DA-SSL-based flood disaster prediction and early warning method

Abstract

The invention discloses a flood disaster prediction and early warning method based on DA-SSL. The method comprises the following steps: acquiring an initial sample of urban pipe network diseases; inputting the initial sample of the urban pipe network disease into an improved PCSWMM model; the improved PCSWMM model outputs a pipe network functional disease sample set with a waterlogging result label; performing sample set expansion on the urban pipe network disease initial sample to obtain an expanded labeled sample set with a waterlogging result label; carrying out information difference measurement on a label sample set / a label-free sample set by utilizing cross entropy, randomly generating a label-free sample set without a waterlogging result label, inputting the label sample set and the label-free sample set into the improved PCSWMM model, and repeatedly training the improved PCSWMM model to obtain a waterlogging result; and obtaining urban inland inundation area results under different pipe network functional disease conditions. By adopting the method, the overflow capacity and flow velocity distribution of the drainage pipe network under the influence of functional diseases can be accurately fitted, and the waterlogging early warning result is very accurate and reliable.

Description

technical field [0001] The invention relates to the field of flood disaster early warning, in particular to a flood disaster forecast and early warning method based on DA-SSL. Background technique [0002] In the process of constructing the urban flood warning and disaster prevention decision-making system with the existing flood disaster prediction and early warning methods (such as the currently relatively mature rain and flood management model (PCSWMM)), the simulation of surface runoff and flow and the pipeline network under torrential rain with different return periods can be comprehensively considered. In the process of hydrodynamic transmission, it is assumed that the drainage pipe network is in a smooth state, and the influence of pipe diseases on the flow capacity and flow velocity distribution is ignored. However, the survey shows that there are 12 functional diseases per kilometer of drainage pipes in major cities across the country, of which scaling and silting d...

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Problems solved by technology

[0006] (1) The influence of pipeline functional diseases (scaling, siltation) on flow capacity and flow velocity distribution is ignored, resulting in serious shortage of accuracy of existing flood disaster prediction and early warning methods in predicting drainage network flow capacity;

[0007] (2) The impact of multiphase flow and multi-field coupling of functional diseases of the pipe network on the one-dimensional and two-dimensional production and confluence of the urban surface and underground is ignored, and it is difficult to ensure the accuracy of the early warning results of waterlogging;

[0008] (3) Using the control variable method to analyze and calculate the corresponding relationship between pipeline functional diseases and waterlogging areas one by one is a heavy workload and difficult to achieve

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