基于地图直接对比的土壤空间表达尺度效应研究——以封丘土壤属性制图为例

将封丘县3 608个土壤样点分为3 463和145个点,分别构成制图数据总集和验证数据总集,再从制图数据总集中通过4%～96%的多尺度随机抽样,构成17个制图子集。分别按Kriging、IDW和以点代面法对土壤有机质、有效磷和速效钾进行预测制图,基于地图直接对比计算制图子集和制图数据总集制图结果的相关系数以评价土壤属性图变化的尺度效应,并与验证数据集评价的多尺度制图结果进行了对比。最后,采用多子集制图结果的变异系数指示多尺度地图表达的不确定性,并将其与基于Kriging估值方差及随机模拟的不确定性表达进行了对比。研究表明,基于地图直接对比可发现,制图效果与样本数量具有显著的分形关系,且分形维数受制图方法和土壤属性空间可变性的双重影响:同样条件下以Kriging方法最小,而以点代面法最大;以土壤速效钾最小,而土壤有效磷最大。验证数据集实测值和估计值的相关系数及均方根误差没有表现预期的分形特征。Kriging估值方差及随机模拟表达的单一尺度制图不确定性明显受采样点分布与Kriging估值大小影响,而基于地图直接对比的多尺度制图的不确定性更客观地反映土壤自然变异,其中土壤有机质、土壤速效钾有较强规律可循,而土壤有效磷则没有规律。     

土壤制图中多等级代表性采样与分层随机采样的对比研究

采样设计是土壤地理研究中备受关注的重要问题。本文以区域尺度土壤属性制图为例,将多等级代表性采样与经典采样中的分层随机采样进行对比研究。以安徽宣城研究区的表层砂粒含量为目标要素,采集数量均为59个的两套样点,设计不同数量(46、58和59)的样点分组,采用两种制图方法进行制图并利用独立验证点进行评价。结果表明:1)无论是采用多元线性回归方法还是基于环境相似度的制图方法,在同等样点数量下,利用代表性样点所得土壤图精度均高于利用随机样点所得精度,并且利用少量代表性样点(46个)所得土壤图精度也高于利用多量随机样点(59个)所得精度;2)随着代表性较低样点的增加,土壤制图精度基本有一个提高的趋势,而采用随机样点所得土壤图的精度波动较大。因此,可认为多等级代表性采样方法是一种可用于区域尺度土壤调查的有效采样方法,且比分层随机采样高效、稳定。     

一种基于样点代表性等级的土壤采样设计方法

采样设计是获取土壤空间分布信息的关键环节,直接影响到土壤制图的精度。目前常用的采样设计方法大多存在着设计样本量大、采样效率不高的问题。当可投入资源难以完成一次性大量采样时,采样往往需要多次、分批进行。然而现有分批采样方法多考虑各批采样点在地理空间的互补性,可能造成样本点在属性空间的重叠,影响采样资源的高效利用。鉴于此,本研究通过对与土壤在空间分布具有协同变化的环境因子进行聚类分析,寻找可代表土壤性状空间分布的不同等级类型的代表性样点,建立一套基于代表性等级的采样设计方法。将该采样方法应用于位于黑龙江省嫩江县鹤山农场的研究区,利用所采集的不同代表性等级的样点进行数字土壤制图并进行验证,探讨采样方案与数字土壤制图精度的关系,以评价本文所提出的采样方法。结果表明,通过代表性等级最高的少量样点可获取研究区的大部分主要土壤类型(中国土壤系统分类的亚类级别),且制图精度较高;随着代表性等级较低样点的加入,土壤图精度提高;但当样点增加到一定数量时,土壤图的精度变化不大。因此,与样点数相比,样点的代表性高低对制图精度的影响更大。该方法所提出的代表性等级可以为样点采集顺序提供参考,有助于设计高效的逐步采样方案。     

