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根据表层土壤(0～40mm)孔隙度与降水量和土壤表面粗糙度之间的关系,提出一种预测表层土壤孔隙度的新方法。基于此目的,在德国波恩大学Dikopshof试验站,以两块采用不同耕作方式(地块1:铧式犁+圆盘耙;地块2:旋转锄+圆盘耙)处理过的耕地为研究对象,以耕后50d内的表层土壤孔隙度(TSP)与土壤表面粗糙度(SSR)为测量对象,分别采用地面激光扫描仪和气压比重计对TSP与SSR随时间的变化进行了连续测量,以研究TSP与SSR两者的动态关系。自2006到2009年,每年夏天进行1次重复试验,以研究不同降雨量对TSP与SSR关系的影响,并引入累计平均日降雨量(ARF)的影响指数。通过4a试验,得出结论:TSP随ARF增加而降低,随SSR降低而降低。在此基础上,建立了由ARF和SSR预测TSP的多元线性模型,且模型通过了F检验。结果表明,借助于地面激光扫描仪和降雨量数据,该模型可快速连续估算不同耕作方式下的土壤表层孔隙度。
According to the relationship between the porosity of surface soil (0 ~ 40mm) and precipitation and soil surface roughness, a new method for predicting the porosity of topsoil was proposed. For this purpose, at the Dikopshof test station at the University of Bonn, Germany, two cultivated lands treated with different tillage systems (Plot 1: Plow + Disc Harrow; Plot 2: Rotary Hoe + Disc Harrow) The changes of TSP and SSR over time were measured continuously by ground laser scanner and barometer with the surface soil porosity (TSP) and soil surface roughness (SSR) within 50 days of plowing. To study the dynamic relationship between TSP and SSR. From 2006 to 2009, a repeat experiment was conducted each summer to study the effect of different rainfall on the relationship between TSP and SSR, and the impact index of cumulative average daily rainfall (ARF) was introduced. Through the 4a test, it was concluded that TSP decreased with increasing ARF and decreased with decreasing SSR. Based on this, a multivariate linear model of predicting TSP by ARF and SSR was established, and the model passed the F test. The results show that with the aid of ground laser scanner and rainfall data, the model can quickly and continuously estimate soil surface porosity under different tillage systems.