This study analyzed water quality and assessed potential risks in tributary rivers in San Fernando, Bukidnon, Philippines. Water samples from 3 sites on the Tigua River and 1 site on the Salug River were tested for physicochemical parameters and heavy metals. Results found slightly lower dissolved oxygen and higher turbidity, conductivity, salinity, and total dissolved solids in tributaries near populated areas, likely due to human impacts. However, all parameters were within national standards and the risk assessment found no potential pollution. Further monitoring was recommended to better understand impacts on these important water sources.

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266 | Galarpe et al.
RESEARCH PAPER OPEN ACCESS
Water quality and risk assessment of tributary rivers in San
Fernando, Bukidnon Philippines
Van Ryan Kristopher R. Galarpe*1
, Kristal Jane L. Heyasa2
, Brawner Brian L. Heyasa3
1
Department of Environmental Science and Technology, University of Science and Technology of
Southern Philippines, Philippines
2
Bachelor of Medicine, College of Medicine, University of Northern Philippines, Philippines
3
Department of Electronics Engineering, University of Science and Technology of Southern Philippines,
Philippines
Article published on July 30, 2017
Key words: San Fernando, Bukidnon, Tigua river, Salug river, River tributaries, Heavy metals
Abstract
Bukidnon, Philippines being identified as an agricultural province needs to ensure water sustainability vital to
support its agroeconomy. This study considered Tigua River with three river tributaries and Salug River with
single station in San Fernando, Bukidnon. Analysis employed single sampling technique to initially assess river
tributaries. Studied water quality parameters were pH, temperature, dissolved oxygen (DO), oxidizing redox
potential (ORP), turbidity, salinity, conductivity, total dissolved solids (TDS) using portable pre-calibrated
meters. Nitrates were also determined using Bruccine colorimetric method. Analyzed heavy metals in total
form were copper (Cu), cadmium (Cd), lead (Pb), and chromium (Cr) using Flame-Atomic absorption
spectrophometry (AAS). Overall, studied river tributaries passed national regulation with risk quotient (RQ)
showing no potential pollution. Heavy metals were below detection limit indicating less traceable quantities in
river tributaries. Salinity, conductivity, and TDS showed positive correlation. The study was preliminary and
further monitoring may be needed.
*Corresponding Author: Van Ryan Kristopher R. Galarpe  vanryangalarpe@gmail.com
Journal of Biodiversity and Environmental Sciences (JBES)
ISSN: 2220-6663 (Print) 2222-3045 (Online)
Vol. 11, No. 1, p. 266-273, 2017
http://www.innspub.net

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267 | Galarpe et al.
Introduction
The province of Bukidnon coined as the watersheds of
Mindanao, Philippines (Broad and Cavanagh, 1988)
have a total of alienable and disposable land of
336,412 ha (40.56%) while 492,966 ha are forestland.
Covered in these land classification are two major
river watersheds, namely, Salug and Pulangi
(Sumbalan et al., 2001). The major river tributary to
these watersheds are the Tigua River as the water
source for Pulangi and the Salug River as the water
source for the Salug River watershed and the Davao
River on the further south. Both rivers are located in
the munipality of San Fernando, an agricultural and
forested area in the province of Bukidnon.
As a major tributary of the river watersheds in the
province of Bukidnon, a need to secure its water
resources upstream is viewed essential. In the past
this municipality had experienced deforestation,
flashflood, and drought prompting civil groups and
activists to rally for environmental protection
(Bautista, 2001) which were successful as measure of
conservation efforts. However, no available studies
were conductedto evaluate present institutional
arrangements for sustainable river water quality or
watersheds.
In particular, the munipicality of San Fernando had
been studied to have a new species and new records of
the genus Doliops Waterhouse, 1841 (Coleoptera:
Cerambycidae) (Barševskis, 2014; Cabras and
Barševskis, 2016). Similarly, Tigua River had been
studied to be one of the diverse rivers in Bukidnon
with gastropod species (Galan et al., 2015). Despite
the existing studies on biodiversity no specific
published study dealt on water quality of these river
tributaries. Thus, this study was conducted to provide
a preliminary study on river tributary water quality in
San Fernando, Bukidnon. The objectives were to
determine selected physicochemical water quality
paramters, determine its status with reference to
standards, and to derive environmental risk
assessment (e.g. risk quotient and river comparison).
Materials and methods
Sampling site
The study site consisted of three sub rivers of Tigua river
and one station in Salug river (Fig. 1-2 & Table 1). The
Tigua river is the main river tributary of Pulangi river in
Bukidnon while Salug river is the tributary river of
Davao river. Both water bodies were located in San
Fernando, Bukidnon. The coordinates of the study sites
were identified using GPS EtREX 20 (Table 1).
