Volume 10, Number 3 (April 2023):4467-4478, doi:10.15243/jdmlm.2023.103.4467 ISSN: 2339-076X (p); 2502-2458 (e), www.jdmlm.ub.ac.id
Open Access 4467 Research Article
River water quality variability in the young volcanic areas in Java, Indonesia
Heru Hendrayana1*, Indra Agus Riyanto2, Azmin Nuha3
1 Department of Geological Engineering, Faculty of Engineering, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
2 Department of Environmental Geography, Faculty of Geography, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
3 Groundwater Working Group (GWWG), Universitas Gadjah Mada, Yogyakarta 55281, Indonesia
*corresponding author: [email protected]
Abstract Article history:
Received 25 November 2022 Accepted 11 January 2023 Published 1 April 2023
Rivers on Java Island are one of the water supply sources to meet the surrounding population's water needs. However, only large, high-priority rivers underwent a comprehensive water quality assessment. Rivers that are not a priority are rarely examined, such as sub-watersheds in Kuntulan, Rejoso. Upper Serayu, Gajahwong, and Glondong. The surrounding community utilizes these five watersheds for irrigation, industry, and domestic. Hence, analyzing the water quality index in the five watersheds during the dry season is necessary. The method used in this research is a comparison of the water quality results between the standards of the Indonesian government and WHO, as well as a comparison of the Water Quality Index (WQI) and Pollution Index (PIj). The method often used in Indonesia is PIj, while WQI is more global and hardly used. The difference in the two ways is expected to provide variations in the water quality index.
The water quality parameters were pH, TDS, TSS, COD, PO43-, NO3-, total coliform, temperature, and EC. Comparing water quality with water quality standards in the five watersheds shows that several samples exceed the standard. WQI result shows that all river water in the five watersheds belongs to the excellent classification. A different result from the PIj index shows that the five watersheds were dominantly moderately polluted, with several samples considered polluted and extremely polluted. Differences in the index formula and water quality standards cause these different results.
The results of the analysis show that the PIj index is more representative than the WQI as the PIj index shows the suitability of the classification comparison of water quality values with water quality standards compared to WQI.
Keywords:
pollution index river
water quality young volcanic area
To cite this article: Hendrayana, H., Riyanto, I.A. and Nuha, A. 2023.River water quality variability in the young volcanic areas in Java, Indonesia. Journal of Degraded and Mining Lands Management 10(3):4467-4478, doi:10.15243/jdmlm.2023.103.4467.
Introduction
Rivers are one of the most widely used water resources by humans (Wriedt et al., 2009; Qin et al., 2019;
Hrozencik and Aillery, 2021). River water is one of the primary sources of raw water for water needs because it is relatively easy to obtain with a large abundance (Tickner et al., 2017). Its utilization has been done
since ancient times in the bank settlements of the Nile, Indus, Yellow Rivers, Euphrates, and Mesoamerica (Hassan, 2011). River water has various uses, both for drinking (Katsanou and Karapanagioti, 2019), domestic (Flörke et al., 2013), agricultural irrigation (D'Odorico et al., 2020), fisheries (Rahimibashar et al., 2012), livestock (Cook et al., 2009), and industry (Shang et al., 2016). With varying degrees of need, the
Open Access 4468 demand for river water increases annually to meet
water consumption in each sector (Munia et al., 2016).
Problems arise when river water pollution becomes a crucial problem worldwide (Virro et al., 2021;
Wilkinson et al., 2022). This polluted river water can harm humans, animals, and plants' well-being (Habeeb et al., 2018; Lin et al., 2022; Younas and Younas, 2022). Preliminary river water quality studies are essential at an early stage before being utilized (Virro et al., 2021; Zhang et al., 2022). Initial water quality studies at an early stage can minimize the impact caused by pollution on rivers (Kamboj et al., 2020).
Additionally, water quality studies provide information on river pollution levels and the treatment that ought to be done. One of the water quality studies widely used worldwide is the Water Quality Index (WQI) (Sutadian et al., 2016). The WQI provides information on the classification of water quality characteristics ranging from excellent to very poor (Banda and Kumarasamy, 2020). Furthermore, a more detailed Pollution Index is applied to each country (Tyagi et al., 2020). The Pollution Index of each country has provisions and standards that are more
detailed than the WQI since they are adjusted to various environmental conditions for each country.
