The invention discloses a city water supply network burst detection method based on dynamic neural network prediction. The method comprises the steps that 1, normal history flow data of the W durationof city water supply nodes is utilized to serve as the original time sequence; 2, the original time sequence is analyzed to obtain a pretreated time sequence; 3, wavelet analysis is carried out, wherein the wavelet analysis is utilized for carrying out denoising on the pretreated time sequence, and denoised flow data is obtained; 4, a model is set up, wherein the NAR dynamic neural network is utilized for training the denoised flow data, and the burst recognition model is set up; 5, a flow time window of the W duration slides backwards along with time, and the flow data is updated; 6, the flow time window of the W duration slides backwards continuously along with time, the step 5 is repeated, and until the accumulation probability of flow abnormality surpasses a set threshold value, it isjudged that the burst accident occur. According to the method, in combination with the wavelet analysis and the dynamic neural network prediction algorithm, burst accident detection of the city watersupply network based on dynamic neural network prediction is achieved.