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Turbidity and Total Suspended Solids of Water: Lentic and Lotic Sites Report


Abstract

The increasing and accumulating levels of contaminants from farms and urban centers have impaired water systems. As the research question of the study, are turbidity and TSS of water in the lentic site (Cragin pond) and lotic site (Turkey Creek) statistically significantly different? In answering the research question, the objective of the study is to compare the quality of water in the lentic system and the lotic system. In this view, the null hypothesis of the study is that the quality of water in the lotic and lentic sites is the same. To determine the quality of water, the study collected samples of water from Turkey Creek and Cragin pond in Joplin Mo. The analysis of the data using the descriptive statistics and the paired samples t-test gave substantial findings. In line with the objective, the findings show that water in the lotic system has high levels of turbidity and TSS. In conclusion, hypothesis testing fails to reject the null hypothesis that turbidity differs statistically significantly (p = 0.088). In contrast, the hypothesis testing rejects the null hypothesis that there is no statistically significant difference in TSS means of water in the lotic system and the lentic system.

Introduction

Rivers in the United States have experienced increased contamination in the recent past due to the encroachment of habitats and watersheds. Turbidity and sedimentation are the main factors that have contributed to the impairment of water systems (Rosado-Berrios and Bouldin, 2016). Anthropogenic activities in various parts of the world have continued to diminish wetlands, forests in watersheds, and vegetation cover (Habersack et al., 2014). Consequently, drainage of water from agricultural areas has increased with time, resulting in increased contamination of water in the river. A recent study done to assess the quality of water revealed that turbidity ranged from 1.21 to 896 nephelometric turbidity units (NTU) while total suspended solids ranged 0.17 to 386.33 mg/L (Rosado-Berrios and Bouldin, 2016). The variation in water quality exists due to differences in watersheds, lentic systems, and lotic systems.

The quality of water in a given ecosystem varies according to human activities on watershed and the nature of lentic and lotic systems. Maintenance of water quality to suit different uses has been an issue in the United States because human activities have consistently increased the rate of water contamination (Rosado-Berrios and Bouldin, 2016). In water bodies such as dams, rivers, lakes, creeks, and ponds, the quality of water should be high for them to support aquatic life and humans. Nonpoint pollutants are the major causes of contamination of surface water as surface runoff from construction sites, farms, recreational sites, towns, and septic systems contaminate water bodies (Schelker et al., 2013). As agricultural activities occur in watersheds, they contribute significantly to the contamination of water in different water bodies (Gilmer et al., 2012). Therefore, the assessment of water quality in various water bodies is essential to understand the extent to which human activities contribute to the contamination of water.

In addition to the nature of watersheds, the nature of ecosystems influences the quality of water. Lentic and lotic systems are two main categories of ecosystems that affect the quality of water and consequently their usage. A lentic system refers to static water bodies such as ponds, pools, lakes, and dams while a lotic system refers to dynamic bodies such as channels, creeks, springs, streams, and rivers (Kaiser and Kalbitz, 2012). Lentic systems affect the quality of water for they serve as temporary reservoirs, which trap surface runoff, allow sedimentation, and support the growth of organisms such as algae and planktons (Figuerola et al., 2012). Sedimentation in lentic systems removes heavy metals and stores them in sediments, resulting in reduced contamination of lotic systems (Sakhare and Kamble, 2014). Subsequently, torrential rains fill lentic systems and cause water in them to overflow into lotic systems.

Turbidity and sediments from agricultural activities are the main factors that contribute to the impairment of water bodies (Glaz et al., 2015). The agricultural activity contributes to turbidity because it determines the extent of vegetation cover and the degree of surface runoff. Areas with high agricultural activity have less vegetation cover and experience extensive surface runoff when compared to areas with low agricultural activity. Bateni et al. (2013) suggest that afforestation, vegetation, and cover crops reduce surface runoff, soil erosion, and sediment loss. Therefore, monitoring of lentic systems is necessary because torrential rains overflow and contaminate lotic systems.

Inlets and outlets of different water bodies influence the quality of water in them because they determine whether a water body is a lentic or a lotic system. Turkey Creek and Cragin ponds are two water bodies representing the lotic system and the lentic system respectively. Normally, the extent of sedimentation and turbidity of water in a given system reflects the quality of water. The presence of a lot of sediments and high turbidity implies that the quality of water is low (Rosado-Berrios and Bouldin, 2016). The increasing human activities around water bodies contribute significantly to impairment and reduction of water quality. According to the 303d list, human activities impair water bodies since they generate sediments, heavy metals, chlorides, and total dissolved solids (Gilmer et al., 2012). Therefore, as pollutants that impair water bodies exist, there is a need to assess and compare the quality of water in Turkey Creek and Cragin ponds.