Studies on the WQI index in Indonesia are relatively rare (Triaji et al., 2017). This problem is due to the studies of water quality in Indonesia dominantly use the Pollution Index (PIj) issued by the Indonesian Ministry of Environmental Regulation in 2003 (Widodo et al., 2019; Novita et al., 2020; Wijayanti et al., 2021). As a result, several studies of river water quality in Java use PIj to measure river pollution.
Studies conducted on Java Island were generally carried out separately, and there was no comparison between one river and the others. Based on the results of several studies, the priority rivers in Java belong to the light, medium, and heavily polluted categories (Kardono, 2018). According to PPEJ (2013), Java Island has nine priority watersheds that must restore their water quality. However, in-depth water quality studies for other watersheds have never been carried out. Therefore, this study aims to examine the water quality of several rivers in 5 watersheds on Java Island (Figure 1). This study also compared each watershed's WQI and PIj water quality index.
Figure 1. Study area (based map source: BIG, 2004).
Open Access 4469 The study area's five watersheds are important water
sources for the surrounding communities. The upstream part of the Kuntulan watershed is located on the Arjuno-Welirang volcano with material consisting of lava, the middle part of the watershed consists of lahar (volcanic mudflow), and the downstream is consists of alluvial deposits. The upstream of the Rejoso watershed, located at Bromo-Tengger Volcano, consists of andesitic lava and tuff. The middle part of the watershed consists of andesite breccia and lahar, and the downstream part consists of alluvial and volcanic sandstone. The upstream of the Glondong watershed, located at Raung Volcano, consists of andesitic lava, autoclastic breccia, and basalt-andesite. The middle part of the watershed consists of laharic breccia. The downstream part consists of alluvium deposits. The upstream Gajahwong watershed is found in Merapi Volcano with material consisting of lava and pyroclastic deposits, the middle part of the watershed consists of laharic breccias, and the downstream part consists of lahar. Lastly, the upstream part of the Upper Serayu watershed is found in Sindoro, and Sumbing Volcanoes with material consisting of lava and pyroclastic breccias, the middle part of the watershed consists of laharic breccias and downstream consists of lahar deposits.
Materials and Methods
The data used in this study were primary data from river water sampling during the dry season. River water samples were tested directly in the field and the laboratory. The water samples parameters examined were temperature, electrical conductivity (EC), Total Dissolved Solid (TDS), and pH. These water samples were taken for laboratory examinations using a 2-litre glass sample bottle and a 2-litre Winkler bottle. The water samples parameters tested in the laboratory were Total Suspended Solid (TSS), Chemical Oxygen Demand (COD), phosphate (PO43-), nitrate (NO3-), and total coliform. The river water samples taken from 5 watersheds in Java Island are divided based on the stream location: the upper stream, the middle stream, and the downstream. The watersheds from which river water samples were taken included Kuntulan (5 samples), Rejoso (5 samples), Upper Serayu (4 samples), Gajahwong (6 samples), and Glondong (6 samples) (Figure 1). In general, the method used in this study consisted of two parts: a comparative analysis of water quality using water quality standards and a comparative analysis of water quality using a water quality index and pollution. The first method of this study, which was the direct comparison of water quality results, was done by comparing water quality based on WHO standards (2012) and Indonesian Government Regulation (2001), WHO standard values (2012) and Indonesian Government Regulation (2001) are explained in detail in Table 1. The analysis was
carried out as a graphic comparison of water quality measurement values with the standards of the two rules using Microsoft Excel.
Table 1. Water quality standard.
No Parameters WHO Indonesia
Government Regulation
1 pH (6-9) (6-9)
2 TDS (mg/L) 500 1,000
3 TSS (mg/L) 20 40
4 COD (mg/L) 80 10
5 PO43- (mg/L) 5 0.2
6 NO3- (mg/L) 50 10
7 Total coliform (CFUs in 100 mL)
100 1,000
The second method was carried out by analyzing the Water Quality Index (WQI) (Akter et al., 2016) and the Pollution Index (PIj) from the Indonesian Ministry of Environmental Regulation (2003). The results obtained from this analysis were index values for each river and river segment. WQI analysis calculations are explained in equations 1, 2, and 3, while PIj analysis calculations are presented in equation 4. The results of these calculations are then entered into the WQI classification (Table 2) and PIj Classification (Table 3) to determine the level of water quality in each watershed.
