Water Quality Analysis Using QUAL2Kw Model During The Rainy Season and Dry Season in Upper Citarum Watershed, West Java, Indonesia

The Increasing population in the upstream Citarum watershed area can trigger increased water pollution caused by anthropogenic pollution such as from domestic waste, agriculture, landfills, and settlements. The equilibrium of ecosystems is disrupted when there is an increase in excess pollutants such as suspended materials and nutrients that will cause eutrophication. The purpose of this study was to analyze river water quality from temperature, pH, DO, BOD, Total phosphate (PO4), and Nitrate (NO3) parameters from upstream Citarum watershed waters using a water quality model, namely Qual2Kw. This model is based on the Streeter-Phelps theory, which includes the natural purification process of river water. The Qual2Kw model can be used for decision-making to limit river water pollution. The locations reviewed in the upstream Citarum watershed area were five sampling points (SP), namely at Cisanti Outlets (1), Wangisagara (2), Koyod (3), after the Cisirung WWTP (4), and Nanjung (5). Site selection is based on sources of pollutants from anthropogenic activities that can pollute river water. The QUAL2kw model is used to simulate water quality and is used as a basis for calculating the carrying capacity of pollutant loads against the desired target water quality. The simulation results of a valid water quality model with the observation results are BOD, TSS, and NO3. and parameters such as temperature, pH, DO, and PO4 are invalid because they have errors below 25%. These three parameters (BOD, TSS, and NO)3 have exceeded the Indonesian government’s water quality standard values both in the dry and rainy season. These three parameters indicate that the high pollution in the upper reaches of the Citarum River is caused by pollutant sources from settlements, agriculture, and animal husbandry.


Introduction
Daily human activities have affected water quality, especially in surface water sources such as rivers.This is because these ecosystems receive and convert the flow of nutrients that enter water bodies.The complex interplay of incoming flows, weather, land-use conditions will affect external nutrient loads that can drive the cause of eutrophication.In addition, global warming is expected to affect the dynamics of nutrients in watersheds by changing atmospheric and meteorological properties such as rainfall patterns, evaporation of water in the atmosphere and rising air temperatures [1].
Water pollution comes from the entry of living things, substances, energy and or other components into the water from human activities that cause a decrease in water quality to a certain level so that water cannot function according to its designation class.The pollutant load is associated with the total amount of pollutants that enter the environment either directly or indirectly in a certain period of time and has two types of polluting sources from the form of distribution, namely point sources and nonpoint sources.Point sources are direct sources of pollution from the discharge of liquid waste into water bodies at a certain location or point.Sources of pollution can be from liquid waste disposal pipes from industry or WWTP processing results that do not meet quality standards.Non-point sources are sources of pollution spread from water bodies or to groundwater in a large area.It usually comes from suburban sources, large cities, rural areas, agriculture, and animal husbandry.This source of pollution can increase when it rains or on it watering because it is carried by runoff water then towards water bodies [2].
Water Pollution Control is a form of prevention and control of water pollution and restoration of water quality to ensure water quality in accordance with water quality standards.To control water pollution, the capacity of water pollution load is determined.The carrying capacity of water pollution load is the ability of water in a water source to receive input pollution load without causing the water to become polluted.The pollution load itself is the number of contaminants contained in water or wastewater.Water Pollution Control is a form of prevention and control of water pollution and restoration of water quality to ensure water quality in accordance with water quality standards.To control water pollution, the capacity of water pollution load is determined.The carrying capacity of water pollution load is the ability of water in a water source to receive input pollution load without causing the water to become polluted.The pollution load itself is the number of contaminants contained in water or wastewater.The determination of the load carrying capacity of pollutants can be analyzed using the Mass Balance method, Streeter-Phelps method and computerized numerical modeling and other methods based on the development of science and technology as long as it can be scientifically accounted [3].
Computational methods are computer-aided simulation methods and are more comprehensive in modeling river water quality by accommodating many sources of pollutants that enter the river system, river hydraulic characteristics and climatological conditions.The simulation method that can be used is the QUAL model type (QUAL2E, QUAL2K, QUAL2KW) [4].The QUAL series model is a water quality assessment simulation tool that can be widely applied although the data used has limitations in forming complex models in 2D or 3D [5].
Water quality models have the complexity of ecohydrological phenomena in rivers with water quality variables that are usually simulated only DO and BOD but can currently be combined transport and transformation processes, such as total suspended solids (TSS), nitrogen (organic nitrogen, nitrate, nitrite, ammonia) phosphorus, dissolved oxygen (DO), chlorophyll a, COD, pesticides and metals can be simulated to focus on terrestrial processes and management by simple hydraulic pollutant routes in river or with a detailed description of the river route and the process of transport of pollutants [6].The QUAL2Kw model can simulate water quality in rivers and canals to measure the impact of non-point source pollution [7].
The QUAL2Kw model has been simulated for the water quality of the Laoguanhe River, China and the Markov process is used to calibrate the model and calculate the water quality risk [8].In addition, in Indonesia the QUAL2Kw model has also been used to analyze the water quality and carrying capacity of the Code River Yogyakarta, and shows that the concentration of ammonia, phosphate, and TSS has exceeded the load carrying capacity of pollutants in the river [9].The Qual2kw model is also used for analysis of the pollutant load capacity of the downstream Citarum River which shows that BOD, COD, phosphate have exceeded the pollutant load, but nitrate is still below the quality standard [10].
From this background, the purpose of this study is to conduct a water quality analysis using the QUAL2kw model in the Citarum River Basin at five location points, namely in Cisanti, Cikawao, Koyod, Rthreatyar and Nanjung Outlets.The location was chosen because it is still within the boundaries upstream of the citarum and the hue of the surrounding environment is agriculture, settlements, livestock and cottage industries.This analysis can later be used as a reference in helping to manage pollution in the upstream part of the Citarum watershed.

