Research on Runoff Management of Sponge Cities under Urban Expansion DOI Open Access
Hongliang Sun,

Shangkun Wu,

Qiyu Dong

et al.

Water, Journal Year: 2024, Volume and Issue: 16(15), P. 2103 - 2103

Published: July 25, 2024

To integrate the sponge city concept into urban development, we propose an analytical approach for runoff volume control, considering expansion. Using Changchun City as a case study and historical land-use data, simulated prediction of City’s structure 2035 change with GeoSOS-FLUS platform. We calculated storage volumes Low Impact Development (LID) designs using 2019 land surface data. The objective is 80% control rate by 2035. Through Monte Carlo simulation sensitivity analysis, assessed impact various types on LID calculations. Findings show that industrial significantly influences volumes. This highlights need precise surveys properties composition in planning more accurate analysis City. results indicate based current data may not meet long-term goals due to increased impervious surfaces coefficients during urbanization.

Language: Английский

Assessing the scale effect of urban vertical patterns on urban waterlogging: An empirical study in Shenzhen DOI

Yuqin Huang,

Jinyao Lin, Xiaoyu He

et al.

Environmental Impact Assessment Review, Journal Year: 2024, Volume and Issue: 106, P. 107486 - 107486

Published: March 8, 2024

Language: Английский

Citations

41

A novel flood risk management approach based on future climate and land use change scenarios DOI
Huu Duy Nguyen, Quoc‐Huy Nguyen, Dinh Kha Dang

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 921, P. 171204 - 171204

Published: Feb. 23, 2024

Language: Английский

Citations

25

Effective or useless? Assessing the impact of park entrance addition policy on green space services from the 15-min city perspective DOI
Qinyu Cui, Lin Tan, Haoran Ma

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 467, P. 142951 - 142951

Published: June 19, 2024

Language: Английский

Citations

10

Attribution analysis of urban social resilience differences under rainstorm disaster impact: Insights from interpretable spatial machine learning framework DOI

Tianshun Gu,

Hongbo Zhao, Yue Li

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: unknown, P. 106029 - 106029

Published: Dec. 1, 2024

Language: Английский

Citations

7

Geographic heterogeneity of activation functions in urban real-time flood forecasting: Based on seasonal trend decomposition using Loess-Temporal Convolutional Network-Gated Recurrent Unit model DOI

Songhua Huan

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 636, P. 131279 - 131279

Published: May 7, 2024

Language: Английский

Citations

6

Understanding the key factors and future trends of ecosystem service value to support the decision management in the cluster cities around the Yellow River floodplain area DOI Creative Commons
Hongbo Zhao,

Xiaoman Xu,

Junqing Tang

et al.

Ecological Indicators, Journal Year: 2023, Volume and Issue: 154, P. 110544 - 110544

Published: June 26, 2023

The ecosystem services value (ESV) is an important basis for measuring ecological environment quality and efficient management of ecosystems. Although there have been many studies devoted to the measurement ESV, research on key influencing factors ESV prediction future development scenarios still limited. This study coupled Deep Forest model Patch-generating Land Use Simulation (PLUS) identify simulated change trend under Shared Socioeconomic Pathways (SSPs). Taking cluster cities around Yellow River floodplain area as object, this quantitatively analyzed spatiotemporal evolution characteristics its from 2000 2020, identified affecting using model. results showed that: (1) overall upward with strong spatial heterogeneity; (2) were construction land ratio, distance railway, SHDI, etc.; (3) best pathway in 2025, 2030 2035 would be SSPs5, SSPs2 SSPs4 respectively. can provide theoretical support maximizing benefits area.

Language: Английский

Citations

11

Investigating the influence of nonlinear spatial heterogeneity in urban flooding factors using geographic explainable artificial intelligence DOI
Entong Ke, Juchao Zhao, Yaolong Zhao

et al.

Journal of Hydrology, Journal Year: 2024, Volume and Issue: unknown, P. 132398 - 132398

Published: Nov. 1, 2024

Language: Английский

Citations

4

Assessing the impact of urbanization on flood patterns in Varanasi, India using Google Earth Engine DOI Creative Commons

Vikas Yadav,

Ashutosh Kainthola,

Gaurav Kushwaha

et al.

Deleted Journal, Journal Year: 2025, Volume and Issue: 2(1)

Published: Feb. 25, 2025

Language: Английский

Citations

0

Exploring the dynamic impact of future land use changes on urban flood disasters: A case study in Zhengzhou City, China DOI Creative Commons

Yuanyuan Bai,

Shao Sun,

Yingjun Xu

et al.

Geography and sustainability, Journal Year: 2025, Volume and Issue: unknown, P. 100287 - 100287

Published: March 1, 2025

Language: Английский

Citations

0

The application of integrating comprehensive evaluation and clustering algorithms weighted by maximal information coefficient for urban flood susceptibility DOI
Hongfa Wang, Yu Meng, Huiliang Wang

et al.

Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 344, P. 118846 - 118846

Published: Sept. 2, 2023

Language: Английский

Citations

9