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Hydro-Geochemical Characteristics of Sawaga River, Malaybalay City, Bukidnon.


The Sawaga River of Malaybalay serves as one of the major sources of water for drinking, irrigation, and industrial uses. However, this river system is severely threatened due to slash and burn farming, illegal logging, mining, and quarrying. In this context, this study was conducted to assess the hydro-geochemical characteristics of the Sawaga River to determine its degree of impairment and hydro-geological processes that may influence the water chemistry. Water samples were collected and analyzed for major cations and anions and other relevant physicochemical parameters. Geochemical modeling was also employed to reveal the mineral phases that may control water chemistry. Results show that the water chemistry of the river was mainly Mg-Cl type and undersaturated with respect to anhydrite, gypsum and halite. Moderately acidic pH, an elevated concentration of nitrate, and high TSS concentration were observed particularly along the agricultural and built-up areas of the river. This overall water quality of Sawaga River could be mainly attributed to the influence of land use and human activities along the river. Hence, regular monitoring should be implemented coupled with strict implementation of environmental laws that should be carried out by the city government of Malaybalay to protect and conserve this river system.

Keywords: Sawaga river, hydro geochemical assessment, land use, water quality, watershed management


The water quality of the watershed is influenced by soil type, geology, vegetation, precipitation, land cover and land use in which the latter has a significant influence on the overall surface water quality of river systems (Boyd, 2000). Various human activities such as deforestation that alter the land cover and land use of the watershed can severely threaten the watershed integrity and stability. Land use alters the texture and composition of the land surface and therefore influences water quality. The study of Belke (2007) has shown that the content of nitrate in water and agriculture is a source of chemical contamination. In agricultural areas, fertilizer runoff can increase the nutrient levels in the water and therefore can decrease the water quality through a series of biological responses to an increase in nutrient levels (Boyd, 2000). It was observed by Poinke and Urban (1985) that the impact of cropland areas on groundwater quality in a small Pennsylvania watershed was substantial compared to forested areas due to the consistent higher level of nitrate concentration, which could be associated to the excessive use of commercial fertilizers. The agricultural area had a land use impact coefficient of 0.01-0.02 mg/L/acre for nitrate while for a forested watershed was approximate -0.06 to -0.01 mg/L/acre for nitrate. These values indicated that agriculture was a source of nitrate, and a forested area acted as a sink of nitrate (Belke, 2005). It was also observed by Tong and Chen (2002) that agricultural areas had higher nutrient inputs, which allowed not only for higher amounts of loading of nitrogen, but also of phosphorus and fecal coliform.

Not only the agricultural and forested areas have shown significant influence in controlling the water quality of the watershed but also the industrially contaminated lands, mine waters, landfill, septic tanks (Lerner and Harris, 2009), waste water effluents (Smart, 2004), and urban sprawl (France, 2005). The study of Bleifuss (1997) on the effects of land use on the water chemistry of Long Island aquifer system was able to show the significant differences in the major cations and anions according to land use using the Piper Plot. Moreover, water-related natural disasters induced by tropical cyclones such as floods, coastal and riverine flooding, mass movements, and landslides also affected the water chemistry and destroyed the watershed (Tsai et al., 2009).

One of the three important watersheds of the City of Malaybalay in Bukidnon is the Sawaga watershed, which is the biggest with a total land area of 47,071.27 hectares. It is composed of 23 sub-watersheds within 19 barangays of the City of Malaybalay. The Sawaga River, which is one of the major tributaries of Pulangui River, drains from Mt. Kitanglad and asses through the urban center of the city before it joins the Pulangi River in Valencia City. The Sawaga watershed serves as the city's major lifeline in providing an important water source for potable water, industries and irrigation uses, and the electric hydropower in Bukidnon.

However, the remaining forest and its natural resources of the Sawaga watershed are at risk due to rapid rate of decrease in forest cover caused by slash and burn farming, illegal logging, mining and quarrying that resulted in frequent occurrences of riverine flooding and landslides within the watersheds. These problems will enhance soil erosion, bacterial and chemical contamination, and variation in stream discharge patterns. Hence, the planned finalization and adoption of the Watershed Management and Rehabilitation Plan of the City of Malaybalay is timely in order to address the above issues. Although there are considerable data that exist, worldwide describing the impact of land use on water resources quality, no data are available for the Sawaga watershed, which is one of the most important sources of water supply of the city. Hence, the conduct of this study will contribute to the enhancement of watershed management policies of the City of Malaybalay.

