Abstract: Traditional water and sediment forecasting methods rely on hydrological models and expert experience, which have limitations in dealing with complex meteorological conditions, multi-source data fusion, and real-time dynamic forecasting. Artificial intelligence technology, leveraging its advantages in data processing, pattern recognition, and predictive analysis, provides new technical means and solutions for water and sediment forecasting. This paper studies the application of artificial intelligence in water and sediment forecasting, mainly using the DWT-LSTM artificial intelligence model, and briefly describes its applications in intelligent water and sediment forecasting and reservoir sediment discharge forecasting. The research results show that the artificial intelligence model can improve the accuracy of water and sediment forecasting, and has significant advantages in water and sediment forecasting, providing important support for enhancing the scientificity, timeliness, and accuracy of flood control work.