Determining potential for pollutant impacts in dynamic coastal waters: comparing morphological settings

The coastal focus and beach culture of Australia’s population in general, and the people of New South Wales in particular, mean that coastal systems are both highly prized and subjected to great pressures. The vast majority of the wastewater generated by the 7.3 million people of New South Wales is discharged directly to the ocean. The dispersion and fate of waterborne pollutants and their potential to impact coastal ecosystems are fundamentally determined by the dynamics of the coastal boundary layer (CBL). This turbulent interface between the coastline and the deep oceans is defined and classified for the first time in this thesis. Coastal morphologies and changes in the orientation of the coastline promote turbulence and strong gradients with extreme variability and heterogeneity over a broad range of scales. Conceptual models are presented to characterise New South Wales coastal boundary layer processes. The broad aims of this thesis are to investigate the coastal boundary layer processes that affect dispersal and advection of pollutants, and to develop conceptual models and tools to facilitate coastal management. Remote sensed ocean colour and sea surface temperature observations define meso-scale CBL phenomena, and this study demonstrates their application to support management decisions in relation to marine algal (phytoplankton) blooms. However, considerable scope exists to improve regional algorithms to deliver better ocean colour products for the optically complex (Case 2) waters of the inner coastal boundary layer. Past failures to consider the CBL (morphological) settings of pollutant discharges to coastal waters have led to inefficient pollutant discharge systems and potential environmental impacts. Two case studies, investigate the principal forcing mechanisms and demonstrate the importance of morphology in controlling the dispersion and retention times of pollutants. The first case study is focused on Sydney coastal waters where pollutant loadings are greater in magnitude and different in character than elsewhere in New South Wales. Here population pressures generate large wastewater loadings but the distances to offshore discharge locations are large compared to the scale of coastal roughness (headlands and bays) and the water is deep, thus reducing the risk of local retention of pollutants and increasing the potential for rapid dilution. By considering simulations of near field effluent plume behaviour in relation to long term ambient nutrient patterns specific periods of the year and depth intervals have been identified when outfalls would have an increased opportunity to influence bloom development, especially the upper half of the water column during late summer. However, algal blooms appear to be principally driven by seasonal oceanic nutrient enrichment. The research presented in this thesis, together with companion research previously published by the author and routine ongoing monitoring, indicate the viability of disposal of the Sydney’s excess sewage effluent (after source control and re-use options have been exhausted) via existing deepwater outfalls. In contrast, inner CBL settings with coastal irregularities (e.g. headlands and bays) have a greater propensity to trap pollutants. A new hydrodynamically relevant morphological classification of New South Wales bays, headlands and islands provides both broad context for case studies and guides preliminary assessments for other locations. This classification reveals a borderline propensity for flow separation and re-circulation in the lee of Corambirra Point which is the focus of the second case study off Coffs Harbour in northern NSW. Direct observations and 3D finite difference hydrodynamic (Eulerian) and particle tracking (Lagrangian) model simulations quantify transient re-circulation associated with local current accelerations and a persistent shear zone located in the wake to the south of Corambirra Point. The flux of ambient water across the prescribed outfall alignment increases eighteen fold, over a shear zone spanning a cross-shore distance of just 1.4km (from 1.6km to 3km offshore). In contrast, the potential for re-entrainment and trapping of effluent in transient re-circulation cells was demonstrated to be insignificant. The proposed location of the outfalls was 1.5km offshore whereas the greatest gain per unit extension of the proposed discharge point coincides with the centre of the shear zone located ~2km offshore. These case studies illustrate specific coastal boundary layer effects and indicate how an understanding of the spatial and temporal scales of these effects can be used to target more specific assessments of potential pollutant impacts. Simple morphological risk assessment tools are also presented to identify factors and processes which limit the exposure of sensitive environments to high pollutant concentrations and loads. Eddy retention effects are generally not incorporated in existing near field models but potential re-entrainment effects in wake zones can be assessed through the eddy retention value, which is introduced in this thesis. Although the approach presented here is focused on New South Wales coastal waters, the framework serves as a basis for general application elsewhere, and as a foundation for further refinement for application to NSW coastal waters. Existing scientific literature indicates that coastal boundary layer processes also shape the distributions of the biological species and communities. This further motivates the development of a process based understanding of coastal boundary layer dynamics as a fundamental platform to support environmental protection and biodiversity conservation initiatives

Estimation of CDOM in Inland Waters via Water Bio-Optical Properties Using a Remote Sensing Approach

