长江中游河岸形态特征及稳定性判别阈值

Statistical characteristics of river bank profile and threshold values for bank stability in Middle Yangtze River

三峡工程运用后,长江中游河床持续冲刷,局部段崩岸现象频发,威胁中游河道防洪安全。本文基于实测数据,揭示了中游河岸形态特征参数的统计规律,并提出了河岸稳定性的判别阈值。结果表明:中游各河段内水下坡比的概率密度总体上符合对数正态分布,当外界因素(来水来沙条件变化或护岸工程实施)导致河岸稳定性降低或增强时,其实际的分布规律会偏离对数正态分布,且其偏离程度可作为判定河段整体稳定性的依据;河型变化对河岸坡比的概率密度分布规律没有明显影响,但对于相对深泓位置的影响相对较为明显;上荆江、下荆江、城汉与汉湖河段的水下坡比阈值分别为>0.22、>0.18、>0.20和>0.28,大于下层河岸土体的休止角对应的坡比(约0.16),表明只有河岸下层土体冲刷到一定程度后,崩岸现象才会发生,符合其动力学过程;各河段内深泓位置的阈值均为离河岸小于平滩河宽的距离的10%。此外,采用提出的稳定性判别阈值确定了2020年长江中游易发生崩岸的区域分布,与实际巡查结果符合较好。

Since the operation of the Three Gorges project,the riverbed in the Middle Yangtze River(MYR)has been continuously eroded,leading to intensive bank erosion in certain local reaches and posing a threat to flood control safety.Based on field measurements,this study reveals the statistical trends of the MYR riverbank morphological parameters,and determines the threshold values for bank stability.The results indicate(1)the probability density of underwater slope is generally log-normal.However,when external factors-such as changes in water and sediment conditions or the implementation of bank protection projects-reduce or enhance bank stability,the actual distribution deviates from the log-normal.And the extent of deviation can be used as a basis for evaluating the overall stability of the river reach.(2)Channel pattern is not a factor that affects significantly the probability density distribution of bank slope,but its impact is relatively significant on the relative thalweg location.(3)The thresholds of underwater slopes are>0.22,>0.18,>0.20,and>0.28 in the Upper Jingjiang,Lower Jingjiang,Chenghan Reach,and Hanhu Reach respectively.These values are greater than the angle of repose of the lower bank soil(nearly 0.16),indicating that bank failure occurs only after the lower soil layer has been eroded to a certain degree,consistent with the dynamic process.(4)The thresholds of thalweg location are less than 10%of the bankfull width.In addition,using our bank stability thresholds,we can determine the distribution of areas prone to bank failure in MYR in 2020,and the results are in good agreement with observations.