基于分区耦合模型的太湖流域地表水资源量研究

许钦; 张坤; 叶鸣; 陈星

doi:10.13928/j.cnki.wrahe.2025.09.003

水利水电技术（中英文） ›› 2025, Vol. 56 ›› Issue (9) : 30 -41. DOI: 10.13928/j.cnki.wrahe.2025.09.003

水环境治理与水生态修复专栏

基于分区耦合模型的太湖流域地表水资源量研究

许钦 ¹^,²^,³ ,
张坤 ¹^,² ,
叶鸣 ⁴ ,
陈星 ⁵

作者信息 +

Research on surface water resources in Taihu Lake Basin based on zonal coupling model

Qin XU ¹^,²^,³ ,
Kun ZHANG ¹^,² ,
Ming YE ⁴ ,
Xing CHEN ⁵

Author information +

文章历史 +

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摘要

【目的】太湖流域是我国经济高度发达的区域，同时也是水资源供需矛盾突出的典型地区。为估算太湖流域多年平均地表水资源量，基于流域地理空间分布、下垫面类型及水文气象条件，【方法】提出分区耦合建模方法，将流域划分为上游山丘区和中下游平原区，分别采用新安江三水源模型和下垫面分类产汇流方法估算1956—2020年地表水资源量，并通过水库径流模拟和一维水动力模型验证结果的可靠性。【结果】研究表明：上游山丘区径流模拟平均确定性系数达0.76,相对误差控制在±7%以内；中下游平原区水位模拟确定性系数平均为0.88,丰水年拟合效果更优；模型估算的多年平均地表水资源量为178.54亿m³,较第二次全国水资源调查评价成果161.5亿m³偏大10.6%,较2006—2020年水资源公报平均值174.81亿m³偏大2.1%。【结论】分区耦合模型估算太湖流域地表水资源量具有较好的适用性和可靠性。降雨序列的延长、湖西区产流估算方式优化、下垫面变化等是造成模型同“二调”成果间存在差异的原因，未来研究中应考虑构建动态参数化方案精进模型估算能力。

Abstract

[Objective] The Taihu Lake Basin is a highly developed economic region in China and a typical area with prominent imbalance between supply and demand of water resources. The aim is to estimate the multi-year average surface water resources in the Taihu Lake Basin based on its geographical distribution, underlying surface types, and hydrometeorological conditions. [Methods] A zonal coupling modeling method was proposed, dividing the basin into the upstream hilly area and the middle-lower plain area. The Xin'anjiang three-source model and the runoff generation and concentration method based on underlying surface classification were used respectively to estimate the surface water resources from 1956 to 2020. The reliability of the result was verified through reservoir runoff simulation and a one-dimensional hydrodynamic model. [Results] The result showed that in the upstream hilly area, runoff simulation achieved an average coefficient of determination of 0.76, with relative errors controlled within ±7%. In the middle-lower plain area, water level simulation yielded an average coefficient of determination of 0.88, with better fitting performance in wet years. The model estimated the multi-year average surface water resources at 17.854 billion m³, which was 10.6% higher than the 16.15 billion m³ reported in the Second National Water Resources Survey and Assessment and 2.1% higher than the 17.481 billion m³ average in the water resources bulletins from 2006 to 2020. [Conclusion] The zonal coupling model demonstrates good applicability and reliability for estimating surface water resources in the Taihu Lake Basin. Differences between the model result and the “Second Survey” result primarily stem from the extended rainfall series, optimized runoff estimation method in the western lake area, and underlying surface changes. Future research should consider developing dynamic parameterization schemes to improve the model's estimation capabilities.