Identification of Groundwater Potential Zone for Drinking ...

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JOINT CONVENTION BANDUNG (JCB) 2021

December 1st – 3rd 2021

Identification of Groundwater Potential Zone for Drinking Water Demand in Muara Empayang

Village, Lahat Regency, South Rina Sahara1, Muhammad Faris Hafiddin2, Muhammad Fadhli1, Tommy Julio Lumban Tobing3

1Geological Engineering Study Program, Sriwijaya University 2DMS Program Pamsinas III Kabupaten Lahat

3Balai Besar Pelaksanaan Jalan Nasional V Sumatera Selatan

Abstract

Water becomes a daily human need for survival such as drinking water, household needs, agriculture, livestock, and

many other things. Along with the increasing number of populations the population compensates for the increasing

water needs. Sehingga needs to research to find out the potential of groundwater that is following standardization in

clean water that can be drink. The study was conducted in Muara Empayang Village by conducting spatial data

analysis using fuzzy logic approaches, geoelectric surveys, and water quality tests according to PERMENKES No.37

of 2017. Fuzzy logic approaches use fuzzy membership and fuzzy overlay operations with slope, geomorphology,

elevation, and drainage parameters. Geoelectric surveys use a terameter (resistivity meter) by an electric current into

the ground using electrodes and recording their resistance in the response time dimension. From validation results

based on fuzzy logic, geoelectric surveys, and water quality tests, the research site has the potential to become an

aquifer with flow through space between grains, moderate productive aquifers with widespread spread have moderate

to low canes with diverse water levels that can be used as community consumption, but need special treatment to be

used as drinking water.

Keywords: Muara Empayang, Groundwater, Drinking water, Fuzzy Logic, Aquifer

Introduction

Groundwater is a very valuable natural resource

in everyday life. The increase in the number of people

every year has an impact on the increasing need for

clean water to support human survival. This raises

concerns about the availability of clean water.

Groundwater is part of the hydrological cycle

and is in rocks below ground level which includes the

discovery, spread, and movement of groundwater with

an emphasis on the relationship of regional geological

conditions (Danaryanto, et al., 2005). The factor that

causes poor groundwater quality is the process of

overexploitation.

Identifying groundwater quality includes

physical, chemical, and biological parameters. It is

strongly influenced by the nature of water, the content

of living things, substances, energy, and other

components in water. The physical analysis includes

smell, taste, amount of solutes, turbidity, temperature,

color. While chemistry in the form of Fe, Cd, CaCo₃,

Mn, NO₂, pH, Zn, CN, SO₄, Pb, and on biological

parameters are Total Coliform and Escherichia Coli.

Regionally the location of the study is on the

Bengkulu sheet composed of Kasai formation and

Plieosen-aged alluvium and quaternary composed of

continental sandstone and clay and pyroclastic

material (fig. 1). The topography of the research area,

in general, is lowlands and low hills with slope slopes

from flat to very steep.

This research aims to find out the potential of

groundwater as well as the distribution of groundwater

spread and quality for drinking water as an effort to

meet the needs of the people of Muara Empayang

Region, East Kikim Subdistrict, Lahat Regency,

South Sumatra.

Data and Method

The research was conducted in Muara Empayang

Area, East Kikim Subdistrict, Lahat Regency, South

Sumatra (fig.2). The methods used are literature

studies and field observations in the form of

geological observations, resistivity surveys, physics,

chemical, and biological sample tests, and

groundwater suitability analysis using fuzzy logic in

ArcGIS software (fig. 3). Literature studies discuss

the regional geology of the research area which is

further carried out field observation in the form of

resistivity surveys with 2 trajectories and 2 potential

electrodes and distances between spaces of 250 meters

using the Schlumberger electrode configuration.

Furthermore, water quality analysis tests were

conducted on 2 samples based on physical, chemical,

and biological characteristics according to Decree

No.32 of 2017 on standard standards of water quality

and health. The last fuzzy logic approach with fuzzy

membership and fuzzy overlay operating models is

available on ArcGIS software. In fuzzy membership

and fuzzy overlay, operations used parameters in the

form of slope, geomorphology, elevation, and

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drainage. Fuzzy membership values are adjusted to

the rating. The value of 0 is very bad, 0.5 is medium

and 1 is a very good water potential zone (Ratheret al.,

2012).

