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Urban communities in environmentally sensitive areas face escalating challenges due to climate change and inadequate infrastructural support, particularly in underserved regions like southside Norfolk, Virginia. This area, characterized by its vulnerability to flooding and a predominantly low-income population, lacks equitable inclusion in broader urban flood protection plans. This research focuses on the development of community-centered resilience strategies through active engagement and collaboration with local residents. The methodology centered around building trust and understanding within the community through a series of interactions and events. This approach facilitated a two-way exchange of information, enabling the research team to gather crucial insights on community-valued assets, prevalent flooding issues, and preferred flood mitigation solutions. The engagement revealed a significant increase in community knowledge regarding climate change, sea level rise, and stormwater management. Residents expressed a strong preference for green infrastructure solutions, including rain gardens, permeable pavements, and living shorelines, alongside concerns about pollution and the need for infrastructure redesign. The outcomes of this community engagement have initiated plans to develop tailored, nature-based flooding solutions. These results are set to inform future urban planning and policy, offering insights to the City of Norfolk and the United States Army Corps of Engineers for potential redesigns of flood intervention strategies that are more inclusive and effective. A template for participatory research to inform coastal hazard management includes cross-sector collaboration, a long-term engagement commitment, and education and surveying opportunities to align solutions to lived, local experiences. This template allows for community trust building, which is especially important in environmental justice communities. The study highlights the importance of community involvement in urban resilience planning, demonstrating that local engagement is essential in shaping community-centric solutions and equitable environmental policies. [ABSTRACT FROM AUTHOR]

Floodplain characteristics contribute to the natural regeneration of vegetation and help facilitate their ecosystem recovery but vary within and between river systems and more so in a river system recovering from anthropogenic disturbances. Here, we explored the floodplain characteristics that contribute to the woody vegetation regeneration on point bars of the middle reach of the Apalachicola River in Florida, USA, which has been passively recovering for over two decades after dredging and disposal activities ended. Woody vegetation regeneration on point bars was analysed using 1999 and 2019 aerial imagery and divided into zones and sections. Data were extracted from a digitized geodatabase regarding several floodplain characteristics with potential to influence vegetation regenetation. Later, we analysed noncollinear floodplain characteristics using a random forest (RF) regression model. The top characteristics that contributed to the RF model include vegetation density, distance‐to‐seeding source and bend curvature. Findings suggest that high vegetation density contributes substantially to woody vegetation regeneration. The negative relationship between distance‐to‐seeding source and vegetation regeneration shows the importance of seeding availability. The bend curvature corresponds with the highest regeneration in the lowermost section of point bars. Our results signify the importance of maintaining healthy vegetated corridors as a buffer to reinforce the vegetation community and potential seed source for passive recovery. These findings regarding floodplain characteristics can be applied to future active restoration of anthropogenically disturbed floodplains. [ABSTRACT FROM AUTHOR]

Numerous studies have concentrated on developing user-centered designs for hazard zone maps but rarely for hazard-oriented geomorphological maps, named as Geomorphological Hazard Thematic Maps (GHTMs) in this study, which provide more detailed information about natural hazards. This study developed a user-centered mapping design for GHTMs for nonexperts in geomorphology. We invited civil engineers and high school educators to evaluate a sample GHTM’s design in group and focus group panel interviews. The civil engineers preferred maps with more geomorphological features, whereas the educators preferred simple designs. Both groups indicated that the inclusion of essential facilities and road networks is essential. The map was also adjusted by adding hillshade layer and by changing the symbology for mass wasting, fault scarps, and fluvial features to increase clarity and simplicity. This case study is the first step toward developing user-centered mapping designs for hazard communication that will deepen their understanding of natural hazards. [ABSTRACT FROM AUTHOR]

Hydrological drought forecasting is essential for effective water resource management planning. Innovations in computer science and artificial intelligence (AI) have been incorporated into Earth science research domains to improve predictive performance for water resource planning and disaster management. Forecasting of future hydrological drought can assist with mitigation strategies for various stakeholders. This study uses the transformer deep learning model to forecast hydrological drought, with a benchmark comparison with the long short-term memory (LSTM) model. These models were applied to the Apalachicola River, Florida, with two gauging stations located at Chattahoochee and Blountstown. Daily stage-height data from the period 1928–2022 were collected from these two stations. The two deep learning models were used to predict stage data for five different time steps: 30, 60, 90, 120, and 180 days. A drought series was created from the forecasted values using a monthly fixed threshold of the 75th percentile (75Q). The transformer model outperformed the LSTM model for all of the timescales at both locations when considering the following averages: M S E = 0.11 , M A E = 0.21 , R S M E = 0.31 , and R 2 = 0.92 for the Chattahoochee station, and M S E = 0.06 , M A E = 0.19 , R S M E = 0.23 , and R 2 = 0.93 for the Blountstown station. The transformer model exhibited greater accuracy in generating the same drought series as the observed data after applying the 75Q threshold, with few exceptions. Considering the evaluation criteria, the transformer deep learning model accurately forecasts hydrological drought in the Apalachicola River, which could be helpful for drought planning and mitigation in this area of contested water resources, and likely has broad applicability elsewhere. [ABSTRACT FROM AUTHOR]

