In these methods, the conventional way to present the response of a flow to the injection of a tracer is to graphically represent the variation in tracer concentration over time the tracer response curve detected in two or more cross sections downstream of the injection point, called sampling sections the distances between the sections in this study are given in Table 1.
The tracer response curve, which is defined based on an analysis of water samples collected at selected time intervals during the passage of the tracer cloud, serves as the basis for determining the time course and dispersion characteristics of a pollutant in watercourses.
Researcher who have studied the subject include Soares et al. The tracer-based methods used in this work were: the statistical method to determine parameter, known as method of moments Fischer et al. These methods are widely accepted in the scientific community.
The comparative method of the discrepancy ratio Rd , originally described by White, Milli, and Crabbe , is used to test the consistency of the experimental data for the longitudinal dispersion coefficient EL. The predicted EL is considered to be identical to the measured value when the Rd value is zero. If it is higher than zero, the predicted EL is overestimated, and if it is lower than zero, the EL is underestimated. Based on this comparative method, the values obtained by the Routing Procedure were adopted as observed values Oi , while those obtained by the empirical formulas and by the other four experimental methods were adopted as estimated values Ei.
The Routing Procedure was chosen as reference because it uses the principle of superposition; hence, it does not take into account how the tracer is released, and is able to adjust the EL value that compares the field measurements against the concentrations presented by the model. In other methods, such as the method of moments, there area problems related to long tails in the concentration distribution.
The Routing Procedure does not present these issues. The purpose of the scenarios was to verify the contamination of water supplied to the first user downstream from the tracer injection point, based on the accidental spill of a contaminant in the Meio, Retiro and Divisa streams.
Simulations of the C vs. And consequently it was possible to determine the concentration of the tracer at critical sections from where water would be withdraw to the first user. These studies were performed for the most critical situation, i. The Q7,10 flow minimum seven-day flow and ten-year recurrence was considered at the tracer injection point in each watercourse.
The Q7,10 was determined using contour maps of specific yield in L s-1 km-2 , which combines the yield with the drainage area, type of soil, and physical and meteorological characteristics of the watershed.
Table 2 presents the geometric and hydraulic data used for the determination of the longitudinal dispersion coefficient EL, using equations and experimental methods. Table 2 also shows that the complete mixing length was considered in all the watercourses, starting from the injection point, Pinj. This paper presents only the results obtained with the routing procedure, since this was the standard method of comparison in the discrepancy analysis, as illustrated in Figure 3.
The results obtained by the other methods and by the equations described in Table 1 are given in the discrepancy analysis in Figure 4, keeping in mind that an Rd of zero indicates similarity with the standard method of comparison. The same amount of tracer was released instantaneously into all the watercourses, i. The highest peak concentrations of tracers were found in the watercourses with the lowest water discharge capacities, indicating their lower pollutant dilution capacity see Figure 3.
Published works on watercourses with similar geometric and hydraulic characteristics have reported similar results to the streams of this study. Figure 4 illustrates the discrepancy ratio Rd between the experimental methods and equations from the literature and the standard Routing Procedure. The analysis of the results for each watercourse is not conclusive because the discrepancy differs according to the various methods and equations described in the literature.
In general, saline, fluorescein and rhodamine tend to be underestimated by the experimental methods and overestimated by the equations. The highest numerical contrast was found for the Retiro Stream, where the discrepancies of the equations described in the literature 0. According to the equations, Ei Oi-1 remained below 0. Figure 4 Discrepancy ratio, Rd, of the experimental methods and equations reported in the literature vs. An analysis of the experimental methods revealed that the peak concentration and crown concentration methods yielded the lowest Rd values.
The crown concentration method yielded an Rd value of According to information obtained from IGAM, the first user downstream from the tracer injection point is located m downstream in the Meio Stream, m downstream in the Retiro Stream, and m downstream in the Divisa Stream. The peak concentration of tracer in the sections where water is withdraw to the first users is indicated in the tracer concentration vs.
Figure 5 Peak concentration reaching the first user downstream from the Pinj in the watercourses under study. According to most of the experimental methods analyzed in this paper, the low pollutant transport and dilution capacity of the Divisa Stream resulted in the highest peak contaminant concentration, which varied from The peak concentrations in the Meio and Retiro streams, according to the different experimental methods, present the same trend in the average curves, indicating higher transport and dilution capacity than the Divisa Stream.
The NaCl injection methodology produced satisfactory results in the experimental determination of the longitudinal dispersion coefficient EL. This suggests that the methodology can be used as a good replacement for the fluorescent tracer, reducing the cost and time spent on laboratory analyses of fluorescein and rhodamine.
