Sedimentation analysis using SWAT model (soil and water assessment tool) in Mamasa Sub-Watershed

Soil fertility and quality of agricultural land have decreased due to erosion and sedimentation in the sub-watershed upstream area. This decrease in soil fertility is due to the loss of NPK nutrients in the topsoil. Erosion and sedimentation in the upstream area of the Mamasa Sub-watershed are caused by land degradation and forest conversion due to land expansion and shifting cultivation for cocoa, corn, and coffee. This study aimed to determine the amount of sediment in the Mamasa Sub-watershed in the Mamasa Regency by using the SWAT model. This research was conducted in the Mamasa Sub-watershed from June to September 2022 through several stages in the form of literature study, primary and secondary data collection. Then proceed with laboratory analysis, making a base map for the data analysis process. SWAT requires input data in land cover, soil type maps, slope maps, and climate data. The SWAT simulation was carried out in the 2012 to 2021 timeframe. The sedimentation values obtained from the SWAT model were sediment values from 0.06 to 34.073.01 tons/ha (55.34%), sediment values from 34.073.01 to 95.323.59 tons/ha (23.27%), sediment value 95.323.59 to 225.951.47 (13.51%), sediment values 225.951.47 to 442.013.09 (6.23%), and sediment values from 442.013.09 to 1,415.454.83 (1.66%). Based on this research, it can be concluded that the highest average sediment is found in the downstream area, with an area of 38,875.66 ha.


Introduction
Land use change is a logical consequence of land use due to population growth.Water, soil, and air pollution occurs due to significant land use and cover changes as natural resources in watersheds (DAS), soil, and water are easily damaged or degraded [1].Land that has been heavily degraded and has become critical land covers an area of around 48.3 million ha or 25.1% of the total area of Indonesia [2].
Based on data from the Lariang Mamasa Watershed and Protected Forest Management Agency (BPDASHL) [3], there are 141 watershed and 67 Sub-watershed in the area of West Sulawesi Province; according to their qualifications, most of the watershed includes watershed that needs to be restored, most of which is land.Critical.Mamasa sub-watershed a cross-provincial watershed sub-province located in the Provinces of South Sulawesi and West Sulawesi and through several district areas.Hydropower Dam with an irrigation area of 85,309 ha in Ulu Saddang Village, Pinrang.This dam is used as a source of raw water and water irrigation for the local community and a hydroelectric power plant.Based on the description above, it is necessary to conduct this research to look at the information on sedimentation data and nutrient loss as target indicators in evaluating the level of land degradation and as additional information in the management of sub-watershed Mamasa.
Mamasa Sub-watershed is located in West Sulawesi and South Sulawesi Provinces, which have an area of 104,680.52 ha.Mamasa Sub-watershed is the Catchment Area of the Bakaru Reservoir which acts as a source of water for the Bakaru hydropower plant.Expanding land and shifting cultivation for cocoa, corn, and coffee have caused damaging land degradation and forest conversion, leading to an increased sedimentation rate in the Bakaru Reservoir.The construction and improvement of road access to the area also trigger this.
Sedimentation or deposition conditions in the Bakaru hydropower reservoir are currently very concerning and impact the operation of the reservoir, which is no longer optimal.Under certain conditions, the turbidity and hardness of the sediment carried along with the flow of water can also cause damage to turbine components and other hydropower plant components and, of course, impact the electricity generated by the Bakaru hydropower plant.As a result of the large amount of sedimentation that occurred in the Bakaru Hydropower Reservoir, it was determined that this was a significant problem that needed attention and had to receive attention from all parties involved in the management of the Bakaru Hydroelectric Power Plant.

Study domain
The research was carried out in Mamasa Sub-watershed, which is geographically located between 3°30'00"-2°51'00" S and 119°15'00"-119°45'00" E (figure 1).Spatial data processing and SWAT analysis were carried out at the Geospatial and Land Use Planning Laboratory, and soil sample analysis was carried out at the Chemistry and Soil Fertility Laboratory, Department of Soil Science, Faculty of Agriculture, Hasanuddin University, Makassar, which took place from July 2022 until Oktober 2022.
Soil sampling to determine the characteristics of soil properties and sediment sampling at the study site based on the results of laboratory tests.Purposive sampling is used to determine the number and location of soil samples.Soil sampling using intact soil samples using ring samples and disturbed soil.Sediment sampling at sediment deposit locations, namely the Bakaru Dam and the outlet point at Subwatershed.

