For the 8th biennial UF Water Institute Symposium, the CCS has organized a comprehensive and diverse program of 3 sessions and 2 expert panels that explore what the future of coastal water quality monitoring, modeling, management, and policy should/could look like from a technological, scientific and engineering perspective, as well as through a management and policy lens. The Symposium, hosted by the UF Water Institute, will be held February 22 – 23 and brings together individuals from a broad range of disciplines and organizations to explore water issues from multiple perspectives.
Center for Coastal Solutions Program
|Feb 22, 2022 CCS 1: The Role of Data Fusion and Artificial Intelligence in Transforming Coastal Hazard Detection and Monitoring
|10:30am||Moderator: Zhe Jiang, UF||Introduction|
|10:35am||Barbara Kirkpatrick, Gulf Coast Ocean Observing System (GCOOS)||Data Aggregation, Citizen Science, and AI – Oh My!|
|11:05 am||Zhe Jiang, Computer & Information Science & Engineering, UF
||Spatiotemporal Machine Learning for Hydrology: A Couple of Examples|
|11:20am||Ronald Fick, UF||Fusing Remote Sensing Data with Spatiotemporal in Situ Samples for Red Tide Detection|
|11:35am||Guangming Zheng, UMD, NOAA/NESDIS/ Center for Satellite Applications and Research||Hypoxia Forecast in the Chesapeake Bay using CNN and LSTM|
|Feb 22, 2022 CCS 2: Unlocking Benthic-Pelagic Coupling Controls of Coastal Eutrophication|
|1:00pm||Moderators: Ashley Smyth & Betty Staugler, UF/IFAS||Introduction|
|1:05pm||Jim Fourqurean, Florida International University||Decomposition and Lability of Soil Organic Matter and Carbon Stocks across a Seagrass Landscape|
|1:35 pm||Chris Anastasiou, Southwest Florida Water Management District||The Hangover Effect: Coupling Seagrass Loss, Macroalgal Growth, & Water Quality in Charlotte Harbor|
|1:50pm||Annie Murphy, INSPIRE
|Human-Facilitated Bivalve Populations Effects on Energy and Nitrogen Flow Through Marine Ecosystems|
|2:05pm||Ashley Smyth, UF|
|Feb 23, 2022 CCS 3: Improving the Condition of Coastal Ecosystems through Collaboration: A Panel Discussion of Lessons from Decades of Estuarine Nutrient Assessment and Management|
|8:30am||Moderator: Elise Morrison, UF||Panel Introduction|
|8:35am – 9:50am||Ed Sherwood, Director, Tampa Bay Estuary Program
David Tomasko, Director, Sarasota Bay Estuary Program
Matt Posner, Director, Pensacola and Perdido Bays Estuary Program
|Feb 23, 2022 CCS 4: The Frontier of Earth Systems Modeling for Hazard Prediction & Management|
|10:30am||Moderators: Maitane Olabarrieta & David Kaplan, UF
|10:35am||Ben Kirtman, University of Miami||Global High-Resolution Earth System Models Representation of Regional Climate Change and Variability|
|11:05 am||Xingyuan Chen, Pacific Northwest National Laboratory||Integrated Modeling of Carbon and Nitrogen Cycling in River Corridors and Watersheds|
||John Warner, USGS & Maitane Olabarrieta, UF||Advancements of a Coupled Ocean Nearshore Forecasting System|
|Feb 23, 2022 CCS 5: Accelerating the Infusion of Science in Coastal Policy – A Panel|
|1:00pm||Moderator: Tom Ankersen, UF Levin College of Law||Panel Introduction|
|1:05pm – 2:20pm||Annie Brett, UF Levin College of Law
Rachel Silverstein, Miami Waterkeeper
Adam Blalock, FL Department of Environmental Protection
Christine Angelini, UF College of Engineering
CCS 1: The Role of Data Fusion and Artificial Intelligence in Transforming Coastal Hazard Detection and Monitoring
Moderator: Zhe Jiang, University of Florida
Gulf Coast Ocean Observing System (GCOOS)
The Gulf of Mexico Coastal Ocean Observing System Regional Association’s mission is to provide information about the Gulf’s coastal and open waters on demand that is accurate, reliable, and benefits people ecosystems and the economy. GCOOS has used several strategies to push forward this mission. The first, is the aggregation of ocean data and making it openly accessible to all. Most people think of real time physical oceanography data (currents, temperature, and salinity) however, GCOOS has also aggregated a lot of historical or legacy data. To achieve the spatial and temporal coverage needed for informed decision making, GCOOS has empowered citizen scientists to assist in data collection/observations. Finally, the use of artificial intelligence, or AI, is being used to analyze large datasets in new novel ways. Specific examples of how GCOOS has used these three strategies will be discussed.
