The impact of landscape patterns on surface runoff in the central urban area of Chengdu DOI Creative Commons
Ying Kang, Jingjing Liu, Qin Liu

et al.

Frontiers in Earth Science, Journal Year: 2025, Volume and Issue: 13

Published: March 31, 2025

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

Language: Английский

The impact of landscape patterns on surface runoff in the central urban area of Chengdu DOI Creative Commons
Ying Kang, Jingjing Liu, Qin Liu

et al.

Frontiers in Earth Science, Journal Year: 2025, Volume and Issue: 13

Published: March 31, 2025

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

Language: Английский

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