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Desalination and Water Treatment
www.deswater.com
doi: 10.5004/dwt.2018.22302
115 (2018) 261–270
May
Assessment of irrigation water quality of Turkey using multivariate statistical
techniques and water quality index: Sıddıklı Dam Lake
Tamer A kkana,*, Okan Yazicioglub, Ramazan Yazicic, Mahmut Yilmazd
aGiresun University, Department of Biology, Faculty of Arts and Science, Giresun, Turkey, email: biyoloji@yahoo.com (T. Akkan)
bOrganic Farming Program, Botanic and Animal Production Department, Technical Vocational Schools of Higher Education,
Ahi Evran University, Kırşehir, Turkey, email: oknyzcoglu@gmail.com (O. Yazicioglu)
cLaboratory and Veterinary Health Department, Çiçekdağı Technical Vocational Schools of Higher Education, Ahi Evran University,
Kırşehir, Turkey, email: rmznyzci@gmail.com (R. Yazici)
dDepartment of Animal Biotechnology, Faculty of Agriculture, University of Ahi Evran, Kırşehir, Turkey,
email: mahmuty20@gmail.com (M. Yilmaz)
Received 2 November 2017; Accepted 5 April 2018
a b s t r a c t
This study was done in order to evaluate the status of the water quality of Sıddıklı Dam Lake as well
as its suitability for irrigated agriculture. Sıddıklı Dam Lake is one of the major irrigation dam lakes
flowing into Hirfanli Dam Lake. Throughout the first report on this study, surface water samples
were taken monitoring 25 physicochemical variables at 4 different sites at every month between Sep-
tember 2015 and August 2016. In the present study, multivariate statistical techniques (hierarchical
cluster analysis (HCA), principal component analysis (PCA)), the Pearson correlation, the Surface
Water Quality Index, and Carlson’s Trophic State Index were applied to the physicochemical variables
on the water quality of the dam lake. Thus, we aim to determine the main pollution factors as well as
the same time risky polluted areas. Sıddıklı Dam Lake was found eutrophic with a mean TSI value
of 57. Moreover, the surface water quality index value was 67, inferring that it is of “medium quality”.
According to the results of HCA, four surface water sampling zones were grouped into two clusters.
Upon looking at the PCA results, on can estimate that the lake dame pollution is mainly from agricul-
tural run-off and soil erosion. Additionally, the water of Sıdıklı Dam Lake is not suitable for drinking,
however it is fit for other purposes such as aquaculture, livestock drinking, and agricultural activities.
Consequently, Sıddıklı Dam Lake has a satisfying level of water quality according to the overall qual-
ity variable permissible limits, however it has been strongly affected by agricultural use.
Keywords: Water quality; Multivariate statistical techniques; Water quality index (WQI); Carlson
trophic state index (TSI)
1. Introduction
Clean freshwater resources are the primary source of
water for domestic, agricultural, and industrial purposes in
many countries. Unfortunately, a lot of negative conditions
are observed in such resources, such as anthropogenic
influences that impair their use for drinking, alongside
industry, agriculture, and recreation purposes [1,2]. The
pollution of freshwater resources with inorganic pollutants
and an excess of certain nutrients has become a worldwide
environmental concern. Nutrients such as phosphorus and
nitrogen are known as the source of eutrophication and are
known to negatively affect aquatic ecosystems [3].
Water quality for irrigation depends on the surrounding
domestic and agricultural activities. Poor quality irrigation
water poses many hazards to agricultural production [4].
The quality of these resources may affect both crop yields
and soil physical conditions, even if all other conditions are
optimal. Therefore, it is necessary to ensure the continuous
monitoring of water resources, or else it can lead to large
losses both in terms of water resources as well as in terms
of agricultural products. The periodic monitoring the water
T. Akkan et al. / Desalination and Water Treatment 115 (2018) 261–270
262
body quality will help protect our waterways from pollution,
and will allow for sustainable use [5]. Recently, water
quality index and multivariate statistical techniques have
been widely used in order to gain a better understanding
of the water quality during monitoring research activity.