This study evaluated the influence of land use on the hydro-geochemical characteristics of the Sawaga watershed of the City of Malaybalay to provide baseline information regarding the present condition of the water quality and the degree of impairment of the watersheds as influenced by various land use patterns within the watershed. The identification of the existing land use pattern surrounding the Sawaga River and the determination of its major ion chemistry and other relevant physicochemical properties were also carried out to understand the hydro-geochemical reactions that control the water chemistry of the river and examine possible correlation between land use and water quality. The acquisition of these data will enable the City of Malaybalay to determine the type of land use that needs significant intervention to sustain the Sawaga watershed.


Data acquisition

Relevant map about the geographic information system and models of the Sawaga River, which contains information on the type of surrounding land use, was obtained from Google Earth and PEDMO, Bukidnon. A reconnaissance survey on the possible sampling points was conducted prior to the collection of water samples. All sampling points for stream and groundwater were selected with the aid of Geographical Positioning System (GPS). Six sampling points were selected in relation to the type of land use.

Collection of Water Samples

In June 2012 to May 2013, two kinds of stream water samples (500 mL each) were collected from each sampling point using a syringe. The water samples were then placed into PP bottles, which were rinsed with the water samples thrice. The bottles were cleansed first with nitric acid solution and rinsed with distilled water prior to their usage. One sample was filtered and acidified for the analysis of major cations. The water samples were immediately brought to an accredited laboratory for chemical analysis.

Chemical Analysis of Water Samples

The major ions that were measured included [Ca.sup.2+], [Mg.sup.2+], [Na.sup.+] and [K.sup.+] for cations and [Cl.sup.-], S[O.sup.2-.sub.4], C[O.sup.-.sub.3], N[O.sup.-.sub.3] and HC[O.sup.-.sub.3] for anions. The major cations were determined by using Atomic Absorption Spectroscopy (AAS). The carbonates, chloride, nitrate, and sulfate were measured using alkalimetry, Mohr method, distillation/titration method, and turbidimetric method, respectively. The temperature was measured using a thermometer while the pH, EC was measured by pH/EC meters. The TSS was measured by gravimetric method. Finally, the measured chemical parameters were compared with the Philippine drinking water standards.

Data Analysis

PHREEQC geochemical code was used to characterize the hydro-geochemical properties of water samples to reveal the mineral phases that control water chemistry (Parkhurst, 1995). By analyzing the hydro-geochemical properties, one could gain a better understanding of the processes and factors that influence the water chemistry of the watershed. Data on the stream chemistry of the watershed were correlated with the spatial variation of various land use types. All statistical analyzes were done using Statistical Analysis Software (SAS).


Description of the study area

Six sampling stations were identified along the Sawaga River and these stations are located at latitude ranging from N 8[degrees]10.502' to N 7[degrees]59.371' and longitude between E 125[degrees]5.608' to E125[degrees]10.017'.

The sampling point in Kalasungay Village has the highest elevation while the sampling point in Bangcud has the lowest elevation as shown in Table 1. Figure 1 shows the land use map surrounding the Sawaga River as it traverses the municipality of Malaybalay with its headwater located in Dalwangan Village of Malaybalay City and drains to Pulangui River in Kahaponan Village in Valencia City. The land surrounding the sampling stations is mainly used for agriculture, based on the 2004 vegetative cover survey, except that in Sumpong and San Isidro that are located along the edge of the urban areas of the City of Malaybalay.

Plates 2a to 2f present the photos of the actual sampling site. In recent years, significant residential and industrial developments have been taking place along the sides of the Sawaga River especially at Sumpong and San Isidro areas.

Physico-chemical Characteristics of Sawaga River

Results of the physicochemical analyzes and field measurement data for each sampling site are presented in Table 2. The temperature ranged from 26 to 32 [degrees]C typical for river waters. The pH values were slightly acidic to slightly basic, within a range between 5.58 to 7.58 as shown in Figure 2.

The most acidic river water was observed in Kalasungay Village, which could be attributed to the presence of organic acids resulting from decomposition of organic wastes from field pasture and the use of fertilizers from agricultural activities. The slightly basic conditions of the Sawaga River along the area of San Jose and Linabo could be caused by the dissolution of calcareous sediments, which can maintain a pH value range from 7.5 to 8.3. Moreover, results also show very high TSS values, which ranged from 162 to 232 mg/L. Intensification of agricultural activities in recent years has been largely known to cause increase sedimentation in rivers. The TSS values at the different sampling sites are presented in Figure 3.

