Water Quality Assessment of El-Salam Canal (Egypt) Based on Physico-Chemical Characteristics in Addition to Hydrophytes and their Epiphytic Algae

Water Quality Assessment of El-Salam Canal (Egypt) Based on Physico-Chemical Characteristics in Addition to Hydrophytes and their Epiphytic Algae
IJEDR
Water Quality Assessment of El-Salam Canal (Egypt)
Based on Physico-Chemical Characteristics in
Addition to Hydrophytes and their Epiphytic Algae
1Abdel-Hamid MI, 2*El-Amier YA, 3Abdel-Aal EI, 4El-Far GM
1,2,4Botany Department, Faculty of Science, Mansoura University, Mansoura, Egypt.
3National Institute of Oceanography and Fisheries (NIOF), Cairo, Egypt.
Water quality of El-Salam Canal was assessed using physico-chemical and certain biological
characteristics. Downstream increase of total soluble inorganic nitrogen (TSIN) and dissolved
reactive phosphorus (DRP) indicated increasing downstream eutrophication. The significant
(P ≤ 0.01) downstream increase of chloride indicated elevated pollution. Water quality index
(WQI) down (53) and up-stream (48) stations indicated bad to moderate condition,
respectively. The increase of N, P, heavy metals and WQI may be attributed to excessive input
of wastewater from El-Serw and Hadous drains. The highest concentrations of Fe (0.138 mg/l),
Mn (0.116), Zn (0.057), Cu (0.019), Pb (0.278) and Cd (0.016) were recorded at downstream
stations. Accumulation of these metals by hydrophytes followed the order: Fe ˃ Mn ˃ Zn ˃ Cu
˃ Pb ˃ Cd. Fifteen different hydrophytes were recorded with marked decline in species
richness during winter and at downstream stations. The epiphytic microalgae were
represented by 50 different taxa, belonging to six phylla including Cyanobacteria,
Chlorophyta, Charophyta, Bacillariophyta, Euglenophyta and Rhodophyta. Thespecies
composition and richness of the epiphytic microalgae was largely influenced by the plant
species, as the highest number of species (42 taxa) was recorded for Ceratophyllum
demersum and the lowest one (31 taxa) for Phragmites australis.
Key words: El-Salam canal, epiphytic algae, hydrophytes, water quality, artificial streams.
INTRODUCTION
Freshwater water supply has become limited due to a
host of multipurpose demands of the ever-increasing
population all over the world (Whittington and
McClelland, 1992). Egypt is one of the most over
populated countries that depends mainly on the River
Nile as the principal source of freshwater supply. It has
become a pressing need for Egyptians to regulate the
use of the River Nile water for agriculture and also for
the reclamation of desert land of Sinai Peninsula and
other Egyptian deserts. For this purpose, El-Salam
canal project was initiated in 1987 as an integral a part
of the North Sinai development project. The canal
represents the largest agricultural drainage water reuse
project in Egypt (FAO, 1989). The total quantity of the
canal water is nearly 4.45 billion m3 year-1 with an
approximate volumetric ratio of 1:1, Nile water to
drainage water. In quantitative terms 2.11 billion m3
year-1 of the Nile freshwater is mixed with 0.435 billion
m3year-1 from drainage water from El-Serw drain and
1.905 billion m3 year-1 water from Bahr Hadous drain
(Elkorashey, 2012).
The role of hydrophytes and microalgae of water quality
monitoring and assessment is well established (Knoben
et al., 1995).
*Corresponding author: Dr. Yasser A. El-Amier:
Department of Botany, Faculty of Science, University of
Mansoura, El-Mansoura, Egypt. E-mail:
yasran@mans.edu.eg, Telephone: 01017229120-
01280288892, (Office): +2 050 2223786, Fax: +2 050
2246781
Co-authors: Abdel-Hamid: mhamid@mans.edu.eg,
Abdel-Aal: emanibrahim2002@gmail.com, El-Far:
ghada_elfar@yahoo.com
International Journal of Ecology and Development Research
Vol. 3(1), pp. 028-043, November, 2017. © www.premierpublishers.org. ISSN: 2167-0449
Research Article

