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Physicochemical Assessment of Water and Sediments of Santa
Barbara Estuary of the Niger Delta, Nigeria
DIENEBIWARI, Ereghotie Ayebaemi
1
, HART, Aduabobo Ibitoru
2
and BABATUNDE, Bolaji Bernard
2
Department of Biological Science, Niger Delta University, Wilberforce Island, Bayelsa State
1
.
Department of Animal and Environmental Biology, University of Port Harcourt, Choba, Rivers State
2
DOI:
https://dx.doi.org/10.51244/IJRSI.2025.1210000215
Received: 20 October 2025; Accepted: 28 October 2025; Published: 15 November 2025
ABSTRACT
The concentration of water and sediment quality parameters such as Dissolved Oxygen (DO), Biological Oxygen Demand (BOD), pH,
Sulphate, Potassium, Calcium, Nitrate, Total Hydrocarbon Concentration (THC), Total Organic Carbon (TOC), and Phosphate was
studied between April 2021 to March 2022. The mean concentration of the parameters in the various stations range between 6.70 – 7.04;
29.09 – 29.45
o
C; 5.11 – 5.77 mg/l; 75.72 – 81.85 mg/l; 89.23 – 90.97 mg/l; 1.29 – 1.88 mg/l; 2.41 – 2.86 mg/l; 1.53 – 2.14 mg/l; 7.08
– 19.58 mg/l, 0.27 – 0.62 mg/l, and 2.34 – 2.52 mg/l for pH, Temperature, Dissolved Oxygen, Potassium, Calcium, Phosphate, Sulphate,
Nitrate, Turbidity, Biological Oxygen Demand, and THC respectively. In sediment, the mean concentration of parameters was between
5.12 – 5.62; 1.73 – 2.36 mg/kg; 3.96 – 5.11 mg/kg; 1.67 – 2.15 mg/kg; 298.90 – 409.40 mg/kg; 419.25 – 491.53 mg/kg; 7.14 – 7.53 %,
and 98.94 – 130.55 mg/kg for pH, Nitrate, Sulphate, Phosphate, Calcium, Potassium, TOC, and THC. In water, there was a significant
variation across study stations (p<0.05), in the concentration of phosphate, nitrate, and turbidity, but no such variation (p>0.05) occurred
in the other parameters. In sediments, there were also spatially significant variations (p<0.05) in the concentrations of pH, Nitrate,
Sulphate, and Phosphate. Overall, the concentrations of these parameters were higher in sediments than in water. Hierarchical Cluster
Analysis grouped the physicochemical parameters of water and sediments from the study area into three clusters. These findings reflect
the dynamic nature of the aquatic environment and the influence of various factors on water and sediment quality.
Keywords: Physicochemical parameter, Sediments Quality, Water Quality, Pollution, Niger Delta.
INTRODUCTION
Water is one of the most utilized natural resources available to man. In its natural state, it is a colorless, odorless, and tasteless liquid
composed mainly of Hydrogen and Oxygen (Boyd, 2020). Its quality is determined by human usage and exploitation of resources
associated with it, and also the presence of ions and non-ions present in it, which differ based on prevailing environmental factors and
biological processes (Van-Wyk et al., 1999; Ward and Tunnel, 2017). The presence and interaction of physical, chemical, and biological
parameters are also key determinants of water quality (Patil, 2012; Vasistha and Ganguly, 2020). These ions and non-ions present are
important determinants in the structure and composition of phytoplankton and benthic macroinvertebrates (Dalu et al., 2017; Sharma et
al., 2020). Factors such as vegetation, human activities, soil type, climate, and geology are significant to its quality (Chaudhry and
Malik, 2017). No one parameter effectively determines a good water quality; rather, a composition of different characteristics effectively
determines its quality (Ward and Tunnel, 2017). As a result of its importance and its continuously changing state, which most times are
often undesirable, and is due to human pressure, its ability to self-purify has been diminished, thus monitoring of the aquatic environment
becomes essential (Khanna et al., 2011; Burt et al., 2014).
The aquatic environment is delicate, hence susceptible to changes at the slightest intrusion. This delicate system is important at a
domestic level, useful for agricultural and industrial water supply systems, important for aquaculture and fisheries production, and for
the overall wellness of the ecosystem (Boyd, 2020). For the effective functioning of man, the ecosystem, communities, and economies,
clean and safe water is a necessity (Aniyikaiye et al., 2019; Matta et al., 2015). Water quality can be assessed through the study of the
physico-chemical and biological parameters of the water (Sellam et al., 2019; Ustaoglu and Tepe, 2019).
There has been an issue with the decline in water quality globally (Lintern et al., 2018; Matta et al., 2015), and the decline of water
quality is one of the most prevalent environmental issues (Custodio et al., 2021). This decline is in part due to agricultural, urban, and
industrial activities, domestic sources, municipal sewage treatment plants, surface runoff, atmospheric deposition, and changes in land
use (Ferrante et al., 2015; Fierro et al., 2017; Liyanage and Yamada, 2017; Wurtsbaugh et al., 2019). In Nigeria, the release of industrial
wastewater into water bodies is primarily the source of pollution in the country's rivers, compromising water quality and disrupting the
microbial and aquatic flora, as well as the release of solid waste into water bodies, together with crude oil spills, all lead to the
deterioration of water quality, and this may ultimately lead to a health crises (Galadima et al., 2011; Kanu and Achi, 2011; Omokaro et
al., 2024). These substances released into the aquatic environment cause changes in physiological conditions that affect the organism’s
immunity, and the impact of these may be deleterious (Enujiugha and Nwanna, 2004). A benchmark of toxicological values determines
the criteria for water quality, and these values are different for different water quality parameters (Lawson, 2011).
