Analysis of erosion management based on GeoWEPP Spatial Modeling on bauxite mining activities PT XYZ in West Borneo

. Bauxite ore open-pit mining activities are conducted in spread areas and increase the potential for water pollution, implying a need for good management. GeoWEPP is a spatial model that predicts the erosion magnitude and the location of sedimentation. This helps in erosion management and control, including constructing a settling pond. Therefore, the purpose of this study was to examine GeoWEPP based on land use, topographic and soil maps, as well as rainfall, and temperature data, then modeled with the GeoWEPP application. GeoWEPP simulation calculations are carried out only at the operational stage of mining activities. The map of the mining activity area in land use is a simulation of the planned activity area obtained from the EIA Document. The results showed that 30 Block/Hills with a total area of 13 602.48 ha obtained sediment of 150 186 m 3


INTRODUCTION
Mining is an important source of state revenue but also contributes to environmental damage. Mining's positive contributions include state revenues such as taxes and PNBP, generating other sectors, and creating job opportunities. The negative impacts include open-pit mining activities that reduce land cover, impacting the hydrological system by increasing evapotranspiration and soil erosion, and decreasing water storage (Anwar et al., 2011). One activity that applies the open-pit method is Bauxite mining. Bauxite is a metal mineral mining material used as raw material for Aluminum, one of the favorite commodities. This is in line with the growing domestic Bauxite mineral downstream program. Bauxite mineral characteristics are generally

Data Collection
Data were collected from relevant agencies and PT XYZ. Rainfall, maximum, and minimum temperature data were obtained from BMKG online data for the Rahadi Oesman Meteorological Station, while 2020 land cover data were collected from the Ministry of Environment and Forestry. DEMNAS map was obtained from the Geospatial Information Agency (BIG), and soil type data was obtained from the Center for Research and Development of Agricultural Land Resources (BBSDLP). Additionally, LIDAR image data and 2019 EIA Documents were collected from PT XYZ. Analysis was conducted based on data from the agency, and no field survey was carried out due to limited time and the conditions of the Covid-19 pandemic.

GeoWEPP Database Development and Analysis Process
GeoWEPP spatial modeling was performed to obtain predictive data on the study site's magnitude of erosion and sedimentation locations. The data analysis process is presented in the flow chart in Figure 1 with the following explanation: 1. Making land-use maps Land use maps are made by updating land cover maps to obtain information on spatial land use conditions. Information was obtained from land cover data made by the Ministry of Environment and Forestry. The data were updated with LIDAR image maps, Landsat 8 OLI satellite imagery, and Google Earth application using ArcGIS 10.4 software. Monitoring large areas and slow changes is conducted using medium resolution such as Landsat Satellite Imagery (Prasetyo, 2017).

Topographic map making
The elevation and slope maps were obtained from the results of DEMNAS data processing from the Geospatial Information Agency and processed using ArcGIS 10.4 software. The processing results are catchment area boundaries, elevation, maps, and slopes.

Climate data analysis
Climate data is processed using the Climate Generator (CLIGEN) software available in GeoWEPP to ensure data continuity. The data used consists of Rainfall, maximum, and minimum temperature data were obtained from BMKG online data for the Rahadi Oesman Meteorological Station.

Soil Data Analysis
Soil type data obtained from BBSDLP were analyzed based on physical and chemical properties of the soil from laboratory analysis in EIA Document PT XYZ. Purposive sampling was used in the primary data in the field using the soil type approach to represent the overall condition of the landform in the same characteristics.

Mining Area Plan Simulation
The mining area plan was simulated to determine the location of the mine pit and road. The plan is based on the mining plan of PT XYZ and EIA Document.

Database Development
GeoWEPP model process used topographic, land use, and soil type data in ASCII format. An analysis was conducted by determining the outlet point using continuous climate data.

Spatial Modeling with GeoWEPP
In the analysis in GeoWEPP integrated with ArcGIS 10.4, the data were not calibrated due to limited time and the COVID-19 pandemic conditions. WEPP model has been used successfully in evaluating natural resource problems using real and interrill separation processes in computer simulation programs in extensive project experiments . Although the WEPP model has excellent results, it is not calibrated (Laflen et al., 2004) with high predictive accuracy (Igwe et al., 2017).