Monitoring of Colored dissolved organic matter (CDOM) in inland waters provides important information for tracing carbon cycle at the land-water interface and studying aquatic ecosystem. Remote sensing estimation of CDOM in the inland waters offers an alternative approach to field samplings in examining CDOM spatial-temporal dynamics. However, CDOM retrieval is a challenge due to the lack of algorithm for resolving bottom effect in shallow inland waters. Moreover, an effective approach based on multi-spectral, high spatial resolution and global coverage satellite images is in urgent need. To resolve these challenges, shallow water bio-optical properties (SBOP) algorithm was developed to overcome bottom reflectance effect on the total water leaving reflectance in shallow inland water. SBOP algorithm included the bottom reflectance in building underwater light transfer model. It was designed based on the field spectral data from four cruises in Lake Huron. SBOP algorithm had an obviously advantage over previous deep water CDOM algorithm (e.g. QAA-CDOM). In this study, Landsat-8 multi-spectral satellite imagery was selected to derive CDOM spatial-temporal dynamics in lake and river waters. The coastal blue band (443 nm), global coverage and high spatial resolution (30 m) of Landsat-8 images offered suitable data for inland water CDOM mapping. The SBOP algorithm was applied on Landsat-8 images in broad ranges of inland waters with high accuracy (Lake Huron (R2 = 0.87), 14 northeastern freshwater lakes (R2 = 0.80), and 6 large Arctic Rivers (R2 = 0.87)). Both the spatial patterns and seasonal dynamics were derived to study the multiple factors’ impact on terrestrially derived CDOM input to the rivers and lakes, including river discharge, watershed landcover, and temperature. This new satellite approach of CDOM estimation in inland waters provided high accuracy spatial-temporal information for studying land-water carbon cycle and aquatic environment

Assessing the potential impacts of a changing climate on the distribution of a rabies virus vector

Common vampire bats (Desmodus rotundus) occur throughout much of South America to northern MeÂxico. Vampire bats have not been documented in recent history in the United States, but have been documented within about 50 km of the U.S. state of Texas. Vampire bats feed regularly on the blood of mammals and can transmit rabies virus to native species and livestock, causing impacts on the health of prey. Thus cattle producers, wildlife management agencies, and other stakeholders have expressed concerns about whether vampire bats might spread into the southern United States. On the other hand, concerns about vampire- borne rabies can also result in wanton destruction at bat roosts in areas occupied by vampire bats, but also in areas not known to be occupied by this species. This can in turn negatively affect some bat roosts, populations, and species that are of conservation concern, including vampire bats. To better understand the current and possible future distribution of vampire bats in North America and help mitigate future cattle management problems, we used 7,094 vampire bat occurrence records from North America and species distribution modeling (SDM) to map the potential distribution of vampire bats in North America under current and future climate change scenarios. We analysed and mapped the potential distribution of this species using 5 approaches to species distribution modeling: logistic regression, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy. We then projected these models into 17 ªworst-caseº future climate scenarios for year 2070 to generate hypotheses about how the vampire bat distribution in North America might change in the future. Of the variables used in this analysis, minimum temperature of the coldest month had the highest variable importance using all 5 SDM approaches. These results suggest two potential near-future routes of vampire bat dispersal into the U. S., one via southern Texas, and a second into southern Florida. Some of our SDM models support the hypothesis that suitable habitat for vampire bats may currently exist in parts of the Mexico-U.S. borderlands, including extreme southern portions of Texas, as well as in southern Florida. However, this analysis also suggests that extensive expansion into the south-eastern and south-western U.S. over the coming ~60 years appears unlikely

Remote Sensing Applications in Coastal Environment

Coastal regions are susceptible to rapid changes, as they constitute the boundary between the land and the sea. The resilience of a particular segment of coast depends on many factors, including climate change, sea-level changes, natural and technological hazards, extraction of natural resources, population growth, and tourism. Recent research highlights the strong capabilities for remote sensing applications to monitor, inventory, and analyze the coastal environment. This book contains 12 high-quality and innovative scientific papers that explore, evaluate, and implement the use of remote sensing sensors within both natural and built coastal environments

Spatiotemporal Abundance Patterns and Ecological Drivers of A Nearshore U.S. Atlantic Fish and Invertebrate Assemblage

Taking an ecosystem approach to fisheries requires the consideration of relevant ecological processes within research and assessment frameworks. Processes affecting ecosystem productivity can be categorized as biophysical (climate variability, primary production), exploitative (fishing), or trophodynamic (food web interactions). This dissertation incorporates these three governing processes to characterize spatiotemporal diversity and population abundance trends for multiple demersal fish and invertebrate species that inhabit the nearshore zone (15-30 ft. depth) along portions of the U.S. Atlantic east coast. Two large marine ecosystems (LMEs) encompass the U.S. East coast – the Southeast and Northeast U.S. Continental Shelf LMEs. The level of connectivity within and between these two ecosystems is well understood for some individual species, but not generally for the nearshore assemblage. The first research chapter of this dissertation is a spatial diversity analysis of 141 fish and invertebrate species that inhabit nearshore waters from Florida to New York. Latitudinal diversity patterns revealed multiple biotic ecotones, or areas of high species turnover. An ecotone was evident in northern spring near the Cape Hatteras border of the two LMEs, but this barrier dissipated as water temperatures homogenized and assemblage connectivity between ecosystems increased throughout the year. Multiple other biotic ecotones were evident within the Southeast U.S. LME and were explained by seasonality and the proximity and area of adjacent estuarine habitat. The second and third research chapters of this dissertation focus on explaining temporal abundance trends for multiple nearshore fish and invertebrate species within the Southeast U.S. LME. For the second research chapter, abundance trends for 71 species were analyzed during 1990-2013 within a univariate time series modeling framework with the goal of determining the relative importance of climate variability and fishing pressure as governing influences on abundance. A decrease in bycatch mortality explained changes for multiple species, while climate variability governed the dynamics for others. Multivariate ordination revealed similar trends for groups of taxonomically related species, indicating governing processes act on species with similar life histories. An extension of results from the second research chapter, research chapter three explores trophic interactions between the bonnethead shark (Sphyrna tiburo) and five of its prey species within Southeast U.S. LME nearshore waters. Multivariate time series modeling supports a negative effect of bycatch on bonnetheads, and population-level predation effects of larger sharks on multiple prey species. Abundance trends for most prey species were also explained by environmental variability associated with the Pacific Decadal Oscillation, although trophic effects were stronger. This body of work incorporates relevant ecological factors in characterizing diversity and abundance trends for fish and invertebrate species comprising the nearshore demersal assemblage within Southeast and Northeast U.S. LMEs. Results indicate seasonal connectivity between LMEs that require further exploration at multiple spatial scales. Abundance time series modeling for multiple species in the Southeast U.S. LME reveals that fishing and trophodynamics may be relatively more influential drivers than climate variability in this sub-tropical system

