A systematic examination of the relationship between CDOM and 1 DOC for various inland waters across China

Chromophoric dissolved organic matter (CDOM) plays a vital role in 9 aquatic ecosystems. Strong relationship has been proven between CDOM and 10 dissolved organic carbon (DOC), which set the basis for remote estimation of DOC 11 with remote sensing data. An algorithm has been developed to retrieve DOC via 12 CDOM absorption at 275 and 295 nm with coastal waters. However, the relationship 13 between DOC and aCDOM(275) and aCDOM(295) for different types of inland waters are 14 still not clear. Further, is the relationship stable with different types of inland waters? 15 In the current investigation, samples from fresh lakes, saline lakes, rivers or streams, 16 urban water bodies, ice-covered lakes were examined. The regression model slopes 17 range from 1.03 for urban waters to 3.13 for river water, with extreme low slope value 18 for highly saline waters (slope is about 0.3); while coefficient of determinations (R 2 ) 19 range from 0.71 (urban waters) to 0.93 (winter waters). The specific CDOM 20 absorption (SUVA254) showed the similar trend, i.e., low values were observed for 21 saline water and waters from semi-arid or arid regions, where strong photo-bleaching 22 Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-380, 2016 Manuscript under review for journal Hydrol. Earth Syst. Sci. Published: 22 August 2016 c © Author(s) 2016. CC-BY 3.0 License.


Introduction
Inland waters play a substantial role for regulating climate at regional scale, and also for global carbon cycling (Cole et al., 2007;Tranvik et al., 2009).Compared with other terrestrial ecosystems, e.g., forest, grassland and agricultural ecosystem, inland waters only occupy a small fraction (3.5%) of the earth surface (Verpoorter et al., 2014).However, they play a disproportional role for global carbon cycling with respect to carbon transportation, transformation and carbon storage (Tranvik et al., 2009;Verpoorter et al., 2014).According to Tranvik et al. (2009), 2.9 Pg C/yr was imported from terrestrial ecosystems to inland waters, of which about 0.6 Pg C was buried in the lake sediment each year, 1.4 Pg C/yr was released into the air as CO 2 or Hydrol.Earth Syst.Sci. Discuss., doi:10.5194/hess-2016-380, 2016 Manuscript under review for journal Hydrol.Earth Syst.Sci.Published: 22 August 2016 c Author(s) 2016.CC-BY 3.0 License.methane, and the rest of 0.9 Pg C/yr was exported to the ocean via river channels.
However, the amount of C retained in the inland waters is still not clear or the uncertainty is still remained for the current knowledge (Raymond et al., 2013).It has been proposed by several researchers that remote sensing might provide a promising tool for quantification of various carbon fractions and carbon storage for inland waters (Cole et al., 2007;Tranvik et al., 2009;Song et al., 2013;Kutser et al., 2015).
Colored dissolved organic matter (CDOM) is one of the largest bioactive reservoirs at earth's surface (Para et al., 2010), and influences light transmittance in aquatic ecosystems (Vodacek et al., 1997;Williamson and Rose, 2010).Dissolved organic carbon (DOC), the major component of CDOM, is a source of nutrients and energy for heterotrophic bacteria, and the mineralization of allochthonous DOC in the aquatic systems into net source of CO 2 in the atmosphere (Jaffe et al., 2008;Raymond et al., 2013).DOC also serves to mediate the chemical environment through production of organic acids (Landon and Bishop, 2002;Brooks and Lemon, 2007), enhance or alleviate toxicity of heavy metals (Cory et al., 2006).A bunch of researches have been conducted to characterize the spatial and seasonal variations of CDOM and DOC for both inland and oceanic waters (Vodacek et al., 1997;Neff et al., 2006;Stedmon et al., 2011) in ice free season, but less is known about saline lakes (Song et al., 2013;Wen et al., 2016), urban waters influenced by sewage effluent and ice covered waters in winter (Belzile et al., 2000(Belzile et al., , 2002)).
The relationship between DOC and CDOM sets a bridge for remote estimation of DOC in both oceanic water (Hoge et al., 1996;Bricaud et al., 2012;Nelson et al., Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-380, 2016 Manuscript under review for journal Hydrol.Earth Syst.Sci.Published: 22 August 2016 c Author(s) 2016.CC-BY 3.0 License.2012) and inland waters (Yu et al., 2010;Griffin et al., 2011;Song et al., 2013;Zhu et al., 2013).Thus, various attempts have been made to examine the relationship between DOC and CDOM.According to Fichot and and Benner (2011), close relationship between CDOM and DOC was observed for water from Mexican Gulf, and stable regression model was established between DOC and a CDOM (275) and a CDOM (295).Similar findings also observed in other estuary waters along a salinity gradient, e.g., the Baltic Sea along the Finish Gulf (Kowalczuk et al., 2006), the Chesapeake Bay (Le et al., 2013).However, investigation by Chen et al. ( 2004) also indicated that the relationship between CDOM and DOC was not conservative due to some process could either be estuarine mixing or photo-degradation.Similar arguments were raised by Spencer et al. (2009) for waters from Congo River and for waters across the mainland of USA (Spencer et al., 2012).Jiang et al. (2012) also examined the relationship between DOC and CDOM for Lake Taihu, and found that a relative stable relationship was observed for water samples collected in different seasons except those measured in winter.Further, obvious seasonal variations were observed, which could be explained by the mixing of various endmembers of CDOM originated from different types of terrestrial ecosystems and internal source as well (Zhang et al., 2010;Spencer et al., 2012).
As argued by Tranvik et al. (2009) andRaymond et al. (2013), remote sensing technology was supposed to play a vital role in quantification of inland waters for carbon cycling.To date, various attempts have been made to characterize DOC and CDOM for both oceanic and inland waters and assess the relationship between these Hydrol.Earth Syst.Sci. Discuss., doi:10.5194/hess-2016-380, 2016 Manuscript under review for journal Hydrol.Earth Syst.Sci.Published: 22 August 2016 c Author(s) 2016.CC-BY 3.0 License.two forms of carbons (Vodacek et al., 1999;Fichot and Benner, 2011;Griffin et al., 2011;Spencer et al., 2012;Zhu et al., 2013).However, the variation for this relationship with various types of inland waters, especially saline water and urban water bodies were not examined in depth.In this study, the characteristics of DOC and CDOM within different types of inland waters across China were examined to determine its spatial feature associated with landscape variations, hydrologic conditions and saline gradients.To specific, the objectives of this study are to: 1) examine the relationship between CDOM and DOC concentrations across a wide range of waters with various physical, chemical and biological conditions, 2) compare the behavior of the relationships between DOC and CDOM for various water types, and 3) establish model for the relationship between DOC and CDOM based on the sorted CDOM absorption features, e.g., SUVA254 and the ratio of a 250 : a 365 (DeHaan, 1993;Weishaar et al., 2003).To address these objectives, 1504 water samples were collected in fresh and saline water lakes, reservoirs, rivers and streams, ponds across China that encompass a broad ranges of DOC, CDOM concentrations with various natural conditions, e.g., temperature, precipitation, hydrology, morphology, soil type and landscape gradients.The findings from this research is essential for understanding the relationship between DOC and CDOM with various types of inland waters, which set a bridge for remote estimation of DOC contained in lakes or reservoirs.