The analysis of the discrepancy ratios, Rd, reveals that the experimental methods tend to underestimate saline solution and fluorescein while the equations tend to overestimate them. The peak concentration and crown concentration methods and the equation proposed by Ribeiro et al.
Argent, R. A new approach to water quality modeling and environmental decision support systems. Environmental Modeling Software, 24 7 , Azamathullaa, H. Support vector machine approach for longitudinal dispersion coefficients in natural streams. Applied Soft Computing, 11 2 , Devens, J. Fischer, H. Mixing in inland and coastal waters. French, R. Open-channel hydraulics.
Goldscheider, N. Tracer tests in karst hydrogeology and speleology. International Journal of Speleology, 37 1 , Kashefipour, S. Longitudinal dispersion coefficients in natural channels. Water Research, 36 6 , p. Krenkel, P. Waste dispersion characteristics of streams using turbulent diffusion phenomenon. As the respective DOM molecular formulae from the mangrove cluster were also related to the higher dissolved Ba, Mn, and TDN concentrations Figure 6 , we suggest that the mangrove-fringed zone is strongly influenced by the input of microbially transformed mangrove DOM from the mangrove porewaters.
Besides the mixing of estuarine waters with the marine endmember, these enrichments of N- and P heteroatoms and aliphatic compounds can be explained by the input of marine DOM from phytoplankton and microbial production as well the as transformation of terrestrial DOM Gonsior et al. This DOM pulse may be rapidly transported along the river toward the coastal ocean, while being relatively unaffected by the estuarine filter. The catchment area of Coffs Creek Estuary is largely deforested and subject to urban and agricultural pressure, which leads to increasing runoff during heavy rain events GeoLINK, We hypothesized that a heavy rain event leads to the enhanced input of DOM and inorganic constituents across the estuary into the coastal ocean.
During the wet season, the values of bulk DOC concentrations and the DOC-normalized relative abundances of the molecular DOM parameters along the estuarine gradient followed a conservative mixing trend. This indicates less biogeochemical transformations in the estuary under wet conditions compared to dry conditions Figure 4 and Supplementary Figure S1. In line with the pulse-shunt concept it also shows that the influence of tidally driven porewater exchange was smaller during the rainy season, probably due to the increased flow conditions, shorter residence time and less exchange with the mangrove sediments.
We suggest that the mixing of the fluvial and marine endmembers was the dominant process responsible for the DOM distribution during the wet season in Coffs Creek Estuary Figure 4 and Supplementary Figure S1. For example, the surface water DOC was more 13 C enriched in the fresh headwaters of the estuary compared to dry season. Yet this signal was strongly shifted to more 13 C depleted DOC in the mangrove-dominated area Figure 4. In the same area we observed the input of aromatic and S-containing molecular DOM components, which indicates an input of highly aromatic DOM compounds e.
Terrestrial organic matter such as degraded lignin and tannin have been previously described as important DOM sources in a mangrove-fringed estuary Dittmar et al. Our data demonstrate that the estuarine surface waters were relatively enriched with DOM compounds from the surrounding mangroves, even under high-discharge conditions, although this molecular fingerprint was less pronounced compared to dry conditions. We calculated the effective export flux of DOC as well as dissolved Mn, Fe, Ba, and TDN from river to estuary and from the estuary to the coastal ocean using the standard estuarine model Kaul and Froelich, for the dry and wet season Table 3.
Based on the catchment area Table 3. The annual flux as well as the effective export flux calculations based on only dry and wet conditions considerably differ from each other. This implies that the strength of the estuarine filter as well as mangrove sources and sinks were also highly variable and depended strongly on the present flow conditions and residence times.
These calculations demonstrate that intertidal mangroves can govern the efficiency of the estuarine filter. Mangroves are known to be important drivers for the coastal organic and inorganic element budgets. DOC outwelling rates from mangrove forests at different locations around the globe show considerable differences ranging between 5 and mmol m —2 day —1 Table 4.
The estimated DOC drainage from mangrove forests in Coffs Creek estuary amounts to 13 mmol m —2 day —1 which is within the lower range of the findings elsewhere Table 4. Our calculations further reveal that tidally driven porewater exchange in mangrove sediments lead to an annual increase of dissolved Mn, Ba as well as DOC and TDN and a decrease of dissolved Fe concentration by a factor of 10, 1.