Calculating Mine Erosion Magnitude and Mapping Sedimentation Locations
The calculation of the erosion magnitude and the sedimentation location used the output of the GeoWEPP model. The outputs include the amount of runoff and sedimentation and its predictions. This involved using a decision-maker perspective, geospatial environmental assessment approach to efficient decisions. It represents the most complex approach using the most readily available data (Renschler, 2003).

Calculating The Size and Placement of The Settling Pond
The management plan is to be carried out in constructing drainage and settling ponds, which sizes are based on mine erosion and runoff. The settling pond placement is based on a map of the sedimentation location. The size calculation is based on the Decree of the Minister of Energy and Mineral Resources No. 1827K/30/MEM/2018 Attachment II Guidelines for mining technical management. According to the decree, mining water storage and settling facilities should be at least 1.25 times the volume of mine water at the highest rainfall for 84 hours and adjusted to its activities. The size of the settling pond is based on the amount of mine erosion and the amount of surface runoff water in m3 units divided by the depth of the settling pond by 3 meters. Settling pond's placement based on the sedimentation location map. An overview of the Settling pond is presented in Figure 2.

Erosion Management Cost Analysis
This study analyzed land acquisition, water quality testing, and settling pond operational and maintenance costs. Economic analysis is cost analysis. Calculated cost data consists of investment costs of making settling ponds and data on operating costs of settling pond maintenance. The cost data used is obtained from the project leader of the company PT XYZ has been applied in a location adjoining the research site and is still a onegroup company. 1. The investment cost of making a settling pond is the cost required to build a settling pond consisting of: a. Land acquisition fee, this fee is the cost to buy and sell or borrow on land that will be used to make settling ponds. At the research site, the cost of land acquisition with a buying and selling scheme amounted to Rp 10 000 000/ha and land acquisition costs with a loan scheme of Rp 5 000 000/ha. The cost of land acquisition with a buying and selling scheme is categorized as pessimistic costs, while borrowing schemes are categorized as optimistic costs. b. Construction costs of settling pond buildings, the making of settling ponds is done by dredging or hoarding an acreage. The settling pond to be built has three ponds. The excavation cost for Optimist Cost is Rp 45 000/m 3 assuming a maximum of 5 KM of transport location, and for pessimistic costs is Rp 50 850/m 3 assuming the transportation location along the >5 KM. 2. The operating costs of settling pond maintenance are the costs required to maintain the settling pond in order to continue functioning, which consists of dredging and transporting sediment costs as well as the cost of testing water samples. The amount of dredging costs amounted to Rp 50 850/m 3 , and the cost of water samples amounted to Rp 1 000 000/sample. Dredging and sampling of samples against settling ponds are carried out once a month during surgery. Dredging activities are not carried out in the last month of operation.

General Condition of Study Site
This study was conducted in Pawan Watershed (DAS) in Sandai Subdistrict and Sungai Laur Subdistrict, Ketapang Regency, West Kalimantan Province. Das Pawan has an elongated shape from north to south with five main rivers, including Pawan, Laur, Kriyau, Kerabai, and Kayung River. This study was conducted in the planned mine opening area of PT XYZ that includes Pawan and Laur Rivers. Bauxite deposits are formed through Laterization in granite, metamorphic and sedimentary rocks (PSDMBP, 2019a). Indonesia's Bauxite potential is 5 234 012 683 tons for resources and 3 609 229 886 tons for reserves (PSDMBP, 2019b). The Laterite in Ketapang has a relatively low Bauxite content of 46.5% and a high silica content of 12% (IAI, 2018). According to Kisman and Pardiarto (2014), Bauxite in Sandai consists of three morphological units, including high hills, low hills, and plains. Stratigraphy occurs from old to young rocks, where the metasedimentary unit consists of sandstone, siltstone and claystone oxidized or lateritized, turning yellow, red, dark red, to limonitic. Figure 3 shows the general condition of the study site.