Materials and Methods
The dataset is composed of five subsets of samples collected from various types of waters across China (Table 1), which encompassed a wide range of DOC and CDOM

Water quality determination
In the laboratory, water salinity was measured through DDS-307 electrical conductivity (EC) meter (μS/cm) at room temperature (20±2℃) and transformed to practical salinity units (PSU).Water samples were filtered and extracted with acetone for chlorophyll-a (Chl-a) concentration determination using a Shimadzu UV-2050PC Hydrol.Earth Syst.Sci. Discuss., doi:10.5194/hess-2016-380, 2016 Manuscript under review for journal Hydrol.Earth Syst.Sci.Published: 22 August 2016 c Author(s) 2016.CC-BY 3.0 License.spectrophotometer (Song et al., 2013).Total suspended matter (TSM) was determined gravimetrically, details can be found in Song et al. (2013).DOC concentrations were determined by high temperature combustion (HTC) with water samples filtered through pre-combusted 0.45 μm GF/F filters (Song et al., 2013).The standards for dissolved total carbon (DTC) were prepared from reagent grade potassium hydrogen phthalate in ultra-pure water, while dissolved inorganic carbon (DIC) were determined using a mixture of anhydrous sodium carbonate and sodium hydrogen carbonate.DOC was calculated by subtracting DIC from DTC, both of which were measured by a Total Organic Carbon Analyzer (Shimadzu, TOC-VCPN).Total nitrogen (TN) was measured based on the absorption levels at 146 nm of water samples decomposed with alkaline potassium peroxydisulfate.Total phosphorus (TP) was determined using the molybdenum blue method after the samples were digested with potassium peroxydisulfate (APHA, 1998).A PHS-3C pH meter was used to determine pH at room temperature (20±2 ℃) in laboratory.

