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Eduvest
� Journal of Universal Studies Volume 2 Number 11, November, 2022 p- ISSN 2775-3735 - e-ISSN 2775-3727 |
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WATER QUALITY OF LAKE TOBA BY SPACE AND TIME BASED ON
ENVIRONMENTAL PHYSICS, CHEMICAL FACTORS AND COMMUNITY PHYTOPLANKTON |
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1Ika Rosenta
Purba, 2Nurhayati 1Departemen of Biology
Education, Faculty of Teacher Training and Education, Universitas Simalungun
Pematang Siantar,
Indonesia 2Universitas Islam
Sumatera Utara (UISU) Medan Indonesia |
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ABSTRACT |
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The characteristics of lake waters, like waters in
general, have specific characteristics such as common property, various sectors
and multiple policies, as well as various administrative areas. This research has been
carried out in the waters of Lake Toba based on space and time for 6 months
with 2 seasons. The details of the research area are divided into four parts,
namely control, wharf, agriculture and marine cages. This research was
conducted based on the activities of the local community in the waters of
Lake Toba. Community activities include agriculture, fisheries with the KJA
system, docks and control in the form of the Binangalom
waterfall. Based on data on the diversity and abundance of phytoplankton, the
quality of the waters of Lake Toba is still in the good category, in this
case the diversity index (H') > 3. The phytoplankton found in the waters
of Lake Toba are 36 species belonging to 23 families, 15 orders, 5 classes
and 3 phyla |
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KEYWORDS |
lake toba; community phytoplankton; environmental physics |
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This work is licensed under a Creative
Commons Attribution-ShareAlike 4.0 International |
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INTRODUCTION
The
characteristics of lake waters, like waters in general, have specific
characteristics such as common property, various sectors and multiple policies,
as well as various administrative areas. The different characteristics
possessed by lake waters are the cause of sensitivity from human activities
that provide a burden in the form of nutrient and mineral input, which is
related to the type of water body and the highly variable germplasm community (Hidayat Lukman et al.,
2017).
The social
benefits that can be provided from the existence of lakes can be optimally
received if lake management policies are interrelated, comply with regulations
that contribute to the potential of lakes for the benefit of the community, and
balance the contributions of attention and values that can be provided (Klessig,
2001). The values
in question are the values of beauty, economy, education, culture, individual
freedom, and spirituality in the lake environment.
Lake Toba is an inland waters that plays a role in every sector, including
the role of local communities and national roles, maybe even international.
Based on national policies, the Lake Toba area is used as one of the Master
Plans for National Tourism Development 2020-2024 (Strategic Plan of the
Ministry of Tourism and Creative Economy, 2020) because it has great potential.
The great
potential of the waters of Lake Toba, one of which is the presence of water
flowing through the inlet which has been utilized for the Sigura-gura
Hydroelectric Power Plant (PLTA), which has a large capacity of up to 286 Megawatts
(MW), compared to the Maninjau PLTA which is only 68
MW, and has operating since 1982 (Kompas, 22 September 2005).
Aquaculture is a
potential that has also developed in the waters of Lake Toba through the
floating net cage system (KJA). This system was first implemented in 1988
(Dharma, 1988). The results of aquaculture from this KJA system in 2010 were
recorded at 28,132.01 tons with 13,160 KJA (Ministry of Marine Affairs and
Fisheries of the Republic of Indonesia, April 2021).
The existence of
conflicting needs between the needs of the community in the form of
socio-economic, production achievement, environmental conservation and the
carrying capacity of the waters makes this KJA activity reap a lot of
controversy. (I. Ridwansyah Lukman,
2010) explains that the development of
the KJA system will be beneficial if the balance between ecological factors,
carrying capacity, and the interests of the surrounding community is carefully
considered.
In line with this,
the Ministry of Maritime Affairs and Fisheries of the Republic of Indonesia
through a coordination meeting on April 20, 2021, urges the Regional Government
(Pemda) to control the KJA around the Lake Toba area
by referring to Government Regulation (PP) Number 81 of 2014 concerning Spatial
Planning for the Lake Toba Region. and its surroundings for the preservation of
this volcanic lake from pollution. The uncontrolled growth of KJA results in a
decrease in water quality. (Maulana,
Wiranto, Kurniawan, Syamsu, & Mahmudin, 2018).
Deby (2013)
explains that the increasing number of KJA causes a high amount of feed that
enters the lake waters. This excessive feeding (over feeding) results in
organic waste or nutrients originating from the rest of the feed that is not
consumed, plus the entry of fish feces into the lake waters is increasing (Nontji,
Patenjengi, Rasyid, & Pirman, 2016);
(Maulana
et al., 2018); (Zulfiah
& Aisyah, 2016).
(Siagian,
2010)
stated
that the presence of organic waste from KJA activities will have an impact on
phosphate levels and the availability of dissolved oxygen which is a parameter
/ measure of the quality of the aquatic environment. The results of (Barus,
2004) proved
that in November 2004 the cause of mass death of carp in the Haranggaol waters of Lake Toba was the dissolved oxygen
(DO) value which decreased to the lowest level of 2.95 mg/l. This proves that
the availability of oxygen is very limited.
The value of 14
mg/l of Biochemical Oxygen Demand (BOD) gives an estimate of the high organic
matter in the water, which comes from the rest of the feed that is not consumed
by farmed fish, as well as nutrients such as nitrogen and phosphorus which
indicate an excess of the threshold that has been set. established (Barus,
2004).
Terangna et al. (2002)
described
that the location of the waters in the middle of the lake about 500 m from the
edge of the lake is oligotropic, this is because it
has a very low nutrient content, light penetration only reaches 11-14 m, and
oxygen levels at a depth of more than 200 m can still be detected. In addition,
the large amount of water hyacinth at the fish farming location detects the
presence of high levels of nutrients.