Additionally, these analyzes allow for the determination of
possible pollutants that affect water sources [6–10]. Şener
et al. [11] used GIS and the Water Quality Index (WQI) in
order assess the suitability of river water from Aksu River,
which is the main source of the Karacaören-1 Lake Dam,
and is used for human consumption.
Kırşehir is one of the most important agricultural cities
within Central Anatolia, it is used both for drinking and
for irrigation water. It is undoubtedly of great importance
to take precautions in order to determine and protect the
quality of these resources. For this reason, the aim of the
present study is/was:
1. To assess surface water quality used in agricultural
and fishery activities,
2. To determine the relationship between stations,
3. To classify water quality variables for spatial differ-
ences, and
4. To clarify the impact of pollution sources on water
quality variables for the lake dam.
Moreover, the results obtained from this study will
provide baseline information for future studies.
2. Material and methods
2.1. Sample location and sampling
Sıddıklı Dam Lake (or Sıddıklı Küçükboğaz Dam Lake,
and originally known as Karababa Dam) is a zoned clay
and rock-filled dam with a central core on Körpeli Boğaz
creek at the border of the Province of Kırşehir Province
in Turkey’s Central Anatolian region. Construction of the
dam began in 1991 and was completed in 2002. The lake
dam is of the clay core-rock filling type. It has a surface
area of 1.62 km2, and an active water level of 25.3 hm3. Built
both for business rental as well as to irrigate the region’s
plains, it was renamed as Sıddıklı Küçük Boğaz Village,
where its main crops are cereals. There are alluvial plains
and erosion galleries in front of Pliocene fractals and lying
mostly around the study area [12]. Generally, this area has
a hard summer continental climate, including cold and
snowy winters and hot and dry summers. Therefore, the
water level fluctuates widely due to irrigation demands and
seasonal rainfall levels.
The surface water samples were collected on a monthly
bases between September 2015 and August 2016 from 4
different stations. Surface water samples (0–20 cm) were
collected in triplicates at each sampling site using a Nansen
bottle. Following collection, the samples were placed
in coolers with ice boxes upon being transported to the
laboratory, and were kept at about 4°C prior to analysis.
2.2. Determination of physicochemical variables
The water temperature, pH, dissolved oxygen,
conductivity, total dissolved solid, salinity, and
oxidoreduction potential were determined using with
equipment of multi-parameter and turbid meter (YSI Pro
Plus, WTW-Turb355). Also, nitrite nitrogen was determined
using the YSI 9300 photometer, and secchi transparency
was determined using a Secchi disc during the sampling
period. Physicochemical variables including alkalinity,
hardness, total suspended solids, sulphite, sulfate, silica,
total phosphorus, orthophosphate phosphorus, total
Fig. 1. Map of study area with sampling point locations (changed from Google earth).
T. Akkan et al. / Desalination and Water Treatment 115 (2018) 261–270
263
ammonia nitrogen, nitrate nitrogen, ammonium, ammonia,
chlorophyll a, and BOD5 were measured using standard
methods [13]. Na and K were determined using flame
photometers. The Water Research Center surface water
quality index (NSF-WQI) was modified and used for seven
parameters of the current situation analysis [14]. Also, the
calculations of TSI were followed by calculated using the
Carlson’s Trophic State Index [15] for the three periods
using the following three equations:
TSLg
Llnl
n
CHLµ∗=−−
()
()
10 62.040.6
82
CHL
TSIgLlnTPln
TP µ∗=−
()
10 64
82
TSIm ln ln
SD
=−
()
10 62∗SD
TSITSI TSITSI
AVG TP CH
LS
D
=++
()
3
where TP = total phosphorus (μg/l); CHL = chlorophyll-a
(μg/l); SD = Secchi depth (m); TSI-AVG = TSI averaged for
all three parameters, and ln = natural logarithm.
