JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 117, G03001, doi:10.1029/2011JG001928, 2012
Dissolved organic carbon and chromophoric dissolved organic matter properties of rivers in the USA Robert G. M. Spencer,1 Kenna D. Butler,2 and George R. Aiken2 Received 15 December 2011; revised 16 May 2012; accepted 20 May 2012; published 3 July 2012.
[1] Dissolved organic carbon (DOC) concentration and chromophoric dissolved organic matter (CDOM) parameters were measured over a range of discharge in 30 U.S. rivers, covering a diverse assortment of fluvial ecosystems in terms of watershed size and landscape drained. Relationships between CDOM absorption at a range of wavelengths (a254, a350, a440) and DOC in the 30 watersheds were found to correlate strongly and positively for the majority of U.S. rivers. However, four rivers (Colorado, Colombia, Rio Grande and St. Lawrence) exhibited statistically weak relationships between CDOM absorption and DOC. These four rivers are atypical, as they either drain from the Great Lakes or experience significant impoundment of water within their watersheds, and they exhibited values for dissolved organic matter (DOM) parameters indicative of autochthonous or anthropogenic sources or photochemically degraded allochthonous DOM and thus a decoupling between CDOM and DOC. CDOM quality parameters in the 30 rivers were found to be strongly correlated to DOM compositional metrics derived via XAD fractionation, highlighting the potential for examining DOM biochemical quality from CDOM measurements. This study establishes the ability to derive DOC concentration from CDOM absorption for the majority of U.S. rivers, describes characteristics of riverine systems where such an approach is not valid, and emphasizes the possibility of examining DOM composition and thus biogeochemical function via CDOM parameters. Therefore, the usefulness of CDOM measurements, both laboratory-based analyses and in situ instrumentation, for improving spatial and temporal resolution of DOC fluxes and DOM dynamics in future studies is considerable in a range of biogeochemical studies. Citation: Spencer, R. G. M., K. D. Butler, and G. R. Aiken (2012), Dissolved organic carbon and chromophoric dissolved organic matter properties of rivers in the USA, J. Geophys. Res., 117, G03001, doi:10.1029/2011JG001928.
1. Introduction [2] Dissolved organic matter (DOM) plays a multifaceted role in aquatic ecosystems and represents a fundamental player in global carbon budgets. DOM takes part in a range of processes within freshwater environments including biological, chemical and physical transformations [Jaffé et al., 2008]. The flux of DOM derived from terrestrial net ecosystem production on entering aquatic environments represents an essential link between terrestrial and aquatic ecosystems and dissolved organic carbon (DOC) is the most important intermediate in the global carbon cycle fueling microbial metabolism [Cole et al., 2007; Battin et al., 2008]. For instance, riverine export of DOC provides the largest flux of reduced carbon from land 1 Global Rivers Group, Woods Hole Research Center, Falmouth, Massachusetts, USA. 2 United States Geological Survey, Boulder, Colorado, USA.
Corresponding author: R. G. M. Spencer, Global Rivers Group, Woods Hole Research Center, 149 Woods Hole Rd., Falmouth, MA 02540, USA. (
[email protected]) ©2012. American Geophysical Union. All Rights Reserved. 0148-0227/12/2011JG001928
to ocean (0.25 Pg C yr1), as current POC flux estimates are lower (0.18 Pg C yr1), and underpins biogeochemical cycling in coastal margins [Hedges et al., 1997; Battin et al., 2008]. With respect to human health, DOM is a water quality constituent of concern as it has been shown to play a role in the formation of carcinogenic and mutagenic disinfection byproducts [Weishaar et al., 2003; Chow et al., 2007] and has also been linked to the transport and reactivity of toxic substances such as mercury [Dittman et al., 2009; Aiken et al., 2011; Bergamaschi et al., 2011]. Therefore, understanding the production, transport and fate of DOM in aquatic ecosystems is of direct relevance to studies addressing issues from water quality to bacterioplankton community structure and function [Crump et al., 2009; Krupa et al., 2012]. Consequently, DOC concentration and DOM composition data for rivers and streams are of interest to a diverse range of scientists and engineers across an assortment of environmental disciplines. [3] The concentration of DOC in streams and rivers typically ranges from approximately 0.5–50 mgL1 and is linked to climate and watershed characteristics [Mulholland, 2003]. Although DOC concentration is an extremely important measurement for deriving fluxes across the landscape and
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Figure 1. Map of the study sites within the U.S. See Table 1 for site names and details.