基于数据库驱动技术的土壤图注记自动配置系统的设计与实现

土壤注记是土壤图制图表达的重要内容,对于理解土壤的发生、分布具有重要意义。在基于全国第二次土壤普查资料进行大比例尺土壤图分幅制图过程中,若对拥有海量土壤空间信息的多分幅大比例尺土壤图实现注记表达,不可能再依赖于传统的制图方式生成注记。为了实现注记上图的自动化和以交互方式解决多个步骤判断问题,构建了土壤图注记自动配置系统。该系统采用图廓边界注记压盖检测与处理技术,解决了注记压盖图廓边界的问题;采用图层、分级码、要素对象的三级控制方法,实现了注记在图层级别上进行整个图层以及背景层注记的设置,在分级码级别上结合统计结果,实现了注记的条件判别与阈值过滤,在要素级别上实现了特殊要素注记的生成。基于数据库驱动技术并以人机交互的方式进行土壤图注记的自动化配置,实现了批量土壤图分幅注记的快速生成,不仅具有较强的灵活性,可适用于不同比例尺土壤图及其他类型地图的注记表达,而且大大提高了数据生产的效率和自动化处理程度。该研究为今后不同比例尺土壤图制图实现注记的自动化配置提供参考。     

利用计算机模拟采样确定合理的土壤采样密度(英)

为了解决土壤采样中精度与经济性的平衡问题，利用计算机模拟采样研究了规则网格土壤采样时合理的采样点密度。首先构造了一个数学扩散模型，设置2～4个种子在一个100×100网格（1×1单位）的不同地方，根据扩散模型进行扩散和叠加，生成模拟的土壤属性分布地图，其结果可很好地模拟某些土壤属性的分布。利用计算机按照不同的网格单元尺寸（如3×3，5×5，7×7等）进行采样，之后利用采样值进行IDW插值处理，将数据点恢复到原始的10000个，并把插值结果与原始值进行比较即可得到采样误差。研究结果表明，当采样网格单元尺寸为属性地图输出栅格单元尺寸的11倍和17倍时，相对采样误差分别为10%和15%。合理的采样密度可以根据允许的采样误差及要求的属性地图输出栅格单元尺寸而定。     

土壤制图中土壤类型配色模型构建与应用

在全国1∶5万土壤图集制图中,土壤类型的配色既需表现土类等高级类型的分布特征,也要表现土属等较低级类型的差别。我国土壤低级类型众多,且1∶5万基本比例尺图幅达2万余幅,采用传统人工设色方法进行土壤制图,不仅效率低,而且难以保持图幅间土壤颜色的协调一致性。针对这一技术难题,本研究采用图幅间相似配色方法和人机交互的设计思想,通过建立1个多层级管理色库、人工设置土壤类型的Q配色单元及其多个近似色系(色组),建立了Q配色单元的避让选色和区域土壤特征分析等5个组件模型,构建了土壤类型配色模型(SCO-Model)。该模型在大比例尺土壤制图中不仅反映了区域土壤的总体分布特征,也表达了土壤类型间的差异,特别是实现了大比例尺土壤制图中土壤类型的快速智能配色,大大提高了制图效率。     

基于传统土壤图的土壤—环境关系获取及推理制图研究

在数字土壤制图研究中,从历史资料中提取准确的、详细的土壤—环境关系对于土壤图的更新和修正十分重要。从传统土壤图中提取土壤类型并从地形数据中提取环境参数,采用空间数据挖掘方法建立土壤—环境关系,并进行推理制图和精度验证。以湖北省黄冈市红安县华家河镇滠水河流域为例,首先选取成土母质和基于地形数据提取的高程、坡度、坡向等7个环境因子;然后利用频率分布原理得到包含土壤类型与环境因子信息的典型样本数据1 410个;采用See5.0决策树方法进行空间数据挖掘,建立土壤—环境关系;将其导入So LIM中进行推理制图;最后利用270个实地采样点验证所得土壤图的精度。土壤图的精度提高了约11%,证明了本研究方法对土壤类型和空间分布推理的可靠性。     