CDOM absorption and spectral slope (S) derivation
First, all the samples were filtered at low pressure, first through a pre-combusted Whatman GF/F filter (0.7μm) in the laboratory, and then the filtrate were further filtered through pre-rinsed 25 mm Millipore membrane cellulose filter (0.22 µm) at a low pressure.Absorption spectra were obtained between 200 and 800 nm at 1 nm increment using a Shimadzu UV-2600PC UV-Vis (Shimadzu Inc., Japan) dual beam spectrophotometer through a 1 cm quartz cuvette (or 5 cm cuvette for ice melted water samples), and Milli-Q water was used as reference for CDOM absorption measurements.The absorption coefficient (a CDOM ) was calculated from the measured optical density (OD) of samples using Eq. ( 1): where β is the cuvette path length (0.01 or 0.05m) and 2.303 is the conversion factor of base 10 to base e logarithms.To remove the scattering effect from fine particles remained in the filtered solutions, a necessitated correction was implemented.The OD (null) is the average optical density over 740-750 nm, which is assumed to be zero for the absorbance of CDOM (Zhang et al., 2007).All absorption measurements were conducted within 48 h after the samples were shipped back to the laboratory.The specific CDOM absorption coefficients were calculated as the ratio of a CDOM (λ) against DOC concentration, and denoted as a* CDOM (λ) with units of (m -1 .L.mg -1 ).In the current study, the value of a* CDOM (λ) at reference wavelength of 350 nm was calculated as suggested by previous investigations (Vodacek et al., 1999;Fichot and Benner, 2011), which will be further used as spectral index for establishing relationship between CDOM and DOC.
A CDOM absorption spectrum, a CDOM (), is generally expressed as an exponential function (Babin et al., 2003): where a CDOM ( i ) is the CDOM absorption at a given wavelength  i , a CDOM ( r ) is the absorption estimate at the reference wavelength (i.e.,  r = 440 nm) and S is the spectral slope.The S is calculated by fitting the data to a nonlinear model over a wavelength range of 300 to 500 nm as suggested by Zhang et al. (2007).

Results and discussion
In all datasets collected over different types of water bodies across China, a large diversity of inland waters with varying water qualities was encountered.High average Chl-a concentrations (46.44±59.71µgL -1 ) are observed in these waters, which ranged between 0.28-521.12µg/L.As shown in Table 1, fresh water, saline water and particularly urban water bodies all exhibited high TN and TP values, indicating that most of the waters are highly eutrophic.It should be noted that even winter water samples also revealed high Chl-a concentration (7.3±19.7µgL - ), which is resulted from high TN (4.3±5.4mgL - ) and TP (0.7±0.6mgL -1 ) concentrations even under ice covered conditions.Due to regional hydro-geologic and climatic conditions, most waters in the semi-arid and arid regions have high electric conductivity (EC: 1067-41000 µs/cm) and pH values (7.1-11.4).Overall, waters are highly turbid by showing high concentration of TSM (119.55 ± 131.37 mgL -1 ), but different water types demonstrated obvious variations in the water column (Table 1).Hydrographic conditions exert strong impact on water turbidity and TSM concentration, thus these two parameters for river and stream samples were not measured in this study (Table 1).
Large variations of water quality parameters extensive geographic conditions set a more representative basis for examination of the relationship between DOC and CDOM, which is potentially helpful for remote estimate of DOC through CDOM absorption properties (Kutser et al., 2015). [Insert

DOC concentrations in various types of waters
The range of DOC concentrations spanned an order of magnitude over these waters being investigated.As shown in  et al., 2002).This condensed effect is particularly marked for these shallow water bodies, where ice forming remarkably condensed the DOC in the underlying waters (Zhao et al., 2016).As shown in lower DOC concentration, while these from Liaohe and Inner Mongolia showed much higher concentration.Likewise, large variations were exhibited for saline waters of different regions (Table 2).Saline waters from the Qinghai and Hulunbir showed much higher DOC concentration, while these from the Xilinguole Plateau and the Songnen Plain exhibited relative lower DOC concentrations.
[Insert Table 2 about here]

