Nutrient inflows and levels in Lake Muhazi, Rwanda
D. Usanzineza a *, I. Nhapi a, U.G. Wali a, J.J. Kashaigili b, N. Banadda c
a
WREM Project, Faculty of Applied Science, National University of Rwanda, Box 117 Butare, Rwanda
Faculty of Forestry and Nature Conservation, Sokoine University of Agriculture, Box 3003 Morogoro,
Tanzania
c
Uganda Industrial Research Institute, P.O. Box 7086, Kampala, Uganda
b
ABSTRACT
Lake Muhazi, in Rwanda, has experienced a dramatic decrease in fish production since the nineteeneighties, typified by low water transparencies and high turbidity levels. The purpose of this study was to
assess the water quality in Lake Muhazi and its tributary rivers, focusing on nutrients. Vertical and
horizontal distributions of nutrients in the Lake were assessed and the concentration of nutrients in the
tributary rivers was determined for the period July to September 2007. The parameters studied were
nitrogen, phosphorous, chlorophyll a, pH, temperature and transparency . Four sampling stations were
located within the Lake. The sampling was done fortnightly. The samples were collected at depths of 0.5
m, 2 m, 5 m, and 1 m from the bottom of the lake. Samples were taken using a Van Dorn Bottle water
sampler and were preserved and analyzed in the laboratory for TP, TN and chlorophyll-a using Standard
Methods. The temperature, transparency (Secchi disc), and pH were also measured. Samples were
preserved and stored in cooler boxes. The results revealed that the nutrient levels in the lake are higher
than those in the inflow rivers, indicating the possibility of having other sources of pollution than the
inflow rivers. The Lake total nitrogen was found to be 0.85±0.22 mg/L, total phosphorus 0.29 ±0.15
mg/L, chlorophyll-a 18.1±10.5 μg/L, and Secchi disc 0.76±0.07 m. The results of this study are higher
than those of previous studies. The majority of the measured parameters show that the lake is eutrophic,
thus calling for urgent intervention to remedy the situation. Measures recommended include improved
management of the catchment to reduce nutrient inflows into the Lake and the development of suitable
discharge standards for all lakeshore activities.
Keywords: Lake water quality, Lake Muhazi, land use , nutrient levels, nutrient distribution, trophic status
1. Introduction
The most common way in which humans affect aquatic ecosystems is through altering nutrient dynamics
(Boostma and Hecky, 1993). Most tropical African lakes are facing problems of rapid population growth
in the riparian communities, which normally discharge pollutants into the lakes. This has led to the rapid
deterioration of water quality in receiving lakes (Wandiga, 2003), and some lakes are experiencing a
decrease in fish production. The surface water bodies in Rwanda are facing problems such as declining
water levels (ADB, 2003) and infestation by water hyacinth and other aquatic weeds, which is a new
phenomenon (MINITERE, 2005). In particular, Lake Muhazi has experienced a dramatic decrease in fish
production since the nineteen eighties, and this may have been caused by bad fishing practices (e.g. use of
small sized mesh nets, strike and poison fishing) (Mukankomeje et al., 1993). Sources of pollution
include tourism development which is increasing around the Lake Muhazi, washing activities in tributary
rivers of the lake and around the lakeshore, irrigation practice around the Kanyonyomba River (a tributary
of Lake Muhazi), contaminated runoff from a disused mining site at Musha on the banks of Lake Muhazi,
and burning of grass for cultivation around the lake. Erosion problems in the lake catchment are
exacerbated by poor land cover and unsustainable land use practices.
White and Downes (1977) argued that nutrient inflows into lakes promote eutrophication, so control of
eutrophication usually means control of nutrient additions. In order to control eutrophication, it is
*
Corresponding author: Email address. usanzineza@yahoo.fr (D. Usanzineza), Tel. +25008454185
2
essential to conduct quantitative assessment of the important nutrient sources and sinks within the system,
so that the effects of reducing a particular input may be assessed. Worldwide, various efforts have been
tried to measure the trophic condition of water bodies. Some of these include Fish (1975) in New Zealand
who produced a nutrient budget for Lake Rotorua, and the Ecology Division (1972) which took a
complex modelling approach to assessing lake status also in New Zealand. While acknowledging the
benefits of modelling for assessing nutrients in lakes, assembling data on nutrient loads is both tedious
and expensive, and in the absence of resources, rapid assessment may provide a useful basis for
developing a management plan for the lake and its catchment.