Result and Discussion

Geolistrik Analysis

The geoelectric testing of Schlumberger's

configuration was performed to determine the

potential of the water. Geolmeasurements are tricks

showing electrical resistivity between 5 - 32 Ohm-

meters (fig. 4) with clay lithology, sand clay, and clay

sand (fig.5). Aquifer system with flow through space

between grains, medium productive aquifers with

widespread have moderate to low cans with varying

water levels (Table 1).

Water Quality Test

Determining the quality water that is worth

drinking or not feasible must be analyzed by water

quality standards issued by PERMENKES No.37 of

2017, it consists of several parameters, namely

Physical, Chemical, and Biological Characteristics.

a) Physical Characteristics

In determining the physical characteristics of

water, it includes temperature, turbidity, color, smell,

and taste (Todd, 2005). In the research area, water

sampling was conducted at two well-point locations

with the codes ME-01 and ME-02. The location of

ME-01 obtained the results that groundwater in the

location of the study does not smell and taste and for

color obtained a value of 15 / 50 from the TCU scale.

Furthermore, the results of the amount of solid toot

(TDS) produced a value of 64 / 1000 units mg/liter and

turbidity produced a value of 0.06 / 25 of the NTU

scale unit. And from the last parameter that

temperature obtained a value of 25 ̊c.

While at the location of ME-02 obtained the results

that groundwater in the research location does not

smell and taste and has a color content of 13/50 from

the TCU scale. Furthermore, in the test results, the

amount of toot solid substances (TDS) produced a

value of 66 / 1000 from mg/lite units, turbidity with a

value equal to the location of ME-01 which is 0.06,

and a jar with a value of 25 ̊c equal to the me-01

sample. In the acquisition of data, using Organoleptic

method for odor and taste tests, Direct Reading for

TDS tests, SNI 06-6989.25-2005 for turbidity and

temperature, and color tests using spectrophotometry

methods.

b) Chemical Characteristic

Determining the chemical characteristics of water

can be done using the methods ICP-OES, SNI 06-

6889, 12-2004, and SNI 6989.11.2019. Quality tests

using the ICP-OES method include iron (Fe),

cadmium (Cd), manganese (Mn), zinc (Zn), and lead

(Pb). The location of ME-01 and ME-02 still qualified

according to the health minister's quality standard test.

The locations of ME-01 and ME-02 have the same

values, namely Iron (Fe) values 0.14, Cadmium <

0.0015, Manganese (Mn) 0.11, Zinc (Zn) < 0.0050

and Timbal (Pb) < 0.0031. Furthermore, SNI 6989.12-

2004 elements of CaCo₃ obtained results that meet the

quality standard where ME-01 has a value of 114 and

ME-02 102. And finally based on SNI 6989.11.2019, analysis of NO₂, pH, and SO₄, from the results of NO₂,

SO₄ value meets the quality standard that is Me-01

0.01, 31.11, and Me-02 0.01, 42.89, but for pH

obtained the results have not met the quality standard

with a value of ME-01 6.43 and mE-02 5.58. The

standard test parameters of quality and analysis results

are in table 2.

c) Biological Characteristic

Determining the biological characteristics of water

can be done using a test detection of coliform bacteria

content (Todd, 2005. According to Decree No. 37 of

2017, the maximum threshold for total coliform is 50

CFU/100 ml, andE-Coil is 0 CFU/100 ml. In the area

of the me-01 and ME-02 research sites, CFU and

Escherichia Coli were 200 ml. Therefore, it can be

known that groundwater at the peneplain site has been

polluted so it is not recommended to be consumed

directly. The standard test parameters and analyst

results are found in table 3.

Fuzzy Logic Data Analyze

Fuzzy logic is a numerical for spatial modeling

problems. A fuzzy system consists of 3 main

elements, namely fuzzy set, fuzzy membership, and

fuzzy production. The fuzzy theory was introduced by

Zadeh, 1965. The membership value of an object

ranges between 0 and 1. The value 1 means the full

membership of an object and the closer the value of 0

the weaker the membership of the object in the fuzzy

set (Kollias et al, 1998).

Fuzzy models use fuzzy membership operations

and fuzzy overlays available on spatial analysis of

ArcGIS software. In generating a map of groundwater

potential by analyzing the interrelationships between

spatial data layers and the influence on groundwater

systems. The fuzzy membership function curve (Fig. 6) defines a point in a fuzzy membership input interval

between 0 and 1. This function helps determine the

influence of the lowest to highest parameters.

