High Resolution Turbidity Modelling in Arctic Nearshore Environments

2021 ◽  
Author(s):  
Konstantin Klein ◽  
Hugues Lantuit ◽  
Birgit Heim ◽  
David Doxaran ◽  
Ingmar Nitze ◽  
...  
Keyword(s):  
Organic Matter ◽  
Spectral Response ◽  
Local Population ◽  
Beaufort Sea ◽  
The Arctic ◽  
High Temporal Resolution ◽  
Landsat 8 ◽  
Sediment Dispersal ◽  
Nearshore Environments ◽  
Sentinel 2

<p>The Arctic is directly impacted by climate change. The increase in air temperature drives the thawing of permafrost and an increase in coastal erosion and river discharge. This leads to a greater input of sediment and organic matter into coastal waters, which substantially impacts the ecosystems, the subsistence economy of the local population, and the climate because of the transformation of organic matter into greenhouse gases. Yet, the patterns of sediment dispersal in Arctic nearshore zones and their role in the Carbon cycle are not well known due to difficult accessibility and challenging weather conditions. In this study we present the first multi-sensor turbidtiy- reflectance relationship that was specifically calibrated for Arctic nearshore environments. Field data was collected during summer seasons 2018 and 2019 in the inner shelf waters of the Canadian Beaufort Sea close to Herschel Island Qikiqtaruk. The turbidity-reflectance relationship was calibrated to mid to high spatial resolution sensors which are used in ocean color remote sensing, including Landsat 8, Sentinel 2, and Sentinel 3, using the relative spectral response functions. The results for Landsat 8 and Sentinel 2 are very promising and showcase the possibility to resolve sediment accumulations, sediment pathways and filaments at higher detail than before. Both sensors are able to resolve high turbidity close to the coast with values comparable to our field measurements. Sentinel 3, on the other hand, is too coarse to resolve these features but provides great applicability due to its high temporal resolution. The transferability  of these relationships to nearshore environments outside the Canadian Beaufort Sea has to be tested in the future with the potential to map the sediment dispersal in nearshore environments at a circum- Arctic scale.</p>

scholarly journals POTENTIAL OF RESAMPLED MULTISPECTRAL DATA FOR DETECTING DESMODIUM-BRACHIARIA INTERCROPPED WITH MAIZE IN A ‘PUSH-PULL’ SYSTEM

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1017-1022 ◽  
Author(s):  
B. T. Mudereri ◽  
E. M. Abdel-Rahman ◽  
T. Dube ◽  
T. Landmann ◽  
S. Niassy ◽  
...  
Keyword(s):  
Crop Yields ◽  
Spectral Response ◽  
Machine Learning Algorithms ◽  
Landsat 8 ◽  
Electromagnetic Spectrum ◽  
Maize Stover ◽  
Pull System ◽  
Multispectral Sensors ◽  
Sentinel 2

Abstract. Poor crop yields remain one of the main causes of chronic food insecurity in Africa. This is largely caused by insect pests, weeds, unfavourable climatic conditions and degraded soils. Weed and pest control, based on the climate-adapted ‘push-pull’ system, has become an important target for sustainable intensification of food production adopted by many small-holder farmers. However, essential baseline information using remotely sensed data is missing, specifically for the ‘push-pull’ companion crops. In this study, we investigated the spectral uniqueness of two of the most commonly used ‘companion’ crops (i.e. greenleaf Desmodium (Desmodium intortum) and Brachiaria (Brachiaria cv Mulato) with co-occurring soil, green maize, and maize stover. We used FieldSpec® Handheld 2™ analytical spectral device to collect in situ hyperspectral data in the visible and near-infrared region of the electromagnetic spectrum. Random forest was then used to discriminate among the different companion crops, green maize, maize stover and the background soil. Experimental ‘push-pull’ plots at the International Centre of Insect Physiology and Ecology (icipe) in Kenya were used as test sites. The in-situ hyperspectral reflectance data were resampled to the spectral waveband configurations of four multispectral sensors (i.e. Landsat-8, Quickbird, Sentinel-2, and WorldView-2) using spectral response functions. The performance of the four sensors to detect the ‘push-pull’ companion crops, maize and soil was compared. We were able to positively discriminate the two companion crops from the three potential background endmembers i.e. soil, green maize, and maize stover. Sentinel-2 and WorldView-2 outperformed (> 98% overall accuracy) Landsat-8 and Quickbird (96% overall accuracy), because of their added advantage of the strategically located red-edge bands. Our results demonstrated the unique potential of the relatively new multispectral sensors’ and machine learning algorithms as a tool to accurately discern companion crops from co-occurring maize in ‘push-pull’ plots.