UF Department of Computer & Information Science & Engineering
With rapidly increasing spatiotemporal data being collected from remote sensing and simulation models, there is a growing need for machine learning (ML) techniques to analyze such rich spatiotemporal data in Earth science (e.g., national water resource management, disaster response). However, spatiotemporal data poses unique challenges in ML, such as spatial and temporal autocorrelation, heterogeneity, paucity of ground truth, and the existence of domain constraints. This talk will demonstrate some novel spatiotemporal ML techniques in the context of flood inundation mapping and National Hydrography Dataset refinement.
UF Department of Computer & Information Science & Engineering
A novel method for combining remote sensing data with spatiotemporally distributed in situ water samples was developed to detect red tide (Karenia brevis) blooms off the southwest coast of Florida. The neural network classifier detects blooms (100,000 cells/L) over a 1 km grid, using six depthnormalized ocean color features from the full lifespan of the MODIS-Aqua remote sensing platform (2002-2021) and in situ red tide sample data collected by the Florida Fish and Wildlife Conservation Commission (FWC). The in-situ data were used to label the remotely sensed data for training and to generate a feature encoding recent, nearby ground truth (K. brevis concentrations) through a KNN spatiotemporal proximity weighting scheme. The network trained on both remotely sensed data and in situ data provided greater detection performance than either network trained on a single dataset, and the classifier outperformed several existing bloom detection methods. All code for this method is available on Github. (https://github.com/Compcon-UF/red-tide-ML).
UMD, NOAA/NESDIS/ Center for Satellite Applications and Research
Seasonal hypoxia has been a persistent threat for ecosystems and fisheries in the Chesapeake Bay. Hypoxia forecast based on coupled hydrodynamic and biogeochemical models has proven useful for fisheries management. These models excel in accounting for the effects of physical forcings on oxygen supply, but are not as good at predicting oxygen demand associated with decay of organic matter. Therefore, the accuracy of hypoxia forecast can be potentially improved with satellite-derived water color data which may help constrain the surface concentration of organic matter. Owing to the optical complexity, however, it is not straightforward to extract organic matter information from water color data in a robust fashion. A promising approach to address this issue is to use deep learning which is great at building end-to-end applications. By training a deep neural network with data of all variables that could affect dissolved oxygen (DO) concentration in the water column, improvement of hypoxia forecast is possible. Here we attempt to predict dissolved oxygen concentration with input data that account for both physical and biogeochemical factors. The physical factors are characterized by the 3-D outputs of a hydrodynamic model, which include the current velocity, water temperature, and salinity, as well as wind velocity. The biogeochemical factors are characterized by satellite-derived spectral reflectance data. Both physical and biogeochemical data are sampled on a weekly basis up to 8 weeks before the observation date of each field measured DO, which is obtained from the Chesapeake Bay Program. In total, we obtained 150,656 training examples from 2002-2018, and used data from the period of 2019-2020 for testing. We adopted a model architecture of combined convolutional neural network (CNN) and long short-term memory (LSTM) with 8 time steps. At each time step, a set of CNNs are used to extract information from the input data. This architecture mimics the evolution process of DO in natural waters. Our approach represents an innovative application of deep learning to solving water quality problems.
