Temporal evolution characteristics and prediction methods of spatial correlation function shape of rough soil surfaces

Abstract

Soil surface roughness is an important boundary parameter that affects land-atmosphere interactions. Previous studies have primarily characterized the temporal-spatial variability of surface roughness parameters based on root mean square height (rmsh) and correlation length (cl), but ignored the change in correlation function shape of rough soil surfaces. In this study, three rough surfaces with different initial roughness (Rough, Medium, and Small) were designed and the temporal changes in their surface heights were observed from 29 April 2015 to 25 August 2015. Through analyzing the temporal variation of the correlation function shape and its prediction methods, the following conclusions were achieved: 1) the fractal correlation function was more consistent with the experimental data than the exponential and Gaussian function; 2) the α value of fractal correlation function represents the correlation function shape, and it changed from 1 (exponential surface) to 2 (Gaussian surface) from the beginning to the end of the experiment; 3) the α prediction method based on Day of Year (DoY) and cumulative rainfall (CR) was better than the rmsh-based method, due to their feasibility for various initial roughness conditions. In general, this study confirmed that correlation function shape of rough soil surfaces is time-dynamic, and we proposed a method for quantifying its temporal dynamics using DoY or CR with the R2 of 0.71 and 0.74 respectively. The results of this study will help to understand the time-varying characteristics of surface roughness parameters and support future research on agricultural remote sensing and wind erosion.