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

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.

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Publication Details

Journal
Frontiers in Earth Science
Published
2025-03-31
DOI
https://doi.org/10.3389/feart.2025.1542985
Citations
2
Primary Topic
Environmental Changes in China
Type
article
Field-Weighted Citation Impact
2.21
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article

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

Yuxi Guo, Wenli Zhao, Ying Kang, Jingjing Liu et al.
2 citations
Frontiers in Earth Science
Environmental Changes in China
2.21
article

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

Yuxi Guo, Wenli Zhao, Ying Kang, Jingjing Liu, Qin Liu
article en
2 citations

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.

Frontiers in Earth ScienceVol. 13
Chinese Academy of Sciences (CN), Institute of Mountain Hazards and Environment (CN)
Openalex Percentile: Top 15%
Environmental Changes in China
2.21
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