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考虑峰丛洼地内涝滞洪的分布式岩溶水文模型

陈立华 杨文哲 陈航 黄文举

水科学进展2025,Vol.36Issue(4):646-656,11.
水科学进展2025,Vol.36Issue(4):646-656,11.DOI:10.14042/j.cnki.32.1309.2025.04.009

考虑峰丛洼地内涝滞洪的分布式岩溶水文模型

A distributed karst hydrological model incorporating flooding detention in peak-cluster depressions

陈立华 1杨文哲 1陈航 1黄文举1

作者信息

  • 1. 广西大学土木建筑工程学院,广西 南宁 530004||广西壮族自治区岩溶区水安全与智慧调控工程研究中心,广西 南宁 530004
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摘要

Abstract

Flooding detention in peak-cluster depressions is a key component of the hydrological cycle in karst basins.To address the limitations of existing hydrological models in accurately representing this process,this study proposes a simulation method based on the water balance principle.A distributed karst Xin'anjiang hydrological model incorporating flooding detention in peak-cluster depressions(DK-XAJ-DF)is developed.Using the Diaojiang River basin as a representative study area,the model simulates the flooding detention volume in the Longtou peak-cluster depression and the streamflow processes at the Hekou and Malong hydrological stations.Results indicate that the hourly simulation of flooding detention volume in the Longtou depression achieves a determination coefficient and relative total error of 0.90 and 0.77%,respectively.During the validation period,the hourly simulation of streamflow yields determination coefficients of 0.85 and 0.89 for the Hekou and Malong stations,respectively,with corresponding total errors of 3.0%and-4.4%.Compared with the original model,the modified DK-XAJ-DF model improves the qualification rates of flood peak discharge and peak timing at the Malong station from 65%to 70%and from 70%to 80%,respectively.By explicitly quantifying the flooding detention effect,the DK-XAJ-DF model enhances simulation accuracy of flood simulation in karst areas.

关键词

洪水预报/内涝滞洪/分布式岩溶水文模型/岩溶区/峰丛洼地

Key words

flood forecasting/flooding detention/distributed karst hydrological model/karst areas/peak-cluster depression

分类

建筑与水利

引用本文复制引用

陈立华,杨文哲,陈航,黄文举..考虑峰丛洼地内涝滞洪的分布式岩溶水文模型[J].水科学进展,2025,36(4):646-656,11.

基金项目

国家自然科学基金项目(52439002 ()

52179010)The study is financially supported by the National Natural Science Foundation of China(No.52439002 ()

No.52179010). ()

水科学进展

OA北大核心

1001-6791

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