roads，normalized difference vegetation index，topographic wetness index，and soil type are selected． A multimodel fusion debris flow prediction model is established by using the Stacking ensemble learning framework combined

with support vector machine，neural network and random forest． The accuracy of the model was verified by ＲOC curve． The success rates of the Stacking fusion model，random forest，neural network，and support vector machine model are 98. 1%，96. 1%，94. 5% and 93. 4%， and the prediction rates are 95. 5%，91. 6%，90. 6% and 89. 7%，respectively． The results show that the Stacking fusion model has the highest accuracy and is most suitable for the evaluation of debris flow susceptibility in Yajiang．

neural network   Yajiang County