Artificial neural network simulation to zero flow of the Heilongtan spring groups in Lijiang

Zero flow of the Heilongtan spring group that is famous scenery in Lijiang, Yunnan Province frequently occurs recently, which severely threatening the sustainable development of Lijiang tourism. In order to know the real reason for zero flow of the Heilongtan spring group and its occurrence regularity, hydrogeological conditions and correlation between precipitation and zero flow of the spring group are analyzed systematically, and a simulation based on artificial neural network model is made also. It is found that the Heilongtan spring group is an incomplete-drainage overflow karst spring at the piedmont formed by fractures. There is causality between the annual precipitation deficit and the zero flow of the Heilongtan spring group. Finally, a BP artificial neural network model with 6-13-3 network topology of the Heilongtan spring group’s zero flow is established. The model uses antecedent precipitation, air temperature and humidity as input vector parameters to simulate different conditions of the Heilongtan spring group’s zero flow. Training samples come from data from 1953 to 2002 , and testing samples come from 2003 to 2012 in the model. At last, it is found that the testing results are coincide with real situation to great extent.