Temporal and Spatial Dynamics of Selected Physicochemical Parameters in Awoye River, Ondo State, Nigeria

419 Nigerian Research Journal of Engineering and Environmental Sciences 10(2) 2025 pp. 419-430 p ISSN: 2635-3342; e ISSN: 2635-3350 Original Research Article Temporal and Spatial Dynamics of Selected Physicochemical Parameters in Awoye River, Ondo State, Nigeria Aribo, E.R. Department of Aquaculture and Fisheries Management, Faculty of Agriculture, University of Benin, Benin City, P.M.B. 1154, Benin City, Nigeria. [email protected] http://doi.org/10.5281/zenodo.18061407 ARTICLE INFORMATION ABSTRACT Article history: Received 01 Sep. 2025 Revised 31 Oct. 2025 Accepted 09 Nov. 2025 Available online 30 Dec. 2025 Rivers play a vital role in supporting human livelihoods and ecological balance, yet their water quality is increasingly affected by natural processes and anthropogenic activities. This study examined the temporal and spatial dynamics of selected physicochemical parameters in the Awoye River, Ondo State, Nigeria, over a six-month period. Water samples were collected from three stations and analyzed using standard methods for parameters including pH, temperature, conductivity, total dissolved solids (TDS), total suspended solids (TSS), dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), nutrients, and oil and grease (O/G). Results indicated marked seasonal and spatial variations. Conductivity, TDS, turbidity, nutrients, and O/G were significantly higher in the rainy season than in the dry season, reflecting the influence of runoff and effluent discharges. Stations located near oil exploration and effluent discharge points recorded elevated levels of chloride, salinity, and hydrocarbons. Although DO concentrations remained within acceptable limits, high BOD and COD values suggested organic enrichment and potential ecological stress. The study underscores the vulnerability of Awoye River to both natural and anthropogenic pressures and recommends continuous monitoring and sustainable management to protect water quality and aquatic resources. © 2025 RJEES. All rights reserved. Keywords: Physicochemical parameters Temporal variation Spatial variation Water quality Nigeria 1. INTRODUCTION Rivers and other freshwater systems are indispensable to both ecological integrity and human wellbeing, serving as critical sources of ecosystem services. They provide water for domestic consumption, irrigation in agriculture, industrial processes, aquaculture, transportation, and recreational activities, while also sustaining biodiversity by supporting diverse aquatic organisms (Boyd, 2020). Beyond their 420 E.R. Aribo / Nigerian Research Journal of Engineering and Environmental Sciences 10(2) 2025 pp. 419-430 direct uses, rivers play a regulatory role in nutrient cycling, climate moderation, and groundwater recharge, making their ecological stability essential for sustainable development (Boyd, 2020). However, the quality of river water is not static; it is shaped by a complex interplay of natural processes and human-induced pressures (Vörösmarty et al., 2010). Natural processes such as weathering of rocks, seasonal hydrological cycles, and climatic conditions can influence the chemical composition and physical properties of river water (Allan and Castillo, 2007). Conversely, anthropogenic activities including urbanization, agricultural runoff, industrial effluents, artisanal mining, oil exploration, and improper waste disposal introduce pollutants and alter hydrological regimes, thereby exacerbating fluctuations in water quality (Omoigberale and Ogbeibu, 2010). These influences manifest in both temporal and spatial variations of physicochemical parameters. Temporal variation refers to changes that occur over time, often linked to seasonal patterns such as rainfall intensity, dry and wet season dynamics, and fluctuations