The following paper about the key factors for climate change impacts on oyster aquaculture has been recently accepted for publication by Environmental Research.
Neokye, E. O., X. Wang, K. K. Thakur, P. Quijon, R. A. Nawaz, and S. Basheer. Climate Change Impacts on Oyster Aquaculture – Part I: Identification of Key Factors. Environmental Research, accepted on February 25, 2024.
More details will come soon once the paper is published.
A special issue on “Building Flood Resilience Under Climate Change” edited by Dr. Wang has now been published with Frontiers in Environmental Science. More details about this special issue can be found at: https://www.frontiersin.org/research-topics/36839/building-flood-resilience-under-climate-change/magazine.
Title: Real-time peak flow prediction based on signal matching
Journal: Environmental Modelling & Software
DOI: https://doi.org/10.1016/j.envsoft.2023.105926
Abstract: Real-time peak flow prediction under heavy precipitation is critically important for flood emergency evacuation planning and management. In the case of emergency evacuation, every second matters as a slightly longer lead time could save more lives and reduce the associated social, economic, and health impacts. Here, we present a model (named SIGMA) based on the principle of signal matching to facilitate real-time peak flow prediction at sub-hourly scales (e.g., minutes to seconds). The SIGMA model divides the target watershed into small zones and the heavy precipitation falling into each zone is collected into a small water tank. As the water tank moves downstream and arrives in the watershed outlet, it will discharge the collected precipitation and generate a small single-pulse streamflow signal. By combining all small signals coming from all zones within the watershed, we will be able to generate a synthesized peak flow signal. The proposed model is applied to simulate the peak flow events observed in a real-world watershed to verify its effectiveness in real-time flood prediction. The results suggest that the presented model can reasonably predict three key aspects of a peak flow event, including the peak flow rate, the arrival time of peak flow, and the duration of the peak flow event. The proposed model is demonstrated to be effective in real-time flood prediction and can be used to support flood emergency evacuation planning and management.
Title: Effective Communication of Coastal Flood Warnings: Challenges and Recommendations
Journal: Sustainability
DOI: https://doi.org/10.3390/su152416693
Abstract: With the increasing risk of coastal flooding facing coastal communities due to climate change, coastal flood warnings (CFWs) are expected to play a critical role in the protection of people and property to ensure communities’ sustainable development. However, as destructive coastal flooding hazards have caused considerable damage in recent years, the effectiveness of coastal flooding warnings could be questioned considering their objective of disaster risk reduction. Here, we deliver a review investigation of the current CFWs in the USA and Canada based on their setup and dissemination, and a case study of two representative coastal flooding events. Through this review, we found that collaboration between multi-level administration regarding CFW mechanisms has the potential to strengthen these mechanisms, improving their efficacy. We also found that CFWs presented in the media often lacked consideration of public acceptance and practicability in their reports, which may have affected the performance of these CFWs. Meanwhile, the technological limitations and uncertain public acceptance may also reduce the CFWs’ effectiveness in application. Accordingly, the media should further consider the understandability of CFW-related reports. Moreover, emergency information channels should be set in both traditional media and social media for accessible use by residents with different customs. Lastly, starting from the normalized prevention of coastal flood disaster, a consensus of crisis awareness should be built with which the social aspects of the defense against coastal flooding can be established for future environmental sustainability.
The following paper about a new model for real-time peak flow prediction based on signal matching has recently accepted for publication by Environmental Modelling & Software.
Wang, X., Q. V. Dau, and F. Aziz. Real-Time Peak Flow Prediction Based on Signal Matching. Environmental Modelling & Software, accepted on December 5, 2023.
More details will come soon once the paper is published.