Devianti, Dewi Sri Jayanti, Indra Mulia, A. Sitorus, Dewi Sartika
Surface runoff by rainfall on oil palm-cultivated land can cause erosion. Method conservation of making biopore infiltration hole on sloping oil palm plantations land has been shown to reduce this runoff. It has been experimentally proven in plots with or without biopores. However, the estimation model of the surface runoff event has not been studied comprehensively. The main novelty of this work is using surface runoff and rainfall observation directly database on oil palm land for the predicted runoff. Estimates model of surface runoff on oil palm plantations are essential to know so that farmers can determine which land conservation is more appropriate in the order they can do forecasting and preparedness for extreme events in their land. In the current study, this paper report to compare two methods of estimating surface runoff model on oil palm land that are given biopores and without biopores using (i) conservation service soil - curve number (SCS-CN) and (ii) artificial neural network (ANN) back-propagation. Thirty data of rainfall and runoff events in the three months were used as input data. The results show that the ANN method can provide a more accurate prediction of surface runoff than the SCS-CN method. © Published under licence by IOP Publishing Ltd.
Department of Agricultural Engineering, Syiah Kuala University, Indonesia; Department of Mechanical Engineering, Nusa Putra University, Sukabumi, Indonesia; Research Center for Appropriate Technology, Indonesian Institut of Sciences, Indonesia
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