Table 1. Description of studied river tributaries in San Fernando, Bukidnon Philippines.
River Station
code
Description Specific Locations Barangays
adjacent to the
river
Latitude Longitude
Salug S1 Salug
Bridge
San Jose river stream to
Salug river
San Jose '23.7430E 125 '45.297007N
Tigua T1 Bonacao
Bridge
river stream from Davao
Region-Bonacao
Bonacao
Sto Domingo
'23.8540E 125 '47.9510N 07
T2 Supitan
Bridge 2
intersection of 2 river
streams from Kibungkog
and Bonacao
Namnam
Iglugsad
'22.5390E 125 '50.3310N 07
T3 Halapitan 6 km from Pulangi river
outflow
Halapitan '19.8670E 125 55.5390N 07
a b
Fig. 1. a) Salug river station (S1) and b) the Tigua river tributary station (T1).

3. J. Bio. & Env. Sci. 2017
268 | Galarpe et al.
Fig. 2. Map of the study site in San Fernando,
Bukidnon. Tigua river consisted of three river
tributaries connecting towards Pulangi River. Salug
river station outflow towards Davao river.
Sampling technique
One grab sampling on January 1, 2017 was employed
in this study. All containers used were polyethylene
bottles (PET) prewashed with distilled water three
times. Upon sampling the container itself were
washed three times with the river water prior to
sample collection and processing in the laboratory.
Surface river waters were taken from four sampling
stations approximately 3-5 m from the above ground.
Collected samples were subjected to lower
temperature, preventing chemical absorption and ion
interference prior to heavy metal analyses (Galarpe
and Parilla, 2014).
Physicochemical analyses
The turbidity meter LaMotte 2020 was used to
analyze the turbidity of the water samples. The pH,
temperature, conductivity, sanility, TDS, and ORP
were analyzed using Oyster meter. The DO of the
water samples were analyzed using Acorn Series DO
Meter OAKION Manufacturing (code 01X555902).
The analyses of Pb, Cd, Cu, Cr, and nitrates were
conducted in the FAST Laboratories. The Pb in total
form was analyzed using 3030 E. Nitric acid
digestion/3111 B. Direct air acetylene Flame AAS
method. The Cd, Cu, and Cr in total form were
analyzed using 3030 F. Nitric acid-hydrochloric acid
digestion/3111 B. Direct air-acetylene Flame AAS
method, respectively. Nitrates was analyzed using
973.50 Bruccine colorimetric method. All samples
were analyzed in triplicates. Methods of analyses
were adopted from AOAC International (2012) and
APHA-AWWA and WEF (2012).
Data Analyses
One Way-ANOVA was employed to compare the
physicochemical parameters in all study sites at 0.05
level of significance. The Pearson correlation was
similarly used to determine association among
parameters studied. Further, all results were
expressed in terms of mean. To derive an
environmental risk estimate all results were subjected
to Risk Quotient (RQ) analysis. The RQ was
calculated as the ratio between the determined
concentration and the available standard (GEF/
UNDP/IMO, 2004). The calculated RQ of >1 can
gauge the physiochemical parameter to likely pose
environmental risk. The DAO 35 standard was used
for estimating RQ in river water samples (Table 2).
Table 2. Reference standard in the study.
Standard Description
DENR/DAO 34
Class AA
Public Water Supply Class I. This class is intended primarily for waters having watersheds
which are uninhabited and otherwise protected and which require only approved
disinfection in order to meet the National Standards for Drinking Water (NSDW) of the
Philippines.
DENR/DAO 34
Class A
Public Water Supply Class II. For source of water supply that will require complete
treatment (coagulation, sedimentation, filtration, and disinfection) in order to meet the
NSDW.
PNSDW (2007) Drinking water guideline

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269 | Galarpe et al.
Results and discussion
Physicochemical analyses
The overall physicochemical parameters were
relatively comparable. Both temperature (27-28 deg
C) and pH ( 6-7) were of the same range.Considerably
the DO concentrations were low in stations T2 and
T3, consequently below the DENR Class AA
standard.Both river tributatries were located adjacent
to the populated area in San Fernando, Bukidnon.