Climate
This study analyzed the site's hydrology using climatic data from the class III meteorological station Rahadi Oesman Ketapang. The station is the closest meteorological station that provides complete data. The data were collected on rainfall and maximum and minimum temperature for the 2011-2020 period. The results of CLIGEN analysis of the climate data are presented the climatic conditions of the study area, where the highest rainfall was 408.5 mm/month recorded in December, with 21 rainy days. The highest sun radiation was 459 langley/day in May, the highest maximum temperature was 32.9°C in May, and the lowest maximum temperature was 31.1°C in November. The results of CLIGEN analysis of the climate data are presented in Figure 4 and Figure 5.

Topography
Topographic conditions influence hydrological analysis by causing runoff differences and contributing to erosion and high sediment yields (Igwe et al., 2017). The runoff is higher when the slope is longer and sloping (Arsyad, 2010). The study area was 41% flat and 20% slightly steep, as shown in Table 1. The area is 40% flat, though there is a need for Bauxite mining management. Bauxite ore mining activities are generally found in hilly areas and potentially cause large runoff and sediment.

Soil
Soil type also affects erosion and runoff because its physical and chemical properties impact its ability to withstand water runoff. Maps from BBSDLP in 2016 showed that the dominant soil order at the study site is Ultisol. The study sites' soil types and physicochemical properties are presented in Table 2. Data on the soil's physical and chemical characteristics were taken from the Environmental Impact Analysis Document (AMDAL) of PT XYZ through sampling on June 22, 2019. In GEOWEPP analysis, soils were grouped based on order. WEPP was used because it predicts almost all types of land (Laflen and Flanagan, 2013).

Land Use (Land Cover)
Land use affects the amount of erosion and runoff, contributing to high sediment (Igwe et al., 2017). Surface runoff is influenced by land use, slope, and soil type (Arsyad, 2010). The study location was 62.40% Dryland Farm Mixed shrubland, followed by plantations at 22.93%, as presented in Table 3. The mining area shown in the land cover map is the planned area of the company PT XYZ. The area had not been cleared during the study and was used for mining activities. Incorporating mining activities such as pits, roads, and product processing areas into the land cover map simulates erosion and sedimentation.

Amount of Erosion of Bauxite Mining Activities
Erosion is the movement of soil or parts of land from one place to another (Arsyad, 2010) by natural media, such as water and wind (Arsyad, 2010;Asdak, 2010). It occurs due to changes in land use and the topographical structure of the watershed (Yüksel et al., 2016). Bauxite mining activities change soil chemical properties and cause a loss of 168.8 tons/ha of natural forest biomass (Wasis et al., 2018).
The magnitude of erosion and sedimentation in GeoWEPP is simulated in the sub-watersheds or the planned mining area. GeoWEPP model simulates sustainable sediment discharges in sub-watersheds of various sizes, topography, and land use (Amaru and Hotta, 2018). Furthermore, it simulates runoff and sediment yields (Zinziao, 2009) with accurate predictions (Haque et al., 2016). The simulated mining block is divided into 30 hills of 13 602 ha, with the mining areas consisting of pit and roads. Moreover, GeoWEPP could assess mines' hydrological and erosional impacts (Wu et al., 2011), producing 150 186 m3/month sediment and 4 202 267 m 3 /month runoff. The simulation of erosion on the hill is shown in Figure 6. GeoWEPP has limitations, such as its inability to simulate relatively flat areas (Kusmawati, 2006), and produces values lower than the observed values (Demir and Oğuz, 2019). The sediment yields simulated by WEPP are lower than those measured in the field (Pieri et al., 2007). The proposed Hill 3 mine area covers 1 974.66 ha, making it the largest, followed by the magnitude of sedimentation. The largest runoff occurred at Hill 3 of 44 344 m 3 /month and 603 482 m 3 /month. The amount of runoff and sedimentation for each hill is presented in Table 4.

Prediction of Bauxite Mining Sedimentation Locations
Prediction of the direction and the magnitude of sedimentation is necessary to determine the location and size of the planned construction of a settling pond. In this situation, data processing using GeoWEPP produced 30 sub-watersheds or channels that help determine the outlet point. WEPP is useful for the time-consuming and inexpensive estimation of soil erosion (Demir et al., 2018) and allows for easier model setup for larger and more complex watershed simulations . The settling pond or outlet point location is presented in Figure 7.