examining temporal and spatial trends, it provides little information about the biochemical composition or quality of DOM and hence its biogeochemical role [Hood et al., 2006; Jaffé et al., 2008; Fellman et al., 2009]. Colored or chromophoric dissolved organic matter (CDOM) parameters have been linked to DOM molecular weight [Peuravuori and Pihlaja, 1997; Helms et al., 2008] and composition in a number of recent studies [Boyle et al., 2009; Spencer et al., 2010a; Osburn and Stedmon, 2011]. Furthermore, the ability to not only examine DOM quality but also its biogeochemical processing (e.g., photochemical or microbial degradation) has previously been related to CDOM parameters [Cory et al., 2007; Fellman et al., 2009; Mann et al., 2012]. These relatively straightforward and inexpensive CDOM measurements can be undertaken with small volumes of water, and recent developments now allow for the possibility of in situ observations [Spencer et al., 2007; Saraceno et al., 2009; Pellerin et al., 2012]. The prospect of high-resolution in situ CDOM measurements is opening up the potential for analyses at the temporal and spatial scales required to truly understand DOM dynamics and variability in freshwater ecosystems. [4] Recent studies have examined the utility of CDOM measurements to derive DOC concentration and examine DOM composition in specific catchment types (e.g.,
northern high-latitude rivers) [Spencer et al., 2009a]. However, their applicability across a gradient of watershed types including watershed size and landscape drained has to date not yet been addressed. This study examined 30 fluvial sites in the U.S. draining all dominant land cover classes within the U.S. and ranging in size from small headwater streams to the mouth of the Mississippi. The aims of this study were twofold: first, we investigated the possibility of relating CDOM to DOC concentration in the comprehensive range of sites studied. We also tried to determine whether there are any unique features of the watersheds where the CDOM-DOC relationship breaks down that could explain these systems’ unsuitability for such an approach. Second, we tested the possibility of utilizing CDOM parameters to address DOM composition across the range of watersheds examined and determined which CDOM parameters may be of the greatest utility to future investigators seeking to address DOM quality in fluvial systems.
2. Materials and Methods 2.1. Study Sites [5] Thirty sites were examined in this study with the aim of covering the diverse range of watersheds found within the United States, with respect to both watershed size and
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Table 1. Riverine Study Site Numbers as Shown in Figure 1 River Number
River Name
River Abbreviation
n
Sampling Period
Watershed Size (km2)
Latitude
Longitude
Daily MaxQ/MinQ
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
Androscoggin Atchafalaya Colorado Columbia Edisto Evergreen Fishing Brook Hubbard Brook Hudson Little Wekiva Lookout Creek Lower Atchafalaya Mississippi Mobile Neversink Oak Creek Passadumkeag Penobscot Pike Porcupine Potomac Rio Grande Sacramento San Joaquin St. Lawrence St. Marys Susquehanna Tanana Yukon at Eagle Village Yukon at Pilot Station
AND ATC COL CUA EDI EVR FBR HBR HUD LWK LCR LAT MIS MOB NEV OCR PAS PEN PIK POR POT RIG SAC SAJ STL STM SUS TAN YRE YRP