El-Amier et al. 029
The diversity and distribution of aquatic plants
represents a crucial issue for understanding the quality
of aquatic ecosystem due to their important ecological
roles and superiority to characterize the water quality of
their habitats. Aquatic biodiversity has enormous
economic and aesthetic value and is largely
responsible for maintaining and supporting the aquatic
environmental health. Under natural conditions,
hydrophytes and their epiphytic microorganisms can
co-exist as essential components of the aquatic
ecosystems (Zahran and Willis, 2003). While epiphytic
algae benefit from the macrophyte as a supporting
physical substrate and a source of secreted nutrients
(Irlandi et al., 2004), hydrophytes may benefit from the
reduced grazing pressure by herbivores (Fonseca and
de Mattos Bicudo, 2011).
Epiphytic algae constitute the majority of algal flora,
especially in shallow lakes, and contribute greatly to the
productivity of lakes (Soylu et al., 2011). Algae are
ideally suited for water quality assessment and have
been proven as reliable bioindicators because they
have rapid reproduction rates and very sensitive
responses to chemical changes, eutrophication and
pollution (Larson et al., 2012). Aquatic plants and
epiphytic microalgae play an important role in the
aquatic food chain, in which they affect the growth and
development of consumer of higher trophic levels
(Simkhada et al. 2006).
The cost of the environmental degradation due to water
pollution is relatively high with serious environmental
and human health consequences. Thus, conservation
strategies to protect and conserve aquatic life are
necessary to maintain the balance of nature and to
protect natural resources for next generations (EPA,
2002).
Since the El-Salam canal water is a mixture of Nile and
drainage waters, the quality of water must be regularly
monitored to address and mitigate any negative
environment impacts of the reuse of drainage water.
Considerable water quality monitoring of El-Salam
canal studies was carried based on physicochemical
characteristics, bacteria and microalgae (e.g. Rabeh,
2001; Sabae et al., 2001; Serag and Khedr, 2001;
Mostafa et al., 2002; El-Degwi et al., 2003; Othman et
al., 2012; Elkorashey, 2012). On the same track, the
present study aims primarily at assessing the water
quality of El-Salam canal depending on water
physicochemical characteristics, distribution and
composition of hydrophytes on addition to the
composition of epiphytic microalgae of two, most
abundant hydrophytes namely, Ceratophyllum
demersum and Phragmites australis.
MATERIALS AND METHODS
Study area
El-Salam canal project starts at the right bank of
Damietta Branch of the Nile River, about 3 km
upstream of the Farskour Dam, with a total length of
252.750 km. It consists of two main parts; the first part
(El-Salam canal) with 89.750 km long and lies west of
the Suez Canal. The second part (El-Sheikh Gaber
Canal) is located east the Suez Canal with a total
length of 163.000 km. Both parts are connected
through a 770 m long siphon, under the Suez Canal
(Elkorashey, 2012). Five sampling stations were
selected along El-Salam Canal (Figure 1). The selected
study area receives a considerable pollution load from
El-Serw drain and Hadous drain, discharging domestic
and agricultural wastewater. The sampling station 1 is
located on hundred meters east Damietta branch (the
eastern branch) of the River Nile where the canal
receives only Nile water. Therefore, this station is
considered as a reference station for all other
downstream stations. The sampling station 2 is located
5.0 km downstream the point of merging between of El-
Salam Canal and El-Serw drain, station 3 situated 5.0
km downstream of the merging point with Hadous
drain, station 4 is located 10 km downstream the station
2 and station 5 is located at the end of the first part of
the El-Salam canal just before the siphon connecting
the two parts of the whole canal.
The sampling programs
Water sampling and analyses
Water samples were collected during the mid-summer
2014 and mid-Winter 2015 from five selected stations
along El-Salam canal (Figure 1). Sampling procedure,
handling and processing followed by Danielson (2006).
Water temperature (oC), pH, total dissolved salts (TDS)
(mg l-1) and dissolved oxygen (DO) (mg O2 l-1) were
measured at the field using YSI 550 brand
multiparameter meter. The collected water samples
were kept cool in ice box until reaching the laboratory
where the chemical analyses were carried out. On the
same day of collection, the water samples were filtered
through Whatman GF/C glass filters and stored at 4 oC
for chemical analysis. Total alkalinity, total hardness,
chloride, nitrite-N, nitrate-N, ammonium, dissolved
reactive phosphorus (DRP) and the trace metals Pb,
Fe, Cd, Zn, Cu and Mn were analyzed according to the
Standard Methods for the Examination of Water and
Wastewater (APHA, 2005).
Hydrophytes sampling and analysis
Hydrophytes were collected from different sampling
stations, during the mid-summer 2014 and mid-Winter
2015, following the method of Danielson (2006). The
identification and nomenclature of the recorded species
followed Tackholm (1974) and Boulos (2005). The
collected plants were prepared for trace metals analysis
by washing with distilled water and air drying for 3-5
days. The air-dried biomass was, grinded and oven
dried at 50 oC till constant weight. A mass of 3.0 g dried
biomass was digested by nitric acid for determination of
heavy metals (APHA, 2005). Analysis of the metals Pb,
Fe, Cd, Zn, Cu and Mn followed the direct aspiration
into an air-acetylene flame (APHA, 2005).

Int. J. Ecol. Devel. Res. 030
Figure 1. A map showing the study area and the sampling stations
Sampling and preparation of epiphytic microalgae
Using a clean scissor, parts (mainly stem) of two
prevailing (at downstream station 2-5, only)
hydrophytes namely Ceratophyllum demersum and
Phragmites australis was clipped and put in separate
clean plastic bags. A measured volume of distilled
water was added to just moister the cut plant parts, the
bags were sealed and were kept in an icebox until
reaching the laboratories. The epiphytic microalgae
were carefully scraped from the surface of macrophyte
parts using a toothbrush, and then raised to a known
volume using distilled water. The epiphytic algal
suspension was preserved using 1% of Lugol's solution
(Prescott, 1978) for qualitative and quantitative analysis
of epiphytic microalgae. The surface area of the
hydrophyte part from which the epiphytic algae were
brushed was calculated using the wetted layer method
of Harrod and Hall (1962).
Qualitative and quantitative analyses of epiphytic
microalgae
Qualitative analysis of epiphytic microalgae was carried
out using light microscope at 400x magnification. The
identification of the algal taxa followed Smith (1920),
Fott (1969), Wehr and Sheath (2003), Komárek and
Zapomělová (2007) and Taylor et al (2007). For the
identification of diatoms, sub-samples of the microalgae
suspension were cleaned according to Cronberg
(1982). The quantitative analysis of epiphytic
microalgae was done by counting the algae scraped
from a known surface area, and preserved in a known
volume, using Sedqwick-Rafter cell of 1 ml capacity.
The biomass was expressed as absolute algal density
(cell cm¬-2).
Chemical and biological assessment of water
quality
The Water Quality Index (WQI) was calculated
according to the method proposed by the American
National Sanitation Foundation (NSF) (Kahler-Royer,
1999) depending on results of certain physical and
chemical parameters of water. Also, some water quality
relevant biological indices were used to evaluate the
trophic and pollution status of water samples. The
biological indices rely mainly on species composition
and abundance of epiphytic microalgae. These indices
included the diversity index (Shannon and Weaver,
1963), saprobic index (Pantle and Buck, 1955) and
trophic diatom index (TDI) (Kelly and Whitton, 1995).
Statistical analysis of data
Basic statistics and correlation analyses were carried
out using STATGRAPHICS (ver. 16.2.4) program.
Correlation coefficients are considered significant at
95% confidence level (P ≤ 0.05).
RESULTS AND DISCUSSION
Physical and chemical characteristics of water
Spatial and seasonal variations of different physico-
chemical parameters are listed in (Table 1). Marked
variations in values of different physical and chemical
parameters did exist between different sampling
stations and seasons. The water temperature varied
from 31.6oC to 34.5oC at summer and from 15.2oC to
15.6oC at winter, with mean annual value of 24.56oC
(Table 1). The water temperature showed strong