High levels of
nutrients, one of which also comes from the waste of agricultural fertilizers,
nitrogen from the atmosphere, phosphate from detergents, other nutrients from
soil erosion, and waste from domestic and industrial (�lvarez-V�zquez,
Bendicho, & Prego, 2014).
Concentration of nutrients is a source of energy that can affect water quality,
causing eutrophication.
Eutrophication is
a buildup or surge due to water pollution from excessive nutrients such as
phosphate (PO4) which threatens especially freshwater ecosystems. In recent
years, Lake Toba has experienced eutrophication with a surge in phosphate
nutrients (Fauziyah
& Wijopriono, 2010) and
changes in nutrient-rich water conditions (I.
Ridwansyah Lukman, 2010).
(Lehmusluoto,
Priadie, & Vauhkonen, 2006) proved
that one of the triggers for eutrophication in Lake Toba is estimated to come
from fish cultivation in KJA and domestic waste. The impact of this
eutrophication can affect the phytoplankton in the waters of Lake Toba.
Phytoplankton
which acts as a primary producer responds to the state of the waters so that it
has a direct impact on the phytoplankton. Thus, it can cause changes in
abundance, number of species, and community structure (Ferreira et al., 2011).
Because
phytoplankton are the lowest trophic level organisms, the presence of
phytoplankton is influenced by several factors, including nutrition, sunlight,
temperature, pH, and predation from zooplankton and the participation of
planktonic fish (Lau
& Lane, 2002);
(Yu,
Liu, Egolf, & Kitanovski, 2010);
(Jiang
et al., 2014).
Due to the ability
of phytoplankton to carry out photosynthesis, it causes these phytoplankton to
become the main energy source for ecosystem activities in the waters through
the food chain structure.
(Nontji
et al., 2016) describes
that the phytoplankton groups commonly found in tropical waters are diatoms
(Bacillariophyceae) and dinoflagellates (Dynophyceae).
The amount and type of excess phytoplankton can be used as an indicator or
measurement of fertility and water conditions (Karydis
& Tsirtsis, 1996);
(Thoha
& Amri, 2011);
(Radiarta,
2013).
As explained by (I.
Ridwansyah Lukman, 2010),
that
specific characteristics such as common property, multisectoral policies and
interests, as well as the existence of various administrative areas of lake
waters are influenced by human activities around the waters of Lake Toba. As a
result, it will change the ecological system of the waters of Lake Toba, where
this will have an impact on the diversity of organism life in the waters.
The diversity of
species can be used as a measure in determining water quality. A group of
species is said to have high diversity if it has many species with the number
of each species evenly distributed. If there are only a few species in the
community, where the number of individuals of each species is not evenly
distributed, it can be said that the community diversity is low. This can be
used as an indicator of the contamination of a water. The theoretical objective
of this study is to determine the water quality in the waters of Lake Toba
according to space and time based on the physical and chemical factors of the
environment and the community of phytoplankton.
Utilization of
Lake Toba in various activities of human life around it, such as fishery
cultivation in the form of marine cages, plant cultivation, tourism,
transportation, and areas where people live. As a result of these various
activities will produce organic or inorganic materials into the waters.
Eutrophication is
a symptom of increasing nutrients in aquatic ecosystems. This process results
in an increase in the primary productivity of the waters which stimulates the
growth of phytoplankton and other flora. Signs of eutrophication are through
algae blooms, reduced light penetration into the water, and reduced oxygen.
Uncontrolled eutrophication process will have an impact on water quality which
causes loss of value and function of the lake.
Like other lakes,
Lake Toba also has the potential to experience eutrophication, due to increased
human activities in the water catchment area (exagenous)
and in the lake waters (indogeneus) which are thought
to contribute a certain amount of phosphorus and nitrogen. Fish farming
activities can be a source of nitrogen and phosphorus waste, which comes from
fish feces, feed residues and other organic materials. The accumulation of
organic elements at the bottom of the lake becomes a source of decomposed
nitrogen and phosphorus.
The types of
living things that occupy the lowest trophic level in aquatic ecosystems are
phytoplankton. As a result of the ability of phytoplankton to photosynthesize,
making it a source of energy directly or indirectly needed for all aquatic
ecosystem life with stages in the food chain structure. Generally in tropical
waters, diatom (Bacillariophyceae) and dinoflagellate (Dynophyceae)
phytoplankton are found (Nontji
et al., 2016). Alleged fertility levels and
changing water conditions are factors in the presence of abundant phytoplankton
types and compositions in waters (Radiarta,
2013); (Thoha
& Amri, 2011);
(Karydis
& Tsirtsis, 1996).
So the
research will focus on: The water quality of Lake Toba according to space and
time based on environmental physicochemical factors and the phytoplankton
community. In accordance with the title, the formulation of the problem in this
study is:
1.
How is the water quality of Lake Toba
according to time and space based on the physical-chemical factors of the
water?
2.
How is the water quality of Lake Toba
according to time and space based on the phytoplankton community?
3.
How is the relationship between the
physical and chemical factors of the waters of Lake Toba and its phytoplankton
community according to time and space?
The research
objective is a factual affirmation related to the expected results of the
research. In accordance with the research model formed in this study, the
purpose of this study is to analyze the quality of the waters of Lake Toba
according to space and time based on the physico-chemical
properties of the water. Analyzing the water quality of Lake Toba according to
space and time based on its phytoplankton community. Analyzing the relationship
between the ������� physical and chemical
factors of Lake ����������� Toba's waters
with the diversity and abundance of phytoplankton according to space and time.