12 27 27 18 15 15 21 31 21 14 12 32 29 25 14 12 27 62 14 35 21 27 22 23 28 14 21 30 28 57
2006–2007 2008–2010 2008–2010 2009–2010 2005–2008 2002–2005 2007–2009 2005–2007 2005–2009 2002–2006 2002–2004 2008–2010 2008–2010 2008–2010 2005–2006 2002–2004 2004–2007 2004–2008 2002–2004 2001–2010 2008–2010 2008–2010 2008–2010 2008–2010 2008–2010 2002–2006 2008–2010 2000–2007 2000–2002 2001–2010
8894 241687 638950 665367 7071 167 65 0.13 498 115 62 246308 2926686 111369 172 65 769 19460 660 76405 29966 456700 59569 35058 773888 1810 70188 66304 293964 831386
43.92 30.69 32.72 46.18 33.03 45.07 43.98 44.57 43.97 28.70 44.21 29.69 29.86 31.09 41.89 42.93 45.18 44.83 45.50 66.99 38.93 25.88 38.46 37.68 45.01 30.36 39.66 64.57 64.79 61.93
69.97 91.74 114.72 123.18 80.39 88.68 74.27 72.25 74.13 81.39 122.26 91.22 89.98 87.98 74.59 87.87 68.47 68.70 88.00 143.14 77.12 97.45 121.50 121.27 74.80 82.08 76.17 149.09 141.20 162.88
35.4 8.3 12.7 7.0 11.2 24.1 —– 4699.2 —– —– 125.0 8.3 6.1 7.5 193.2 420.8 —– 31.2 12.5 276.5 165.6 191 12.9 58.1 1.6 1970.4 304.2 16.1 21.3 31.1
landscape drained (Figure 1, Table 1). For example, watersheds range in size from headwater streams (e.g., Hubbard Brook WS6; 0.132 km2) to the mouth of the Mississippi River (2,926,686 km2). Focus was especially placed on larger watersheds (e.g., Atchafalaya, Colorado, Columbia, Mississippi, Mobile, Potomac, Rio Grande, Sacramento, San Joaquin, St. Lawrence, Susquehanna and Yukon) near their terminus to examine the applicability of utilizing CDOM to derive DOC export to coastal waters. The rivers chosen also include a diverse range of terrestrial ecosystems including permafrost underlain (e.g., Porcupine), forest (e.g., Androscoggin, Evergreen, Penobscot, Pike), agriculturally impacted (e.g., Mississippi, Sacramento, San Joaquin), urban (e.g., Little Wekiva, Oak Creek), swamp (e.g., Edisto, St. Marys), arid and semi-arid highly regulated systems (e.g., Colorado, Columbia, Rio Grande) and rivers draining from the Great Lakes (e.g., St. Lawrence). 2.2. Water Sample Collection and Processing [6] Water samples were collected across the annual hydrograph to encompass the range of discharge conditions for each study site. The majority of samples were collected as part of the U.S. Geological Survey National Stream Quality Accounting Network (NASQAN) and National Water Quality Assessment (NAQWA) programs from 2000–2010 (Table 1). Sample collection took place over a minimum of two years and up to a maximum of ten years and all analyses were conducted in one laboratory. All water samples were filtered in the field through Gelman AquaPrep 600 capsule filters (0.45 mm)
that were pre-rinsed with sample water. The hydrophobic organic acid fraction (HPOA) was obtained following established protocols [Aiken et al., 1992; Spencer et al., 2010b]. In brief, samples were acidified to pH 2 using HCl and passed through a column of XAD-8 resin. The HPOA fraction was retained on the XAD-8 resin and then back eluted with 0.1 M NaOH. 2.3. Dissolved Organic Carbon and Chromophoric Dissolved Organic Matter Analyses [7] Dissolved organic carbon measurements were carried out on a heated persulfate oxidation OI Analytical Model 700 TOC analyzer [Aiken, 1992]. UV-visible absorbance measurements were