2.3. Statistical analysis
Descriptive statistical analysis, including One-way
ANOVA with Tukey’s multiple range test was done, with
a significance of (p < 0.05). Also, a nonparametric, one-
way analysis of the variance, as well as the Kruskal-Wallis
H-test were used to determine a seasonal difference. The
relationships between the considered variables were tested
using correlation analysis with Pearson’s test. Multivariate
statistical analysis of the overall water quality variables
was performed using principal component and hierarchical
cluster analysis (PCA-HCA) [16]. Statistical analysis of the
results was carried out using SPSS 21.0.
3. Results and discussion
The annual mean values of physicochemical variables
ranged between, for WT: 3.10 and 25.70°C, EC: 0.635 and
1.111 mS/cm, TDS: 0.42 and 1 g/L, pH: 7.35 and 8.52, DO:
4.75 and 15.39 mg/L, salinity: 0.31 and 0.79 ppt, , TAN:
0.110 and 1.408 mg/L, NO3-N: 0.094 and 2 mg/L, NO2-N:
0.0031 and 0.037 mg/L, NH3: 0.001 and 0.102 mg/L, NH4
+:
0.102 and 1.362 mg/L, silica: 1.3 and 75.5 mg/L, TP: 0.026
and 2.882 mg/L, O-PO4: 0.033 and 3.710 mg/L, SO3: 2 and
18 mg/L, SO4: 25 and 106 mg/L, Na: 8.50 and 16.80 mg/L,
K: 0.90 and 18.50 mg/L, alkalinity: 9 and 28.50 mg/L,
hardness: 12 and 27.50°F, Chl_a: 0.818 and 4.235 μg/L,
turbidity: 0.01 and 49.84 NTU, TSS: 0.42 and 2.16 g/L, BOD5:
0.10 and 6.12 mg/L, and secchi disc depth: 97 and 275 cm.
Spatial changes of all of the physiochemical variables in the
surface water are shown in Table 1.
The highest and lowest values of the physicochemical
variables were determined according station: WT, pH,
alkalinity, hardness, NH3, Chl_a, BOD5 and WT, EC, TDS,
salinity, TAN, NO3, NH3, NH4, K, TP, O-PO4, SO4, alkalinity
at Station 1; SD, SO4, SO3, O-PO4 and TDS, salinity, NO2, SO3,
SO4, Na, Chl_a at Station 2; EC, TDS, salinity, TSS, TP and
DO, SO4, silica, TSS, NH3 at Station 3; DO, turbidity, NO3,
NO2, SO3, silica, TAN, NH4, Na, K and TDS, pH, turbidity,
SD, hardness, K, BOD5 at Station 4.
The Turkish surface water quality system is classified
into four groups. Class I refers to very clean water, class
II refers to less contaminated water, class III refers to
considerably contaminated water, and class IV refers to
extremely contaminated water [17]. The surface water
of the dam lake is in good condition in terms of pH and
NO3-N values according to SWQR. DO and NH4 and
O-PO4 values are generally classified as Class I, however
these values are sometimes classified as Class III, II, and
IV, respectively. Moreover, the present results indicate
that some water quality variables from previous studies
which were used for irrigation water in Turkey are also
suitable for Sıddıklı Lake Dam, and are demonstrated in
Table 2. According to these studies on Turkish freshwater
sources, TDS, TSS, turbidity and BOD5 values were found
to be lower compared to those in the present study (Table
2). DO measurement is especially vital for aquatic life. The
optimum DO values for good water quality had ranged from
4 to 6 mg/L, which ensures healthy aquatic life in a water
body [18]. In this study, minimum dissolved oxygen values
were measured at 4.75 mg/L. The results that Kaplan et al.
[19] had determined in terms of TDS concentrations (mg/L)
in the Perisuyu River were lower than our results. Mutlu
and Uncumusaoğlu [20] had found the pH values in the
surface water of the Maruf Dam to be in range of 7.71–8.98.