Lowland coastal plain rivers are important for navigation and ecosystems, having unique concerns regarding water and sediment management. The Apalachicola River in Florida, the lower end of the ACF (Apalachicola–Chattahoochee–Flint) system, had historical modifications beginning in the 1800s. Most impacts are attributable to the Apalachicola Navigation Project in the latter half of the 20th century, which included dredging, disposal, rock and snag removal, artificial cutoffs, and wing‐dike building. As one of few studies using paired hydrographic surveys over a long reach and time (170 km, 50 years), we defined four zones of bed elevation change between 1960 and 2010 based on the cumulative thalweg elevation plots. The river has four bed change zones: (1) uppermost, marked degradation from river mile (RM) 106 to 85 because of dam construction; (2) middle, minimal degradation from RM 85 to 34; (3) artificial cutoff zone, highest degradation, from RM 34 to 27; and (4) lowermost zone, aggradation from RM 27 to Apalachicola Bay because of upstream bed and bank sediment disturbances. Artificial cutoffs and lithology influence lateral migration, with rates being highest in cutoff zones and least in areas with some bedrock upstream and finer sediments downstream. Length changes from 1941 to 2019 are stable, except for the middle reach, which lengthened nearly 10%, and the lower non‐tidal reach, where length shortened with cutoffs then regained in subsequent decades. Minimizing disturbance has led to 18% of the sand bar area revegetating since a decade of dredging ended. This framework helps in understanding historic and ongoing human activities, notably upstream water consumption, connectivity changes, sediment inputs, and climate change, that will affect the water and sediment management of the river, its floodplain, and bay, thus varying approaches for restoration. [ABSTRACT FROM AUTHOR]

Anthropogenic impacts in large rivers are widely studied, but studies of recovery once a disturbance has stopped are uncommon. This study examines the biogeomorphic recovery of a 40‐km river corridor on the mid‐Apalachicola River, Florida following the cessation of dredging, disposal, and snag removal in 2002. This failed navigation project resulted in vegetation losses (~166 ha between 1941 and 2004), river widening, and increased point bar areas. We used paired sets of imagery for a 10‐year period during the recovery process at two different flow levels to assess sand bar change, land cover change, and their spatial variations. Most large sand bars decreased significantly in area due to growth of pioneer species, typically from the bankside of the bar. Mean bar area shrank 0.17 and 0.20 ha for the 30th and 1st percentile flows, respectively. For the entire study area, both water‐level comparisons showed gains in vegetation (23.36 and 15.83 ha), compensated by losses in the extent of water (16.83 and 8.55 ha) and sand bar losses (6.53 and 7.28 ha). Overall, these gains during the 10‐year passive recovery period are equivalent to ~15% of the vegetation losses that resulted from the navigational dredging. As found in other studies, most of the pioneer vegetation grew approximately 2 m relative elevation above the low‐water surface. The initial length of the tree line and the area of herbaceous growth both had a significant and positive relationship with the area of new vegetation growth over the study interval. As parts of the river are healing, reduced channel capacity from narrowing and tree growth will benefit the floodplain. As elsewhere, understanding of a river's biogeomorphology, hydrology, and disturbance history can help in selecting appropriate recovery metrics to further advance the understanding and management of disturbed floodplains. © 2020 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Alluvial river landscapes of the lower Mississippi and Atchafalaya rivers in the south-central USA are flood prone and have shifted historically in position and form, resulting in interventions for flood reduction, navigation, and water supply. Fisk mapped these landscapes in the middle of the twentieth century as a series of artistic colourful map plates. Selected areas are revisited with modern data sets (LiDAR from 2003, hydrographic surveys from 2006 and 2007) including two sites along the Mississippi River (near the Old River juncture and near Morganza Floodway) and one in the middle Atchafalaya River. By using 2D and 3D geovisualization, we find that the extent, variety, and dimensions of anthropogenic landforms have grown in prominence since Fisk's mapping. The volumes of the highest positive landforms are quantified to provide some indication of direct and indirect anthropogenic activity in these landscapes. [ABSTRACT FROM AUTHOR]