Journal of Natural Resources and Environmental Management http://dx.
org/10.
29244/jpsl.
RESEARCH ARTICLE
Analysis of the Pollution Load Capacity of Batang Merao Watershed in Jambi Province Syiskha Eka Patria.
I Putu Santikayasab.
Suria Darma Tariganc Study Program of Natural Resources and Environmental Management.
Postgraduate School of IPB University.
IPB Baranangsiang Campus.
Bogor, 16143.
Indonesia Department of Geophysics and Meteorology.
Faculty of Mathematics and Natural Sciences.
IPB University.
IPB Darmaga Campus.
Bogor, 16680.
Indonesia Department of Soil Science and Land Resources.
Faculty of Agriculture.
IPB University.
IPB Darmaga Campus.
Bogor, 16680.
Indonesia Article History Received 16 November 2023 Revised 20 February 2024 Accepted 24 February 2024 Keywords Batang Merao.
QUAL2Kw.
Total Maximum Daily Loads ABSTRACT The Batang Merao Watershed, has been experiencing a decline in water quality due to human activities involving waste utilization and disposal.
Therefore, an analysis is necessary to determine the Total Maximum Daily Loads (TMDL.
This study aims to calculate the TMDL of the Batang Merao Watershed and the current as well as the five-year future pollution load capacity using the QUAL2Kw water quality model based on the regulations outlined in the Minister of Environment and Forestry's Regulation No.
01 of 2010.
The calibration results of the model using the Nash Sutcliffe Efficiency (NSE) for TSS.
BOD5, and COD parameters were 0.
766, 0.
574, and 0.
633, respectively, indicating that water quality modeling can be used to predict river pollution loads.
The modeling results indicate that the Total Maximum Daily Loads (TMDL.
for the Batang Merao Watershed are 95,057 kg day-1 for TSS parameters, 5,739 kg day-1 for BOD5 parameters, and 46,774 kg day-1 for COD parameter.
Meanwhile, the current pollution loads are 147,962 kg day-1 for TSS, 10,086 kg day-1 for BOD5, and 60,369 kg day-1 for COD.
In the estimated condition, in the year 2028, the pollution loads will amount to 163,023 kg day-1 for TSS parameters, 11,432 kg day-1 for BOD5 parameter, and 69,211 kg day-1 for COD parameter.
Introduction Batang Merao River Watershed spans two administrative regions: Kerinci Regency and Sungai Penuh City in Jambi Province.
The Batang Merao Watershed plays a vital role for the residents of Kerinci Regency and Sungai Penuh City.
It serves as a water source for agricultural irrigation, provides additional livelihoods for fishing communities, and is utilized for daily activities, such as bathing, washing, and sanitation.
Additionally, it serves as a raw water source for drinking water regional companies and supports alternative energy sources, such as Micro-Hydro Power Plants .
People living along the riverbanks rely on the Batang Merao River for household waste disposal.
Furthermore, agricultural activities along riverbanks involve livestock such as cattle, goats, and ducks.
The increasing population growth along the Batang Merao River has exacerbated these issues.
The degradation of the Batang Merao Watershed is on the rise, and in addition to changes in land cover, poor watershed management is also a significant factor contributing to declining watershed quality .
Activities such as the disposal of waste into the river, runoff from agricultural fields, and sand mining operations in the upstream regions of Sub-DAS Siulak and Batang Merao have led to water quality that is unfit for consumption.
Laboratory tests have revealed elevated levels of chloride (C.
and iron (F.
that exceed river water quality standards .
Rivers are natural water resources that must be preserved and protected from pollution sources, including pollutants and liquid waste originating from industrial, domestic, agricultural, and other sources .
Corresponding Author: Syiskha Eka Patri ekapatrisyiskha@apps.
Study Program of Natural Resources and Environmental Management.
Postgraduate School of IPB University.
IPB Baranangsiang Campus.
Bogor.
Indonesia.
A 2024 Patri et al.
This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY) license, allowing unrestricted use, distribution, and reproduction in any medium, provided proper credit is given to the original authors.
Think twice before printing this journal paper.
Save paper, trees, and Earth! Based on the results of the Environmental Management Performance Information Document for Sungai Penuh City in 2022, both upstream and downstream of the Batang Merao River have concentrations of parameters such as BOD5 (Biochemical Oxygen Deman.
COD (Chemical Oxygen Deman.