CCS 2: Unlocking Benthic-Pelagic Coupling Controls of Coastal Eutrophication
Moderators: Ashley Smyth & Betty Staugler, UF/IFAS
Florida International University
The paradigm for understanding the accumulation of organic carbon (Corg ) in coastal “blue carbon” habitats holds that burial of Corg slows decomposition and leads to stability of carbon stocks. Further, it is generally assumed that the presence of the plant communities contributes to the buried organic matter and the stability of the carbon stocks. This study tested these assumptions and examined the lability of soil Corg as a function of environmental and plant community drivers. Samples of surficial sediment and seagrass community characteristics were collected at 93 locations across the ca. 15,000 km2 of seagrass beds in south Florida. Ramped pyrolysis was used to describe the relative lability of soil organic carbon across the landscape. Organic matter (OM) was lost at all temperatures from 180° C to 600° C, suggesting that even the relatively high combustion temperature of 550° C underestimates OM content by ≈ 10% on average. Additionally, deployments of model substrates (canvas strips) were used to examine decomposition rates of buried and surficial organic material at a subset of these sites. On average, finer, muddier soils contained slightly higher Corg stocks than coarser sediment sites, but the relationships between sediment grain size and seagrass community structure was weak. The lability of soil organic carbon varied with grain size; as much as 80% of the Corg was refractory in coarse-grained soils compared to less than 30% in muddy soils. In muddy soils, burial decreased cellulose decomposition rate by an average of 22 – 39 % compared to surficial breakdown, but in coarse-grained soils, burial enhanced cellulose decomposition rate by at least 55 %. Taken as a whole, this study suggests that burial does not enhance Corg storage in all blue carbon environments, and that soil C stores are only weakly correlated with seagrass biomass at the landscape scale.
Southwest Florida Water Management District
Charlotte Harbor, in southwest Florida, is the second largest open water estuary in Florida with a surface area of approximately 700 square kilometers. From 1988 to 2018, seagrass coverage remained relatively stable between roughly 7,000 and 8,000 hectares. In 2020, seagrass coverage reached its lowest levels in 32 years, since the Southwest Florida Water Management District began mapping seagrass. Between 2018 and 2020, the Harbor lost an unprecedented 1,798 hectares of seagrass. Most notably, the east side of Charlotte Harbor, known as “the east wall,” lost half (712 hectares) of its seagrass. Concurrent with seagrass loss was an explosion of drift and attached benthic macroalgae. This relatively sudden shift from seagrass to macroalgae occurred in the wake of a protracted regional red tide event that lasted approximately 15 months from October 2017 to January 2019. While red tide was extreme in many coastal areas along southwest Florida, the east wall was largely spared direct impact. We hypothesize that seagrass loss and macroalgal proliferation along the east wall was not a direct result of red tide, rather it was a function of its aftermath, a phenomenon we term “the hangover effect.” During and after the major red tide event, massive amounts of nutrients from dead and decaying organisms were likely released into the water column. Many of these nutrients through the process of denitrification would have become bioavailable in the water column which were then rapidly assimilated by the macroalgae. We utilize seagrass maps, aerial imagery, water quality data, and hydrodynamic modeling to support the idea that “the hangover effect” at least in part led to the greatest loss of seagrass in Charlotte Harbor in over 30 years.