scholarly journals Geochemistry of Coastal Permafrost and Erosion-Driven Organic Matter Fluxes to the Beaufort Sea Near Drew Point, Alaska

2021 ◽  
Vol 8 ◽  
Author(s):  
Emily M. Bristol ◽  
Craig T. Connolly ◽  
Thomas D. Lorenson ◽  
Bruce M. Richmond ◽  
Anastasia G. Ilgen ◽  
...  
Keyword(s):  
Organic Matter ◽  
Organic Carbon ◽  
Late Pleistocene ◽  
21St Century ◽  
Marine Sediments ◽  
Coastal Erosion ◽  
Beaufort Sea ◽  
The Arctic ◽  
The Holocene ◽  
Kuparuk River

Accelerating erosion of the Alaska Beaufort Sea coast is increasing inputs of organic matter from land to the Arctic Ocean, and improved estimates of organic matter stocks in eroding coastal permafrost are needed to assess their mobilization rates under contemporary conditions. We collected three permafrost cores (4.5–7.5 m long) along a geomorphic gradient near Drew Point, Alaska, where recent erosion rates average 17.2 m year−1. Down-core patterns indicate that organic-rich soils and lacustrine sediments (12–45% total organic carbon; TOC) in the active layer and upper permafrost accumulated during the Holocene. Deeper permafrost (below 3 m elevation) mainly consists of Late Pleistocene marine sediments with lower organic matter content (∼1% TOC), lower C:N ratios, and higher δ13C values. Radiocarbon-based estimates of organic carbon accumulation rates were 11.3 ± 3.6 g TOC m−2 year−1 during the Holocene and 0.5 ± 0.1 g TOC m−2 year−1 during the Late Pleistocene (12–38 kyr BP). Within relict marine sediments, porewater salinities increased with depth. Elevated salinity near sea level (∼20–37 in thawed samples) inhibited freezing despite year-round temperatures below 0°C. We used organic matter stock estimates from the cores in combination with remote sensing time-series data to estimate carbon fluxes for a 9 km stretch of coastline near Drew Point. Erosional fluxes of TOC averaged 1,369 kg C m−1 year−1 during the 21st century (2002–2018), nearly doubling the average flux of the previous half-century (1955–2002). Our estimate of the 21st century erosional TOC flux year−1 from this 9 km coastline (12,318 metric tons C year−1) is similar to the annual TOC flux from the Kuparuk River, which drains a 8,107 km2 area east of Drew Point and ranks as the third largest river on the North Slope of Alaska. Total nitrogen fluxes via coastal erosion at Drew Point were also quantified, and were similar to those from the Kuparuk River. This study emphasizes that coastal erosion represents a significant pathway for carbon and nitrogen trapped in permafrost to enter modern biogeochemical cycles, where it may fuel food webs and greenhouse gas emissions in the marine environment.

scholarly journals Tracing the transport of colored dissolved organic matter in water masses of the Southern Beaufort Sea: relationship with hydrographic characteristics

2012 ◽  
Vol 9 (3) ◽  
pp. 925-940 ◽  
Author(s):  
A. Matsuoka ◽  
A. Bricaud ◽  
R. Benner ◽  
J. Para ◽  
R. Sempéré ◽  
...  
Keyword(s):  
Organic Matter ◽  
Surface Layer ◽  
Dissolved Organic Matter ◽  
Heat Budget ◽  
Ocean Color ◽  
Beaufort Sea ◽  
The Arctic ◽  
Strongly Correlated ◽  
Colored Dissolved Organic Matter ◽  
Color Data

Abstract. Light absorption by colored dissolved organic matter (CDOM) [aCDOM(λ)] plays an important role in the heat budget of the Arctic Ocean, contributing to the recent decline in sea ice, as well as in biogeochemical processes. We investigated aCDOM(λ) in the Southern Beaufort Sea where a significant amount of CDOM is delivered by the Mackenzie River. In the surface layer, aCDOM(440) showed a strong and negative correlation with salinity, indicating strong river influence and conservative transport in the river plume. Below the mixed layer, a weak but positive correlation between aCDOM(440) and salinity was observed above the upper halocline, resulting from the effect of removal of CDOM due to brine rejection and lateral intrusion of Pacific summer waters into these layers. In contrast, the relationship was negative in the upper and the lower haloclines, suggesting these waters originated from Arctic coastal waters. DOC concentrations in the surface layer were strongly correlated with aCDOM(440) (r2 = 0.97), suggesting that this value can be estimated in this area, using aCDOM(440) that is retrieved using satellite ocean color data. Implications for estimation of DOC concentrations in surface waters using ocean color remote sensing are discussed.