in temperature that affect dissolved oxygen levels, turbidity, and nutrient concentrations (Oketola et al., 2020; Ololade and Adewuyi, 2022). Spatial variation, on the other hand, reflects differences in water quality across locations within the same river system, often arising from localized land use patterns, soil characteristics, topography, effluent discharges, and point or non-point sources of pollution along the river course (Akoteyon et al., 2019; Eniola et al., 2021). Together, these variations provide a comprehensive picture of river health and resilience, offering insights into the interactions between environmental processes and human activities. Physicochemical parameters such as pH, air and water temperature, electrical conductivity, total dissolved solids (TDS), total suspended solids (TSS), colour, turbidity, chloride, salinity, sulphate, nitrate, phosphate-phosphorus, chemical oxygen demand (COD), dissolved oxygen (DO), biological oxygen demand (BOD), oil and grease, sodium, potassium, and calcium are widely recognized as fundamental indicators of water quality and ecological integrity (Edokpayi et al., 2018; Olalekan et al., 2020; Ogbeibu et al., 2021). These parameters provide valuable insights into the chemical composition, physical characteristics, and overall health of aquatic ecosystems. For instance, pH and temperature influence the solubility of gases and the biological availability of nutrients and metals, while dissolved oxygen and BOD serve as direct measures of the capacity of the water body to support aquatic life (Akpan and Offem, 2019). Similarly, turbidity, conductivity, and nutrient concentrations (e.g., nitrate and phosphate) are closely linked to land use activities, pollution inputs, and hydrological processes within a river basin (Nkwoji et al., 2020). Monitoring the temporal and spatial dynamics of these parameters is therefore crucial in evaluating the ecological status of freshwater systems. Temporal assessments allow researchers to identify seasonal or climatic influences, such as increased runoff during rainy seasons that may elevate turbidity and nutrient loading, or reduced flows in the dry season that concentrate pollutants. Spatial assessments, on the other hand, reveal how land use practices, effluent discharges, geomorphology, and human settlement patterns contribute to variations in water quality along different sections of a river. In Nigeria, river systems are increasingly exposed to multiple stressors arising from rapid urbanization, agricultural runoff, oil exploration, and industrial discharges. These pressures significantly alter their physicochemical balance and pose considerable risks to aquatic biodiversity, ecosystem services, and human health (Chindah et al., 2019). The Awoye River in Ondo State holds particular socio-economic importance, serving as a vital source of water for fishing, agriculture, and domestic use among surrounding communities. However, like many rivers in the Niger Delta region, it is highly vulnerable to seasonal flooding, indiscriminate waste disposal, artisanal oil exploration, and other anthropogenic disturbances that may trigger fluctuations in its physicochemical properties. Investigating the temporal and spatial dynamics of selected physicochemical parameters in the Awoye River is therefore crucial. Such a study provides baseline data necessary for assessing the ecological health of the river and for detecting pollution trends linked to both natural variability and human activities. The findings will offer valuable insights to guide effective water resource management, inform evidence-based policy decisions, and support conservation measures aimed at protecting aquatic 421 E.R. Aribo / Nigerian Research Journal of Engineering and Environmental Sciences 10(2) 2025 pp. 419-430 biodiversity. Ultimately, this knowledge is critical to safeguarding the livelihoods and well-being of local populations whose socio-economic activities and food security are directly tied to the river. 