El-Amier et al. 031
Table 1. Mean values of three replicates (SDs were less than 5% of mean values) of physical and chemical parameters of water at different sampling stations in mid-summer 2014 and mid-winter
2015. Values are expressed in mg l-1
unless otherwise stated.
Parameters
Sampling stations Guidelines
St. 1 St. 2 St. 3 St. 4 St. 5
1Egyptian
law
No.48/1982
2Irrigation
Summer Winter Summer Winter Summer Winter Summer Winter Summer Winter
Temperature o
C 33 16 34.5 15.5 34.5 15.2 34.2 15.4 31.6 15.6 - -
pH (units) 7.88 7.74 7.85 7.72 7.72 7.67 7.72 7.62 7.75 7.73 7 – 8.5 6.0 – 8.5
TDS 210 300 230 520 360 570 720 860 550 390 - 2000
DO, mg O2l-1
7.8 14.5 6.5 12 7.3 13.3 5 10.3 8.1 7.5 ≥ 5 -
Total alkalinity, mg CaCO3 l-1
105 100 107.5 112.5 137.5 135 147.5 155 160 165 - -
Total hardness, mg CaCO3 l-1
68.75 33.75 67.5 48.13 95 57 136.25 73.125 130 82.5 <200 610
Chlorides 35.54 57.14 44.43 85.70 102.18 140.46 215.47 219.02 211.03 266.63 - 1063
Nitrite- N 0.008 0.062 0.035 0.072 0.189 0.134 0.217 0.126 0.326 0.122 - -
Nitrate- N 0.163 0.654 0.265 0.574 0.369 0.629 0.431 0.635 0.415 0.559 45 -
Ammonia- N 0.06 0.238 0.276 0.515 0.386 1.242 0.656 1.746 0.5 1.748 - -
TSIN 0.231 0.954 0.576 1.16 0.944 2.01 1.304 2.51 1.241 2.43 - -
DRP 0.36 0.022 0.415 0.025 0.443 0.027 0.519 0.216 0.491 0.021 2 -
Fe
Heavymetals
0.035 0.11 0.138 0.099 0.109 0.121 0.123 0.114 0.118 0.108 ≤ 1.0 5
Mn 0.081 0.089 0.077 0.093 0.116 0.088 0.093 0.098 0.097 0.105 ≤ 0.5 0.2
Zn 0.033 0.038 0.035 0.029 0.039 0.032 0.041 0.053 0.036 0.057 ≤ 1.0 2
Cu 0.011 0.012 0.009 0.017 0.017 0.019 0.014 0.015 0.015 0.017 ≤ 1.0 0.2
Pb 0.285 0.187 0.278 0.192 0.162 0.248 0.231 0.205 0.226 0.198 ≤ 0.05 5
Cd 0.006 0.009 0.007 0.011 0.009 0.016 0.012 0.10 0.013 0.008 ≤ 0.01 0.01
WQI 54 52 53 47 52 48 45 47 48 48
Water pollution status based
on WQI
Medium Medium Medium Bad Medium Bad Bad Bad Bad Bad
1
Egyptian standard regularities of article 60-law No. 48/1982 regarding minimum standards for the water quality of the Nile River.
2
FAO (1985)
TDS= Total dissolved salts; DO=Dissolved Oxygen; TSIN = Total soluble inorganic nitrogen; DRP = Dissolved reactive phosphorus; WQI = Water quality index.

Table 2. Pearson correlation matrix of different physical, chemical and biological parameters.
Parameters 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
Temperatureo
C 1 1
pH 2 0.62 1
Dissolved Oxygen 3 -0.78 -0.54 1
Total dissolved salts 4 -0.34 -0.8 0.26 1
Total alkalinity 5 -0.13 -0.47 -0.21 0.45 1
Total hardness 6 0.66 0.11 -0.71 0.21 0.58 1
Chlorides 7 -0.27 -0.48 -0.17 0.55 0.95 0.5 1
TSIN 8 -0.77 -0.75 0.38 0.56 0.66 -0.17 0.74 1
DRP 9 0.94 0.4 -0.75 -0.04 0.07 0.77 -0.07 -0.6 1
WQI 10 0.43 0.6 -0.2 -0.81 -0.46 -0.25 -0.66 -0.6 0.23 1
(A)
Diversity index 11 -0.26 -0.08 0.48 -0.26 -0.35 -0.46 -0.35 0.01 -0.47 0.12 1
Saprobic index 12 -0.33 -0.11 0.28 -0.38 -0.09 -0.35 -0.09 0.14 -0.56 0.07 0.77 1
TDI 13 0.17 -0.22 0.16 -0.13 -0.12 0.04 -0.27 -0.22 0.05 0.14 0.62 0.64 1
(B)
Diversity index 14 -0.06 0.37 -0.24 -0.26 0.37 0.3 0.45 0.08 -0.11 -0.23 -0.23 0.07 -0.4 1
Saprobic index 15 -0.02 -0.21 -0.17 0.17 0.76 0.59 0.74 0.37 0.01 -0.48 0.13 0.33 0.24 0.61 1
TDI 16 0.26 0.11 -0.18 0.25 -0.56 -0.02 -0.4 -0.44 0.28 -0.18 -0.18 -0.33 -0.09 -0.41 0.6 1
Water
Fe 17 -0.12 -0.01 -0.03 -0.11 -0.43 -0.47 -0.32 0.05 -0.24 0.19 0.41 0.3 0.09 -0.54 -0.41 0.43 1
Mn 18 -0.01 -0.4 -0.13 0.05 0.54 0.27 0.38 0.25 0.03 0.06 -0.14 0.38 0.49 0.02 0.41 -0.4 -0.24 1
Zn 19 -0.26 -0.33 -0.31 0.25 0.72 0.17 0.74 0.7 -0.12 -0.01 -0.43 -0.07 -0.39 0.18 0.28 -0.32 0.12 0.43 1
Cu 20 -0.6 -0.69 0.61 0.27 0.33 -0.18 0.31 0.52 -0.58 -0.34 0.49 0.68 0.6 0.01 0.51 -0.46 -0.18 0.56 0.03 1
Pb 21 0.19 0.46 -0.07 -0.12 -0.3 -0.03 -0.21 -0.2 0.16 0.06 0.14 -0.39 -0.44 0.04 -0.17 0.15 0.17 -0.91 -0.29 -0.6 1
Cd 22 -0.4 -0.68 0.27 0.72 0.3 -0.16 0.32 0.58 -0.11 -0.32 -0.43 -0.51 -0.37 -0.46 -0.31 0.12 0.09 0.06 0.48 0 -0.13 1
Macrophytes
Fe 23 -0.3 -0.85 0.18 0.73 0.42 0.05 0.42 0.62 -0.11 -0.46 0.12 0.07 0.27 -0.58 0.17 0.07 0.36 0.32 0.43 0.41 -0.27 0.63 1
Mn 24 -0.38 0.37 0.49 -0.49 -0.37 -0.53 -0.31 -0.1 -0.55 0.23 0.3 0.25 -0.22 0.5 -0.1 -0.32 -0.25 -0.39 -0.41 0.1 0.26 -0.42 -0.71 1
Zn 25 -0.4 -0.6 0.25 0.64 0.21 -0.23 0.24 0.53 -0.13 -0.25 -0.47 -0.53 -0.44 -0.45 -0.42 0.17 0.14 0.01 0.48 -0.09 -0.11 0.99 0.55 -0.37 1
Cu 26 -0.73 -0.05 0.77 -0.18 -0.23 -0.69 -0.13 0.29 -0.83 0 0.49 0.38 -0.14 0.31 -0.01 -0.38 -0.07 -0.34 -0.25 0.39 0.2 -0.15 -0.3 0.88 -0.13 1
Pb 27 -0.25 -0.72 0.24 0.51 0.01 -0.16 0.02 0.27 -0.16 -0.35 0.18 0.27 0.51 -0.69 -0.12 0.36 0.45 0.44 0.13 0.46 -0.57 0.44 0.8 -0.61 0.4 -0.31 1
Cd 28 -0.6 -0.52 0.23 0.76 0.35 -0.05 0.59 0.69 -0.35 -0.74 -0.23 -0.32 -0.58 0.1 0.12 0.19 0.11 -0.31 0.42 0.05 0.22 0.6 0.45 -0.11 0.6 0.17 0.15 1
- (A) Based on the epiphytic microalgae on Ceratophyllum demersum, (B) Based on the epiphytic microalgae on Phragmites australis,
- Listed are the coefficient of significant correlation (P ≤ 0.05)
TDS= Total dissolved salts; DO=Dissolved Oxygen; TSIN = Total soluble inorganic nitrogen; DRP = Dissolved reactive phosphorus; WQI = Water quality index