The contamination of sediments can lead to significant losses in species and biodiversity (Luoma, 1990; Markovic, 2003), as well as
harmful food chain reactions affecting benthic communities and upper trophic levels (McGrath et al., 2019). These communities face
extreme challenges due to increasing ocean pollution (Taylor et al., 2019). Coastal areas not only serve as habitats for aquatic organisms
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ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue X October 2025
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but also play a critical role in the global carbon cycle. They can either contribute organic matter to the open ocean or function as carbon
sinks by accumulating materials in sediments (Azevedo et al., 2007). Once contaminants enter the environment, they interact with
sediments, the water column, and organisms. These interactions are governed by physical and chemical processes, leading to various
outcomes such as the chemical release, immobilization, or transformation of contaminants into more reactive forms or byproducts that
are accessible to organisms (NRC, 2003). Benthic organisms, which live in or on sediments (Wokoma and Umesi, 2017), comprise the
largest single ecosystem in terms of spatial coverage, as they are found in oceans (Snelgrove, 1997). Their structure and abundance are
influenced by physical and biological factors (Govindan, 2002). Benthic organisms play a vital role in the cycling and recycling of
nutrients within the aquatic ecosystem, acting as a link between inaccessible nutrients in detritus and valuable protein sources for fish
(Andem et al., 2012). Oil pollution related to sedimentation has been shown to negatively impact benthic macrofauna. Baguley et al.
(2015) observed decreased evenness and diversity of benthic organisms near wellheads during the Deepwater Horizon spill. Similarly,
Fisher et al. (2016) reported a decline in sediment infauna diversity and noted that recovery was slow one year after the disaster. The
loss of functional diversity among benthic organisms significantly affects ecosystem function (Waldbusser et al., 2004); however,
responses of benthic communities to petroleum-related disturbances vary between different locations (Olsen et al., 2007). Sediment type
is a crucial factor in the distribution of benthic macrofauna (Mwakisunga et al., 2020), and the zonation of benthic organisms is
determined by sediment characteristics (Fresi et al., 1983).
Different water and sediment quality parameters have different acceptability criteria. These acceptability criteria are determined either
by an international standard or a national one, and a deviation from the standard could imply the introduction of a foreign body to the
ecosystem.
MATERIALS AND METHODS
Water and sediment samples were collected from the Santa Barbara estuary monthly between April 2021 to March 2022. Samples for
the determination of other physico-chemical variables were collected, preserved, and transported to the laboratory by standard
procedures. The samples were collected from four sampling stations, labeled 1-4, with the following respective geographical
coordinates: - Station 1: 04° 31' 59.6" N, 006° 30' 00.2" E; Station 2: 04° 32' 02.8" N, 006° 30' 18.6" E; Station 3: 04° 31' 51.7" N, 006°
30' 28.5" E, and Station 4: 04° 32' 07.9" N, 006° 30' 42.5" E. The water samples were analyzed in situ and ex-situ, and sediments were
analyzed ex-situ only to determine the quality of the Santa Barbara River of the Niger Delta. Sediment samples were collected using
the processes described in Hart and Zabbey (2005). The presence of certain water quality parameters, such as Dissolved Oxygen, pH,
Turbidity, and Temperature, was measured using a Hanna 98594 in situ test kit, while others were carried out ex-situ. For the parameters
analysed ex situ, the Hach DR/890 colorimeter and the GBC Avanta Ver 1.33 AAS were used to test for the presence of metals like
calcium and potassium. Biochemical oxygen demand (BOD) was determined by the 5-day BOD test.
QUALITY ASSURANCE AND QUALITY CONTROL (QA/QC)
The purity of the elemental standards was assessed using Atomic Absorption Spectroscopy (AAS). The accuracy of the prepared
standards was verified with certified reference materials, and the analytical procedure was performed in triplicate. All instruments
utilized were calibrated with calibration standards, and the analytical process included the use of blanks and repeated measurements.
Additionally, all reagents used during the testing were of high purity.
Figure 1: Map of the Study Area
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ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue X October 2025
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STUDY AREA
Sampling Station 1
This station is situated at the entrance of the Santa Barbara River with a latitude and longitude of 04
O
31
I
59.6
II
N and 006
O
30
II
00.2
II
E on the global positioning system. The station is housing a pipeline running through it and a sparse vegetation of mangrove plants.
Notable organisms found in this station are the mudskippers, periwinkles, and different varieties of crabs on the mudflat.
Sampling Station 2
This station is directly opposite a fishing camp called “Shellkiri”, which means Shell land in the Nembe Ijaw dialect. The name of the
settlement comes from the fact that the SPDC used to be the operator of OML 29, which is now operated by Aiteo. The station is located
at a latitude and longitude of 04
O
32
I
02.8
II
N and 006
O
30
II
18.6
II
E on the global positioning system.
Sampling Station 3
This station is located on a latitude and longitude of 04
O
31
I
51.7
II
N and 006
O
30
II
28.5
II
E on the global positioning system and is rich
with a luxuriant mangrove vegetation together with sparse vegetation of Nypa palm.
Sampling Station 4
Located close to this station is a small fishing settlement with about four families, and this location has a collection of very tall mangrove
trees. It is located at a latitude and longitude of 04
O
32
I
07.9
II
N and 006
O
30
II
42.5
II
E on
the global positioning system.
DATA ANALYSIS
Physicochemical parameters of water and sediments were analyzed using MS Excel software. Hierarchical Cluster Analysis was
performed on both water and sediment parameters. Additionally, Pearson Correlation and Analysis of Variance (ANOVA) tests were
conducted with significance set at p < 0.05, using IBM SPSS 20 software.
RESULT
Physico-Chemical Parameters of Water
The results of the physicochemical analysis for the study area reveal significant findings across various parameters, detailed in the
accompanying tables.
The highest average potassium concentration was detected at Station 4, with a mean of 81.85 ± 57.18 mg/L, whereas Station 2 recorded
the lowest concentration at 75.72 ± 52.95 mg/L. Monthly comparisons indicated that July had the highest potassium level (134.61 ±
11.57 mg/l), while November showed the lowest (10.12 ± 1.41 mg/l). Notably, there was a sharp decline in potassium levels from
September to December 2021. Although the analysis revealed significant monthly variations (p < 0.05), the spatial distribution showed
no significant differences among the stations (p > 0.05).
Similar to potassium, the calcium concentrations also varied significantly by month (p<0.05) but not by station (p>0.05). The peak
calcium level was observed in June (114.15 ± 1.89 mg/l), with the lowest concentration recorded in September (50.07 ± 6.74 mg /l).