TSS (Total Suspended Solid.
, and fats and oils that exceed the water quality standards outlined in Government Regulation No.
82 of 2001.
Class II.
The Water Quality Index/Indeks Kualitas Air (IKA) from 2015 to 2021 tended to increase.
In 2015, the IKA value was 30.
in 2021, it increased to 51.
To develop programs for water quality management and pollution control, it is essential to have a good understanding of the various human activities that influence rivers .
Jambi Province has not yet established the Total Maximum Daily Load (TMDL) for the Batang Merao Watershed.
However, based on the water quality monitoring results in the 2022 Regional Environment Management Performance Information Document/Dokumen Informasi Kinerja Pengelolaan Lingkungan Hidup Daerah (DIKPLHD), the Batang Merao Watershed is experiencing light pollution.
This indicates that the pollution entering the river exceeded the river's TMDL.
Therefore, according to the Ministry of Environment and Forestry's Regulation No.
01 of 2010 regarding Procedures for Controlling Water Pollution, local governments must determine water quality.
Determining wastewater quality standards begins by determining TMDL to understand the riverAos pollution load capacity.
Determining the TMDL and pollution load capacity for both the existing condition and the next five years requires a substantial amount of financial resources and a significant amount of time to generate accurate data .
Therefore, water quality modeling approaches are necessary to minimize these issues.
The QUAL2Kw model is a commonly used one-dimensional water quality simulation model designed to simulate variations in river water quality and is capable of calculating the rate of changes and dispersion due to pollution loads .
In Indonesia, numerous studies have been conducted to assess pollution modeling, particularly using QUAL2Kw, on rivers with hydrological characteristics similar to those of the Batang Merao River.
One such example is modeling the Karang Mumus River in Samarinda City using QUAL2Kw, which can provide calculations for pollution load capacity.
This enables the formulation of strategies to manage the Karang Mumus River .
The QUAL2Kw model on the Tukad Bandung River, one of the major rivers flowing Denpasar, allows for the simulation of the pollution load.
This simulation provided alternative management options derived from simulated scenarios .
The simulation results from the QUAL2Kw model can calculate the excess pollution load of BOD5 and COD parameters in the Bukit Batu River in Bengkalis Regency .
Water quality modeling can assess pollution loads under various scenarios, thereby helping to determine effective water resource management policy strategies .
,8Ae.
Water quality is critical for water resource management .
Based on the issues mentioned above, the decline in the water quality of the Batang Merao River indicates that the watershed has experienced pollution, which, in turn, impacts the sustainability of water resources within the Batang Merao Watershed.
Given the complexity of the Batang Merao River issues and the existing studies on the decline in water quality and quantity in the Batang Merao Watershed, it is necessary to research and identify the dominant factors contributing to the decline in river water quality.
This study should also aim to obtain the TMDL through QUAL2Kw model simulations and formulate watershed management policy strategies.
The goal is to ensure that the Batang Merao River can be utilized in accordance with its intended purposes and remains sustainable.
Methods Study Area The research was conducted from May to July 2023 at 13 sampling points, as shown in Table 1, spanning 74 km from the upstream to the downstream of the Batang Merao Watershed.
Among these points, eight sampling locations were used as data for the model simulation, and five sampling points were employed for model calibration.
River water sampling activities were carried out from morning to afternoon using the grab sampling method, following the guidelines outlined in the Indonesian National Standard (SNI 8995Ae2.
regarding the Sampling Method for Physical and Chemical Testing of Water.
This research was conducted in the Batang Merao Watershed, located in the administrative regions of Kerinci Regency and Sungai Penuh City in Jambi Province.
The research area map is shown in Figure 1.
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Figure 1.
Study area.
Table 1.
Sampling points.
No.
Sampling points Upstream Segment 1 (Agricultura.
Segment 1 (Residentia.
Segment 2 (Residentia.
Segment 2 (Agricultura.
Segment 3 (Residentia.
Segment 3 (Agricultura.
Segment 4 (Agricultura.
Segment 4 (Residentia.
Segment 5 (Residentia.
Segment 6 (Residentia.
Segment 6 (Agricultura.
Downstream Coordinate point S 01051'18" E 101016'06.
S 01053'09" E 101017'46"
S 01054'22" E 101017'56"
S 01056'45" E 101020'05"
S 01057'17.
9" E 101020'34.