Location
The location of this research was conducted in the upstream Citarum River Basin, Bandung Regency, West Java Province.There are 5 sampling locations, namely at Cisanti, Cikawao, Koyod, Rancamnyar and Nanjung Outlets, the locations are shown in Figure 1 as sampling point (SP).The distance of the closest location between the 2nd point (Cikawao) and the 3rd point (Koyod) is 12.72 km, while the farthest distance between the 3rd point (Koyod) and the 4th point (Rancamanyar) is 20.33 km.These locations were selected, based on the pollutant source from human activities that will impact river water quality, such as settlements, agricultural fields, livestock, and home industries.Also, these locations were selected based on the sampling safety and accessibility condition.To discover the water dilution and alteration, sampling was carried out in 2021 during two seasons, namely rainy season (April) and dry season (October).Sampling was performed with the Grab Sample tool.Samples were taken directly from the water body to describe the water characteristics at the sampling time.

Water Quality Model
The QUAL2Kw model, GA (genetic algorithm) is included to determine the optimal value of the kinetic rate parameter, so that it can be used for calibration [11].But from its novelty developed by Tufts University, the QUAL2Kw model is a version of the QUAL2E one-dimensional water quality model.QUAL2Kw can simulate steady flow with repeated diel limit conditions and with non-fixed and nonuniform flow in its kinematic flow wave.QUAL2Kw can simulate the process of transportation, migration and transformation of many parameters, besides in its use the river should be divided into several ranges as research units, hydrological conditions and water quality in one homogeneous unit [8].
The QUAL2Kw model is a development of the Qual2E model with the Virtual Basic for Application (VBA) programming language that can be run with Microsoft Excel programs [12].In modeling with QUAL2Kw can simulate rivers in one-dimensional form with flows in the form of nonuniform, fixed flow and present rivers based on the impact of two sources, namely point sources and non-point sources.Water quality parameters that can be simulated include temperature, conductivity, inorganic solids, DO, CBODslow, CBODfast, organic nitrogen, NH4, NO2, NO3, organic phosporus, inorganic phosporus (SRP), phytoplankton, detritus (POM), pathogens, Alkalinity, pH [13].
The QUAL2Kw model can be used to assess water quality and climate class approaches in Asia i.e., Koppen-Geiger (tropical, temperate, cold and arid) and for water quality evaluation using water quality indices.The results found that flows from dry, temperate and tropical climates showed a downward trend in DO with respect to the longitudinal profile of major river streams [14].The advantages of the QUAL2Kw model compared to the QUAL2E include the interface and software environment can be implemented with Microsoft windows, the model segment uses river segments that do not have the same space and double loading for incoming and outgoing loads can be inserted into any segment, anoxia QUAL2KW supports anoxic conditions by reducing the oxidation reaction to zero at low oxygen levels, interaction of water deposits, the flux of water deposits on dissolved oxogens and nutrients is simulated internally, automatic calibration, generic algorithms can be entered to determine the optimum value of the kinetic rate parameter to maximize the fit of the model with the measured data, and can present a river based on the impact of two sources, namely point sources and diffuse sources [12].

Model Simulation Results
The Qual2kw model is used for water quality simulation.This model has its basic programs are Visual Basic and Fortran in Microsoft Excel view.This simulation is carried out repeatedly to obtain the concentration and discharge of pollutant sources (models) that best match the observed water quality.The results of model simulations that are close to the concentration of water quality from observations and have passed the matching chi square test, can be used as a basis in calculating the carrying capacity of pollution loads on the desired target water quality.
Model simulations were carried out for two seasons, namely the rainy season and the dry season.The following is the result of the simulation.The parameters that are accepted for validity from the simulation results are NO3, TSS, BOD parameters, while parameters such as pH, Do and Phosphate cannot be accepted for validity, this is because the simulation value of these parameters has a high error value, because the model is accepted if the error is below 25%.The determination of the km point is seen at a distance of km.Point km 0 is the 5th sampling point and point km 65.553 is the 1st sampling point.The 5th point is Nanjung and the 1st point is at Cisanti Outlet.