Objectives

The objective of the study is to compare the quality of water in Turkey Creek and Cragin pond in Joplin Mo representing the lotic systems and the lentic systems respectively. The study hypothesized that the quality of water in lotic systems and lentic systems differ significantly. The parameters of water quality that the study compared are turbidity and total suspended solids (TSS).

Materials and Methods

Study Sites

The study sites are Turkey Creek and Cragin pond Joplin Mo, which represent lotic systems and lotic systems. Increasing human activities and encroachment of the environment has increased sedimentation, total dissolved solids, and turbidity, resulting in impaired water bodies. Turkey Creek is a lotic system because its water flows while Cragin pond is a lentic system because its water is stagnant.

Sample Collection and Analysis

To assess the quality of water in lentic and lotic systems, quality parameters of water at the field were measured using handheld mufti-probe meter, YSI ProPlus. Lotic samples were collected from the middle of the flowing water in Turkey Creek while lentic samples were collected from Cragin pond. Four types of samples were collected from nine sites in each of the systems within a period of numerous weeks (Table 1). Lentic and lotic samples were collected, placed in Nalgene containers, and carried to the laboratory for further analysis. Within 72 hours, analysis of water quality was done in the laboratory using nephelometric method 2130B (Gilmer et al., 2012). The samples were removed from the fridge, warmed to the room temperature, and then shaken to form a homogenous mixture. Each sample was poured on a clean glass cuvette and analyzed using Hach Turbidimeter. The data from multiple sites of both lentic and lotic systems were averaged and the descriptive statistics generated as shown in the appendix section (Tables 2, 3, 4, and 5).

Data Collection and Statistical Analyses

Nine samples from the lotic system and the lentic system were selected and their data compared in the study. The data obtained from samples were averaged and the means recorded for further analysis. In data analysis, the study compared data within and between lentic sites and lotic sites. The parameters of water quality compared are turbidity and total suspended solids (TSS). The descriptive statistics and the paired samples t-test were used to compare the quality of water in lentic and lotic systems.

Results

Descriptive Statistics

Table 2 indicates the distributions of averages of each of the nine samples. In the lentic system, the highest average of turbidity is 3.26 while the lowest average is 2.33. Furthermore, Table 2 shows that the averages of TSS range from 1 to 12. Comparatively, in the lotic system, Table 3 shows that the averages of turbidity range from 2.6 to 21.6 whereas the averages of TSS range from 6 to 44.

Comparison of turbidity and TSS of the lentic system and the lotic system shows some differences. In the lentic system, the descriptive statistics show that the mean of turbidity is 3.0±0.91 while the mean of TSS is 4.89±3.82 (Table 4). Comparatively, in the lotic system turbidity is 6.22±6.20 while the mean of TSS is 15.11±15.07 (Table 5). Therefore, the descriptive statistics reveal that the lentic system has lower turbidity and TSS than the lotic system.

Inferential Statistics

The paired samples t-test shows that the turbidity of water in the lotic system (6.22) is higher than the turbidity of water in the lentic system (3.00), although the difference is statistically insignificant (p = 0.088), as shown in Table 6. Thus, the paired samples t-test fails to reject the null hypothesis that there is no statistically significant difference in means of turbidity of water in the lentic system and the lotic system. Additionally, the paired samples t-test indicates that the levels of TSS in the lotic system (15.11) are higher than that of the lentic system (4.89), t(8) = 1.89, p = 0.047 (Table 7). In this view, the paired samples t-test rejects the null hypothesis that there is no statistically significant difference in means of TSS of water in the lotic system and the lentic system.

Discussion/Conclusion

In line with the objective, the study indicates that the quality of water in lentic and lotic systems has different levels of turbidity and TSS. The findings are in line with the previous findings that water quality in lotic systems and lentic systems have different qualities (Sakhare and Kamble, 2014). Regarding the finding of turbidity, the study indicates that the lotic system has a higher mean than the lentic system. The explanation of the difference in the level of turbidity is that the lotic systems are turbulent for they constantly dissolve soil and sediments, resulting in their turbidity (Rosado-Berrios and Bouldin, 2016). Moreover, since turbulence increases the surface area of water to dissolve oxygen (Datry et al., 2014), it creates a favorable environment for the growth of bacteria, algae, and planktons (Glaz et al., 2015). As the water of the lotic system originated from Turkey Creek, the turbulence was minimal leading to an insignificant difference in means.

Additionally, the findings show that water in Turkey Creek and Cragin pond has a different TSS. Specifically, the findings show that lotic systems have a higher level of TSS than lentic systems because they are not only dynamic but also vigorous. The paired samples t-test rejects the hypothesis that water in the lotic system and the lentic system has different means of TSS, which are statistically significant. In this view, Bateni et al. (2013) explain that the lotic system is a turbulent ecosystem because sediments do not settle down leading to a higher level of TSS than in the lentic system. Therefore, the findings have proved that TSS and turbidity are the primary factors that impair water bodies.

