensemble empirical mode decomposition (EEMD). Then, intrinsic mode functions (IMFs) and trend were predicted by autoregressive integrated moving average (ARIMA) which has strong ability of approximation to stationary series. A new coupling model based on MEEMD-ARIMA was constructed and applied to runoff prediction in the Lower Yellow River. The results showed that the model had higher accuracy and was superior to the CEEMD-ARIMA model or EEMD-ARIMA model. Therefore, it can provide a new idea and method for annual runoff prediction.


2018 ◽  
Vol 246 ◽  
pp. 01089
Author(s):  
Yongqiang Wang ◽  
Zhiming Liu ◽  
Zhe Yuan ◽  
Jijun Xu ◽  
Jin Chen

Taking the source region of the Yellow River as an example, this paper first introduces the theory of energy value and its basic steps. Then combined with the Yellow River source area, the variation characteristics of precipitation and surface water resources from 1961 to 2011 in the Yellow River source area were analyzed, and both of them showed a trend of decreasing year by year. On this basis, using the theory of energy value, combined with relevant parameters, taking 2011 year as an example, further analyses the chemical energy and solar energy of water resources in the Yellow River source area, and gives the value of surface water resources. The value of water resources per unit is 1.59 yuan/m3. For the Yellow River source area, the overall value of water resources for the whole basin in 2011 is 33.55 billion yuan. It can provide a reference for the analysis of the value of surface water resources in the Yellow River Basin.


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