S 01058'02.
9" E 101021'18.
S 01058'17.
9" E 101021'41.
S 02000'37.
1" E 101023'00.
S 02001'02.
1" E 101023'04.
S 02002'36.
6" E 101024'41.
S 02006'02.
7" E 101025'53.
S 02007'41.
7" E 101027'05.
S 02008'07.
1"E 101027'24.
Data Collection Method Descriptive and experimental research was conducted, and the data collected included both primary and secondary data.
Primary data collection involved in-situ parameters measured at the sampling locations, including temperature and pH.
Additionally.
GPS coordinates were recorded, and river water velocity was measured using a current meter.
Other collected data included river depth and width measurements, cloud cover, and shade.
The length of each river segment and area of agricultural land were determined using ArcGIS 10.
8 software.
Water samples from the river were collected and subjected to water quality testing for parameters such as TSS (Total Suspended Solid.
BOD 5 (Biochemical Oxygen Deman.
, and COD (Chemical Oxygen Deman.
at the Environmental Laboratory of the Jambi Provincial Environmental Agency.
Secondary data, such as wind speed and shade, were obtained from online.
ccessed on 3 July 2.
, while population data were sourced from bps.
ccessed on 3 July 2.
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Data Analysis Method The water quality of the Batang Merao Watershed was analyzed in the laboratory for the following parameters: TSS, analyzed based on SNI 6989.
3:2019.
BOD5, analyzed based on SNI 6989.
72:2009.
and COD, analyzed based on SNI 6989.
73:2019.
The laboratory test results, along with other supporting data, were input into the QUAL2Kw application with three different modeling scenarios, as shown in Table 2.
Table 2.
QUAL2Kw models.
No.
Model Water quality Existing Next 5 years Upstream Water quality standard Class II PP 22 Year 2021 Existing conditions Existing conditions Point source Trial and error Diffuse source Trial and error Existing Existing Trial and error Population growth rate Purpose Determine TMDL of Batang Merao Watershed Determine the current pollution load capacity Determine the pollution load capacity for the year 2028 Water quality modeling based on standards results in the TMDL, which is used as a reference in determining the river's pollution load capacity.
TMDL is the ability of water in the body to accept pollutants but does not cause the water to be polluted.
if the river's pollution load exceeds its TMDL, it means the river lacks pollution load capacity, indicating pollution.
Conversely, the river was considered unpolluted if the pollution load was less than the TMDL.
Existing water quality modeling describes the current conditions of a river.
When the pollution load capacity is known, it can be used to determine whether the river is polluted.
Meanwhile, water quality modeling for five years ahead estimates the river's condition in the year 2028, assuming population growth based on the population growth rate in 2022 based on secondary data from Kerinci Regency in figures 2023 and Sungai Penuh City in figures 2023, with point sources, climate, and river discharge remaining in their current state.
The population growth projection uses the following arithmetic formula for Malthus .
ycEycu = ycE0.
where Pn is population at the end of the year.
P0 is population at the beginning of the year, r is population growth rate, t is difference between the end and beginning years.
After estimating the population in 2028, the clean water usage rate was calculated using Formula 2 for Preston .
Qclean water = Population .
x Clean water requirement .
L person-1 day-.
Clean water flow is needed to calculate the domestic wastewater flow using Formula 3, according for Fair .
Qdomestic wastewater = 80% x Qclean water After inputting all data into the QUAL2Kw application, concentration models for each segment are yielded.
model calibration was performed before calculating the pollution load using the concentration data obtained from the model.
Model calibration using the Nash-Sutcliffe efficiency (NSE) provides results with relatively small errors and has been proven effective in simulating water quality data for efficient river water quality restoration planning .
The Nash-Sutcliffe efficiency test aims to verify the model's accuracy using the criteria presented in Table 3 by Nash and Sutcliffe .
Ocycu .
cuOey.
2 ycAycIya = 1 Oe Ocycn=1 ycu .
cuOeyc.
ycn=1 where NSE is Nash-Sutcliffe coefficient, n is number of data points, y is value from the model result, x is value from the observed data, and xI is mean value of the observed data.
Table 3.
Nash-Sutcliffe Efficiency (NSE) value criteria.
NSE value 75< NSE < 1 65 < NSE < 0.
5 < NSE < 0.
NSE < 0.
Interpretation Very good Good Satisfactory Unsatisfactory If the NSE value is more significant than 0.