面向数字土壤制图的土壤采样设计研究进展与展望

全球化土壤环境问题的出现对基础输入数据的精度、尺度和时序提出了更高要求,面向数字土壤制图的土壤采样研究得到了快速发展。首先利用文献计量学的方法定量化分析国内外土壤采样研究学科分布和研究热点变化;随后重点梳理了国内外土壤采样研究的文献,根据不同的土壤调查目的、调查区历史采样点将土壤采样设计分为:土壤全面采样设计、土壤补充采样设计、土壤验证采样设计和土壤监测采样设计;最后介绍了基于样点的推理制图方法。在此基础上,对未来在多尺度的土壤采样设计、土壤–环境因子关系的新型假设和采样设计中现实问题的量化等方面进行了展望,旨在为数字土壤调查工作的开展提供参考依据。     

基于不同模型的区域尺度耕地表层土壤有机质空间分布预测

研究不同模型对土壤有机质空间预测的性能差异对制定更加科学合理的采样策略、提升采样效率和提高土壤空间预测精度有着重要的指导意义。本研究将6496个土壤样点按8∶2的比例分层随机分成训练集与验证集,应用普通克里格、随机森林以及随机森林－回归克里格三种有代表性的数字化土壤制图（Digital Soil Mapping,DSM）模型,对河南省许昌市耕地表层土壤有机质含量及空间分布进行预测,对三种模型性能表现进行综合评价。三种模型输出的预测结果显示:研究区耕地表层土壤有机质含量水平一般,均值为18.70 ~ 18.81 g kg?1,变异系数0.15 ~ 0.17,属中等强度变异;空间分布总体格局为西北与西南部分山地褐土区、东南部砂姜黑土区表层有机质含量高,中北部脱潮土、石灰性潮土区表层有机质含量低。验证结果表明:三种模型性能表现无明显差距,预测精度基本一致,输出结果对研究区耕地表层土壤有机质变异解释百分比在33% ~ 34%之间,在相同和相近尺度土壤有机质空间预测案例研究里属中等水平。在协变量有限且样点分布较为均匀的情况下,普通克里格模型便于快速获得研究区目标变量的空间分布;如果协变量比较丰富且易于收集利用,或是进行空间预测的同时还需要甄别不同因素对目标变量的影响大小,则建议采用随机森林模型;协变量有限,但样点密度较大时,随机森林－回归克里格模型可能是对目标变量进行空间预测的不错选择。     

样点代表性等级采样法在丘陵山区土壤表层有机质制图中的应用

基于样点代表性等级的土壤采样方法在成本、应用性、制图准确度上具有明显的优势,但在其他方面(如敏感性)上仍需要大量研究。为了进一步研究这种方法的可用性,本文以安徽宣城境内的丘陵山区为研究区,应用该方法分析以往土壤采样点的代表性等级,进而研究样点代表性等级对土壤制图准确度的影响。研究结果表明:①高等级代表性链广泛存在,而低等级代表性链则较少;②代表性链的等级有效地从不同程度反映出土壤形成环境的变异;③样点代表性采样设计的采样点与规则化网格采样、目的性采样有很大不同;④一般地,随着低等级样点的逐渐加入,制图准确度增加,但增幅随着样点等级的降低而降低。这些结果说明,样点代表性等级采样法在应用、成本、准确度几个方面都有明显的优点,因而具有较好的应用前景。需要注意的是,在应用该方法选择样点时,样点的代表性应达到一定级别,以避免制图准确度不会因为样点的加入而降低。此外,由于其他地形地貌类型(如平原区)还缺乏较好的土壤协同环境因子,该方法的应用受到了一定程度的限制。     

Effect of tillage treatments upon soil tests for soil acidity,soil phosphorus and soil potassium at three soil depths

Abstract

Soil samples were obtained at 0–3, 3–6, 6–9 and 0–9 inch depths from experimental plots receiving five tillage treatments. Each of two samplers composited approximately six one‐inch cores from each plot. Soil samples were analyzed for acidity, P and K using routine analysis procedures in the University of Illinois Soil Testing Laboratory.