The TSS is highly dependent on the discharge of the river, vegetative cover, and the size catchment area, in which rivers with high discharge rate, largest catchment area and highly loosed top soil will produce the largest TSS concentration and loadings (Sullivan et al., 2004).

The spatial variations in water chemistry are related to changes in lithologic and hydrologic settings, as well as anthropogenic disturbances (Moskovchenko et al., 2009). The electrical conductivity (EC), which is a measure of water to conduct electricity, varied between 89.3 to 198.7 [mu]S/cm. This parameter is highly dependent on the concentrations of dissolved ions in water; thus, it is expected that San Jose, Linabo and Bangcud that exhibited higher concentrations of dissolved cations and anions would have higher EC values compared with other sites as shown in Figure 4.

On the other hand, Figure 5 shows the concentrations of major cations and anions of Sawaga River in the different sampling sites. Chloride ion showed the highest concentration with values ranging from 11.52 to 19.5 mg/L and tended to be relatively higher at the downstream sections of the river (S4 to S6). It can also be seen from the figure that nitrate concentrations were relatively elevated in all sampling sites ranging from 6.30 to 12.60 mg/L. The highly cultivated and urbanized areas tended to have higher nitrate concentrations compared to that in San Jose that is partly surrounded by bushland, grassland, and open canopy cover. The relatively higher nitrate concentration in the Sawaga River could be attributed to the leaching of nitrate from fertilizers and reduced nitrogen compounds in agricultural areas and sewage from residential and commercial establishments. The rest of the measured cations and anions ([Ca.sup.2+], [Mg.sup.2+], [Na.sup.+], [K.sup.+] and S[O.sup.2-.sub.4]) had concentrations below 5 mg/L and showed no significant changes in concentrations in the different sampling sites except for [Ca.sup.2+], [Mg.sup.2+], [Na.sup.+], which were relatively higher in San Jose and Linabo sampling sites.

Hydrogeochemical facies

Figure 6 presents the Collins diagram showing the concentration (in eq/L) of major cations and anions as measured. The total height reflects the total dissolve solids TDS of the water. As shown in the figure, the Sawaga River is mainly dominated by Mg-Cl type of water. The dissolution of feldspar and dolomites could be the primary source of magnesium. The remoteness of seawater from Sawaga River suggests that the rain water is the main source for Cl (-) (Kumar et al., 2009).

Geochemical modeling

Only the sampling sites in San Jose and Linabo were modeled to determine the saturation indices of mineral phases that control the surface water chemistry due to the significant charge imbalance in other sampling sites. SI describes quantitatively the deviation of water from equilibrium with respect to dissolved minerals (Azaza et al., 2011). Based on the geochemical results using Phreeqc, the water samples from San Jose and Linabo were undersaturated with respect to anhydrite, gypsum, and halite. Table 3 presents the saturation indices of the minerals phases.

Correlation matrix

The Pearson correlation matrix of physicochemical parameters is presented in Table 2. Strong correlations among [Ca.sup.2+],, [Mg.sup.2+], [Na.sup.+], and [Cl.sup.-] were observed. These compositional relations among dissolved species can reveal the origin of solutes and the process that generated the observed water compositions (Azaza et al., 2011). In this study, the EC and pH also showed strong positive correlations although there was no direct link between these two parameters. In the case of EC and the measured concentrations of cations and anions, strong positive correlations were observed since EC is established according to the number of ions in the solution. The higher the concentration of ions, the higher the electrical conductivity of the solution. As expected, [Na.sup.+] and [Cl.sup.-] exhibited strong positive correlation of 0.939 at 0.01 significance level. The molar ratio of [Na.sup.+]/[Cl.sup.-] of < 1.0 indicates that the ion exchange process is the dominant source for [Na.sup.+] (Azaza et al., 2011). The moderate correlation between Ca and Mg (r = 0.808) could probably indicate that the concentration is governed by limestonedolomite weathering (Kumar et al., 2009).

Cluster analysis

Cluster analysis of water quality data from the six sampling stations was used to determine whether various parts of the Sawaga River could be grouped into homogenous zones. Figure 7 shows the cluster diagram showing the sampling sites relationships. Two evident groups and two individual clusters can be observed from the dendrogram using Ward Linkage. The upper part of Sawaga River, to include the Kalasungay, San Isidro and Sumpong areas, showed high similarity and characterized by lower pH, EC, the areas in [Cl.sup.-], [Mg.sup.2+], [Ca.sup.2+] and [Na.sup.+] values compared to that in the lower part of the river that included San Jose, Linabo and Bangcud. The cluster analysis also reveals that the San Jose and Bangcud sampling sites showed distinct characteristics that could be mainly attributed to the nitrate concentration. San Jose and Bangcud sites exhibited the lowest and highest concentration of nitrate, respectively. This finding clearly shows the impact intensive agricultural activities have on the water quality of the Sawaga River. The surrounding land of the Sawaga River in Bangcud is predominantly used for agricultural (rice fields), which is distinct from the rest of the sampling sites.