In another study, pH values of dam water were found to
be in the range of 8.16–8.70 [21]. In similar Turkish studies,
the geological structure is generally limy, and the measured
pH values demonstrate the slightly alkali character of our
lakes [22].
The analysis of Pearson correlation of the physiochemical
variables had indicated the absence of positive and good
correlation (above 0.7, Table 3). On the other hand, there
was less of a significant correlation between some of the
variables. The WT had shown significant and positive
correlation between sulfate, TSS, and BOD5 (r = 0.754,
r = 0.714, r = 0.880), as well as a negative high correlation
between TAN and NH4 (r = –0.735, r = –0.767). The EC had
shown a significant and positive high correlation between
TDS and salinity (r = 0.808, r = 0.813). Also, the TDS had
shown a significant and positive high correlation with
regards to salinity (r = 0.997). The Turbidity had shown
a significant and positive correlation between TSS and K
(r = 0.885, r = 0.747). The sulfate had shown a significant and
positive correlation with BOD5 (r=0.816). The alkalinity had
shown a significant and positive correlation with hardness
(r = 0.831). The TAN had shown a significant and positive
high correlation with NH4 (r = 0.998), as well as negative
correlation with BOD5 (r = –0.827). Lastly, NH4 had shown a
significant and negative correlation with BOD5 (r = –0.848).
Statistical analyzes of 48 samples taken monthly from the
four stations were conducted. For the Anova and Kruskal-
Wallis H-test analyses, seasonal mean levels (except for TP
and SD) were significantly different (p < 0.05); however
there were no significant differences between stations
(p > 0.05).
In a PCA analysis comprised of 25 physicochemical
variables, seven components were included. These
T. Akkan et al. / Desalination and Water Treatment 115 (2018) 261–270
264
Table 1
The Sıddıklı Dam Lake water quality variables
Stations
1 2 3 4
Mean SE± Min. Max. Mean SE± Min. Max. Mean SE± Min. Max. Mean SE± Min. Max.
WT (°C) 14.60 2.278 3.10 25.70 14.6 4 2.246 3.10 25.40 14.41 2.179 3.10 23.70 14.16 2.150 3.10 23.10
EC (m S/c m) 0.770 0.039 0.635 1.090 0.792 0.039 0.636 1.093 0.797 0.041 0.660 1.111 0.799 0.038 0.652 1.095
TDS 0.567 0.053 0.416 1.0 01 0.579 0.052 0.416 0.988 0.582 0.052 0.429 1.001 0.585 0.050 0.423 0.988
Salinity(ppt) 0.43 0.043 0.31 0.77 0.44 0.042 0.31 0.77 0.44 0.042 0.32 0.79 0.44 0.040 0.32 0.77
DO (mg/L) 8.98 0.780 5.76 14.7 9 9.59 0.770 6.82 14.58 8.75 0.875 4.75 14. 83 9.37 0.833 5.80 15. 39
pH 8.25 0.080 7.4 6 8.52 8.28 0.055 7. 8 2 8.50 8.22 0.079 7. 4 0 8.42 8.16 0.082 7. 3 5 8.41
TAN (mg/L) 0.685 0.120 0.110 1.335 0.710 0.103 0.116 1.182 0.667 0.110 0.114 1.207 0.758 0.099 0.347 1.408
NO3-N (mg/L) 0.273 0.039 0.094 0.605 0.280 0.041 0.139 0.640 0.298 0.055 0.109 0.650 0.433 0.153 0.101 2.000
NO2-N (mg/L) 0.007 0.001 0.004 0.013 0.008 0.001 0.003 0.015 0.010 0.002 0.004 0.019 0.013 0.003 0.004 0.037
NH3 (mg/L) 0.037 0.008 0.001 0.102 0.038 0.008 0.002 0.081 0.032 0.005 0.001 0.068 0.030 0.005 0.003 0.064
