Spatial Variation of Dissolved Nutrient and Heavy Metal Concentrations in River Bed Sediments as Influenced by Land-Use Patterns in Ogun-Osun River Basin, Nigeria ()
1. Introduction
Changes in land-use patterns are directly altering the functioning of ecosystems worldwide [1]. The changes, however, have significant impact on the nutrient concentrations, and concomitantly influence the quality of river water and water resources. These impacts can be negative and positive [2]. Agriculture, forestry, metaliferous mining, smelting industry, urban related activities are some of the land-use/land-cover types that have been identified with varying impacts on the hydrological regimes of a basin. However, soils may be contaminated by heavy metals such as Zn, Cd, Pb and Cu due to sludge from these land-uses [3,4] while nutrient from animal manure and other related agricultural activities also contribute to the quality of sediments washed off the land surfaces [5]. Earlier observation by [6] shows that land-use has impact on water quality through changes in sediment and nutrient loads, salts, metals and agrochemicals, influx of pathogens and change in the temperature regime. Sediment can further act both as a physical and chemical pollutant. Physical contribution of sediment to pollution includes increase in turbidity, sedimentation leading to loss of downstream reservoir capacity, destruction of coral reefs, loss of spawning grounds for certain fish while chemical pollution of sediment includes redistribution of adsorbed metals and nutrients as well as hydrophobic organic metals in the river systems [7].
River water quality is controlled by numerous natural and anthropogenic factors. For instance the water quality in the Tibetian Rivers in China is related to the mining activities in the region [8]. River sediments receive significant anthropogenic loads of metals and other pollutants from both point and non-point sources, which increase their natural concentrations. Metals, for instance, from different sources normally accumulate together, mostly in fine-grained fractions of sediments [9]. To this extent, researchers have identified river sediments as a reliable medium in the study of river pollution and for confirmation of impairment status and possible sources of pollutants when studying river pollution [10-12].
In Nigeria, there have been increasing pressures on land and water resources in an attempt to increase the production of food, fiber, fuel wood, and feeds for the growing population. This agricultural intensification has led to a substantial increase in the rates of fertilizer applications, use of sludge, animal and industrial wastes, which both improve yields and have deleterious consequences for downstream aquatic systems, where nutrient loading can drive eutrophication [13]. Efforts have been channeled to understand the water quality status of rivers in Nigeria, even though very often, the spatial scale does not always encompass the immediate hydrological basin in such investigations. Thus, the major hydrological basins that describe the nation water resources systems are not adequately described in terms of pollution and pollutants distribution; while assessments of water quality in relation to most rivers are location specific without a clear picture of status of river systems at the basin level. Even then, the extent of sediments pollution as a possible source of secondary pollution has not being given much attention, most often, sediment characterizations are not always included in environmental assessment except in response to specific events. This has resulted in paucity of information on the status of river bed sediment quality in relation to heavy metals and other nutrient levels across Nigerian hydrological basins. Hence, there is limitation to the understanding of the impact on surface water resources generally in Nigeria. Therefore, this study was designed to: 1) assess the spatial variations of nutrient concentrations and heavy metals pollutants; and 2) determine the contribution of river bed sediments to water pollution as influenced by land-use patterns along Ogun and Ona river catchments of Ogun-Osun River Basin in Nigeria.
2. Materials and Methods
2.1. Description of the Study Area
The study areas (Figure 1) cover the Ogun and Ona catchments (approx. 29,000 km2), about 65% of the Ogun-
Figure 1. Sampling locations in Ogun and Ona catchment areas.
Osun River Basin (OORB) in Nigeria. The OORB is one of the 12 delineated hydrological basins describing Nigeria land area. River bed sediments of 8 rivers were assessed from 24 locations across the catchments. Land-use patterns within the study catchments are interspersed majorly with urban, agricultural, grazing grassland and forest as the major land-use types. Ogun and Ona rivers drain the Ogun and Ona catchments respectively with other rivers (Ogunpa, Ofiki, Ibu, Omi, Ewekoro and Opeki) serving as major tributaries [14]. The rainfall within the basin ranged between 990 ± 62 mm - 1500 ± 87 mm from upstream north to the downstream south. The Ogun, Ona, Ogunpa, Ofiki and Ibu rivers are perennial while Omi, Ewekoro and Opeki rivers are seasonal. However, all the rivers are sources of water either as raw water for treatment plants, direct use for domestic supply by rural populace across the basin or for agricultural purposes.
2.2. Sediment Sampling and Quality Indicators
Sediment samples were collected at 0 - 20 cm depth in 24 locations across the catchments using bucket auger. The samples were collected in February 2011, a period characterized with low rainfall in the study area. To ensure representative sampling, bulk sediment samples in each location were composite of 3 sub-samples. The samples were stored in an acid (HNO3) washed plastic bags for laboratory analyses.
