Water quality is a major issue in
South Africa, where efforts to expand clean water supplies to the whole
population in the post-Apartheid era have faced severe challenges due to a
limited supply of potable water combined with a large, fast growing and
diffusely distributed population. One of the major obstacles to this objective
has been widespread eutrophication of reservoirs, largely as a result of
agricultural runoff. Eutrophication of water occurs when high levels of
nutrients, such as nitrogen and phosphorus, in the water support growth of
algae and other organisms which can prove detrimental to the ecosystem and the
health of anybody drinking the water.
Ideally reservoir water should be
oligotrophic prior to treatment (i.e. have very low levels of nutrients), but
only 3% of South African surface waters are thought to fall into this category by the National Eutrophication Monitoring Programme of the Department of Water Affairs, while 37% are deemed to be mesotrophic (having intermediate levels of
nutrients), 33% are eutrophic (having high levels of nutrients) and 28% are
hypertrophic (having very high levels of nutrients). Waters in the latter two
categories are prone to Algal Blooms, and in particular growths of
Cyanobacteria (filament-forming photosynthetic Bacteria) which produce toxins
harmful to other organisms, and Fish kills and deaths of Wildlife and Domestic
Animals due to Cyanobacterial toxins are a common occurrence in South Africa.
Water quality in South African
reservoirs is monitored by the National Eutrophication Monitoring Programme,
however limited resources combined with a very large number of small reservoirs
scattered over a very wide area make direct sampling of water a challenging
task, and ways of supplementing this monitoring in order to better prioritise
resources are actively being sought.
Hartbeespoort Dam in North West Province is notorious for high levels of eutrophication and frequent Cyanobacterial blooms. Igmar Grewar/African Lens.
In a paper published in the South African Journal of Science on 27 May 2015, Mark Matthews of CyanoLakes (Pty) Ltd. and the Department of Oceanography at the University of Cape Town and Stewart
Bernard of the Department of Oceanography at the University of Cape Town and
Earth Systems Earth Observation at the Council for Scientific and Industrial Research describe the results of an analysis of ten years of data collected by
the European Space Agency's Medium Resolution Imaging Spectrometer (MERIS) satellite,
which collected data between 2002 and 2012.
All molecules absorb energy in
the form of electromagnetic radiation (light) across a broad spectrum, but can
only store so much energy before it is re-emitted. Once this energy limit is
exceeded the molecule must re-emit the energy, but does this at specific
wavelengths corresponding to the chemical bonds present in the molecule. This
means that every molecule has a distinctive electromagnetic spectrum, which can
be used to detect specific molecules on Earth from orbiting satellites, or on
other planets from telescopes on Earth.
Matthews and Bernard developed an
algorithm for determining the difference between oligotrophic, mesotrophic,
eutrophic and hypertrophic waters, as well as detecting differences between Cyanobacterial
and other Algal blooms and detecting Cyanobacterial surface scums, which are
considered to be a particular health hazard. This was applied to fifty of the
largest water bodies in South Africa (measured by surface area), excluding
waterways that were narrower than 600 m, highly seasonal in their extent or
strongly affected by tidal movements.
In order to test the validity of
this Matthews and Bernard looked for known instances of Cyanobacterial blooms
within the data; that is to say blooms that were recorded from ground analysis
that should also have appeared in the satellite data.
Blooms of the Cyanobacterium Ceratium hirundinella, were first
detected at Albert Falls Dam in October 2006, with clearer conditions
prevailing by January 2007. The satellite data was able to replicate this
perfectly, and revealed that an earlier bloom had occurred in the spring and
summer of 2004, which was not identified at the time.
A comparison between the spatial distribution and magnitude of chl-a
determined from in-situ and satellite measurements for Ceratium hirundinella blooms in Albert Falls Dam. MERIS scenes acquired
simultaneous to in-situ measurements are shown for (c) 13 October 2006 and (d)
22 January 2007. Matthews & Bernard (2015).
Cyanobacterial blooms were
discovered to be occurring in the winter at Midmar Dam in 2005. This was
surprising, as such blooms do not generally occur at temperatures of less than
20˚C, and has been linked to excess nitrogen in the water, generated by
overwintering waterfowl, which enabled the Cyanobacteria to thrive at lower
temperatures. Such winter blooms have subsequently been detected at a number of
other South African reservoirs. Mathews and Bernard were able to detect these
winter blooms at Midmar Dam using the MERIS data.
Chl-a maps for Midmar Dam showing two scenes acquired near or
simultaneous to measurements made by in 2005 illustrating winter Cyanobacteria
detection. The sample points in ground surveys are indicated at 1 and 2; the maximum
chl-a value measured was 92 mg/m3. The arrows indicate pixels
identified as cyanobacteria. Matthews & Bernard (2015).