5, the modeled concentration data can be used as a reference for pollution load calculations.
The pollution load calculation was based on the formula provided by Novotny and Olem .
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BP = Q x C x f where BP is pollution load .
g day ).
Q is discharge .
s ).
C is pollutant concentration .
g L ), and F is correction factor .
4 kg L s mg-1 m-3 day-.
The pollution load obtained from water quality modeling based on standards is referred to as the TMDL.
The pollution load capacity for existing conditions and five years ahead can be calculated using the following Pollution Load Capacity .
g day-.
= TMDL Oe Calculated pollution load Results and Discussion River Segmentation The initial step in calculating the TMDL was to divide the river into six segments, as shown in Figure 2.
River segmentation is based on administrative district boundaries, pollution source locations, and the length of each river segment.
The river segmentation map provides the length of each river segment as indicated in Table 4.
These data are essential for inputting into the QUAL2Kw application.
The pollution load capacity for each river segment was determined in the TMDL calculation.
Therefore, this information is crucial for establishing policy recommendations for river management based on the pollution-load capacity of each Figure 2.
River segmentation map.
Table 4.
River segment identification.
Segment http://dx.
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District Mount Kerinci Siulak and Siulak Mukai Warm Water and Western Warm Water Depati IV Hamparan Rawang and Village Land Kumun Debai and Kerinci Lake Total Segment length .
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The water quality concentration values entered into the QUAL2Kw application were for sampling points 1, 2, 4, 6, 9, 10, 11, and 13, while the other points were used for model The calibration results of the model using the NSE for TSS.
BOD5, and COD parameters were 766, 0.
574, and 0.
633, respectively, indicating that water quality modeling can be used to predict river pollution loads.
The proximity of the observed values to the model results indicates that the TSS.
BOD 5, and COD concentrations from the water quality model can be used in TMDL calculations.
Figure 3 shows the QUAL2Kw output graph, where the x-axis represents the sampling points from upstream to downstream, and the y-axis represents the pollutant concentration.
The black squares represent the observed data, whereas the red lines represent the model data.
Figure 3 shows that the observed and model data are similar in terms of concentration values, and there is a trend of increasing concentration values from upstream to Batang_Merao .
/16/2.
BOD .
g L-.
ISS .
g L-.
Batang_Merao .
/16/2.
COD .
g L-.
Distance upstream (K.
Distance upstream (K.
Batang_Merao .
/16/2.
Distance upstream (K.
Figure 3.
QUAL2Kw output graphAecomparison of observed data with model data .
TSS .
BOD, .
COD.
Pollution Load Capacity The calculation of the TMDL for the Batang Merao Watershed is based on key river water quality parameters, which include TSS.
BOD5, and COD.
The water quality standards for the TMDL calculations in the Batang Merao Watershed are based on Class II water quality standards according to Government Regulation No.
of 2021 on the Implementation of Environmental Protection and Management.
Annex VI.
National Water Quality Standards.
The key parameters used in the model were Class II standards: 3 mg L-1 for BOD5, 25 mg L1 for COD, and 50 mg L-1 for TSS.
The calculation of TMDL for the Batang Merao Watershed was performed using the QUAL2Kw application, and it involved trial and error adjustments to the water quality test concentration for point sources and diffuse sources until the concentration distribution of TSS.
BOD5, and COD parameters at each sampling point was below Class II water quality standards according to government regulations .
The calculation results are listed in Table 5.
In Table 5, the concentration of each segment is presented as the output of QUAL2Kw application.
The obtained concentration values met the water quality standards and were used to calculate the Total Maximum Daily Load (TMDL).
The calculated TMDL for the Batang Merao Watershed can serve as a reference for determining the current and future pollution load capacity.
The pollution load capacity for each segment can serve as a guideline for government authorities to monitor the water quality of the Batang Merao Watershed.
The government can formulate different policies for each segment based on the values obtained for TSS.
BOD5, and COD.
The TMDL obtained through modeling represents the maximum allowable pollution load that the Batang Merao Watershed can withstand.
If the river only receives pollution loads, as presented in Table 5, it can undergo optimal self-purification, ensuring the river's water quality is well preserved.
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Table 5.
Presents the results of TMDL calculations for the Batang Merao Watershed.
Segment
Total
TSS
Concentration .
g L-.
TMDL .
g day-.