Station 4 displayed the highest mean calcium level (90.97 ± 27.85 mg/l), while Station 1 had the lowest (89.23 ± 32.77 mg/l).
Phosphate levels demonstrated both temporal (between months) and spatial (between stations) variations, indicated by significant
differences found in the analysis (p<0.05). The highest phosphate concentration occurred in October (2.08 ± 0.63 mg/l) and the lowest
in July (1.18 ± 0.38 mg/l). Station 4 recorded the highest calcium level (1.88 ± 0.42 mg/l) and Station 1 the lowest (1.29 ± 0.31 mg/l).
Sulphate concentrations across study stations showed no significant variation (p>0.05), while significant monthly variations (p<0.05)
were observed. The maximum sulphate level was recorded in Station 1 (2.86 ± 0.89 mg/l), with the lowest in Station 2 (2.41 ± 0.34
mg/l). The month of April 2021 had the highest sulphate concentration (3.70 ± 0.68 mg/l), and March 2022 had the lowest (1.95 ± 0.19
mg/l).
Nitrate levels were highest in July 2021 (2.60 ± 0.29 mg/l) and lowest in May 2021 (1.28 ± 0.50 mg/l). Station 4 recorded the peak
nitrate concentration (2.14 ± 0.38 mg/l), whereas Station 1 had the lowest (1.53 ± 0.67 mg/l). The analysis revealed significant
differences (p<0.05) between months and among stations.
Station 4 showed the highest turbidity level (19.58 ± 4.68), while Station 3 was the least turbid (7.08 ± 2.53). The month of July 2021
had the least turbidity (6.75 ± 3.86), while February 2022 saw the highest turbidity (16.75 ± 5.79). Turbidity was generally higher in
drier months and lower in the rainy season. Significant spatial variations were found, although no significant temporal variations were
noted.
BOD levels ranged from 2.22 to 2.64. November 2021 had the highest BOD (2.64 ± 0.14), and May 2021 had the lowest (2.22 ± 0.08).
Station 2 recorded the highest BOD mean (2.52 ± 0.20), while Station 3 had the lowest (2.34 ± 0.19). While temporal variations were
significant (p<0.05), spatial variations among stations were not (p>0.05).
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Physico-Chemical Parameters of Sediments
The total organic carbon value recorded was highest in November 2021, with a mean and standard deviation of 7.79 ± 0.21, and the
lowest total organic carbon on record was in May 2021, with a mean and standard deviation of 6.75 ± 0.37. Station 2 had the most TOC
(7.53 ± 0.38), while the least station with TOC was at station 3, with a mean and standard deviation of 7.14 ± 0.31. There was a
significant variation (P<0.05) for TOC values in the various stations and months.
The month of March 2022 had the record level of potassium (789.03 ± 283.06 mg/kg), and October recorded the least quantity (207.73
± 81.37) of potassium in the sediment. The months of January to May had a considerably higher amount of potassium in sediments as
opposed to the amount of potassium recorded from June to December. Also, station 1 had the largest amount of potassium, with a mean
and standard deviation of 491.53 ± 305.45 mg/kg, and station 2 recorded the least amount (419.25 ± 276.70 mg/kg) of potassium. The
amount of potassium recorded in the stations was not spatially different, as there was no significant difference (P>0.05) between the
stations. The same was not true for the amount of potassium recorded in the different months, as they were significantly different
(P<0.05) from one another, as revealed by the analysis of variance test conducted between the months of study. A significant variation
exists between October and April, January, February, and March.
The amount of calcium recorded in the sediments during the study period showed no significant variation (P>0.05) both spatially and
temporally. Be that as it may, station 4 had the largest amount of calcium (409.40 ± 387.18), and station 3 had the least (298.90 ± 90.46).
August 2021 had the record (474.21 ± 81.94) quantity of calcium during the study, and October had the least amount (220.10 ± 126.33).
The months of September to December 2021 recorded the lowest amount of calcium during the study.
The mean value of the most concentrated sediment with phosphate was sediments from station 2, with a mean and standard deviation
of 2.15 ± 0.26, and station 4 had the least concentration of phosphate in sediments (1.67 ± 0.47). The month of January 2022 recorded
the highest concentration of phosphate (2.50 ± 0.11), while May 2021 recorded the lowest amount (1.41 ± 0.28). The months of
November to December witnessed a consecutive increase in phosphate levels in sediments. The concentration of phosphate varied
significantly (P<0.05) between the stations, and the same variation (P<0.05) was recorded between the months of study.
Sulphate levels were highest in station 2 as revealed by the mean and standard deviation (5.11 ± 0.93), whilst station 4 had the lowest
amount of sulphate (3.96 ± 0.91). The month of September had the largest amount (5.38 ± 0.12) of sulphate in sediment collected from
the study area, and the month of July had the least amount (3.86 ± 0.61) of sulphate. There was no significant difference (P>0.05) in the
amount of sulphate recorded during the months of study; the same was untrue for the amount of sulphate recorded in the various stations,
as they varied significantly (P<0.05).
The level of nitrate in sediments differed significantly (P<0.05) both within the months of study and among the different study stations.
No significant variations between the months of study, but a significant variation was recorded between stations 4 and 1, and between
stations 4 and 2. The highest mean and standard deviation (2.36 ± 0.33) value of sulphate in the various stations was recorded in station
2, while station 4 recorded the least mean and standard deviation (1.73 ± 0.57) of the sulphate present in the sediments of the study
stations.
The pH level recorded during the duration of this study varied significantly (P<0.05) spatially and temporally. There was no significant
interaction between the levels of pH recorded during the months of study, but it showed significant variations between pH levels across
the different study stations.
Station 2 had a record pH and standard deviation of 5.62 ± 0.27, while station 3 recorded the least pH with a value of 5.12 ± 0.49. March
2022 had the record of the highest pH (5.67 ± 0.19), and April 2021 had the lowest pH level (4.99 ± 0.39). A careful examination of the
pH values recorded in the different months of the study shows a steady increase in pH level from July 2021 to March 2022.
Cluster Analysis
A hierarchical clustering analysis was used to study the clustering patterns of physicochemical parameters in sediments and water from
the study area. In water and sediments, three clusters were formed as shown in the dendrogram above, with a rescaled distance of 25
(Figure 2, 3). Physicochemical parameters in the same cluster are homogeneous, while those in a separate cluster are heterogeneous.
