Bioscience Methods 2018, Vol.9, No.1, 1-11
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2017a, b), sewage through pier toilet system (Agedah et al., 2015; Ogamba et al., 2015c; Izah and Angaye, 2016a,
b), market wastes (Ben-Eledo et al., 2017).
The resultant effects of anthropogenic activities could have overall effect on the aquatic ecosystem. Beside impact
on the water and sediment quality which have a relationship (Seiyaboh et al., 2016a, b; Kigigha et al., 2018), it
could affect aquatic organisms such as fisheries and macrophytes. This is because aquatic organisms have the
tendency to bioaccumulate toxicants such heavy metals in their body (Ogamba et al., 2017a, b; Aghoghovwia et
al., 2016). When toxicants are accumulated in tissues of aquatic organisms it could have an effects on the
consumers of such life forms over a prolong period of time.
Several studies have been carried out on surface water resources in Bayelsa state. Some of the notable once
include Kolo creek (Ogamba et al., 2015a), Ikoli creek (Ogamba et al., 2015b; Seiyaboh and Izah, 2017a), Nun
river (Ogamba et al., 2015c; Seiyaboh et al., 2016b, 2017a; Kigigha et al., 2018), Sagbama creek (Seiyaboh et al.,
2017a, b), Taylor and Nun River (Daka et al., 2014), Epie creek (Izonfuo and Bariweni, 2001; Seiyaboh et al.,
2016a; Ben-Eledo et al., 2017). Most of these studies were carried out with regard to microbial, physicochemical
quality of the surface water and sediment. As such there is the need to frequently monitor surface water resources
to determine the level of human activities since surface water is used for domestic purposes by the residents
aligning surface water system in Bayelsa state.
Water quality assessment is carried with regard to three major parameters including physical, chemical and
biological analysis. Each of the three major constituents provides vital information about the water quality. Water
quality is essential in assessing the productivity level which could influence trophic structure in the aquatic food
web. Hence, this study aimed at assessing the physicochemical characteristics of Nun River at Gbarantoru and
Tombia town axis in Bayelsa state, Nigeria.
1 Materials and Methods
1.1 Study area
Nun River is one of the major surface water resource found in the
s
outhern Nigeria. The Rivers has its source
from River Niger and it passes through several communities forming tributaries in Bayelsa state and emptied into
the Ocean through estuaries. Specifically, the river passes through Tombia and Gbarantoru in Yenagoa local
government area of Bayelsa state (Aghoghovwia et al., 2018a,b).. Like most coastal region of Bayelsa state, the
surface water is a major recipient of municipal solid wastes and sewage through the use of pier toilet system
(Aghoghovwia et al., 2018a,b). The water is also a major sink of runoff resulting from several human activities on
land. In the area, there is an oil and gas facilities. The climatic condition of the area especially with regard to
temperature and relative humidity is similar to the values that have been widely reported in other part of Niger
Delta (Izah et al., 2015; Ogamba et al., 2015b; Izah et al., 2017a, b, c; 2018). Two distinct seasons’ i.e. wet season
(April to October) and dry season (November to February) are observed in the area (Ogamba et al., 2015b).
1.2 Sampling techniques
Water samples were collected from three locations (viz: location A-around oil and gas installations, B-Gbarantoru
and C-Tombia town) using 1000 mL container between December 2017 to February, 2018. The samples were
labeled and transported to the laboratory in an ice for analysis.
1.3 Analytical procedure
The physico-chemical parameters of the water samples collected including pH, conductivity, total dissolved solids,
dissolved oxygen, salinity and turbidity were analyzed
in-situ
using their respective probes. While total hardness,
total alkalinity, nitrate, chloride, sulphate, total suspended solid, calcium, potassium, magnesium, sodium and
biological oxygen demand were analyzed using the scheme of Ademoroti (1996), APHA (1998).
1.4 Statistical analysis
SPSS version 20 was used to carry out the statistical analysis. Data were expressed as mean±Standard deviation.