Hartbeespoort Dam is noted for
its extensive surface blooms of the Cyanobacterium Microcystis aeruginosa, which leads to the formation of toxic
surface scums. These surface scums have previously been detected in Landsat
data, and Matthews and Bernard were also able to detect them in the MERIS data.
Surface scum maps of Hartbeespoort Dam from simultaneously acquired
MERIS and Landsat imagery. Dark-green pixels correspond to surface scum in the
MERIS imagery. Matthews & Bernard (2015).
Of the 50 bodies included in the
study, 36 were found to be hypertrophic, three eutrophic, four mesotrophic and
seven oligotrophic. All of these bodies suffered Cyanobacterial blooms, with
five determined to have extensive blooms (defined as blooms covering more than
30% of the surface of the water body), 18 had intermediate coverage (between
10% and 30% of the surface covered by blooms), 13 had little coverage (between
1% and 10% of the surface covered by blooms) and 14 had insignificant coverage
(less than 1% of the surface of the water body covered by the blooms). Twenty
six of the reservoirs also suffered Cyanobacterial surface scum formation,
though of these 23 never had scums which covered more than 1% of the surface of
the water body, two (Spitskop and Darlington Dams) occasionally produced scums
which exceeded 1% surface cover, but never 5%, while only Hartbeespoort Dam
produced scums which covered more than 10% of the surface area.
A small group of reservoirs were
found to be highly turbid (i.e. have very low clarity due to extensive organic
material suspended in the water), including Mthatha, Ncora, Erfenis,
Krugersdrift, Ntshingwayo and Allemanskraal Dams. These are likely to have been
highly eutrophic and prone to Cyanobacterial blooms, though the high level of
turbidity makes this hard to assess, and Matthews and Bernard recommend that
further investigations are carried out at these bodies.
Once these reservoirs were
excluded the most eutrophic bodies were Grassridge, Klipvoor and Bloemhof,
while the least eutrophic were Sterkfontein, Pongolapoort and Midmar. The
bodies with the highest levels of Cyannobacteria were Barberspan, Hartbeespoort
and Koppies, where the average coverage exceeded 45% of the surface area, while
Lake Chrissiesmeer, Spitskop and Vaal Dams all had average coverage close to
30%. Most of these bodies suffered the worst blooms in March and April – the
end of the summer season.
Over the course of the study Darlington,
Heyshope, Kalkfontein, Lubisi, Rustfontein, Vanderkloof and Xonxa appeared to
suffer from increasing eutrophication, while this fell at Bronkhorstspruit,
Kwena, Ncora, Roodekoppies, Vaalkop and Voëlvlei (though Matthews and Bernard
are cautious about interpreting two much from the limited data available). The
levels of Cyanobacterial blooms appeared to be increasing at Klipvoor and
Vaalkop Dams, but decreasing at Barberspan, Brandvlei, Darlington and Kuhlange
(Kosi Lake). Instances of Cyanobacterial scums appeared to be increasing at Lake
Chrissiesmeer, Loskop, Vaal and Roodekoppies Dams.
Finally all of the water bodies
were given a score from zero to nine, based upon their levels of
eutrophication, frequency of Cyanobacterial blooms and development of scums.
This revealed Hartbeespoort Dam to be the worst affected body, and the only one
which scored a nine on the scale used, with hypertrophic water, and frequent and
extensive Cyanobacterial blooms and scum events. The next worst reservoir was Spitskop
with a score of seven, which also suffered high levels of eutrophication,
frequent Cyanobacterial blooms and scum events. Four bodies, Darlington, Barberspan,
Koppies and Lake Chrissiesmeer, scored six on the scale, all of which show high
levels of eutrophication and frequent Cyanobacterial blooms. Two of these
bodies, Barberspan and Chrissiesmeer, are considered to be important resources
for wildlife, particularly Birds, and their poor condition is considered to be
a threat to South African biodiversity. Twenty five bodies scored four or five
on the scale, indicating eutrophic waters with frequent or occasional Cyanobacterial
blooms, in need of management to protect their water quality, and only twelve
achieved scores of two or less, indicative of oligotrophic or mesotrophic
waters and low levels of Cyanobacterial activity, though none of these were
completely free of Cyanobacteria, suggesting that all shoulf be the subject of
ongoing monitoring and management.
The MERIS satellite ceased
functioning in 2012, so further monitoring of water quality with this satellite
is not possible. However the Sentinel 3 satellite, due to be launched in 2015,
should provide equivalent data from 2016 until at least 2026, so the methods
developed with the MERIS data do have potential use for ongoing monitoring of
South African water resources. A number of other such missions are also in the
pipeline, some of which will provide higher resolution spectrographic data,
with the potential to expand the use of remote sensing to monitor environmental
conditions in Southern Africa.
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