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1.重庆交通大学河海学院,重庆 400074
2.广西平陆运河建设有限公司,广西南宁 530022
3.水利部信息中心,北京,邮编100053
Online First:15 October 2026,
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ZHOU Mi, CHENG Yaofei, ZHU Bing, et al. flood forecasting during the construction period of the Pinglu Canal[J/OL]. Engineering Journal of Wuhan University, 2026, 1-10.
ZHOU Mi, CHENG Yaofei, ZHU Bing, et al. flood forecasting during the construction period of the Pinglu Canal[J/OL]. Engineering Journal of Wuhan University, 2026, 1-10. DOI: 10.14188/j.1671-8844.2025.0320.
平陆运河当前施工段受钦江流域上游自然河道洪水威胁,为保障施工期人员及设备安全,提出构建融合栅格型分布式水文模型与实时滚动修正机制的洪水预报模型,通过提升预报精度与时效性支撑精准撤离决策。模型基于D8流向算法划分流域栅格结构,依据栅格土地利用类型配置产流参数,耦合新安江产流模型与马斯京根-康吉汇流算法,实现洪水过程全链条模拟。采用钦州(闸上)和陆屋两个水文站的长系列实测数据率定模型产汇流参数,验证期结果显示纳什效率系数(
<math id="M1"><mi>N</mi><mi>S</mi><mi>E</mi></math>
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6.60400009
2.45533323
)超过0.8,径流总量相对误差(
<math id="M2"><mi>R</mi><mi>E</mi></math>
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4.65666676
2.37066650
)趋近于0。对2024年的三场典型洪水进行预报分析,模型均提前24小时发布预警,且预报精度满足施工安全管控需求(
<math id="M3"><mi>N</mi><mi>S</mi><mi>E</mi><mo>></mo><mn mathvariant="normal">0.8</mn></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=120274211&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=120274239&type=
14.81666565
2.45533323
,
<math id="M4"><mi>R</mi><mi>E</mi><mo><</mo><mo>±</mo><mn mathvariant="normal">10</mn><mi mathvariant="normal">%</mi></math>
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https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=120274241&type=
18.03400040
2.96333337
),为平陆运河施工期及运行期防洪提供了技术参考。
The construction section of the Pinglu Canal is currently threatened by floods from the natural river course in the upper reaches of the Qinjiang River Basin. To ensure the safety of personnel and equipment during the construction period
a flood forecasting model integrating a grid-based distributed hydrological model and a real-tim
e rolling correction mechanism is proposed. It supports accurate evacuation decisions by improving forecast accuracy and timeliness.The model divides the watershed grid structure based on the D8 flow direction algorithm
configures runoff generation parameters according to the grid land use type
and couples the Xinanjiang runoff generation model with the Muskingum-Cunge routing algorithm to realize the full-chain simulation of the flood process. Long-series measured data from two hydrological stations
Qinzhou (upstream of the gate) and Luwu
are used to calibrate the model's runoff generation and routing parameters. Results during the validation period show that the Nash-Sutcliffe efficiency coefficient (
<math id="M5"><mi>N</mi><mi>S</mi><mi>E</mi></math>
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7.70466709
2.87866688
) exceeds 0.8
and the relative error of total runoff (
<math id="M6"><mi>R</mi><mi>E</mi></math>
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5.41866684
2.79399991
) approaches 0.Forecast and analysis of three typical floods in 2024 indicate that the model issued early warnings 24 hours in advance for all cases. The forecast accuracy meets the requirements of construction sa
fety management(
<math id="M7"><mi>N</mi><mi>S</mi><mi>E</mi><mo>></mo><mn mathvariant="normal">0.8</mn></math>
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17.27199936
2.87866688
,
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21.08200073
3.47133350
)
providing technical reference for flood control during the construction and operation periods of the Pinglu Canal.
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