Fresh waters
The relationships between DOC and CDOM have been examined based on CDOM absorption spectra at different wavelength (Fichot and Benner, 2011;Spencer et al., 2012).As suggested by Fichot and Benner (2011), CDOM absorptions at 275 nm (CDOM275) and 295 nm have stable performances for DOC estimates.As shown in  et al., 2008).Further, soils in Northeast China are endorsed with high organic carbon, which may also contribute high concentration of DOC and CDOM in waters from this region (Jin et al., 2016).Compared with waters from East and South China, water bodies in Northeast China show less algal bloom due to the low temperature, thus autochthonous CDOM is less presented in waters from Northeast China (Song et al., 2013;Zhao et al., 2016).

Saline lakes
As shown in Fig. 2b, a strong relationship (R 2 = 0.85) between DOC and CDOM275 was demonstrated for saline waters.However, compared to fresh waters, much lower regression slope value (slope = 1.28) was exhibited for saline waters.photochemical processes resulting in lower regression slope value (Spencer et al., 2012).The findings highlighted that remote sensing of DOC through CDOM absorption algorithm for saline waters was remarkably different from fresh waters.

Stream and rivers
Though some of the samples scattered from the regression line (Fig. 2c), close relationship between DOC and CDOM275 was revealed for samples collected in rivers and streams.Compared with the other water types (Fig. 2), the highest regression slope value (slope = 3.13) was exhibited with river and stream water

Urban waters
Although close relationship between DOC and CDOM275 was revealed with urban waters (Fig. 2d, R 2 = 0.71), it is much scattered compared with other water types (Fig. 2), particularly with samples presenting DOC concentration less than 60 mg/L.
Similarly, very large variability of regression slope values was demonstrated, ranging from 0.78 to 4.16.It is apparent that urban water bodies are severely affected by human activities, particularly sewage, effluents and runoff from urban impervious surface containing large amount of DOM and nutrient discharge into urban waters.
Elevated nutrients generally result in algal bloom for some of the urban water bodies (Chl-a range: 1.0-521.1µg/L;average: 38.9µg/L).Thereby, DOC and CDOM derived from phytoplankton may also contribute a portion that should not be neglected (Zhao et al., 2016;Zhang et al., 2010).More or less affected by sewage effluent, the DOM in urban waters is much complex than those from natural water bodies.Thus, a large variation of the relationship between DOC and CDOM275 is expected with urban waters.

Ice covered lakes and reservoirs
As demonstrated in Fig. 2e, a closest relationship (R 2 = 0.93) between DOC and CDOM275 was recorded with waters beneath ice covered lakes and reservoirs in Northeast China.It was argued that the close relationship indicated the concurrent processes taken place for DOC accumulation and CDOM biogeochemical activities (Finlay et al., 2003;Stedmon et al., 2011).The strong positive correlations between DOC and CDOM275 is probably due to ice formation condensed these two parameters.The other possible explanation is that ice and snow cover shield out most of the solar radiation that may cause a series of biochemical process for CDOM contained in water, the inflows and direct rainfall over lakes or reservoirs also diminished, thus causing limited effect on DOC concentration and CDOM composition (Uusikiv et al., 2010;Belzile et al., 2002).Further, the autochthonous DOC and CDOM for ice covered waters are also very limited due to the weak primary production in winter (7.3µg/L).Thus, much close relationship between DOC and CDOM is expected for winter waters.
Comparatively, a loose correlation between DOC and CDOM275 was demonstrated for ice melting waters (Fig. 2f) are probably due to the ice/water depth ratio, which cause variation of dissolved components expelled during ice formation.
The other reason is probably due to the biologically derived DOC in the ice matrix, which could be varied due to the light and nutrient conditions (Arrigo et al., 2010;Muller et al., 2011).Apparently, CDOM from ice melting waters were mainly originated from maternal water during the ice formation, also from algal biological processes (Stedmon et al., 2009;Arrigo et al., 2010).The DOC and CDOM concentrations in maternal waters, and ice formation processes may cause the variations for their relationship, thus the regression slopes varies.Similarly, snow cover, and nutrients in the ice also cause the variation for biochemical processes, that ultimately result in the relationship between DOC and CDOM may differ from corresponding waters (Bezilie et al., 2002;Spencer et al., 2009).Interestingly, the regression slopes for ice samples (slope = 1.35) and under lying water sample (slope = [Insert Fig. 2 about here]

