With the development of marine resource exploration and marine pollutant monitoring， monitoring and collection of hydrologic data have become an important research direction.Among them， underwater wireless sensor networks play an important role in hydrological data acquisition. This paper studies the data collection of sensor nodes in the two-dimensional monitoring model network of underwater wireless sensors. The proposed method optimizes the path of sensor nodes by using self-organizing mapping （SOM）.We combine the optimized path graphics and the K-means algorithm to find the path internal aggregation point.Then we find the data acquisition point within the sensor communication radius through the aggregation point and the sensor node. Finally， the optimal path of autonomaous underwater vehicle （AUV） to each data collection point is found through SOM. In the verification experiment， 52 sensor nodes are arranged within a range of 1 200 m×1 750 m under the water， and the path obtained by data collection points is optimized by 6.7% compared with the path planning of sensor nodes in the same acquisition sequence. Compared with the optimal solution of sensor node path， the path obtained by reorganizing the self-organizing path planning of data collection points is improved by 12.2%. The results of increasing the number of sensor nodes are similar， so the proposed method can improve the data acquisition efficiency of AUV.