Thousands of residents around the Warri area, Niger Delta rely on water from the river for public use, industrial supplies, power plant cooling and wastewater treatment. Good water quality and a healthy aquatic ecosystem are essential to maintain fish and other aquatic biota (Arimoro and Osakwe, 2006). Similarly, boaters and swimmers enjoy the aesthetic values of a healthy ecosystem.
The Warri River is among the most diverse ecosystem of macroinvertebrates (Olomukoro,
1996) and fish (Ogidiaka, 2006). People always have been closely associated
with water sources for drinking, food and transportation and Warri River is
no exception. Most Nigerian rivers are generally turbid with a high concentration
of suspended silt, particularly during the rainy season (Ita et al.,
1985). The quality of water, unlike the very obvious physical changes that take
place during the development of water resources, is an attribute that affects
the biodiversity (flora and fauna) of aquatic systems. The effects are usually
subtle and before any obvious changes are noticeable extensive damage would
have been done. Nigerian freshwaters are usually very productive at the primary
(algae), secondary (zooplankton) and tertiary (fish and other aquatic vertebrate)
levels. However, in industrial areas and urban centers there is some pollution
with high levels of faecal coliforms (Ogbondeminu, 1986), heavy metals, organic
wastes and industrial wastes which constitute public health hazards (Arimoro
et al., 2007). Although, water quality is to some extent an index of
water pollution, the indices presently used in Nigeria are inadequate to indicate
the damage that is done by heavy metals, metalloids, organic and inorganic compounds
and blue green algae. The common indicators for assessing water quality in Nigeria
(Ikomi et al., 2003) are temperature, pH, biological oxygen demand, turbidity,
dissolved oxygen, ammonia, nitrogen and coliform counts.
Studies of the physical and chemical hydrology of water bodies, both lotic and lentic, in many African countries and Nigeria in particular have received considerable attention. Amongst the numerous contributions are the studies of Nwadiaro and Umeham (1985), Onwudinjo (1990), Adeniji and Mbagwu (1990, 1991), Ogbeibu and Victor (1995), Ikomi and Owabor (1997), Jonnalagadda and Mhere (2001), Olomukoro and Egborge (2003), Ikomi et al. (2003), Imoobe and Oboh (2003), Olaleye and Adediji (2005), Armah et al. (2005) and Fafioye et al. (2005) among others.
The Warri River, a coastal river in the Niger Delta affected by various effluents of industries located in the area offers an opportunity to further quantify the impact of such effluents on the water quality which may lead to better understanding of the pollution processes in the river that may lead to improved regulation and policy development.
The present study aims at describing the spatiotemporal variations of water physicochemical parameters as affected by the industrial effluents and to identify the parameter(s) that most influence the variations observed.
MATERIALS AND METHODS
Description of Study Area
Warri River is one of the most important coastal rivers of the Niger Delta
area of Nigeria. The river takes its source from a point, 10 km away from Utagba-Uno
and lies within 50211-60001 N (Fig. 1), covering a surface
area of above 255 km2 with a length of about 150 km (NEDECO, 1961).
From its source, the river flows south-westerly to link the industrial towns
of Aladja and Warri. Beyond the Warri port the main channel of the river joins
the Forcados estuary, which empties into the Atlantic Ocean. Warri is part of
the wettest region of Nigeria and with two recognizable annual seasons of variable
duration, the dry and the rainy seasons (NEDECO, 1961; Egborge, 1987). The rainy
season lasts for about 8-10 months. The main features of the climate for the
period October to May 2006 are shown in Fig. 2 and Table
1. The relevant human activities in the river are commercial sand dredging,
production of gravel, fishing, washing and so on. The level of pollution is
relatively high in the areas sampled due mainly the effluent coming in from
the industries in Warri town.
Description of Study Stations Station 1
This station is located upstream. Industries are not sited around this station.
Human activities are reduced here to bathing and fishing. The vegetation is
covered with various plants, fern plants, Penitum puperium, oil palm.
Elaeis guineensis, Azolla sp. This station was taken as the reference
station owing to the absence of discharge coming into the river from industries.
Located close to the Warri town by a site were car is constantly washed.
