流域暴雨洪涝预测模型比较分析OA
Comparison and analysis of watershed rainstorm and flood prediction models
洪涝预测模型在地表水流运动部分主要由水文产汇流、一维及二维水动力等模块组成.在比较国内外已有流域洪涝预测模型的基础上,提出水文汇流模块与一维、二维水动力模块动态双向耦合模型(DBCM及DCM2D),其精度与效率等性能优于已有洪涝预测模型.DBCM将流域分成非淹没区和淹没区,两个区域在空间上互不重叠,非淹没区采用水文模型和粗网格计算,以提高计算效率;淹没区采用浅水方程和细网格计算,以保证计算精度.两个区域以耦合界面连接,通过耦合界面的水量守恒,模型具有较好的精度,并克服了已有间接耦合模型与实际流动过程不符及总体水量不守恒的不足.DCM2D 在DBCM的基础上增加一维水动力模块,是分布式水文、一维及二维水动力模型的直接双向耦合,旨在更真实地反映洪涝发生发展过程,可以兼顾计算精度与计算效率.
A flood prediction model is usually an integration of a hydrologic module,a one-dimensional(1D)module,a two-dimensional(2D)hydrodynamic module,and others for surface water flow simulation.This paper compares the related models updated in the domestic and international literature,and develops a dynamic two-way coupling of hydrologic and 2D hydrodynamic models(DBCM and DCM2D),to achieve its performances-such as computational efficiency and accuracy-higher than the previous models.DBCM divides the watershed into non-inundation and inundation zones,spatially nonoverlapping,with the former calculated on coarse grids for hydrologic modeling,while the latter on fine grids for 2D hydrodynamic modeling.These two sets of zones are joined and coupled through movable interfaces,by applying the conservation rules of water volume and momentum.DBCM overcomes the deficiencies of the previous models that couple the two sets but breaking the conservation rules,and thus achieves better accuracy.DCM2D is an expanded DBCM by adding a 1D hydrodynamic module,and therefore achieves an internally bidirectional coupling of the distributed hydrologic module and the 1D and 2D hydrodynamic modules.These new models are aimed to better describe the real flood process while considering both computational accuracy and efficiency.
周琦;江春波;刘昭伟
清华大学 水利水电工程系,北京 100084||清华大学 水圈科学与水利工程全国重点实验室,北京 100084清华大学 水利水电工程系,北京 100084||清华大学 水圈科学与水利工程全国重点实验室,北京 100084清华大学 水利水电工程系,北京 100084||清华大学 水圈科学与水利工程全国重点实验室,北京 100084||清华四川能源互联网研究院,成都 610213
建筑与水利
流域洪涝预测DCM2DDBCM双向耦合精度与效率
watershed flood predictionDCM2DDBCMtwo-way couplingcomputational accuracy and efficiency
《水力发电学报》 2026 (9)
14-26,13
京津冀环境综合治理国家科技重大专项项目(2025ZD1202102)国家自然科学基金面上项目(52179068)清华四川能源互联网研究院有组织科研项目(35130240067)
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