A Comprehensive Flood Risk Assessment for Railroad Network: Case Study for Iowa DOI Creative Commons
Atiye Cikmaz, Yazeed Alabbad, Enes Yıldırım

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: April 19, 2024

Abstract Climate-induced disasters, particularly floods, pose a substantial risk to human well-being. These risks encompass economic losses, infrastructural damage, disruption of daily life, and potential loss life. This study focuses on understanding flood critical infrastructure, emphasizing the resilience reliability essential services during such disasters. In United States, railway network is vital for distribution goods services. research specifically targets in Iowa, state where impact flooding railways has not been extensively studied. We employ comprehensive GIS analysis assess vulnerability network, bridges, rail crossings, facilities under 100- 500-year scenarios at level. Additionally, we conduct detailed investigation into most flood-affected counties, focusing susceptibility bridges. Our state-wide reveals that 100-year scenario, up 9% railroads, 8% 58% 6% are impacted. these figures increase 16%, 14%, 61%, 13%, respectively. Further, our secondary using depth maps indicates approximately half bridges zones studied counties could become non-functional both scenarios. findings crucial developing effective disaster management plans strategies, ensuring adequate preparedness climate change impacts infrastructure.

Language: Английский

Comprehensive flood vulnerability analysis in urban communities: Iowa case study DOI
Yazeed Alabbad, İbrahim Demir

International Journal of Disaster Risk Reduction, Journal Year: 2022, Volume and Issue: 74, P. 102955 - 102955

Published: April 8, 2022

Language: Английский

Citations

63
A web-based analytical urban flood damage and loss estimation framework DOI
Yazeed Alabbad, Enes Yıldırım, İbrahim Demir

et al.

Environmental Modelling & Software, Journal Year: 2023, Volume and Issue: 163, P. 105670 - 105670

Published: March 7, 2023

Language: Английский

Citations

33
Social vulnerability and climate risk assessment for agricultural communities in the United States DOI
Tuğkan Tanır, Enes Yıldırım, Celso M. Ferreira

et al.

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 908, P. 168346 - 168346

Published: Nov. 6, 2023

Language: Английский

Citations

19
Flood susceptibility mapping using fuzzy analytical hierarchy process for Cedar Rapids, Iowa DOI

Beyza Atiye Cikmaz,

Enes Yıldırım, İbrahim Demir

et al.

International Journal of River Basin Management, Journal Year: 2023, Volume and Issue: 23(1), P. 1 - 13

Published: May 24, 2023

Floods affect over 2.2 billion people worldwide, and their frequency is increasing at an alarming rate compared to other disasters. Presidential disaster declarations have issued increasingly almost every year in Iowa for the past 30 years, indicating that state on rise of flood risk. A multi-disciplinary approach required, which underlying hydrologic processes cause floods are closely linked with watershed-level socio-economic functions using effective collaboration tools ensure community participation co-production mitigation plans while paying attention socio-environmental justice principles. Considering existing limitations needs, we conducted a risk assessment by utilizing geophysical datasets case study Cedar Rapids, Iowa. Flood outputs generated based three main groups: geophysical-based risk, socioeconomic combined An extensive literature review determine pairwise comparison matrices parameters used analytical hierarchy process (AHP) fuzzy AHP methods. Our results indicate high- very-high-risk susceptibility zones primarily located central urban areas lower elevations, regardless method type (AHP or FAHP). According overall results, large area Rapids consists medium level according map method. The show high very high-risk 16% studied region, medium, low low-risk correspond 84%. Besides, nearly 40% population lives zones.

Language: Английский

Citations

18
An interdisciplinary overview of levee setback benefits: Supporting spatial planning and implementation of riverine nature‐based solutions DOI Creative Commons
Charles B. van Rees, Matt Chambers, Angela J. Catalano

et al.

Wiley Interdisciplinary Reviews Water, Journal Year: 2024, Volume and Issue: 11(6)

Published: July 24, 2024

Abstract Nature‐based solutions (NbS, and related concepts like natural infrastructure, Ecosystem‐based Adaptation, green infrastructure) are increasingly recognized as multi‐benefit strategies for addressing the critical sustainability challenges of Anthropocene, including climate emergency biodiversity crisis. Mainstreaming NbS in professional practice requires strategic, landscape‐level planning integrating multiple sources benefits their synergies trade‐offs. Levee setbacks (LS) among best‐studied riverine with flood risk management, drought resilience, water quality recreational opportunities, ecological restoration biodiversity. Although awareness multifarious LS forms Natural Capital is growing, implementation remains ad‐hoc opportunistic. To address this gap one major example NbS, we review synthesize literature across diverse disciplines to provide an overview primary social, economic, mechanisms that affect co‐benefit delivery projects. Next, make information relevant practitioners, link these spatial metrics can be used approximate relative magnitude project costs mechanisms. Finally, highlight examples key trade‐offs should considered planning. This synthetic approach intended familiarize readers potential LS, understanding how select prioritize sites further study implementation. Synergies important benefit drivers abound, social equity concerns will paramount ensuring successful other future. article categorized under: Engineering Water > Sustainable Planning Life Nature Freshwater Ecosystems

Language: Английский

Citations

8
A web-based decision support framework for optimizing road network accessibility and emergency facility allocation during flooding DOI Creative Commons
Yazeed Alabbad, Jerry Mount, Ann Melissa Campbell

et al.