2. MATERIALS AND METHODS 2.1. Description of the Study Area Sampling was conducted in Awoye community, located in Ilaje Local Government Area of Ondo State, Nigeria. Awoye, a major fishing terminal, lies within a coastal region where about 75% of the land is covered by water. Ilaje LGA extends between latitude 6°N–6.3°N and longitude 4.45°E, sharing boundaries with Ikale LGA to the North, the Atlantic Ocean to the South, Ogun State to the West, and Delta State to the East. The area covers approximately 180 km of coastline, making Ondo State one of the states with the longest coastlines in Nigeria. This is shown in Figure 1. Figure 1: Map of study area (Adeyemo et al., 2015) 2.2. Sampling Stations Three stations were chosen for this study\based on their effluent characteristics. Station 1 and 2 were based on their proximity to petroleum activities (sources of pollutants), while station 3 was use as control. Station 1: The NNPC Platform (5°.441N, 4°.321E) is a long-standing oil facility linked to over 25 wells and the Chevron/NNPC joint venture at Opoekeba. Operating for more than two decades, it contributes to environmental pollution through effluent discharges, waste oils, gas flaring, and spills. These activities have degraded water quality and reduced local livelihoods, with farming and fishing largely abandoned due to restrictions and declining fish catches. Station 1 is shown in Plate 1. Station 2: The stone jetty, located at latitude 50.55N and longitude 4°.91, is heavily impacted by mixed effluent sources from agriculture, domestic activities, and petroleum operations. Constructed by the Niger Delta Development Commission (NDDC), it serves as a hub for boat mooring, cargo handling, and passenger movement, which introduces waste oil, carbon deposits, and domestic waste into the water. This is shown in Plate 2. 422 E.R. Aribo / Nigerian Research Journal of Engineering and Environmental Sciences 10(2) 2025 pp. 419-430 Station 3: This is Awoye gulf and it is located between latitude 50.781N and Longitude 40.91E. It is at the lower reaches of the River where it narrows and enters into the adjacent Atlantic Ocean with a width of between 20-35m, This is shown in Plate 3. 2.3. Field Procedure Water samples were collected in replicates over six months from three locations for laboratory analysis. Water was sampled using plastic and oxygen bottles, using USEPA (2008) procedures. Physicochemical parameters (e.g., pH, temperature, conductivity, TDS, TSS, COD, DO, BOD, nutrients, salinity, oil and grease, major ions) were analyzed to assess water quality and ecological health. 2.4. Analysis of Physical and Chemical Parameters in Water 2.4.1. pH The pH of each water sample saw determined using a porTable pH meter (cole-parmer pocket pH tester model 5900). 2.4.2. Air and water temperature Air and water temperatures were determined in-situ using a centigrade mercury thermometer (APHA, 1989). The thermometer was allowed to stay in each medium for 3 minutes to stabilize before taking the value. 2.4.3. Electrical conductivity The electrical conductivity of the surface water was determined by using conductivity meter (APHA, 1989, ASTM, 1986). The electrode was allowed to stay in the surface water for 1 minute to stabilize before reading the value which was expressed in micro-siemens (µS). 2.4.4. Total dissolved solids (TDS) The total dissolved solid in the surface water from each sampling station was determined in the laboratory by the use of TDS meter (ASTM, 1986). The electrodes were allowed to stay in the water for 1 minute to stabilize before reading the value which was expressed in mg/1. 