Water Quality Assessment of Sawaga River

Overall, the water quality of Sawaga River is acceptable only for navigation and other similar uses because of its high nitrate and TSS concentrations above the Philippine Water Standards. The water is not safe for drinking, swimming, fishing, and even for agricultural purposes if the nitrate concentration is above 7 mg/L. The observed TSS concentrations in the different sampling sites were also way above the maximum limit of 110 mg/L (


Based on the results of this study, the water chemistry of the surface water from Sawaga River is mainly Mg-Cl type. The measured concentration of cations and anion is below 5 mg/L except for chloride and nitrate. Ion exchange process and limestone-dolomite weathering may have probably controlled the concentrations of [Na.sup.+], and [Ca.sup.2+] and [Mg.sup.2+], respectively. Results of geochemical modeling reveal that the surface water is undersaturated with anhydrite, gypsum, halite and sulfur. Results of this study have also shown that land use largely affects surface water quality, with a predominance of non-point-source discharges contributing contaminants to Sawaga River. Elevated concentration of nitrates can be attributed to intensive use of fertilizers from agricultural areas and field pasture as well as from livestock production that occasionally drain into streams, causing water quality problems. Sewage from built-up areas can also contribute to water problems of Sawaga River. Hence, the overall water quality of Sawaga River is already disturbed and needs significant intervention.


Regular monitoring should be implemented coupled with strict implementation of environmental laws that should be carried out by the city government of Malaybalay in order to protect and conserve this environmentally significant river system.


Azaza, F., Ketata, M., Bouhlila, R., Gueddari, M. And Riberio, L. 2011 Hydrogeochemical characteristics and assessment of drinking water quality in Zeuss--Koutine aquifer, southeastern Tunisia. Environmental Monitoring and Assessment 174:283-298.

Bleifuss, P., Hanson, G., Schoonen A., 1997 A geochemical study of the effects of land use on nitrate contamination in the Long Island aquifer system. (Unpublished report), accessed through the internet.

Belke, M. 2005 Impact of land use on the water quality in the Indian Lake Watershed: An integrated geographic information systems approach. Wright State University M.S. Thesis.

Boyd, C.E. 2000 Water quality: An introduction. Kluwer Academic Publishers.

France, L. 2005 An Assessment of the Effects of Urban Land-Use/Land-Cover on Stream Water Quality in the Mid-Ohio River Watershed Using GIS and Remote Sensing. Wright State University M.S. Thesis.

Kumar, S., Rammohan, V., Dajkumar, J., Jeevanandam, S. 2009 Assessment of groundwater quality and hydrogeochemistry of Manimuktha River basin, Tamil Nadu, India. Environmental Monitoring and Assessment, 159:341-351.

Lerner, D., Harris, B. 2009 The relationship between land use and groundwater resources and quality. Land Use Policy, 265, S265-S273.

Moskovchenko, D., Babushkin, A., and Artamonova, G. 2009 Surface water quality assessment of the Vatinsky Egan River catchment, West Siberia. Environmental Monitoring and Assessment, 148:359-368.

Parkhurst, D.L., 1995 User's Guide to PHREEQC-A Computer Program for Speciation, Reaction-Path, Advective-Transport, and Inverse Geochemical Calculations. U.S. Geological Survey, Water-Resources Investigations Report 95-4227.

Pionke, H., Urban, J. 1985 Effect of agricultural land use on groundwater quality in a small Pennsylvania Watershed. Groundwater, 23 (1), 68-80.

Smart, M.E. 2004 Using LANDSAT Data to Correlate Land Use with Water Quality: A Case Study of the Upper Little Miami River Watershed. Wright State University MS Thesis.

Tong, S. and W. Chen. 2002 Modeling the Relationship between Land Use and Surface Water Quality. Journal of Environmental Management, 66, 377-393.

Tsai, C., Lin, T., Hwong, J., Lin, N., Wang, C., Hamburg, S. 2009 Typhoon impacts on stream water chemistry in a plantation and an adjacent natural forest in central Taiwan. Journal of Hydrology, 378 (3-4), 290-298.