In water, there was a significant positive correlation between potassium and calcium at p<0.01 level. This relationship may be the reason
why both parameters are in the same cluster (Figure 4). There was also a positive correlation between THC and Turbidity, between
Phosphate and Sulphate, and a negative correlation between pH and BOD (Figure 4, Table 5); all of which are members of cluster 2.
There was, however, an interaction between members of cluster 2 and cluster 1. This possible interaction may be influenced by the
negative correlation between Temperature and pH, and a positive relationship between Temperature and Turbidity. In sediments
however, the only interaction between physicochemical parameters was between the positive correlation phosphate and pH (Table 6),
all these are clustered together.
Table 1: Mean concentration of physico-chemical parameters of water samples from the different study stations
Station 1
Station 2
Station 3
Station 4
NESREA Standard
(2011)
pH
6.70 ± 0.64
a
6.84 ± 0.72
a
6.90 ± 0.73
a
7.04 ± 0.66
a
6.5 – 8.5
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Temperature (
o
C)
29.45 ± 2.32
a
29.09 ± 2.32
a
29.35 ± 2.26
a
29.42 ± 2.71
a
D.O (mg/L)
5.23 ± 1.11
a
5.24 ± 1.12
a
5.77 ± 1.81
a
5.11 ± 0.90
a
Potassium (mg/L)
76.27 ± 55.70
a
75.72 ± 52.95
a
76.47 ± 56.82
a
81.85 ± 57.18
a
50.00
Calcium (mg/L)
89.23 ± 32.77
a
89.66 ± 28.30
a
89.61 ± 27.85
a
90.97 ± 27.85
a
180
Phosphate (mg/L)
1.29 ± 0.31
a
1.70 ± 0.44
ab
1.50 ± 0.35
ab
1.88 ± 0.42
b
3.5
Sulphate (mg/L)
2.86 ± 0.89
a
2.41 ± 0.34
a
2.60 ± 0.70
a
2.43 ± 0.57
a
100
Nitrate (mg/L)
1.53 ± 0.67
a
1.63 ± 0.67
ab
1.83 ± 0.23
ab
2.14 ± 0.38
b
9.1
Turbidity (NTU)
11.25 ± 3.77
ab
11.83 ± 3.99
b
7.08 ± 2.53
a
19.58 ± 4.68
c
B.O.D (mg/L)
2.42 ± 0.15
a
2.52 ± 0.20
a
2.34 ± 0.19
a
2.44 ± 0.22
a
3.0
THC (mg/L)
0.62 ± 0.92
a
0.27 ± 0.40
a
0.44 ± 0.42
a
0.64 ± 0.71
a
*Parameters with the same superscript are not significantly different (p>0.05).
Table 2a: Mean and standard deviation of physico-chemical parameters of water samples between April 2021 to March 2022.
pH
Temp.(
o
C)
D.O
(mg/L)
Potassium
(mg/L)
Calcium
(mg/L)
Phosphate
(mg/L)
Sulphate
(mg/L)
Nitrate
(mg/L)
Turbidity
(NTU)
B.O.D
(mg/L)
THC
(mg/L)
7.13 ±
0.05
cd
28.15 ±
0.13
bc
7.13 ±
0.05
c
122.68 ±
10.12
b
112.18 ±
0.77
c
2.04 ±
0.31
a
3.70 ±
0.68
d
1.93 ±
0.35
ab
13.75 ±
9.43
a
2.61 ±
0.23
a
0.78 ±
0.16
a
7.85 ±
0.20
f
29.74 ±
0.55
d
6.56 ±
0.34
bc
50.52 ±
7.48
a
82.66 ±
7.39
b
1.38 ±
0.30
a
2.19 ±
0.11
a
1.28 ±
0.50
a
12.50 ±
6.45
a
2.22 ±
0.08
a
0.09 ±
0.10
a
7.39 ±
0.13
df
27.16 ±
0.18
ab
4.25 ±
0.13
a
125.26 ±
35.01
b
114.15 ±
1.89
c
1.80 ±
0.40
a
3.45 ±
0.73
cd
1.90 ±
0.26
ab
8.25 ±
5.96
a
2.36 ±
0.09
a
0.018 ±
0.02
a
7.43 ±
0.41
df
26.21 ±
0.61
a
4.80 ±
0.22
ab
134.61 ±
11.57
b
109.57 ±
7.29
c
1.18 ±
0.38
a
2.55 ±
0.35
abc
2.60 ±
0.29
b
6.75 ±
3.86
a
2.24 ±
0.12
a
0.01 ±
0.00
a
7.53 ±
0.26
df
26.67 ±
0.47
a
5.48 ±
0.51
abc
134.96 ±
18.42
b
111.02 ±
6.60
c
1.28 ±
0.31
a
2.58 ±
0.30
abc
1.88 ±
0.39
ab
9.50 ±
3.11a
2.39 ±
0.18
a
0.01 ±
0.00
a
7.10 ±
0.03
cd
26.89 ±
0.61
ab
5.19 ±
0.26a
bc
13.36 ±
1.32
a
50.07 ±
6.74
a
1.38 ±
0.30
a
2.17 ±
0.27
a
1.48 ±
0.75
ab
12.50 ±
5.44a
2.38 ±
0.39
a
0.29 ±
0.31
a
*Parameters with the same superscript are not significantly different (p>0.05).