El-Amier et al. 033
positive correlation with pH (r = 0.62), total hardness (r
= 0.66) and DRP (r = 0.94) and exhibited negative
strong correlation with DO (r = -0.78) and TSIN (r = -
0.77), Cu in water (r = -0.6), Cu and Cd of hydrophytes
with correlation coefficient of -0.73 and -0.6,
respectively (Table 2).
Water temperature is considered as a potential
environmental factor controlling the aquatic life in
aquatic environments. Therefore obvious variations in
water temperature may contribute to the obvious
periodicity and succession of hydrophytes and algal
communities (Behrndt, 1990).
The pH of water was slightly alkaline (7.62 - 7.85) this
pH range complies with the Egyptian law No. 48/1982
(1982) and water standards for irrigation (FAO, 1985).
The water pH maintained strong positive correlations
with water temperature (r = 0.62) and WQI (r = 0.6)
and strong to very strong negative correlation with total
dissolved salts (r = -0.8), TSIN (r = -0.75), Cu (-
0.69) and Cd (-0.68) of water, Fe, Zn and Pb of
hydrophytes with correlation coefficient of -0.85, -
0.6 and -0.72, respectively (Table 2). Significant (P
≤ 0.05) gradual downstream decrease in DO but
obvious increase in TDS, total alkalinity, total hardness,
chlorides, nitrite-N, nitrate-N, ammonia-N and DRP
were recorded lengthwise the study area (Table 1).
Although the relatively low concentrations of DO at
downstream stations 2-5 during summer (5.0 – 8.1 mg
O2 l-1); this range is still within the approved guidelines
of the Egyptian law No. 48/1982. Dissolved oxygen
maintained strong negative correlation with water
temperature (r = -0.78), total hardness (r = -0.71) and
DRP (r = -0.75) (Table 2). This parameter maintained
strong positive correlation with Cu in water and
hydrophytes with coefficients of 0.61 and 0.77,
respectively. Dissolved oxygen, is an important
environmental parameter that decides ecological health
of a stream and protects the aquatic life (Chang, 2002).
Total alkalinity ranged between 105 and 160 mg
CaCO3.l-1 in summer and between 100 and 165
CaCO3.l-1, in winter (Table 1). The elevated level of
total alkalinity at downstream station may be attributed
to the excessive discharge of drainage wastewater.
Total alkalinity correlated positively with chloride (r =
0.95), TSIN (r = 0.66), saprobic index (r = 0.76) and Zn
in water (r = 0.72) (Table 2). In general, alkaline water
promotes high primary productivity (Kumar and
Prabhahar, 2012), and the alkalinity in the range from
50.08 to 499.84mg CaCO3.l-1 is common in most of the
freshwater ecosystems (Ishaq and Khan, 2013). Total
hardness ranged from 67.5 mg CaCO3 l-1 to 130 mg
CaCO3 l-1 and from 35.5 mg CaCO3 l-1 to 82.5 mg
CaCO3 l-1 during summer and winter seasons,
respectively. The total hardness maintained strong
negative correlation with DO (r = -0.71) and Cu in
macrophytes (r = -0.69) and strong positive correlation
with DRP (r = 0.77). Chloride concentrations increased
significantly from up to downstream stations, both in
summer (35.5 – 211.07 mgl-1) and in winter (57.2 –
266.6 mgl-1) (Table 1). Chloride content maintained
strong positive correlation with TSIN (r=0.74) and
saprobic index (r=0.74) and strong negative correlation
with WQI (r = -0.66) (Table 2).
The nitrite-N concentrations fluctuated between 0.035
and 0.326 mgl-1 during summer and from 0.072 to
0.134 mgl-1 during winter (Table 1). Nitrate-N ranged
from 0.265 to 0.431 mgl-1, during summer and from
0.574 to 0.635 mgl-1 during winter (Table 1). Ammonia-
N exhibited site to site obvious variation both in
summer (0.06 - 0.656 mgl-1) and winter (0.238 - 1.748
mgl-1). The total soluble inorganic nitrogen (TSIN)
ranged between 0.58 and 2.51 mgl-1 (Table 1),
indicating typical eutrophic water of the study area.
Vollenweider (1971) concluded that if TSIN above 0.3
mg l-1 it indicates eutrophic condition of water.
This result was further supported by the results of the
biological index TDI (Figure 7) that indicated typical
eutrophic nature of the sampled water. The TSIN
maintained strong positive correlation with total
alkalinity (r = 0.66), chloride (r = 0.74), Zn in water (r =
0.7), Fe and Cd in macrophytes with coefficients of 0.62
and 0.69, respectively, and strong negative correlation
with temperature (r = -0.77), pH (r = -0.75), DRP (r = -
0.6), WQI (r = -0.6) (Table 2).
Significant seasonal differences (P ≤ 0.05) in DRP were
recorded during this study (Table 1). Concentrations of
DRP ranged from 0.025 mgl-1 (St. 1) to 0.216 mgl-1 (St.
3), during winter and from 0.36 mgl-1 (St. 1) to 0.519
mgl-1 (St. 3), during summer (Table 1). Soria et al.
(1987) reported that the industrial and urbane
wastewater are rich in phosphorus. Therefore, the
relatively higher levels of downstream phosphorus can
be attributed to the wastewaters discharge from El-
Serw and Hadous drains. DRP showed very strong
positive correlation with temperature (r=0.94) (Table 2).
The values of WQI in the study area ranged from 45 to
53 with a mean value of 48, indicating poor water
quality (Table 1). The WQI show negative correlation
with TDS (r = -0.81), chloride (r = -0.66), TSIN (r = -0.6)
and Cd in macrophytes (r = -0.74) and positive
correlation with pH (r = 0.6) (Table 2).
Heavy metals content of water Six different heavy
metals namely Fe+2, Mn+2, Zn+2, Cu+2, Pb+2 and
Cd+2 were analyzed (Table 1). Although the
concentration of some heavy metals in water were
relatively higher than those permitted by Egyptian law
No. 48/1982 for irrigation water, they are still below the
limits approved by FAO (1996)for irrigation purposes
(Table 1). Some trace metals recorded high
concentration levels including Fe (0.138 mgl-1), Mn
(0.116 mgl-1), Zn (0.057mgl-1), Cu (0.019 mgl-1), Pb
(0.278 mgl-1) and Cd (0.016 mgl-1). However, the
concentrations of these heavy metals are lower than
the highest concentration reported by Hafez (2005) for
the same study area. The relatively higher levels of