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Fuzzy overlay is a relative relationship and

interaction measurement. Fuzzy overlay approach in

the form of fuzzy And, fuzzy Or, fuzzy Product, fuzzy

Sum and fuzzy Gamma.

1. Fuzzy And: Fuzzy overlay type to find locations

that meet a wide variety of criteria.

2. Fuzzy Or: Fuzzy overlay type to find a location

that meets one of the criteria.

3. Fuzzy Product: Fuzzy overlay type to find

locations with various combined fuzzy

membership values.

4. Fuzzy Sum: Fuzzy overlay type for possible

locations that correspond to fuzzy membership

inputs.

5. Fuzzy Gamma: A very complex fuzzy overlay

type with a combination of various spatial sub-

data.

In fuzzy membership and fuzzy overlay,

operations are used in a suitable combination of slope,

geomorphology, elevation, and drainage. Fuzzy

membership values are adjusted to the rating. The

value of 0 is very bad, 0.5 is medium and 1 is a very

good water potential zone. Secondary data processing

based on DEMNas data on a scale of 1:40,000. The

slope of slopes based on Widyaatmanti classification

2016 to 6 categoy. Geomorphology from elevation

consists of 2 landfrom. In addition, DEM data used for

elevation classification and high drainage density

reflects the basin where fluid flows with a rapid

hydrological response to rainfall while low drainage

density indicates slow-response basins to rainfall at

the research site consisting of flat or almost flat until

very steep (fig. 7).

In the fuzzy overlay combine various spatial data,

applied fuzzy sum operators, a fuzzy sum approach

that shows the location of the study can be used with

a value between 0.2 to 1(fig. 8) as well as weighting

in table 4.

Conclusions

Based on the results of data analysis using

geoelectric surveys, water quality analysis, and fuzzy

logic, it can be known that the research site has the

potential to meet the needs of the people of Muara

Empayang Region, East Kikim Subdistrict, Lahat

Regency, South Sumatra. This can be known from the

results of fuzzy membership and fuzzy overlay

approaches with a value range of 0.2 to 1 that shows

low hills topography areas with sloping slopes.

Electric surveys show electrical resistivity between 5-

32 Ohm-meter with clay lithology, sandy clay, and

clay sand can be known the flow of a medium

productive aquifer system with widespread has a

moderate to low with varying water levels.

Furthermore, in determining water quality, tests of

the characteristics of physics, chemistry, and biology

are carried out. The physical characteristics of water

quality can be used, but in chemical tests, the pH

content has not been met because it obtained results

less than the quality standard, and biological results do

not support water used directly.

From this, the need for further systematics to

become water that is worth drinking directly.

References

Danaryanto, Djaendi., et al. 2007. Department of

energy and mineral resources geological agency,

geological environment center, Bandung.

Gafoer, S., et al. 1992. Geological Research and

Development Centre.

Goyal, Sandeep., et al. 2017. Journal of Geomatics,

11, 2.

Kollias, V.J.and D.P., Kollias, 1998. Computers and

Electronics in Agriculture, 20, pp. 79–95.

Mallik, Santanu., et al. 2021. Ecological Indicators

121 (2021) 107179.

Rafati, S., and M. Nikeghbal. 2017. The International

Archives of the Photogrammetry, Remote Sensing

and Spatial Information Sciences, Volume XLII-

4/W4, 2017

Rather, J.A., and A.B. Zameer and A. Raouf (2012). Journal of Advances in Remote Sensing and GIS, Vol.

1, No. 2, 2012, 218-233.

Republic of Indonesia. 2017. PERMENKES No.32 of

2017. Jakarta. Government of the Republic of

Indonesia.

Todd, D.K., et al. 2005. Groundwater Hydrology,

Third Edition. NewYork: John Wiley & Sons

Acknowledgments

We are grateful to Joint Convention Bandung for

accepted our paper. We would like to thank all

members of JCB Sriwijaya for supported this study.