2.4.5. Total suspended solids A Whatman No.42 filter paper was oven dried to a constant weight (wi)g at the temperature of 85°C. A known volume (100 ml) of properly shaken water sample was filtered through the dried filter paper. After filtration, the filter paper with its contents were oven dried again at a temperature of 85°C to a content weight (W2) g. Plate 3: The Entrance into the Atlantic Ocean Plate 2: Stone Jetty with Marine Operations Plate 1: NNPC/Chevron Operation Platform in 423 E.R. Aribo / Nigerian Research Journal of Engineering and Environmental Sciences 10(2) 2025 pp. 419-430 Weight of total solids in 100 ml = (W1 – W2) g Therefore, the total solids in 1 litre of water was calculated using Equation 1. Total solids (mg/L) =(𝑊1−(𝑊 2) 𝑋 1000 𝑉 (1) 2.4.6. Colour The colour of the water samples was determined by spectrophotometric method (APHA, 1989) using HACHDR/2000. The value of the colour was expressed in platinum cobalt scale (Pt-Co). 2.4.7. Turbidity Water turbidity was determined at the point of collection by nephalometric method using HACHDR/2000 (APHA, 1989; ASTM, 1986). The value of the turbidity was expressed in Nephelometric Turbidity Unit (NTU) 2.4.8. Chloride Chloride was determined by the Argentometric method (APHA, 1989, ASTM, 1986). 25ml of water sample in a conical flask, few drops of potassium chromate were added as indicator turning the solution yellow. The yellow solution was titrated with silver nitrate (0.01M AgNOs) by adding drop by drop from a burette until the yellow colour turned light brown signifying the end point of the titration. This is calculated using Equation 2. Chloride (mg/L) =𝑀 𝑋 𝑇 𝑋 𝑀𝐴 𝑋 1000 𝑉 𝑠 (2) Where, M = molarity of AgNO₃ (mol/L), T = titre value (volume of AgNO₃ used, mL), MA = molar mass of Cl⁻ = 35.45 g/mol, and VS = aliquot volume of sample used (mL) 2.4.9. Salinity Total Dissolved Salts (TDS) is measured by evaporating a known volume of water to dryness, then weighing the solid residue remaining. 2.4.10. Sulphate Sulphate in water samples was determined by the turbidimetric method (APHA, 1989). 2.4.11. Nitrate Nitrate was determined by the Brucine sulphanillic acid colourimetric method (APHA, 1989; ASTM, 1986). 2.4.12. Phosphate-P Phosphate-P was determined by the ascorbic acid method (ASTM, 1986). 2.4.13. Chemical oxygen demand (COD) Chemical oxygen demand was determined by close influx titrimetric method (APHA, 1989; ASTM, 1986). 2.4.14. Dissolved oxygen The dissolved oxygen of the surface water from each sample station was determined in the laboratory by using an oxygen meter griffin model DOS-210 (APHA, 1989), and expressed in ml/l. 2.4.15. Biological oxygen demand (BOD) The biological oxygen demand level in each water sample was determined in the laboratory using an oxygen meter griffin model DOS - 21 OK (APHA, 1989), after five days, and expressed in mg/1. The biological oxygen demand (BOD) was calculated by subtracting the dissolved oxygen value DO5 from DO1 (DOD05) 2.4.16. Oil and grease Determination of oil and grease in Water with a Mid-Infrared Spectrometer (APHA, 1989) 424 E.R. Aribo / Nigerian Research Journal of Engineering and Environmental Sciences 10(2) 2025 pp. 419-430 2.4.17. Sodium and potassium Sodium and potassium were determined by the flame emission photometric method (APHA, 1989). The water samples were aspirated into the Gallemkamp flame analyser and the values of sodium and potassium were read and expressed in mg/l. 2.4.18. Calcium The titrimetric method was used to determine calcium in water sample (APHA, 1998). 2.5. Data Analysis Means, standard deviations, and standard error (95% confidence limit) were calculated for all physical and chemical parameters measured. Analysis of variance (ANOVA) was performed to establish the significant differences in the monthly concentrations of parameters during the study period. If ANOVA yielded a significant F-value, A posteriori comparison using Duncan's multiple range test was performed to detect the locations, month of the significant differences. The data obtained for dry and rainy seasons were analyzed using an unpaired t-test (n1-n2) to detect the differences between the two seasons: correlation coefficients were calculated using the 2012 SPSS Windows package. 