NH4 (mg/L) 0.648 0.119 0.102 1.307 0.672 0.103 0.114 1.153 0.635 0.108 0.106 1.160 0.728 0.098 0.323 1. 362
Silica (mg/L) 13.55 5.370 1.95 62.50 12.75 4.798 1.45 55.50 13.45 4.966 1.25 5 7. 5 0 15.36 6.346 1.70 75.50
SO4 (mg/L) 63.00 6.499 25.00 84.00 69.92 6.642 25.00 106.00 6 5.17 5.863 25.00 89. 0 0 65.42 5.220 33.00 84.00
SO3 (mg/L) 11.0 0 1.022 6.00 17. 0 0 10.42 1.264 2.00 18.0 0 10.00 1.087 4.00 16.0 0 10.25 1.426 3.00 18.00
TP (mg/L) 0.170 0.044 0.026 0.467 0.155 0.037 0.048 0.459 0.400 0.234 0.029 2.882 0.234 0.088 0.028 1.112
O-PO4 (mg/L) 0.752 0.253 0.033 2.573 0.957 0.334 0.055 3.710 0.920 0.294 0.068 3.519 0.833 0.244 0.076 2.849
Alk. (mg/L) 15.45 1.462 9.00 28.50 15.18 1.277 11. 50 26.50 15.48 1.336 12.50 28.00 15.68 1.380 11.50 2 7. 5 0
Hard. (°F) 18.44 1.302 13.80 2 7. 5 0 1 7. 3 3 1.021 14.0 0 24.00 1 7. 9 0 0.883 14.0 0 23.50 1 7. 7 8 1.095 12.00 26.00
Chl_ a (μg/L) 2.394 0.248 1.286 4.235 2.396 0.273 0.818 3.998 2.240 0.272 0.883 3.617 2.234 0.251 1.135 3.964
TSS (g/L) 1.04 0.140 0.54 1.68 1.06 0.170 0.44 2.00 0.98 0.158 0.42 2.16 1.01 0.146 0.44 1.60
Na (mg/L) 13.20 0.383 10.90 16. 30 13.05 0.585 8.50 16 .20 13.55 0.352 11.3 0 15.30 14.0 6 0.423 11.30 16.8 0
K (mg/L) 5.65 1.692 0.90 17.4 0 3.76 0.790 1.30 10.40 4.46 1.242 1.0 0 16.60 5.63 1.848 0.90 18.50
Turb. (NT U ) 13.70 4.429 0.77 38.75 12.96 4.298 0.10 46.90 13.18 4.297 0.62 44.53 16.04 5.326 0.01 4 9.84
BOD5 (mg/L) 3.38 0.567 0.50 6.12 3.38 0.558 0.45 6.10 3.36 0.544 0.44 6.09 3.07 0.543 0.10 5.05
SD (cm) 174.7 15.3 110.0 268.0 171.9 13.1 128.0 275.0 171.6 13.9 118.0 251.3 152.7 14.5 9 7.0 2 59.0
T. Akkan et al. / Desalination and Water Treatment 115 (2018) 261–270
265
components were acquired with eigenvalues >1 summing
up 84.52% of the total variance in the surface water results.
(Table 4, Figs. 2 and 3). The first PC, which accounts for
31.61% of the total variance has a strong positive loadings
on WT, SO4, and BOD5, a moderate positive loading on
Chl_a, and a strong negative loadings on TAN and NH4.
This first factor, which is also known as the “organic
pollutant factor”, can be based on domestic waste as well as
seasonal changes [26].
The second or “ionic” factor, which accounts for 19.18%
of the total variance, has a strong positive loading on EC,
TDS, and salinity, as well as moderate positive loadings
on SD. Soil erosion and precipitation are the natural
source of these variables in this region. The third or “pH
Factor”, in accounting for 10.65% of the total variance, has
a strong positive loading on pH and NH3, as well as strong
negative loadings on DO. Seasonal changes are the natural
source of these variables within this region. The fourth
or the “geological” factor, in accounting for 7.86% of the
total variance, has a strong positive loadings on alkalinity
and hardness. This situation corrleates with carbonate,
bicarbonate and lime deposits in the lake dam bed. The
fifth or “agricultural” factor, PC accounting for 6.60% of
the total variance, has a strong positive loading on NO3-N,
and moderate positive loadings on NO2-N, K, and turbidity.