Table 2b: Mean and standard deviation of physico-chemical parameters of water samples between April 2021 to March 2022
pH
Temp.(
o
C)
D.O
(mg/L)
Potassium
(mg/L)
Calcium
(mg/L)
Phosphate
(mg/L)
Sulphate
(mg/L)
Nitrate
(mg/L)
Turbidity
(NTU)
B.O.D
(mg/L)
THC
(mg/L)
October
6.07 ±
0.31
ab
32.25 ±
0.37
e
6.56 ±
2.58
bc
11.49 ±
1.28
a
50.36 ±
5.08
a
2.08 ± 0.63
a
3.20 ±
0.60
bcd
1.83 ±
0.54
ab
12.00 ±
6.88
a
2.43 ±
0.20
a
0.70 ±
0.59
a
November
5.77 ±
0.12
a
29.30 ±
0.53
cd
4.99 ±
0.39
ab
10.12 ±
1.41
a
50.99 ±
4.77
a
1.50 ± 0.22
a
2.60 ±
0.25
abc
2.28 ±
0.34
ab
11.50 ±
4.20
a
2.64 ±
0.14
a
0.07 ±
0.10
a
December
7.08 ±
0.15
cd
32.15 ±
0.55
e
5.60 ±
0.43
abc
11.90 ±
1.94
a
59.01 ±
2.73
a
1.68 ± 0.28
a
2.36 ±
0.20
a
1.85 ±
0.52
a
15.00 ±
3.16
a
2.42 ±
0.18
a
1.93 ±
1.08
b
January
6.05 ±
0.17
ab
33.15 ±
1.22
e
5.58 ±
0.41
abc
96.40 ±
12.17
b
113.27 ±
5.33
c
1.53 ± 0.49
a
2.12 ±
0.25
a
1.55 ±
0.55
ab
16.50 ±
6.81
a
2.49 ±
0.09
a
0.50 ±
0.22
a
February
6.41 ±
0.29
b
30.20 ±
0.26
d
4.32 ±
0.88
a
115.67 ±
24.99
b
112.22 ±
7.85
c
1.68 ± 0.46
a
2.01 ±
0.25
a
1.40 ±
0.42
a
16.75 ±
5.79
a
2.50 ±
0.05
a
0.75 ±
0.39
a
March
6.62 ±
0.31
bc
30.05 ±
0.17
d
3.58 ±
0.72
a
114.59 ±
42.21
b
112.91 ±
2.40
c
1.58 ± 0.32
a
1.95 ±
0.19
a
1.35 ±
0.35
a
14.25 ±
4.86
a
2.49 ±
0.07
a
0.76 ±
0.40
a
*Parameters with the same superscript are not significantly different (p>0.05).
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ISSN No. 2321-2705 | DOI: 10.51244/IJRSI |Volume XII Issue X October 2025
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Table 3: Mean and Standard deviation of physico-chemical parameters in sediments from in the different stations between April 2021
to March 2022.
Station 1
Station 2
Station 3
Station 4
pH
5.23 ± 0.40
a
5.62 ± 0.27
b
5.12 ± 0.49
a
5.28 ± 0.16
ab
Nitrate (mg/kg)
2.25 ± 0.20
b
2.36 ± 0.33
b
1.95 ± 0.45
ab
1.73 ± 0.57
a
Sulphate (mg/kg)
4.69 ± 0.50
ab
5.11 ± 0.93
b
4.28 ± 0.50
a
3.96 ± 0.91
a
Phosphate (mg/kg)
2.05 ± 0.34
ab
2.15 ± 0.26
b
1.98 ± 0.31
ab
1.67 ± 0.47
a
Calcium (mg/kg)
339.58 ± 102.23
a
331.75 ± 181.92
a
298.90 ± 90.46
a
409.40 ± 387.18
a
Potassium (mg/kg)
491.53 ± 305.45
a
419.25 ± 276.70
a
421.59 ± 294.90
a
465.35 ± 286.31
a
TOC (%)
7.40 ± 0.49
a
7.53 ± 0.38
a
7.14 ± 0.31
a
7.14 ± 0.37
a
THC (mg/kg)
122.90 ± 128.06
a
113.14 ± 128.80
a
98.94 ± 117.30
a
130.55 ± 153.21
a
*Parameters with the same superscript are not significantly different (p>0.05).
Table 4a: Mean and Standard deviation of physico-chemical parameters in sediments from April 2021 to March 2022.
TOC
(%)
Potassium
(mg/kg)
Calcium
(mg/kg)
Phosphate
(mg/kg)
Sulphate
(mg/kg)
Nitrate
(mg/kg)
pH
THC
(mg/kg)
April
7.31 ±
0.95
ab
733.90 ±
215.76
bc
431.30 ±
44.71
a
1.86 ± 0.48
abc
5.08 ± 2.19
a
1.95 ± 0.55
a
4.99 ±
0.39
a
296.53 ±
48.20
d
May
6.75 ±
0.37
a
577.12 ±
235.40
abc
348.83 ±
121.04
a
1.41 ± 0.28
a
4.65 ± 0.27
a
1.75 ± 0.13
a
5.02 ±
0.38
a
0.65 ± 0.99
a
June
7.33 ±
0.40
ab
323.31 ±
33.90
ab
457.27 ±
89.30
a
1.86 ± 0.32
abc
4.25 ± 0.92
a
1.83 ± 0.28
a
5.23 ±
0.33
a
2.27 ± 4.45
a
July
7.48 ±
0.21
ab
282.02 ±
48.62
a
472.50 ±
82.51
a
1.91 ± 0.39
abc
3.86 ± 0.61
a
2.10 ± 0.61
a
5.02 ±
0.34
a
2.01 ± 1.42
a
August
7.44 ±
0.37
ab
312.31 ±
52.27
a
474.21 ±
81.94
a
1.85 ± 0.26
abc
4.94 ± 0.50
a
1.80 ± 0.26
a
5.14 ±
0.30
a
2.51 ± 1.03
a
Sept.
7.08 ±
0.35
ab
221.99 ±
95.58
a
223.60 ±
130.22
a
1.54 ± 0.24
ab
5.38 ± 0.12
a
2.45 ± 0.13
a
5.13 ±
0.15
a
3.06 ± 0.57
a
*Parameters with the same superscript are not significantly different (p>0.05).
Table 4b: Mean and Standard deviation of physico-chemical parameters in sediments from April 2021 to March 2022.
TOC
(%)
Potassium
(mg/kg)
Calcium
(mg/kg)
Phosphate
(mg/kg)
Sulphate
(mg/kg)
Nitrate
(mg/kg)
pH
THC
(mg/kg)
Oct.
7.28 ±
0.16
ab
207.73 ± 81.37
a
220.10 ±
126.33
a
2.16 ± 0.10
bc
4.12 ± 0.81
a
1.83 ± 0.39
a
5.33 ±
0.30
a
388.09 ±
62.47
e
Nov.
