Special Issue "Flood Risk Assessment in Urban Areas"

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Hydrogeology".

Deadline for manuscript submissions: closed (15 December 2020) | Viewed by 1998

Special Issue Editor

Dr. Usman T. Khan
E-Mail Website
Guest Editor
Department of Civil Engineering, York University, Toronto, ON M3J, Canada
Interests: urban hydrology; flood risk assessment; hydroinformatics; data-driven modelling; uncertainty analysis; stormwater management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

More than half the global population now lives in urban areas, a trend that is expected to continue as more people move from rural areas to cities. Estimates suggest that 68% of the global population will live in urban areas by 2050. Urban growth is projected to occur across the board: megacities, major cities, as well as regional and mid-sized cities. These projected increases in urban population will lead to rapid urbanization and, when coupled with climate change, will lead to an increase in flood risk. This is due to multiple factors: changes in the flood hazard, an increase in exposure to flood hazards, and an increase in social vulnerability of populations within cities. Thus, innovative flood risk assessment tools must be developed to address each of these components to assist decision-makers, engineers, and urban planners to manage, mitigate, and reduce flood risk in urban areas.

Thus, for this Special Issue, I invite submissions of original research papers, rapid communications, technical notes, review articles, and discussions on topics related to the latest advances in flood risk assessment in urban areas including, but not limited to:

  • Geospatial techniques for flood risk assessment
  • Flood risk mapping at various spatial and temporal scales
  • Integration of flood hazard, exposure, and vulnerability
  • Uncertainty in flood risk estimates and assessment
  • Real-time and crowd-sourced data for flood risk assessment
  • Early warning systems and decision support systems for flood risk assessment
  • Flood risk assessment under changing climate and urbanization scenarios
  • Data-driven approaches for flood forecasting, mapping, and assessment

Dr. Usman T Khan
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • flood risk
  • urban hydrology
  • geospatial techniques
  • flood risk mapping
  • climate change
  • urbanization
  • flood exposure
  • flood hazard
  • flood vulnerability

Published Papers (1 paper)

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Research

Article
Flood Hazard Estimation under Nonstationarity Using the Particle Filter
Geosciences 2021, 11(1), 13; https://doi.org/10.3390/geosciences11010013 - 29 Dec 2020
Cited by 1 | Viewed by 1417
Abstract
The presence of the nonstationarity in flow datasets has challenged the flood hazard assessment. Nonstationary tools and evaluation metrics have been proposed to deal with the nonstationarity and guide the infrastructure design and mitigation measures. To date, the examination of how the flood [...] Read more.
The presence of the nonstationarity in flow datasets has challenged the flood hazard assessment. Nonstationary tools and evaluation metrics have been proposed to deal with the nonstationarity and guide the infrastructure design and mitigation measures. To date, the examination of how the flood hazards are affected by the nonstationarity is still very limited. This paper thus examined the association between the flood hazards and the nonstationary patterns and degrees of the underlying datasets. The Particle Filter, which allows for assessing the uncertainty of the point estimates, was adopted to conduct the nonstationary flood frequency analysis (NS-FFA) for subsequently estimating the flood hazards in three real study cases. The results suggested that the optimal and top NS-FFA models selected according to the fitting efficiency in general align with the pattern of nonstationarity, although they might not always be superior in terms of uncertainty. Moreover, the results demonstrated the association and the sensitivity of the flood hazards to the perceived patterns and degrees of nonstationarity. In particular, the variations of the flood hazards intensified with the increase in the degree of nonstationarity, which should be assessed in a more elaborate manner, i.e., considering multiple statistical moments. These advocate the potential of using the nonstationarity characteristics as a proxy for evaluating the evolutions of the flood hazards. Full article
(This article belongs to the Special Issue Flood Risk Assessment in Urban Areas)
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