Journal of Hydrology, Journal Year: 2020, Volume and Issue: 595, P. 125670 - 125670
Published: Oct. 21, 2020
Language: Английский
Journal of Hydrology, Journal Year: 2020, Volume and Issue: 595, P. 125670 - 125670
Published: Oct. 21, 2020
Language: Английский
Nature Reviews Earth & Environment, Journal Year: 2021, Volume and Issue: 2(9), P. 592 - 609
Published: Aug. 10, 2021
Language: Английский
Citations
434The Science of The Total Environment, Journal Year: 2021, Volume and Issue: 782, P. 146927 - 146927
Published: April 6, 2021
Language: Английский
Citations
124Journal 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
96Water Research, Journal Year: 2022, Volume and Issue: 221, P. 118755 - 118755
Published: June 14, 2022
Language: Английский
Citations
88Water, 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
79Construction and Building Materials, Journal Year: 2023, Volume and Issue: 407, P. 133308 - 133308
Published: Sept. 30, 2023
Language: Английский
Citations
61Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 132697 - 132697
Published: Jan. 1, 2025
Language: Английский
Citations
5The Science of The Total Environment, Journal Year: 2025, Volume and Issue: 968, P. 178908 - 178908
Published: Feb. 22, 2025
Language: Английский
Citations
2Reviews 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
134Journal of Environmental Management, Journal Year: 2020, Volume and Issue: 271, P. 111025 - 111025
Published: July 6, 2020
Language: Английский
Citations
114