7.79 ±
0.21
b
215.50 ± 64.95
a
221.71 ±
126.29
a
1.90 ± 0.28
abc
3.91 ± 0.71
a
1.85 ± 0.73a
5.40 ±
0.59
a
218.11 ±
59.77
cd
Dec.
7.60 ±
0.33
ab
215.70 ± 47.26
a
229.98 ±
135.44
a
2.00 ± 0.30
abc
4.31 ± 0.40
a
1.88 ± 0.64
a
5.51 ±
0.41
a
164.31 ±
41.80
bc
Jan.
7.19 ±
0.05
ab
766.57 ±
295.27
c
427.37 ±
464.29
a
2.50 ± 0.11
c
4.85 ± 0.20
a
2.50 ± 0.16
a
5.64 ±
0.28
a
122.70 ±
26.03
b
Feb.
7.23 ±
0.10
ab
748.02 ±
216.12
c
222.45 ±
77.72
a
2.36 ± 0.04
c
4.38 ± 0.08
a
2.43 ± 0.22
a
5.66 ±
0.19
a
113.97 ±
17.74
b
Mar.
7.14 ±
0.05
ab
789.03 ±
283.06
c
409.57 ±
504.60
a
2.19 ± 0.19b
c
4.40 ± 0.17
a
2.53 ± 0.17
a
5.67 ±
0.19
a
84.48 ±
22.26
b
*Parameters with the same superscript are not significantly different (p>0.05).
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Figure 2: Cluster analysis for physicochemical parameters of water.
Figure 3: Cluster analysis for physicochemical parameters of sediment.
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Table 5: Pearson correlation for physicochemical parameters of Water
Correlations
c
pH
Temp
D.O
Potassium
Calcium
Phosphate
Sulphate
Nitrate
Turbidity
BOD
THC
pH
Pearson Correlation
1
-.604
*
.133
.342
.281
-.351
.113
-.013
-.468
-.714
**
-.194
Sig. (2-tailed)
.037
.681
.277
.376
.264
.727
.969
.125
.009
.546
Temp
Pearson Correlation
-.604
*
1
.202
-.418
-.238
.421
-.252
-.384
.737
**
.295
.618
*
Sig. (2-tailed)
.037
.529
.177
.457
.173
.430
.217
.006
.353
.032
D.O
Pearson Correlation
.133
.202
1
-.306
-.293
.338
.438
.030
.097
.006
.127
Sig. (2-tailed)
.681
.529
.333
.356
.283
.154
.926
.764
.986
.694
Potassium
Pearson Correlation
.342
-.418
-.306
1
.971
**
-.132
.133
.092
-.221
-.092
-.306
Sig. (2-tailed)
.277
.177
.333
.000
.683
.681
.776
.491
.776
.334
Calcium
Pearson Correlation
.281
-.238
-.293
.971
**
1
-.088
.044
-.058
-.042
-.056
-.215
Sig. (2-tailed)
.376
.457
.356
.000
.785
.891
.857
.896
.862
.501
Phosphate
Pearson Correlation
-.351
.421
.338
-.132
-.088
1
.632
*
-.113
.329
.493
.460
Sig. (2-tailed)
.264
.173
.283
.683
.785
.027
.727
.297
.104
.132
Sulphate
Pearson Correlation
.113
-.252
.438
.133
.044
.632
*
1
.473
-.422
.185
-.101
Sig. (2-tailed)
.727
.430
.154
.681
.891
.027
.121
.171
.565
.755
Nitrate
Pearson Correlation
-.013
-.384
.030
.092
-.058
-.113
.473
1
-.668
*
.031
-.213
Sig. (2-tailed)
.969
.217
.926
.776
.857
.727
.121
.018
.924
.507
Turbidity
Pearson Correlation
-.468
.737
**
.097
-.221
-.042
.329
-.422
-.668
*
1
.493
.638
*
Sig. (2-tailed)
.125
.006
.764
.491
.896
.297
.171
.018
.103
.026
BOD
Pearson Correlation
-.714
**
.295
.006
-.092
-.056
.493
.185
.031
.493
1
.286
Sig. (2-tailed)
.009
.353
.986
.776
.862
.104
.565
.924
.103
.368
THC
Pearson Correlation
-.194
.618
*
.127
-.306
-.215
.460
-.101
-.213
.638
*
.286
1
Sig. (2-tailed)
.546
.032
.694
.334
.501
.132
.755
.507
.026
.368
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).
c. Listwise N=12
Table 6: Pearson correlation for physicochemical parameters of Sediments
Correlations
b
TOC
Potassium
Calcium
Phosphate
Sulphate
Nitrate
pH
THC
TOC
Pearson
Correlation
1
-.494
-.102
.243
-.494
-.280
.135
.300
Sig. (2-tailed)
.102
.753
.447
.103
.377
.676
.344
Potassium
Pearson
Correlation
-.494
1
.315
.420
.290
.534
.354
.003
Sig. (2-tailed)
.102
.318
.174
.360
.074
.258
.992
Calcium
Pearson
Correlation
-.102
.315
1
-.009
.120
-.041
-.324
-.416
Sig. (2-tailed)
.753
.318
.978
.710
.899
.305
.178
Phosphate
Pearson
Correlation
.243
.420
-.009
1
-.266
.490
.803
**
.379
Sig. (2-tailed)
.447
.174
.978
.403
.106
.002
.225
Sulphate
Pearson
Correlation
-.494
.290
.120
-.266
1
.282
-.234
-.189
Sig. (2-tailed)
.103
.360
.710
.403
.375
.464
.557
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Nitrate
Pearson
Correlation
-.280
.534
-.041
.490
.282
1
.550
-.186
Sig. (2-tailed)
.377
.074
.899
.106
.375
.064
.563
pH
Pearson
Correlation
.135
.354
-.324
.803
**
-.234
.550
1
.193
Sig. (2-tailed)
.676
.258
.305
.002
.464
.064
.548
THC
Pearson
Correlation
.300
.003
-.416
.379
-.189
-.186
.193
1
Sig. (2-tailed)
.344
.992
.178
.225
.557
.563
.548
**. Correlation is significant at the 0.01 level (2-tailed).
b. Listwise N=12
DISCUSSION
This study evaluated the physicochemical parameters of water and sediments along the Santa Barbara estuary of the Niger Delta,
Nigeria. Some of the parameters evaluated include: pH, Dissolved Oxygen, THC, TOC, BOD, Calcium, Potassium, Phosphate, Nitrate,
and Sulphate. These parameters determine the habitability and productivity of organisms in the aquatic environment.
