Multi-parameter water quality testing model for marine environmental pollution emergency response

When building a multi-parameter water quality testing model for marine environmental pollution emergency response, the characteristics of marine environmental data are analyzed based on the method of a data-driven model artificial neural network, and the mapping relationship between state variables of the marine environment is established by taking state variables of the marine environment as input-output parameters of the model. The method of emergency multi-parameter inversion of the combined unit model is used to optimize the inversion of emergency parameters (chemistry and biology) of a data-driven model with regional variation, and to invert the near-optimal solution. Based on the inversion results, a non-conservative water quality testing model of marine environmental pollution is constructed from the two emergency parameters of chemistry and biology. This model mainly studies the decomposition rate of nitrogen and phosphorus and the effects of phytoplankton growth, respiration, withering and sedimentation on the nutrient value from the two aspects of chemical decomposition speed and biological process which affect the change of the nutrient value of marine environmental pollution. The water quality concentration of the marine environment is determined according to nutrient value, and the ocean ring is realized. The test results of the water quality test model are as follows: the predicted values of chlorophyll and inorganic nitrogen content in Liaodong Bay and Bohai Bay, China is in good agreement with the measured values, and the predicted values of inorganic nitrogen, chlorophyll current and water level in the nutrient salts of Liaodong Bay and Bohai Bay are in good agreement with the measured values. The test results are of high accuracy.