Land-to-ocean fluxes and biolability of organic matter eroding along the Beaufort Sea coast near Drew Point, Alaska

2021 ◽  
Author(s):  
Emily Bristol ◽  
Craig Connolly ◽  
Thomas Lorenson ◽  
Bruce Richmond ◽  
Anastasia Ilgen ◽  
...  
Keyword(s):  
Organic Matter ◽  
Organic Carbon ◽  
Active Layer ◽  
Late Pleistocene ◽  
Coastal Erosion ◽  
Organic Matter Content ◽  
Beaufort Sea ◽  
The Arctic ◽  
Series Data ◽  
Sea Coast

<p>Coastal erosion rates are increasing along the Alaskan Beaufort Sea coast due to increases in wave action, the increasing length of the ice-free season, and warming permafrost. These eroding permafrost coastlines transport organic matter and inorganic nutrients to the Arctic Ocean, likely fueling biological production and CO<sub>2</sub> emissions. To assess the impacts of Arctic coastal erosion on nearshore carbon and nitrogen cycling, we examined geochemical profiles from eroding coastal bluffs and estimated annual organic matter fluxes from 1955 to 2018 for a 9 km stretch of coastline near Drew Point, Alaska. Additionally, we conducted a laboratory incubation experiment to examine dissolved organic carbon (DOC) leaching and biolability from coastal soils/sediments added to seawater.</p><p>Three permafrost cores (4.5 – 7.5 m long) revealed that two distinct horizons compose eroding bluffs near Drew Point: Holocene age, organic-rich (~12-45% total organic carbon; TOC) terrestrial soils and lacustrine sediments, and below, Late Pleistocene age marine sediments with lower organic matter content (~1% TOC), lower carbon to nitrogen ratios, and higher δ<sup>13</sup>C-TOC values. Organic matter stock estimates from the cores, paired with remote sensing time-series data, show that erosional TOC fluxes from this study coastline averaged 1,369 kg C m<sup>−1</sup> yr<sup>−1</sup> during the 21<sup>st</sup> century, nearly double the average flux of the previous half century. Annual TOC flux from this 9 km coastline is now similar to the annual TOC flux from the Kuparuk River, the third largest river draining the North Slope of Alaska.</p><p>Experimental work demonstrates that there are distinct differences in DOC leaching yields and the fraction of biodegradable DOC across soil/sediment horizons. When core samples were submerged in seawater for 24 hours, the Holocene age organic-rich permafrost leached the most DOC in seawater (~6.3 mg DOC g<sup>-1</sup> TOC), compared to active layer soils and Late-Pleistocene marine-derived permafrost (~2.5 mg DOC g<sup>-1</sup> TOC). Filtered leachates were then incubated aerobically in the dark for 26 and 90 days at 20°C to examine biodegradable DOC (i.e. the proportion of DOC lost due to microbial uptake or remineralization). Of this leached DOC, Late Pleistocene permafrost was the most biolabile over 90 days (31 ± 7%), followed by DOC from active layer soils (24 ± 5%) and Holocene-age permafrost (14% ± 3%). If we scale these results to a typical 4 m tall eroding bluff at Drew Point, we expect that ~341 g DOC m<sup>-2 </sup>will rapidly leach, of which ~25% is biodegradable. These results demonstrate that eroding permafrost bluffs are an increasingly important source of biolabile DOC, likely contributing to greenhouse gas emissions and marine production in the coastal environment.</p>

scholarly journals A Google Earth Engine Tool to Investigate, Map and Monitor Volcanic Thermal Anomalies at Global Scale by Means of Mid-High Spatial Resolution Satellite Data