This study is based on a preliminary assessment of nutrient levels in Lake Muhazi as there are no prior
studies that could allow a more detailed assessment of the Lake. The purpose of this study was to
investigate the nutrient inflows and status of Lake Muhazi by assessing vertical and horizontal
distribution of nutrients in the Lake, and nutrient concentrations in the inflow rivers. This study focused
only on the water column because nutrient concentration within the water column is important as it is
from here that nutrients are taken up by phytoplankton which may then form blooms if excess nutrients
are present. There was no equipment for collecting lake sediments.
2. Materials and methods
2.1 Study area
Lake Muhazi is situated in the Eastern Province of Rwanda along the northern margin of the Rwamagana
District. The location of the Lake is shown in Fig 1. With an altitude of 1,443 m, Lake Muhazi has a total
catchment area of 829 km2, a surface area of 34.1 km2, depth of 14 m (max) and 10 m (average) and a
volume of 330 x 106 m3. The maximum length of this lake is approximately 37 km with a mean width of
0.6 km (Ministry of Infrastructure, 2007). Lake Muhazi currently has an earth dam at its discharge point
into the Nyabugogo River which was constructed in 1999 in an attempt to protect the Lake from drying
up.
Figure 1. Location of Lake Muhazi in Rwanda.
2.2 Sampling sites, sample collection and analysis
The sampling study was conducted from July to September 2007. Samples were collected approximately
every two weeks at four sites in Lake Muhazi, at fourteen sites on tributary streams, and at one site on an
outflow river of Lake Muhazi (Nyabugogo River) as shown on Fig 2. A GPS was used to identify the
3
sampling sites. At each site in the lake, water samples were collected at depths of 0.5m, 2m, 5m from the
water surface, and at 1m from the bottom of the lake.
Lake Muhazi
N
Legend
: Samplingsite on Rivers
R14
R14
R15
R15
R15
R12
R12
R12
R13
R13
L4
L4
Dam
Dam
R4
R4
R11 R10
R10
R11
R11 R10
R4
R9
R9
R9
R3
R3
R3
R7
R7 R7
R2
R2
LL33
LakeMuhazi
R1
L1
L1
L2
L2
R6
R6
R6
R8
R8
R8
R1
R1
R1 : Ntaruka
R2 : Gashogoshogo
R3 : Nyakambu
R4 : Nyamarebe
R5 : Gahurura
R6 : Ingarani
R7 : Kanyonyomba
R8 : Kiruhura
R9 : Njume
R10: Buganya
R11: Nyagatugu
R12: Murama
R13: Isereka
R14: Mwange
R15: Nyabuogo
: Samplingsite in Lake
R5
R5
R5
L1: Kavumu
L2: Nyarubuye
L3: Kibilizi
L4: Rwesero
Figure 2. The Lake Muhazi catchment and the location of sampling sites inside the Lake and on tributary
rivers for points monitored July-Sept’07.
The parameters measured were pH, temperature, Secchi disc depth, chlorophyll-a, total nitrogen (TN) and
total phosphorus (TP). A survey of land use activities around the lake was also conducted. Samples were
collected using a Van Dorn sampling bottle. The collected samples were stored in 560 ml plastic bottles
and placed on ice in cooler boxes. The samples were carefully preserved and analysed according to
Standard Methods (APPHA/AWWA/WEF, 2005). The TN and TP samples were unfiltered and digested
with alkaline per-sulphate solution, whilst algae was filtered and extracted with ethanol. Secchi disc
depths were determined in the field using a 20 cm diameter Secchi disc. The temperature and the pH were
also measured in the field using HACH field testing kits.
2.3 Data analysis
Descriptive statistics were used to analyze data in terms of mean, median and standard deviation using
Microsoft Excel and SPSS software. The median was used to express the difference between data sets as
the median is less sensitive to outliers (extreme scores) than the mean and thus a better measure than the
mean for skewed distributions (Helsel and Hirsch, 2002). The mean was used for the comparison of data
with the water quality guideline as it is considered representative of the whole sample. Its value depends
equally on all of the data which may include outliers (Helsel and Hirsch, 2002). For the comparison of the
difference between means, a one-way analysis of variance test was used.
3. Results and discussion
3.1 Characteristics of tributary rivers of Lake Muhazi
The sampling of water from the tributary rivers was done four times during the period of July –
September 2007 and the TN and TP average results are shown on Fig 3.
4
Figure 3. Concentration of TN and TP in water of inflow rivers, July-Sept’07.