2.3. Laboratory Procedures
The sediment samples were air dried, crushed and allowed to pass through 2 mm mesh size, and then stored in glass bottles for subsequent analysis. Total organic carbon (TOC) content was determined using wet digestion method [15]. Total nitrogen (TN) was determined by Kjeldahl method [16]. Total phosphorus (TP) was determined using ascorbic acid method for the digested solution [17]. A molybdate colourimetric test was used to determine 
-P content in the digested solution [17]. For the analysis of heavy metals (Cadmium-Cd, Mercury-Hg, Lead-Pb, Zinc-Zn, Copper-Cu, Iron-Fe, Manganese-Mn and Chromium-Cr), subsamples of the airdried sediment samples were oven-dried at 105˚C for 24 hr and thereafter sieved using 500 micron sieve. 100 mg of the sample was digested with a mixture of 6 ml HF; 4 ml HNO3 and 1 ml HClO4 following [18]. All analyses were carried out in triplicate by direct aspiration into BUCK 211 Atomic Absorption Spectrophotometer Model against the standard concentration of the metals.
2.4. Statistical Analysis
Descriptive statistics were performed on the data. The Duncan Multiple Range Test (DMRT) was used to compare the sediment pollutant characteristics across the rivers. Pearson correlation analysis was carried out to evaluate relationships among variables and across the locations. Significant relationships were established among the variables at P < 0.05 unless otherwise stated. Hierarchical cluster analysis (HCA) was applied to the river sediment quality data set to group similar sampling locations (spatial variability) across the river basin [19,20]. In this approach, clusters are formed sequentially by starting with the most similar pair of objects and forming higher clusters step by step. The Euclidean distance usually gives the similarity between two samples and a “distance” can be represented by the “difference” between analytical values from both samples. The HCA was performed on the normalized data set by means of the Ward’s method, using Euclidean distances as a measure of similarity. All statistical analyses were performed using SPSS 16.0 software.
2.5. Pollution Load Index and Accumulation Factor
Pollution Load Index (PLI), the potential of a metal to cause secondary pollution in river water at observed concentration, was computed as described by [21].
PLI = n√ (Product of n number of CF values) (1)
Where: n = Number of Metals
(2)
The world average concentrations of Cu (45 mg/kg), Zn (95 mg/kg), Fe (46,000 mg/kg), Mn (800 mg/kg), Pb (20 mg/kg), Cr (100 mg/kg) and Cd (0.3 mg/kg) were considered as the background values [21].
The degree of accumulation of sediment pollutants along the river courses was estimated by the Accumulation Factor (AF). The AF is the ratio of average concentration of a given parameter downstream (after a source discharge) to the corresponding average concentration upstream (before the source discharge) [22].
3. Results and Discussion
3.1. Bed Sediment Nutrients and Heavy Metal Concentrations
Table 1 shows the characteristics of nutrients and heavy metals in the river courses. The mean 
-P observed in the basin was 12.8 ± 1.09 mg/kg. The highest concentration of 14.7 mg 
-P/kg was observed in Ona river and the least (10.4 mg 
-P/kg) in Ewekoro river. The mean TP was 10.9 ± 1.11 mg/kg in the catchments. Ogun river had the highest TP of 12.1 mg/kg while Ewekoro had the least TP of 7.4 mg/kg in the basin. The
Table 1. Concentration of sediment quality indicators in the river basin.
higher concentration of P forms in Ogun-Osun river basin could be related to the use of fertilizers, especially Pfertilizers, laundry soaps and discharge of wastewater in the river systems. Waste disposal in the basin especially within the urban area is not adequately controlled since Nigeria has weak legislation and regulations on the handling, disposal and use of municipal wastes and fertilizers across agricultural land-uses [23]. Also, river Ewekoro flows across the Sagamu axis (in the downstream), a semi-industrial area where cement production are pre-dominant coupled with mining of rock phosphate. The observed phosphate and total phosphorous range in the sediment were high and this could contribute to secondary pollution in the river system.
Mean TOC in the study basin was 3.21 ± 0.65 g/100g with the highest value observed in Ogun river (5.1 g/100g) while the lowest observed sediment organic content was 2.4 g/100g from Ona river. The TN also ranged between 0.24% - 0.49% while river Ogun recorded the maximum level of TN. The levels of TOC, TN, TP and 
-P showed the influx of organic and nutrient content from major land-use into the river system which contributed to the observed sediment quality. Whereas rivers Ogunpa, Omi and Ona are purely urban drainages, Ogun and Ofiki drain agricultural, urban and grazing land-uses. It has been observed that agricultural soils can contribute up to 220 kg∙C∙ha−1∙yr−1 of soil carbon in eroded soil [24]. Rivers Ewekoro and Opeki are within agricultural sub-urban land-use and therefore, the input from urban and agricultural runoff contributes to the sediment quality of the Opeki, Omi and Ewekoro rivers.