The pH, which affects the physiology of organisms (Chen and Durbin, 1994; Hansen, 2002), had a mean concentration of 5.77 - 7.85
(Table 2a, b) in water during the months of study and 6.7 – 7.04 in the different study stations. The level of pH in water in this study
area is not so different from the levels reported by Ibisi et al. (2017) and Ifelebuegu et al. (2017). The pH of water samples from the
various stations where within the approved permissible limit of 6.5- 8.5 set by NESREA. These mean ranges are considered to be ideal
for organisms to thrive and function optimally in the aquatic environment (Hansen, 2002; Offem et al., 2011). A range between 8 – 10
is, however, considered unideal (Obahiagbon et al., 2014). The level in sediment, however, ranged from 4.99 – 5.67 and 5.12 – 5.62 in
the study stations and months of study, respectively (Table 3; 4a, b). These levels are closer to acidity than the levels recorded in water.
These levels are, however, linked to hydrocarbon pollution (Ukpene et al., 2024), and this result is consistent with the reports of Hart
and Zabbey (2005); Dirisu and Edwin-Wosu (2022); and Udo et al. (2024), who reported acidic pH in sediments in their studies of
sediments in the Niger Delta. The comparatively higher-level mean range of total hydrocarbon concentration (THC) levels in sediments
than water in this study further strengthens the argument of Ukpene et al. (2024) that the pH of a medium is affected by oil spills.
The mean THC level recorded in water was 0.27 – 0.64 in the study stations and 0.01 – 1.93 in the different months of the study (Table
1; Table 2a, b), while the range of 98.94 – 130.55 was recorded in sediments from the various stations, and the range of 2.01 – 388.09
was recorded in sediments during the months of study (Table 3; Table 4a, b). Other studies, like Ogeleka et al. (2016) and Kpee and
Bekee (2021), have also reported greater levels of THC in sediments than in water.
The low concentration of THC in water reported in this study is consistent with the reports of Oribhabor and Ogbeibu (2009), Ngah et
al. (2017), but a far cry from the THC concentrations in water by Ibigoni-Clinton et al (2009), Daka and Moslen (2013), and Gijo et al.
(2016). Also, the levels of THC in sediments from this study were far above the levels reported by Ezekiel et al (2011); Ebong and John
(2021); Dere-Biemgbo and Oriakpono (2022), and Ebikeme et al. (2023). The greater levels of THC in sediment embolden the sediment
as the repository of waste in the aquatic environment (Owoh-Etete et al., 2023).
The temperature of the aquatic environment triggers different physiological responses by different organisms (Fekri et al., 2018;
Trombetta et al., 2021; Kazmi et al., 2022; Mei et al., 2022). In this study, the mean temperature level was between 26.67 – 33.15 °C
during the months of the study, and 29.09 – 29.45 °C in the different study stations. The mean temperature levels in this study are similar
to the levels reported by Bunza et al. (2024). These levels have also been reported to be ideal for the growth and development of
plankton, benthic organisms, and fish, although these organisms have different tolerance ranges for temperature (Jain et al., 2013; Fekri
et al., 2018; Bunza et al., 2024).
The biological oxygen demand (BOD) level in this study was between 2.22 – 2.64 during the months of the study, and 2.34 – 2.52 in
the stations of the study. This concentration is similar to the reports of Komolafe et al. (2014), Dere-Biemgbo and Oriakpono (2022),
but less than the level reported by Gijo et al. (2016). An increase in BOD levels has been reported to affect species diversity (Komolafe
et al., 2014; Bello et al., 2024), thus, these low levels of BOD in this study area would support the growth of aquatic dwellers, barring
any intrusions. Though Komolafe et al. (2014) and Zhao et al. (2020) reported significant seasonal variations in BOD levels from their
studies, no significant variation was reported during the months of this study. The permissible limit for BOD as approved by NESREA
is 3.0 mg/l, and this level is higher than the level of BOD recorded during this study.
Dissolved oxygen in water from the different stations ranged between 5.11 – 5.77 mg/l. At concentrations above 4.5 mg/l, dissolved
oxygen supports the optimal growth of zooplankton (Banerjee et al., 2019), while at concentrations between 8.5 – 10 mg/l, there is
usually a low diversity of zooplankton (Ogidi et al., 2024). Based on the aforementioned, this study area is likely to support the growth
of zooplankton. Jonah et al (2020) reported a lower level of dissolved oxygen when compared to this study, while other researchers,
like Hart and Zabbey (2005), Imachrist et al (2024), and Ogidi et al. (2024), had higher levels of dissolved oxygen in their study area.
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In this study, mean nitrate concentrations in sediments were noted between 1.95 - 2.36 mg/kg in the study stations and 1.75 – 2.53 mg/kg
during the months of study. The reasons for these low nitrate levels in sediments are a lack of agricultural activity and the presence of
petroleum hydrocarbons in sediments (Ifelebuegu et al., 2017; Udoinyang et al., 2023). These two reasons align with this study, as there
are no agricultural activities in this study area, and there are high levels of hydrocarbons, as indicated by this study. The concentrations
of nitrate in sediments reported by Kartikasari et al (2013), Udoinyang et al (2023), and Jonah et al (2024) are higher than the
concentrations reported in this study. In water, the mean concentration of nitrate was between 1.53 – 2.14 and 1.28 – 2.60 mg/l for the
study stations and months of study, respectively. The concentration of nitrate in the study area was above the permissible limit of 9.1
mg/l approved by NESREA. The concentrations of nitrate in water, however, are lower than the concentrations reported in sediments.
The concentration of nitrate in water is higher in this study than the report of Dere-Biemgbo and Oriakpono (2022), but lower than the
report of Adesuyi et al. (2015) and Oladeji (2020).