Data analysis
Data analysis in this study was carried out using the SWAT Model, which is a physical-based modeling that has been widely used in various types and conditions of watershed SWAT modeling can predict the effect of land management on water runoff, sediment, and agricultural land in a complex relationship in a watershed including soil type, land use, and land condition management periodically.SWAT uses the MUSLE formula for erosion and sedimentation analysis [4].The MUSLE formula is an extension of the Universal Soil Loss Equation (USLE) developed by Wischmeier and Smith (1978); erosion is calculated using the following equation: The SWAT model uses the MUSLE formula for sedimentation calculations.Unlike the USLE method, which calculates erosion based on rain's kinetic energy, MUSLE predicts sediment yield using the flow factor.This eliminates the need for Sediment Delivery Ratio (SDR) since the flow factor represents the energy used to break down and transport the sediment [5].Sediment results in the SWAT model are calculated using the equation: Sed = 11.8 (Qsurf.Qpeak.Areahru) 0.56 .Kusle.Cusle.Pusle.LSusle.CFRG (2)

Data Calibration and Validation
Hydrological simulation in a watershed can only be accepted if validated and calibrated statistically.Debit data is used to calibrate the model.Validation and calibration were assessed by regression of determination (R2) and Nash-Sutcliffe Efficiency (NSE) models.The R2 value describes how far the relationship between the simulation results and the observed results is between 0-1.The Nash method is used to see the normal distribution, determining the distance between the measurement and the simulation.NSE indicates how close the measurement results are to the simulation data or close to the 1:1 line.The NSE range is between -∞ and 1.0; NSE = 1 is the optimal value.Values between 0.0 and 1.0 generally indicate an acceptable level of model capability in conducting simulations.Value < 0.0 indicates that the average measurement value is better than the simulation value; in other words, the model's ability to carry out the simulation is unacceptable.The model's ability to describe the characteristics of the watersheds is evaluated using daily data and is accepted when it shows NSE > 0.5 [6].

General conditions
Rainfall data in the Mamasa watershed, obtained from rainfall data from the PERSIANN-CCS highresolution satellite precipitation product (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks -Cloud Classification System from CHRS -the University of Arizona available from 2003.PERSIANN-CCS rainfall data can be downloaded via the CHRS website in text format (*.txt) from 2011 to 2021 based on station points.The following is the distribution of the annual rainfall area in the Mamasa Sub-watershed and its distribution in each watershed area (Table 1).Calculation of rainfall in the Mamasa Sub-watershed, using the Isohyet method.Mamasa Subwatershed region has a hilly and mountainous topography.Mamasa Sub-watershed is included in the medium and high categories based on the rainfall classification.The Mamasa Sub-watershed, around 89.01% of its area, is 1000-3000 meters above sea level.Data from the results of rainfall intensity processing are also obtained from satellites PERSIANN-CCS 2011-2021.Preparation of rainfall intensity data using the Isohyet method.The classification of rainfall intensity for the Mamasa Subwatershed is very low.The following is the rainfall intensity data in Mamasa Sub-watershed (Table 2).

Table 2. Rain Intensity in Mamasa Sub-watershed
The slope effect on the watershed can be seen in erosion and runoff.According to [1] the steeper the slope, the greater the amount of soil splashed by the collision of raindrops; the steeper and sloping slope will increase the surface runoff velocity and surface runoff carrying energy.Approximately 85.74 slopes in Mamasa Sub-watershed fall into the steep and very steep; this will affect the high erosion and surface runoff, which will encourage landslides and high sedimentation in the river (Figure 2(A)).In the context of the Mamasa Sub-watershed, soil data were obtained from the BBSDLP Landsystem.The distribution of the area of soil types (Table 4).Mamasa Sub-watershed area, Inceptisol soil type.Inceptisol soil is young soil starting to develop and is prone to weathering.Most Inceptisol soils develop on steep slopes, where soil erosion has transported some of the topsoils continuously (Figure 2 (B)) Land cover can be in the form of vegetation and construction covering the land's surface.Land cover is related to the appearance of the earth's surface, such as buildings, lakes, and vegetation [7].Changes in land use from non-built-up to built-up in watershed areas, such as from dry fields or forests to settlements, can reduce the ability of the land to absorb rainwater.The acquisition of land cover data comes from data from the Ministry of Environment and Forestry in 2020 (Figure 2(C))

