降雨过程中不同粗糙度土表微地貌特征演变与三维模型的建立

Evolution of Microrelief Features during Rainfalls and Etablishment of 3D Models for Different Soil Surface Roughness

作者: 专业:资源环境信息工程 导师:蔡崇法 年度:2010 学位:硕士  院校: 华中农业大学

Keywords

Laser scan, Soil surface roughness, Maximum depression storage, Soil roughness model

        土表粗糙度作为反映土表微地貌形态和物理性状的指标,在水土保持工作和土壤侵蚀研究中是一个重要因子。然而,关于土表粗糙度在侵蚀过程中详细的定量信息极其有限。本文以3-5mm、2-3mm、小于2mm紫色土团聚体为供试土样制造不同粗糙度土表,从水力侵蚀过程中土表粗糙度及最大填洼量定量化特征演变角度出发,通过室内人工降雨模拟试验,研究了不同坡度下三种不同粗糙土表上中下坡位糙度、最大填洼量时空变化特征,以期进一步明确其在水蚀过程中的变化及其作用。研究坡面土表微地貌对土壤侵蚀过程的影响及其在坡面侵蚀过程的变化对于建立基于过程的土壤侵蚀模型有重要意义,并通过改进高斯模型和分形模型,建立适合不同粗糙度土表的描述模型,以期丰富土壤侵蚀过程和机理的定量化研究内容。1.通过评价随机糙度计算法、微地形指数法、弯曲度指数法、平均上坡凹陷量法、平均绝对高差法在微域土表上的适用性,选择土表粗糙度评价指标,用聚合洼地法和漫水法评价最大填洼量的测算方法,结果表明:平均绝对高差法是土表粗糙度最佳评价指标;采用聚合洼地法和漫水法计算得到的最大填洼量基本相等,这两种算法在最大填洼量的计算上无显著性差异。采样精度越高越能捕捉微小的洼地,越能准确反映最大填洼量。2.以激光微地貌扫描为手段,定量研究降雨过程中土表微地貌的演变过程,结果表明:四种坡度三种不同粗糙度土表上中下坡位微地貌特征时空变化规律表现出不一致性;坡度对平滑土表微地貌特征演变过程影响最大,中等粗糙土表次之,粗糙土表影响最小;随着坡度的增加,三种不同粗糙度土表上坡、中坡、下坡土表粗糙度及最大填洼量均呈增加趋势;同一坡面不同坡位土表粗糙度及最大填洼量的下降幅度:中坡>下坡>上坡,或增加幅度:中坡<下坡<上坡。3.MNG法模拟的粗糙土表的MDS、LD·LS与实测土表基本相等,虽然高程频率分布、偏度和半变异函数与实测土表存在差异,但是就微地貌的特征描述来说已经到达了模拟的要求,因此,MNG法适用于粗糙土表的模拟。MRMD法模拟的中等粗糙和平滑土表的MDS、LD·LS与实测土表基本相等,且半变异函数与实测土表基本一致,因此,MRMD法适用于中等粗糙和平滑土表的模拟。
    As an indicator to reflect the form of microrelief and physical characteristics, soil surface roughness plays an important part in water and soil conservation and the soil erosion research. However, the quantitative information about the soil surface roughness in erosion process is very limited. The paper made three different soil surface roughness according to the soil samples of purple soil aggregates which are 3-5mm,2-3mm and less than 2mm. From the measurable changing aspect of soil surface roughness and MDS in hydraulic erosion process, the paper also studied the temporal and spatial variation features of the soil surface roughness and MDS for the three different soil surface roughness in the different parts of slope throughout the indoor artificial rainfall so as to make sure the changes in the erosion process and its function. The research of the influence of microrelief on the erosion process and its change during the process has great significance on establishing the soil erosion model based on the process.What’s more, it enriched the quantitative research on the process and mechanism of soil erosion by improving Gaussian model and Fractal model and establishing the simulate model that can be suitable for different soil surface roughness.1.Roughness index was selected by evaluating the applicability of random roughness, microrelief index an peak frequency, tortuosity, mean upslope depression and limiting elevation different and slope in the microzone. The method of calculating MDS was evaluated by J&D algorithm and M&V algorithm.The results indicated limiting elevation different and slope was the best roughness index, the difference between MDS calculated by J&D algorithm and calculated by M&V algorithm was not statistically significant, the higher the sampling precision was, the more small depression can be obtained, and the more precise MDS can be.2.Using laser scan to study quantitatively the changes of characteristics of microrelief during rainfalls. The results illustrated that the temporal and spatial variation features of roughness and MDS of different parts of slope under different slopes for three different soil surface roughness showed inconsistency. Slopes had significant effects on the changes of characteristics of microrelief for smooth soil surface, the medium rough soil surface took second place, and the rough soil surface had minimum effects on the changes of characteristics of microrelief. With the increase of slope, the roughness and MDS of different parts of slope for three different soil surface roughness showed an increasing trend. The roughness and MDS of different parts of slope for one slope showed the trend:the middle of slope decreased larger or increased smaller than the bottom of slope, the bottom of slope dropped off larger or increased less than the upper of slope.3.The MDS and LD·LS of rough soil surface simulated with MNG were equal to observed soil. Although there were differences on frequency distributions of heights, coefficient of skewness, semivariogram between simulated soil surface and observed soil, the simulated requirements according to the features of microrelief were reached. Thus the method was fit for the simulation of rough soil surface. The MDS and LD·LS of the medium rough and smooth soil surface simulated with MRMD were equal to observed soil.Besides, there were a little differences on semivariogram between simulated soil surface and observed soil.Therefore this method was fit for the simulation of medium rough and smooth soil surface.
        