Few significant differences were attributed to sampler and it was concluded that samplers using similar sampling techniques were obtaining soil samples from the same population.

No significant differences in soil acidity at different depths were observed. The different tillage methods did significantly affect soil P at the 0–3 inch depth, but had no significant effect on soil P at deeper depths. Different tillage methods also significantly affected soil K values at different depths.     

Usability of soil survey soil texture data for soil health indicator scoring

Soil textural information is an important component underlying other soil health indicators. Soil texture analysis is a common procedure, but it can be labor intensive and expensive. Soil texture data typically are available from the Soil Survey Geographic (SSURGO) database, which may be an option for determining soil health texture groups (SHTG). The SSURGO database provides soil texture information in the soil map unit (SMU) name, taxonomic class category (family), and detailed values (≤ 2 mm soil fraction) of percent sand, silt and clay by soil horizon. The objective of this study was to examine the possibility of using SSURGO data for SHTG at the 147-ha Cornell University Willsboro Research Farm in New York state as an alternative for soil texture data determined manually on collected soil core samples. Comparative results revealed that representative values for soil texture from the SSURGO database generally matched measured mean values for all SMUs.     

土壤含水率与土壤碱度对土壤抗剪强度的影响

土壤含水率和土壤碱度是表征土壤物理化学性质的两个重要参数。通过室内三轴不固结不排水试验，研究了土壤含水率和土壤碱度对土壤抗剪强度的影响。试验处理采用5种土壤碱度(土壤可交换钠百分比ESP=0、5、10、20、40)和4种土壤质量含水率(0.05、0.10、0.20以及饱和含水率0.34)水平。试验结果显示，土壤黏聚力随着土壤含水率的增加基本上呈先增大后减小之趋势；当土壤含水率在0.10附近时黏聚力达到其最大值。土壤内摩擦角随着土壤含水率的增加而线性减小。土壤碱度对土壤黏聚力的影响机理较为复杂，其影响效果随土壤含水率的增加而减小；但土壤碱度对土壤内摩擦角的影响较小。土壤碱度对土壤抗剪强度的影响程度明显地小于土壤含水率对其的影响程度。     

Relationships between soil respiration and soil moisture

The interaction of soil microbes with their physical environment affects their abilities to respire, grow and divide. One of these environmental factors is the amount of moisture in the soil. The work we published almost 25 years ago showed that microbial respiration was linearly related to soil-water content and log-linearly related to water potential. The paper arose out of collaboration between two young researchers from different areas of soil science, physics and microbiology. The project was driven by not only our curiosity but also the freedom to operate without the constraints common to the current system of science management. The citation history shows three peaks, 1989, 1999 and from 2002 to the present day. Interestingly, the annual citation rate is as high as it has ever been. The initial peak is due to the application of the work to studies on microbial processes. The second peak is associated with the rise of simulation modelling and the third with the relevance of the findings to climate change research. In this article, our paper is re-evaluated in the light of subsequent studies that allow the principle of separation of variables to be tested. This re-evaluation lends further credence to the linear relationship proposed between soil respiration and water content. A scaled relationship for respiration and water content is presented. Lastly, further research is suggested and more recent work on the physics of gas transport discussed briefly.     

A soil core for routine soil sampling

Abstract

The design, materials and dimensions for constructing a coring device for sampling soil fauna and flora at different depths is described.     