This factor represents fertilizer pollution sources, and can
explain the high levels of organic nitrogen compounds
consuming large amounts of oxygen, which undergoes
aerobic processes leading to formation of ammonia and
nitrate nitrogen. The sixth or “pesticides” factor, which
accounts for 4.58% of the total variance, has a moderate
positive loading on sulfide, and strong negative loading on
Na. This factor is due to the discharge of pesticides carried
by a feeder stream into the dam lake water and, and is a
harmful towards certain bacteria. The seventh or “fertilizer”
factor, whih accounts for 4.05% of the total variance, has
a strong positive loading on TP, and moderate positive
loading on silica. The phosphate has its origin in lake dam
waters due to the use of phosphatic fertilizers, and because
it feeds into a stream that is contaminated with domestic
wastewater.
The HCA classifies the four sampling stations into two
major clusters (Fig. 4). The first cluster corresponds to station
4. This station is located at the entrance to the river points
that feed into the lake dam. The second cluster corresponds
to Stations 2, 1, and 3. These sampling stations are situated
on the other side of sampling location in this lake dam, and
receives its pollution mainly from agricultural run-off and
soil erosion.
We should note that the NSF-WQI had been applied in
many studies involving fresh water systems [6,9,27]. The
NSF-WQI was used to aggregate seven parameters and their
dimensions into a single score, in turn showing a picture of
the water quality. This index had shown that, according to
pH, BOD5, WT, TP, NO3-N, turbidity and total solids values,
the water quality score was 67 and was deemed as being
medium quality water. Lumb et al. [28] had reported that the
NSF-WQI index results for seven parameters scenarios at
the Don River (Canada) had ranged from 59–78. In another
study on NSF-WQI, researchers had revealed that water
quality of Golgol river had good or average conditions at
all stations at different months [29].
Table 2
Comparison of water quality variables in the similar previous studies
Kralkizi Dam
reservoirs,
[21]
Groundwater in
the Bafra Plain,
[23]
Eğirdir Lake,
[24]
Küçüksu Pond,
[25]
Maruf Dam,
[20]
This study
WT (°C) 4 .4 – 2 7.2 20.8–27.7 14.17–20.8 3.10 –25.70
pH 8.16–8.70 7.71–8.98 7.9 – 8 . 4 2 7. 3 5 – 8. 5 2
DO (mg/L) 6.84 –11.40 3.1–11.98 9.30–12.24 9–12 4.75–15.39
Salinity (ppt) 0.040– 0.140 0.31–0.79
TDS (mg/L) 1.342–8.132 420–1001
TSS (mg/L) 0.8–8.6 1.02 –9.50 1.2–9.62 420 –2160
Hardness (mg/L) 138–200 25.49* 12–27.5
Alkalinity (mg/L) 94–150 9–28.5
Na (mg/L) 2 – 7.11 257–2514 4.52–13.47 36.42–74.40 3 7.2 4 – 5 3 .8 8 8.5–16. 8
K (mg/L) 0.87–59.13 5.76–18.220 2.473* 0.9–18.5
Turb. (NT U ) 0.37–14. 2 0.01– 49.84
NH4 (mg/L) 0–1.89 0.0001–0.004 0.102–1.362
NO2-N (mg/L) 0–0. 014 0.019–0.08 0.0005–0.0081 0.003–0.037
NO3-N (mg/L) 0.002–0.483 0.72– 4.23 2.40–13.86 4.21* 0.094 –2
O-PO4 (mg/L) 0.33* 0.033 –3.710
BOD5 (mg/L) 0.360–2.180 2.19* 0.10–6.12
*: mean value.