Eutrophication, the increased supply of organic matter to a system, is often attributed to excess nutrient inputs and can lead to detrimental effects such as low oxygen and habitat loss. However, coastal sediments harbor microbial communities capable of transforming bioavailable nitrogen into inert gas (i.e. denitrification), thus potentially mediating eutrophication. For example, filter-feeding bivalves have been recognized as important facilitators of nitrogen removal by enhancing denitrification in sediments. This talk will explore controls on this critical microbial metabolism using clam aquaculture as a model system. Surprising results showed that, on a local scale, high densities of clams can be a source of nitrogen by facilitating nitrogen recycling and promoting dissimilatory nitrate reduction to ammonium (DNRA), a microbial pathway that competes with denitrification. Depending on the ultimate source of phytoplankton supporting the cultivated bivalves, these filter-feeders may serve as a noncanonical bottom-up control on primary production on a local scale. Since denitrification removes nitrogen while DNRA recycles it, understanding what controls the partitioning between these microbial pathways and how this dynamic may shift in response to changes such as organic matter input, nutrient addition, or salinity is essential to predicting how key ecosystem services will change over time. This is one example where suspension feeders have tremendous influence on these microbial nitrogen transformations, resulting in dramatic shifts in the energy flow through the ecosystem. Another example where anthropogenic activity may result in changes to populations of benthic filter-feeders is the development of offshore wind. The talk will conclude by discussing how shifts in the benthic community associated with the introduction of wind turbine foundations as novel structures may have large impacts to the energy flow of both the pelagic and benthic compartments of the northwest Atlantic outer continental shelf.
Soil and Water Sciences, University of Florida
Sponges dramatically alter ecosystem water quality by combining extraordinary pumping rates and rapid, dynamic biogeochemical transformations. Large-scale sponge die-offs in the nearshore waters of the Florida Keys have led to a deficit in water filtration capacity, affecting water clarity. Rapid rates of organic matter remineralization by some sponge species can make them critical sources of dissolved inorganic nitrogen (DIN) in tropical ecosystems. Given the importance of nitrogen (N) for controlling primary production, there is a need to understand the influence sponges have on N in the surrounding water column. The overarching goal of this research is to establish the rates and mechanisms of spongemediated N cycling processes in Florida Bay by quantifying DIN transformations for 3 sponge species. Specifically, we measured net fluxes of N2, ammonium, and nitrite+nitrate associated with glove (Spongia cheiris), loggerhead (Spheciospongia vesparium), and sheepswool (Hippospongia lachne) sponges found in the Florida Keys. Preliminary results suggest that all 3 species of sponges are net nitrogen-fixing, as indicated by a negative N2 flux. Additionally, all 3 sponge species were a source of DIN as signified by positive fluxes for ammonium and nitrite+nitrate. Nitrogen fixation rates were higher for sheepswool and loggerhead sponges compared to the glove sponges. DIN production was highest for the sheepswool sponge. Regardless of species, nitrogen fixation was more substantial than the DIN flux to the water column. The newly fixed nitrogen may be retained by the sponge or the associated microbial community, while the DIN flux is associated with nitrification and remineralization of organic matter. Our results reinforce previous findings that sponges, and their associated microbial community, are essential to the productivity and nutrient cycling in tropical ecosystems.
CCS 3: Improving the Condition of Coastal Ecosystems through Collaboration: A Panel Discussion of Lessons from Decades of Estuarine Nutrient Assessment and Management
Moderator: Elise Morrison, University of Florida
Panel Focus: 1) the monitoring collaborations necessary to initially develop goals and document coastal habitat recovery in Florida estuaries; 2) contemporary triggers and conditions that have led to additional coastal eutrophication concerns for maintaining coastal habitats and natural resources within Florida’s urbanizing coast; and 3) a vision for ecosystem monitoring collaborations and needs within Florida’s estuaries of national significance that will help ascertain whether recovery and positive restoration trajectories are maintained into the future. Specific case studies from Florida’s estuaries, such as Tampa Bay, Sarasota Bay, and the Indian River Lagoon, will be discussed.