There were variations in river bed heavy metals among the sampling locations across the basin. Figures 2 and 3 showed the distributions of Fe, Cd, Zn, Hg, Cu, Mn, Pb and Cr. The minimum Fe observed in the sediment was 1.1 mg/kg in ON4 and maximum concentration of 2.1 mg/kg in EW1. The observed Fe concentration in OG3, ON3, OG4, OG5 and OF1 were higher than other sampled locations. This could be due to the urban land-use in those locations except OF1 which is located in the agricultural area upstream of the Ogun River. Zn ranged between 1.2 mg/kg (OF3) and 2.1 mg/kg (IB2). The general observation of heavy metals in the sediment across the basin showed that Fe, Zn, Cu, Mn, Cr and Pb did not exceed the world average in tropical rivers [25] as compared with Cd which exceeded the limit (0.3 mg/kg). This implies that the levels of metal in the sediments have not reached a limit that could be of major concern (except for Cd) even though this was not the case with heavy metals in the river water as earlier documented [26]. The variations in concentration of heavy metals across the locations reflect different levels of inputs across the catchment from anthropogenic activities and land-use characteristic [27].
Among the rivers, significant differences (p < 0.05) existed in sediment quality indicators except for TOC (Table 2). The DMRT separated the rivers according to the level of significance of observed variable. River Ewekoro draining a semi-urban catchment was significantly higher than other rivers in terms of Cd, Cr and Fe while Ogun, Ona, Ofiki and Omi are similar in 
-P, TN, Cr and TOC.
Figure 2. Distribution of Fe, Zn, Mn and Cu in sediments across rivers in Ogun and Ona basin.
Figure 3. Distribution of Pb, Cr, Cd and Hg in sediments across rivers in Ogun and Ona basin.
Table 2. Mean separation of average values of sediment quality indicators.
A strong correlation (p < 0.01) was observed between TOC, 
-P and TN. However, TOC did not correlate with TP. The correlation between TOC and 
-P may relate to the particulate phosphorous in the sediment whereas, TP included the bounded and occluded phosphorous which are not readily available and therefore not strongly related to the organic carbon content in the sediment [28].
3.2. Correlation of Heavy Metals and Organic Load
There were inverse relationships among Fe, Zn, Mn with TOC in the sediment collected from Ogun river. These are similar to what were obtained in Ona and Ofiki rivers. These relationships with high R2 (between 0.62 and 0.85) showed that Fe, Zn, and Mn content in the river bed sediment may not be associated with organic carbon level alone, but also deposition of metals in particulate form.
Vuori [29] observed that the oxidized Fe particles in river water are removed by settling on the river bed where they may be periodically re-suspended depending on their size and the velocity of the current. During instream activities, Fe3+ oxyhydroxides are reduced to Fe2+, some parts of the complex diffused upward and become oxidized while others could form other minerals and iron sulfide [29]. This dynamics may account for increased level of Fe outside the concentration bounded in the organic matter [30]. The sorption and co-precipitation of metals by Fe-oxides decrease the bioavailability and toxicity of water-borne metals [27]. The higher the concentration of heavy metals in the sediments, the higher the risk portends by such metal to initiate secondary pollution with attendant health risks especially metals that are carcinogenic or mutagenic. Sediment-bound nutrients create a reserve pool which can be released back to the overlying waters, enhancing nutrient enrichment effects such as eutrophication [11,31].
The correlation between the metal concentrations and the organic matter content in the sediments has been shown by various researchers as a valid relationship that points towards pollution characteristics [31]. Although, adsorbed pollutants on the sediments may not be readily available for aquatic organisms, the variation of some physical and chemical characteristics of the overlying water may provoke the release of the metals back to the aqueous phase, hence under changing environmental conditions sediments may themselves become important pollution sources. This is a major danger in accumulation of metals in sediments of rivers and lakes. This phenomenon therefore, increases the possibility of secondary pollution which is much difficult to control or remediate in hydrological systems.
Location ON5 which is the last point on Ona river had the highest phosphate and TP. A high correlation (0.84, p < 0.05) was observed between 
and TP (Table 3) across the basin which implies that much of the phosphorous in the system are related to particulate phosphate [27]. Similarly, high correlation (0.91, p < 0.01) was equally observed between TOC and TN which confirms the understanding that high organic load is related to nitrogen pollution in a water body. The relationship between TOC and TN followed a linear regression (Figure 4). Lack of correlation of phosphate with metals on the other hand was because phosphates released during anaerobic decomposition are very soluble in water and are not bounded to sediment particles [32]. Soluble phosphate easily contributes to phosphate in the river water. This substantiates the work of [33] which reported the significance of phosphorous compounds in eutrophication of rivers in sub-Saharan Africa.
There was no significant correlation between observed concentration of heavy metals in the sediment and locations across the basin. This shows that the observed levels of sediment metals are not related to a specific location. This observation shows that there is a high homogeneity in the anthropogenic characteristics which confirm high diffuse (non-point) pollution in the river systems of Ogun and Ona sub-basins.
3.3. Pollution Load and Accumulation Factor Pattern
Figure 5 is the computed Pollution Load Index (PLI) of