RESEARCH METHOD
The determination
of the research area was carried out based on considerations of land use in the
study area and the problems studied, namely covering the waters of Lake Toba,
so that the selected area is expected to be in accordance with what is the main
problem in this study.
This research has
been carried out in the waters of Lake Toba based on space and time for 6
months with 2 seasons. The details of the research area are divided into four
parts, namely control, wharf, agriculture and marine cages.
This research was
conducted based on the activities of the local community in the waters of Lake
Toba. Community activities include agriculture, fisheries with the KJA system,
docks and control in the form of the Binangalom
waterfall.
There are research
data obtained in situ, namely measurements and data directly obtained at the
research station and there are also ex situ measurements, namely measurements
and data acquisition are carried out outside the research station, so it is
necessary to take samples taken to the laboratory.
The sampling
method used at each station is purposive random sampling. Sampling was carried
out for 1 year, starting in April 2018, May 2018, and July 2018 (dry season)
and continued in October 2018, November 2018 and December 2018 (BMKG, 2017).
Sampling was carried out every month with 4 times of taking by means of 2 times
of taking for the morning test and 2 times of taking for the afternoon test.
Each station has 2 sub stations. Sampling was carried out vertically and horizontally
where vertically it was taken at a depth of 0m and 5m while horizontally it was
taken at a distance of 20 m and 50 m from the edge of the lake towards the
middle of the lake. The sampling time was carried out in the morning at
08.00-11.30 WIB and in the afternoon at 13.00-16.30 WIB with a sampling time of
90 minutes.
RESULTS AND DISCUSSION
Table 1
The Mean Result of
Measurement of Water Physics and Chemical Factors based on
Sampling Room
|
Parameter |
Unit |
Control |
Agriculture |
Dock |
KJA |
Quality standards |
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|
1 |
PO 4 |
mg/L |
0.009 |
0.011 |
0.013 |
0.01 2 |
0.2 |
|
2 |
BOD 5 |
mg/L |
0.8 0 |
0.9 0 |
0.69 |
0.7 6 |
3 |
|
3 |
Temperature |
�C |
26, 60 |
26.41 |
26.69 |
26,70 |
Deviation 3 |
|
4 |
Degree of
Acidity (pH) |
- |
8.02 |
7.89 |
8.27 |
8.12 |
6-9 |
|
5 |
Dissolved
Oxygen (DO) |
mg/L |
6.79 |
6.76 |
6.42 |
4 |
>4 |
|
6 |
Conductivity |
S/cm |
163.61 |
164, 60 |
163.31 |
166.23 |
- |
|
7 |
TDS |
mg/L |
91.4 8 |
94.39 |
98.11 |
97.39 |
1000 |
|
8 |
Total Nitrates |
mg/L |
2.14 |
3.29 |
2.14 |
3.95 |
10 |
|
9 |
Light Penetration |
m |
5,10 |
4.9 6 |
3.93 |
3.44 |
- |
Average Results of
Measurement of Water Physics and Chemical Factors Based on
Sampling Time
|
Parameter |
Unit |
Dry season |
Rainy season |
Quality standards |
|||||
|
April |
May |
July |
Oct |
Nov |
Des |
||||
|
1 |
Phosphate
(PO4) |
mg/L |
0.011 |
0.011 |
0.01 |
0.011 |
0.014 |
0.01 |
0.2 |
|
2. |
BOD 5 |
mg/L |
0.42 |
0.26 |
1.14 |
0.39 |
0.88 |
1.63 |
3 |
|
3 |
Temperature |
�C |
26.76 |
26.56 |
26.72 |
26.90 |
26.21 |
26.45 |
Deviation
3 |
|
4 |
Degree
of Acidity (pH) |
- |
8.04 |
8.12 |
7.74 |
8.50 |
8.20 |
7.85 |
6-9 |
|
5 |
Dissolved
Oxygen (DO) |
mg/L |
5.91 |
6.17 |
5.94 |
5.77 |
5.82 |
6.36 |
>4 |
|
6 |
Conductivity |
S/cm |
168.41 |
166.75 |
164.99 |
160.52 |
161.48 |
164.47 |
- |
|
7 |
TDS |
mg/L |
109.19 |
104.70 |
104.68 |
46.62 |
102.50 |
104.36 |
1000 |
|
8 |
Total Nitrates |
mg/L |
2.31 |
2.38 |
1.89 |
3.73 |
3.55 |
3.43 |
10 |
|
9 |
Light Penetration |
m |
4.36 |
4.30 |
5.23 |
4.81 |
4.14 |
3.28 |
- |
Based on
Table 1 and Table 2 of the physical and chemical parameter conditions based on
space, the dissolved oxygen (DO) parameter in the KJA is worth 4 which means it
is at the threshold of the quality standard. According to (Garno,
Nugroho, & Hanif, 2020), the water quality
of Lake Toba is included in the class II category based on water quality
standards. Class II water uses are intended for infrastructure/facilities such
as water recreation, freshwater fish farming, livestock farming, water for
irrigating crops, and/or other uses that require the same water quality as
those uses.
The average
phosphate (PO4) measurement by space was in the range of 0.009 mg/L
- 0.013 mg/L. The lowest value of phosphate (PO4) was found in the
control area/Binangalom Situmurun
with a value of 0.009 mg/L and the highest value of phosphate (PO4) was
in the dock area/Ajibata with a value of 0.013 mg/L.
According to (Tungka, Haeruddin, & Ain, 2016), phosphate can be in organic form (organically bound phosphorus) or
inorganic form (including orthophosphates and polyphosphates). The cause of
high phosphate levels in the waters is due to the presence of domestic waste
containing detergent. Detergents can increase phosphate levels because
phosphate ions are one of the constituents of detergents.
