Mapping the pollutants in surface riverine flood plume waters in the Great Barrier Reef, Australia

Devlin, Michelle; McKinna, Lachlan I. W.; Álvarez‐Romero, Jorge G.; Petus, Caroline; Abott, B.; Harkness, P.; Brodie, Jon

doi:10.1016/j.marpolbul.2012.03.001

Cited by 138 publications

(135 citation statements)

References 54 publications

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“…The aim of these programs is to halt and reverse the decline in the quality of water flowing into the GBR, supported by continual monitoring of water quality conditions in the region. Because of its synoptic-scale spatial coverage and near-daily over-pass frequency, ocean color remote sensing has become an integral part of monitoring and reporting spatiotemporal trends in water quality for the GBR region [Brando et al, 2011;Devlin et al, 2012;Devlin and Schaffelke, 2009;Fabricius et al, 2014;Schroeder et al, 2012;Weeks et al, 2012].…”

Section: Test Region: the Great Barrier Reefmentioning

confidence: 99%

“…This is consistent with Weeks et al [2012] who used a regionally tuned water clarity algorithm to determine that clearest waters in the central and southern GBR occur during September due to strong intrusions onto the GBR shelf of clear oligotrophic waters from the Coral Sea. Weeks et al [2012] also reported that least clear optical conditions occur during the Austral Wet Season (summerautumn), during which high rainfall events cause riverine discharge of terrestrial nutrients and sediments that flow onto the GBR shelf Devlin et al, 2012]. …”

Section: Seasonal Variabilitymentioning

confidence: 99%

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A semianalytical ocean color inversion algorithm with explicit water column depth and substrate reflectance parameterization

et al. 2015

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A semianalytical ocean color inversion algorithm was developed for improving retrievals of inherent optical properties (IOPs) in optically shallow waters. In clear, geometrically shallow waters, light reflected off the seafloor can contribute to the water-leaving radiance signal. This can have a confounding effect on ocean color algorithms developed for optically deep waters, leading to an overestimation of IOPs. The algorithm described here, the Shallow Water Inversion Model (SWIM), uses pre-existing knowledge of bathymetry and benthic substrate brightness to account for optically shallow effects. SWIM was incorporated into the NASA Ocean Biology Processing Group's L2GEN code and tested in waters of the Great Barrier Reef, Australia, using the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua time series (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013). SWIM-derived values of the total non-water absorption coefficient at 443 nm, a t (443), the particulate backscattering coefficient at 443 nm, b bp (443), and the diffuse attenuation coefficient at 488 nm, K d (488), were compared with values derived using the Generalized Inherent Optical Properties algorithm (GIOP) and the Quasi-Analytical Algorithm (QAA). The results indicated that in clear, optically shallow waters SWIM-derived values of a t (443), b bp (443), and K d (443) were realistically lower than values derived using GIOP and QAA, in agreement with radiative transfer modeling. This signified that the benthic reflectance correction was performing as expected. However, in more optically complex waters, SWIM had difficulty converging to a solution, a likely consequence of internal IOP parameterizations. Whilst a comprehensive study of the SWIM algorithm's behavior was conducted, further work is needed to validate the algorithm using in situ data.

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Section: Test Region: the Great Barrier Reefmentioning

confidence: 99%

Section: Seasonal Variabilitymentioning

confidence: 99%

A semianalytical ocean color inversion algorithm with explicit water column depth and substrate reflectance parameterization

et al. 2015

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“…They represent a gradient from the inshore to the offshore boundaries of river plumes. Each plume water type is associated with characteristic optical properties, light levels and colours, as well as different concentrations and proportions of land-sourced contaminants (e.g., [11][12][13][14][15][16]). Table 1 gives examples of remote sensing monitoring products developed through the GBR Marine Monitoring Program (MMP) to improve our understanding of the relationships between coastal water quality in river plumes and its effects on marine ecosystems [15].…”

Section: Introductionmentioning

confidence: 99%

“…River plume maps have been developed to document the spatial extent and frequency of occurrence of the GBR plume water types (Table 1A). Coupled with in situ data, river plume maps have been used to document water quality conditions associated with river plumes (Table 1B) (e.g., [12][13][14][15]). The remote sensing outputs are produced as single-week and multi-week (seasonal and multi-annual, see Table 1) composite maps and provide an aggregated approach to reporting contaminant concentrations in the GBR marine environment.…”

Section: Introductionmentioning

confidence: 99%

“…River plume maps have thus been used as an interpretative tool for understanding changes in seagrass meadow health [18] and, in a case study in Cleveland Bay (north Queensland), the decline in seagrass meadow area and cover was positively linked to a high occurrence of primary plume water masses mapped through Moderate Resolution Imaging Spectroradiometer (MODIS) imagery [19]. There is, however, a need to improve these remote sensing monitoring products and incorporate them into unique Risk Assessment Frameworks focusing on the GBR-wide scale and incorporating the potential of cumulative impacts from multiple contaminants in river plume waters [13,16]. The assessment of risk in this study is defined as "the methods by which the likely adverse effect of combined contaminants on ecosystems is estimated with a known degree of certainty using scientific methodology" [20].…”