Anthropogenic water pollutants in a form of organic
matter discharges from adjacent community may
have contributed to lower DO levels (Chapman,
1996). The higher conductivity, salinity, and TDS
concentrations were recorded in T2 and T3 as
compared to S1 and T1. Conductivity may indicate
potential levels of ions in water (Chapman, 1996) and
TDS can be associated to carbonates in water samples
(Pip, 2000). Both inorganic and organic chemical
attributes affecting TDS, salinity, and conductivity
can be induced by anthropogenic discharges from
populated area. Strong associaion of TDS, conductivity,
and salinity were similarly determined by other water
quality studies in the Philippines (Galarpe and Parilla,
2012; Galarpe and Parilla, 2014; Achas et al., 2016).
Nonetheless, these parameters were within the normal
range/standard set.
Overall trend showed higher turbidity levels among
river tributaries adjacent to central district of San
Fernando, specifically T2 and T3. This can be
attributed from dust deposition and anthropogenic
runoffs from adjacent communities. Study in the past
similarly showed Tigua sub-watershed with the
highest soil accumulation at 181.25 ton/ha/yr (Marin
and Jamis, 2016).On the other hand, studied metals
(Pb, Cd, Cu, and Cr) were below the detection limit
whereas nitrates were within the range 0.75-1.66
ppm. The nitrates level were higher in S1, site
distinctively sorrounded by agriculutral land (e.g. rice
fields and banana). Consequently, nitrogen leaching
from ploughed land area to river catchment may
increase nitrate concentration (Neill, 1989; Schilling
et al., 2000; Boithias et al. 2014). Summary of results
is shown in Table 3.
Table 3. Summary of the physicochemical analyses of tributary river water.
Parameter
River Standard
S1 T 1 T 2 T 3
DENR
Class AA
PNSDW
pH 6.7 6.8 6.7 6.7 6.5-8.5 6.5-8.5
Temp (deg C) 27.2 27.1 27.3 27.6 - -
DO (ppm) 9.87 9.45 4.25 3.9 5.0 -
ORP(mV) 24 24 22 24.7 - -
Conductivity (uS/cm) 179 204 194 205 - -
Salinity (ppm) 90 102 98 102 - -
TDS (ppm) 121 137 130 136 500 500
Turbidity (ntu) 11.2 1.12 10.4 32.9 - 5
Pb (ppm) <0.01 <0.01 <0.01 <0.01 0.01 0.05
Cd (ppm) <0.003 <0.003 <0.003 <0.003 0.003 0.01
Cu (ppm) <0.03 <0.03 <0.03 <0.03 1.0 1.0
Cr (ppm) <0.03 <0.03 <0.03 <0.03 0.05 -
Nitrates (ppm) 1.66 0.97 1.01 0.75 7 50
Statistical comparison
Overall, studied physicochemical parameters showed
significant difference (p <0.05) among river
tributaries (see Table 4). Statistical results using
ANOVA confirmed site specific variation with
elevated concentrations for pH, temperature, DO,
ORP, TDS, salinity, conductivity, and turbidity in T2
and T3. Further, the correlation analysis (see Table 5)
showed strong association among parameters of
conductivity-salinity (r = 0.99), salinity-TDS (r
=0.99), and conductivity-TDS (r =1) in all studied
river tributaries (Table 3).

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270 | Galarpe et al.
Present findings were in agreement with the studies
of Köse et al. (2014) and Tokatli et al. (2014) on
stream waters showing positive correlation
between TDS, conductivity, and salinity.
Considerably, temperature and turbidity showed
positive correlation (r = 0.98). River tributary with
higher temperature had higher turbidity, indicating
anthropogenic influence to water quality.
Table 4. ANOVA of the physicochemical parameters in river tributaries.
Parameter F-value p-value F-critical Decision
pH 5.507937 0.023942 4.066181 Significant difference
Temp 27.27778 0.000149 4.066181 Significant difference
DO 112.4677 7.02E-07 4.066181 Significant difference
ORP 6.857143 0.013319 4.066181 Significant difference
TDS 456.1349 2.8E-09 4.066181 Significant difference
Salinity 733.2046 4.24E-10 4.066181 Significant difference
Conductivity 437.416 3.31E-09 4.066181 Significant difference
Turbidity 1225.94 5.46E-11 4.066181 Significant difference
Table 5. Correlation coefficient analysis of the physicochemical parameters in river tributaries.