3. RESULTS AND DISCUSSION The summaries of the results of the physico-chemical properties in water samples from the Stations, months, and seasons are presented in Tables 1, 2, and 3. Table 3 shows that with the exception of air and water temperature and alkalinity, the mean values for all other physical and chemical properties were higher in the rainy season than in the dry season at all the stations. Air temperature was higher in wet season in station 3, while water temperature was higher in the wet season at station 2. 3.1. Physicochemical Parameters in Water The physio-chemical analysis of study stations of Awoye River (January-June, 2015) revealed the following properties as presented in Tables 1, 2, and 3. 3.1.1. pH The mean value of pH showed that station 3 had the highest (5.71±0.20) and station1 has the lowest (5.58±0.09) as shown in Table 1. On monthly basis, the highest mean value was found in the month of June (5.93±0.20) while the lowest was March (5.52±0.03). This is revealed in Table 2, Seasonally, in Table 3, the mean distribution of pH was higher in the rainy season (5.73±0.18) than in dry season (5.53±0.09). There was no significant difference (p>0.05) among the 3 stations, but there was a significant difference (P<0.05) between the months with June significantly different (P<0.05) from all other months. The physicochemical assessment of Awoye River revealed that the water body is under significant stress from both natural and anthropogenic activities. The pH values recorded were generally acidic (5.42–6.11), falling below the World Health Organization (WHO) and national regulatory standards of 6.5–8.5. This acidity may be attributed to decaying organic matter, metallic ions, and acid rain linked to prolonged gas flaring in the area, making the water unsuitable for drinking and potentially harmful to aquatic organisms. 3.1.2. Air and water temperature The lowest air temperature was observed in Station 3 (27.30±0.76o), while the highest temperature of 28.65±0.290 was recorded in station 1 (Table 1). On monthly basis, the highest air temperature 28.33±0.23o was recorded in the month of June, while the lowest of 27.43±0.23o in the month of April '(Table 2). Seasonally, there was higher mean air temperature in almost all the rainy season (27.88+0.64o) than in dry season (27.87±0.93o) (Table3). There was a significant difference (P<0.05) between stations with station 1 significantly different from station 2 and 3, but there was no significant difference (P>0.05) among the months, using Duncan Multiple Range Test. The mean distribution of water temperature revealed that station 1 had the highest (23.50±0.46), and station 2 the lowest (23.27±0.38) (tab1). On monthly basis, the highest value (23.17±0.15) was found in February, while the lowest (22.93±0.15) was in January. Seasonally, there was no difference between the values obtained in rainy season from those obtained in dry season. There was no significant difference (P>0.05) between the months but there was a significant difference (P<0.05) between the stations, with station 3 significantly different from station 1 and 2. Temperature values for both 425 E.R. Aribo / Nigerian Research Journal of Engineering and Environmental Sciences 10(2) 2025 pp. 419-430 air and water were within acceptable limits, although slightly elevated at stations close to gas flaring sites, reflecting localized thermal influence. Table 1: Mean (+SD) comparison of physico-chemical parameters of the study stations of Awoye River (January-June, 2015) Physicochemical