T. Akkan et al. / Desalination and Water Treatment 115 (2018) 261–270
266
Table 3
Pearson correlations of the physicochemical variables
WT EC TDS Sal. DO pH Tu r b. SD NO2–N NO3–N SO4SO3Silica Alk.
p < 0.01
WT 1–0.422 –0.436 –0.549 0.633 0.553 0.754 –0.219
EC –0.285 10.808 0.813 –0.603 –0.449 – 0.407 –0.465
TDS 10.997 – 0.573 0.493 –0.451 –0.392 –0.415 0.255
Sal. 1–0.582 0.496 –0.454 –0.394 –0.393
DO 0.302 0.271 0.284 1–0.702 –0.597 – 0.552 –0.351 – 0.472
pH 10.465
Turb. 10.633 0.602 0.346 –0.438
SD 1
NO2-N 10.492 0.371
NO3-N 0.295 1
SO41
SO30.240 1
Silica 0.332 0.333 1
Alk. –0.283 0.297 0.255 0. 2 74 1
Hard. 0.317 –0.263 – 0.259
TSS
TP
O-PO40.330
TAN 0. 312 – 0.298 – 0.245
NH3–0.273
NH40.274 –0.330 –0.271
Na 0.247 –0.296 – 0.282 0.241
K0.257
Chl_a –0.243 –0.240 – 0.322 0.277 –0.269
BOD5–0.319 –0.259 0.242
p < 0.05
T. Akkan et al. / Desalination and Water Treatment 115 (2018) 261–270
267
Table 3 (Continued)
Hard. TSS TP O–PO4TAN NH3NH4Na KChl_a BOD5
p < 0.01
WT 0.714 0.422 –0.735 0.426 –0.767 0.381 0.512 0.880
EC 0.396 –0.575 –0.403 –0.554 0.336 – 0.482
TDS –0.583 –0.405 – 0.382 –0.447
Sal. 0.338 –0.590 –0.417 – 0.411 – 0.438
DO –0.571 –0.548 – 0.668 –0.393
pH 0.635 –0.367
Turb. – 0.460 0.885 0.458 0.480 –0.330 0.747 0.416
SD
NO2-N 0.616 0.403 0.369 0.523 0.377
NO3-N 0.521 0.371
SO40.364 0.401 –0.675 –0.695 0.421 0.816
SO30.362 0.3 61 –0.512
Silica 0.357 –0.494 – 0.353 –0.476 0.529
Alk. 0.831 –0.509 –0.418
Hard. 1–0.452 – 0.361 – 0.397
TSS 10.529 –0.450 0.490 –0.484 – 0.367 0.650 0.358 0.498
TP 1
O-PO4– 0.277 10.501 0.362
TAN 10.998 –0.582 – 0.827
NH31
NH41–0.576 –0.848
Na 0.251 1
K.2 61* –0.327 1
Chl_a 10.552
BOD50.278 1
p < 0.05
T. Akkan et al. / Desalination and Water Treatment 115 (2018) 261–270
268
4. Conclusion
The use of agricultural fertilizers is believed to increase
the nitrogen and phosphorus compound concentrations
due to the absence of freshwater plants that might affect
the increase in these ion concentrations in the dam lake
zone.
In the present study, the surface water quality of
the Sıddıklı Lake Dam was analyzed using multivariate
statistical analysis, the water quality index, and Carlson’s
Trophic State Index. The result of cluster analysis was
grouped, whereby four sampling sites into two clusters
according to similar features. Considering the increase of
NH4, O-PO4, decrease of DO concentrations were evaluated
according to SWQR as a Classes 3–4. Also, the Water
Research Center Water Quality Index had shown that the
water quality class is medium quality qater. Moreover,
Sıddıklı Dam Lake is in a hypereutrophic state as based on
the TP, in a hypolimnic state as based on the Chl_a, and in
an eutrophic state as based on the SD and mean TSI.