The concentrations of TP in the tributary rivers of Lake Muhazi ranged from 0.02 mg/L to 0.35 mg/L
with the highest value at point R15 (Nyabugogo River). Point R15 is beyond the Lake and in an area
where sugar cane cultivation is predominant. Point R1 also had high TP levels and this is attributed to the
polluted runoff from Kayonza town. The concentration of TN ranged from 0.08 mg/L to 0.91 mg/L. Point
R5 (Gahurura River) had the highest concentration of TN. This is probably due to its location in a large
wetland which is exploited for rice cultivation. Similarly, Point R7 (Kanyonyomba River) had 0.43 mg/L
concentration of TN and is also under rice cultivation.
3.2 Temperature and pH profiles of the water column
The temperature profiles of Lake Muhazi at different sampling sites are shown in Fig 4.
21
22
Temp, oC
23
24
25
26
20
27
22
Temp, oC
23
24
25
26
27
20
0
2
4
1st sampling
2nd sampling
3rd sampling
6
8
10
12
Depth from water surface, m
0
Depth from water surface, m
21
2
4
1st sampling
2nd sampling
3rd sampling
6
8
10
22
Temp, oC
23
24
25
26
27
2
4
1st sampling
2nd sampling
3rd sampling
6
8
10
12
12
(a) Site L1
21
0
Depth from water surface, m
20
(b) Site L2
(c) Site L3
Figure 4. Temperature profiles at the 3 stations monitored in L. Muhazi, July-Sept’07
The data collected shows a difference in temperature of approximately 2°C between the surface and the
bottom water, except for the temperature profile measured on the second sampling date where the
difference was about 4°C at L1. In general, the water temperature decreases from the surface towards the
bottom.
The pH of the waters of Lake Muhazi is slightly alkaline (6.2 – 8.5) and did not fluctuate much as is
shown in Fig 5. The mean pH of the lake was 7.8. At each sampling site, the pH decreased with the depth
as shown in Fig X. The pH at the bottom was lower by 1 to 2 units compared with that of the surface. The
pH was higher at the lake surface where high levels of the phytoplankton were observed. This
phenomenon occurs mainly in mid-June and at the end of August, and is related to the assimilation of
CO2 dissolved by the phytoplankton in water. The pH of the lake was higher as compared to those found
in river. The average pH in the rivers varied between 6.1 and 7.1, and the average pH in the lake was 7.8.
5
pH
7
6
8
5
9
1st sampling
2nd sampling
3rd sampling
Depth from water surface, m
Depth from water surface, m
4
pH
7
8
5
9
6
8
10
12
1st sampling
2nd sampling
3rd sampling
2
4
6
8
10
2
4
8
9
1st sampling
2nd sampling
3rd sampling
6
8
10
12
12
(a) Site L1
pH
7
6
0
0
0
2
6
Depth from water surface, m
5
(c) Site L3
(b) Site L2
Figure 5. pH profiles at the 3 stations monitored in L. Muhazi, July-Sept’08.
3.3 Chlorophyll-a and transparency
The chlorophyll-a concentration at various depths were also analyzed. The descriptive statistics of
chlorophyll a concentration at various depths are presented in Table 1. Fig 6 shows the vertical and
horizontal distribution of Chlorophyll-a in the lake. The average of the measurements taken is 18.1 µg/L
(± standard deviation of 10.5 µg/L). It was observed that the chlorophyll-a concentration was high at 0.5
m depth, and the chlorophyll-a concentration increased toward the western part of the lake.
The descriptive statistics of chlorophyll a concentration at various depths are presented in Table 4.3. The
general average of the measurements taken is 18.1 µg/L (standard deviation equal to 10.5).
Table 1. Descriptive statistics of chlorophyll-a in Lake Muhazi.
Parameter
Number of
samples; N
21
Chlorophyll-a
(µg/L)
Valid N (listwise)
Minimum
Maximum
Range
Mean
1.7
37.1
35.4
18.1
21
30
10
22
Mean concentration of Chl a (µg/L)
20
21
20
19
18
17
16
0
15
0.5 m
(a)
Std.
Deviation
10.5
2m
Depth
5m
L1
(b)
L2
L3
L4
Lake sampling sites
Figure 6. Average chlorophyll-a concentration in L. Muhazi, July-Sept’07 (a) Mean concentrations at
various depths, and (b) Horizontal distribution.