2020 ◽  
Vol 12 (19) ◽  
pp. 3232
Author(s):  
Nicola Genzano ◽  
Nicola Pergola ◽  
Francesco Marchese
Keyword(s):  
Spatial Resolution ◽  
Satellite Data ◽  
Hot Spot ◽  
Global Scale ◽  
Google Earth ◽  
High Temporal Resolution ◽  
Landsat 8 ◽  
Thermal Anomalies ◽  
Google Earth Engine ◽  
Sentinel 2

Several satellite-based systems have been developed over the years to study and monitor thermal volcanic activity. Most of them use high temporal resolution satellite data, provided by sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) that if on the one hand guarantee a continuous monitoring of active volcanic areas on the other hand are less suited to map thermal anomalies, and to provide accurate information about their features. The Multispectral Instrument (MSI) and the Operational Land Imager (OLI), respectively, onboard the Sentinel-2 and Landsat-8 satellites, providing Short-Wave Infrared (SWIR) data at 20 m (MSI) and 30 m (OLI) spatial resolution, may make an important contribution in this area. In this work, we present the first Google Earth Engine (GEE) App to investigate, map and monitor volcanic thermal anomalies at global scale, integrating Landsat-8 OLI and Sentinel-2 MSI observations. This open tool, which implements the Normalized Hot spot Indices (NHI) algorithm, enables the analysis of more than 1400 active volcanoes, with very low processing times, thanks to the high GEE computational resources. Performance and limitations of the tool, such as its next upgrades, aiming at increasing the user-friendly experience and extending the temporal range of data analyses, are analyzed and discussed.

scholarly journals Comparison of Landsat-8 and Sentinel-2 Data for Estimation of Leaf Area Index in Temperate Forests

2019 ◽  
Vol 11 (10) ◽  
pp. 1160 ◽  
Author(s):  
Lorenz Hans Meyer ◽  
Marco Heurich ◽  
Burkhard Beudert ◽  
Joseph Premier ◽  
Dirk Pflugmacher
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
High Sensitivity ◽  
Tree Cover ◽  
High Temporal Resolution ◽  
Landsat 8 ◽  
Linear Regression Models ◽  
Area Index ◽  
Spectral Bands ◽  
Sentinel 2

With the launch of the Sentinel-2 satellites, a European capacity has been created to ensure continuity of Landsat and SPOT observations. In contrast to previous sensors, Sentinel-2′s multispectral imager (MSI) incorporates three additional spectral bands in the red-edge (RE) region, which are expected to improve the mapping of vegetation traits. The objective of this study was to compare Sentinel-2 MSI and Landsat-8 OLI data for the estimation of leaf area index (LAI) in temperate, deciduous broadleaf forests. We used hemispherical photography to estimate effective LAI at 36 field plots. We then built and compared simple and multiple linear regression models between field-based LAI and spectral bands and vegetation indices derived from Landsat-8 and Sentinel-2, respectively. Our main findings are that Sentinel-2 predicts LAI with comparable accuracy to Landsat-8. The best Landsat-8 models predicted LAI with a root-mean-square error (RMSE) of 0.877, and the best Sentinel-2 model achieved an RMSE of 0.879. In addition, Sentinel-2′s RE bands and RE-based indices did not improve LAI prediction. Thirdly, LAI models showed a high sensitivity to understory vegetation when tree cover was sparse. According to our findings, Sentinel-2 is capable of delivering data continuity at high temporal resolution.

scholarly journals Multi-Dimensional Remote Sensing Analysis Documents Beaver-Induced Permafrost Degradation, Seward Peninsula, Alaska

2021 ◽  
Vol 13 (23) ◽  
pp. 4863
Author(s):  
Benjamin M. Jones ◽  
Ken D. Tape ◽  
Jason A. Clark ◽  
Allen C. Bondurant ◽  
Melissa K. Ward Jones ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Unmanned Aircraft ◽  
The Arctic ◽  
Series Data ◽  
Landsat 8 ◽  
Permafrost Degradation ◽  
Channel Network ◽  
Seward Peninsula ◽  
Sentinel 2

