AUTHOR=Kang Ying , Liu Jingjing , Liu Qin , Zhao Wenli , Guo Yunjun 

TITLE=The impact of landscape patterns on surface runoff in the central urban area of Chengdu

JOURNAL=Frontiers in Earth Science

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2025.1542985

DOI=10.3389/feart.2025.1542985

ISSN=2296-6463

ABSTRACT=Urbanisation has led to drastic changes in urban landscape patterns, which, in turn, have altered urban hydrological processes and surface runoff, causing urban waterlogging and significantly affecting water supply. Thus, identifying the characteristics of urban landscape patterns and re-vealing how they impact surface runoff can provide a scientific basis for landscape optimisation and regulation, promoting urban ecological security and sustainable development. This study constructs a Source-Sink Runoff Landscape Index (SSRLI), and it utilises the Storm Water Management Model (SWMM) to simulate the spatial distribution characteristics of surface runoff in the central urban area of Chengdu under different rainfall scenarios, exploring the relationship between landscape patterns and surface runoff. The results indicate: ① In 2022, the landscape types in the central urban area of Chengdu were mainly farmland, forestland, and impervious surfaces, accounting for 83.27% of the total study area. ② As rainfall intensity increased, the average rainfall-runoff conversion rate increased from 0.263 to 0.599. The impact of urban green spaces on surface runoff exhibited nonlinear characteristics. When the proportion of green spaces reached 32.5%, their effectiveness in reducing surface runoff improved significantly. ③ When the proportion of urban green spaces was less than 20%, it positively correlated with runoff depth; above 20%, the correlation became negative, especially after 40%, where rainfall had a lesser impact. When the proportions of farmland and forestland were low, their effectiveness in reducing runoff decreased with increasing rainfall intensity. Similarly, the impact of impervious surfaces also diminished with increasing rainfall intensity. ④ The SSRLI demonstrated good applicability in predicting changes in surface runoff, showing a significant positive correlation with runoff depth. This correlation gradually weakened as rainfall intensity increased. In summary, this study provides insights into the intricate relationship between urban landscape patterns and surface runoff, emphasizing the importance of green spaces in mitigating urban flooding and promoting sustainable urban development.