ORCID No. 0000-0001-6806-4703


ORCID No. 0000-0003-4960-4449

Central Mindanao University

Musuan Bukidnon, Philippines
Table 1. Details of Site Description and Sampling

Sampling    Location                 Coordinates
No.                       Latitude              Longitude

[S.sub.1]   Kalasungay   N8[degrees] 10.502'   E125[degrees] 05.608'

[S.sub.2]   Sumpong      N8[degrees] 09.677'   E125[degrees] 07.046'

[S.sub.3]   San Isidro   N8[degrees] 08.874'   E125[degrees] 07.720'

[S.sub.4]   San Jose     N8[degrees] 06.021'   E125[degrees] 09.545'

[S.sub.5]   Linabo       N8[degrees] 02.931'   E125[degrees] 10.017'

[S.sub.6]   Bangcud      N7[degrees] 59.371'   E12[degrees]5 09.043'

Sampling    Elevation  Land Use          Weather
No.         (m,asl)                      Condition

[S.sub.1]   732.74     Field             Clear/
                       Pasture/          Sunny
[S.sub.2]   664.20     Agricultural/     Clear/
                       Residential       Sunny
[S.sub.3]   594.97     Field             Clear/
                       Pasture/          Sunny
[S.sub.4]   429.46     Agricultural/     Clear/
                       Residential       Sunny
[S.sub.5]   350.82     Agricultural/     Clear/
                       Residential       Sunny
[S.sub.6]   333.15     Agricultural/     Clear/
                       Residential       Sunny

Table 2. Phyico-chemical Parameters of the Six Sampling Points during
the Wet and Dry Season

Sampling                                   Parameters
               Temp.       pH      EC     TSS    C[O.sup.-.sub.3]
            ([degrees]C)         ([mu]S/

Kalasungay    29          5.58    89.3    214         bdl
Sumpong       26          6.70    83.9    212         bdl
San Isidro    32          6.26    92.0    232         bdl
San Jose      31          7.57   180.8    162         bdl
Linabo        32          7.58   198.7    232         bdl
Bangcud       30          6.97   172.1    187.5       bdl

Sampling                     Parameters
            [Cl.sup.-]  N[O.sup.-.sub.3]  S[O.sup.2-.sub.4]  [Ca.sup.2+]


Kalasungay    16.16         8.40              3.69               0.00
Sumpong       11.52         8.40              3.30               0.00
San Isidro    12.41         9.10              3.69               0.00
San Jose      18.61         6.30              3.18               5.47
Linabo        19.50         7.70              2.82               5.06
Bangcud       19.06        12.60              2.52               1.57

Sampling                     Parameters
            [Mg.sup.2+]  [N.sup.a+]  [K.sup.*]

Kalasungay      3.48         2.97      1.84
Sumpong         4.01         2.37      1.30
San Isidro      4.16         2.13      1.61
San Jose        7.14         6.05      0.97
Linabo          7.20         6.72      0.98
Bangcud         7.52         6.33      2.82

Note: bdl: below the detection limit, values in bold correspond to dry

Table 3. Saturation Indices (SI) of Anhydrite, Gypsum and Halite

Sampling area   Anhydrite   Gypsum   Halite   Sulfur

San Jose        -4.22       -4.03    -8.43    -54.51
Linabo          -4.14       -8.53    -8.49    -54.25

Table 4. Correlation Matrix of the Physico-chemical Parameters

Parameters   pH          EC           TSS     Cl          NO3

pH          1
EC           .852 (*)   1
TSS         -.387       -.392       1
Cl           .551        .895 (*)   -.419   1
NO3         -.217       -.031        .047    .053       1
SO4         -.714       -.796        .326   -.683       -.446
Ca           .865 (*)    .898 (*)   -.410    .756       -.463
Mg           .859 (*)    .969 (**)  -.489    .835 (*)    .138
Na           .788        .984 (**)  -.445    .939 (**)   .060
K           -.382       -.103       -.111    .105        .942 (**)
Temp.        .324        .558        .090    .506       -.087

Parameters    SO4         Ca        Mg          Na         K       Temp.

SO4         1
Ca          -.511      1
Mg          -.873 (*)   .808      1
Na          -.842 (*)   .841 (*)   .963 (**)  1
K           -.300      -.500       .051        .016       1
Temp.       -.129       .528       .482        .461       -.112      1

(*). Correlation is significant at the 0.05 level (2-tailed).
(**). Correlation is significant at the 0.01 level (2-tailed).
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Author:Opiso, Einstine M.; Alburoa, Jim Loui R.
Publication:Liceo Journal of Higher Education Research
Article Type:Report
Date:Dec 1, 2014
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