Numerous studies have demonstrated that the combination models can improve the runoff forecast performance compared to individual forecasts. However, some models do not take into account the effects of inappropriate sub-models on the combination models. Based on this, a medium-and long-term runoff integrated forecasting method based on optimal sub-models selection was proposed. First, the sub-models, including linear regression (MLR), BP neural network (BPNN), wavelet neural network (WNN), and support vector regression (SVR), are optimally selected based on the nearness degree. Second, ridge regression (RR) is used to combine the optimal sub-models to predict runoff. Finally, the Guandi hydropower station is taken as an example to verify the effect of the integrated forecasting model. The results show that SVR, BPNN, and WNN are the optimal sub-models, and RR-3 is the optimal integrated forecasting model composed of the optimal sub-models. In addition, compared with the other two combination models, the RR-3 performs better.

Activities, particularly harbor construction, often exert significant and non-negligible impacts on coastal environments. Therefore, it is of great practical importance to quantitatively assess the effects of such construction on the surrounding topography, such as tidal flats. This study focuses on the coast of Jiangsu Binhai Harbor. Using multi-source and multi-temporal remote sensing images, digital elevation models of tidal flats surrounding Binhai Harbor were generated for the years 2013, 2015, and 2017 through the waterline method. A quantitative analysis was conducted utilizing GIS spatial analysis techniques to examine erosion–deposition patterns, contour changes, and typical cross-sectional comparisons. The findings reveal that, although the overall coastline is in a state of erosion, the localized impacts of harbor construction are evident. Between 2013 and 2017, the northern tidal flats experienced overall erosion, whereas deposition occurred near the harbor’s root areas. Compared to 2013–2015, there was a significant decrease in erosion between 2015 and 2017, indicating that the construction of the project had a significant impact on the northern tidal flats. Throughout the five-year study period, the tidal flats within the breakwater underwent continuous adjustment, shifting from being close to the shoreline to being concentrated on both sides of the breakwater. Significant siltation was observed on the inner side of the breakwater at Binhai Harbor between 2015 and 2017, with an increase of 0.86 km² in the area above −2 m. This study demonstrates that remote sensing technology is highly effective in monitoring changes in coastal topography, especially under the influence of human activities.