DOC versus CDOM based on SUVA254 and M (a 250 :a 365 ) values
Through comparison of the relationships between DOC and CDOM275, it can be seen that the regression slope vales exhibit large variability for various types of waters.The underlying reasons may lies in the aromacity and colored fractions in DOC component (Spencer et al., 2009(Spencer et al., , 2012)).Since SUVA254 is an effective indicator to characterize CDOM molecular weight, and is calculated by the ratio of CDOM absorption at 254 nm to DOC (Weishaar et al., 2003), it may reflect the regression slope value between DOC and CDOM absorption at 275 nm.As shown in Fig. 3a, it is obvious that SUVA254 presented high values for both fresh water bodies, and waters from rivers or streams as well.Saline water and winter water samples show intermediate SUVA254 values, while urban water and ice melting water show lower values.The M value (a 250 : a 365 ) is another indicator to demonstrate the variation of molecular weight and aromacity of CDOM components (Dehaan, 1993).As shown in for various types of waters being investigated.

Regression based on SUVA254 grouping
Based on the threshold value for SUVA254, eight subsets of paired DOC and CDOM275 were grouped.Figs.4a to 4f demonstrated the regressions between DOC and CDOM275 with a SUVA254 increment of unity.Fig. 4g and 4h exhibited the cases with SUVA254 threshold larger than unity.Except the regression model with SUVA254 less than one (Fig. 4a), better performances were achieved for regression models based on SUVA254 thresholds between 2 to 6 (Figs.4b-4f).As shown in [Insert Fig. 4 about here]

Regression based on M value grouping
Likewise, regression models between DOC and CDOM275 were established based on Based on the regression analysis on pooled dataset, it can be concluded that it is possible to derive DOC concentration based on CDOM absorption spectra, and the latter parameter can be estimated from remotely sensed data (Zhu et al., 2011;Kuster et al., 2015).

Conclusion
As a powerful means, remote sensing plays a crucial role in assessing CDOM and DOC in lake and reservoir waters.However, in order to get accurate estimates of CDOM and DOC in waters, it is necessary to get insight into the regional water

Tables
Hydrol.Earth Syst.Sci.Discuss., doi:10.5194/hess-2016-380,2016   Manuscript under review for journal Hydrol.Earth Syst.Sci.Published: 22 August 2016 c Author(s) 2016.CC-BY 3.0 License.originating from different sources.The first dataset (n = 288; from early spring 2009 to late October 2014) was measured from samples collected in fresh lakes and reservoirs for describing variations in absorption properties of different CDOM and DOC sources during the growing season with various landscape types.The second dataset (n = 345; from early spring 2010 to late mid-September 2014) was measured from samples collected in brackish to saline water bodies for investigating variations in CDOM absorption properties and hydrological impact on DOC concentration.The third dataset (n =322; from early May 2012 to late October 2014) was measured from samples collected in rivers and streams across a wide region in China.The fourth data (n = 328; from 2011 to 2014 in the ice frozen season) was measured from samples collected in northeast China in winter from both lake ice and underlying waters.The fifth dataset (n = 221; from early May 2013 to mid-October 2014) was measured of samples from urban water bodies, including lakes, ponds, rivers and streams, which was severely influenced by sewage effluents.It is expected that CDOM and DOC from various water types may illustrate a general trend between these two parameters.[Insert Fig.1 about here] Hydrol.EarthSyst.Sci.Discuss., doi:10.5194/hess-2016-380,2016   Manuscript under review for journal Hydrol.Earth Syst.Sci.Published: 22 August 2016 c Author(s) 2016.CC-BY 3.0 License.
Hydrol.Earth Syst.Sci.Discuss., doi:10.5194/hess-2016-380,2016   Manuscript under review for journal Hydrol.Earth Syst.Sci.Published: 22 August 2016 c Author(s) 2016.CC-BY 3.0 License.1.27)are very close, which may also explain that the dominant components of CDOM and DOC in the ice are from maternal underlying waters.