In this study, however, the mean phosphate levels in sediments ranged between 1.67 - 2.15 mg/kg in the study stations, with monthly
concentrations from 1.41 - 2.50 mg/kg, which is not so different from the study of Goodluck (2024), there has also been reports of
higher concentration levels of phosphate in sediments when compared to the findings of this study (Tamunotonye et al., 2021; Jonah et
al., 2024). Howbeit, in water, the concentration of phosphate was between 1.29 – 1.88 mg/l in the stations, and 1.18 – 2.08 mg/l during
the months of the study. The concentrations of phosphate in water from this study are less than the concentration in the sediment. The
low concentrations of phosphate in water had also been reported by Oladeji (2020) and Dienye et al. (2023). The concentration of
phosphate in water was below the permissible level of 3.5 mg/l by NESREA.
The mean potassium concentration in sediments from this study ranged from approximately 421.59 - 491.53 mg/kg across various
stations, and 215.50 - 789.03 mg/kg by month. The high concentrations of potassium reported in this study align with previous findings
of high potassium concentration in sediments from the Niger Delta (Jason-Ogugbue and Ezekwe, 2020; Okoro and Emegha, 2022;
Asunbo and Tanee, 2022) but differ from studies showing lower potassium levels (e.g., Seiyaboh et al., 2017; Ogamba and Nwabueze,
2017). Due to the high concentration of potassium in sediments from this study, they can be used to amend nutrient-deficient soils
(Junakova et al., 2021).
In water, the mean concentration of potassium was from 75.72 - 81.85 mg/l between the stations and from 10.12 to 134.96 mg/l during
the entire sampling period. Similar high concentrations of potassium in water have been reported by Ezekwe et al (2022) and
Ogunbanwo and Faleti (2018). On the contrary, Seiyaboh et al (2016) in their study of the Orashi River reported a far lesser concentration
of potassium (1.08 – 8.35 mg/l). The concentration of potassium in water recorded in this study was higher than the approved limit of
50 mg/l for surface water by NESREA.
The concentrations of calcium in water reported by Seiyaboh et al (2016) and Ogbeide and Edene (2023) are lower when compared to
the level reported in this study. The mean concentration of calcium in this study ranged between 89.23 and 90.97 mg/l for the different
study stations, and between 50.07 and 114.15 mg/l in the different months of the study. The mean calcium concentration in the water
was less than the approved permissible concentration of 180 mg/l by NESREA, and this might be grossly less than the concentration
needed for aquatic life. These low concentrations across the stations may harm aquatic life in the estuary. The calcium concentrations
in sediments from this study ranged from 220.10 - 474.2 mg/kg and 298.90 – 409.40 mg/kg, surpassing those reported in other studies
(Ekperusi et al., 2022; Ezekwe et al., 2022). High concentration of calcium in sediment may indicate a robust presence of
macroconsumers in the study area (Correa et al., 2018).
The concentrations of sulphate in water reported by Oborie and Osemele (2024); Ogbeide and Edene (2023) are higher when compared
to 2.41 - 2.86 mg/l and 2.01 - 3.70 mg/l reported concentrations for the study stations and the months of the study; these concentrations
were, however, higher than the concentrations of sulphate reported by Ekperusi et al. (2022). The level of sulphate permissible by
NESREA is about 100 mg/l in surface water, but the levels recorded in the stations are a far cry from the permissible level. Thus, there
may be an issue of sulphate deficiency in the study area.
In sediments, the concentration of sulphate was 3.96 – 5.11 mg/kg in the study stations, and 3.86 – 5.38 mg/kg during the months of the
study. These concentrations were higher when compared to the concentrations in water. The concentrations of sulphates present in
sediment reported in the previous studies (Ezekiel et al., 2011; Dere-Biemgbo and Oriakpono, 2022) were higher than those found in
this study (Table 3, 4a, b), indicating a possible decrease in organic matter input within the study area.
The turbidity levels recorded during this study ranged from 7.08 to 19.58 NTU for the various stations and from 6.75 to 16.75 NTU for
the various months of the study. These concentration levels were higher than those reported by Ogbonna et al. (2021) but lower than the
range reported by Ogbeibu et al. (2020). It is noteworthy that Station 4, which holds the record of being the most turbid station, also has
the highest concentration of Nitrate and Phosphate when compared with other stations. Thus, an increase in nutrient levels and pollution
caused by petroleum hydrocarbons can invariably be linked to an increase in turbidity.
The mean TOC concentrations in this study ranged from 6.75 - 7.79, suggesting that the levels recorded might not yet threaten benthic
diversity (Hyland et al., 2005). Unlike previous studies that suggested rainfall affects TOC levels (Al-Hasani et al., 2024), this study did
not observe significant monthly variations.
The Hierarchical Cluster Analysis is a tool employed to show the similarity, natural relationship or interactions in a data set that are
apparently invisible (Omoleomo et al., 2008; Ogbuagu and Ayoade, 2012). A similar tool has been employed by Raimi and Sawyerr
(2022) in the study of groundwater in Obrikom. This analysis revealed the presence of three clusters in water and sediment. These
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clusters have been shown to reveal the spatial distribution of chemical components (Omoleomo et al., 2008). The result of the HCA is
shown in Figures 2 and 3 for water and sediment samples. In sediments, the first cluster comprised Phosphate, Nitrate, Sulphate, pH,
and TOC; the second cluster comprised THC only. In water, however, the first cluster comprised Phosphate, Nitrate, Sulphate, BOD,
THC, and pH; the second cluster comprised D.O., Turbidity, and Temperature; while the third cluster contained potassium and calcium
in both water and sediment. The clustering pattern for both sediment and water may be an indication that both environments may be
polluted from the same source.
CONCLUSION
Due to the pressures from crude oil exploration activities in this area, it is essential to monitor water and sediment quality parameters
regularly. These monitoring efforts will help identify any stress within the environment, allowing regulators to take decisive action to
limit the release of pollutants. This is crucial, as pollution can have widespread effects on families whose livelihoods depend on the
productivity of aquatic ecosystems. Conclusively, the findings indicate that while the Santa Barbara estuary may support a variety of
aquatic life, the presence of hydrocarbons may pose challenges that need to be continuously monitored to protect the ecosystem's health.
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