面向输沙过程模拟的改进流向算法OA北大核心CSTPCD
An improved flow direction algorithm for sediment transport simulations
流域中的输沙过程是地貌学和地表动力学的重要研究内容.前人通过流向算法和实测地形变化来推测输沙率的空间分布,但是简单地应用流向算法会造成模拟过程中出现质量不守恒的情况.因此,设计了面向输沙过程模拟的改进流向算法,判断模拟过程中质量守恒情况,即输沙率是否为负值,若存在,则将负值输沙率重设,阻止负值输沙率向下游传播.对经典的D8、MFD-se、MFD-md 3种流向算法进行了改进实验.结果表明:(1)改进后的D8单流向算法相较于改进前的性能平均提升了1.26%.(2)改进后的MFD-se单流向算法相较于改进前的性能平均提升了4.17%.(3)改进后的MFD-md单流向算法相较于改进前的性能平均提升了4.54%.
Sediment transport process in catchments is a critical research area in the fields of geomorphology and surface dynamics.Numerous researchers have applied flow direction algorithms and topographic change detec-tion to spatially infer sediment transport.However,the simple application of flow direction algorithms often leads to mass conservation issues during simulation.Therefore,an improved flow direction algorithm for sediment transport process simulation was developed.This algorithm ensures mass conservation by checking whether the sediment transport rate is negative;if it is negative,reset the rate to zero to prevent the spread of negative sedi-ment transport rates downstream.Experiments were conducted using the D8,MFD-se,and MFD-md algorithms with the proposed improvements.The results are as follows:(1)The improved flow direction algorithm successfully eliminated negative values in the simulated sediment transport rate,thereby achieving the intended purpose.(2)The performance of the improved D8 algorithm increased by 1.26%.(3)The performance of the improved MFD-se algo-rithm increased by 4.17%,considerably enhancing sediment transport process simulations.(4)The performance of the improved MFD-md algorithm increased by 4.54%,further boosting the effectiveness of the sediment trans-port process simulations.
沈心怡;代文;刘爱利;陶宇;赵成义
南京信息工程大学地理科学学院,江苏 南京 211800||南京师范大学地理科学学院,江苏 南京 210023南京信息工程大学地理科学学院,江苏 南京 211800南京林业大学南京现代林业协同创新中心,江苏 南京 210037
流向算法数字高程模型输沙率质量守恒地形变化
flow direction algorithmdigital elevation modelsediment transport ratemass conservationtop-ographic change
《干旱区地理》 2024 (008)
1380-1387 / 8
国家自然科学基金(42301478,42130405);江苏省高等学校自然科学研究项目(22KJB170016)资助
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