Research on Ecological Risk Assessment Model Based on Genetic Algorithm

Abstract

In this study, Daxia river, a typical watershed in northwest China, was selected as the research area. The heavy metal content of the soil in the basin is affected by topography, meteorological factors and vegetation. The use of traditional methods to sample heavy metals in the basin soil consumes manpower and material resources, and is affected by geographical environment and weather conditions, resulting in inefficiency. In order to more accurately screen the factors related to soil water content, the characteristics of the global optimization of genetic algorithm are used, and the key factors are screened by controlling the iteration times to accelerate convergence. Furthermore, using the method of multiple regression, using the data from 2015 to 2017, a prediction model for soil heavy metal content was established. The conformity of this model is more than 80%, which can effectively characterize the soil heavy metal content in the study area. The establishment of this model provides a good theoretical and practical basis for the heavy metal content of soil in small and medium-sized watersheds in the future.