Open Access proceedings Journal of Physics: Conference series Civil and Environmental Science Journal Vol. 02, No. 01, pp. 001-014, 2019 1 Analysis of The Correlation Between Land Use Changes in Sub Watershed Wuno Toward Lifetime of Wuno Reservoir, Sigi District, Central Sulawesi Province Wardani Yuliana1, Suhartanto Ery1, Haribowo Riyanto1 1 Water Resources Engineering Department, Universitas Brawijaya, Malang, 65145, Indonesia uly86.yw@gmail.com Received 03-01-2019; revised 11-01-2019; accepted 22-01-2019 Abstract. Wuno Reservoir is located in Sigi Biromaru District, Sigi Regency, Central Sulawesi Province. It is planned for 50 years. This analysis to known the condition of ideal land use so that the life time of the reservoir reaches 50 years. Trend of land use change, erosion and sediment rate estimation using the ArcSWAT model. During 2008-2016, natural forest land use showed a downward trend, while mixed gardens, shrubs, fields and settlements showed an increasing trend. The erosion rate in 2008-2010 increased by 72.5%, in 2010-2012 it increased by 1.45%, in 2012-2014 decreased by 0.09% and in 2014-2016 increased by 0.98%. In 2008- 2016 Low BEHI area was reduced by 3.74%, medium BEHI was increasing by 14.11%, BEHI High increased by 16.57% and BEHI Very High increased by 12.64%. This shows that the rate of erosion and the extent of BEHI are influenced by changes in land use. Based on the results of analyzing the lifetime of the reservoir, changes in land use also affect the reduced useful life of the reservoir. Vegetative land conservation efforts are adjusting forest areas so that rate of erosion decreases by 62.75%. Mechanical land conservation efforts in the form of the construction of 6 check dams so that weight of sediment decreases by 89.24%. Keywords: ArcSWAT, Land Use, Erosion Rate, Bank Erosion Hazard Index, Reservoir Lifetime. 1. Introduction Erosion is a moving or transporting land or parts of land from one place to another by natural media [4]. The occurrence of erosion is determined by climatic factors (rainfall intensity), topography, soil characteristics, vegetation cover, and land use [9]. Land use changes have resulted in an increase in the value of land erosion, surface runoff, critical watershed condition and an increase in the amount of sediment which has resulted in a reduced lifetime of the reservoir [1, 2, 10, 12, 13, 14]. Wuno Reservoir is located in Oloboju Village, Sigi Biromaru District, Sigi Regency, Central Sulawesi Province. Wuno Reservoir utilizes the Wuno and Konju Rivers. Located in the Wuno Sub- watershed, Palu River Basin and included in the Palu Lariang River Basin. Its use is to meet the needs of irrigation water for 1,500 Ha of rice fields and 500 Ha of shallot farming, and to supply raw water needs [6, 7] with 50 years of lifetime. Increased erosion occurred in the Wuno Sub-watershed in 1992 to 2006 [5]. During the period of 1 (one) year the sediment potential in the Wuno River increased by Civil and Environmental Science Journal Vol. 02, No. 01, pp. 001-014, 2019 2 6,270 m3 [6, 7]. The Wuno river is suitable for raw water because there are not many residential arears. Residential areas sometimes have toxicity levels that are high enough to affect the aquatic habitat and these toxicity levels should be managed [8]. Increased erosion and sediment will have an impact on the reduced useful life of the reservoir [3]. Based on the results of analyzing, the rate of erosion and the extent of BEHI are influenced by changes in land use. Land use changes also affect the reduced useful life of the reservoir. Vegetative land conservation efforts are adjusting forest areas so that rate of erosion decreases by 62.75%. Mechanical land conservation efforts in the form of the construction of 6 check dams so that weight of sediment decreases by 89.24%. 