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Table 1. Interpretation result of survey electric resistivity

Table 2. Fisical and chemistry analysis of water quality

1 0,00 5,17

2 5,17 10,21

3 10,21 35,85

4 35,85 ˜

1 0,00 6,49

2 6,49 70,88

3 70,88 ˜

Akuifer

GL.1

64,39

5,20

15,82

Tanah Penutup

Lempung

Lempung Pasiran Akuifer

GL.2

19,30

Tanah Penutup

Pasir Lempungan

Lempung

Lempung Pasiran

Perkiraan Litologi Perkiraan Hidrogeologi

114,39

32,44

6,52

Air Tanah Bebas

Hasil Penafsiran

Kedalaman Tahan JenisLapisan Titik Duga

No Parameter SatuanStandar Baku Mutu

(Kadar Maksimum)Hasil Metode Pemeriksaan

1 Bau # Tidak Berbau Tidak Berbau Organoleptik

2 Rasa # Tidak Berasa Tidak Berasa Organoleptik

3 Jumlah zat padat terlarut (TDS ) mg/liter 1000 64 Direct Reading

4 Kekeruhan SkalaNTU 25 0,06 SNI 06-6989.25-2005

5 Suhu °C Suhu udara ±3 25 SNI 06-6989.25-2005

6 Warna Skala TCU 50 15 Spektrofometri

1 Besi (Fe) mg/liter 1 0,03 ICP - OES

2 Kadmium (Cd) mg/liter 0,005 <0,0015 ICP - OES

3 Kesadahan (CaCo₃) mg/liter 500 114 SNI 06-6989.12-2004

4 Mangan (Mn) mg/liter 0,5 0,06 ICP - OES

5 Nitrit (NO₂) mg/liter 1 0,01 SNI 6989.11.2019

6 pH (di Laboratorium) # 6,5 - 8,5 6,43 SNI 6989.11:2019

7 Seng (Zn) mg/liter 15 <0,0050 ICP - OES

8 Sianida (CN) mg/liter 0,1 <0,003 Spektrofometri

9 Sulfat (SO₄) mg/liter 400 31,11 SNI 6989.20:2019

10 Timbal (Pb) mg/liter 0,05 <0,0031 ICP - OES

1 Bau # Tidak Berbau Tidak Berbau Organoleptik

2 Rasa # Tidak Berasa Tidak Berasa Organoleptik

3 Jumlah zat padat terlarut (TDS ) mg/liter 1000 66 Direct Reading

4 Kekeruhan SkalaNTU 25 0,06 SNI 06-6989.25-2005

5 Suhu °C Suhu udara ±3 25 SNI 06-6989.25-2005

6 Warna Skala TCU 50 13 Spektrofometri

1 Besi (Fe) mg/liter 1 0,14 ICP - OES

2 Kadmium (Cd) mg/liter 0,005 <0,0015 ICP - OES

3 Kesadahan (CaCo₃) mg/liter 500 102 SNI 06-6989.12-2004

4 Mangan (Mn) mg/liter 0,5 0,11 ICP - OES

5 Nitrit (NO₂) mg/liter 1 0,01 SNI 6989.11.2019

6 pH (di Laboratorium) # 6,5 - 8,5 5,58 SNI 6989.11:2019

7 Seng (Zn) mg/liter 15 <0,0050 ICP - OES

8 Sianida (CN) mg/liter 0,1 <0,003 Spektrofometri

9 Sulfat (SO₄) mg/liter 400 42,89 SNI 6989.20:2019

10 Timbal (Pb) mg/liter 0,05 <0,0031 ICP - OES

B. Kimia

ME 02

A. Fisika

ME 01

A. Fisika

B. Kimia

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Table 3. Biology analysis of water quality

Table 4. Thematic parameters of fuzzy membership

Figure 1. Geology Map Muara Empayang (Modified S. Gafoer, T.C. Amin and R. Pardede, 1992)

Nama SampelCFU/100 ml

Total Coliform

CFU/100 ml

Escheria Coli

ME 01 200 200

ME 02 200 200

Parameter Class Fuzzy membership

Geomorphology Low Hill 0,22

Low Land 0,24

Slope (%)

0 – 2 1

3 – 7 1

8-13 0,85

14 - 20 0,25

21 - 55 0,31

56 - 140 0,16

Elevation (m)

50 - 75 1

75 - 100 1

100 - 125 1

Drainage

0 - 14 0,08

28 - 42 0,04

42 - 56 0,02

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Figure 2. Field observation electric resistivity and water quality analysis at Muara Empayang

Figure 3. Research Flow

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Figure 4. 1D Schlumberger from electric resistivity at Muara Empayang

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Figure 5. Vertical cross-sectional resistance type point estimate electric resistivity

Figure 6. Fuzzy membership function program (Modified Goyal, Sandeep et al, 2017)

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Figure 7. Fuzzy membership parameters

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Figure 8. Groundwater potential zone from combination geomorphology, slope, elevation, and drainage.

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