Table 3. Distribution of hydrophytes at different sampling stations along the study area during summer 2014 and winter 2015.
Plant species
Sampling stations
St. 1 St. 2 St. 3 St. 4 St. 5
Summer Winter Summer Winter Summer Winter Summer Winter Summer Winter
Alternanthera sessilis (L.)
DC.
- - + + + - + - - -
Ceratophyllum demersum
L.
- - + + + + + + + +
Cyperus alopecoroids L.
Rottb.
- - - - + - - - - -
Cyperus articulates L. - - - - + - + - + -
Cyperus difformis L. - - - - + - - - - -
Echinochloa stagnina
(Retz.) P. Beauv.
+ - + + - - - - - -
Eichhornia crassipes (C.
Mart.) Solms
+ + + - - - - - - -
Ludwigia stolonifera (Guill.
& Perr.) P.
- - + - - - - - - -
Myriophyllum spicatum L. - - + + + + - - - +
Persicaria salicifolia (Willd)
Assenov
- - - - + + - - - -
Phragmites australis
(Cav.) Trin. Ex Steud.
- - + - + - + - + -
Pistia stratiotes L. + + + - - - - - - -
Potamogeton nodosus
Poir.
- - - - - - - + - -
Saccharum spontaneum L.
Mant. Alt
+ + - - - - - - - -
Typha domingensis (Pers.)
Poir. Ex Steud.
- - - - + - - - - +
Number of different
species at each station
4 3 8 4 9 3 4 2 3 3
+ = present, - = absent
trace metals in water may be attributed to the excessive
discharge of wastewater from Hadous and El-Serw
drains.
Distribution of aquatic macrophytes along the
study area
Fifteen different hydrophyte plants were recorded
during the period of study (Table 3). The distribution of
these aquatic plant species along El-Salam canal
varied from site to another and also from summer to
winter. The number of hydrophyte species recorded in
summer was relatively higher than those recorded in
winter at all stations. Gradual downstream decrease in
number of hydrophytes was obvious (Table 3). The
highest number of species (9 and 8 species) were
recorded at the sampling stations 3 and 2 during
summer, respectively, (Table 3). The most dominant
species which were recorded almost during summer
and winter seasons were Alternanthera sessilis,
Ceratophyllum demersum, Myriophyllum spicatum and
Phragmites australis. Other macrophyte species were
restricted to a particular sampling site, for example
Saccharium spontaneum was only recorded at
reference station 1, which receive only freshwater for
the eastern branch of the River Nile. The hydrophytes
Echinochloa stagnina, Eichhornia crassipes, Ludwigia
stolonifera and Pistia stratiotes were only reported at
the sampling station 1 and 2 (Table 3).
Karr and Chu (1999) stated that the ability to protect
biological resources depends on our ability to identify
and predict the effects of human actions on biological
systems; thus, the data provided by the living
organisms can be used to estimate the degree of
environmental impact and its potential danger for other
living organisms. Aquatic hydrophytes may play a
central role in the biological monitoring since diversity
of species and varying distribution of macrophytic
vegetation are reliable indicators of the water quality of
any aquatic ecosystem (Ravera, 2001).
Heavy metals content of hydrophytes
The concentration ranges of different trace metals in
biomass of different aquatic hydrophytes were Fe (15-
20.4 mg g-1), Mn (10.6-14.8 mg g-1), Zn (5.81-10.3 mg
g-1), Cu (1.22-3.04 mg g-1), Pb (1.3-2.45 mg g-1) and Cd
(0.22-0.73 mg g-1). (Table 4). Accordingly the
bioaccumulation pattern of these trace elements in
biomass of different hydrophytes followed the order Fe
˃ Mn ˃ Zn ˃ Cu ˃ Pb ˃ Cd (Table 4). Non-significant (P
≤ 0.05) differences were recorded for bioaccumulation
of different heavy metals by different hydrophytes
(Table 4).Heavy metals of biomass of different
hydrophytes maintained strong to very strong
relationship (P ≤ 0.05) with the physical and chemical
parameters of water, in addition to the heavy metals