降雨过程中不同粗糙度土表微地貌特征演变与三维模型的建立

摘要6-7
ABSTRACT7-8
1 绪论9-10
2 国内外研究进展10-16
    2.1 土表粗糙度的概念、类型及影响因子10-11
        2.1.1 土表粗糙度的概念10
        2.1.2 土表粗糙度分类10-11
        2.1.3 土表粗糙度影响因子11
    2.2 土表粗糙度的量测与测算方法11-12
    2.3 土表粗糙度对坡面侵蚀的影响12-13
    2.4 最大填洼量与坡面侵蚀的关系13-15
    2.5 土表粗糙度模型15-16
3 研究内容与技术路线16-18
    3.1 研究目的和意义16
    3.2 研究内容16-17
    3.3 技术路线17-18
4 材料与方法18-26
    4.1 研究区域及样品采集18
    4.2 试验小区设置18-19
    4.3 人工模拟降雨19
    4.4 微地貌数据采集与预处理19-21
        4.4.1 激光微地貌扫描仪工作原理19-20
        4.4.2 激光点云数据采集与预处理20-21
    4.5 评价微地貌特征演变21-22
    4.6 土表粗糙度三维模型建立22-26
        4.6.1 基于正态高斯分布的中值滤波法(Median filtering methodbasedon normal-Gaussian model,MNG)22-23
        4.6.2 基于随机中点位移法的中值滤波法(Median filtering methodbased on Random Midpoint Displacement,MRMD)23-26
5 结果与分析26-53
    5.1 微地貌特征评价指标的筛选与算法实现26-34
        5.1.1 粗糙度26-28
        5.1.2 最大填洼量28-34
    5.2 连续降雨过程中土表微地貌特征演变34-43
        5.2.1 粗糙土表35-37
        5.2.2 中等粗糙土表37-39
        5.2.3 平滑土表39-41
        5.2.4 小结41-43
    5.3 土表粗糙度三维模型验证43-53
        5.3.1 最大填洼量(MDS)和土表粗糙度指标(LD·LS)43-44
        5.3.2 DEM可视化比较44-49
        5.3.3 高程分布特征分析49-50
        5.3.4 半变异函数比较分析50-53
6 结论53-54
参考文献54-59
致谢59
        


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