Fig. 3b ,
Fig.3b, fresh water, river and stream water, and urban water exhibit low values, which

Fig. 4a -
Fig.4a-4h, as a whole, the regression slope values have strong links with SUVA254 Hydrol.Earth Syst.Sci.Discuss., doi:10.5194/hess-2016-380,2016   Manuscript under review for journal Hydrol.Earth Syst.Sci.Published: 22 August 2016 c Author(s) 2016.CC-BY 3.0 License.M threshold values (Fig.5).A relative loose correlation between DOC and CDOM275 was revealed with dataset where M value was less than 5 (Fig.5a).It should be noted that the highest regression slope value was achieved among different groups of subset of data.The large range of M value (0<M<5.0)may explain the scattered data pairs in Fig.5a; similar reason can be ascribed to the group with M value ranging from 4 to 6 (Fig.5b).Better regression models were achieved with intermediate M value groups, where regression slope values were close to each other (ranging from 1.15 to 1.38) with high determination of coefficients (R 2 > 0.88).With increased M values, small regression slope values were obtained (Figs.5g-h).Loose relationship between DOC and CDOM275 was obtained with relative low or high M values (Fig.5g).However, very close relationship (R 2 = 0.99) was yielded with extremely high M values (Fig.5h).It can be seen that most of samples are from these presented in embedded diagram in Fig.2b, the limited water bodies in the group may be explain this coincidently high R-square value.With more samples collected from different water bodies in this extreme group, a loose relationship between DOC and CDOM275 may be expected, which also needs future explorations.As noted in Figs.5c-5f, close regression slope values were obtained, implicating that a comprehensive regression model with intermediate M value groups may be achieved.As expected, a promising regression model (the diagram was not shown) between DOC and CDOM 275 was achieved (y = 1.269x + 6.55, R 2 = 0.925, N = 998, p < 0.001) with pooled dataset presenting in Figs.5c to 5f.As shown in Fig.6a, a close relationship between DOC and CDOM 275 was obtained with the pooled dataset (N = Hydrol.Earth Syst.Sci.Discuss., doi:10.5194/hess-2016-380,2016 Manuscript under review for journal Hydrol.Earth Syst.Sci. Pblished: 22 August 2016 c Author(s) 2016.CC-BY 3.0 License.1504)collected from different types of inland waters.However, it should be admitted that the extremely high DOC samples may advantageously contribute the better performance of the regression model.Thus, regression model was established without these eight samples (DOC > 300 mg/L), still acceptable accuracy can be achieved (Fig.6b, R 2 = 0.66, p < 0.01).In addition, regression model based on logarithm transformed pool dataset was also established (Fig.6c, R 2 = 0.82, p < 0.01).It can be seen that most of the paired data sitting close to the regression line except some scattered ones.

FiguresFig. 1 .
FiguresFig.1.Water types and sample distributions across the mainland of China.
Table 1, low averaged concentration of DOC was observed for river waters, but even lower DOC concentrations were measured with ice melting waters sampled in winter.It should be noted that large variations were measured with waters from rivers and streams (Table2).Generally, low DOC concentrations were found in rivers or streams in the drainage systems developed in Tibetan Plateau or arid regions where soil contains relative low concentration of soil organic carbon, while inverse trend were found in rivers or streams surrounded by forest or wetlands.Among the five types of waters investigated, high DOC concentrations were recorded for saline waters, ranging from 2.3 to 300.6 mg/L.This investigation indicated that saline waters originated from the Songnen Plain, the HulunBuir Plateau and part of waters from Tibetan Plateau generally exhibits high concentration of DOC, while some of waters supplied with snow melt water or ground waters generally exhibit low DOC concentrations even with high salinity.Compared with samples collected in growing seasons, higher DOC concentrations were observed in ice covered water bodies (7.3-720 mg/L), which is due to the condensed effect caused by the DOC expelled from ice formation (Bezilie
Earth Syst.Sci.Discuss., doi:10.5194/hess-2016-380,2016 Manuscript under review for journal Hydrol.Earth Syst.Sci.Published: 22 August 2016 c Author(s) 2016.CC-BY 3.0 License.absorption values and specific CDOM absorption (SUVA254) as well.On the contrast, saline waters illustrate low SUVA254 values due to the long residence time and strong photo-bleaching effects on waters in the semi-arid regions.Influenced by effluents and sewage waters, CDOM from urban water bodies showed much complex absorption feature.With respect to ice melting water samples, SUVA254 for CDOM was lowest for all groups of waters concerned.
water types systematically.The investigation showed that CDOM absorption varied significantly, and generally river waters and fresh lake waters exhibit high CDOM Hydrol.
762various types of waters.