El-Amier et al. 035
Table 4 (Cont.). Heavy metals content (ppm) of hydrophytes at different sampling stations along the study area during mid-summer 2014
and mid-winter 2015. Listed are the mean concentration values. Standard deviations ranged between 0.5 and 3% of mean values.
Plant species season
Cu Pb Cd
St.1 St.2 St.3 St.4 St.5 St.1 St.2 St.3 St.4 St.5 St.1 St.2 St.3 St.4 St.5
Alternanthera
sessilis
S - 2.09 2.19 2.03 - - 1.78 1.33 1.94 - - 0.46 0.29 0.57 -
W - 2.13 - - - - 1.51 - - - - 0.38 - - -
Ceratophyllu
m demersum
S - 2.57 1.57 2.07 2.29 - 1.92 2.32 1.3 2.01 - 0.59 0.34 0.26 0.64
W - 2.47 2.8 1.85 1.65 - 2.04 2.12 2.14 1.82 - 0.46 0.53 0.63 0.46
Cyperus
alopecoroids
S - - 2.75 - - - - 1.5 - - - - 0.43 - -
W - - - - - - - - - - - - - - -
Cyperus
articulates
S - - 1.22 2.61 1.87 - - 2.2 1.45 1.9 - - 0.22 0.4 0.53
W - - - - - - - - - - - - - - -
Cyperus
difformis
S - - 1.31 - - - - 2.23 - - - - 0.26 - -
w - - - - - - - - - - - - - - -
Echinochloa
stagnina
S 1.61 1.68 - - - 2.06 1.6 - - - 0.56 0.36 - - -
W - 1.86 - - - - 1.44 - - - - 0.31 - - -
Eichhornia
crassipes
S 1.48 1.81 - - - 2.01 1.65 - - - 0.53 0.4 - - -
W 2.26 - - - - 1.56 - - - - 4 - - - -
Ludwigia
stolonifera
S - 2.45 - - - - 1.89 - - - - 0.56 - - -
W - - - - - - - - - - - - - - -
Myriophyllum
spicatum
S - 2.33 1.98 - - - 1.84 2.45 - - - 0.53 0.44 - -
W - 2.62 2.24 - 2.16 - 2.08 2.26 - 1.97 - 0.49 0.73 - 0.6
Persicaria
salicifolia
S - - 2.88 - - - - 1.54 - - - - 0.47 - -
W - - 1.36 - - - - 1.98 - - - - 0.5 - -
Phragmites
australis
S - 1.96 2.47 2.35 1.74 - 1.72 1.42 1.38 1.86 - 0.53 0.37 0.33 0.5
W - - - - - - - - - - - - - - -
Pistia
stratiotes
S 1.74 2.19 - - - 2.09 1.81 - - - 0.59 0.5 - - -
W - 2.35 - - - - 2 - - - - 0.43 - - -
Potamogeton
nodosus
S - - - - - - - - - - - - - - -
W - - - 2.11 - - - - 2.21 - - - - 0.7 -
Saccharum
spontaneum
S 1.98 - - - - 2.14 - - - - 0.06 - - - -
W 1.99 - - - - 1.48 - - - - 0.34 - - - -
Typha
domingensis
S - - 3.04 - - - - 1.58 - - - - 0.5 - -
W - - - - 2.33 - - - - 2.02 - - - - 0.67
Mean values 2.07 1.85 0.58
counted in water samples (Table 2). Fe maintained
strong positive correlation with TDS (r = 0.73), TIN (r =
0.62), Cd in water (r = 0.63) and Pb in hydrophytes (r =
0.8), strong negative correlation with Mn (r = -0.71) and
very strong correlation with pH (r = -0.85) (Table 2). Mn
exhibited very strong positive correlation with Cu in
hydrophytes (r = 0.88) and very strong negative
correlation with Pb in hydrophytes (r = -0.61). Zn
maintained strong positive correlation with TDS (r =
0.64), very strong positive correlation with Cd in water
(r = 0.99) and strong negative correlation with pH (r = -
0.6) (Table 2). The Cu in hydrophytes correlated
strongly with water temperature (r= -0.73), DO (r= 0.77)
and total hardness (r= -0.69) and very strong
correlation with DRP (r=-0.83) and Mn (r= 0.88) in
hydrophytes (Table 2). Pb in hydrophytes maintained
strong negative correlation with pH (r = -0.72), diversity
based on the epiphytic microalgae of Phragmites
australis (r = -0.69) and Mn in macrophyte (r = -0.61)
and very strong positive correlation with Fe in
hydrophytes (r = 0.8). Cd showed strong positive
correlation with TDS (r = 0.76), TIN (r = 0.69) and Cd in
water (r = 0.6) and strong negative correlation with
water temperature (r = -0.6) and WQI (r = -0.74) (Table
2).
The results indicated substantially higher heavy metal
content of biomass of all hydrophytes (Table 4)
compared to that of water (Table 1). This finding may
indicate that hydrophytes recorded in this study are
good accumulator of heavy metals and may play
important role in metal bioremediation. Also, the
obvious downstream decrease in species number of
hydrophytes with the marked increase in water
pollution, indicated by WQI, highlighted these
hydrophytes as good bioindicators of water quality
along the study area.
Aquatic hydrophytes are good indicators of water
quality because of their remarkable ability to
accumulate and tolerate high concentrations of the
heavy metals, which may be 106 times as high as their
concentrations in aquatic environment (Chung and
Jeng, 1974; Kovacs et al., 1984; Matagi et al., 1998;
Baldantoni et al. 2005; Duman et al. 2009; Fawzy et al.
2012). Bioaccumulation of heavy metals from water

Table 5. Seasonal and spatial variation in population density (cell cm-2
) of different epiphytic microalgae of the hydrophytes Ceratophyllum demersum and Phragmites australis along the study area.
Identified microalgae species
Density (cellcm-2
) on different macrophyte plants
Ceratophyllum demersuma
Phragmites australisa, b
St.2 St.3 St.4 St.5 St.1 St.2 St.3 St.4 St.5
S W S W S W S W S S S S S
Cyanobacteria
Jaaginema subtilissimum (Kützing ex Forti) Anagnostidis&Komárek 102242 - - - - - - - - - - -
Pseudoanabeana sp 97720 63525 5402 - 66186 15770 20377 - 242262 104395 751355 47013
Total cells cm-2
199962 63525 5402 - 66186 15770 20377 - 242262 104395 751355 47013
Chlorophyta
Characium hookeri (Reinsch) Hansgirg 2880 18098 2970 2824 3791 6740 - 5154 - 11475 44464 10290
Chlorella sp - - - - - - - - - - 22232 -
Monactinus simplex (Meyen) Corda, nom. Inval 36001 - - - - - - - - - - -
Monoraphidium sp - 9049 891 2824 1625 3370 - - 5986 4590 44464 -
Oedogonium sp 27360 153835 38903 162381 38456 21903 16486 37797 6651 195075 135412 37487
Scenedesmus bijuga (Turpin) Lagerheim - - - - - - - - 5321 - - 2940
Scenedesmus quadrispina Chodat - - - - - - - - 5320.76 - 18189.7 -
Scenedesmus sp - 18098 1188 - 10833 - 1081 - - - - -
Stylosphaeridium stipitatum (Bachmann) Geitler &Gimesi - - - - - 3369.75 - - - - - -
Ulothrix sp - - 14254 - 16249 - - - - 64260 216255 -
Total cells cm-2
66241 199080 58205 168029 70954 35382 17567 42951 23278 275400 481016 50717
Charophyta
Closterium sp - 9049 297 - 15707 - - - - - - -
Cosmarium sp 2880 - - - 1083 3370 - - - - 6063 1470
Mougeotia sp 17280 81442 - 35300 48206 6740 - 18899 - - - 162442
Spirogyra sp 76321 298621 - 264046 57955 90983 - 226782 - - 60632 -
Total cells cm-2
96482 389112 297 299346 122951 101093 - 245681 - - 66696 163912
Bacillariophyta
Aulacoseira granulata (Ehrenberg) Simonsen - - - - - - - - - 4590 - -
Cocconeis placentula Ehrenberg 7200 27147 891 55069 1083 23588 5676 6872 4656 4590 - -
Cyclotella meneghiniana Kützing 1440 - 594 4236 15707 3370 4594.49 6872 - 4590 12127 2205
Cymbella kappii (Cholnoky) Cholnoky - 18098 - - - - - - 2660 - - -
Diatoma vulgaris Bory - - - - 542 - - - - - - -
Entomoneis paludosa (W.Smith) Reimer - - - - - 1685 - - - - - -
Fragilaria biceps (Kützing) Lange Bertalot 10080 27147 891 15532 2708 2190 810.792 15462 - - - -
Gomphonema parvulum Kützing - 0 3861 - 5958 - - 15462 - - 36379 -
Gomphonema laticollum E. Reichardt 4320 36196 - 8472 2708 3370 810.792 - 9311 - - -