11,828 20,372 13,710 19,063 11,044 19,040 95,057 BOD5 Concentration .
g L-.
TMDL .
g day-.
1,088 1,086 1,254 5,739 COD Concentration .
g L-.
TMDL .
g day-.
6,677 9,619 6,636 9,031 5,518 9,293 46,774 The Existing Pollution Load Capacity Water quality modeling to calculate the pollution load capacity under existing conditions represents the water quality that best matches the current situation.
Repeated trials and errors were conducted to determine the diffuse source concentrations, to produce a combination of pollutant source concentrations that best aligned with the observed concentration distribution.
The pollution load capacities for each parameter are presented in Table 6.
Table 6.
Existing pollution load capacity.
Segment Total Pollution load .
g day-.
TSS
BOD5
COD
13,288
7,247
18,211
1,510
11,639
15,543
1,066
8,874
33,598
2,612
13,791
25,409
1,414
6,913
41,915
2,542
11,904
147,962 10,086 60,369
Pollution load capacity .
g day-.
TSS
BOD5
COD
Ae1,460 Ae130 Ae571 Ae2,161 Ae423 Ae2,020 Ae1,832 Ae300 Ae2,238 Ae14,533 Ae1,526 Ae4,760 Ae14,365 Ae681 Ae1,395 Ae22,875 Ae1,288 Ae2,611 Ae52,905 Ae4,347 Ae13,594 In the existing model, which represents the current conditions of the Batang Merao Watershed, nearly all segments exceeded the TLDM.
The TLDM, based on the national water quality standards outlined in Regulation No.
22 of 2022 Regarding the Implementation of Environmental Protection and Management is smaller in Table 5 than the pollution loads in Table 6.
Therefore, the pollution load capacity of the Batang Merao Watershed has surpassed the required water quality standards.
The negative sign (A.
in Table 6 indicates a deficiency in the pollution load capacity, meaning that the pollution loads are higher than the TLDM for the Batang Merao Watershed.
The calculations for the TSS parameter revealed that the highest pollution load came from Segment 6, amounting to 41.
915 kg day-1.
Segment 6 was located downstream, and pollution loads from all along the river accumulated in this segment.
The accumulation of pollution loads from residential, agricultural, and livestock activities carried by the water flow renders Segment 6 unable to achieve optimal self-purification, leading to high pollution loads in this This is in line with research by Badrzadeh et al.
, which suggests that residential and agricultural activities contribute to pollutant loads that degrade river quality.
This results in an increasing deficit in Segment 6's pollution load capacity.
The calculations for the pollution load of the BOD5 and COD parameters were highest in Segment 4, the shortest segment.
The length of the segment affects the dilution of pollutants carried by the water flow.
A shorter segment resulted in less dilution, leading to higher concentrations of BOD5 and COD.
Pollution Load Capacity for the Next 5 Years The water quality model to determine the capacity for the next five years is conducted by calculating domestic wastewater discharge based on the population growth rate and involves trial and error with diffuse source concentrations.
The results of these calculations are presented in Table 7, where the negative sign (-) indicates a deficiency in the pollution load capacity, meaning that the pollution loads exceed the TLDM for the Batang Merao Watershed.
In Table 7, which represents an estimation of pollution loads in 2028, we observe an increased deficit in pollution load capacity compared to the existing conditions.
In the water quality model for the next five years, which predicts river pollution loads in the absence of effective management and with an increasing population growth rate, it is anticipated that the pollution loads in 2028 http://dx.
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will rise.
Consequently, the pollution load capacity falls significantly short of achieving river water quality that meets the standards.
This aligns with the research by Xu et al.
, which highlights the cumulative effects of pollution over time in the absence of restoration and management, exacerbating water quality Table 7.
Pollution load capacity for the next 5 years.
Segment Total Pollution load .
g day-.
TSS
BOD5
COD
15,303
1,109
8,115
21,364
1,638
13,867
19,106
1,493
10,219
37,014
2,949
15,534
26,550
1,526
7,968
43,685
2,717
13,509
163,023 11,432 69,211
Pollution load capacity .
g day-.
TSS
BOD5
COD
Ae3,475 Ae296 Ae1,438 Ae992 Ae550 Ae4,247 Ae5,395 Ae728 Ae3,583 Ae17,950 Ae1,863 Ae6,503 Ae15,507 Ae793 Ae2,450 Ae24,646 Ae1,463 Ae4,216 Ae67,966 Ae5,693 Ae22,437 Segment 6 represents the highest pollution load for TSS, as all upstream wastewater accumulates in Segment 6 which is the downstream area.
