Back to Search Start Over

Research on the quantitative relationship between topographic features and river network structures.

Research on the quantitative relationship between topographic features and river network structures.

Authors :
Li, Fawen
Wang, He
Liu, Huifeng
Source :
Physical Geography; Feb2024, Vol. 45 Issue 1, p1-19, 19p
Publication Year :
2024

Abstract

Hydrologists pursue the long-term goals of studying the relationship between hydrological processes and geomorphological processes, establishing quantitative relationships between these processes and finding ways to directly derive hydrological processes from topographic parameters to reduce the dependence on hydrological data. In this study, the river network of the Haihe River Basin was extracted based on DEM, and 18 representative small basins were selected as samples. Four river network parameters (the river network density, average branch ratio, average length ratio and fractal dimension) and four topographic parameters (the slope, topographic relief, surface roughness and roundness rate) were calculated for 18 small basins. The river network features and topographic features of the basin were analysed. Correlation analysis, one-dimensional linear regression, partial correlation analysis and multiple linear regression (stepwise regression) methods were used to analyse the quantitative relationship between topographic parameters and river network parameters. The analysis results were tested by a significance test, the final goodness of fit of the regression model was good, and the results were reliable. The correlations are spatially heterogeneous and may show variable results in different regions. This study guides river network planning and management, and managers should pay attention to the correlation between river networks and topography in the long term. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02723646
Volume :
45
Issue :
1
Database :
Supplemental Index
Journal :
Physical Geography
Publication Type :
Academic Journal
Accession number :
174684513
Full Text :
https://doi.org/10.1080/02723646.2022.2163541