El-Amier et al. 037
Table 5. Cont.: Seasonal and spatial variation in population density (cell cm-2
) of different epiphytic microalgae of the hydrophytes Ceratophyllum demersum and Phragmite saustralis along the study
area.
Identified microalgae species
Density (cellcm-2
) on different macrophyte plants
Ceratophyllum demersuma
Phragmites australisa, b
St.2 St.3 St.4 St.5 St.1 St.2 St.3 St.4 St.5
S W S W S W S W S S S S S
Gomphonema minutum (C. Agardh) C. Agardh - - - - - - - - - - 20211 -
Gomphonema pseudoaugur LangeBertalot - - - - - - - - 8646 6885 40421 -
Gyrosigma acuminatum (Kützing) Rabenhorst - 27147 - - - - - - - - - -
Gyrosigma attenuatum (Kützing) Rabenhorst - - - - 1625 - - - - - - -
Gyrosigma fasciola (Ehrenberg) J.W. Griffith & Henfrey - - 297 - - 6740 1891.85 - - - - -
Gyrosigma parkeri (Harrison) Elmore - - - - - 1685 - - - - - -
Mastogloia smithii Thwaites ex W.Smith 9049 - 4236 - - - - - - - - -
Melosira varians C. Agardh - 54295 - 22592 2167 8424 - 18899 - - - -
Navicula antonii Lange Bertalot - - - - - 8424 - - 6651 - 30316 5145
Navicula germainii Wallace 7200 - - - - - - - 1995 - - -
Navicula recens (Lange Bertalot) Lange Bertalot - 18098 - 40948 17874 - 14053.7 72158 - 9180 18190 -
Navicula schroeteri Meister - - 4751 - - - - - - - - -
Navicula trivialis LangeBertalot 20160 126688 - - - - - - 10642 - - -
Nitzschia capitellata Hustedt, nom. Inval - 45245 - - - 15164 - - - - - -
Nitzschia acicularis (Kützing) W. Smith 2880 - - - 1625 - - - - - 4042 -
Nitzschia clausii Hantzsch - 9049 - - - 1685 - - - - - -
Nitzschia gracilis Hantzsch - - 1782 - - - - 53260 - - - -
Nitzschia linearis W.Smith 18720 90491 2673 46596 2167 16849 - 20617 7981 11475 - -
Nitzschia palea (Kützing) W.Smith - - - 24004 22207 - 6486.34 - - 2295 36379 2205
Nitzschia paleacea Grunow - - - - - - - 41233 6651 2295 - -
Nitzschia sigma (Kützing) W.Smith - - - - - - - - - 2295 2021 -
Ulnaria ulna (Nitzsch) P.Compère - - - - - - - - 1330 - - -
Total cells cm-2
81050 479603 19975 217450 76371 112887 34323.5 250835 60524 48195 200086 9555
Euglenophyta
Euglena proxma P.A.Dangeard - - 594 - - 5055 - - - - - -
Phacus pleuronectes (O.F.Müller) Nitzsch ex Dujardin - - - - 542 - - - 665 - 2021 -
Total cells cm-2
- - 594 - 542 5055 - - 665 - 2021 -
Rhodophyta
Compsopogon sp 60481 696782 20194 124257 31415 - 10270 51542 115063 - 252634 -
Total cells cm-2
60481 696782 20194 124257 31415 - 10270 51542 115063 - 252634 -
Total cell count 504215 1828102 104668 809083 368418 270187 82538 591009 441791 427991 1753808 271197
Number of identified epiphytic microalgae species 18 20 18 14 24 21 11 14 17 14 20 9
S= summer, W = winter, St. = station; a= Both hydrophytes were not recorded at the reference station 1.
b= this hydrophyte was completely absent at all station during winter.

Figure 2. Total number of epiphytic microalgae taxa of Ceratophyllum demersum and Phragmites
australis and their distribution among different taxonomic phyla.
Figure 3. Number of different epiphytic microalgae of Ceratophyllum demersum recorded in mid-summer
2014 and mid-winter
environment depends on the habit of aquatic
macrophyte i.e. free-floating, submerged and emergent,
plant species, plant organ and numerous abiotic
factors, making all of them indispensable for bio-
filtration and heavy metal cycling in aquatic ecosystems
(Lewis, 1995; Rascioa and Navari-Izzo, 2011).
Species composition and density of epiphytic
microalgae
According to the relatively higher abundance and
seasonal occurrence of the two hydrophytes namely C.
demersum and P. australis along the study area, their
epiphytic microalgae were qualitatively and quantitative
analyzed. The epiphytic algal community of El-Salam
canal were represented by 50 taxa, which belonging to
6 major algal phylla namely Cyanobacteria (2),
Chlorophyta (10), Charophyta (4), Bacillariophyta (31),
Euglenophyta (2) and Rhodophyta (1) (Figure 2, Table
5). Interesting results emerged from investigating the
distribution of different epiphytic microalgae groups on
the two hydrophytes C. demersum and P. australis
(Figure 2). The highest species richness (42 taxa) was
recorded for C. demersum while the lowest one (31
taxa) was recorded for P. australis. On station level, the
number of the identified algal taxa varied from a highest
value of 24 species (Figure 3) to a lowest one of 9
species (Figure 4). The most common epiphytic
microalgae include Pseudoanabeana sp, Characium
hookeri, Monoraphidium sp, Oedogonium sp,