WQI = ∑ Qi. Wi (1)
Qi = (Ci/Si) x 100 (2)
Wi = 1/Si (3)
where:
WQI : Water Quality Index Ci : Concentration of Parameter Si : Standard Value of Parameter
PIj= (4)
where:
PIj : Pollution Index
Lij : Concentration of Water Quality Standard Cij : Concentration of Parameter
Table 2. Standard Water Quality Index (WQI).
No Value Classification 1 (0-25) Excellent 2 (26-50) Good 3 (51-75) Poor 4 (75-100) Very Poor
5 (>100) Unsuitable for Drinking Source: Soni and Thomas (2013).
Open Access 4470 Table 3. Standard Pollution Index (PIj).
No Value Classification 1 (0-1) Good Water Quality 2 (1.1-5) Moderately Polluted 3 (5.1-10) Polluted
4 (>10) Extremely Polluted Source: Ministry of Environmental Regulation (2003).
Results and Discussion
Based on the results of the TDS values measured in the five watersheds, it was known that all samples were still below the Indonesian Government Regulation Standard (Figure 2). However, two samples in the Gajahwong River exceeded the WHO standards, namely samples no 5 and 6, with TDS values of 521 mg/L and 639 mg/L. The two samples had high TDS values originating from domestic waste, considering that they are located in the downstream watershed in Yogyakarta City, with the dominant land use being settlements (Figure 11). All of these samples had a uniform pattern that continues to increase due to increasing TDS values from upstream to downstream of the watershed.
The measured TSS values in the five watersheds showed that only the Glondong Watershed had a TSS value below the WHO standard (Figure 4). In comparison, the other four watersheds were dominant in exceeding the Indonesian TSS standard. The highest TSS value was found upstream of the Rejoso Watershed at 356 mg/L, which is caused by a large amount of sediment entering the river because the upstream area is used for intensive agricultural activities and Mount Bromo Tengger Tourism (Asmara et al., 2022).
The same pattern was also found in the upper Serayu, which had a TSS value of 50 mg/L in the upstream area due to intensive upstream farming and tourism activities in Dieng (Sudarmadji and Pudjiastuti, 2018).
A high TSS value was also found in the downstream Kuntulan watershed at 132 mg/L. The high TSS value at that location was caused by the start of flooding in the river that entered the Bekacak Dam, which resulted in a large amount of material being deposited.
From the COD values in the five watersheds, it is known that all samples are still below WHO standards (Figure 4). Different results were found in the Rejoso and Glondong watersheds, where the dominant water exceeded the Indonesian Government Regulation Standard. The overall COD value in the Rejoso watershed from upstream to downstream (10- 17 mg/L) exceeded the Indonesian standard due to pollution from agricultural fertilizer waste in the upstream and domestic waste in the middle- downstream part of the watershed. This problem is because a high COD value indicates that the amount of oxygen used to oxidize organic matter chemically is relatively high (generally because the location of the river from upstream to downstream is polluted with organic matter).
The same pattern was also found in the Glondong watershed, where all COD values from upstream to downstream exceeded the Indonesian standard (18-29 mg/L). The causes are quite different compared to the Rejoso watershed. Namely, in the upstream of the Glondong watershed, organic matter pollution is caused by weathering of organic material from forests and gardens (forests and gardens dominate the upstream Glodondong watershed). In contrast, the downstream is caused by agricultural fertilizer and domestic waste from settlements (Figure 11D).
Figure 2. TDS value in dry season.
0 200 400 600 800 1000 1200
1 2 3 4 5 6
TDS (mg/L)
Sample Points TDS
Kuntulan Rejoso
Upper Serayu Gajahwong
Glondong WHO Standard
Indonesia Standard
Open Access 4471 Figure 3. TSS result in dry season.
Figure 4. COD value in dry season.
The results of PO43- values in the five watersheds showed that all samples are still below WHO standards (Figure 5). However, the graph also shows different results for all watershed values, which exceeded the Indonesian Government Regulation standard (>0.2 mg/L). The highest PO43- value was found in the Gajahwong watershed, ranging from 0.3 to 0.9 mg/L from upstream to downstream. These results are due to the watershed located in the city of Yogyakarta, which is dominant in the form of settlements that contribute the most significant amount of domestic waste. The PO43- values in the Glondong watershed ranged from 0.3 to 0.8 and were influenced by agricultural land use
and settlements in the middle and downstream.
