Small watershed quaternary deposit thickness estimation method based on machine learning model

The invention provides a small watershed quaternary deposit thickness estimation method based on a machine learning model, and the method comprises the steps: selecting influence factors which affect the thickness of quaternary deposits, and obtaining the influence factor data of each investigation point; establishing a deposit thickness model based on a machine learning model according to the actual thickness of the quaternary deposit of each survey point and the influence factor data to obtain the estimated thickness of the quaternary deposit of each survey point, and selecting the model with the minimum error as an optimal model through model precision test adjustment parameters; and obtaining influence factor data of the research area, establishing a deposit thickness model by using the optimal model, and obtaining a thickness distribution diagram of the quaternary deposit in the research area. The technical scheme provided by the invention has the beneficial effects that basic data and other contents are