Remote sensing technologies for the assessment of marine and coastal ecosystems

Abstract This chapter reviews the Remote Sensing (RS) technologies that are particularly appropriate for marine and coastal ecosystem research and management. RS techniques are used to perform analysis of water quality in coastal water bodies; to identify, characterize and analyze river plumes; to extract estuarine/coastal sandy bodies; to identify beach features/patterns; and to evaluate the changes and integrity (health) of the coastal lagoon habitats. For effective management of these ecosystems, it is essential to have satellite data available and complementary accurate information about the current state of the coastal regions, in addition to well-informed forecasts about its future state. In recent years, the use of space, air and ground-based RS strategies has allowed for the rapid data collection, Image processing (Pixel-Based and Object-Based Image Analysis (OBIA) classification) and dissemination of such information to reduce vulnerability to natural hazards, anthropic pressures, and to monitoring essential ecological processes, life support systems and biological diversityinfo:eu-repo/semantics/submittedVersio

Remote sensing for optimal estimation of water temperature dynamics in shallow tidal environments

Given the increasing anthropogenic pressures on lagoons, estuaries, and lakes and considering the highly dynamic behavior of these systems, methods for the continuous and spatially distributed retrieval of water quality are becoming vital for their correct monitoring and management. Water temperature is certainly one of the most important drivers that influence the overall state of coastal systems. Traditionally, lake, estuarine, and lagoon temperatures are observed through point measurements carried out during field campaigns or through a network of sensors. However, sporadic measuring campaigns or probe networks rarely attain a density sufficient for process understanding, model development/validation, or integrated assessment. Here, we develop and apply an integrated approach for water temperature monitoring in a shallow lagoon which incorporates satellite and in-situ data into a mathematical model. Specifically, we use remote sensing information to constrain large-scale patterns of water temperature and high-frequency in situ observations to provide proper time constraints. A coupled hydrodynamic circulation-heat transport model is then used to propagate the state of the system forward in time between subsequent remote sensing observations. Exploiting the satellite data high spatial resolution and the in situ measurements high temporal resolution, the model may act a physical interpolator filling the gap intrinsically characterizing the two monitoring techniques

A 55-Year Time Series Station for Primary Production in the Adriatic Sea: Data Correction, Extraction of Photosynthesis Parameters and Regime Shifts

In 1962, a series of in situ primary production measurements began in the Adriatic Sea, at a station near the island of Vis. To this day, over 55 years of monthly measurements through the photic zone have been accumulated, including close to 3000 production measurements at different depths. The measurements are conducted over a six-hour period around noon, and the average production rate extrapolated linearly over day length to calculate daily production. Here, a non-linear primary production model is used to correct these estimates for potential overestimation of daily production due to linear extrapolation. The assimilation numbers are recovered from the measured production profiles and subsequently used to model production at depth. Using the recovered parameters, the model explained 87% of variability in measured normalized production at depth. The model is then used to calculate daily production at depth, and it is observed to give on average 20% lower daily production at depth than the estimates based on linear extrapolation. Subsequently, water column production is calculated, and here, the model predicted on average 26% lower water column production. With the recovered parameters and the known magnitude of the overestimation, the time-series of water column production is then re-established with the non-linearly-corrected data. During this 55-year period, distinct regimes were observed, which were classified with a regime shift detection method. It is then demonstrated how the recovered parameters can be used in a remote sensing application. A seasonal cycle of the recovered assimilation number is constructed along with the seasonal cycle of remotely-sensed chlorophyll. The two are then used to model the seasonal cycle of water column production. An upper and a lower bound on the seasonal cycle of water column production based on remotely-sensed chlorophyll data are then presented. Measured water column production was found to be well within the range of remotely-sensed estimates. With this work, the utility of in situ measurements as a means of providing information on the assimilation number is presented and its application as a reference for remote sensing models highlighted