The average PO4
measurement based on time is in the range of 0.01 mg/L - 0.014 mg/L.
The lowest phosphate value is in the dry season to be precise in July and in
the rainy season to be precise in December with a value of 0.01 mg/L, while the
highest phosphate value is in the rainy season to be exact in November with a
value of 0.014 mg/L. According to (Patty, Arfah, & Abdul, 2015) the main source of phosphate and nitrate nutrients comes from the
decomposition process of weathering or decomposition of plants and the remains
of dead organisms both from the waters themselves and from the plains that
enter the waters. Based on the PO4 data obtained, Lake Toba's water is still in
a good range, which is still below 0.2 mg/L. The average Phosphate (PO4)
diagram based on the space and time of sampling can be seen in Figure 1.
Figure 1
Diagram of Mean PO 4 Measurement Results by Space and Time
The average BOD 5
measurement based on space is in the range of 0.69 mg/L - 0.90 mg/L. The
lowest BOD 5 value was found in the dock area/Ajibata
with a value of 0.69 mg/L and the highest BOD 5 was in the
agricultural area/Laguboti with a value of 0.90 mg/L.
The BOD 5 obtained is relatively low, so it
can be concluded that the levels of organic compounds such as household waste
which are easily biodegradable in Lake Toba are relatively small. According
to Barus (2004), the value of BOD 5 is
derived from the amount of dissolved oxygen used by microorganisms to
biodegrade organic compounds such as household waste. According to (Lee, 1978), the classification
of the level of pollution of organic compounds in waters can be determined
based on the value of BOD5. The following is a list of water quality
statuses based on BOD 5 values, namely 2.9 classified as unpolluted,
3.0-5.0 classified as lightly polluted, 5.10-14.9 moderately polluted, and 15
heavily polluted.
The average BOD 5
measurement based on the time of sampling was in the range of 0.26 mg/L -
1.63 mg/L. The lowest BOD 5 average was found in the dry season,
precisely in May with a value of 0.26 mg/L and the highest BOD 5 average was
found in the rainy season, precisely in December with a value of 1.63 mg/L. In
the rainy season BOD 5 has increased due to
the entry of organic matter, especially household waste from the mainland to a
lower place, namely water. Organic matter that is easily decomposed by aerobic
microorganisms biologically can increase the value of BOD 5 in a waters. According to (Andika,
Wahyuningsih, & Fajri, 2020), stated that BOD5 can be measured from the amount of
dissolved oxygen used by microorganisms during the decomposition process of
organic matter under aerobic conditions. The BOD 5 value is not
absolutely used to indicate the amount of organic matter actually contained in
a water, but only to measure the amount of oxygen needed by aerobic bacteria to
decompose organic matter that is easily decomposed (Andika
et al., 2020).
data from the BOD 5 measurement in the waters of Lake Toba
above shows that the quality of the waters of Lake Toba is good, which is in
the range below 2 mg/ L. The BOD 5 value
obtained shows an indication of low levels of organic matter in the waters,
because the BOD 5 value indicates the oxygen demand used by aerobic
bacteria in the waters to carry out the oxidation process of organic matter in
the water which indirectly indicates the presence of easily decomposed organic
matter in the waters (Ginting, 2002). The BOD 5
average diagram based on space and time of sampling can be seen in Figure
2.
Figure 2
Diagram of Mean BOD 5 Measurement Results by Space and Time
Temperature
The average temperature measurement results in Lake Toba by space are in
the range of 26.41�C - 26.70�C. The temperature at each research location did
not show a significant difference between one location and another. The lowest
temperature was at the farm/Laguboti location with a
value of 26.41 and the highest temperature was at the KJA/Haranggaol
location with a value of 26.70. Temperatures in agricultural areas/Laguboti are low due to agricultural
activities, where plants in agricultural areas utilize sunlight for
photosynthesis, thereby reducing the intensity of sunlight entering the lake
which further affects the decrease in ambient temperature. The temperature
in the KJA/Haranggaol area is high because of the many activities of the surrounding community
such as fish farming, docks and local community settlements. High activity can
increase the temperature in water bodies. According (Ginting,
2002), the pattern of
increasing temperature in a waters can be influenced by anthropogenic factors (factors caused by human activities around
the lake). (Maniagasi,
Tumembouw, & Mudeng, 2013), states that the temperature of a waters can increase and decrease due
to several factors including the altitude of an area, high rainfall, and the
intensity of sunlight that penetrates a waters.
The average temperature measurement results in Lake Toba based on time
are in the range of 26.21 - 26.90 �C. The lowest temperature is in the rainy
season, precisely in November with a value of 26.21 �C and the highest
temperature is in the rainy season, precisely in October with a value of 26.90
�C. The temperature in each season and month did not change significantly,
because at the time of sampling the weather was not too hot and the rainfall in
Lake Toba was not too high. October is the first month of the rainy season,
this month the light intensity is still as in the dry season and at the time of
sampling there has been no rain in the Lake Toba area, while in November enters
the second month of the rainy season where the rain begins to fall so that the
temperature in the Lake area experiences decline. According to (Brower, Zar, &
Von Ende, 1990), water temperature conditions can be influenced by atmospheric conditions
that regulate climate, seasons, changes in weather and changes in sunlight
intensity. According to (Barus, 2004), temperature
fluctuations in tropical waters throughout the year are not too high so that
the annual water temperature measurement value is not too high. The optimum
temperature that is good for phytoplankton life in waters is around 20 �C - 30
C, in that range plankton can grow and reproduce optimally and quickly. High
temperatures can affect the level of water density and the ability of
phytoplankton to float on the surface of the waters (Maresi & Yunita, 2015) The average
temperature diagram based on space and time of sampling can be seen in Figure
3.
