Perbandingan Erosi Model MUSLE dengan Erosi Pengukuran Rainfall Simulator

Abstrak. Potensi bahaya erosi pada lahan berlereng seperti perkebunan perlu kiranya dilakukan pengukuran dan perkiraan erosi. Metode salah satunya adalah model MUSLE (Modified Universal Soil Loss Equation) yang awalnya dikembangkan skala petak pertanian di Amerika Serikat, sehingga untuk mengetahui sejauhmana mampu memperkirakan maka akurasi tingkat dengan membandingkan dua plot percobaan tanaman kacang tanah bayam. Erosi penelitian ini yaitu menggunakan simulasi hujan buatan berupa alat rainfall simulator. Sampel simulator diambil dari Perkebunan Kurma kelerengan curam 25% jarak tanam 8 x m2 tanpa adanya penerapan penutup tanah. Pengukuran per kejadian pemberian terlebih dahulu mengukur limpasan literan kemudian menimbang tertampung bagian bawah (reservoir). Hasil menujukkan perbedaan berkisar antara9 10-6 ton/ha - 6,62 ton/ha, bayam 1,92 10-5 6,37 ton/ha. Tingkat memiliki persamaan y = 0,000086x-0,000028 nilai korelasi (r) 0,82 (sangat kuat), (R2) 0,67 (kuat) RMSE 1,6. Sedangkan 0,00095x-0,0001 0,86 0,74 1,44. Nilai 1 dikarenakan variasi dihasilkan oleh suatu jauh pengukurannya.Comparison of Erosion Models with Rainfall Simulator MeasurementAbstract. The potential for erosion hazards on sloping land such as plantation needs to be measured and estimated erosion. There are several methods estimating erosion, one which is the model. an estimation method developed a farm scale in United States, so find out what extent able estimate rate accuracy carried by comparing measurements two experimental plots peanut spinach plants. Measurement this study uses artificial rain simulations form samples were taken from Barbatee Dates Plantation steep slope spacing without application ground cover crops. incidence using first measuring runoff liters then weighing that stored at bottom results showed there differences measurement plants ranging 9 tons/ha 6.62 tons/ha, 1.92 tons. / ha 6.37 tonnes ha. plant has equation 0.000086x-0.000028 correlation value 0.82 (very strong), (R2 ) 0.67 (strong) 1.6. Whereas 0.00095x-0.0001 0.86 0.74 1.44. because variation generated far value.