6
Previous studies noted that the maximum concentration of chlorophyll-a, occurred between 1 m and 2 m
in depth (Plisnier, 1989; Mukankomeje et al., 1993). This is explained by an optimum in quality
(frequency) and quantity (lux) of the light for the phytoplankton. The average Secchi disc transparency
results for the three sampling runs done during this study were 0.87 m at L1, 0.83 m at L2 and 0.77 m at
L3 (Fig 7).
Figure 7. Variation of transparency in Lake Muhazi.
Fig 7 shows that the transparency at L1 was nearly always higher by 0.10 m compared to that measured at
L3. In 1986 and 1987 at Karambi, not far from L1 on the eastern part of the Lake Muhazi, the average of
monthly measurements was 0.81 m. The transparency at Karambi was also nearly always higher by 0.10
m than that measured at Giheta, not far from L3 on the western side of the lake in 1986 and 1987
(Plisnier, 1989). This was the same case during this research. In this lake, the change of the transparency
is explained by the change in the phytoplankton levels which are lower when the transparency is high
(Plisnier, 1989). It is also important to note that the transparency seems to have slightly increased since
the study of Mukankomeje (1993). Mukankomeje (1987) found an average transparency of 0.65 m
compared to 0.76±0.07 m from the current study. Perhaps this corresponds to a decrease in the content of
sediments coming from erosion since the enactment of the Organic Law of 2005 determining the
modalities of protection, conservation and promotion of the environment in Rwanda. The building of the
dam in 1999 at the outlet of the lake has also increased the lake level thereby diluting the concentration of
suspended material in the lake and also proving a longer hydraulic retention time for the sediments to
settle down at the lake bottom.
3.4 Nutrients profiles and their distribution in Lake Muhazi
The nitrogen and phosphorus profiles in the Lake are shown in Figs 8 and 9. The nutrient levels in Lake
Muhazi ranged from 0.47 to 4.78 mg/L for TN and from 0.08 to 1.02 mg/L for TP. The average TN levels
of 0.26 mg/L while TP levels of 0.09 mg/L in inflows rivers seem to be low compared by those found in
the lake TN (0.85±0.22 mg/L) and TP (0.29±0.15 mg/L) . The results show that nutrient concentrations
are above the recommended concentrations of 0.3 mg/L TN and 0.01 mg/L TP for oligotrophic systems
(Mandaville, 2000). Assuming an algal cell composition of C106H180O45N16P (Lee and Jones, 1986), a
stoichiometric N:P ratio of 1:7 can be derived. The average N:P ratio in Lake Muhazi is 1:3, suggesting
nitrogen is the limiting nutrient. However, it will be misleading to make firm conclusions based on this
ratio alone as both nutrients are present in abundance in the lake. Other factors in the pelagic environment
like zooplankton grazing, light or micro-nutrients could be the limiting factor for algae or aquatic plant
growth in the lake. The abundance of P in the lake could also explain why the bulk of it is not contained
in algae as would be normally expected for a productive lake. Lake Muhazi is now eutrophic according to
the OECD Fixed Boundary System or Diagnostic Model (OECD, 1982) (TP  100 mg/m3; mean
chlorophyll-a  25 mg/m3; mean Secchi disc depth  1.5 m).
7
TN, mg/L
0.4
0.9
TN, mg/L
1.4
1.9
0.4
TN, mg/L
1.4
0.4
1.9
4
6
8
10
12
1st sampling
2nd sampling
3rd sampling
2
4
6
8
10
12
(a) Site L1
0.9
1.4
1.9
0
Depth from water surface, m
1st sampling
2nd sampling
3rd sampling
2
Depth from water surface, m
Depth from water surface, m
0.9
0
0
2
4
6
8
1st sampling
2nd sampling
3rd sampling
10
12
(b) Site L2
(b) Site L3
Figure 8: Vertical profile of TN at the 3 Lake sampling sites monitored July-Sept’08
0.1
TP, mg/L
0.3
0.4
0.2
0.5
0.6
0.1
0.2
TP, mg/L
0.3
0.4
0.5
0.6
0.1
0
4
1st sampling
2nd sampling
3rd sampling
6
8
10
2
4
1st sampling
2nd sampling
3rd sampling
6
8
10
TP, mg/L
0.3
0.4
0.5
0.6
2
4
1st sampling
2nd sampling
3rd sampling
6
8
10
12
12
12
0.2
0
Depth from water surface, m
2
Depth from water surface, m
Depth from water surface, m
0
(c) Site L3
(b) Site L2
(a) Site L1
Figure 9: Vertical profile of TP at the 3 Lake sampling sites monitored July-Sept’08
3.5 Relation between Secchi disc, Chlorophyll-a and Nutrients
Most eutrophication models are based on empirical relationships between abiotic variables. Therefore, a
series of regressions were performed considering abiotic variables commonly used in eutrophication
studies. The TP and TN were used as independent variables. Both TN and TP did not show a significant
and linear relationship with chlorophyll-a as was expected (Figure 10). The coefficient R2 for this
regression was 0.0876 for Chlorophyll-a versus TN, and 0.0071 for Chlorophyll-a versus TP. The
regressions analysis were also performed between TP, TN and the Secchi disc measurements and results
showed that both TN and TP had no significant and linear relationship with the Secchi disc measurement.