�������
Figure 3
Diagram of the Average of Temperature Measurement Results by Space and
Time
Degree of Acidity (pH)
The average result of pH measurement based on space is
in the range of 7.89-8.27. The lowest value is found in the agricultural area/Laguboti with a value of 7.89 and
the highest value is found in the dock area/Ajibata with a value of 8.27. The pH value
can decrease and increase due to the process of photosynthesis and changes in
the concentration of oxygen (O2) from photosynthesis and CO2 to help the
photosynthesis process. According to Anisah
(2017), the pH value can also be lower due to high concentrations of organic
matter, in addition to other factors that can also affect the high and low pH
values, including biological activity, photosynthetic activity, temperature,
and fluctuations in O2 and CO2 concentrations.
The average pH measurement results based on the time of
the sample are in the range of 7.44-8.50. The lowest average pH is in the dry
season, precisely in July with a value of 7.74 and the highest penetration is
in the rainy season, precisely in October with a value of 8.50. According to (Berutu, 2018), the ideal pH for freshwater biota life is around 6.8-8.5. A pH value that is too low will increase the solubility of
metals in water and an increase in metals in water causes toxic properties for
aquatic organisms, whereas a high pH can increase the concentration of ammonia
in water which is also toxic for aquatic organisms. The decreasing pH value in
waters is indicated by the increasing organic compounds in the waters. The
average pH diagram based on space and time of sampling can be seen in Figure 4.
Figure 4
Diagram of Average Results of Ph Measurements Based on Space and Time
The average DO
measurement based on space is in the range of 4 mg/L-6.79 mg/L. The lowest DO
value was in the KJA/Haranggaol area with a value of
4 mg/L and the highest DO was in the control area/Binangalom
Situmurun. The KJA/Haranggaol
area has the lowest DO value due to the use of dissolved oxygen (DO) for fish respiration and aerobic decomposition of feed and fish
waste. The control area has a high DO because in
that area there is no activity or little activity. According to (Suryanti & Sumartini, 2013) dissolved oxygen
(DO) levels can be reduced due to the presence of pollutants that can use
oxygen when decomposed by aerobic microorganisms. Pollutants consist of organic
and inorganic materials originating from various sources.
The average DO
measurement based on time is in the range of 5.77 mg/L-6.36 mg/L. The lowest DO
average is in the rainy season, precisely in October with a value of 5.77 mg/L
and the highest DO is in the rainy season, precisely in December with a value
of 6.36 mg/L. According to Barus (2004), DO has daily
and seasonal fluctuations that are influenced by temperature and photosynthetic
activity that produces oxygen. rainy season increases DO because the water
temperature decreases. A good DO value in the waters ranges from 6.3 mg/L, the
lower DO value if the level of pollution in the waters is high. The data from the research showed a good DO value because
it was above 6.3 mg/L, except in the KJA location which had a DO value below
6.3 mg/L. The average DO diagram based on space and time of sampling can be
seen in Figure 5.
Figure 5
Diagram of the Average of DO Measurement Results by Space and Time
The average
conductivity measurement based on space is in the range of 163.61 S/cm - 166.23 S/cm. The lowest conductivity
value was in the control area/Binangalom Situmurun and wharf/Ajibata with
a value of 163.61 S/cm and the highest conductivity was in the KJA/Haranggaol area with a value of 166.23 S/cm. According to (Irwan & Afdal, 2016), conductivity is a measure of the ability of an organic and inorganic
compound dissolved in water bodies to conduct electric current. The electric current in the solution is carried by the
cations and anions contained in the solution. Ions have their own characteristics
in conducting electric current. The number of ions in a solution is affected by
the dissolved solids. The greater the amount of dissolved solids in the solution, the greater the number of
ions in the solution, so the value of conductivity or electrical conductivity
is greater.
The average conductivity measurement based on time is in the range of 160.52 S/cm - 168.41 S/cm. The lowest average
conductivity is in the rainy season, precisely in October with a value of
160.52 S/cm and the highest conductivity in the dry season, precisely in April,
with a value of 168.41 S/cm. The dry season results in
the accumulation of dissolved solids in the waters. The more dissolved solids
increase the ions that can conduct electric current in a waters. According to (Alina, Soeprobowati, &
Muhammad, 2015), conductivity or electrical
conductivity is used as an indicator of fertility and water pollution levels. High electrical conductivity indicates the amount of waste
in the form of organic and mineral types that enter the water body. Normal
conditions in waters have electrical conductivity values ranging from 20-1500
Siemens/cm (Zaharuddin, Wahyuningsih, & Mutadi, 2016). Therefore, based on the value of electrical
conductivity in the waters of Lake Toba, it is still included in the good
category. The average conductivity diagram based on space and time of sampling
can be seen in Figure 6.
Figure 6
Diagram of the Means of Conductivity Measurement Results by Space
and time
Total Dissolved Solids (TDS)
The average TDS
measurement (total dissolved solids) based on space is in the range of 91.47 mg/L - 98.11 mg/L. The lowest TDS value was in
the control area/Binangalom Situmurun
with a value of 91.47 mg/L and the highest TDS was at the wharf/Ajibata research site with a value of 98.11 mg/L. This is because in general the surrounding community often
uses Lake Toba for daily activities such as washing and disposing of household
waste around the pier. According to (Hidayat, Suprianto, & Dewi, 2016), waste disposal from the results of population activities, fisheries,
industry and port or shipping activities is quite influential on aquatic
ecosystems and the accumulation of waste disposal will be very dangerous for
the health of the people around the waters. Changes in the concentration of TDS
can be dangerous because it will cause changes in salinity, changes in the
composition of the ions, and the toxicity of each ion. Changes in salinity can
disrupt the balance of aquatic biota, biodiversity, cause species that are less
tolerant, and cause high toxicity in the life stages of organisms (Hidayat et al., 2016).