parameters Station 1 Station 2 Station 3 P Remark pH 5.58+0.09a 5.60+0.21a 5.71+0.20a 0.357 P>0.05 Air temp (oc) 28.65+0.29a 27.67+0.45b 27.30+0.76b 0.002 P<0.05 Water temp(oc) 23.50+0.46 a 23.27+0.38ab 23.00+0.18b 0.085 P>0.05 Conductivity(µS) 178.00+16.88 a 162.17+22.48a 121.83+17.87b 0.000 P<0.05 TDS (mg/l) 89.00+8.44a 81.08+11.24a 60.92+8.94b 0.000 P<0.05 TSS (mg/l) 27.59+2.61a 25.14+3.48a 6.71+0.98b 0.000 P<0.05 Alkalinity(mg/l) 36.60+0.58a 36.50+1.32a 35.74+1.18a 0.344 P>0.05 Colour 4.74+0.07c 7.55+0.28a 5.43+0.19b 0.000 P<0.05 Turbidity(NTU) 17.36+0.12 a 17.38+0.28a 17.54+0.26 a 0.359 P>0.05 Chloride(mg/l) 153.40+5.06a 148.65+6.74a 136.55+5.36b 0.000 P<0.05 Salinity0/00 0.599+9.42a 0.590+12.55a 0.567+9.97b 0.000 P<0.05 Sulphate(mg/l) 10.86+1.03a 9.89+1.37a 11.09+1.63a 0.302 P>0.05 Nitrate (mg/l) 7.48+0.71a 6.81+0.94ab 6.33+0.93b 0.105 P>0.05 Phosphate(mg/l) 5.34+0.51ab 4.87+0.67b 6.09+0.89a 0.028 P<0.05 COD(mg/l) 72.98+6.92a 66.49+9.22a 74.32+10.90a 0.303 P>0.05 DO(mg/l) 8.11+0.99a 8.50+1.62a 9.36+1.66a 0.336 P>0.05 BOD(mg/l) 2.90+0.67b 2.71+0.53b 5.33+3.23a 0.059 P>0.05 O/G(mg/l) 10.76+2.75a 2.74+1.35b 1.38+0.31b 0.000 P<0.05 Na+(mg/l) 12.46+1.18a 11.35+1.57a 13.40+1.97a 0.120 P>0.05 K+(mg/l) 21.36+2.03a 19.46+2.70a 20.71+3.04a 0.461 P>0.05 Mg2+(mg/l) 3.9 2+0.37a 3.57+0.49a 3.90+0.57a 0.403 P>0.05 Ca2+(mg/l) 2 .14+0.20a 1.33+0.19b 0.76+0.11c 0.000 P<0.05 Means in the horizontal row with the same letters are not significantly different (P>0.05) Table 2: Mean (+SD) monthly comparison of physico-chemical parameters of Awoye River (January-June, 2015) Physicochemical parameters Jan Feb Mar April May June pH 5.53+0.12b 5.53+0.12b 5.52+0.03b 5.61+0.03b 5.65+0.02b 5.93+0.20a Air temp(oc) 27.47+1.31a 27.47+1.31a 28.10+0.89a 27.43+0.84a 27.87+0.50 a 28.33+0.23a Water temp(oc) 22.93+0.15a 22.93+0.15a 23.17+0.15a 23.37+0.38a 23.33+0.58 a 23.30+0.26a Conductivity(µS)) 141.33+271a 141.33+271a 129.67+313a 164.33+27.6a 171.33+30.07 a 176.00+30.64a TDS(mg/l) 70.67+13.81a 70.67+13.81a 64.83+15.57a 82.17+13.81a 85.67+15.04 a 88.00+15.32a TSS(mg/l) 18.21+10.56a 18.21+10.56a 16.87+10.19a 21.01+11.88a 21.99+12.54 a 22.58+12.86a Alkalinity(mg/l) 36.90+0.81a 36.90+0.81a 36.98+0.20a 36.36+0.20a 36.13+0.10a 34.41+1.20a Colour 5.79+1.37a 5.79+1.37a 5.79+1.46a 5.89+1.49a 5.93+1.48 a 6.24+1.65a Turbidity(NTU) 17.30+0.16b 17.30+0.16b 17.28+0.04b 17.41+0.04b 17.45+0.02b 17.83+0.2 7a Chloride(mg/l) 142.40+8.28a 142.40+8.28a 138.90+9.34a 149.30+8.28a 151.40+9.02 a 152.80+9a Salinity 0.758+15.41a 0.578+15.41a 0.572+17.37 a 0.591+15.41a 0.595+16.78 a 0.598+17.10a Sulphate (mg/l) 9.73+0.61b 9.73+0.61b 8.88+0.80b 11.36+0.88a 11.82+0.63a 12.15+0.65a Nitrate(mg/l) 6.31+0.58bc 6.31+0.58bc 5.77+0.83c 7.35+0.49ab 7.65+0.50a 7.86+0.50a Phosphate(mg/l) (PO43-) 4.98+0.56ab 4.98+0.56ab 4.54+0.48b 5.82+0.80a 6.05+0.70a 6.22+0.73a COD(mg/l) 65.35+40.4b 65.35+4.04b 59.63+5.34b 76.31+5.85a 79.38+4.07a 81.56+4.27a DO(mg/l) 8.80+0.55b 8.80+0.55b 6.69+0.42c 7.76+0.49bc 9.00+0.56b 10.88+1.54a BOD(mg/l) 2.29+0.14a 2.29+0.14a 2.66+0.02a 4.29+2.12a 4.98+2.46 a 5.37+ 3.93a O/G(mg/l) 4.44+4.69a 4.44+4.69a 3.42+3.61a 4.34+4.58a 5.51+5.82 a 7.59 + 7.07 a Na+(mg/l) 11.37+0.94bc 11.37+0.94bc 10.37+0.95c 13.29+1.39ab 13.82+1.13a 14.20+1.18a K+(mg/l) 18.81+1.02b 18.81+1.02b 17.18+1.67b 21.95+1.25a 22.84+0.66a 23.47+0.69a Mg2+(mg/l) 3.48+0.19b 3.48+0.19b 3.18+0.29b 4.06+0.27a 4.23+0.17 a 4.34+0.18a Ca2+(mg/l) 1.29+0.65a 1.29+0.65a 1.20+0.66a 1.50+0.72a 1.56+0.74 a 1.60+0.76a 426 E.R. Aribo / Nigerian Research Journal of Engineering and Environmental Sciences 10(2) 2025 pp. 419-430 Table 3: Mean (+SD) seasonal comparison of physico-chemical parameters in water (January-June, 2015) Physicochemical parameters Station 1 Station 2 Station 3 Dry Wet Dry Wet Dry Wet pH 5.50±0.01 5.65±0.07 5.45±0.05 5.74±0.21 5.62±0.06 5.80±0.27 Air temp 28.83±0.31 28.47±0.12 27.70±0.26 