The detergent and other reagents used for washing cars are washed into the river
directly without any treatment. The substratum is covered by coarse sand and
gravel and the depth is about 1.7 m. This station is sparsely vegetated with
such plants as Azolla spp., Pistia and Ludwigia species.
|| Map of Warri River showing the sampling stations
||Rainfall data of Warri area, Nigeria (Sep. 2005-Jun 2006).
Source-Meteorological station of Warri Airport, Osubi, Nigeria
This station is located in Warri town. The discharges from the fuel filling
station are drained into this section of the stream. This station is sparsely
vegetated with grasses, few Pistia sp. and water hyacinth Eichhornia
crassipes. It has a low gradient.
This station is located in Aladja. At this station effluent samples from
the Helipad/Canteen and Maintenance/New PC laboratory discharges are drained
into the surface water.
||Relative Humidity data of Warri area, Nigeria (Sep. 2005-Jun
2006). Source- Meteorological station of Warri Airport, Osubi, Nigeria
This station is relatively vegetated compared to station 3 with fringing vegetation
comprising mainly of Cyrtosperma senegalens, Pandanus candelabrum
and Anthocleista voeglii.
This station is located at the downstream reaches of the Warri River. The
watershed drains through mangrove swamp forest. It has a low gradient and 200-300
m wide with a depth of 7-10 m. The area is not entirely fresh water most of
the year. During the dry season months (Dec-Feb) they become brackish due to
incursion of marine waters from Forcados (Egborge, 1987).
Water Quality Analysis
Sampling for water quality parameters was carried out in the five study
stations at monthly intervals between Oct 2005 and June 2006, covering both
dry and rainy seasons. Surface water temperatures were recorded with a thermometer.
Conductivity, pH, total alkalinity, Dissolved Oxygen (DO) and Biochemical Oxygen
Demand (BOD5), total suspended solids were determined according to
APHA (1985) methods. Monthly rainfall data were obtained from the meteorological
station in Warri.
Ammonia and Phosphate-phosphorus (PO4-P) were measured spectrophotometrically after reduction with appropriate solutions (APHA, 1985). Chemical Oxygen Demand (COD) was determined after oxidation of organic matter in strong Tetraoxosulphate VI acid medium by K2Cr2O7 at 148°C, with back titration. Total Dissolved Solid (TDS) was estimated by multiplying specific conductance by factor of 0.65. Others such as Iron, Copper and Salinity were determined using methods described by APHA (1985). To measure the oil and grease content of the water samples, the colouration of solvent (Xylene) was measured with a UV/Visible spectrophotometer.
A summary of the physicochemical parameters obtained in Warri River for the different stations are shown in Table 2. Also indicated are Means±standard error values and the maximum and minimum values for each parameter in parentheses. ANOVA is included to detect a significant difference among each station, while the monthly variations are given in Table 3.
Temporal variation in Hydrogen ion concentration and the variations between
stations is shown in Table 3. pH fluctuated between 6.16 and
8.22 in all the stations sampled. Station 3 recorded more neutral values in
pH and tended to be more alkaline than the other stations. The highest pH value
of 8.22 was recorded for this station in October. There were no significant
difference in pH among the stations sampled (p>0.05). Also, there were no
seasonal patterns in pH. It did not vary between the various months sampled
as indicated by Analysis of variance (ANOVA).
|| Physicochemical Parameters of the section of Warri River
receiving waste water from industries (Oct 2005-May 2006)
|*: Indicates that it is significantly different (p<0.05),
**: Significantly different at p<0.001. values are mean ± Standard
Error, minimum and maximum values are given in parentheses)
Surface Water Temperature
Surface water temperatures were consistently high between 26.3 and 30.3°C
during the entire period of study. There was no significant difference (p>0.05)
in surface water temperatures recorded between the months and between the different
sampling stations. Lower temperatures were recorded in the month of January
for all sampling stations.
Turbidity measured in NTU was significantly higher in station 2 than all
the other stations sampled. Analysis of various results indicated that turbidity
significantly varied among the various sampling stations. The highest turbidity
value (18.6 NTU) was recorded in station 2 in January 2006 and the lowest value
(4.5 NTU) was recorded in October 2005 in station 3. Generally stations 1, 4
and 5 recorded similar fluctuations in turbidity. Station 2 on the other hand
recorded fairly higher values. Analysis of variance result also showed that
there were no significant monthly variations observed among the various sampling
stations. In addition, no clear seasonal pattern in Turbidity was observed.