Section: Introductionmentioning

confidence: 99%

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Estimating the Exposure of Coral Reefs and Seagrass Meadows to Land-Sourced Contaminants in River Flood Plumes of the Great Barrier Reef: Validating a Simple Satellite Risk Framework with Environmental Data

et al. 2016

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River runoff and associated flood plumes (hereafter river plumes) are a major source of land-sourced contaminants to the marine environment, and are a significant threat to coastal and marine ecosystems worldwide. Remote sensing monitoring products have been developed to map the spatial extent, composition and frequency of occurrence of river plumes in the Great Barrier Reef (GBR), Australia. There is, however, a need to incorporate these monitoring products into Risk Assessment Frameworks as management decision tools. A simple Satellite Risk Framework has been recently proposed to generate maps of potential risk to seagrass and coral reef ecosystems in the GBR focusing on the Austral tropical wet season. This framework was based on a "magnitudeˆlikelihood" risk management approach and GBR plume water types mapped from satellite imagery. The GBR plume water types (so called "Primary" for the inshore plume waters, "Secondary" for the midshelf-plume waters and "Tertiary" for the offshore plume waters) represent distinct concentrations and combinations of land-sourced and marine contaminants. The current study aimed to test and refine the methods of the Satellite Risk Framework. It compared predicted pollutant concentrations in plume water types (multi-annual average from 2005-2014) to published ecological thresholds, and combined this information with similarly long-term measures of seagrass and coral ecosystem health. The Satellite Risk Framework and newly-introduced multi-annual risk scores were successful in demonstrating where water conditions were, on average, correlated to adverse biological responses. Seagrass meadow abundance (multi-annual change in % cover) was negatively correlated to the multi-annual risk score at the site level (R 2 = 0.47, p < 0.05). Relationships between multi-annual risk scores and multi-annual changes in proportional macroalgae cover (as an index for coral reef health) were more complex (R 2 = 0.04, p > 0.05), though reefs incurring higher risk scores showed relatively higher proportional macroalgae cover. Multi-annual risk score thresholds associated with loss of seagrass cover were defined, with lower risk scores (ď0.2) associated with a gain or little loss in seagrass cover (gain/´12%), medium risk scores (0.2-0.4) associated with moderate loss (´12/´30%) and higher risk scores (>0.4) with the greatest loss in cover (>´30%). These thresholds were used to generate an intermediate river plume risk map specifically for seagrass meadows of the GBR. An intermediate river plume risk map for coral reefs was also developed by considering a multi-annual risk score threshold of 0.2-above which a higher proportion of macroalgae within the algal communities can be expected. These findings contribute to a long-term and adaptive approach to set relevant risk framework and thresholds for adverse biological responses in the GBR. The ecological thresholds and risk scores used in this study will be refined and validated through ongoing monitoring and assessment. As uncertainties are red...

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Impact of an extreme flood event on optical and biogeochemical properties in a subtropical coastal periurban embayment (Eastern Australia)

et al. 2014

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Major floods impacted the city of Brisbane, eastern Australia, in January 2011, delivering large amounts of dissolved and particulate materials and nutrients into the adjacent coastal embayment, Moreton Bay. The resulting spatially resolved changes in biogeochemical and optical properties in Moreton Bay were examined 1, 2, 6, 19, and 49 weeks after the main freshwater discharge. One week postflood, total suspended matter (TSM) and chlorophyll a (TChla) concentrations varied over 1 order of magnitude throughout Moreton Bay, the particle scattering coefficient at 555 nm varied by a factor of 20, and the total absorption coefficient and colored dissolved organic matter (CDOM) absorption coefficient at 440 nm varied by a factor of 5. The largest changes in biogeochemical and optical properties observed during our study were from 1 to 2 weeks after the floods: near the Brisbane River mouth, TSM decreased by a factor of 3, CDOM by a factor of 2, while TChla increased by a factor of 3. Within a year, optical and biogeochemical properties recovered to levels similar to nonflood conditions. The strong changes in the characteristics of the particulate and dissolved material following the flood event and subsequent biological and photochemical processes led to a large spatial and temporal variability in the relative contribution of different constituents to the total absorption coefficient at 440 nm, the particle single scattering albedo, and the specific inherent optical properties. This work has significant implications for the accuracy of standard ocean color remote sensing algorithms in coastal waters during flood events.

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Mapping the pollutants in surface riverine flood plume waters in the Great Barrier Reef, Australia

Cited by 138 publications

References 54 publications

A semianalytical ocean color inversion algorithm with explicit water column depth and substrate reflectance parameterization

A semianalytical ocean color inversion algorithm with explicit water column depth and substrate reflectance parameterization

Estimating the Exposure of Coral Reefs and Seagrass Meadows to Land-Sourced Contaminants in River Flood Plumes of the Great Barrier Reef: Validating a Simple Satellite Risk Framework with Environmental Data

Impact of an extreme flood event on optical and biogeochemical properties in a subtropical coastal periurban embayment (Eastern Australia)

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