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Forecast Model of Interannual Increment for Summer Runoff and Its Verification in the Upper Reaches of the Yangtze River
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摘要: 基于1980—2020年长江上游夏季径流量、降水和气温等资料, 采用小波分析、最优子集回归等方法, 分析径流量、降水量和气温的变化关系, 探讨引发径流量变化的前兆气候异常信号, 并构建径流量年际增量预测模型。结果表明: 径流量多寡直接取决于流域总降水量, 两者表现出显著的准两年周期振荡特征, 年际增量之间的相关系数(TCC)为0.88, 达到0.001显著性水平。流域平均气温对径流量变化影响相对较小。影响径流量变化的关键前兆气候信号为孟加拉湾冬季风、春季高原季风等8个气候特征量。所建模型在建模时段内(1981—2015年)的拟合值与观测值的TCC为0.81, 达到0.001显著性水平; 符号一致率(SCR)为77.1%, 在径流量变化异常年为100.0%;均方根误差为0.57。在2016—2020年的后报试验中, 模型预测与观测值的SCR为80.0 %, 均方根误差为0.99。经反演的预测径流量平均相对误差绝对值为19.3%。该模型对长江上游夏季径流量及其年际变化的预测准确率大于80%。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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图 1 长江上游流域气象观测站(黑色圆点) 和寸滩水文站、武隆水文站、宜昌水文观测站(红色三角) 分布
(灰色粗实线为长江上游流域界，蓝色实线为河流)
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)
图 2 1980—2013年长江上游夏季径流量序列的均一化检验统计量T (虚线表示达到0.1显著性水平) (a) 以及2003—2013年宜昌水文站与三峡水库入库夏季径流量的相对误差绝对值(b)
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
图 3 1980—2020年夏季长江上游流域要素距平值 (a)径流量，(b)总降水量，(c)平均气温
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
图 4 1981—2015年长江上游夏季降水量与气象要素场年际增量的相关系数(等值线)
(填色为显著性水平)
(a)春季850 hPa和200 hPa经向风切变，(b)前期秋季海平面气压场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
图 5 1981—2015年长江上游夏季降水与春季气象要素场年际增量的相关系数
(a)Q1 (填色为显著性水平)，(b)600 hPa涡度(填色为显著性水平)、散度(等值线) 和风矢量(箭头)
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
图 6 1981—2015年气象要素年际增量间的相关系数
(填色为显著性水平)
(a)春季500 hPa高度场与夏季长江上游降水量，(b)春季EUI指数与夏季500 hPa高度场和整层水汽通量，(c)春季EUI指数与夏季500 hPa垂直速度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
图 7 1981—2015年春季北半球极涡中心经向位置指数与夏季500 hPa高度场年际增量相关系数(等值线)
(填色为显著性水平)
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)
图 8 1981—2015年前冬澳大利亚高压指数与夏季气象要素年际增量的相关系数
(a)海平面气压(填色为显著性水平) 和925 hPa风场，(b)500 hPa高度场(填色为显著性水平) 和整层水汽场
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
图 9 1981—2015年夏季长江上游标准化径流量年际增量(a)及径流量(b)观测值与模拟值变化曲线
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
图 10 2016—2020年长江上游夏季径流量年际增量模型预测值与观测值
(a)标准化径流量年际增量及均方根误差，(b)径流量和相对误差绝对值
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
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