Beavers have established themselves as a key component of low arctic ecosystems over the past several decades. Beavers are widely recognized as ecosystem engineers, but their effects on permafrost-dominated landscapes in the Arctic remain unclear. In this study, we document the occurrence, reconstruct the timing, and highlight the effects of beaver activity on a small creek valley confined by ice-rich permafrost on the Seward Peninsula, Alaska using multi-dimensional remote sensing analysis of satellite (Landsat-8, Sentinel-2, Planet CubeSat, and DigitalGlobe Inc./MAXAR) and unmanned aircraft systems (UAS) imagery. Beaver activity along the study reach of Swan Lake Creek appeared between 2006 and 2011 with the construction of three dams. Between 2011 and 2017, beaver dam numbers increased, with the peak occurring in 2017 (n = 9). Between 2017 and 2019, the number of dams decreased (n = 6), while the average length of the dams increased from 20 to 33 m. Between 4 and 20 August 2019, following a nine-day period of record rainfall (>125 mm), the well-established dam system failed, triggering the formation of a beaver-induced permafrost degradation feature. During the decade of beaver occupation between 2011 and 2021, the creek valley widened from 33 to 180 m (~450% increase) and the length of the stream channel network increased from ~0.6 km to more than 1.9 km (220% increase) as a result of beaver engineering and beaver-induced permafrost degradation. Comparing vegetation (NDVI) and snow (NDSI) derived indices from Sentinel-2 time-series data acquired between 2017 and 2021 for the beaver-induced permafrost degradation feature and a nearby unaffected control site, showed that peak growing season NDVI was lowered by 23% and that it extended the length of the snow-cover period by 19 days following the permafrost disturbance. Our analysis of multi-dimensional remote sensing data highlights several unique aspects of beaver engineering impacts on ice-rich permafrost landscapes. Our detailed reconstruction of the beaver-induced permafrost degradation event may also prove useful for identifying degradation of ice-rich permafrost in optical time-series datasets across regional scales. Future field- and remote sensing-based observations of this site, and others like it, will provide valuable information for the NSF-funded Arctic Beaver Observation Network (A-BON) and the third phase of the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) Field Campaign.

scholarly journals A PRELIMINARY INVESTIGATION ON COMPARISON AND TRANSFORMATION OF SENTINEL-2 MSI AND LANDSAT 8 OLI

2018 ◽  
Vol XLII-3 ◽  
pp. 2619-2624 ◽  
Author(s):  
F. Chen ◽  
S. Lou ◽  
Q. Fan ◽  
J. Li ◽  
C. Wang ◽  
...  
Keyword(s):  
Linear Transformation ◽  
Spectral Response ◽  
Preliminary Investigation ◽  
Transformation Model ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Linear Transformation Model ◽  
Data Archives ◽  
The Difference ◽  
Sentinel 2

A PRELIMINARY INVESTIGATION ON COMPARISON AND TRANSFORMATION OF SENTINEL-2 MSI AND LANDSAT 8 OLI Timely and accurate earth observation with short revisit interval is usually necessary, especially for emergency response. Currently, several new generation sensors provided with similar channel characteristics have been operated onboard different satellite platforms, including Sentinel-2 and Landsat 8. Joint use of the observations by different sensors offers an opportunity to meet the demands for emergency requirements. For example, through the combination of Landsat and Sentinel-2 data, the land can be observed every 2–3 days at medium spatial resolution. However, differences are expected in radiometric values (e.g., channel reflectance) of the corresponding channels between two sensors. Spectral response function (SRF) is taken as an important aspect of sensor settings. Accordingly, between-sensor differences due to SRFs variation need to be quantified and compensated. The comparison of SRFs shows difference (more or less) in channel settings between Sentinel-2 Multi-Spectral Instrument (MSI) and Landsat 8 Operational Land Imager (OLI). Effect of the difference in SRF on corresponding values between MSI and OLI was investigated, mainly in terms of channel reflectance and several derived spectral indices. Spectra samples from ASTER Spectral Library Version 2.0 and Hyperion data archives were used in obtaining channel reflectance simulation of MSI and OLI. Preliminary results show that MSI and OLI are well comparable in several channels with small relative discrepancy (< 5 %), including the Costal Aerosol channel, a NIR (855–875 nm) channel, the SWIR channels, and the Cirrus channel. Meanwhile, for channels covering Blue, Green, Red, and NIR (785–900 nm), the between-sensor differences are significantly presented. Compared with the difference in reflectance of each individual channel, the difference in derived spectral index is more significant. In addition, effectiveness of linear transformation model is not ensured when the target belongs to another spectra collection. If an improper transformation model is selected, the between-sensor discrepancy will even largely increase. In conclusion, improvement in between-sensor consistency is possibly a challenge, through linear transformation based on model(s) generated from other spectra collections.