On the other hand, for the BOD5 and COD parameters, the highest pollution load was found in Segment 4, which was the shortest segment at 4.
19 km in length.
Additionally, tranquil and straight flow patterns reduce air reaeration in river water.
This diminished reaeration process causes suboptimal self-purification in Segment 4, leading to high BOD5 and COD pollution loads.
It is important to note that COD concentration is a key parameter for assessing wastewater biodegradability and evaluating the mass and energy balances in the overall processes .
The increase in population without proper wastewater treatment leads to an increase in domestic wastewater, resulting in higher concentrations of BOD5 and COD.
This is consistent with the theory that domestic wastewater contains both solid and liquid household waste, often containing bacteria and organic materials, leading to elevated BOD5 levels .
It is predicted that by 2028, in line with the growing population, pollution loads will continue to increase, causing the Batang Merao Watershed to further exceed its pollution load capacity.
This aligns with research by .
, which suggests that a rising population leads to increased pollution that degrades water quality.
After obtaining the TLDM for the Batang Merao Watershed and calculating the pollution load capacity for both the existing and 5 years future conditions, it can be concluded that without proper river management, river water quality will decline, and pollution loads will increase.
Firmansyah et al.
explain that in Indonesia, in 2018, there were 25 heavily polluted rivers, and by 2019, this number had increased to 38.
The pollution load capacity of rivers needs to be determined to serve as a guideline for river management efforts.
Management policies for the Batang Merao Watershed in the Jambi Province are expected to restore the pollution that has occurred and ensuring the quality and intended use of the watershed.
Currently, freshwater sources are contaminated by various sources, including industrial, urban, biomedical, and other anthropogenic activities .
Pollution has severe adverse effects on the environment and communities .
The proximity of settlements to rivers, often located along riverbanks, should prompt the government to initiate a large-scale policy to educate people on regulations prohibiting the construction of houses along riverbanks.
This would enable the government to plant vegetation along rivers and create green belts that prevent landslides.
Vegetation along riverbanks can also act as a filter, preventing pollutants from entering the river and mitigating pollution loads.
For short-term policies, it is crucial to construct communal wastewater treatment plants to manage domestic wastewater from the settlements.
The design and management of these communal treatment plants should involve expert teams to ensure their optimal functioning.
Regular maintenance and monitoring are essential to ensure that all domestic wastewater is correctly accommodated, preventing further river discharge.
Community participation in managing communal treatment plants can also have economic benefits, such as utilizing the final sludge as a component in concrete brick production, which is in line with research by Amsayazhi and Mohan .
The issue of sludge disposal can be significantly reduced if sludge, whether raw, digested, dried, or incinerated, can be economically utilized on a large scale .
Proper domestic wastewater management is a key solution for controlling river pollution.
As suggested by Bilgili et al.
, as domestic wastewater directly dumped into the environment increases, recycling practices such as composting food scraps become Household waste management is a critical practice that should be integrated from waste This journal is A Patri et al.
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generation to disposal .
The considerable increase in the contamination load and diversity of urban, agricultural, and industrial contaminants has necessitated the need to understand the process of changes and predict the quality of water resources.
In this regard, simulations are considered as important tools .
Conclusion The pollution load for both the existing conditions and the next five years exceeded the TLDM for the Batang Merao Watershed based on Regulation No.
22 of 2021.
This resulted in a pollution load capacity deficiency for the TSS.
BOD5, and COD parameters.
Short-term and long-term policy strategies are required to manage the Batang Merao Watershed to ensure the river's water quality can be used as intended.
Short-term strategies can involve the construction of communal wastewater treatment plants, planting vegetation along riverbanks to create green belts, enhancing community participation, and implementing regulations that contribute to water quality restoration.
Long-term efforts should be made to relocate settlements from riverbanks to areas suitable for residential development.
Author Contributions SEP: Acquisition of data.
Analysis, interpretation of data and revision.
IPS: Conception and design of the study.
Drafting the manuscript, and Critical review.
SDT: Conception and design of the study.
Drafting the manuscript, and Critical review.
Conflicts of Interest There are no conflicts to declare.
References