A farmland immersion evaluation method based on grey clustering

Abstract

As we all know, the degree of farmland immersion is affected by many factors such as soil moisture content, natural pore ratio, saturation, soil lithology and so on. However, the conventional submergence assessment method only uses the relative relationship between the depth of phreatic water and the rising height of capillary water to judge the degree of submergence, which is obviously unreasonable. Therefore, in this paper, a method of farmland immersion evaluation based on trigonometric whiteness weight function grey clustering is proposed. The physical properties of soil, surface soil lithology of vadose zone and groundwater level elevation are included in the evaluation index system, and the degree of submergence is classified, and then the weight function is constructed to determine the degree of submergence hazard of each observation point in the immersion area. Case study shows that the method is reasonable and feasible for farmland immersion evaluation.