Infiltration Wells Effectiveness Analysis: Study in Purwantoro Village, Malang City DOI Open Access

Oxike Morillyn,

Moh. Khusaini,

Vietha Devia

et al.

Jurnal Penelitian Pendidikan IPA, Journal Year: 2024, Volume and Issue: 10(12), P. 10029 - 10036

Published: Dec. 18, 2024

Infiltration wells are one of the effective infrastructure in draining rainwater so that they can reduce waterlogging, but existing infiltration need to be reviewed for their effectiveness as water shortages still occurring especially Purwantoro Village.The study aims determine and calculate appropriate number Village. The method used this research is a hydrological analysis, planned flood discharge analysis dan well analysis. results showed Village varies greatly, with highest at 82.8% lowest 11.3%. To increase wells, many 109 needed waterlogging. conclusion lack because limited, it necessary add maintenance deposits contained wells.

Language: Английский

Toward Explainable Flood Risk Prediction: Integrating A Novel Hybrid Machine Learning Model DOI
Yongyang Wang, Pan Zhang, Yulei Xie

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106140 - 106140

Published: Jan. 1, 2025

Language: Английский

Citations

2
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
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Xiaotian Qi,

Soon‐Thiam Khu,

Pei Yu

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 132842 - 132842

Published: Feb. 1, 2025

Language: Английский

Citations

0
City-scale integrated flood risk prediction under future climate change and urbanization based on the shared socioeconomic pathways (SSP) scenarios DOI
Wen Liu, Xin Zhang, Qi Feng

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 132971 - 132971

Published: Feb. 1, 2025

Language: Английский

Citations

0
Development of a real-time dynamic inundation risk assessment approach on paddy fields during typhoons: Exploration of adaptation strategies and quantification of risks DOI
Bing-Chen Jhong, Foong Ling Chen, Ching‐Pin Tung

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 380, P. 124981 - 124981

Published: March 13, 2025

Language: Английский

Citations

0
A new approach to evaluating urban flood risk: the case of Guangdong Province in China DOI
Wenping Xu,

Pil Soo Han,

David Proverbs

et al.

Urban Water Journal, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 17

Published: March 14, 2025

Language: Английский

Citations

0
Impact of 2D and 3D factors on urban flooding: Spatial characteristics and interpretable analysis of drivers DOI
Yongheng Wang, Qingtao Zhang,

Jingkun Zhang

et al.

Water Research, Journal Year: 2025, Volume and Issue: unknown, P. 123537 - 123537

Published: March 1, 2025

Language: Английский

Citations

0
Uncertainty pattern and an integration strategy in flood susceptibility modeling: Limited sample size DOI
Jun Liu,

Xueqiang Zhao,

Yangbo Chen

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 133184 - 133184

Published: March 1, 2025

Language: Английский

Citations

0
Revealing the dynamic effects of land cover change on land surface temperature in global major bay areas DOI
Qingtao Zhang, Yijia Guan, Xinyu Wu

et al.

Building and Environment, Journal Year: 2024, Volume and Issue: 267, P. 112266 - 112266

Published: Nov. 4, 2024

Language: Английский

Citations

3
Flood risk assessment of coastal cities based on GCW_ISODATA and explainable artificial intelligence methods DOI

Yawen Zang,

Huimin Wang, Zhenzhen Liu

et al.

International Journal of Disaster Risk Reduction, Journal Year: 2024, Volume and Issue: unknown, P. 105025 - 105025

Published: Nov. 1, 2024

Language: Английский

Citations

2