PRELIMINARY WATER, SALT, AND NUTRIENT BUDGETS

FOR LAGOS LAGOON, NIGERIA

By , C. E. Isebor¹, L. Awosika¹ and S. V. Smith²

¹Nigerian Institute for Oceanography and Marine Research,
P.M.B 12729, Victoria Island, Lagos, Nigeria.

²University of Hawaii,1000 Pope Road, Honolulu, Hawaii 96822, USA

STUDY AREA DESCRIPTION

Lagos Lagoon, covering 700 km², is a brackish coastal lagoon, on the Western part of Nigeria (6^o 26' - 37'N; 3^o 23' - 4^o 20'E) and the largest along the West African coast. The lagoon is separated from the ocean by a narrow strip of barrier bar complex and opens into the sea through the Commodore channel. The lagoon is drained by four main rivers: Ogun, Agboyi, Majidun and Aye. The lagoon is shallow, with an average depth of about 1.5 m Shoals of sand are scattered in the lagoon and are usually exposed during low tides. Many small islands occur within the Lagos lagoon.

The population of the city of Lagos is about 5 million people, with many industries and untreated sewage dumped directly into the Lagos lagoon. The Lagos lagoon was initially used for fishing in the early century but increasing population and establishment of industries most of which are located in the Lagos metropolis, the lagoon became a major waterway for commerce. Due to this seasonal distribution of rainfall the lagoon system, the excessive flooding introduces a lot of detritus and nutrients from the adjoining mangrove swamps and land. The environmental pollutants such as the discharge of raw sewage or primary treated sewage into the lagoon are on the increase. Other sources of pollution are contamination from sawmills, heavy metal load coupled with contaminants from domestic and industrial solid waste.

Nutrient level are significantly higher in wet season than in dry season, there is an inverse relationship between nutrient levels and salinity, nutrient levels drop with increase in salinity. The vegetation around the lagoon is basically fringed by the red mangrove; Rhizophora racemosa, Rhizophora mangle, Rhizophora harrisonii and the grass ; Paspalum veginatum, water hyacinth in the dry season; Eichornia crassipes. The fauna is composed of fresh, marine and brackish water species depending on the season. Among the fauna exploited for commercial purpose are; prawns, shrimps, crabs, oysters, pelagic and demersal fishes.

WATER AND SALT BUDGETS

Being open to the sea all year round, the brackish environment is therefore a consequence of the influence of tidal sea water incursion and freshwater discharge from the adjoining creeks and rivers. Tides in the Lagos lagoon derives its energy from the ocean and are semi-diurnal in nature with two unequal amplitude.

The water and salt budgets describe the exchange of water between the Lagos lagoon and the open ocean in the Gulf of Guinea by process of advection and mixing. The concept behind the budgets is to establish fresh water inflows (such as runoff, precipitation, ground water, sewage) and evaporative loss of fresh water. There must be a compensating outflow (or inflow) to balance the water volume in the system. Salt must be conserved in the system, hence salt fluxes not accounted for by the salinity used to describe the fresh water flows must be balanced by mixing (Gordon et al., 1996). There is a distinct wet and dry season for this system (each occupying about half the year), but available runoff data cannot be resolved into wet season and dry season data. Tables 1 and 2 contain the data used to constrain the freshwater and salinity budgets.

Table 1: Lagos Lagoon Freshwater Budget inputs.

Table 2. Salinity of the Lagos Lagoon and the adjacent Ocean.

The water balance for each season is calculated using equation (1) from Gordon et al. (1996):

dV₁ /dt =V_Q + V_P + V_G + V_O +V_E +V_R (1)

assuming steady state (i.e dV₁ /dt = 0), then the residual flow (V_R) is:

V_R = -V_Q - V_P - V_G -V_O - V_E (2)

substituting terms in Eq. 2 with data in table 1, V_R can be obtained for the wet and dry seasons.

Wet Season: V_R = (- 9 - 4 - 1 - 0 + 4) x 10⁶ m³ d^-1 = + 10 x 10⁶ m³ d^-1; and

Dry Season: V_R = (-9 -3 -1 -0 + 4) x 10⁶ m³ d^-1 = + 9 x 10⁶ m³ d^-1.

The salt balance is calculated from Eq. 3, in order to balance salt input via mixing with salt output from residual outflow. It is assumed that the salinity of outflowing water (S_R) is the average of lagoon and oceanic salinity.

dV₁S₁/dt = V_QS_Q + V_PS_P + V_GS_G + V_OS_O + V_ES_E + V_RS_R + V_X (S₂ - S₁) (3)

Where or V_X represents the mixing volume exchanged volume between the ocean and the lagoon. As the salinity of freshwater inflow terms can be assumed as 0, then Eq. 3 can be simplified to:

dV₁S₁/dt = V_RS_R + V_X(S₂-S₁) (4)

Assuming that S₁ remains constant through time (i.e) assuming steady state

0 = + V_RS_R + V_X(S₂ - S₁) (5)

By re-arrangement:

V_X = -V_RS_R/(S₂ - S₁) (6)

Substituting terms in Eq. 6 with salinity data in table 2 for wet and dry season is obtained.

Wet Season: V_X = - [(-10 x 10⁶)(21.5)]/(29 - 14) = -14 x 10⁶ m³ d^-1; and

Dry Season: V_X = - [(-9 x 10⁶)(27)]/(33 - 21) = -20 x 10⁶ m³ d^-1.

