Developing a hybrid modeling and multivariate analysis framework for storm surge and runoff interactions in urban coastal flooding DOI
Ahad Hasan Tanim, Erfan Goharian

Journal of Hydrology, Journal Year: 2020, Volume and Issue: 595, P. 125670 - 125670

Published: Oct. 21, 2020

Language: Английский

Causes, impacts and patterns of disastrous river floods DOI
Bruno Merz, Günter Blöschl, Sergiy Vorogushyn

et al.

Nature Reviews Earth & Environment, Journal Year: 2021, Volume and Issue: 2(9), P. 592 - 609

Published: Aug. 10, 2021

Language: Английский

Citations

434

From local to regional compound flood mapping with deep learning and data fusion techniques DOI Creative Commons
David F. Muñoz, Paúl Muñoz, Hamed Moftakhari

et al.

The Science of The Total Environment, Journal Year: 2021, Volume and Issue: 782, P. 146927 - 146927

Published: April 6, 2021

Language: Английский

Citations

124

An Overview of Flood Concepts, Challenges, and Future Directions DOI
Ashok K. Mishra,

Sourav Mukherjee,

Bruno Merz

et al.

Journal of Hydrologic Engineering, Journal Year: 2022, Volume and Issue: 27(6)

Published: March 24, 2022

This review provides a broad overview of the current state flood research, challenges, and future directions. Beginning with discussion flood-generating mechanisms, synthesizes literature on forecasting, multivariate nonstationary frequency analysis, urban flooding, remote sensing floods. Challenges research directions are outlined highlight emerging topics where more work is needed to help mitigate risks. It anticipated that systems will likely have significant risk due compounding effects continued climate change land-use intensification. The timely prediction floods, quantification socioeconomic impacts developing mitigation strategies continue be challenging. There need bridge scales between model capabilities end-user needs by integrating multiscale models, stakeholder input, social citizen science input for monitoring, mapping, dissemination. Although much progress has been made in using applications, recent upcoming Earth Observations provide excellent potential unlock additional benefits applications. community can benefit from downscaled, as well ensemble scenarios consider changes. Efforts also data assimilation approaches, especially ingest local, citizen, media data. Also enhanced compound hazards assess reduce vulnerability impacts. dynamic complex interactions climate, societal change, watershed processes, human factors often confronted deep uncertainty highlights transdisciplinary science, policymakers, stakeholders vulnerability.

Language: Английский

Citations

96

Performance synergism of pervious pavement on stormwater management and urban heat island mitigation: A review of its benefits, key parameters, and co-benefits approach DOI
Junsong Wang,

Qinglin Meng,

Zou Ya

et al.

Water Research, Journal Year: 2022, Volume and Issue: 221, P. 118755 - 118755

Published: June 14, 2022

Language: Английский

Citations

88

Flood Detection in Urban Areas Using Satellite Imagery and Machine Learning DOI Open Access
Ahad Hasan Tanim,

Callum Blake McRae,

Hassan Tavakol-Davani

et al.

Water, Journal Year: 2022, Volume and Issue: 14(7), P. 1140 - 1140

Published: April 1, 2022

Urban flooding poses risks to the safety of drivers and pedestrians, damages infrastructures lifelines. It is important accommodate cities local agencies with enhanced rapid flood detection skills tools better understand how much a region may experience at certain period time. This results in management orders being announced timely manner, allowing residents preemptively avoid flooded areas. research combines information received from ground observed data derived road closure reports police department, remotely sensed satellite imagery develop train machine-learning models for City San Diego, CA, USA. For this purpose, are extracted Sentinel 1 fed into various supervised unsupervised machine learning models, including Random Forest (RF), Support Vector Machine (SVM), Maximum Likelihood Classifier (MLC), detect pixels images evaluate performance these ML models. Moreover, new framework developed which works based on change (CD) approach Otsu algorithm, fuzzy rules, iso-clustering methods urban detection. Results evaluation RF, SVM, MLC CD show 0.53, 0.85, 0.75 0.81 precision measures, 0.9, 0.85 0.9 recall values, 0.67, 0.79 F1-score, 0.69, 0.87, 0.83 0.87 accuracy measure, respectively, each model. In conclusion, image classification method offers least required computational time mapping. systematic will be potentially useful other risk flooding, hopefully detecting nuisance floods, by using reducing transportation design infrastructure planning.

Language: Английский

Citations

79

A comprehensive review on pervious concrete DOI
Mostafa Adresi, Alireza Yamani, Mojtaba Karimaei Tabarestani

et al.

Construction and Building Materials, Journal Year: 2023, Volume and Issue: 407, P. 133308 - 133308

Published: Sept. 30, 2023

Language: Английский

Citations

61

Forecasting Multi-Step-Ahead Street-Scale nuisance flooding using seq2seq LSTM surrogate model for Real-Time applications in a Coastal-Urban city DOI Creative Commons
Binata Roy, Jonathan L. Goodall, Diana McSpadden

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 132697 - 132697

Published: Jan. 1, 2025

Language: Английский

Citations

5

Exploring infiltration effects on coastal urban flooding: Insights from nuisance to extreme events using 2D/1D hydrodynamic modeling and crowdsourced flood reports DOI Creative Commons
Sergio A. Barbosa,

Yidi Wang,

Jonathan L. Goodall

et al.

The Science of The Total Environment, Journal Year: 2025, Volume and Issue: 968, P. 178908 - 178908

Published: Feb. 22, 2025

Language: Английский

Citations

2

Understanding of Contemporary Regional Sea‐Level Change and the Implications for the Future DOI
B. D. Hamlington, Alex Gardner, Erik R. Ivins

et al.

Reviews of Geophysics, Journal Year: 2020, Volume and Issue: 58(3)

Published: April 17, 2020

Abstract Global sea level provides an important indicator of the state warming climate, but changes in regional are most relevant for coastal communities around world. With improvements to sea‐level observing system, knowledge change has advanced dramatically recent years. Satellite measurements coupled with situ observations have allowed comprehensive study and improved understanding diverse set drivers that lead variations space time. Despite advances, gaps contemporary remain inhibit ability predict how processes may future change. These arise part due complexity linkages between Here we review individual which then describe they combine vary regionally. The intent paper is provide overview current cause identify discuss limitations uncertainty our these processes. Areas where lack or needed information planning efforts particular focus. Finally, a goal this highlight role expanded observation network—particularly as related satellite observations—in scientific contributors

Language: Английский

Citations

134

Learning from Floods: Linking flood experience and flood resilience DOI

Da Kuang,

Kuei‐Hsien Liao

Journal of Environmental Management, Journal Year: 2020, Volume and Issue: 271, P. 111025 - 111025

Published: July 6, 2020

Language: Английский

Citations

114