El-Amier et al. 039
Figure 4. Number of different epiphytic microalgae of Phragmites australis recorded in
mid-summer 2014.
Ulothrix sp, Cosmarium sp, Mougeotia sp, Spirogyra
sp, Cocconeis placentula, Cyclotella meneghiniana,
Cymbella kappii, Fragilaria biceps, Gomphonema
parvulum, Gomphonema laticollum, Navicula recens,
Navicula trivialis, Nitzschia linearis, Nitzschia palea,
Nitzschia paleacea, Phacus pleuronectes and
Compsopogon sp. (Table 5). The % density
contribution of different epiphytic microalgae groups to
the density of total community varied greatly depending
on hydrophyte species and sampling stations (Figures
5 and 6). On an average basis the % density
contributions (values in parenthesis) of different major
algal phyla were Cyanophyta (21.86%, 2.33% and
34.85%), Chlorophyta (27.33%, 13.01% and 28.94%),
Charophyta (13.19%, 34.31% and 16.06%),
Bacillariophyta (24.36%, 34.35% and 9.97%),
Euglenophyta (0.18%, 0.47% and 0.08%) and
Rhodophyta (13.07%, 15.15% and 10.11%), to the
density of epiphytic microalgae communities of C.
demersum in summer, in winter (Figure 5) and that of
P. australis in summer (Figure 6), respectively.
Comprehensive seasonal and spatial quantitative data
about the densities (cell cm-2) of different epiphytic
microalgae of C. demersum and P. australis are given
in Table 5. These data clearly indicated substantial
differences in cell densities of individual's epiphytic
microalgae that were largely dependent on season,
plant species and sampling sites. It must be stressed
that, the identified epiphytic microalgae exhibited
distinctly substantial size difference. Therefore the cell
count in this case cannot be considered as an accurate
measure of relative abundance or biomass. Not only
obvious seasonal and local variations did exist in cell
densities of different epiphytic microalgae but also
marked variations in number of different species were
also evident. The evident seasonal, local, species-
dependent variations in cell densities and species
richness of different epiphytic microalgae may be
attributed to the variations of different environmental
factors of the study area including, for instance
temperature (Marcarelli and Wurtsbaugh, 2006), light
(Tuji, 2000), nutrient availability specially nitrogen and
phosphorous (Larson et al., 2012), water quality and
system hydrodynamics (Moschini-Carlos et al., 2000),
plant species (Hadi and Al-Zubadi, 2001), hydrological
regimes (Algarte et al., 2009) and biological control by
grazing (Rosemond et al., 1993).
Larger algal species or those with slower growth rates
are able to persist perennially while Cyanobacteria
have seasonal fluctuations in abundance (Greenwood
and Rosemond, 2005). The quantitative abundance of
Cyanobacteria during summer season (Figures 5 and
6) may be mainly attributed to the relatively higher
temperature and lower values of alkalinity (Bhat et al.,
2011). Light levels can also greatly influence algal
growth and abundance as a result of differential photo-
pigment adaptations (Davis and Lee, 1983). Diatoms
and red algae have greater tolerances and/or
preference to low light levels than green algae which
grow better under higher light intensities (Huang et al.,
2009). This results agree with our results in which the
highest cell densities of diatom species and the red
alga Compospogon sp., were in winter (Table 5). Also,
the dominance of diatom species during winter (Table
5) may be attributed to its ability to thrive well in
relatively cold waters (Sarwar and Zutshi, 1988).
However, Maraşlıoğlu and Dönmez (2016) have stated
that algal density is generally high in autumn while
decreasing in spring, summer and winter. Apparently,
our findings seem to be opposite to each other, but in
fact they support each other. Because the average
water temperature values in winter (15.54˚C) of our
study area correspond to the autumn water temperature
values of most other regions.
Biological indices
Epiphytic algae are good indicators of water quality and
environmental changes due to their sensitivity to

Figure 5. Percentage contribution of different groups of epiphytic microalgae to the total epiphytic community of
Ceratophyllum demersum during mid- summer 2014 and mid-winter 2015.
Figure 6. Percentage contribution of different groups of epiphytic microalgae to the total epiphytic community of
Phragmites australis during mid-summer 2014.
Figure 7. Spatial variation in diversity, saprobity and TDI indices of epiphytic microalgae attached to the
immersed shoots of the hydrophytesCeratophyllum demersum and Phragmites australis along El-Salam canal.
external sources of pollutions (Barbour et al., 1999).
Armitage et al. (2006) revealed that the accelerated
eutrophication in aquatic environments may alter
natural algal biomass and community composition. In
this study, the values of diversity, saprobity and trophic
diatom index, based on epiphytic microalgae species of
St. 1 St. 2 St. 3 St. 4 St. 5 St. 1 St. 2 St. 3 St. 4 St. 5
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2.2
2.4
2.6
2.8
3.0
Sampling stations
Diversity
Ceratophyllum demersum Phragmites australis
Light pollution
Moderate pollution
Heavy pollution
Summer Winter
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2.2
2.4
2.6
2.8
3.0
3.2
3.4
Saprobity
Eutrophic
Mesotrophic
Oligotrophic
Ultraoligotrophic
Sampling stations
Summer Winter
0
10
20
30
40
50
60
70
80
90
100
TDI
Sampling stations
Summer Winter
Very low nutrient concentrations
Low nutrient concentrations
Intermediate nutrient concentrations
High nutrient concentrations
Very high nutrient concentrations

El-Amier et al. 041
Ceratophyllum demersum and Phragmites australis,
revealed the deterioration of water quality along El-
Salam canal (Figure 7). The values of diversity ranged
from 1.09 to 1.67 indicating a moderate pollution status
of El-Salam canal during summer. Meanwhile, during
winter the diversity values for all stations along El-
Salam canal were below 1.0 (Figure 7), indicating the
heavy pollution status of the canal. The values of
saprobity for the two seasons were between the 1.7 to
3.0 indicating the mesotrophic status of the canal.
Similarly, the values of TDI ranged from 60 to 100,
indicating the presence of high concentrations of
nutrients in the canal during summer and winter (Figure
7).The results of biological indices are supported by
that of WQI, that indicate moderate pollution of the
study area. Strong and significant (P ≤ 0.05) correlation
was recorded between the different biological indices.
Also, weather the substrate of the epiphytic algae was
Ceratophyllum demersum or Phragmites australis, the
saprobic index maintained strong positive correlation
with diversity index and TDI with correlation coefficients
of 0.6 and 0.77, respectively (Table 2). Also, saprobic
index and TDI, which based on epiphytic algae on
Ceratophyllum demersum, showed strong positive
correlation with Cu of water with coefficients of 0.68
and 0.6, respectively.
CONCLUSIONS
In conclusion both physico-chemical and biological data
indicated progressive water quality deterioration from
the reference station 1, receiving only Nile water to the
downstream station that receive excessive wastewater
discharges from El Serw and Hadous drains. The
physico-chemical analysis, hydrophytes and epiphytic
microalgae proved good integrated tools for reliable
assessment of water quality of El-Salam canal.
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Accepted 07 May, 2017.
Citation: Abdel-Hamid MI, El-Amier YA, Abdel-Aal EI,
El-Far GM (2017). Water Quality Assessment of El-
Salam Canal (Egypt) Based on Physico-Chemical
Characteristics in Addition to Hydrophytes and their
Epiphytic Algae. International Journal of Ecology and
Development Research, 3(1): 028-043.
Copyright: © 2017 El-Amier et al. This is an open-
access article distributed under the terms of the
Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any
medium, provided the original author and source are
cited.

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