Comprehensive Assessment of Flood Risk and Vulnerability for Essential Facilities: Iowa Case Study DOI Creative Commons

Cori Grant,

Yazeed Alabbad, Enes Yıldırım

et al.

Urban Science, Journal Year: 2024, Volume and Issue: 8(3), P. 145 - 145

Published: Sept. 18, 2024

In this study, nine different types of essential facilities in the state Iowa (such as hospitals, fire stations, schools, etc.) were analyzed on a county level terms flood depth, functionality and restoration time after flooding, damage sustained during flooding. These also their location relative to 100 y 500 zones. Results show that number within extent reached up 39%, scenario all but one six chosen counties lost 100% facilities. Most found have depth 1 4 ft deep 480 days. The purpose study is bring awareness decisionmakers regarding risk flooding events pose highlight increasing dangers broader scale. This will be beneficial improve mitigation strategies, emergency response plans, ensuring services are available event future floods for affected areas.

Language: Английский

The Implementation of Multimodal Large Language Models for Hydrological Applications: A Comparative Study of GPT-4 Vision, Gemini, LLaVa, and Multimodal-GPT DOI Creative Commons

Likith Kadiyala,

Omer Mermer, R. Dinesh Jackson Samuel

et al.

Hydrology, Journal Year: 2024, Volume and Issue: 11(9), P. 148 - 148

Published: Sept. 11, 2024

Large Language Models (LLMs) combined with visual foundation models have demonstrated significant advancements, achieving intelligence levels comparable to human capabilities. This study analyzes the latest Multimodal LLMs (MLLMs), including Multimodal-GPT, GPT-4 Vision, Gemini, and LLaVa, a focus on hydrological applications such as flood management, water level monitoring, agricultural discharge, pollution management. We evaluated these MLLMs hydrology-specific tasks, testing their response generation real-time suitability in complex real-world scenarios. Prompts were designed enhance models’ inference capabilities contextual comprehension from images. Our findings reveal that Vision exceptional proficiency interpreting data, providing accurate assessments of severity quality. Additionally, showed potential various applications, drought prediction, streamflow forecasting, groundwater wetland conservation. These can optimize resource management by predicting rainfall, evaporation rates, soil moisture levels, thereby promoting sustainable practices. research provides valuable insights into advanced AI addressing challenges improving decision-making

Language: Английский

Citations

4
Urban flood risk assessment and evacuation planning: a bi-level optimization model for sustainable high-density coastal areas DOI Creative Commons
Xinyue Gu, Yan Mao, Xintao Liu

et al.

Annals of GIS, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 13

Published: Jan. 13, 2025

Flooding caused by extreme climate change is becoming increasingly severe, especially in high-density coastal areas worldwide. Although many studies have conducted risk assessments of urban floods, most not formed a comprehensive evacuation plan considering population distribution and flood disaster risk. To further enhance planning emergency management for areas, this study uses Victoria Harbor Hong Kong, typical flood-prone region, as research area. The first conducts exposure assessment classifies different regions according to levels. Then, combining ability with the changing road flows, novel bi-level optimization model proposed allocate zones citizens day night. With upper level using genetic algorithm minimize total system time lower applying user equilibrium evacuee allocation, forms an that considers hotspots impact risks on network. findings show functional high pedestrian flow, tourist spots, commercial centres, schools are exposed higher Besides, simulation matches zoning results actual activities can effectively achieve goal evacuating 480,000 people within 12–18 minutes. This innovatively proposes effective reference government's work.

Language: Английский

Citations

0
Geo-WC: Custom Web Components for Earth Science Organizations and Agencies DOI
Sümeyye Kaynak, Baran Kaynak, Carlos Erazo Ramirez

et al.

Environmental Modelling & Software, Journal Year: 2025, Volume and Issue: unknown, P. 106328 - 106328

Published: Jan. 1, 2025

Language: Английский

Citations

0
A community-centric intelligent cyberinfrastructure for addressing nitrogen pollution using web systems and conversational AI DOI

Samrat Shrestha,

Jerry Mount,

Gabriel Vald

et al.

Environmental Science & Policy, Journal Year: 2025, Volume and Issue: 167, P. 104055 - 104055

Published: April 4, 2025

Language: Английский

Citations

0
Effectiveness of regional risk mitigation policies in equitably improving connectivity to essential service during hurricane-induced floods DOI

Naqib Mashrur,

Sabarethinam Kameshwar

International Journal of Disaster Risk Reduction, Journal Year: 2024, Volume and Issue: 112, P. 104775 - 104775

Published: Aug. 23, 2024

Language: Английский

Citations

2
A Positional Knowledge-Guided Multiscale Gaussian Detail Enhancement Deep Learning Network for Ground Fissure Extraction DOI Creative Commons
Weiqiang Luo, Ming Hao, Shilin Chen

et al.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Journal Year: 2024, Volume and Issue: 17, P. 13881 - 13892

Published: Jan. 1, 2024

Language: Английский

Citations

1
Comprehensive Assessment of Flood Risk and Vulnerability for Essential Facilities: Iowa Case Study DOI Creative Commons

Cori Grant,

Yazeed Alabbad, Enes Yıldırım

et al.

Urban Science, Journal Year: 2024, Volume and Issue: 8(3), P. 145 - 145

Published: Sept. 18, 2024

In this study, nine different types of essential facilities in the state Iowa (such as hospitals, fire stations, schools, etc.) were analyzed on a county level terms flood depth, functionality and restoration time after flooding, damage sustained during flooding. These also their location relative to 100 y 500 zones. Results show that number within extent reached up 39%, scenario all but one six chosen counties lost 100% facilities. Most found have depth 1 4 ft deep 480 days. The purpose study is bring awareness decisionmakers regarding risk flooding events pose highlight increasing dangers broader scale. This will be beneficial improve mitigation strategies, emergency response plans, ensuring services are available event future floods for affected areas.

Language: Английский

Citations

0