The average TDS
measurement based on time and season is in the range of 46.62
mg/L - 109.19 mg/L. The lowest TDS average is in the rainy season,
precisely in October with a value of 46.62 mg/L and the highest TDS is in the
dry season, precisely in April with a value of 109.19 mg/L. According to (Chandra, Singh, & Tomar, 2012), total dissolved
solids are composed of elements and chemical compounds in the form of
carbonate, bicarbonate, chloride, sulfate, phosphate, nitrate, calcium,
magnesium, sodium, potassium, iron and manganese. The dissolution or weathering
of rock and soil slowly dissolves in water and forms dissolved solids. The
higher the TDS value and the main ion in the waters, the higher the electrical
conductivity/conductivity in these waters (Tessema, Mohammed, Birhanu, & Negu, 2014). The average TDS
diagram based on space and time of sampling can be seen in Figure 7.
Figure 7
Diagram of the Average of TDS Measurement Results by Space and Time
Total Nitrates
The average measurement of total nitrate by space is in
the range of 2.14 mg/L - 3.95 mg/L. The lowest total
nitrate value was in the control area/ Binangalom Situmurun and wharf/Ajibata with
a value of 2.14 mg/L, while the highest total nitrate value was in the KJA/Haranggaol area with a value of 3.95 mg/L. This is because
in the KJA area there are continuous activities such as feeding fish which
tends to cause a buildup or increase in the content of nitrate produced in
these waters. According to Putri et al . (2014), KJA
contributes nitrogen in the waters, namely in the form of leftover feed that is
not eaten by fish, fish feces, and fish metabolic waste in the form of ammonia
and urea. The feed given to fish contains about 68% - 86% nitrogen released
into the aquatic environment and the rest is eaten by fish.
The average measurement of total nitrate based on time
is in the range of 1.89 mg/L - 3.73 mg/L. The lowest total nitrate value was
found in the dry season, precisely in July with a value of 1.89 mg/L and the
highest total nitrate value was in the rainy season, precisely in October with
a value of 3.73 mg/L. According to (Effendi, 2003), the value of the
nitrate content contained in the waters can be used as a parameter of the
fertility level of a waters. Oligotrophic waters have nitrate values ranging
from 0 � 1 mg/l, mesotrophic waters have nitrate values ranging from 1 � 5 mg/l
and eutrophic waters have nitrate levels ranging from 5 � 50 mg/l. Diagram of
the average total nitrate based on space and time of sampling can be seen in
Figure 4.8.
Figure 8
Diagram of Average Measurement Results of Total Nitrate by Space and
Time
Light Penetration
The average results of light penetration measurements
in Lake Toba by space are in the range of 3.44 m - 5.10 m. The lowest value was
found in the KJA/Haranggaol area with a value of 3.44
m and the highest value was found in the control area/Binangalom
Situmurun with a value of 5.10 m. The low light
penetration value in the KJA/Haranggaol area is due
to the large number of community activities around the lake such as fish
farming which affects the change in water color and the increasing amount of dissolved solids that block light from entering
the water body, while the highest penetration value in control/Binangalom Situmurun is caused by
the lack of activity in the water bodies. environment that can produce
dissolved solids so that light penetration penetrates deeper water bodies.
According to (Suin, 2002), the amount
of dissolved solids contained in a body of water affects the penetration of
light (the penetration of sunlight into the body of water). The high amount of dissolved solids in the water causes the water to
have a cloudy color. This situation can inhibit the entry of light into water
bodies which will further affect the distribution and intensity of
photosynthesis of aquatic plants including phytoplankton (Sembiring, 2018).
The average result of light penetration measurement
based on time is in the range of 3.28 m - 5.23 m. The lowest light penetration
value is in the rainy season, precisely in December with a value of 3.28 m and
the highest penetration value is in the dry season, precisely in July with a
value of 5.23 m. High penetration in the dry season is caused by the low
intensity of rain falling to the earth and hot weather always lasts that month,
while the low light penetration in the rainy season is caused by the higher
intensity of rain falling to the earth so that the research area is often
covered with clouds and reduced sunlight entering the earth. The average light
penetration diagram based on space and time of sampling can be seen in Figure
9.
Figure 9
Diagram of the Average of Light Penetration Measurement Results by Space
and time
From
the research that has been carried out, several conclusions can be written,
namely the results of measurements of physico-chemical
factors in the waters of Lake Toba showing temperature, light penetration,
acidity (pH), oxygen solubility (DO), biological oxygen demand (BOD5),
conductivity, total dissolved density. (TDS), Nitrate (NO3) content and
Phosphate (PO4) content according to space and time are generally still in a
good range, except in the KJA area, where the solubility of oxygen (DO) is low or
in the range below normal.
Based
on data on the diversity and abundance of phytoplankton, the quality of the
waters of Lake Toba is still in the good category, in this case the diversity
index (H') > 3. The phytoplankton found in the waters of Lake Toba are 36
species belonging to 23 families, 15 orders, 5 classes and 3 phyla. The
dominant type of phytoplankton according to space and time is Staurastrum sp. and Sphaerocystis
sp. Types of Chlorobotrys sp., Ephitemia
sp., and Spirulina sp. found only in the control area. Types of Microcystis sp.
found only on the dock. Types Ulothrix sp., Volvox sp., Spirogyra sp. found in
control areas, farms and docks and not found in KJA areas. Plectonema
sp. found in control areas, cages, and docks and not found in agricultural
areas. Types of Cymbella sp. found in the KJA and
wharf areas while in control and agricultural areas it was not found. Aphanizomenon sp. found in the control and agricultural
areas, while in the KJA and wharf areas were not found.