undertaken within 48 h of collection on a Hewlett-Packard photo-diode array spectrophotometer (model 8453) between 200 and 800 nm using a 10 mm quartz cell. All samples were analyzed at constant laboratory temperature and sample spectra were referenced to a blank spectrum of distilled water. All absorbance data presented in this manuscript are expressed as absorption coefficients, a (l), in units of m1 [Hu et al., 2002]. Chromophoric DOM (CDOM) absorption coefficients (Napierian) were calculated from: aðlÞ ¼ 2:303AðlÞ=l;
ð1Þ
where A(l) is the measured absorbance and l is the cell path length in meters. The CDOM absorption ratio at 250 nm to 365 nm was calculated (a250:a365) and SUVA254 values were derived by dividing the UV absorbance (A) at l = 254 nm
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Table 2. Mean (SD) Riverine Dissolved Organic Carbon (DOC), Fraction HPOA and Chromophoric Dissolved Organic Matter (CDOM) Parameters River Abbreviation
DOC (mgL1)
Fraction HPOA
SUVA254 (LmgC1m1)
a250:a365
S275–295 (103nm1)
AND ATC COL CUA EDI EVR FBR HBR HUD LWK LCR LAT MIS MOB NEV OCR PAS PEN PIK POR POT RIG SAC SAJ STL STM SUS TAN YRE YRP
6.4 (0.9) 5.2 (0.9) 3.1 (0.4) 2.0 (0.3) 8.9 (3.4) 4.5 (3.6) 7.3 (1.9) 3.1 (1.1) 5.3 (1.0) 5.3 (2.5) 1.0 (0.4) 5.1 (0.7) 4.1 (0.5) 5.5 (1.2) 2.1 (1.5) 6.7 (1.9) 12.0 (4.3) 9.8 (2.9) 8.0 (5.0) 10.0 (5.9) 3.3 (0.6) 4.8 (0.5) 2.4 (0.8) 3.8 (1.1) 2.7 (0.2) 42.1 (16.0) 2.5 (0.5) 3.2 (1.9) 5.2 (3.0) 8.3 (5.0)
0.56 (0.01) 0.47 (0.04) 0.39 (0.03) 0.42 (0.04) 0.54 (0.04) 0.45 (0.07) 0.54 (0.03) 0.49 (0.04) 0.52 (0.03) 0.46 (0.04) 0.43 (0.09) 0.47 (0.03) 0.45 (0.02) 0.50 (0.03) 0.47 (0.05) 0.44 (0.04) 0.61 (0.04) 0.58 (0.03) 0.52 (0.07) 0.51 (0.05) 0.40 (0.04) 0.35 (0.03) 0.39 (0.05) 0.41 (0.03) 0.28 (0.03) 0.67 (0.06) 0.40 (0.04) 0.46 (0.07) 0.50 (0.06) 0.51 (0.05)
3.59 (0.15) 3.22 (0.33) 1.67 (0.22) 2.62 (0.43) 3.75 (0.29) 3.08 (0.60) 3.89 (0.29) 2.80 (0.27) 3.48 (0.22) 2.85 (0.44) 2.45 (0.35) 3.13 (0.24) 2.99 (0.23) 3.45 (0.34) 2.47 (0.66) 2.86 (0.52) 4.19 (0.30) 3.80 (0.26) 3.71 (0.55) 3.02 (0.55) 2.31 (0.33) 2.03 (0.24) 2.41 (0.51) 2.47 (0.25) 1.31 (0.16) 4.56 (0.28) 2.25 (0.28) 2.68 (0.54) 3.00 (0.64) 3.08 (0.47)
5.05 (0.35) 5.25 (0.45) 9.05 (1.47) 5.89 (1.09) 4.70 (0.23) 4.89 (0.44) 4.81 (0.13) 6.55 (0.86) 5.16 (0.31) 5.50 (0.46) 6.46 (2.32) 5.41 (0.53) 5.45 (0.61) 4.80 (0.53) 6.65 (2.43) 6.19 (0.76) 4.56 (0.17) 4.98 (0.30) 4.87 (0.42) 5.72 (1.14) 5.73 (0.77) 7.38 (0.84) 5.34 (0.72) 5.93 (1.21) 9.65 (2.30) 4.20 (0.27) 5.79 (0.68) 5.66 (1.10) 5.93 (1.12) 5.52 (0.90)
14.53 (0.76) 14.85 (0.80) 21.69 (1.56) 16.33 (1.37) 13.32 (0.41) 13.62 (0.40) 13.85 (0.62) 16.02 (1.14) 14.64 (0.73) 16.02 (1.05) 13.19 (1.10) 15.32 (0.83) 15.14 (0.80) 14.27 (1.63) 15.53 (1.65) 15.46 (1.20) 13.38 (0.59) 14.13 (0.89) 14.28 (1.61) 15.54 (2.06) 15.74 (1.71) 19.80 (1.45) 15.69 (1.43) 15.71 (0.73) 22.96 (1.76) 12.47 (0.78) 15.33 (1.57) 16.13 (1.78) 15.95 (2.02) 15.26 (1.87)
by the DOC concentration (mgL1) and is reported in the units of liter per milligram carbon per meter [Weishaar et al., 2003]. The spectral slope parameter (S) was calculated using a nonlinear fit of an exponential function to the absorption spectrum in the ranges of 275–295 nm and 350–400 nm using the equation:
S350–400 (103nm1) 16.69 16.63 18.99 16.87 16.92 15.97 17.31 20.03 17.32 16.98 16.18 16.88 16.56 16.23 17.86 17.92 16.44 17.05 17.04 18.17 16.58 17.76 16.35 16.87 18.95 16.65 17.34 17.77 18.17 17.89
(0.62) (0.88) (2.09) (1.13) (0.64) (0.89) (0.28) (1.56) (0.27) (0.59) (2.56) (0.86) (1.24) (0.75) (1.27) (1.05) (0.24) (0.33) (0.29) (1.67) (1.79) (1.36) (1.26) (0.87) (3.17) (0.57) (1.45) (1.90) (2.14) (1.45)
SR 0.87 (0.04) 0.89 (0.04) 1.15 (0.09) 0.97 (0.06) 0.79 (0.03) 0.86 (0.05) 0.80 (0.03) 0.80 (0.05) 0.84 (0.04) 0.94 (0.05) 0.82 (0.09) 0.91 (0.04) 0.92 (0.06) 0.88 (0.08) 0.86 (0.10) 0.86 (0.06) 0.81 (0.04) 0.83 (0.04) 0.80 (0.07) 0.86 (0.08) 0.96 (0.13) 1.12 (0.11) 0.96 (0.07) 0.93 (0.04) 1.23 (0.16) 0.75 (0.06) 0.89 (0.14) 0.89 (0.06) 0.88 (0.07) 0.85 (0.07)
3. Results
1992]. A higher fraction HPOA therefore typically indicates an increased contribution from allochthonous organic matter sources (i.e., terrestrial), whereas a lower fraction HPOA is indicative of organic matter from autochthonous sources (i.e., algal or microbial) or photodegraded DOM [McKnight and Aiken, 1998; Cory et al., 2007]. For example, microbially dominated Antarctic lakes have been shown to have a fraction HPOA of approximately 0.23 [Aiken et al., 1992], whereas allochthonous-dominated aquatic systems have greater fraction HPOA values (e.g., Arctic blackwater stream = 0.47 [Cory et al., 2007] and Suwannee River = 0.58 [Aiken et al., 1992]). Increasing fraction HPOA is also important with respect to toxic substances such as mercury as it acts as a ligand and studies have shown strong positive linear relationships between the fraction HPOA and dissolved mercury concentration [Schuster et al., 2008; Dittman et al., 2009].
3.1. Bulk Dissolved Organic Carbon and Fractionation [8] Mean riverine DOC concentrations ranged from 1.0 mgL1 (0.4 SD) in Lookout Creek to 42.1 mgL1 (16.0 SD) in St. Marys (Table 2, Figures 2a–2b). The majority of U.S. rivers had mean riverine DOC concentrations between 2.0–10.0 mgL1. Mean fraction HPOA ranged from 0.28 (0.03 SD) in the St. Lawrence to 0.67 (0.06 SD) in St. Marys and the bulk of rivers studied had a mean fraction HPOA between 0.40–0.60 (Table 2, Figures 2c–2d). The HPOA fraction has historically been described as primarily composed of fulvic acid with the remainder as humic acid and thus represents the high molecular weight, aromatic carbon-dominated fraction of DOM [Aiken et al., 1979,
3.2. Chromophoric Dissolved Organic Matter [9] Mean SUVA254 values in the rivers examined ranged from 1.31 L mg C1 m1 (0.16 SD) for the St. Lawrence to 4.56 L mg C1 m1 (0.28 SD) in St. Marys (Table 2, Figures 3a–3b). The majority of the rivers examined in this study had mean SUVA254 values between 2.00 and 3.80 L mg C1 m1 (Table 2, Figures 3a–3b). SUVA254 values have been positively correlated to the percent aromaticity of DOM as measured by 13C-NMR [Weishaar et al., 2003]. The lowest mean SUVA254 values observed in U.S. rivers are comparable to values reported for HPOA isolates from microbial-dominated end-members such as Pony Lake (1.7 L mg C1 m1) and Lake Fryxell (1.8 L mg C1 m1;
aðlÞ ¼ aðlref Þesðllref Þ ;
ð2Þ
where a(l) is the absorption coefficient of CDOM at a specified wavelength, lref is a reference wavelength and S is the slope fitting parameter. The spectral slope ratio (SR) was calculated as the ratio of S275–295 to S350–400 [Helms et al., 2008].