Settling Pond Construction
A settling pond is very important in mining activities to collect water and deposit solid particles from the mining area. The water coming out of the mining site does not cause turbidity and silting of the river due to the solid particles carried along. Therefore, settling ponds are effective as a mine wastewater management method (Wahyudin et al., 2018) In Bauxite mining, treatment at the settling pond does not involve chemicals. The size of the settling pond area to be built is adjusted to the predicted total sediment and runoff. The location and area of the settling pond development plans are presented in Table 5 and Figure 7. The settling pond design plan for Bauxite mining is a square or rectangular adjusted to field conditions. It has a depth of 3 meters and a minimum of 3 ponds consisting of a Sediment zone, where water with mud enters the pond for settling, a Safety pond zone for periodic inspection of water environmental quality standards, Mud zone for settling mud solids.

Investment Cost for Settling Pond
The investment cost for settling pond construction consists of land acquisition and construction costs. Land acquisition cost is the fee of taking over land ownership from the community with a sale and purchase scheme (buy-up) or a borrow-to-use scheme (term). In comparison, the construction cost is the expense of making a settling pond obtained by excavation or stockpiling. The cost of land acquisition with a borrow-touse and a sale and purchase (buy-up) schemes are Rp 5 000 000/ha and Rp 10 000 000/ha, respectively, while excavation or stockpiling costs Rp 5 850/m 3 .
Settling ponds are built on the mining blocks or Hills outlets to accommodate runoff water and sediment from the mining area before being discharged into water bodies. There are 30 settlement ponds to be built, covering 145.08 hectares and a depth of 3 meters. The construction cost for the entire settling pond is Rp 196 585 791 231 for optimistic fees and Rp 222 773 049 768 for pessimistic charges. The cost difference is due to differences in land acquisition schemes, where optimistic costs use buying and selling while pessimistic costs use a borrow-to-use scheme. Meanwhile, the excavation cost for the Optimistic Cost is Rp 45 000/m 3 assuming the transportation location is a maximum of 5 KM and for the pessimistic cost is Rp 50 850/m 3 assuming the transportation location is >5 KM. The details are presented in Table 6.

Settling Pond Maintenance Operational Costs
The operational costs of settling pond maintenance include dredging and sediment transport and water sample testing costs. Maintenance activities are carried out every month to produce an average of 122 m 3 /ha/month sediment. Furthermore, the average operational cost of settling pond dredging in the mine opening area is Rp 37 942 685/month. The average cost of the water sample is Rp 1 000 000/ha, while the total planned cost of settling pond maintenance is Rp 3 139 414 818. The costs in detail are presented in Table 7. The time for mining activities for each mining block (hill) is different. One set of mining equipment consisting of one excavator and 30 dump trucks has a 6 ha/month capacity. The longest mining activity was 33 months, carried out on block hill 3.

Postoperative Management
The settling pond would not be dredged to ensure reclamation and revegetation in the last month of mining. Reclamation begins with land management and planting cover crops to reduce erosion and increase soil fertility. Also, overburden should be minimized and dams and drains built to reduce impacts on soil quality (Kamble and Bhosale, 2019b).
GeoWEPP simulation results showed that cover crop planting significantly reduced erosion or sediment. The analysis found that soil tillage and certain plant varieties could be modeled effectively (Demir and Oğuz, 2019). An open ex-mining area produces 80.76 ton/ha/year sediment, which could be reduced to 3.03 ton/ha/year and 0.02 ton/ha/year during the cover crop growth and maturity, respectively. Erosion, sediment, and runoff control techniques prioritize the vegetative method by maintaining ground cover vegetation (Suhartanto, 2005). Therefore, cover crops should be planted immediately after completing the mining activities.

CONCLUSION
The analysis showed a simulation of 30 hills covering 13 602.48 ha, producing sediment of 150 186 m 3 /month and the runoff of 4 202 267 m 3 /month. GeoWEPP analysis on the planned mining block area obtained 30 outlet points to be used for the settling pond construction. Moreover, the optimistic and pessimistic costs of constructing the entire settling pond are Rp 222 047 640 944 and Rp 222 773 049 768, respectively. The settling pond maintenance cost at all outlet points during operation is Rp 3 139 414 818. Planting cover crops in ex-mining areas effectively reduce erosion 0.02 ton/ha/year during the cover crop growth and maturity, respectively.