山区县域洪水预测研究--以阳朔县为例

Research on Flood Prediction in Mountainous County:A Case Study of Yangshuo County

山区县域的洪水灾害是我国防洪减灾体系中的薄弱环节。为提升洪水预测的准确性,以桂林阳朔县为例,基于HEC-HMS和InfoWorksICM模拟平台,构建田家河流域的水文水动力模型。利用2017—2022年间多场洪水数据对模型进行率定和验证。在此基础上,根据田家河与漓江的洪峰遭遇,预测12种不同洪水重现期组合的情景工况,并对每种情景下的淹没耕地面积、村庄数量、旧城区淹没面积以及新城区淹没面积进行统计和分析。研究结果表明:(1)遇龙河沿岸受灾情况受其上游暴雨洪水的影响,田家河流域洪水重现期TTJH=50a时,淹没耕地面积将超过8.15km2,沿途受影响村庄超过27个;(2)旧城区主要受漓江过境洪水的影响,漓江洪水重现期TLJ=20a时,漓江水位漫堤行洪,西街将处于1~2m的水深之中;(3)新城区对田家河流域及漓江洪水都表现出较高的敏感性,当洪水等级超过TTJH=10a且TLJ=20a或者TTJH=20a且TLJ=10a时,新城区将会遭遇较严重的洪灾。研究结果可为山区县域洪水预测提供参考。

The Flood in mountainous county area is a critical challenge within China's flood control and disaster management sys-tem.Aiming at improving flood prediction accuracy,this study selected Yangshuo County in Guilin as a case and developed a hydrological-hydraulic coupled model for the Tianjia River Watershed by HEC-HMS and InfoWorks ICM platforms.By refining and testing the model with floods from 2017 to 2022,12 scenarios of different flood return period combinations based on flood peak encounters of Tianjia River and Li Rivers were predicted.Statistics analysis were conducted on the area of submerged culti-vated land,the number of villages,the submerged area of the old town and the new town under each scenario.The findings indi-cate:(1)The flooding along the Yulong River banks is influenced prominently by upstream torrential floods.When the flood re-turn period in the Tianjia River Basin(TTJH)reaches 50 a,the submerged farmland area will exceed 8.15 km2,affecting more than 27 villages along the way.(2)The old town is mainly affected by the floods from the Li River.When Li River flood return period TLJ=20 a,the water level of the Li River overflows the embankments,and The West Street will be under water with depth of 1-2 m.(3)The new town district demonstrates heightened sensitivity to floods from both the Tianjia River Basin and the Li River.When the flood level exceeds either TTJH=10 a and TLJ=20 a or TTJH=20 a and TLJ=10 a,the new town area will suffer serious flood disasters.The research results can provide references for flood prediction in mountainous county.