Parameters pH Temp DO ORP Conductivity Salinity TDS Turbidity Nitrates
pH 1 -0.62 0.53 0.19 0.47 0.47 0.54 -0.63 -0.22
Temp 1 -0.81 0.28 0.36 0.33 0.27 0.98 -0.53
DO 1 0.28 -0.44 -0.47 -0.4 -0.68 0.69
ORP 1 0.23 0.14 0.21 0.43 -0.05
Conductivity 1 0.99 1 0.25 -0.95
Salinity 1 0.99 0.20 -0.96
TDS 1 0.16 -0.93
Turbidity 1 -0.39
Nitrates 1
Risk assessment
The RQ values (Table 6) for all studied river
tributaries showed no potential risk with reference
to DENR Class AA and A water standards, and
PNSDW (2007). The values for pH and
temperature with RQ =1 were mainly due to lowest
reference standard although the results were
within the regulations. It can be extrapolated that
T1, T2, T3, and S1 had good river water quality
during the sampling.
Table 6. RQ of selected physicochemical parameters in studied river tributaries.
Parameter
S1 T 1 T 2 T 3
AA A PNSDW AA A PNSDW AA A PNSDW AA A PNSDW
pH
1.03-
0.79
1.03-
0.79
1.03-
0.79
1.03-
0.79
1.03-
0.79
1.03-
0.79
1.03-
0.79
1.03-
0.79
1.03-
0.79
1.03-
0.79
1.03-
0.79
1.03-
0.79
Temp
1.04-
0.91
1.04-
0.91
1.03-
0.79
1.04-
0.90
1.04-
0.90
1.03-
0.79
1.05-
0.91
1.05-
0.91
1.03-
0.79
1.06-
0.92
1.06-
0.92
1.03-
0.79
TDS 0.24 0.12 0.24 0.14 0.27 0.27 0.26 0.13 0.26 0.27 0.14 0.27
Nitrates 0.23 0.23 0.03 0.14 0.14 0.019 0.14 0.14 0.015 0.11 0.11 0.015
Comparison to Philippine rivers
Compared parameters were pH, TDS, DO, and
nitrates which were common analyses in studied
rivers in the Philippines. Distinctively, the pH of S1,
T1, T2, and T3 were relatively comparable to Labo
and Clarin Rivers (Labajo-Villantes, 2014).
These rivers were adjacent to agricultural lands and
located primarily in the same region exhibiting
comparable pH. The TDS were similarly comparable
to Labo and Clarin Rivers (Labajo-Villantes, 2014)
and Mama River (Martinez et al., 2011) which were
all located in agricultural areas.

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271 | Galarpe et al.
The DO in T1 and S1 were comparable to Mananga
River (Flores and Zafaralla, 2012), Labo and Clarin
Rivers (Labajo-Villantes, 2014) and Mama River
(Martinez et al., 2011) indicating less anthropogenic
impacts. The nitrate levels were comparable to other
cited river studies (Table 7).
Table 7. Comparison of selected physicochemical properties of river tributaries.
River pH TDS DO Nitrates Reference
Tigua River, Bukidnon
T1
T2
T3
Salug River, Bukidnon
S1
6.7
6.8
6.7
6.7
137
130
136
121
9.45
4.25
3.9
9.87
0.97
1.01
0.75
1.66
This study
Butuanon River, Cebu
Upstream
Midstream
Downstream
7.17
7.60
7.26
392.67
536.67
558.83
4.43
0.10
0.07
2.07
0.16
0.06
Maglangit et al. (2014)
Buhisan River, Cebu 7.2-7.6 - 0.07-4.4 - Maglangit et al. (2015)
Bulacao River, Cebu 7.4-8.0 - 2.1-8.1 - Maglangit et al. (2015)
Lahug River, Cebu 7.4-7.7 - 0-6.5 - Maglangit et al. (2015)
Mananga River, Cebu 8.03-8.76 - 5.45-6.87 2.28-3.15 Flores and Zafaralla (2012)
Pampanga River, Pampanga 8.29 - 4.37 5.38 Arbotante et al. (2015)
Mamba River, Southern Luzon 8.1 210 6.77 - Martinez et al. (2011)
Labo River
Clarin River,
Misamis Occidental
6.40 -8.27 71.0-27.0 2.40-10.60
3.90-11.20
0.13 -
0.90
Labajo-Villantes (2014)
Conclusion
The studied parameters showed site specific
variations (p<0.05) and can be ranked T3>T2>T1>S1.
The ranked was extrapolated from anthropogenic
inputs influencing water quality in T3 and T2.
Similarly, a positive correlation among parameters,
namely, TDS, salinity, and conductivity were
determined. Overall tributary river water quality
analyses were within the standards. Environmental
risk assessment showed no potential risk as indicated
by RQ<1 and descriptive comparable assessment with
other river studies in the country. Present findings are
preliminary and further analyses maybe essential.
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