Urban Informatics, Journal Year: 2024, Volume and Issue: 3(1)

Published: March 8, 2024

Abstract Transportation systems can be significantly affected by flooding, leading to physical damage and hindering accessibility. Despite flooding being a frequent occurrence, there are limited accessible online tools available for supporting routing emergency planning decisions during flooding. Existing generally based on complicated models not easily non-expert users, highlighting the need efficient communication decision-making analyzing flood impacts transportation networks various stakeholders, including public, minimize adverse those groups. This paper presents web application that uses graph network methods latest technologies standards assist in describing events terms of operational constraints provide analytical support mobility mitigation these events. The framework is designed user-friendly, enabling users access information about road status, shortest paths critical amenities, location-allocation, service coverage. study area includes following two communities State Iowa, Cedar Rapids Charles City, which were used test application's functionality explore outcomes. Our research demonstrates affect bridge operation, from locations arbitrary point-to-point routing, facility placement, introduced solve complex flood-related decision tasks an understandable representation vulnerability, enhancing strategies. Therefore, this provides valuable tool stakeholders make informed

Language: Английский

Citations

7
Modeling of Harmful Algal Bloom Dynamics and Integrated Web Framework for Inland Waters in Iowa DOI Creative Commons
Özlem Baydaroğlu, Serhan Yeşilköy,

Anchit Dave

et al.

EarthArXiv (California Digital Library), Journal Year: 2024, Volume and Issue: unknown

Published: May 2, 2024

Harmful algal blooms (HABs) are one of the major environmental concerns, as they have various negative effects on public health, recreational services, ecological balance, wildlife, fisheries, microbiota, water quality, and economics. HABs caused by many sources, such pollution based agricultural activities, wastewater treatment plant discharges, leakages from sewer systems, natural factors like pH light levels, climate change impacts. While causes recognized, it is unknown how toxin-producing algae develop well key processes components that contribute to their weight due distinct dynamics each lake variety unpredictability conditions influencing these dynamics. Modeling in a changing essential for achieving sustainable development goals regarding clean sanitation. However, lack consistent adequate data significant challenge all studies. In this study, we employed sparse identification nonlinear (SINDy) technique model microcystin, an toxin, utilizing dissolved oxygen quality metric evaporation meteorological parameter. SINDy novel approach combines regression machine learning methods reconstruct analytical representation dynamical system. Moreover, model-driven web-based interactive tool was created disseminate education, raise awareness HAB events, produce more effective solutions problems through what-if scenarios. This web platform allows tracking status lakes observing impact specific parameters harmful formation. Users can easily share images user-friendly platform, allowing others view lakes.

Language: Английский

Citations

4
Comprehensive analysis of riverine flood impact on bridge and transportation network: Iowa case study DOI

E.B. Duran,

Yazeed Alabbad, Jerry Mount

et al.

International Journal of River Basin Management, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 14

Published: Jan. 29, 2025

Language: Английский

Citations

0
A Conversational Intelligent Assistant for Enhanced Operational Support in Floodplain Management with Multimodal Data DOI

Vinay Pursnani,

Yusuf Sermet, İbrahim Demir

et al.

International Journal of Disaster Risk Reduction, Journal Year: 2025, Volume and Issue: unknown, P. 105422 - 105422

Published: March 1, 2025

Language: Английский

Citations

0
High‐resolution flood probability mapping using generative machine learning with large‐scale synthetic precipitation and inundation data DOI Creative Commons
Lipai Huang, Federico Antolini, Ali Mostafavi

et al.

Computer-Aided Civil and Infrastructure Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: April 23, 2025

Abstract High‐resolution flood probability maps are instrumental for assessing risk but often limited by the availability of historical data. Additionally, producing simulated data needed creating probabilistic using physics‐based models involves significant computation and time effort, which inhibit its feasibility. To address this gap, study introduces Precipitation‐Flood Depth Generative Pipeline, a novel methodology that leverages generative machine learning to generate large‐scale synthetic inundation produce maps. With focus on Harris County, Texas, Pipeline begins with training cell‐wise depth estimator number precipitation‐flood events model model. This estimator, emphasizes precipitation‐based features, outperforms universal models. Subsequently, conditional adversarial network (CTGAN) is used conditionally precipitation point cloud, filtered strategic thresholds align realistic patterns. Hence, feature pool constructed each cell, enabling sampling generation events. After generating 10,000 events, created various depths. Validation similarity correlation metrics confirms accuracy distributions. The provides scalable solution high‐resolution maps, can enhance mitigation planning.

Language: Английский

Citations

0