2. Material and Methods 2.1. Material The data used in this study include Daily 2002-2015 rainfall data, Palolo rain station and Sibalaya rain station, digital Elevation Model (DEM) map, land use map in 2008, 2010, 2012, 2014 and 2016, map of soil types, map of Central Sulawesi Province Forest Areas and soil samples for each land use and soil type 2.2. Methods 2.2.1. Hydrological Analysis Consistency Test The data consistency test is conducted to find out whether there are data irregularities in the available rain data, so that it can be known whether the data is suitable for use in further hydrological analysis or not. In this study 2 (two) methods were carried out, namely (1) double mass curve; (2) Rescaled Adjusted Partial Sums (RAPS). Rainfall station location affects the consistency of data, this is indicated by the designed rainfall difference for each definite recurrence time is relatively small [11]. Homogeneity Test A series of hydrological data presented chronologically as a function of the same time is called a periodic series. Generally published field data are debit data, rainfall data, etc., are basic data as hydrological analysis material. The data is arranged in the form of a periodic series, so that before being used for further analysis must be tested. Testing the data it means is: (1) Test of Absence of Trend; (2) Stationary Test; (3) Persistence Test. The three stages of testing are often referred to as data filtering (data screening). Abnormalities Test (Outliers) Outliers is data that deviates too far from other data in a data set. The existence of these data outliers will make the analysis of a series of data biased, or not reflect the actual. Outliers test done to find out whether the maximum data and minimum data from the available data sets are suitable for use or not. 2.2.2. Soil Water Assessment Tool Analysis (SWAT) Measurement and estimation of erosion is difficult to do precisely because the process of events and the factors that influence them is very complex. But with some assumptions and simplifications, erosion measurement and estimation can be done with an acceptable level of approach. There are various ways of observing or measuring erosion that occur, among others, by direct observation in the field, interpretation of topographic maps and aerial photographs and direct measurements with experiments. In this study the erosion rate is calculated by the SWAT model. The SWAT model calculates erosion based on the USLE Modification formula [4]: Civil and Environmental Science Journal Vol. 02, No. 01, pp. 001-014, 2019 3 sed = 11.8 (Qsurf x q peak x a hru )0.56 K x C x P x LS x CFRG (1) with: sed = sediment yield (ton) Qsurf = surface runoff volume (mm/ha) q. peak = peak discharge (m3/sec) a hru = Watershed area (ha) K = soil erodibility C = plant factors P = land management factors LS = slope factor CFRG = soil material roughness factor 2.2.3. Bank Erosion Hazard Index Analysis The score of the erosion hazard value is stated in the Bank Erosion Hazard Index (BEHI), which is defined as follows [4]: 𝐡𝐸𝐻𝐼 = π‘ƒπ‘œπ‘‘π‘’π‘›π‘ π‘–π‘Žπ‘™ πΈπ‘Ÿπ‘œπ‘ π‘–π‘œπ‘› (π‘‘π‘œπ‘›.β„Žπ‘Žβˆ’1.π‘¦π‘’π‘Žπ‘Ÿβˆ’1) 𝑇 (π‘‘π‘œπ‘›.β„Žπ‘Žβˆ’1.π‘¦π‘’π‘Žπ‘Ÿβˆ’1) (2) With T is the magnitude of erosion that can still be left behind. The bank erosion hazard index can be determined as set out in the T Value Assessment Guide for Land in Indonesia (Table 1). Table 1. Bank Erosion Hazard Index Classification Bank Erosion Hazard Index Value Classification < 1.0 1.01 – 4.0 4.01 – 10.0 > 10.01 Low Medium High Very High 2.2.4. Reservoir Lifetime Analysis The lifetime of the reservoir is the time when the reservoir can be used to hold water and distribute it. Reservoir utilization age in terms of full dead storage by sediments. Deposition time from various elevations is cumulative to get the age of the reservoir. The lifetime of the reservoir can be calculated by the equation: 𝑇 = 𝑉 (𝐿×𝑆×𝐸) (3) with: T = Lifetime of reservoir (year) V = Dead Storage Volume (m3) L = Watershed area (km2) S = Erosion intensity = Vs/L Vs = The average volume of sediment entering the reservoir (ton/year) = Ws/Ξ³d Ws = The weight of the average sediment that enters the reservoir (ton/year) Ξ³d = The dry weight of the sediment deposits = 0.963 ton/m3 E = Efficiency of reservoir catches Civil and Environmental Science Journal Vol. 02, No. 01, pp. 001-014, 2019 4 2.2.5. Land Conservation Direction Vegetative methods or ways to utilize the role of plants in the effort to control erosion and/or preservation of soil, in the implementation can include the following activities: (a) Forest Restoration (reforestation) and reforestation, (b) planting cover crops, (c) planting crops in contour lines, (d) planting plants in strips, (e) rotating crops and (f) mulching and utilization of plant litter. In this research, vegetative handling efforts were carried out were forest restoration or forest area adjustment. Forest area adjustment refers to map of Central Sulawesi Forest Area. Check Dam Building (Controlling Dam) is a building built in river grooves with construction of soil filling material reinforced with a waterproof coating. Check dam buildings have functions other than as sediment capture buildings, as well as building river bed control. 3. Result and Discussion 3.1. Hydrological Analysis Consistency Test The method of testing with the Dual Mass Curve method is to compare the long-term annual rainfall data from a raindrop station with the average rainfall data of a group of rain stations in the same period. If the test results state the data at a station is consistent, it means that there is no environmental change in the station's area of influence and no change in how to measure it during the recording of the data. Figure 1. Double Mass Curve Chart of Palolo Station Rain Data Figure 2. Dual Mass Curve Chart of Sibalaya Station Rain Data Table 2. Consistency Test Results of Double Mass Curve Method No Rain Station Consistency Test Result Gradient (R2) Linier Regression (y) Angel Gradient (Tg Ξ±) 1 2 3 4 5 6 1 Palolo 0.9896 y = 0.9621x - 343.4 43.89Β° Consistent 2 Sibalaya 0.9896 y = 1.0286x + 442.9 45.81Β° Consistent From Figure 2, Figure 3 and Table 2 it can be concluded that the rainfall data at Palolo and Sibalaya Stations is consistent data. Civil and Environmental Science Journal Vol. 02, No. 01, pp. 001-014, 2019 5 If the rain station that affects the study area is less than 3 (three), then the test of the consistency of rainfall data is done by the method RAPS (Rescaled Adjusted Partial Sums). The recapitulation of the results of the consistency test of the RAPS method is presented in Table 3. Table 3. Consistency Test Results RAPS Method No Rain Station Consistency Test RAPS Method Q/n0.5 count < Q/n0.5 table dan R/n0.5 count < R/n0.5 table Result Q/n0.5 count Q/n0.5 table R/n0.5 count R/n0.5 table 1 2 3 4 5 6 7 1 Palolo 0.72 1.07 0.96 1.26 Consistent 2 Sibalaya 0.55 1.07 0.88 1.26 Consistent From Table 3 above shows that value Q/n0,5 count < value Q/n0,5 table and value R/n0,5 count < value R/n0,5 table, so that it can be concluded that the rainfall data at Palolo and Sibalaya Stations is consistent data. Homogeneity Test In this study, the annual rainfall data of the rain station were tested for the absence of trends with the Spearman method using 2-sided T-Test. Recapitulation of test results is presented in the following. Table 4. Trend Absence Test Results No. Rain Station Trend Absence Test (t count < t table) Result t count value t table value 1 2 3 4 5 1 Palolo -1.367 2.179 Trend Absence 2 Sibalaya 0.391 2.179 Trend Absence From Table 4 above shows that the value of t arithmetic < value of t table, so it can be concluded that the rainfall data on Palolo and Sibalaya Stations includes independent data (Rt and Tt are not interdependent). Periodic series is called stationary if the values of the statistical parameters (mean and variant) are relatively unchanged (stable) from the period or the time series. If one of the statistical parameters is found to change from the part of the period or the amount of time available, the periodic series is called not stationary. Non-stationary periodic series indicates that the data is not homogeneous or not the same type. Testing the variance value from the periodic series can be done with the F-Test. Recapitulation of test results is presented in the following. Table 5. Stationary Test Results No Rain Station Stationary Test F count < F table dan t count < t table Result Variability Stability Stability of average value F count F table t count t table 1 2 3 4 5 6 7 1 Palolo 2.24 3.79 -0.41 2.18 homogeneous 2 Sibalaya 0.61 3.79 0.37 2.18 homogeneous Civil and Environmental Science Journal Vol. 02, No. 01, pp. 001-014, 2019 6 From Table 5 above shows that the calculated F value < F table value and t count value