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Figure 2. Box plots of (a–b) DOC, and (c–d) fraction of hydrophobic organic acid fraction (HPOA) for the 30 rivers. Note the different y axis scale between Figures 2a and 2b. The black dotted line and the black solid line represent the mean and the median, respectively. The horizontal edges of the boxes denote the 25th and 75th percentiles, the whiskers denote the 10th and 90th percentiles, and black circles represent outliers. Weishaar et al., 2003], and aquatic systems with little vascular plant input (e.g., groundwaters: 1.3–1.6 L mg C1 m1) [Spencer et al., 2008]. Similarly, the highest mean SUVA254 values reported in this study are comparable to values for HPOA isolates from allochthonous-dominated endmembers (e.g., Ogeechee and Suwannee Rivers; 3.2– 5.3 L mg C1 m1) [Weishaar et al., 2003] and aquatic systems with significant vascular plant inputs (e.g., blackwaters: 3.4–4.5 L mg C1 m1) [Spencer et al., 2008, 2010a]. [10] The a250:a365 ratio has previously been related to the aromatic content and molecular size of DOM with increasing values indicating a decrease in aromaticity and molecular size [Peuravuori and Pihlaja, 1997]. Mean a250:a365 values ranged from 4.20 (0.27 SD) in St. Marys to 9.65 (2.30 SD) in the St. Lawrence, with the bulk of a250:a365 mean values in the rivers examined ranging from 5.00–6.50 (Table 2, Figures 3c–3d). The lowest and highest mean a250: a365 values in St. Marys and the St. Lawrence are comparable to allochthonous-dominated blackwaters of the Great Dismal
Swamp (4.57–4.64) and coastal waters (e.g., Georgia Bight = 8.7 1.4), respectively [Helms et al., 2008]. [11] The spectral slope parameter (S) describes the spectral dependence of the CDOM absorption coefficient and as a result provides information with respect to the quality of the CDOM [Blough and Del Vecchio, 2002). S has been shown to vary with the source of CDOM and also to be sensitive to biological and photochemical alteration of the source material [Stedmon and Markager, 2001; Obernosterer and Benner, 2004; Osburn and Stedmon, 2011]. Typically, a steeper S value has been related to a decrease in molecular weight and aromaticity of DOM [Blough and Green, 1995; Helms et al., 2008]. Historically, S has been calculated over a range of wavelengths and 275–295 nm (S275–295) and 350– 400 nm (S350–400) were chosen because Helms et al. [2008] in their extensive study of S in a range of aquatic ecosystems and DOM sources observed the first derivative of the natural log spectra had the greatest variation in these ranges. The slope ratio (SR) of S275–295: S350–400 has also been
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Figure 3. Box plots of (a–b) SUVA254, and (c–d) a250:a365 for the 30 rivers. The black dotted line and the black solid line represent the mean and the median, respectively. The horizontal edges of the boxes denote the 25th and 75th percentiles, the whiskers denote the 10th and 90th percentiles, and black circles represent outliers. shown to be sensitive to characterizing CDOM in natural waters, with lower relative values indicative of DOM of higher molecular weight, greater aromaticity and increasing vascular plant inputs [Helms et al., 2008; Spencer et al., 2010a; Osburn et al., 2011]. [12] Mean S275–295 values ranged from 12.47 103 nm1 (0.78 SD) in St. Marys to 22.96 103 nm1 (1.76 SD) in the St. Lawrence and the majority of U.S. rivers exhibited S275–295 values between 13.00–16.50 103 nm1 (Table 2, Figures 4a–4b). The shallowest mean S275–295 values are comparable to allochthonous-dominated waters such as the Congo River (12.34 103 nm1) [Spencer et al., 2009b], the Yukon River at the peak of the freshet (12.28 103 nm1) [Spencer et al., 2009a] and the Great Dismal Swamp (12.7– 12.8 103 nm1) [Helms et al., 2008]. The steepest mean S275–295 values are comparable to data from U.S. coastal waters (e.g., 24.00 103 nm1 in the Georgia Bight [Helms et al., 2008] and 22.00–28.00 103 nm1 in surface waters of the northern Gulf of Mexico [Shank and Evans, 2011]), and
the minimum values for lakes in the Great Plains (e.g., 22.18 103 nm1) [Osburn et al., 2011], which represent DOM from autochthonous sources and photochemically degraded allochthonous DOM. Mean S350–400 values followed a similar trend to S275–295 values but covered a narrower range with shallowest values in Evergreen River of 15.97 103 nm1 (0.89 SD) and steepest values in Hubbard Brook of 20.03 103 nm1 (1.56 SD) (Table 2, Figures 4c–4d). Most U.S. rivers had S350–400 values between 16.50–18.25 103 nm1. As observed for S275–295, the steepest mean S350–400 values are comparable to previously reported data for coastal waters (18.00–19.00 103 nm1) [Shank and Evans, 2011] and prairie lakes (22.41 103 nm1) [Osburn et al., 2011]. Similarly, the shallowest mean S350–400 values are analogous to data reported from aquatic ecosystems with high allochthonous inputs such as the Congo River (15.21 103 nm1) [Spencer et al., 2009b]. [13] The mean SR values ranged from 0.75 (0.06 SD) in St. Marys to 1.23 (0.16 SD) in the St. Lawrence, with the