The water exchange (t ) in Lagos Lagoon for wet and dry season can be calculated from Eq. 7, where |V_R| is the absolute value of V_R:

t = V_system / (V_x + |V _R|) (7)

where V_system is the total volume of the system (1,050 x10⁶ m³):

Wet Season: t = (1,050 x 10⁶ m³)/(14 + 10) x 10⁶ m³ d^-1 = 44 days.

Dry Season: t = (1,050 x 10⁶ m³)/(20 + 9) x 10⁶ m³ d^-1 = 36 days.

We doubt that this difference in water exchange time between the wet and dry seasons is significant, but this wet-dry comparison gives some sense of the sensitivity of the calculations. Because V_Q is treated as constant, the main terms affecting water exchange calculations are the lagoon and ocean salinity estimates. Figure1 summarizes the average water and salt budgets for this system and gives the water exchange time based on the average data to be 36 days.

Figure 1. Average annual water and salt budgets for the Lagos Lagoon. Green arrows are known; red arrows and figures are calculated.

BUDGETS OF NONCONSERVATIVE MATERIALS

This system poses a challenge for estimating fluxes of nutrients, because the river and groundwater nutrient concentrations are not known and because there are no direct estimates of nutrient loading associated with waste discharge into the system. Nevertheless it is possible to make useful estimates of the nonconservative nutrient budgets for this system. Some assumptions are made for the sake of these calculations. Although the area immediately adjacent to the lagoon is heavily impacted by human activity, it is assumed that the nutrient composition of river flow above the city of Lagos is relatively unimpacted by human activity.

From Meybeck (1987) and Meybeck et al. (1989), the dissolved inorganic N (probably dominantly NO₃) and dissolved inorganic P concentrations of river flow are assumed to be within about twice typical "background river concentrations", or about 8 and 0.1 mmol m^-3, respectively. Multiplying these concentrations by river flow (V_Q) of 9 x 10⁶ m³ d^-1, we obtain dissolved inorganic N and P loading rates of about 70,000 mol N per day and 900 mol P per day. These figures are not likely to be accurate to better than a factor of two. We assume that groundwater inputs are contained within the uncertainty of these fluxes.

From a summary of literature data, we estimate that per capita domestic sewage production accounts for about 0.9 mol N per person per day and about 0.07 mol P per person per day. Of this production, about 60% of the N and 35% of the P in the waste load is assumed to be inorganic: about 0.5 mol inorganic N and 0.02 mol P per person per day. Most of the population of 5 million persons discharges their waste fairly directly into Lagos lagoon, so about 2.5 x 10⁶ mol inorganic N and 0.1 x 10⁶ mol inorganic P per day are estimated to enter this system as domestic waste loads. These estimates are likely to be low, because they do not account for industrial loads. Clearly the waste load overwhelmingly dominates over the river load. We have no estimates of atmospheric fallout but also assume this input to be contained in the uncertainties of these estimates. We combine the two to suggest that the terrestrial load of inorganic N is about 3 x 10⁶ mol per day, and the inorganic P load is about 0.1 x 10⁶ mol per day.

We can now use the following equation from Gordon et al. (1996) to estimate the nonconservative flux (DY) for any material, Y:

dV₁Y₁/dt = V_QY_Q + V_PY_P + V_GY_G + V_OY_O + V_EY_E + V_RY_R + V_X (Y₂ - Y₁) + DY (8)

There are data on nutrient concentrations in the lagoon (we use the annual average data; Figure 2), so we can estimate the hydrographic fluxes and crude estimates of the nonconservative nutrient fluxes for this system: From this figure, it can be seen that, despite the elevated nutrient concentrations in the lagoon, relatively little of the nutrient loading to this system escapes to the open coast; the system is effectively a trap for most of the terrestrially derived nutrients. DDIP is estimated to be -0.1 x 10⁶ mol d^-1, and DDIN is estimated to be -3 x 10⁶ mol d^-1.

Figure 2. Dissolved inorganic P and N budgets for the Lagos Lagoon.

The P and N budgets can be used for calculations of primary production minus respiration (p-r) and nitrogen fixation minus denitrification (nfix-denit) according to the procedures outlined in Gordon et al. (1996).

If we assume that all of the DDIP is accounted for by (p-r), and that this net metabolism is dominantly by plankton with a C:P ratio of 106:1, then (p-r) = -106 x DDIP = 11 x 10⁶ mol d^-1. On an annual cycle and averaged over the lagoon area of 700 km², this is equivalent to a net production rate of about 6 mol C m^-2 yr^-1. If the terrestrial discharge of DIP into this system is underestimated, then DDIP would be more negative than we have estimated and (p-r) would be higher. If mangroves (with a much higher C:P ratio) dominate the net production of this system, then (p-r) would be higher than this estimate. Because the mangroves only fringe the system, we assume the production to be plankton-dominated. Unfortunately, we do not have an estimate of primary production for comparison to this net production; however the system appears to be a net producer of organic matter.

(nfix-denit) is estimated as the difference between observed and expected DDIN, where the expected DDIN is estimated from the plankton N:P ratio of 16:1. Thus, (nfix-denit) = -3 x 10⁶ -16 x (-0.1 x 10⁶) mol d^-1 = -1.4 x 10⁶ mol d^-1. Averaged over an annual cycle and the entire lagoon area, this is 0.7 mol m^-2 yr^-1. In comparison with other estimates of nearshore denitrification, this is a very reasonable estimate. It is thus quite feasible that this system denitrifies all of the waste nitrogen entering the system.

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Last Updated 21 May 2006 by FW