Sediment plays an important role in the water quality of a lake by acting as both a nutrient source and sink. The amount of phosphorus and nitrogen in the water depends on the internal load from the sediment as well as the external load. To estimate the effects of sediment load on the water quality of a reservoir, we applied a three-dimensional hydrodynamic and transport model based on the benthic chamber experimental results at Euiam Lake, South Korea. As shown in the sensitivity analysis results, the eutrophication period could be significantly extended by a change of phosphorus flux rates from the sediments. The increased phosphorus flux from the sediments intensifies the algal growth of Euiam Lake, which could cause serious algal bloom during spring and fall. This study provides information on nutrient concentrations in the sediment of Euiam Lake, verifies the role of the sediment as a source or sink of nutrients, and evaluates the effect of sediment release of nutrients and contaminants on water quality. This research is a useful tool in determining the effects of internal load in lakes and establishing the operation guideline for sediment management in order to maintain feasible water quality for beneficial use.

Conventional analysis techniques and sample preprocessing methods for identifying trace metals in soil and sediment samples are costly and time-consuming. This study investigated the determination and quantification of heavy metals in sediments by using a Laser-Induced Breakdown Spectroscopy (LIBS) system and multivariate chemometric analysis. Principle Component Analysis (PCA) was conducted on the LIBS spectra at the emission lines of 11 selected elements (Al, Ca, Cd, Cr, Fe, K, Mg, Na, Ni, Pb, and Si). The results showed apparent clustering of four types of sediment samples, suggesting the possibility of application of the LIBS technique for distinguishing different types of sediments. Mainly, the Cd, Cr, and Pb concentrations in the sediments were analyzed. A data-smoothing method—namely, the Savitzky–Golay (SG) derivative—was used to enhance the performance of the Partial Least Squares Regression (PLSR) model. The performance of the PLSR model was evaluated in terms of the coefficient of determination (R²), Root Mean Square Error of Calibration (RMSEC), and Root Mean Square Error of Cross Validation (RMSECV). The results obtained using the PLSR with the SG derivative were improved in terms of the R² and RMSECV, except for Cr. In particular, the results for Cd obtained with the SG derivative showed a decrease of 25% in the RMSECV value. This demonstrated that the PLSR model with the SG derivative is suitable for the quantitative analysis of metal components in sediment samples and can play a significant role in controlling and managing the water quality of rivers.