Total Dissolved Solids (TDS)
The value of TDS was significantly higher in stations 2, 3 and 4. Stations
1 and 5 recorded lower TDS values. The highest TDS value (898 mg L-1)
was recorded in station 4 in March 2006. The lowest value of mg L-1
was recorded in station 1 in November 2005. Statistical analysis using ANOVA
indicated that TDS was significantly different (p<0.05) among the stations
sampled. TDS did not however show any marked temporal or seasonal variation
although relatively higher values were measured in the dry season month of March
in all the stations it did not vary significantly (p>0.05).
||Temporal and spatial variation in some physical and chemical
characteristics of Lower Warri River from October 2005 to May 2006
Total Suspended Solids
TSS values were lower than the TDS values in all the stations sampled and
in all sampling months. Generally TSS fluctuated between 2.7 and 10.9 mg L-1.
There was significant difference (p<0.05) using ANOVA in the value of TSS
among the different sampling stations. Also relatively higher values of TSS
were recorded during the months of October to January 2006 as compared to the
months of February to May 2006. Station 2 recorded relatively higher values
of TSS as compared to the other stations sampled. The lowest mean TSS value
of 3.36 mg L-1 was recorded in the month of May for station 3.
Electrical conductivity (EC) fluctuated between 45.5 and 1735 μS cm-1.
There was significant difference (p<0.05) in EC among the various stations
sampled. Station 4 recorded relatively higher values in electrical conductivity
in most of the months sampled. Station 5 recorded relatively lower electrical
conductivity values of 52.7 to 238.0 μS cm-1 as compared with
the other stations sampled. Analysis of variance (ANOVA) result also indicated
that the electrical mean values of conductivity did not vary between within
months and did not show any seasonal pattern.
Salinity varied between 13.65 and 520.5 mg L-1. There was no
significant difference (ANOVA) in salinity measured monthly although relatively
higher values of salinity were measured in the dry season months. There were
marked differences in salinity measured among the various sampling stations.
Station 4 recorded higher values in salinity followed by station 2 and 3 in
that order. Station 5 with a mean salinity value of 48.48 mg L-1
recorded a range of 15.7 to 74.5 mg L-1 and accounted for the lowest
salinity values. Generally, the highest value of 520.5 mg L-1 was
recorded in station 4 in the month of February.
Dissolved oxygen values were consistently low in all the stations and in
all the months sampled. Dissolved oxygen value fluctuated between 1.4 to 6.7
mg L-1. Station 1 and 4 recorded relatively higher oxygen values.
There were no marked or distinct variations in dissolved oxygen among the different
sampling months neither was there any marked seasonal variation. Analysis of
variance (ANOVA) result indicated that dissolved oxygen values among the various
sampling stations were not significant (p>0.05).
Biochemical Oxygen Demand
Biochemical oxygen demand fluctuated between 0.3 and 54.4 mg L-1.
The upstream station recorded lower values of BOD. Station 2 and 3 recorded
relatively high values of mean 26.28 and 18.65 mg L-1, respectively
showing high organic burden load. Analysis of variance result showed that BOD
was significantly different (p<0.05) among the various stations sampled.
There were no marked temporal variation observed neither was there any seasonal
pattern in BOD. The lowest BOD value of 0.3 mg L-1 was recorded in
the upstream station 1 in the month of March. Again, low BOD value of 0.8 mg
L-1 was recorded in the downstream station. A very high BOD value
was recorded in the month of November as well as in the month of April for station
Chemical Oxygen Demand
Chemical oxygen demand fluctuated between 10 and 80 mg L-1. The
value of COD was nearly uniform in all the stations sampled except again for
station 2 with a mean of 43.75 mg L-1 which was significantly higher
than the means recorded for the other stations sampled. Analysis of variance
(ANOVA) was slightly significant (F = 4.42, p>0.05) among the various sampling
stations. A post hoc test using Duncan multiple range tests showed that the
means of station 2 was different from that of the other stations which were
not different from each other. There were no significant differences in the
monthly values of COD neither were there any marked seasonal pattern observed.