Ed Sherwood Director, Tampa Bay Estuary Program
David Tomasko, Director, Sarasota Bay Estuary Program
Duane De Freese, Director, Indian River Lagoon Council
CCS 4: The Frontier of Earth Systems Modeling for Hazard Prediction & Management
Moderators: Maitane Olabarrieta and David Kaplan, University of Florida
Global High-Resolution Earth System Models Representation of Regional Climate Change and Variability
University of Miami
This presentation focuses on southeast US climate variability and change simulated by global earth system models at unprecedented ocean (~10 km) and atmosphere (~25 km) resolution, and how these simulations differ from traditional IPCC climate simulations at ~100 km resolution in both that atmosphere and ocean. Particular focus is placed on large-scale drivers of regional extremes in rainfall, temperature and coast sea-level contrasting how north Atlantic variability and change drives regional southeast US changes in extremes that are not detected at more typical resolutions.
Pacific Northwest National Laboratory
Process-based watershed models that couple subsurface, land-surface, and energy budget processes are highly desired at the watershed and basin scales to answer a wide range of science questions. The river corridors play important roles in watershed carbon and nitrogen cycling and the removal of excess nutrients. At basin scales, the incorporation of hydrologic complexity and molecular information on microbiome structure (i.e., species composition and distribution of enzyme-encoding genes), microbial expression (i.e., RNA transcription and protein translation), and metabolomes (i.e., reactants and products) will greatly improve a river corridor model (RCM) in capturing distinct water quality signatures across variations in land use, hydrogeology, climate, and disturbances. We have developed an RCM that resolves reactions occurring in both the water columns and in the river corridors as impacted by the hydrologic exchange flows (HEFs). Applying this RCM to the Columbia River Basin (CRB), we found that the physical properties influencing HEFs and land use are the primary controls of the spatial variability in river corridor denitrification. Next, we will enhance the mechanistic foundation of the RCM by linking dynamic river flow processes and heterogeneous terrestrial inputs with variable temperatures and reaction kinetics (informed by molecular properties) to investigate water, energy, and solute fluxes across the river-groundwater interface under both baseline and post-fire conditions. Our approach can be generalized beyond CRB and applied to other basins facing environmental disturbances and water challenges of national significance.
John Warner, USGS; presented by Maitane Olabarrieta, University of Florida
Rising coastal populations, surging sea levels and strengthening coastal storms are increasing risk to coastal communities. Prediction of extreme storms and their local impacts on the coastal environment, habitat, and infrastructure is crucial for management decisions and to provide early warning for evacuations and minimize loss of life and property. Coastal management plans to reduce risk can be guided by the application of numerical models that account for the complex interactions between the atmosphere, watersheds, the ocean and coastal ecosystems. The application of these types of models to past and future events, can help understand the complex dynamics of the coastal region and the consequences associated to coastal erosion, water quality and landscape changes. The prediction of these impacts has advanced tremendously in the past 10 years, due in part to advances in computational capabilities and observational systems. In this talk I will describe the Coupled Ocean-Atmosphere-Waves-Sediment Transport modeling system which dynamically couples state of art earth system oceanic, atmospheric and watershed numerical models. This system can be applied to better understand the effects of different coastal hazards such as such as rip-currents, pollutant transport in the nearshore region, barrier island erosion and breaching, red-tide transport, from others. Accurate assessment of impacts to these realistic systems requires high resolution nearshore and coastal information of landcover, bathymetry, topography, and oceanographic observations for comparison to model predictions. In this talk I will show different applications and I will talk about the future development areas.
Moderator: Tom Ankersen, UF Levin College of Law
Panel Focus: Driven by rapid developments in sensor design and deployment, robotics, big data acquisition, storage and analytics, artificial intelligence and Earth Systems modeling, the pace of coastal science has accelerated. At the same time, the scale and gravity of the hazards confronting coastal waters, shorelines and communities has also been accelerating. Many of these coastal hazards are systemic – warmer water, rising seas, tropicalization – the result of the changing climate. Others are more localized – legacy pollution, altered hydrologic regimes, ecosystem disturbance. Synergies between these global and local impacts, coupled with multidecadal time horizons, present a profound policymaking challenge.
Annie Brett, UF Levin College of Law
Rachel Silverstein, Miami Waterkeeper
Adam Blalock, Florida Department of Environmental Protection
Christine Angelini, UFCollege of Engineering