Natural Hazards, Journal Year: 2024, Volume and Issue: unknown
Published: Oct. 24, 2024
Language: Английский
Natural Hazards, Journal Year: 2024, Volume and Issue: unknown
Published: Oct. 24, 2024
Language: Английский
Journal of Hydrology, Journal Year: 2024, Volume and Issue: 633, P. 130916 - 130916
Published: Feb. 21, 2024
Language: Английский
Citations
11International Journal of Disaster Risk Reduction, Journal Year: 2024, Volume and Issue: 102, P. 104310 - 104310
Published: Feb. 1, 2024
Language: Английский
Citations
9Frontiers in Engineering and Built Environment, Journal Year: 2025, Volume and Issue: 5(1), P. 1 - 21
Published: Jan. 31, 2025
Purpose The study aims to identify the areas of flood susceptibility and categorize Gangarampur sub-division into various zones. It also aspires evaluate efficacy integrating Geographic Information Systems (GIS) with Artificial Neural Networks (ANN) for analysis. Design/methodology/approach factors contributing floods such as rainfall, geomorphology, geo-hazard, elevation, stream density, land use cover, slope, distance from roads, Normalized Difference Water Index (NDWI) rivers were analyzed ANN model helps construct map area. For validating outcome, Receiver Operating Characteristic (ROC) is employed. Findings results indicated that proximity rivers, rainfall deviation, cover are most significant influencing occurrence in demonstrated a prediction accuracy 85%, its effectiveness Originality/value research offers novel approach by analysis sub-division. By identifying key deviation use, achieves 85% accuracy, showing risk mapping. These findings provide critical insights planners devise targeted mitigation strategies.
Language: Английский
Citations
1International Journal of Disaster Risk Reduction, Journal Year: 2024, Volume and Issue: 103, P. 104342 - 104342
Published: Feb. 16, 2024
Language: Английский
Citations
8Urban Climate, Journal Year: 2024, Volume and Issue: 56, P. 102018 - 102018
Published: July 1, 2024
Language: Английский
Citations
7Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: 31(11), P. 17206 - 17225
Published: Feb. 9, 2024
Language: Английский
Citations
6Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 359, P. 121067 - 121067
Published: May 1, 2024
Language: Английский
Citations
5Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 360, P. 121024 - 121024
Published: May 17, 2024
Language: Английский
Citations
4Integrated Journal for Research in Arts and Humanities, Journal Year: 2025, Volume and Issue: 5(1), P. 24 - 29
Published: Jan. 12, 2025
A recent key challenge called urban flooding has grasped Indian cities, collectively impacted by climate change and unsustainable infrastructural developments. Major cities throughout the country e.g., Mumbai, Delhi, Kolkata Chennai, as well smaller like Vadodara Guwahati, are facing increased frequency intensity of floods. Extreme rainfall events, sprawl, inadequate infrastructure drive this. Further, this can solely be a consequence heavy but, is intricately linked to man-made alterations encroachment on water bodies, antiquated drainage systems, surge in population leading higher waste production. The fast-paced urbanisation last few decades resulted decline natural bodies that once soaked excess downpours monsoon seasons. Additionally, systems many were designed for lesser rainfall, incapable coping with intense shorter spells. Accumulation siltation have further multi-folded inundation issues India. Due incurred economic losses human fatalities remain difficult believe. Collective awakening stakeholders climate-resilient infrastructure, proper management, upgrading outdated reduce inflated risks
Language: Английский
Citations
0Buildings, Journal Year: 2025, Volume and Issue: 15(3), P. 495 - 495
Published: Feb. 5, 2025
Natural and man-made disasters significantly challenge the safety stability of urban infrastructure (UI), disrupting daily operations impeding economic development. However, existing research on resilience (UIR) lacks comprehensive categorization critical infrastructure, insufficiently considers impacts natural disasters, offers limited empirical analysis interactions among pressure, state, response (PSR) dimensions. This study aims to establish a UIR assessment index examine coupling coordination (CC) levels obstacle indicators PSR across four Chinese municipalities. The results reveal that (1) is most influential overall more amenable artificial interventions than pressure state resilience; (2) generally, CC in municipalities were relatively high, advancing from an inferiorly intermediately balanced development stage over period, highlighting effective strategies such as enhanced resource allocation post-disaster recovery initiatives are recommended for adoption by similar cities; (3) identified, targeted proposed based each municipality’s unique characteristics. findings offer theoretical insights practical implications enhancing perspective utilizing models.
Language: Английский
Citations
0