A different pattern was found in the Rejoso and Kuntulan watersheds with PO43- values ranging from 0.4-0.5 mg/L with industrial waste dominance in the middle of the watershed due to the Pandaan and Kejayan industrial areas and domestic waste dominance in the downstream areas due to settlements and agriculture (Figure 11B). The lowest PO43- value was found in the Upper Serayu watershed, which is influenced by agricultural waste.
From the results of the comparison of NO3-
(nitrate) values in the five watersheds, all samples are still below the WHO Standard (Figure 6).
0 50 100 150 200 250 300 350 400
1 2 3 4 5 6
TSS (mg/L)
Sample Points TSS
Kuntulan Rejoso
Upper Serayu Gajahwong
Glondong WHO Standard
Indonesia Standard
0 10 20 30 40 50 60 70 80 90
1 2 3 4 5 6
COD (mg/L)
Sample Points COD
Kuntulan Rejoso
Upper Serayu Gajahwong
Glondong WHO Standard
Indonesia Standard
Open Access 4472 Figure 5. PO43- value in dry season.
Figure 6. NO3- value in dry season.
The same thing was also found in the Kuntulan, Upper Serayu, and Glondong watersheds which also had NO3- values below Indonesian Government Regulation standards. Different results were found in the Rejoso Watershed, where all samples exceeded the Indonesian Government Regulation standard (>10 mg/L). This value is due to the high upstream agricultural waste in the form of vegetables and agricultural paddy waste in the middle and downstream of the watershed. Another pattern is found in the Gajahwong watershed, with nitrate values exceeding standards in the middle and downstream parts of the watershed caused by domestic waste from settlements in Yogyakarta. There are no agricultural
areas downstream of the Gajahwong watershed resulting in domestic waste still dominating the downstream areas. The results of the analysis of total coliform values in the five watersheds showed that all of them exceeded the WHO Standard (>100 CFUs in 100 mL) (Figure 7). Only the Kuntulan watershed has a total coliform value below the Indonesian Government Regulation standard. The total coliform value of the Gajahwong watershed is relatively high from upstream to downstream (>2,400 CFUs in 100 mL) due to dense settlements in the city of Yogyakarta, which contribute to bathroom waste. These results follow previous research, which stated that the total coliform value in the Gajahwong Watershed remained 0
1 2 3 4 5 6
1 2 3 4 5 6
PO43-(mg/L)
Sample Points PO43-
Kuntulan Rejoso
Upper Serayu Gajahwong
Glondong WHO Standard
Indonesia Standard
0 10 20 30 40 50 60
1 2 3 4 5 6
NO3-(mg/L)
Sample Points NO3-
Kuntulan Rejoso
Upper Serayu Gajahwong
Glondong WHO Standard
Indonesia Standard
Open Access 4473 high during the dry and rainy seasons (Saraswati et al.,
2019). A different pattern is found in the Upper Serayu watershed, with a total coliform of >2,400 CFUs in 100 mL. That problem is caused by organic
fertilization on agricultural land in the upper reaches of the Dieng area (Figure 10A) and tourism activities in Dieng, which dispose of bathroom waste directly into the river.
Figure 7. Total coliform value in the dry season.
The Rejoso Watershed also has a high total coliform value (>2,400 CFUs in 100 mL) due to organic fertilization activities on agricultural land in the upper reaches of Bromo and tourism activities in Bromo, which dispose of bathroom waste directly into the river. Meanwhile, the Glondong watershed is also known to have a high total coliform value (>2,400 CFUs in 100 mL) caused by fertilizer contamination in plantation areas and rice fields, as well as household waste from bathrooms.
Based on measurements of pH values in the five watersheds, it was found that all samples were below
WHO and Indonesian standards (6-9) (Figure 8). The highest pH was located in Rejoso watershed, ranging from 8.2-8.6, while the lowest pH was in the Gajahwong watershed, with a value of 6.6-7.3. The pH value of the Kuntulan, Upper Serayu, and Glondong watersheds has the same pattern, which ranges from 7- 8. The graph also shows that the pH value pattern of the five watersheds is generally higher from upstream to downstream. This phenomenon is because the further downstream, the greater the pH value due to the increasing chemical compounds, carbon dioxide, ammonia, and alkalinity.
Figure 8. pH value in dry season.
