Visualization Of Groundwater Flow Field Based On Information Entropy Screening And Feature Lines Extraction

As an underground component of water cycle,groundwater cycle is an important hydrological process to provide renewable fresh water and maintain the basic flow of surface water system in land environment.It is found that the groundwater circulation under the wavy groundwater level occurs in the form of hierarchical nested flow system.However,due to its transparent nature,it is difficult to observe the flow field movement and change process directly.It is necessary to identify and display the flow field change law contained in its data with the help of more effective and more intuitive flow field visualization technology.The visualization technology of three-dimensional groundwater flow field can clearly reveal the law of groundwater movement and provide intuitive and vivid groundwater dynamic information for groundwater research.In this paper,in order to deal with the problem that it is difficult to express the flow lines clearly caused by too many streamlines in the three-dimensional groundwater flow field,an algorithm based on information entropy screening is proposed to extract the characteristic lines of groundwater flow field.In the algorithm,information entropy is used to calculate the area with violent changes in groundwater flow field and detect the critical points.The eigenvalue of the area with critical points is calculated.According to the calculation results,the streamline is drawn by matching the template of seed points.In other areas,the flow line is drawn by random scatter method.The calculation of information entropy uses Leopardi isosphere segmentation method,and the critical point detection uses linear interpolation method.The streamline drawing of groundwater circulation system in three-dimensional t ó thian basin is carried out.The results show that the method in this paper can draw more and clearer flow field information on the premise of ensuring the accuracy of groundwater flow field change law and important characteristics,and solve the problem of occlusion and disorder caused by too many streamline in the extraction of groundwater flow field characteristic lines,which provides relevant analysis for groundwater field Methods and tools.Around these contents,the work of this paper is as follows:(1)Based on the research status of groundwater visualization at home and abroad,the information entropy visualization method and the feature-based visualization method are analyzed.(2)In order to solve the problem of low efficiency and heavy workload of featurebased flow visualization algebraic calculation,the concept of flow information entropy is introduced in the process of groundwater flow field feature detection.The information entropy calculation is used to obtain the areas with violent changes in groundwater flow field and detect the critical points,and the eigenvalue calculation is carried out for the areas with critical points,According to the calculation results,the streamline is drawn by matching the seed point template.In other areas,the streamline is drawn by random scatter method.The calculation of information entropy uses Leopardi's sphere segmentation method,and the critical point detection uses linear interpolation method.(3)On the basis of the above,the algorithm of feature line extraction of groundwater flow field based on information entropy screening is studied and implemented.The algorithm allows users to adjust the information entropy influence factor,seed frequency,seed proportion,etc.,which improves the adaptability and scope of the feature extraction algorithm.(4)Based on the research and the demand of groundwater visualization,aiming at the three-dimensional flow field of the Tóthian basin,this paper designs and develops the visualization software of groundwater flow field feature line extraction based on information entropy screening,tests and verifies the detection method of groundwater feature line in this paper,and achieves a better visualization effect of groundwater flow field.