Research on Flood Prediction and Risk Assessment Based on Multiple Models and Entropy Weight Method

The global water cycle under the combined influence of climate warming and economic development is the focus of international attention. Warming can cause melting glaciers and higher sea levels, and trigger extreme weather, increasing damage from flooding. Flood prediction and risk assessment have become the key to disaster prevention and mitigation work, requiring the influence of multiple factors. For this phenomenon, this paper establishes a mathematical analysis model to make reasonable planning and decisions to prevent economic losses and casualties caused by flood disasters. In this paper, we calculate the Spearman correlation coefficient using SPSS and train it using a classification algorithm. The CSV was divided into different categories, the weights of different indicators were obtained according to the entropy weight analysis, and the seven heaviest indicators were visualized with bar graphs. It was concluded that factors such as monsoon intensity, topographic drainage, and river management were unrelated to urbanization and agricultural practices. Then the flood prediction model based on entropy weight topography was preliminarily constructed and verified. By comparing the prediction results of the test set, the model's accuracy can be improved by drawing the error, and according to the requirements of the problem, five indicators are selected to build multiple linear regression and flood probability models. The flood prediction model is based on mathematical, physical principles and historical data, taking into account meteorological factors (such as rainfall, rainfall intensity, etc.), hydrology (such as river level, flow), terrain, soil, etc., to simulate and predict the future flood situation in a specific area. These models can help relevant departments and personnel to prepare for flood control in advance, formulate emergency measures, and optimize water resources management, to reduce the loss of life and property and social and economic impact caused by floods.