甬江流域鄞州平原区极端洪水对暴雨的响应特征

Variations in extreme water level responses to rainstorms in the Yinzhou Plain of the Yongjiang River Basin

为深刻揭示变化环境下甬江流域鄞州平原区雨洪关系特征,以姜山水文站为例,基于1962—2021年逐日降水和水位观测资料,利用分位数扰动法和极端降雨水位时变相关模型,从扰动过程和时变关系两个方面,探讨了水位对极端暴雨的响应特征演变趋势。结果表明:近60年姜山水文站年最大1、3 d降水量和年最大水位均呈显著上升趋势,变化倾向率分别为8.39 mm/10 a、12.66 mm/10 a和0.67 m/10 a;年最大1、3 d降水量和最大水位均呈现相似的阶段性扰动特征,即1960—1984年以负扰动为主,1985—2012年扰动强度较为平稳,2013—2021年为显著扰动;在选用的12个模型中,Time-varing Normal、Time-varing Rotated Gumbel、Timevaring Symmetrized Joe-Clayton等3个动态时变响应模型能更好地拟合极端洪水对暴雨的响应。总体上,年最大水位对年最大3 d降水量的响应以1990s—2000s为高值期,呈现先升后降的阶段性特征。研究结果可以加深城镇化对雨洪关系影响机制的认知,也可供区域洪涝灾害预警和预测参考。

This study aims to elucidate the evolution of the storm-flood relationship in the Yinzhou Plain area of the Yongjiang Basin amidst changing environmental conditions.The responses of extreme water levels to heavy rains were analyzed over the period 1962 to 2021 at Jiangshan Station,considering disturbance characteristics and time-varying responses.The quantile disturbance method(QPM)and a time-varying correlation model were employed for this investigation.The findings revealed a significant increase in annual maximum 1-day/3-day precipitation and maximum water level,with rates of 8.39 mm/10a,12.66 mm/10a,and 0.67 m/10a,respectively.The three indicators exhibited similar temporal perturbation patterns over the last 60 years according to QPM.Disturbances were predominantly negative from 1960 to 1984 and significantly positive from 2013 to 2021.Among the 12 selected models,the three time-varying models—Time-varying Normal,Time-varying Rotated Gumbel,and Time-varying Symmetrized Joe-Clayton—provided better fits for rainstorm-flood correlations.Generally,the response of annual maximum water level to annual maximum 3-day precipitation exhibited a stage characteristic of first rising and then falling.The high values of correlation were predominantly observed from the 1990s to the 2000s.These results enhance our understanding of the influence of urbanization on extreme precipitation-water level relationships and play a crucial role in the early warning and prediction of regional flood disasters.