0 500 1000 1500 2000 2500 3000
1 2 3 4 5 6
CFUs in 100 mL
Sample Points Total Coliform
Kuntulan Rejoso
Upper Serayu Gajahwong
Glondong WHO Standard
Indonesia Standard
0 5 10
1 2 3 4 5 6
pH
Sample Points pH
Kuntulan Rejoso
Upper Serayu Gajahwong
Glondong WHO and Indonesia Standard
WHO and Indonesia Standard
Open Access 4474 In the analysis EC values in the five watersheds, a
pattern varied for each (Figure 9), although in general, the pattern of EC in all watersheds seems to increase from upstream to downstream. The greater the downstream EC value is due to the increasing addition of dissolved salts in water and dissolved ions. The highest EC value was found in the Gajahwong watershed, ranging from 392-901, caused by the high TDS value in the Gajahwong watershed. Thirumalini
and Joseph (2009) stated a positive correlation between changes in EC values and TDS. These results again show that domestic waste pollution is relatively high in the Gajahwong watershed, dominated by settlements in the Yogyakarta City area. For EC values in other watersheds, the average has the same pattern, ranging from 150-300 µS/cm. All of these watershed samples are classified as freshwater based on EC values (<1,500 µS/cm) (Suherman, 2007).
Figure 9. EC value in the dry season.
The results of temperature measurements in the five watersheds show varying patterns (Figure 10).
Generally, the temperature pattern at all watershed locations increases from upstream to downstream.
This result shows the effect of elevation and altitude, where the lower the elevation, the greater the
temperature value. Therefore, the lowest temperature values of all watersheds are in the upstream part, while the highest temperatures are in the downstream part of the watershed. The lowest temperature value is found in the Upper Serayu watershed of 18 °C at an elevation of 2,000 masl.
Figure 10. Temperature value in dry season.
0 100 200 300 400 500 600 700 800 900 1000
1 2 3 4 5 6
µS/cm
Sample Points Electrical Conductivity
Kuntulan Rejoso Upper Serayu
Gajahwong Glondong
0 5 10 15 20 25 30 35
1 2 3 4 5 6
°C
Sample Points Temperature
Kuntulan Rejoso
Upper Serayu Gajahwong
Glondong
Open Access 4475 In contrast, samples in other upstream watersheds are
generally found at an altitude of 600 masl with a temperature of around 21°C. The overall temperature distribution in the downstream watershed has the same value of 29 °C, while in the middle of the watershed, it generally ranges from 24-27 °C. WQI analysis in the study area shows that the results of the WQI index values in the five watersheds of the study area are included in the excellent classification for both the value of each sample point and the total of all samples
(Table 4). However, quite different results were found in the PIj index analysis, where most watersheds were classified as moderately polluted, polluted, and highly polluted (Table 5). The PIj Index analysis shows that only sample number 1 in the upstream part of the Kuntulan watershed belongs to the classification of good water quality. This result was because the samples at that location had the lowest COD, PO4, NO3, and total coliform values compared to other samples.
Table 4. Water Quality Index (WQI) study area.
No Watershed Water Sampling Points Total Classification
1 2 3 4 5 6
1 Kuntulan 0.54 1.55 0.61 1.15 0.53 - 4.39 (0-25) Excellent
2 Rejoso 0.61 2.77 1.58 0.66 1.62 - 7.26 (26-50) Good
3 Upper Serayu 1.15 1.01 1.09 1.06 - - 4.30 (51-75) Poor
4 Gajahwong 1.06 0.90 1.05 1.06 0.98 0.97 6.02 (75-100) Very Poor 5 Glondong 0.88 0.87 0.86 0.88 0.88 0.91 5.29 Unsuitable for Drinking
Table 5. Pollution Index (PIj) study area.