Relationship between soil respiration and soil moisture

Microbial activity is affected by changes in the availability of soil moisture. We examined the relationship between microbial activity and water potential in a silt loam soil during four successive drying and rewetting cycles. Microbial activity was inferred from the rate of CO₂ accumulating in a sealed flask containing the soil sample and the CO₂ respired was measured using gas chromatography. Thermocouple hygrometry was used to monitor the water potential by burying a thermocouple in the soil sample in the flask. Initial treatment by drying on pressure plates brought samples of the test soil to six different water potentials in the range -0.005 to -1.5MPa. Water potential and soil respiration were simultaneously measured while these six soil samples slowly dried by evaporation and were remoistened four times. The results were consistent with a log-linear relationship between water potential and microbial activity as long as activity was not limited by substrate availability. This relationship appeared to hold for the range of water potentials from ?0.01 to ?8.5 MPa. Even at ?0.01 MPa (wet soil) a decrease in water potential from ?0.01 to ?0.02 MPa caused a 10% decrease in microbial activity. Rewetting the soil caused a large and rapid increase in the respiration rate. There was up to a 40-fold increase in microbial activity for a short period when the change in water potential following rewetting was greater than 5 MPa. Differences in microbial activity between the wetter and drier soil treatments following rewetting to the original water potentials are discussed in terms of the availability of energy substrate.     

Volumetric soil measures for routine soil testing

Abstract

The design, dimensiors and materials for constructing volumetric soil measures for routine soil testing use are presented. Scoop calibration techniques are also described. Reproducibility of results obtained under routine laboratory, conditions are shown. The measures include volumes of 1.0‐, 2.5‐, 5.0‐ and 10‐ cm³ respectively.     

Why soil erosion models over-predict small soil losses and under-predict large soil losses

Evaluation of various soil erosion models with large data sets have consistently shown that these models tend to over-predict soil erosion for small measured values, and under-predict soil erosion for larger measured values. This trend appears to be consistent regardless of whether the soil erosion value of interest is for individual storms, annual totals, or average annual soil losses, and regardless of whether the model is empirical or physically based. The hypothesis presented herein is that this phenomenon is not necessarily associated with bias in model predictions as a function of treatment, but rather with limitations in representing the random component of the measured data within treatments (i.e., between replicates) with a deterministic model. A simple example is presented, showing how even a `perfect' deterministic soil erosion model exhibits bias relative to small and large measured erosion rates. The concept is further tested and verified on a set of 3007 measured soil erosion data pairs from storms on natural rainfall and run-off plots using the best possible, unbiased, real-world model, i.e., the physical model represented by replicated plots. The results of this study indicate that the commonly observed bias, in erosion prediction models relative to over-prediction of small and under-prediction of large measured erosion rates on individual data points, is normal and expected if the model is accurately predicting erosion rates as a function of environmental conditions, i.e., treatments.     

An equivalent soil mass procedure for monitoring soil organic carbon in multiple soil layers

Soil carbon stocks are commonly quantified at fixed depths as the product of soil bulk density, depth and organic carbon (OC) concentration. However, this method systematically overestimates OC stocks in treatments with greater bulk densities such as minimum tillage, exaggerating their benefits. Its use has compromised estimates of OC change where bulk densities differed between treatments or over time periods. We argue that its use should be discontinued and a considerable body of past research re‐evaluated. Accurate OC estimations must be based on quantification in equivalent soil masses (ESMs). The objective of this publication is to encourage accurate quantification of changes in OC stocks and other soil properties using ESM procedures by developing a simple procedure to quantify OC in multiple soil layers. We explain errors inherent in fixed depth procedures and show how these errors are eliminated using ESM methods. We describe a new ESM procedure for calculating OC stocks in multiple soil layers and show that it can be implemented without bulk density sampling, which reduces sampling time and facilitates evaluations at greater depths, where bulk density sampling is difficult. A spreadsheet has been developed to facilitate calculations. A sample adjustment procedure is described to facilitate OC quantification in a single equivalent soil mass layer from the surface, when multiple‐layer quantification is not necessary.     

节水灌溉对盐渍土盐分调控与土壤微生物区系的影响

河套灌区是我国大型自流灌区之一,盐渍化是该区土壤主要障碍因素之一。目前,河套灌区葵花田生育期灌溉量约为1 100～1 200 m3hm-2,灌溉用水量偏大和地下水位偏高已成为制约当地灌溉农业可持续发展的主要障碍:一方面,水资源浪费严重;另一方