Sediments discharge analysis using tank model for disaster mitigation

Environmental degradation as a result of deforestation carried out in the Catchment resulted in a decrease in its ability to store water. This has the effect of increasing the amount of sediment discharge. The process of estimating sediment discharges is very difficult because the data input variables are many and varied, usually, the data are very limited, because the erosion process occurs until the sediment discharge mechanism is quite complex. The process of sediment discharges in Catchment s is influenced by rain and surface runoff and is represented in the storage type. In this study, an approach using the Tank Model was conducted. The purpose of this study is to develop a tank model for sediment discharge analysis in disaster mitigation. The steps are setting the field experiment for collecting rain and discharge sediment data as the model input and setting the model analysis by making the structure and formulation of the tank model. There are 3 proposed tank models namely Tank Model 1 (three tanks, series, and cascade), Tank Model 2 (two cascade tanks), and Tank Model 3 (three cascade tanks). Model parameters are determined using the Genetic Algorithm (AG) method optimization approach. The analysis shows that Tank Model 3, composed of 3 (three) cascade tanks, represents a Catchment better than the other 2 tank models. This can be seen from the value of the accuracy of the model, namely the value of volume error (VE), the value of relative error (RE), the value of the mean least square error (RMSE), and the value of the correlation coefficient (R). But still has a range of differences for the value of sediment discharges, the cause may be a factor in the pattern of rain spread in the hydrological process, synchronization of the measurement process and data length, and the possible assumptions of the model parameters.