scholarly journals Introducing WIW for Detecting the Presence of Water in Wetlands with Landsat and Sentinel Satellites

2019 ◽  
Vol 11 (19) ◽  
pp. 2210 ◽  
Author(s):  
Lefebvre ◽  
Davranche ◽  
Willm ◽  
Campagna ◽  
Redmond ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Near Infrared ◽  
Ground Truth ◽  
Short Wave ◽  
Water Dynamics ◽  
High Temporal Resolution ◽  
Landsat 8 ◽  
Model Combining ◽  
Wide Range ◽  
Sentinel 2

Many wetlands are characterized by a vegetation cover of variable height and density over time. Tracking spatio-temporal changes in inundation patterns of these wetlands remains a challenge for remote sensing. Water In Wetlands (WIW) was predicted using a dichotomous partitioning of reflectance values encoded based on ground-truth (n = 4038) and optical-space derived (n = 7016) data covering all land cover types (n = 17) found in the Rhône delta, southern France. The models were developed with spectral data from Sentinel 2, Landsat 7, and Landsat 8 sensors, hence providing a monitoring tool that covers a 35-year period (same sensor for Landsat 5 and 7). A single model combining the near infrared (NIR ≤ 0.1558 to 0.1804, depending on sensors) and short-wave infrared (SWIR2 ≤ 0.0871 to 0.1131) wavelengths was identified by three independent analyses, each one using a different satellite. Overall accuracy of water maps ranged from 89% to 94% for the training samples and from 90% to 94% for the validation samples, encompassing standard water indices that systematically underestimate flooding duration under vegetation cover. Sentinel 2 provided the highest performance with a kappa coefficient of 0.82 for both samples. Such tool will be most useful for monitoring the water dynamics of seasonal wetlands, which are particularly sensitive to climate change while providing multiple services to humankind. Considering the high temporal resolution of Sentinel 2 (every 5 days), cumulative water maps built with the WIW logical rule could further be used for mapping a wide range of wetlands which are either periodically or permanently flooded.

scholarly journals UV/PAR radiation and DOM properties in surface coastal waters of the Canadian shelf of the Beaufort Sea during summer 2009

2013 ◽  
Vol 10 (4) ◽  
pp. 2761-2774 ◽  
Author(s):  
J. Para ◽  
B. Charrière ◽  
A. Matsuoka ◽  
W. L. Miller ◽  
J. F. Rontani ◽  
...  
Keyword(s):  
Organic Matter ◽  
Dissolved Organic Matter ◽  
Beaufort Sea ◽  
The Arctic ◽  
Mackenzie Delta ◽  
Fluorescence Excitation ◽  
Low Salinity ◽  
Fluorescent Dissolved Organic Matter ◽  
Main Driver ◽  
Mackenzie River

Abstract. Surface waters from the Beaufort Sea in the Arctic Ocean were evaluated for dissolved organic carbon (DOC), and optical characteristics including UV (ultraviolet) radiation and PAR (photosynthetically active radiation) diffuse attenuation (Kd), and chromophoric and fluorescent dissolved organic matter (CDOM and FDOM) as part of the MALINA field campaign (30 July to 27 August). Spectral absorption coefficients (aCDOM (350 nm) (m−1)) were significantly correlated to both diffuse attenuation coefficients (Kd) in the UV-A and UV-B and to DOC concentrations. This indicates CDOM as the dominant attenuator of both UV and PAR solar radiation and suggests its use as an optical proxy for DOC concentrations in this region. While the Mackenzie input is the main driver of CDOM dynamics in low salinity waters, locally, primary production can create significant increases in CDOM. Extrapolating CDOM to DOC relationships, we estimate that ∼16% of the DOC in the Mackenzie River does not absorb radiation at 350 nm. The discharges of DOC and its chromophoric subset (CDOM) by the Mackenzie River during the MALINA cruise are estimated as ∼0.22 TgC and 0.18 TgC, respectively. Three dissolved fluorescent components (C1–C3) were identified by fluorescence excitation/emission matrix spectroscopy (EEMS) and parallel factor (PARAFAC) analysis. Our results showed an aquatic dissolved organic matter (DOM) component (C1), probably produced in the numerous lakes of the watershed, that co-dominated with a terrestrial humic-like component (C2) in the Mackenzie Delta Sector. This aquatic DOM could partially explain the high CDOM spectral slopes observed in the Beaufort Sea.

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