## 5 Conclusions  
In this study, validation and evaluation of the measured data were performed for the sediment yield estimation models developed using the classification and prediction techniques of data mining. The latter was capable of generating accurate classification and prediction results for rivers in South Korea, as follows: (1) models developed using the general watershed characteristic factors that affect the sediment and 34 SD values calculated based on the FD-SRC method (M1 using MEP for total sediment load, and M2 using SEMEP for total sediment load) and (2) models (M3-M8) developed using hydraulic explanatory variables related to flow and 540 total sediment load results estimated through MEP. As a result of the analysis, that most of the sediments were confirmed to be transported in the form of suspended sediments (\(\text{Q}_{\text{s}}/\text{Q}_{\text{t}}>99\%\)) in the mainstream of Nakdong River. For model validation, flow characteristics were measured using ADCP, and the SSCs of 82 point were measured using laser diffraction equipment at the main stream of the Nakdong River at the site at which the tributaries of Geumho, Hwang, and Nam Rivers inflowed in the main stream. Based on the analyzed results, the total suspended sediment load estimated using the EDI method was assumed to be the total sediment load, and the model was validated accordingly. Models M1 and M2 provided relatively reliable prediction results, considering the calibration SD values of other points located in the main stream of the Nakdong River. Although the models were developed using a small number of results (34), a sufficient number of total sediment loads (1962 and 1808) was considered at various flow conditions to calculate the SD values. Additionally, the consistent predicted results were obtained from the consistent index values, which corresponded to the explanatory variables; accordingly, the two models yielded reasonable and consistent prediction results. However, the accurate prediction of the change in sedimentation caused by the inflow of relatively small tributaries in the continuous main stream with a large watershed area was not possible due to the purpose of model development. In addition, unlike the results of previous studies, model M2 was developed based on the total sediment load calculated according to the SEMEP and yielded superior prediction results, and model M1 based on the total sediment load calculated according to the MEP, which yielded better prediction results owing to spatial and temporal lumping problems. In the cases of models M3-M8, which were developed to predict the total sediment transport of rivers in South Korea, a good prediction performance was demonstrated for changes in the sediment yield owing to the inflow of tributaries compared with the models, which used watershed characteristics as explanatory variables. However, there was a significant difference in the prediction results depending on the model structure. Specifically, validation was performed with the results measured in the main stream of the Nakdong River with similar characteristics, but the determined submodels of M4 were based on explanatory variables with relatively large coefficients of variation and thus exhibited a low prediction performance (RMSE = 145,134 tons/km\({}^{2}\)year). For comparison between models with other explanatory variables and response variables, SD values were calculated by applying the FD-SRC method based on the prediction results of the models developed by [PERSON] and the 10-year daily discharge data in the vicinity of the gauging points. In the result, models (M6 and M8) with simplified submodel classifications based on low-coefficient variations yielded highly accurate prediction results, which reflected the differences due to the inflow of tributaries. The reason based on which the models showed excellent prediction results is that M3-M8 used a large number of sediment load measurements in Nakdong River as calibration data.