According to the PCA, the nutrient variable, organic
pollution, and solid groups are the dominant determinants
Table 4
Varimax rotated factor matrix for the whole data set
Variabl e PC 1 PC 2 PC 3 PC 4 PC 5 PC 6 PC 7
Eigenvalues 7.9 0 4 4.794 2.663 1.966 1.649 1.14 4 1.012
Percentage of variance 31.614 19.17 5 10.65 0 7. 8 6 4 6.596 4. 576 4.048
Accumulative % 31.614 50.789 61.439 69. 3 03 75.899 80.475 84.523
Factor loadings (varimax normalized)
WT 0.831 –0.301 0.310 – 0.134 0.196 – 0.153 0.025
EC 0.050 0.770 –0.256 0.193 –0.234 – 0.217 0.059
TDS –0.069 0.916 –0.088 0.139 –0.199 – 0.114 –0.073
Salinity – 0.074 0.920 – 0.107 0.158 – 0.194 –0.086 – 0.059
DO –0.245 0.10 7 –0.806 – 0.070 –0.379 –0.122 0.032
pH –0.248 0.124 0.860 –0.049 0.045 0.192 0.080
Turbidit y 0.348 –0.413 0.285 –0.295 0.615 0.204 –0.081
SD –0.011 0.662 0.482 –0.17 7 –0.097 0.239 0.084
NO2-N 0.247 – 0.322 0.392 – 0.111 0.585 – 0.149 0.172
NO3-N 0.098 – 0.179 –0.024 – 0.084 0.871 0.043 –0.041
SO40.782 –0.018 0.316 0.381 0.152 – 0.139 0.036
SO3–0.306 –0.452 0.019 0.312 0.129 0.654 –0.007
Silica 0.465 0.118 –0.209 0.052 0.087 0.063 0.614
Alkalinity –0.110 0.083 – 0.041 0.951 –0.120 –0.045 0.029
Hardness 0.185 0.203 –0.15 0 0.865 –0.196 – 0.032 0.034
TSS 0.486 –0.392 0.339 –0.381 0.427 0.247 0.117
TP 0.008 – 0.103 0.013 0.009 –0.039 0.017 0.917
O-PO40.293 – 0.371 0.481 – 0.173 – 0 .014 0.224 –0.297
TAN – 0.936 – 0.163 0.120 0.072 –0.137 0.026 –0.103
NH3 0.024 –0.342 0.823 –0.204 0.026 –0.076 –0.230
NH4 –0.94 4 – 0.142 0.069 0.085 – 0.140 0.031 – 0.089
Na 0.079 0.051 – 0.199 0.196 –0.070 – 0.877 – 0.046
K0.192 – 0.299 0.14 2 – 0.341 0.508 0.327 0.023
Chlorophyll a 0.706 –0.253 – 0.284 0.021 –0.003 0.227 0.148
BOD50.920 –0.138 0.129 0.036 0.051 – 0.174 –0.110
Extraction method: Principal component analysis.
Rotation method: Varimax with Kaiser normalization.
a Rotation converged in 8 iterations.
The factor loadings were classified according to loading values as; “strong (>0.75),” “moderate (0.75–0.50),” and “weak (0.50–0.30)”.
T. Akkan et al. / Desalination and Water Treatment 115 (2018) 261–270
269
of surface water quality in water bodies. Moreover, a
dangerous level of reduction has been observed on the water
bodies due to irrigation. It is evident that the anticipatory
measures taken by the local governments still remain
inadequate. In conclusion, all of our analysis indicate that
these important sources need to be monitored regularly.
If not, these pollutants can be hazardous both for human
health for aquatic organisms in the Sıddıklı Dam Lake, and
for agricultural products in irrigated areas.
Acknowledgments
We would like to thank BAPKOM (Ahi Evran University)
for financially supporting this project (Number: PYO_FEN_
FEN.4001.15.004). On the other hand, the preliminary results
of this article have been presented as oral presentation “A
Preliminary Review of Water Quality Parameter in Sıdıklı
Küçükboğaz Dam Lake (Kırşehir), Turkey” in the IBCESS
conference of Giresun University in 2016.
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