Research On The Inversion Of Natural Environment Elements,risk Assessment And Allocation Of Rescue Base In The Arctic

With the accelerated warming of the world and the rapid melting of sea ice in the Arctic,the Arctic passages get more and more attention.Under the background of global warming,it is of great significance to occupy the commanding heights of exploiting the Arctic,which can not only help us decrease the dependence on the Strait of Malacca,but also help us smoothly implement the development strategy of the " 21 st century maritime Silk Road " and the " Polar Silk Road ".The sailing safety supporting is the basic work for China to implement the Arctic strategy successfully and the navigation risk assessment and emergency rescue are important aspects of sailing safety supporting.At the same time,the shortage and less accuracy of visibility,weak robustness of the risk assessing result of navigating across the Arctic and the unreasonable layout of rescue base in the Arctic are prominent problems in the above two aspects.This paper is written to solve the prominent problems in the sailing safety supporting and the main work and conclusions are as follows:(1)The method of generating the gridded visibility data based on artificial neural network and numerical correction was proposed and the superiority of the method has been tested.The results showed that the inferred visibility based on artificial neural network has more accuracy than that from the numerical weather prediction model.(2)The spatial and temporal features of visibility in the Arctic was analyzed based on the generated visibility data in the Arctic.The results showed that visibility in the Arctic in July and August is lower than in other months of the year and the visibility in March and May is higher than in other months.The visibility in the south of 80 °N is higher than in the north and the visibility in the Arctic is generally good.(3)The model of predicting visibility based on Dynamic Bayesian Network was proposed and 3 prediction experiments were carried out over the Arctic Ocean region.The results showed that the general relative error of predicted visibility is less than that bsed on numerical weather prediction model,however,the predicted results were effective only for 3 days and the accuracy of the predicted results decreases with time.(4)The method of assessing and forecasting the natural risk of navigating in the Arctic based on Dynamic Bayesian Network was proposed to improve the robustness of the assessed result.The methods were tested in the Northeast Passage and the results showed that Dynamic Bayesian Network can not only well deal with the dynamic data but can also reduce the effect of inaccurate data on the results.The predicted result of the mode has important significance for judging the navigability of the Arctic Passage in the short term.(5)Set-Double Covering Median Model was innovatively constructed to determine the best allocation of rescue base in the Arctic and the algorithm to solve the model was also given.The rescue bases can not only cover all the areas in the Arctic,but also minimize the cost of distance and economic factors.In addition,the constructed model ensured that two rescue bases were responsible for rescuing the areas with high navigation risk.