The coefficient R2 for these regressions were, respectively, 0.1959 for Secchi disc versus TN, and 0.1104
for Secchi disc versus TP. Thus, this set of regressions could not confirm that TP and TN could be good
descriptors of the trophic status of Lake Muhazi.
y = -0.0515x + 58.749
R2 = 0.0876
40
35
35
30
30
Chl a (µg/L)
Chl a (µg/L)
40
25
20
15
25
20
15
10
10
5
5
0
y = 0.0076x + 15.213
R2 = 0.0071
0
0
200
400
600
800
1000
1200
0
TN (µg/L)
(a)
100
200
300
400
500
600
700
TP (µg/L)
(b)
Figure 10: Linear regression between mean concentrations of (a) TN and (b) TP and mean
concentrations of chlorophyll-a for L. Muhazi, July to Sept’07
8
90
86
y = -0.039x + 112.03
R2 = 0.1959
84
Secchi (cm)
85
Secchi (cm)
y = 0.0125x + 75.282
R2 = 0.1104
88
80
75
82
80
78
76
74
70
72
65
600
70
650
700
750
(a)
800
850
900
950
TN (µg/L)
1000
0
(b)
100
200
300
400
500
600
700
TP (µg/L)
Figure 11: Linear regression between mean concentrations of (a) TN and (b) TP and mean Secchi disc
measurements for L. Muhazi, July to Sept’07
This study could only show the situation in Lake Muhazi in as far as nutrients in the water column are
concerned. It would have been ideal to have major inflows gauged so that the response of the Lake to
nutrient loadings could be established. This would also required a year-round monitoring study which was
not possible with the resources available. Nutrient levels in the sediments would also be interesting to
monitor as they could give the extent to which the lake is already affected.
4. Conclusions and recommendations
4.1 Conclusions
From the results of this study, the following conclusions were drawn:
1) The horizontal and vertical nutrient profiles of Lake Muhazi show a lot of variability, making it
difficult to rely on the observed nutrient concentration profiles to understand the nutrient
dynamics in Lake Muhazi. Overall, the TN concentration averaged 0.85±0.22 mg/L, and TP
averaged 0.29±0.15 mg/L, Secchi disc averaged 0.76±0.07 m, and chlorophyll-a averaged
18.1±10.5 µg/L. The lake is now eutrophic.
2) The levels of nutrients in the inflow rivers of Lake Muhazi were considered generally low and
always below 1 mg/L for both TN and TP. This could be due to the buffering capacity of the
wetlands around each inflow river.
4.2 Recommendations
From the results and discussions in this report, the following recommendations were derived:
1) It is crucial and urgent to identify all controllable sources of pollution (e.g., poor soil and land
management in agriculture, domestic sewage disposal practices, etc) throughout the watershed of
Lake Muhazi and use this information to develop appropriate pollution reduction measures.
2) Immediate action could be taken to reduce major pollution sources such as improving wastewater
disposal systems, the use of phosphorus detergents in the lake and its catchment, and
rehabilitation of disused mining sites.
3) Long-term water quality monitoring and river flow gauging is required for at least a year to cover
seasonal fluctuations.
4) In future studies, it is necessary to measure dissolved oxygen profiles so as to better understand
nutrient transformations in the lake.
5) An investigation on the sudden increase in nutrients towards the lake outlet is needed.
6) An estimation of nutrient input from other sources (communities and industries around the lake)
or from atmospheric deposition would be also interesting so that a comparison with the input
from rivers could be done.
Acknowledgements
9
This research was generously supported by funding from the Water Resource and Environmental
Management Project in the Faculty of Applied Science and analytical work was conducted at the Faculty
of Science Laboratory, National University of Rwanda.
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