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Prediction of the change trends of the scour near the head of the spur dike based on BP neural network
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摘要: 丁坝坝头冲刷坑的深度及位置变化影响坝基稳定，是丁坝安全评估的重要参数，且是一个复杂的非线性系统问题。以长江张南水道为研究对象，基于2008—2016年实测资料，分析来水来沙及其变化过程、冲刷坑位置和深度的变化，研究确定影响冲刷坑深度及位置变化的因子是河床边界条件(水深、河宽)、坝体属性(丁坝长度、挑角)及来水来沙因素(年径流量、年输沙量、不同级别来水来沙持续的天数)，建立了基于BP神经网络的冲刷坑深度及位置变化趋势预测模型。计算结果表明，BP神经网络模型得到的冲刷坑深度和位置预测值与实测值较吻合，误差在(1.8~6.5)%，研究结果可为丁坝安全评估提供依据。Abstract: The scours' maximum depth and position changes have a full influence on spur dikes' safety, and are important parameters for evaluating the dikes' safety. Taking the Zhangnan waterway on the Changjiang River as an example, this paper analyses the relationship between incoming flow, sediment and scours' changes. The influencing factors of scours are the riverbed boundary conditions (water depth, river width), spur body properties (spur length, picking angle), incoming flow and incoming sand factors (annual runoff, annual sediment transport, days of different runoff and sediment transport). Based on the BP neural network's theory, a prediction model of the erosion changes near the spur is built. The result shows that the predicted values are approximate to the true one, which proves that this prediction model is feasible and effective. The result of this study can provide reference for the improvement of spur dikes' safety assessment.
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Key words:
- spur dike /
- scours' depth /
- scours' position /
- characteristics of water and sediment /
- BP neural network
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图 1 张家洲水道南港下浅区工程平面布置
Figure 1. Plan layout of the lower shallow area of Zhangjiazhou Waterway
图 2 2008—2016年1#~4#丁坝冲刷坑深度变化
Figure 2. Change of scouring depth of 1# ~ 4# pits from 2008 to 2016
图 3 2008—2016年1#~4#冲刷坑最深点位置变化
Figure 3. Change of deepest point position of 1#~4# scouring pits from 2008 to 2016
图 4 2008—2016年年径流量、年输沙量与1#丁坝冲刷深度变化
Figure 4. Changes of annual runoff, annual sediment transport volume and scouring depth of 1# spur from 2008 to 2016
图 5 2008—2016年年径流量、年输沙量与1#丁坝冲刷位置变化
Figure 5. Changes of annual runoff, annual sediment transport volume and scouring position of 1# spur from 2008 to 2016
图 6 九江水文站2008—2016年日均流量含沙量过程
Figure 6. Process of daily average flow and sediment concentration in Jiujiang hydrological station from 2008 to 2016
图 7 坝头冲刷坑几何尺度
Figure 7. Schematic diagram of geometrical scale of scouring pit near spur head
表 1 张南水道1#~4#丁坝参数
Table 1. Parameters of 1#~4# spur of Zhangnan Waterway
丁坝编号 坝长/m 坝轴线与主流夹角/° 丁坝间距/m 1# 275 83 — 2# 511 96 931 3# 428 86 907 4# 548 89 805 
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表 2 2010和2012年逐日平均流量及含沙量持续天数
Table 2. Daily average flow and sediment concentration in 2010 and 2012
d 年份 不同流量对应的天数 不同含沙量对应的天数 Q1≤15 000 m3/s 15 000 < Q2≤25 000 m3/s 25 000 < Q3≤40 000 m3/s Q4>40 000 m3/s S1≤0.06 g/m3 0.06 < S2≤0.10 g/m3 0.10 < S3≤0.25 g/m3 S4>0.25 g/m3 2010年 180 53 87 49 125 133 104 8 2012年 149 100 75 41 125 134 93 13
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表 3 2015年张南水道1#~4#丁坝检验样本
Table 3. Inspection sample of 1#~4# spurs of Zhangnan Waterway in 2015
样本标号 日期 丁坝编号 H/m d/m h/m B/m b/m α/° TQ1/d TQ2/d TQ3/d TQ4/d TS1/d TS2/d TS3/d TS4/d Q/万m3 G/万t 1 2015-07-23 1# 2.0 76.9 6.8 655.6 275 83 77 132 109 31 58 213 78 0 7 096 5 380 2 2015-07-23 2# 2.7 123.7 7.0 540.3 511 96 77 132 109 31 58 213 78 0 7 096 5 380 3 2015-07-23 3# 4.7 85.2 9.5 577.2 428 86 77 132 108 31 58 213 78 0 7 096 5 380 4 2015-07-23 4# 5.0 83.2 9.2 577.2 548 89 77 132 109 31 58 213 78 0 7 096 5 380
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表 4 2015年BP网络模型预测值与实测值比较
Table 4. Comparison of predicted and actual values of BP network model in 2015
日期 丁坝编号 参数 实测值/m 预测值/m 绝对误差/m 相对误差/% 2015-07-23 1# 冲刷深度(m) 2.0 1.9 -0.1 -5.0 最深点距坝轴线距离(m) 76.9 78.3 1.4 1.8 2015-07-23 2# 冲刷深度(m) 2.7 2.6 -0.1 -3.7 最深点距坝轴线距离(m) 123.7 130.5 6.8 5.5 2015-07-23 3# 冲刷深度(m) 4.7 4.8 0.1 2.1 最深点距坝轴线距离(m) 85.2 88.5 -3.3 -3.9 2015-07-23 4# 冲刷深度(m) 5.0 4.8 -0.2 -4.0 最深点距坝轴线距离(m) 83.2 88.6 -5.4 -6.5
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