Oil and Grease (OG)
Oil and grease fluctuated between 0.01 and 17.9 mg L-1. The upstream
(station 1) and downstream (station 5) recorded considerably lower oil and grease
values. Station 2 recorded relatively higher values of OG. It had a mean of
7.49 mg L-1 and was the cause of the observed differences among the
stations sampled (p<0.05). Station 3 also recorded relatively higher values
of OG but not up to the range obtained in station 2. There were no significant
differences in OG measured in the different months (p>0.05) neither was there
any seasonal pattern observed in the value of OG.
Phosphates in the surface water sampled fluctuated between 0.009 and 1.88.
Again station 2 recorded considerably higher values of phosphates in all the
months sampled. A mean of 1.25 mg L-1 was recorded for this station.
The upstream and downstream stations recorded much lower phosphates values in
all the months sampled. Analysis of variance showed that there were significant
differences (p<0.01) in the value of phosphates recorded among the stations.
The values of phosphates were uniform in station 3 and 4. Station 3 varied from
0.01 mg L-1 recorded in October to 0.12 mg L-1 recorded
in November 2005. Station 4 on the other hand fluctuated from 0.01 mg L-1
recorded in the months of March and April 2006 to 0.04 mg L-1 recorded
in May 2006. Analysis of variance did not detect any significant difference
(p>0.05) in phosphates value recorded monthly neither was there any seasonal
patter in phosphates observed.
Ammonium fluctuated between a low value of 0.32 mg L-1 recorded
in the month of January in station 5 to 6.315 mg L-1 recorded in
the month of February in station 2. Station 4 recorded relatively lower values
of ammonia throughout the months of sampling. The values of ammonium recorded
in station 1, 3 and 5 were uniform and not too different from each other. Analysis
of variance result showed that there was significant difference (p<0.05)
in the values of ammonium recorded among the stations. This test also revealed
that ammonium varied slightly within the months sampled. A relatively higher
value was recorded in the month of February in all the stations sampled except
in station 4 and was also generally high in January 2006
Iron fluctuated between 0.19 and 6.03 mg L-1 in station 3 and
4 respectively. The downstream station recorded considerably lower. Iron values
of between 0.31 to 1.24 mg L-1. This range was also similar to that
obtained in Station 1 (0.48-1.05 mg L-1) and Station 3 (0.19-0.42
mg L-1). Station 4 recorded relatively higher values of Iron in all
the months sampled with the highest value of 6.03 mg L-1 recorded
in the month of February 2006. Analysis of variance result showed that there
was significant variation (p<0.05) in the values of Iron recorded among the
various sampling stations. There was no significant difference in the values
of Iron observed monthly. Again there was no clear seasonal pattern observed.
The values of copper were significantly (p<0.05) higher in stations 2
and 3 as compared with the upstream and downstream stations. Generally copper
fluctuated between 0.00 mg L-1 recorded in the month of February
in Station 1 to 0.06 mg L-1 recorded in month of January in Station
2. Stations 1, 4 and 5 recorded uniform values in copper fluctuating from 0.00
to 0.02 mg L-1. Analysis of variance result showed that the values
of copper was significantly (p<0.05) different among the sampling stations
but not different among the different sampling months (p>0.05). Again, there
was no observed seasonal pattern of variation in copper.
The rainfall and relative humidity regimes during the period of study were typical of the deltaic area of Nigeria with relatively high values of these parameters in the months of May and July (Ikomi et al., 2003).
The pH range of 6.60-8.22 recorded in the study indicates that the water was slightly acidic with occasional slight alkaline condition. Generally rivers flowing through forest are acidic with pH ranging from 4 to neutrality (Welcomme, 1975). The range recorded in this study is very close to those recorded in many Nigerian and other African water bodies (Egborge et al., 1986; Onwudinjo, 1990; Ogbeibu and Victor, 1995; Jonalagadda and Mhere, 2001). Like the observations of Egborge et al. (1986) and Odum (1992) there was no discernible seasonal pattern in the pH.
Water temperature did not show any seasonal variations. The absence of seasonal variations in the water temperature is explained by the fact that water has great specific heat capacity. Hence the radiation received by the water body hardly brings about serious fluctuation on a daily basis. However, the effects of cloud cover and river flow on the ambient and water temperature must not be ignored (Imoobe and Oboh, 2003). Thus it seems that the response to the major changes in ambient temperature is slow since a body of water must absorb vast quantities of heat in order to increase or decrease its temperature by 10°C.