There
are five highest genera obtained based on the time of sampling, one of which is
Chroococcus which belongs to the Cyanophyceae
class. The high abundance of genera from the Cyanophyceae
class can be an indication of organic pollution. The presence of the genera
Microcystis, Oscillatoria, and Scenedesmus in large numbers indicates the
condition of polluted waters. These genera are associated with polluted waters.
There are 7 taxa that are tolerant of organic pollution in Lake Toba, namely
Oscillatoria sp., Navicula sp., Nitzschia
sp., Synedra sp., Stigeoclonium sp., Closterium sp.,
and Melosira sp.
Physical
and chemical factors of the waters that are significantly related to the
diversity of phytoplankton species in Lake Toba based on space and time are
total nitrate levels and light penetration with a contribution of 32.7%.
REFERENCES
Alina, Ayu Ambar,
Soeprobowati, Tri Retnaningsih, & Muhammad, Fuad. (2015). Kualitas Air Rawa Jombor Klaten, Jawa
Tengah Berdasarkan Komunitas Fitoplankton. Jurnal Akademika Biologi, 4(3),
41�52.
�lvarez-V�zquez, M. A., Bendicho, Carlos, & Prego,
R. (2014). Ultrasonic Slurry Sampling Combined With Total Reflection X-Ray
Spectrometry For Multi-Elemental Analysis Of Coastal Sediments In A Ria System.
Microchemical Journal, 112, 172�180.
Andika, Bayu,
Wahyuningsih, Puji, & Fajri, Rahmatul. (2020). Penentuan Nilai Bod Dan Cod Sebagai Parameter Pencemaran Air Dan Baku
Mutu Air Limbah Di Pusat Penelitian Kelapa Sawit (Ppks) Medan. Quimica:
Jurnal Kimia Sains Dan Terapan, 2(1), 14�22.
Barus, Ternala
Alexander. (2004). Faktor-Faktor Lingkungan
Abiotik Dan Keanekaragaman Plankton Sebagai Indikator Kualitas Perairan Danau
Toba (Environmental Abiotic Factors And The Diversity Of Plankton As Water Quality
Indicators In Lake Toba, North Sumatera, Indonesia). Jurnal Manusia Dan
Lingkungan, 11(2), 64�72.
Berutu, Wantrido P.
(2018). Produktivitas Primer Perairan
Danau Toba Kecamatan Silalahi Kabupaten Dairi Provinsi Sumatera Utara.
Brower, James E.,
Zar, Jerrold H., & Von Ende, C. N. (1990).
Field And Laboratory Methods For General Ecology. Wm. C. Brown
Publishers Dubuque, Iowa, Usa.
Chandra, Sulekh,
Singh, Arendra, & Tomar, Praveen Kumar. (2012). Assessment Of Water Quality Values In Porur Lake Chennai, Hussain Sagar
Hyderabad And Vihar Lake Mumbai, India. Chemical Science Transactions, 1(3),
508�515.
Effendi, H. (2003). Study Water Quality For Resource Management And Aquatic Environments. Penerbit
Kanisius. Yogyakarta.
Fauziyah, Fauziyah,
& Wijopriono, Wijopriono. (2010).
Densitas Schooling Ikan Pelagis Pada Musim Timur Menggunakan Metode
Hidroakustik Di Perairan Selat Bangka. Jurnal Penelitian Sains, 13(2).
Garno, Yudhi Soetrisno,
Nugroho, Rudi, & Hanif, Muhammad. (2020).
Kualitas Air Danau Toba Di Wilayah Kabupaten Toba Samosir Dan Kelayakan
Peruntukannya. Jurnal Teknologi Lingkungan, 21(1), 118�124.
Ginting, Eva
Marlina. (2002). Pengaruh Aktivitas
Manusia Terhadap Kualitas Air Di Perairan Parapat Danau Toba.
Hidayat, Diky,
Suprianto, R., & Dewi, Putri Sari. (2016).
Penentuan Kandungan Zat Padat (Total Dissolve Solid Dan Total Suspended Solid)
Di Perairan Teluk Lampung. Analit: Analytical And Environmental Chemistry,
1(1).
Irwan, Fadhilah,
& Afdal, Afdal. (2016). Analisis Hubungan
Konduktivitas Listrik Dengan Total Dissolved Solid (Tds) Dan Temperatur Pada
Beberapa Jenis Air. Jurnal Fisika Unand, 5(1), 85�93.
Jiang, Yu Jiao, He,
Wei, Liu, Wen Xiu, Qin, Ning, Ouyang, Hui Ling, Wang, Qing Mei, Kong, Xiang
Zhen, He, Qi Shuang, Yang, Chen, & Yang, Bin. (2014). The Seasonal And Spatial Variations
Of Phytoplankton Community And Their Correlation With Environmental Factors In
A Large Eutrophic Chinese Lake (Lake Chaohu). Ecological Indicators, 40,
58�67.
Karydis, M., &
Tsirtsis, G. (1996). Ecological Indices: A
Biometric Approach For Assessing Eutrophication Levels In The Marine
Environment. Science Of The Total Environment, 186(3), 209�219.
Klessig, Lowell L.
(2001). �Lakes And Society: The Contribution Of Lakes
To Sustainable Societies. Lakes & Reservoirs: Research & Management,
6(2), 95�101.
Lau, S. S. S., &
Lane, S. N. (2002). Biological And Chemical
Factors Influencing Shallow Lake Eutrophication: A Long-Term Study. Science
Of The Total Environment, 288(3), 167�181.
Lee, Lung Fei.