Rainy Seasons
The results of the model in the rainy season show that there are several parameters seen passing the class 2 river quality standard and some are still below the quality standard.a. Water temperature Figure 2 is a temperature graph from the model simulation which shows that the water temperature during the rainy season is still in 25℃ -27℃ at sampling points 1-5 (km 0-65,553).Based on government regulations the normal temperature is 22℃ -28℃, therefore the water temperature in the Citarum upstream watershed can still support aquatic life.The red line is describe for temperature minimum and maximum, the dot black square is mean temperature from observation.

Figure 1 .
Figure 1.Sampling points (sp) in upper Citarum watershed Figure 1 depicts water sampling location in Citarum upstream watershed.Total distance from first to last location is 65.55 km.The distance of the closest location between the 2nd point (Cikawao) and the 3rd point (Koyod) is 12.72 km, while the farthest distance between the 3rd point (Koyod) and the 4th point (Rancamanyar) is 20.33 km.These locations were selected, based on the pollutant source from human activities that will impact river water quality, such as settlements, agricultural fields, livestock, and home industries.Also, these locations were selected based on the sampling safety and accessibility condition.To discover the water dilution and alteration, sampling was carried out in 2021 during two seasons, namely rainy season (April) and dry season (October).Sampling was performed with the Grab Sample tool.Samples were taken directly from the water body to describe the water characteristics at the sampling time.

Figure 2 .
Figure 2. Graph of water temperature parameter model results in the rainy season b. pH Figure 3 is a pH graph from the model simulation which shows that the pH of the water during the rainy season is still in a condition that meets quality standards at sampling points 1 -5 (km 0 -65,553).The water pH during rainy season is still in a condition water quality standard around 7 -8.

Figure 3 .
Figure 3. Graph of pH parameter model results in the rainy season

Figure 4 .
Figure 4. Graph of DO parameter model results in the rainy season d.BOD Figure 5 is a graph of BOD from the model simulation which shows that BOD during the rainy season exceeds the quality standards at sampling points 2 -5 and between sampling points 4 and 3 (km 0 -64).However, at the 1st sampling point, BOD is still in class 2 quality standard (km 64 -65,553).BOD value in water quality standard class 2 is 3 mg/l.

Figure 5 .
Figure 5. Graph of BOD parameter model results in the rainy season

Figure 6 .
Figure 6.Graph of TSS parameter model results in the rainy season f.NO3 Figure 7 is a graph of NO3 from the model simulation which shows that NO3 during the rainy season exceeds the quality standard at sampling points 3 -5 (km 33.45 -0).However, at sampling points 1 -2 NO3 values are still below the quality standard (km 33.45 -65.553).NO3 value in water quality standards is 10 mg/l.

Figure 7 .
Figure 7. Graph of NO3 parameter model results in the rainy season

Figure 8 .
Figure 8. Graph of PO4 parameter model results in the rainy season3.1.2.Dry SeasonsThe results of the model in the dry season show that there are several parameters seen passing the class 2 river quality standard and some are still below the quality standard.a. Temperature Figure9is a temperature graph from the model simulation which shows that the water temperature during the dry season is still in a condition that meets quality standards at sampling points 1-5 (km 0-65,553).

Figure 9 .
Figure 9. Graph of water temperature in the dry season

Figure 10 .
Figure 10.Graph of pH parameter model results in the dry season c.TSS Figure 11 is a TSS graph from the model simulation which shows that TSS water during the dry season is in conditions above the quality standard at sampling points 2-5 (km 0-60).However, the 1st sampling point is still below the quality standard (km 62 -65,553).

Figure 11 .
Figure 11.Graph of TSS parameter model results in dry season d.DO Figure 12 is a graph of DO from the model simulation which shows that the DO of water during the dry season is in conditions above the quality standard at sampling points 4 -5 and partly between sampling point 4 and sampling point 3 (km 0 -29).However, sampling points 1 -3 and some between sampling points 3 and 4 (km 29 -65,553) are still below the quality standard.

Figure 12 .
Figure 12.Graph of DO parameter model results in the dry season e. BOD Figure 13 is a BOD graph from the model simulation showing that the BOD of water during the dry season is above the quality standard at sampling points 2-5 (Km 0-62).However, sampling point 1 (km 62 -65,553) is still below the quality standard.

Figure 13 . 11 Figure 14 .
Figure 13.Graph of BOD parameter model results in the dry season f.NO3 Figure 14 is a graph of NO3 from the model simulation which shows that NO3 water during the dry season is in conditions above the quality standard at sampling points 1 -5 (km 0 -65,553).

Figure 15 .
Figure 15.Graph of PO4 parameter model results in the dry season