Turbidity is a measure of the ability of a water to received light and is caused by small particles in the various stations were turbidity exist. Station 2 was significantly more turbid than all the other stations examined. This can be attributed to the compounds discharge from the near by fuel oiling station into the river.
The influxes of industrial effluents significantly lead to the increase in total dissolved solids in station 2, 3 and 4. Station 1 and 5 recorded lower values. Dissolved solids values were high during the dry season period and low in the rainy season, thus reflecting a seasonal pattern of variation. High dissolved solids (<600 mg L-1) as the ones recorded in station 4 may be harmful to aquatic life (Velz, 1985).
Conductivity values from this study show that the sections of the Warri River sampled contain appreciable amount of dissolved ions thus forming a saline barrier for the survival of sensitive organisms. The values recorded for station 1, 2 and 5 is similar to that reported by Egborge et al. 1986 in Bench river, Adebisi 1981 in Upper Ogun River, Nigeria. Station 4 recorded remarkably high conductivity values as a result of the nature of effluents discharge from helipad canteen and New PC laboratory. These discharges thus contain significantly high amounts of ions that exceed the recommended standard by EPA. Salinity values recorded in this study stations also indicates that station 2, 3 and 4 had significantly higher amount of salt contents. On the other hand the upstream and down stream stations had lower salt content.
The dissolved oxygen concentration of the section of the river examined showed that the river was poorly aerated, irrespective of season and station. The low mean values of dissolved oxygen recorded falls short of the relatively higher values reported by Egborge et al. (1986) and Umeham (1989). These low values observed may be as a result of the nature of the effluents discharge into the water that places a high demand on the dissolved oxygen. Again, the raw effluents discharge into the water resulted to high COD and BOD values.
The colloidal suspension in the effluent discharges may have likely increase turbidity and reduce transparency of the water body. This finding is consistent with the reported work of Olaleye and Adedeji (2005) of Oluwa River receiving palm oil effluent in Ondo state, Nigeria.
In addition, the high levels of dissolved oxygen and suspended solids in the water systems increased the BOD and COD, which depleted the dissolved oxygen in the water system. The levels of TDS in a broad sense therefore reflect the pollutant burden on the aquatic system.
Oil and grease values were high in the sampled stations especially in station 2 which normally receive effluents discharge into the stream from a nearby filing station. Studies of the aquatic ecosystems in the Niger Delta have also indicated high levels of oil and grease in areas prone to oil spills (Ibiebele et al., 1983; Dahlin et al., 1985).
The monthly variation pattern and the mean values recorded for some nutrients (phosphate and ammonium) are similar to those waters in Nigeria receiving effluents of various sorts from industries and domestic activities (Olaleye and Adedeji, 2005; Adebisi, 1981; Ogbondeminu, 1986). The heavy or trace metals (Iron, Copper, Chromium, Lead) were usually present in the waters examined particularly at much lower concentrations. Many of the trace metals like lead (Pb) and Cadmium (Cd) are highly toxic to humans and other living organisms and their presence in surface water above background concentration is undesirable (Velz, 1985). Unlike many organic pollutants, metals are not chemically or biologically degradable, but may be bioconcentrated in the food chain.
This process of biomagnification, biomagnifications or bioaccumulation has been responsible for major pollution indicators in the past (Radojevie and Bashkin, 1999). The concentrations of heavy metals recorded in this study were high although not up to the maximum allocable limits set by Federal Ministry of Environment, Nigeria.
From the data collated in this research, the physicochemical parameters monitored in station 2, 3 and 4 showed high levels of dissolved and suspended solids. This must have been as a result of the nature of the effluents discharged from the watershed into the river. Station 2 particularly in some months sampled exceeded the limits set by Federal Ministry of Environment and International Bodies. Staff of the various industries located along the sketch of the river should avoid the discharge of wastes that are not environmental friendly. Regular flushing and maintenance of the saver pit is recommended. Accordingly, water from these sample stations is not entirely free from gross pollution and cannot be used for domestic purposes and drinking without treatment.