The application discloses a kind of
groundwater vulnerability modeling methods based on
machine learning, it is related to
groundwater analysis field, including the following steps: obtaining
groundwater multi-
source data and carrying out hierarchical management;The classification management result is carried out, and the multi-source classification data and corresponding multi-source classification characteristic data are obtained;
Groundwater multi-
source data is stored in distribution, and interactive
feature dataset is generated according to storage result;The initial DRASTIC model is analyzed by traversing the obtained interactive
feature dataset, and the
model parameter reference image is generated by the obtained traversal analysis result;Model related parameters are associated according to
model parameter reference image Analysis obtains adjustment parameter;Real-time groundwater multi-
source data is obtained, and the initial DRASTIC model is flexibly coupled and analyzed according to the location information in
model parameter reference image of real-time groundwater multi-source data belonging to the model parameter reference image;The adaptability and accuracy of the model are improved to some extent.