Table 4. Summary of literature data on dissolved organic carbon DOC outwelling in mangrove dominated areas. We combined bulk geochemical parameter analysis with non-targeted molecular DOM analysis to reveal biogeochemical transformations along a mangrove-fringed estuary.
After passage through the mangrove-fringed zone, phosphorous containing DOM compounds were relatively depleted in the creek surface waters. In contrast, sulfur- and nitrogen-containing DOM as well as aromatic DOM compounds were relatively enriched in the surface creek waters, which we ascribe to the discharge of mangrove porewater. In the high salinity zone of the estuary, additional autochthonous microbial sources and the removal of aromatic DOM compounds, probably due to photodegradation and co-precipitation along with metals such as Mn caused a shift to a more aliphatic DOM signature toward the marine zone see conceptual model in Figure 8.
The observed biogeochemical transformations were less pronounced during wet compared to dry conditions, which we ascribe to shorter residence times and hence less exchange with the mangrove sediments. Our flux calculations showed that mangroves affect estuarine biogeochemical processes and may be important sources of DOM and inorganic nutrients TDN, Mn to the ocean.
Our study confirms that mangroves have a fundamental impact on the DOM, nutrient and trace metal cycling in estuaries. In comparison to other estuarine systems, biogeochemical processes in mangrove-fringed estuaries may have an even more important function in buffering nutrients, trace metal and DOM fluxes to the coastal ocean between high and low discharge events, than previously assumed.
Data used to produce the results of this manuscript can be obtained by contacting CM. CM performed the chemical analyses. IS provided the dissolved carbon, nitrogen, and phosphorous data. CM wrote the manuscript with significant contributions from all authors.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Eleonore Gruendken and Katrin Klaproth ICBM, University of Oldenburg were thanked for their excellent technical assistance during trace metal and molecular dissolved organic matter analyses, respectively.
This study was carried out in the framework of the Ph. We acknowledge the two reviewers and the editor for their thoughtful and valuable comments, which led to an improved manuscript. Alongi, D. The influence of stand age on benthic decomposition and recycling of organic matter in managed mangrove forests of Malaysia. Ayukai, T. Fluxes of nutrients and dissolved and particulate organic carbon in two mangrove creeks in northeastern Australia. Mangroves and Salt Marshes 2, — Google Scholar.
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Its diffusive behaviour is no different from the diffusive behaviour of salt or fresh water. In the upstream direction it diffuses in the same way as the salt water diffuses upstream, while in the downstream direction it follows the freshwater diffusion.
If its concentration at the outlet is c out , its concentration C in the estuary upstream from the release point is thus proportional to the salt fraction, while downstream from the release point it is proportional to the freshwater fraction Figure Here, S out is the vertically averaged salinity at the outlet location and f out the fresh water fraction at the outlet location. This shows that it is possible to predict the distribution of a pollutant in the entire estuary if the salinity distribution is known.
The equation assumes steady state conditions, ie continuous release of the pollutant at the constant concentration c out. The concentration of non-conservative pollutants decreases even in the absence of diffusion, through either biochemical or geochemical reaction. An example for such a situation would be the concentration of coliform bacteria released through a sewage outlet. The relationship between the concentration C of such a pollutant, the salinity S and the fresh water fraction f is not as straightforward as in the case of conservative pollutants, but concentration levels are always lower than those derived from the conservative case.
An estimate for the concentration can be determined by subdividing the estuary into compartments. In this equation, compartments are numbered from the inner end of the estuary, n is the compartment containing the outfall, and p is the compartment where the concentration is evaluated. T is the tidal period and k the decay constant for the pollutant.
The larger k , the faster the decrease of the concentration over time. Biochemical or geochemical processes do not only reduce the concentration of a non-conservative pollutant, they often also give rise to an increase in the concentration of another substance, which in turn may produce a third substance as a result of its own decay, and so on.
Whether this chain of events constitutes pollution or not depends on the degree of harmfulness of each substance. Ammonium nitrogen, for example, is used as a fertiliser on land. Under natural conditions it convertes to nitrate Figure The introduction of nutrients into the marine environment does not automatically constitute pollution. But when nitrate and other nutrients are again mineralised in sea water this process requires oxygen, which is not in unlimited supply in the ocean.
Too much nutrient can lead to such a reduction of oxygen levels that the lack of oxygen can become a threat to marine life. Under such circumstances nutrients have to be regarded as pollutants. The chain of events triggered by their presence is then an example of a system of coupled non-conservative pollutants. The description of the concentration distribution of coupled non-conservative pollutants requires the solution of a coupled system of differential equations, a task well beyond the scope of these notes.
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