Suspended sediment concentration (SSC) is one of the most critical parameters in ocean ecological environment evaluation and it can be determined using ocean color remote sensing (RS). The purpose of this study is to develop a model that provides a reliable and sensitive evaluation of SSC retrieval using RS data. Data were acquired for and gathered from the Gulf of Bohai where SSC levels are relatively low with an average value below 30 mg·L⁻¹. The study indicates that the most sensitive band to SSC levels in the study area is the NIR band of Landsat5 TM images. A quadratic polynomial semi-analytical model appears to be the best retrieval model based on the relationship between the inherent optical properties (IOPs) and apparent optical properties (AOPs) of water as described by the quasi-analytical algorithm (QAA). The model has a higher precision and effectiveness for SSC retrieval than data-driven statistical models, especially when SSC level is relatively high. The average relative error and the root mean square error (RMSE) are 12.32% and 4.53 mg·L⁻¹, respectively, while the correlation coefficient between observed and estimated SSC by the model is 0.95. Using the proposed retrieval model and TM data, SSC levels of the entire study region in the Gulf of Bohai were estimated. These estimates can serve as the baseline for efficient monitoring of the ocean environment in the future.

With the improvement of short-term flood forecasting and short-term rainfall forecast accuracy, as well as the advance of hydrological and meteorological information collection and collation methods, the reservoir flood regulation method taking rainfall or inflow forecast into consideration is gaining more and more attention. As the index of Forecast-Based Operation (FBO), the forecasted factor plays an important part in determining success or failure of FBO due to its uncertainty and accuracy. In this study, possible risk sources were analyzed considering the process and the characteristics of reservoir flood regulation firstly, and the uncertainty of the forecast information and the FBO risks were discussed based on hypothesis testing. Then, combined with the case study of applying FBO on Ankang Reservoir, in which the forecasted net rainfall was selected as the index of the FBO rules, the probability distribution of the forecasted net rainfall errors was derived as the basis of risk analysis. Finally, FBO risk analysis was conducted based on Monte Carlo method for several real flood processes, while a simulation was also carried out with the Conventional Operation (CO) for contrast. The results indicate that the maximum risk was reduced more than half when FBO was adopted. Consequently, the possible remedial measures were put forward in the case of invalid forecast happened based on simulation and the analysis of the principle of flood regulation. The conclusions and methods in this research provide ideas for real-time flood regulation and risk management of reservoirs.