27.63±0.67 27.07±0.95 27.53±0.61 Water temp 23.53±0.59 23.47±0.42 23.13±0.21 23.40±0.52 22.87±0.12 23.13±0.12 Conductivity 163.00±3.46 193.00±5.00 143.00±8.66 181.33±9.29 106.33±8.08 137.33±3.51 TDS 81.50±1.73 96.50±2.50 71.50±4.33 90.67±4.65 53.17±4.04 68.67±1.76 TSS 25.27±0.54 29.92±0.78 22.17±1.34 28.11±1.44 5.85±0.44 7.56±0.20 Alkalinity 37.07±0.08 36.13±0.42 37.43±0.36 35.57±1.26 36.28±0.42 35.20±1.57 Colour 4.68±0.01 4.80±0.06 7.36±0.07 7.75±0.28 5.34±0.06 5.51±0.25 Turbidity 7.26±0.01 7.46±0.09 7.19±0.07 7.58±0.27 7.42±0.08 7.66±0.36 Chloride 48.90±1.04 57.90±1.50 42.90±2.60 54.40±2.79 31.90±2.42 41.20±1.05 Salinity 90.95±1.93 107.69±2.79 79.79±4.83 101.18±5.18 59.34±4.51 76.63±1.96 Sulphate 9.95±0.21 11.77±0.31 8.72±0.53 11.06±0.57 9.68±0.73 12.50±0.32 Nitrate 6.85±0.14 8.11±0.21 6.01±0.36 7.62±0.39 5.53±0.42 7.14±0.18 Phosphate 4.89±0.10 5.79±0.15 4.29±0.26 5.44±0.28 5.32±0.40 6.87±0.18 COD 66.83±1.42 79.13±2.05 58.63±3.55 74.35±3.81 64.86±4.93 83.77±2.14 DO 7.78±1.17 8.43±0.88 7.83±1.18 9.17±1.95 8.68±1.31 10.04±1.95 BOD 2.35±0.25 3.46±0.36 2.36±0.25 3.05±0.53 2.53±0.13 8.14±1.58 O/G 9.08±1.30 12.44±2.95 2.04±0.29 3.44±1.73 1.19±0.17 1.58±0.31 Na+ 11.41±0.24 13.51±0.35 10.01±0.61 12.69±0.65 11.70±0.89 15.11±0.39 K+ 19.56±0.42 23.16±0.60 17.16±1.04 21.76±1.11 18.08±1.37 23.35±0.60 Mg2+ 3.59±0.08 4.25±0.11 3.15±0.19 3.99±0.21 3.40±0.26 4.39±0.11 Ca2+ 1.96±0.04 2.32±0.06 1.17±0.07 1.49±0.08 0.66±0.05 0.85±0.02 Means in the horizontal row with the same letters are not significantly different (p>0.05) 3.1.3. Conductivity The conductivity of water samples varied across seasons and stations, with the highest mean value recorded in June (178.00 ± 30.64 µS/cm) and the lowest in March (129.67 ± 31.13 µS/cm). Conductivity was generally higher during the rainy season (170.56 ± 26.02 µS/cm) compared to the dry season (137.44 ± 25.64 µS/cm). Statistical analysis showed a significant difference (P < 0.05) among stations, with station 3 differing significantly from stations 1 and 2, although no significant variation was observed across the months. Conductivity and salinity levels were high, indicating a brackish water environment likely influenced by Atlantic Ocean intrusion and petroleum-related activities. These parameters exceeded WHO freshwater standards, underscoring the impact of saline encroachment. 3.1.4. Total Dissolved Solids (TDS) For total dissolved solids (TDS), station 1 had the highest mean value (89.00 ± 8.44 mg/L), while station 3 had the lowest (64.83 ± 15.57 mg/L). Monthly variation showed that TDS peaked in June and was lowest in March, with higher concentrations in the rainy season (170.50 ± 26.02 mg/L) compared to the dry season (137.44 ± 25.64 mg/L). ANOVA revealed significant differences among stations (P < 0.05), with station 3 significantly lower than stations 1 and 2, but no significant difference between months. 3.1.5. Total Suspended Solids (TSS) Total suspended solids (TSS) were highest in June (22.58 ± 12.86 mg/L) and lowest in March (16.87 ± 15.57 mg/L). Seasonal variations showed consistently higher values during the rainy season. Although no significant differences were found among months (P > 0.05), significant differences occurred among stations (P < 0.05), with station 3 differing significantly from stations 1 and 2. The study further showed that total dissolved solids (TDS) and total suspended solids (TSS) were within acceptable limits, though higher TSS values during the rainy season reflected runoff from surrounding human activities. Alkalinity levels were low, suggesting the river has poor buffering capacity and is therefore more vulnerable to heavy metal toxicity. Turbidity levels exceeded permissible limits, pointing to organic decay and anthropogenic contributions, while chloride concentrations were also higher than WHO standards, likely due to seawater intrusion and effluent discharge. Nutrient concentrations, particularly phosphate, exceeded WHO standards and indicated nutrient enrichment, which could promote eutrophication. 