Vol.33, NO.1, 2022
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Article Navigation >  Journal of Applied Meteorological Science  > 2022  >  33(1): 115-128
Pang Yishu, Zhang Jun, Qin Ningsheng, et al. Forecast model of interannual increment for summer runoff and its verification in the upper reaches of the Yangtze River. J Appl Meteor Sci, 2022, 33(1): 115-128. DOI:  10.11898/1001-7313.20220110.
Citation: Pang Yishu, Zhang Jun, Qin Ningsheng, et al. Forecast model of interannual increment for summer runoff and its verification in the upper reaches of the Yangtze River. J Appl Meteor Sci, 2022, 33(1): 115-128. DOI:  10.11898/1001-7313.20220110.
shu

Forecast Model of Interannual Increment for Summer Runoff and Its Verification in the Upper Reaches of the Yangtze River

DOI: 10.11898/1001-7313.20220110
  • 1.

    Sichuan Climate Center, Chengdu 610072

  • 2.

    Institute of Plateau Meteorology, CMA, Chengdu/Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province, Chengdu 610071

  • 3.

    Three Gorges Cascade Dispatching and Communication Center, Yichang 443000

  • 4.

    Chengdu University of Information Technology, Chengdu 610103

  • Received Date: 2021-06-24
  • Rev Recd Date: 2021-09-27
  • Publish Date: 2022-01-19
    Abstract
  • The upper reaches of the Yangtze River is the hydropower resources and flood control focus for the whole river. Summer is an important period for flood diversion operation and hydropower development. Therefore, the relationships between summer runoff, precipitation and surface air temperature are analyzed, and the precursory physical climate signals for the runoff in the upper reaches of the Yangtze River are analyzed. By optimal subset regression and some other statistical methods, an annual increment prediction model with multi climatic factors for the runoff is built. The results show that the runoff directly depends on total precipitation in the basin, and they both show a slow downward trend in the past 40 years with a prominent quasi biennial oscillation. Their temporal correlation coefficient (TCC) is 0.81, exceeding the significant level of 0.001. By contrast, the average temperature of the watershed shows a significant upward trend, while influents less on the amount of runoff. On interannual time scale, the decisive role of precipitation on runoff is more prominent, while the influence of average temperature further weakens. Based on physical mechanism analysis, 8 key climate preceding signals of runoff are selected. They are the Bay of Bengal monsoon and Australian High in winter, Indonesia Australia meridional wind shear, meridional position of the northern hemisphere polar vortex, Ural Mountain circulation, plateau monsoon and the temperature at high altitude basin in spring, and autumn sea level pressure dipole of the Indian Ocean. The prediction model for summer runoff built on these factors is tested by TCC, sign consistent rate (SCR), root mean square error (RMSE), absolute relative error (AE) and some other techniques. By the indication of test, fitting rate of the model is 0.81 during its modeling period from 1981 to 2015. In addition, SCR between the simulated and observed value is 77.1%, which is 100.0% for the abnormal years, and the RMSE is 0.57. After inversion calculation, TCC of the simulated with observed runoff is 0.66, exceeding the significant level of 0.001, and the average AE is 14.5%. In the post-test from 2016 to 2020, SCR and RMSE of the model are 80.0% and 0.99, respectively. The average AE of predicted runoff is 19.3%. Overall, the prediction accuracy of this model for summer runoff and its interannual variation characteristics of the upper reaches of the Yangtze River is more than 80%. Compared with the existing prediction models, prediction skills of this model are significantly improved, indicating a potential applicability.
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    References(58)

  • Fig. 1  Distribution map of meteorological observation stations (the black dot) and Cuntan, Wulong and Yichang hydrological observation stations (the red triangles) in the upper reaches of the Yangtze River

    (the gray thick solid line is the boundary of the upper reaches of the Yangtze River, the blue solid lines are for rivers)

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    Fig. 2  The homogeneity test result T of summer runoff series of upper reaches of the Yangtze River from 1980 to 2013 (the dashed line denotes 0.1 significant level) (a) and the absolute relative error of summer runoff between Yichang hydrological station and Three Gorges Reservoir from 2003 to 2013

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    Fig. 3  Anomalies of elements in the upper reaches of the Yangtze River in summer from 1980 to 2020 (a)runoff, (b)precipitation, (c)average temperature

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    Fig. 4  Correlation coefficient of annual increment between precipitation in the upper reaches of the Yangtze River in summer and meteorological elements field from 1981 to 2015 (the contour)

    (the shaded denotes significant level)
    (a)meridional wind shear between 850 hPa and 200 hPa in spring, (b)sea level pressure in preceding autumn

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    Fig. 5  Correlation coefficient of annual increment between summer precipitation in the upper reaches of the Yangtze River and meteorological elements field from 1981 to 2015

    (a)Q1 (the shaded is significant level), (b)vortex (the shaded is significant level), divergence (the contour) and wind vector (the arrow) at 600 hPa

    DownLoad: Full-Size Img PowerPoint

    Fig. 6  Correlation coefficient of annual increment between meteorological elements from 1981 to 2015

    (the shaded denotes significant level)
    (a)height at 500 hPa in spring and precipitation in the upper reaches of the Yangtze River in summer, (b)EUI in spring and 500 hPa height, water vapor of the whole layer in summer, (c)EUI in spring and 500 hPa vertical velocity in summer

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    Fig. 7  Correlation coefficient (the contour) of annual increment between the Northern Hemisphere polar vortex central latitude index in spring and 500 hPa height in summer from 1981 to 2015

    (the shaded denotes significant level)

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    Fig. 8  Correlation coefficient of annual increment of Australian High index in the the preceding winter between meteorological elements in summer from 1981 to 2015

    (a)sea level pressure (the shaded denotes significant level) and wind at 925 hPa, (b)500 hPa height (the shaded denotes significant level) and the water vapor of the whole layer

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    Fig. 9  The simulated and observed standardized annual increment of runoff(a) and runoff(b) in the upper reaches of the Yangtze River in summer from 1981 to 2015

    DownLoad: Full-Size Img PowerPoint

    Fig. 10  The observed and forecasted value by the prediction model for annual increment of summer runoff in the upper reaches of the Yangtze River from 2016 to 2020

    (a)standardized annual increment and its root mean square error, (b)runoff and its absolute relative error

    DownLoad: Full-Size Img PowerPoint
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    • Received : 2021-06-24
    • Accepted : 2021-09-27
    • Published : 2022-01-19
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