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Figure 4. Box plots of (a–b) S275–295, (c–d) S350–400, and (e–f) SR for the 30 rivers. Note the different y axis scale between Figures 4a and 4b and between Figures 4e and 4f. The black dotted line and the black solid line represent the mean and the median, respectively. The horizontal edges of the boxes denote the 25th and 75th percentiles, the whiskers denote the 10th and 90th percentiles, and black circles represent outliers. majority of U.S. rivers ranging from 0.80–0.95 (Table 2, Figures 4e–4f). Lower mean SR values are similar to data reported from Arctic rivers at the peak of the freshet (e.g., Yukon = 0.79; Yenisey = 0.79) when they receive significant vascular plant inputs [Spencer et al., 2009a; Stedmon et al., 2011], or blackwater tropical rivers during the onset of the wet season (0.79) [Spencer et al., 2010a]. The highest mean SR values are comparable to mean values from prairie
lakes (1.36) [Osburn et al., 2011] and coastal waters (1.20– 1.40) [Shank and Evans, 2011].
4. Discussion 4.1. Deriving DOC Concentration From CDOM in U.S. Rivers [14] Historically, relationships between CDOM and DOC have principally been examined in coastal waters [Ferrari
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Figure 5. Relationships between dissolved organic carbon (DOC) and chromophoric dissolved organic matter (CDOM) absorption (a254, black circles, black line; a350, gray circles, gray line; and a440, white circles, black dashed line): (a) Mississippi River and (b) Hubbard Brook.
et al., 1996; Vodacek et al., 1997; Rochelle-Newall and Fisher, 2002]. Although CDOM represents only a fraction of the total DOC pool a number of studies have reported strong correlations between CDOM properties and DOC concentration in coastal waters [see Del Vecchio and Blough, 2004, and reference therein; Mannino et al., 2008]. The investigation of CDOM and DOC relationships in riverine environments is also extremely pertinent to facilitate the development of improved DOC flux estimates through increased temporal coverage via recently developed in situ instrumentation [Spencer et al., 2007; Saraceno et al., 2009;
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Downing et al., 2009; Pellerin et al., 2012]. Furthermore, a recent study by Griffin et al. [2011] highlighted the potential to derive DOC via CDOM in a major river (Kolyma, Siberia) using Landsat satellite imagery. Therefore, if robust CDOM versus DOC relationships can be derived for rivers they can be utilized to examine shifts in the export and timing of the flux of DOC in highly dynamic periods (e.g., storms, snowmelt) in small watersheds when the majority of DOC export occurs [Inamdar et al., 2006; Saraceno et al., 2009; Pellerin et al., 2012], and also to improve estimates of the land-ocean flux of terrestrial DOC from major rivers [Spencer et al., 2009a]. To assess this objective in the diverse range of U.S. rivers studied here with respect to both watershed size and landscape drained we examined CDOM absorption relationships at a254, a350 and a440 to DOC (Figure 5, Table 3). [15] Absorption coefficients at 254, 350 and 440 nm correlated strongly and positively with DOC concentration for the majority of U.S. rivers (Table 3). Examples of relationships between DOC and a254, a350 and a440 are shown for the smallest (Hubbard Brook WS6) and largest (Mississippi) watersheds studied in Figure 5. The relationship between absorption coefficient and DOC concentration varied between the wavelengths studied with typically stronger relationships observed at shorter wavelengths. CDOM absorption spectra typically decrease in an approximately exponential fashion with increasing wavelength, and so the accuracy of CDOM measurements decreases at longer wavelengths resulting in a weakening in the correlation [Baker et al., 2008]. This is particularly the case for samples exhibiting low CDOM absorption values. [16] In the U.S. rivers examined in this study a number of rivers consistently standout as having statistically weak relationships between CDOM and DOC concentration. The Rio Grande (r2 = 0.453; p = 0.0001) and the St. Lawrence (r2 = 0.206; p = 0.0154) are the only two rivers that do not exhibit a statistically significant relationship at the