Maximum Debit (Qmax), Minimum Debit (Qmin), and Average Debit (Qav)
Water debit flow is the rate at which water flows (in the form of water volume) through a cross-section of a river per unit of time.In the SI system, the amount of water debit is expressed in cubic meters per second (m 3 /second).According to [4], one of the critical indicators in assessing watershed conditions is the maximum and minimum debit water ratio.[6] Assessed that a macro evaluation of watersheds could be carried out using the maximum-minimum water debit ratio (Qmax/Qmin).The water debit ratio describes the condition of the river in the dry season and the peak water debit in the rainy season.The river will naturally show changes in the watershed hydrological ability to absorb rainwater, characterized by an extreme difference between the river water debit in the rainy season and the river water debit in the dry season.The value of infiltration and surface runoff influences this difference.The greater the infiltration, the greater the water reserves in the soil, whereas the more significant the surface runoff, the lower the ability of the soil to absorb rainwater.Rainwater that falls will immediately flow into the river, accelerating the peak water debit [5].Based on the SWAT simulation results, the following is the area distribution of the maximum debit (Qmax) (Table 5), minimum water debit (Qmin) (Table 6), average water debit (Qav) (Table 7) Mamasa Sub-watershed.The middle region of the Mamasa Sub-watershed, which has high sedimentation, is Balla District, Mehalaan District, Sesenapadang District, Sumarorong District, and Tanduk Kalua District.Balla Sub-District has an area of 891 ha, with a sedimentation value belonging to class 4. Mehalaan Sub-District has a class 3 sedimentation value of only 75 ha.The area of Sesenapadang District, which has a high sedimentation value, is 1,188 ha, with 754 ha belonging to class 3, 433 ha to class 4, and an area of 0.3 ha to class 5.As for the Sumarorong District, the area of 1,878 ha has sedimentation value included in class 3. Tanduk Kalua has an area of 2,354 ha for an area with a class 3 sedimentation value and an area of 995 ha for an area whose sedimentation value is classified in class 4. The downstream area of the Mamasa Sub-watershed, which has a relatively high sedimentation value and is classified in class 3, is Lembang District, with an area of 4,647 ha.[1] States that sediment is soil and parts of soil transported by water from a place that experiences erosion in a watershed and generally enters a body of water, where the water speed slows down.
Meanwhile, according to [9] sediment results from erosion processes, either surface erosion, trench erosion, or other types of erosion.Sediment generally settles at the bottom of hillsides, flooded areas, waterways, rivers, or reservoirs.Sediment distribution can be seen in (Figure 3).Sediment yield is the amount of sediment originating from erosion in the water catchment area, measured at a certain period and place.The following is the distribution of the area of sedimentation values in the Mamasa watershed sub-district in Table 8.

Conclusion
Based on the results of research that have been done, the area that has high sedimentation is quite large, especially in the upstream area, the sedimentation that occurs will cause turbidity in river water.Sedimentation in the middle section results from the accumulation of sediment loads in the upstream section plus sediment loads originating from the central region.Sedimentation in the downstream

Figure 1 .
Figure 1.Mamasa Sub-watershed is part of which is located in two provinces, West Sulawesi and South Sulawesi Steep slopes or cliffs will increase the driving force.The steep slopes are formed by river water, springs, seawater, and wind erosion.Most slope angles that cause landslides are 180 o if the edges of the slopes are steep and the plane of the landslides is flat [1].The following is the distribution of slope area in the Mamasa Subwatershed (Table.

3 )Figure 2 .
Figure 2. (A) The slope in Mamasa Sub-watershed is classified into five slope classes.(B) Based on the USDA classification, there are two types of soil in the Mamasa Sub-watershed.(C) Based on the land cover classification, it is dominated by forest areas and dry land agriculture.

3. 4 .
Calibration and validationBased on the tests performed, the Nash-Sutcliffe efficiency values were obtained (NS) and R2, respectively, 0.60 (satisfactory) and 0.7089, as seen in Figures4-Aand 4-B.R2 values range from 0.0 to 1.0.Higher value means the model performs better.A value of R2 ≥ 0.5 is considered acceptable ).The consistency of the SWAT model after calibration can be seen from the model river water debit SWAT with measured river water debit is shown by the Nash-Sutcliffe (NS) value of 0.63 (satisfactory) and R2 of 0.7089 A. Correlation graph B. Regression graph

Figure 4 .
Figure 4. (A) Comparison of the model's observed and simulated water debit after calibration.(B) Regression analysis comparison of observation water debit and water debit model simulation after calibration.

Table 3 .
The slope of Mamasa Sub-watershed

Table 4 .
Type of soil Mamasa Sub-watershed

Table 7 .
Average water debit Mamasa Sub-watershed Sesenapadang District, and Tawalian District have high sedimentation values.Mamasa District, with an area of 849 ha, has a sedimentation value that belongs to class 3, with an area of 2,591 ha in class 4 and an area of 788 ha in class 5.For Sesenapadang District, the area with high sedimentation is 3,697 ha, with 1,193 ha included in class 3, 1,559 ha included in class 4, and 945 in class 5. Tawalian District, with an area of 2,393 ha, of which 2,344 ha of sedimentation level belonged to class 3 and 48 ha to class 4. Furthermore, the area of Pana District has a sedimentation level in class 3, namely an area of 39 ha.