(1978). Unionism And Wage Rates: A Simultaneous Equations Model
With Qualitative And Limited Dependent Variables. International Economic
Review, 415�433.
Lehmusluoto, Pasi,
Priadie, Bambang, & Vauhkonen, Juha. (2006). Indonesian Lake Crisis, A Reality? Proceedings Of The 11 Th World
Lakes Conference-- Proceedings, 1, 343�348.
Lukman, Hidayat,
Haryani, Gadis Sri, Chrismadha, Tjandra, Henny, Cynthia, Fakhrudin, M., &
Tri Widiyanto, Sulastri. (2017). Tiga
Dasawarsa Berkarya Pusat Penelitian Limnologi Lipi.
Lukman, I.
Ridwansyah. (2010). Study Of Morphometry
Condition And Several Stratification Parameters Of Lake Toba. Jurnal
Limnotek, 17(2), 158�170.
Maniagasi, Richard,
Tumembouw, Sipriana S., & Mudeng, Yoppy. (2013). Analisis Kualitas Fisika Kimia Air Di Areal Budidaya Ikan Danau Tondano
Provinsi Sulawesi Utara. E-Journal Budidaya Perairan, 1(2).
Maresi, Sinta
Ramadhania Putri, & Yunita, Etyn. (2015). Fitoplankton
Sebagai Bioindikator Saprobitas Perairan Di Situ Bulakan Kota Tangerang.
Maulana, Yudi Y.,
Wiranto, Goib, Kurniawan, Dayat, Syamsu, Iqbal, & Mahmudin, Dadin. (2018). Online Monitoring Of Shrimp Aquaculture In Bangka Island Using Wireless
Sensor Network. International Journal On Advanced Science, Engineering And
Information Technology, 8(2), 358�364.
Nontji, Maymuna,
Patenjengi, Baharuddin, Rasyid, Burhanuddin, & Pirman, Pirman. (2016). Analysis Of Reduce Potential Methane Gas Emission By Methanotrofic
Bacteria From Rice Field In Gowa. Modern Applied Science, 10(7),
183.
Patty, S. I., Arfah,
H., & Abdul, M. S. (2015). Nutriens
(Phosphate, Nitrate), Dissolved Oxygen, And Dissolved Ph And They Relation To
Productivity Of Jikumerasa Waters, Buru Island. Jurnal Pesisir Dan Laut
Tropis, 1(1), 43�50.
Radiarta, I. Nyoman.
(2013). Hubungan Antara Distribusi
Fitoplankton Dengan Kualitas Perairan Di Selat Alas, Kabupaten Sumbawa, Nusa
Tenggara Barat. Jurnal Bumi Lestari, 13(2), 234�243.
Sembiring,
Alexsander G. A. (2018). Hubungan Kelimpahan
Fitoplankton Dan Faktor Fisika Kimia Perairan Di Danau Toba Desa Tigaras
Kecamatan Pardamean Kabupaten Simalungun Provinsi Sumatera Utara.
Siagian, Dame.
(2010). Analisis
Pengaruh Strukttur Corporate Governance Terhadap Perusahaan Yang Mengalami
Financial Distress (Studi Empiris Pada Perusahaan Publik Yang Tercatat Di Bei
Pada Tahun 2005�2009). Media Riset Akuntansi, Auditing & Informasi, 10(3),
46�64.
Suin, Nurdin
Muhammad. (2002). Metoda Ekologi.
Suryanti, S.
Rudiyanti, & Sumartini, Susi. (2013). Kualitas
Perairan Sungai Seketak Semarang Berdasarkan Komposisi Dan Kelimpahan
Fitoplankton. Journal Of Management Of Aquatic Resources, 2(2),
38�45.
Tessema, A.,
Mohammed, A., Birhanu, T., & Negu, T. (2014). Assessment Of Physico-Chemical Water Quality Of Bira Dam, Bati Wereda,
Amhara Region, Ethiopia. Journal Of Aquaculture Research And Development,
5(6).
Thoha, H., &
Amri, K. (2011). Composition And
Abundance Of Phytoplankton In South Kalimantan Waters. Oseanologi Dan
Limnologi Di Indonesia, 37(2), 371�382.
Tungka, Anggita
Wahyuningtyas, Haeruddin, Haeruddin, & Ain, Churun. (2016). Konsentrasi Nitrat Dan Ortofosfat Di Muara Sungai Banjir Kanal Barat Dan
Kaitannya Dengan Kelimpahan Fitoplankton Harmful Alga Blooms (Habs)
Concentration Of Nitrate And Orthophosphate At Banjir Kanal Barat Estuary And
Their Relationship With The Abundance Of Harmful Algae Blooms. Saintek
Perikanan: Indonesian Journal Of Fisheries Science And Technology, 12(1),
40�46.
Yu, Bingfeng, Liu,
Min, Egolf, Peter W., & Kitanovski, Andrej. (2010)
. A Review Of Magnetic Refrigerator And Heat Pump Prototypes
Built Before The Year 2010. International Journal Of Refrigeration, 33(6),
1029�1060.
Zaharuddin,
Nathasya, Wahyuningsih, Hesti, & Mutadi, Ahmad. (2016). Penentuan Kualitas Air Di Danau Kelapa Gading Kelurahan Kisaran Naga
Kabupaten Asahan Provinsi Sumatera Utara. Aquacoastmarine, 14(4),
94�102.
Zulfiah, Naila,
& Aisyah, Aisyah. (2016). Status Trofik
Perairan Rawa Pening Ditinjau Dari Kandungan Unsur Hara (No3 Dan Po4) Serta
Klorofil-A. Bawal Widya Riset Perikanan Tangkap, 5(3), 189�199.