In conclusion, hypothesis testing fails to reject the null hypothesis that turbidity differs statistically significantly (p = 0.088). In contrast, the hypothesis testing rejects the null hypothesis that there is no statistically significant difference in TSS means of water in the lotic system and the lentic system.

Appendices

Table 1: Sample Sites and Locations.

Sites Locations
1 Wilson, Kelly, Owings, Freed
2 Flowers, Sheat, O’Dell, Buckner
3 Khang, Lenahan, Hernandez
4 Colby, Greg, Ashley, Jesse
5 Chelsea, William, Lance, Breck
6 Murray, Smelser, Fraser, Young
7 Mikal, Mika, Amber, Mileah
8 Colton, Blake, Elena
9 Diana, Nicole, Brice, Zainab

Table 2: Lentic Averages.

1 2 3 4 5 6 7 8 9
Turbidity 2.74 5.33 2.62 2.71 3.26 2.91 2.33 2.45 2.67
TSS 12 10 3 4 6 3 1 4 1

Table 3: Lotic Averages.

Parameters 1 2 3 4 5 6 7 8 9
Turbidity 7.89 3.11 21.6 2.29 2.6 4.2 8.41 2.88 3.02
TSS 9 8 39 44 6 7 10 7 6

Table 4: Descriptive Statistics of Lentic Samples.

Parameters Mean STDEVA Count SE
Turbidity 3.00 0.91 9.00 0.30
TSS 4.89 3.82 9.00 1.27

Table 5: Descriptive Statistics of Lotic Samples.

Parameter mean stdeva count SE
Turbidity 6.22 6.20 9.00 2.07
TSS 15.11 15.07 9.00 5.02

Table 6: Turbidity.

Turbidity (lotic system) Turbidity (lentic system)
Mean 6.222222222 3.002222222
Variance 38.47834444 0.832619444
Observations 9 9
Pearson Correlation -0.258801652
Hypothesized Mean Difference 0
df 8
t Stat 1.486317438
P(T<=t) one-tail 0.087751897
t Critical one-tail 1.859548033
P(T<=t) two-tail 0.175503794
t Critical two-tail 2.306004133

Table 7: TSS.

TSS (lotic system) TSS (lentic system)
Mean 15.11111111 4.888888889
Variance 227.1111111 14.61111111
Observations 9 9
Pearson Correlation -0.179864526
Hypothesized Mean Difference 0
df 8
t Stat 1.892988086
P(T<=t) one-tail 0.047493998
t Critical one-tail 1.859548033
P(T<=t) two-tail 0.094987997
t Critical two-tail 2.306004133

Works Cited

Bateni, F, S. Fakheran and A. Soffianian. 2013. Assessment of land cover changes and water quality changes in the Zayandehroud River Basin between 1997-2008. Environment Monitoring and Assessment 185(1):10511-10519.

Datry, T., S.T. Larned and K. Tockner. 2014. Intermittent rivers: A challenge for freshwater ecology. BioScience 64(3): 229-235.

Figuerola, B., A. Maceda-Veigaand, and A. De Sostoa 2012. Assessing the effects of sewage effluents in a Mediterranean creek: Fish population features and biotic indices. Hydrobiologia 694(1):75-86.

Gilmer, A.M., C.A. Rosado-Berrios and J.L. Bouldin. 2012. Establishing baseline nutrient and sediment input in the lower Cache River watershed, AR. Journal of the Arkansas Academy of Science 66(12): 62-66.

Glaz, P., J.P. Gagne, P. Archambault, P. Siros and C. Nozais. 2015. Impact of forest harvesting on water quality and fluorescence characteristics of dissolved organic matter in eastern Canadian Boreal Shield lakes in summer. Biogeosciences 12(1): 6999-7011.

Habersack, H., D. Haspel and M. Kondolf. 2014. Large rivers in the anthropocene: Insights and tools for understanding climatic, land use, and reservoir influences. Water Resources Research 50(5): 3641-3646.

Kaiser, K. and K. Kalbitz. 2012. Cycling downward-dissolved organic matter in soils. Soil Biology and Biochemistry 52(1): 29-32.

Rosado-Berrios, C. A. and J.L. Bouldin. 2016. Turbidity and total suspended solids on the lower Cache River watershed, AR. Bulletin of Environmental Contamination and Toxicology 96(6): 738-743.

Sakhare, S.S. and N.A. Kamble. 2014. Assessment of sewage pollution of lentic and lotic ecosystems from Gadhinglaj Tahsil, District Kolshapur, Maharashtra. International Journal of Pharma Sciences and Research 5(9): 594-605.

Schelker, J., L. Kuglerová, K. Eklöf, K. Bishop and H. Laudon. 2013. Hydrological effects of clear-cutting in a boreal forest: Snowpack dynamics, snowmelt, and stream flow responses. Journal of Hydrology 484(1): 105-114.

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