Recogniton of water-using behavior of rural residents is of great significance to alleviate the shortage of water resources and improve the safety and management of water consumption in rural areas, where the water is in short and water consumption keeps increasing. A mixing model combining the HMM and BP neural network is proposed, based on the excellent classification ability of BP network and the powerful modeling capabilities in time domain of HMM. This model established a HMM for the six events of water-using behavior and the output probability of each model were calculated. Then the BP neural network was trained through the probability and expected output, and the test data and the established combination model were selected to match and the recognition result was obtained. The results showed that the new mixing model was 8.78% more accuracy in water-using behavior recognition than the HMM model alone, and 8.92% more accuracy than the BP neural network alone, showing its application value.