中文摘要：

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。

英文摘要：

The objective of this paper was to develop a new method to predict topsoil （0-40 mm） porosity （TSP） using soil surface roughness （SSR） under rainfall influence. For this purpose, serial experiments were conducted in Dikopshof Experimental Station, Bonn University, Germany at each summer form year 2006 to 2009. In these experiments, TSP and SSR of two fields cultivated by two different tillage types （moldboard plow ＋ harrow for field 1 and rotary hoe ＋ harrow for field 2 ） were measured after tilled （0-50 days） under natural conditions. In here TSP was measured by pycnometer and SSR by laser profilemeter. A new index of rainfall was defined as accumulative mean rainfall （ARF） to investigate the rainfall influence. The four year＇s results showed that TSP reduced with the increase of ARF and decrease of SSR. Based on this relation, a multiple linear regression model for predicting TSP using SSR under rainfall impacts was established. Verifying by F-test, this model was suitable for estimating TSP. Using the data of laser profilemeter and rainfall, this model will be used to predict topsoil porosity under different tillage types.