No Watershed Water Sampling Points Total Classification
1 2 3 4 5 6
1 Kuntulan 0.70 2.13 1.31 1.88 5.48 - 11.50 (0-1) Good Water Quality 2 Rejoso 1.50 2.93 2.50 1.82 3.20 - 11.95 (1,1-5) Moderate Polluted 3 Upper Serayu 1.43 1.36 2.09 1.99 - - 6.88 (5,1-10) Polluted 4 Gajahwong 1.23 1.30 1.34 2.13 1.98 1.95 9.94 (>10) Extreme Polluted 5 Glondong 1.96 1.65 1.44 1.94 1.69 1.94 10.62
Different things were also observed in sample number 5, located downstream of the Kuntulan watershed, which belonged to the polluted classification. Based on the observations and analysis results, this occurs because the COD, PO4, and pH values at these locations are classified as high. The dominance of all sample points in the five watersheds belongs to the moderately polluted classification. In total, all samples included in the highly polluted category were found in the Kuntulan, Rejoso, and Glondong watersheds, while the samples included in the overall polluted classification were in the Upper Serayu and Gajahwong watersheds. A comparison of the water quality index using the WQI and PIj methods in the five watersheds showed very different results. The WQI analysis generally showed that the water quality was excellent. In contrast, the PIj analysis showed variations in water quality from moderate, Polluted, and extreme pollution. These results are caused by the difference in the standard limit values for each WHO parameter which is more general and global than the more specific Indonesian standards (Table 1). WHO standard parameter values are much smaller than Indonesian standards for TDS, TSS, and Total coliform parameters and much more significant for COD, PO4, and NO3 parameters. In addition, there are
also differences in the WQI equation formula, which uses a weighted sum (Equation 1), while PIj uses the square root of the harmonic mean of squares (Equation 4). This difference in formula affects the final calculation results, which also produces differences in the results of water quality studies (Sutadian et al., 2016; Banda and Kumarasamy, 2020; Tyagi et al., 2020). Differences were also found in the classification of the final results of the two analyzes, where the WQI analysis had a more extensive range, namely 0-100, compared to the PIj analysis, which only had a range of 0-10. The classification of PIj proves to be more detailed because it has been adapted to Indonesian standards (Barokah et al., 2017;
Nurrohman et al., 2019; Widodo et al., 2019; Novita et al., 2020; Damayanti et al., 2021; Rahmatillah et al., 2021; Wijayanti et al., 2021). In addition, the PIj analysis can also be applied to a single collection of water quality specimens (Saraswati et al., 2019), in contrast to the WQI study, which requires taking several water quality samples (Chen et al., 2022). The results of the PIj analysis are known to be under direct comparisons between the parameter values measured with the standard parameter limit values, where the entire watershed is considered polluted for each parameter.
Open Access 4476 Figure 11. Land use map (based map source: BIG, 2004).
The results are in stark contrast to the WQI classification, which also compares the parameters measured with the standard parameter limit values of the WQI classification, which indicates overall water quality is excellent. These results follow research from Triaji et al. (2017), which states that in Indonesia, there are WQI values in rivers that are included in the medium class. Similar results were found elsewhere with a WQI range of 0-50, which is included in the good/excellent classification (Said and Khan, 2021;
Soni and Thomas, 2013). In another analysis, the results of a different WQI classification with a score of 0-25 were included in the very bad/poor class (Akinbile and Omoniyi, 2018; Chen et al., 2022). For this reason, it can be stated that there are differences in the analysis and classification results based on the calculation results of the WQI formula.
Conclusion
The five watersheds studied in this study are all found in young volcanic deposit areas in Indonesia, which are in a tropical climate, so all of them have a pattern that typically has almost the same water quality, both WQI and PIj values. However, the differences in the results of water quality classification using WQI and PIj analysis show very different results. Based on this study, for the WQI index, the overall results of river water in the five watersheds belong to the excellent
classification. Meanwhile, for the results of the PIj index, it was found that the five watersheds dominantly belong to the moderately polluted category, with several samples belonging to the polluted and extremely polluted classifications. The difference in the analysis and classification results is due to the difference in the index formula and water quality standards used. The results of the PIj index are generally more representative than the WQI with a classification comparison of water quality values with water quality standards which is also more appropriate than the WQI. The comparison of water quality between WHO and Indonesian Government standards shows that the whole watershed has several water quality samples that exceed the standards. In general, the water quality in the five watersheds exceeds the quality standards, so special treatment is needed so that the water in the five watersheds is suitable to be used as a source of raw water for drinking water. However, for the water used for irrigation, livestock, industry, and fisheries, it can be said that the water from the five watersheds is still suitable for direct use.
Acknowledgements
The authors thank the Department of Geological Engineering, Faculty of Engineering, Universitas Gadjah Mada, for research permits, equipment, and laboratory support. The authors also thank PT Tirta Investama and PT Tirta Fresindo Jaya for the research collaboration.
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