427 E.R. Aribo / Nigerian Research Journal of Engineering and Environmental Sciences 10(2) 2025 pp. 419-430 3.1.6. Alkalinity Alkalinity values ranged from 35.74 ± 1.18 mg/L at station 3 to 36.60 ± 0.58 mg/L at station 1. The highest monthly mean was recorded in January and February (36.90 ± 0.81 mg/L), while the lowest occurred in June (34.41 ± 1.20 mg/L). Seasonal means were slightly higher in the rainy season compared to the dry season, though no significant differences were found among stations or months (P > 0.05). 3.1.7. Water Water colour varied significantly across stations, ranging from 4.74 ± 0.07 Pt-Co units at station 1 to 7.55 ± 0.28 Pt-Co units at station 2. June recorded the highest monthly mean (6.24 ± 1.65), while the lowest was observed in January and February (5.79 ± 1.37). Higher values occurred during the rainy season. ANOVA confirmed significant differences among stations (P < 0.05), with all stations differing significantly from one another, though no significant differences were observed across months. 3.1.8. Turbidity Turbidity values ranged between 17.36 ± 0.12 NTU at station 1 and 17.54 ± 0.26 NTU at station 3. June recorded the highest mean turbidity (17.83 ± 0.27), while January and February had the lowest (17.30 ± 0.16). Rainy season values were generally higher than those in the dry season. While no significant differences occurred among stations (P > 0.05), monthly variation was significant (P < 0.05), with June significantly higher than other months. 3.1.9. Chloride Chloride concentrations were highest at station 1 (153.40 ± 5.06 mg/L) and lowest at station 3 (136.55 ± 5.36 mg/L). The highest monthly mean was observed in June (152.80 ± 9.19 mg/L), while March recorded the lowest (138.90 ± 9.34 mg/L). Seasonal values were higher in the rainy season. Significant variation was found among stations (P < 0.05), with station 3 differing significantly from stations 1 and 2, though no significant differences were detected across months. 3.1.10. Salinity Salinity values ranged from 0.567 ± 9.97‰ at station 3 to 0.599 ± 9.42‰ at station 1. The highest mean salinity occurred in June (0.598 ± 17.10‰), while March recorded the lowest (0.572 ± 17.37‰). Higher values were observed during the rainy season. Significant differences were found among stations (P < 0.05), with station 3 differing from stations 1 and 2, but no significant monthly variation was recorded. 3.1.11. Sulphate Sulphate levels ranged from 9.89 ± 1.37 mg/L at station 2 to 11.09 ± 1.63 mg/L at station 3. June recorded the highest mean sulphate concentration (12.15 ± 0.65 mg/L), while March had the lowest (8.88 ± 0.80 mg/L). Rainy season values were higher across stations. Although no significant differences were observed among stations (P > 0.05), there were significant differences between months (P < 0.05), with April, May, and June differing from the other months. 3.1.11. Nitrate Nitrate concentrations ranged from 6.33 ± 0.93 mg/L at station 3 to 7.48 ± 0.71 mg/L at station 1. The highest monthly mean was recorded in June (7.86 ± 0.50 mg/L), while March had the lowest (5.77 ± 0.83 mg/L). Seasonal means were consistently higher in the rainy season, though no significant differences were observed among stations or months (P > 0.05). 3.1.12. Phosphate Phosphate concentrations were highest at station 2 (4.87 ± 0.67 mg/L) and lowest at station 3 (6.09 ± 0.89 mg/L). The highest monthly mean occurred in June (6.22 ± 0.73 mg/L), while the lowest was in March (4.54 ± 0.48 mg/L). Rainy season concentrations were higher than dry season values. ANOVA showed significant differences among both stations and months (P < 0.05), with station 3 significantly higher than stations 1 and 2.