基于有机质诊断指数的土壤镉含量反演方法研究

自20世纪20年代以来,随着工业化发展进程的加快,土壤重金属污染日趋严重,镉(Cd)因其不易分解被土壤中的有机质吸附在土壤中富集,它不仅影响作物的生长发育[1],而且Cd通过作物的吸收富集于果实中,从而通过食物链危害人体健康[2,3]。传统的土壤Cd含量测定方法是系统采集土壤表层样品,然后采用室内化学分析方法[4]。这些方法存在费钱、费时等缺陷,不能满足快速有效监测土壤Cd含量的需要。80年代后高光谱遥感技术的出现,为土壤理化性质的监测提供了新的技术手段。高光谱遥感技术利用土壤反射光谱获取土壤理化成分。土壤实验室反射光谱已成功用来预测具有光谱特征的成分,如氮含量[5]、铁氧化物[6]、碳酸盐[     

黄土偏振反射影响因子交互作用试验分析

早期遥感土壤反射光谱的研究主要是将土壤样品表面看作郎伯体,进行垂直对地观测采集数据。大量实验表明,土壤含水量、有机物含量、氧化铁含量、机械组成以及土壤表面粗糙度均会对土壤的光谱反射率产生显著影响[1]。随着遥感应用研究的深入,在20世纪70年代末,Suits、Hapke、Strahler、李小文等大批学者对地物的二向反射做了定量研究,从而使遥感进入了获取地物三维信息的崭新阶段[2~5]。偏振反射是二向反射的孪生姊妹,人们在对土壤的二向反射进行研究的同时也势必要对土壤的偏振反射进行一定的研究[6]。已有的一些观测研究表明,土壤含水量与土壤反射光偏振度之间存在着关系,即含水量越大偏振度越高,这可解     

旅游活动对泰山景区土壤质量的影响

随着旅游活动在全球范围内的迅速发展,其对自然环境的影响也成为旅游环境研究的热点。国外关于旅游对土壤性质影响的研究始于20世纪60年代,研究内容主要涉及到践踏、露营等不同类型与不同强度旅游干扰对土壤理化性质的影响等[1]。     

基于包络线法对土壤光谱特征的提取及其分析

土壤的光谱反射率是土壤内在的理化特征之光谱行为的综合反应。Stoner比较详细地描述了五大类土壤光谱反射曲线类型及其与土壤性质、土壤发生分类的关系。戴昌达等根据360～2500nm的土壤光谱反射率，将我国主要土壤的光谱反射特性曲线划分为平直型、缓斜型、陡坎型和波浪型四类。王深法等对浙江省石灰土光谱特征进行分类研究，     

藏西沙化草地根系分布与土壤理化性质的关系

[目的]调查和分析沙化过程中草地根系与土壤理化性质的关系,为藏西草地沙化的治理提供理论依据。[方法]以西藏西部典型的沙化草地为研究对象,通过S采样法进行采样,对0—15 cm土层土壤理化性质进行研究。[结果]随着沙化程度的加剧,土壤根系含量下降,pH值与速效钾含量先升高后降低,容重升高,含水量、有机质、全氮、碱解氮、速效磷降低。土壤根系含量与pH值和容重间存在极显著负相关关系(p<0.01),相关系数分别为-0.806和-0.735;与含水量、有机质、全氮、碱解氮和速效磷存在极显著正相关关系,相关系数分别为0.771,0.658,0.590,0.686,0.382。[结论]草地沙化过程中植物根系含量与多个土壤理化性质指标存在相关关系,并受土壤理化性质的制约。     

基于近地高光谱的土壤氯离子含量估测

[目的]建立土壤氯离子与高光谱波段的多元线性回归模型,获取盐渍化信息,为盐分的高精度提取提供更有效的方法,为农业生态环境重建工作提供科学依据。[方法]以山东省垦利县作为研究区,于2014年10月5—7日野外采集93个土壤样本,利用ASD高光谱仪野外采集土样高光谱数据并进行预处理,然后采用多元回归和主成分分析方法建立估测氯离子含量的高光谱模型,以快速估测氯离子含量。[结果]氯离子在近红外749,830,987,1301,1 432,1 486nm较为敏感,在土壤光谱分析的基础上,得到室内风干土壤氯离子含量预测最优模型,模型均通过T检验和F检验,能较好地预测土壤氯离子含量。[结论]研究区土壤各组分盐离子中,阳离子以钠离子为主,阴离子以氯离子为主,该模型使间接得到土壤盐分含量具有较好可行性。     

塔里木河上游表土积盐量遥感信息提取研究

国外利用卫星遥感进行土壤盐渍化研究始于20世纪70年代，至90年代以来一直以目视判读为主，Bao作了盐渍土光谱特征的专门研究，发现土壤盐渍化程度越高，光谱反射越强；在红光和绿光波段，地表植被覆盖影响盐渍土的光谱反应；土壤含水量也会影响盐渍土的光谱响应模式。骆玉霞等对盐渍土遥感信息单要素分类与遥感信息地理信息综合分类进行了比较研究。     

八达岭森林土壤养分空间变异性研究

环境的变异性对于物种的分布是十分重要的,许多研究已经证明了环境的变异性和物种丰富度之间存在正相关的关系[1,2]。在森林生态系统中,这个关系可以通过地下资源的变异性来解释说明。而土壤资源的空间变异性在个别尺度上很可能影响到该区域植被的分布、物种的丰富度和个别有机体的性能。因此,研究土壤特性的空间变异性对于了解森林群落结构和生态系统进程有着极其重要的作用[3,4]。从20世纪70年代开始,国外许多学者开始了土壤特性空间变异性研究。20世纪80年代以来,我国一些学者也开始了土壤某些特性空间变异性研究。20世纪90年代,土壤空间变异性的研究方法得到了近一步的发展。主要表现为地统计学和地理信息系统的有     

基于成像光谱技术预测氮素在土壤剖面中的垂直分布

可见—近红外(vis-NIR)高光谱成像技术应用于土壤科学是当前数字土壤研究的新方向。本研究考察了该技术预测土壤剖面氮素垂直分布的可行性。深达1 m的土壤整段剖面(1 000 mm×170 mm×65 mm)采自湖北崇阳县,成像光谱仪配备了25μm狭缝,视场角13.1°的35 mm焦距镜头和1 004×1 002像素的面阵CCD,拍摄得到剖面vis-NIR高光谱影像(400~1 000 nm共753个波段)。对获取的影像先通过几何校正解决影像形变问题,再采用监督分类方法识别提取有效土壤像素,剔除阴影裂缝等无效像素。最后利用室内土样vis-NIR反射光谱建立的土壤全氮校正模型,对3个土壤整段剖面的高光谱影像数据进行全氮(TN)预测制图。结果表明,vis-NIR成像光谱技术对土壤整段剖面TN含量预测效果达到甚至优于经标准制样处理后所建模型精度。但存在纵向局限性,其良好地还原了浅层土壤氮素的分布规律,0~600 mm为较佳预测深度。     

基于红外衰减全反射光谱的温室土壤盐分特征研究

与传统的露地耕作土壤不同,温室土壤在耕作过程中受较多的人为调控,但在调控的过程中产生了多种问题,如大量施肥导致的土壤盐渍化[1]。因此,研究如何表征温室土壤的离子特征并预测温室土壤的发展是当前设施农业发展所面临的重要问题。常规农化分析只从不同的角度分析温室土壤的特征,很难实现整体上的综合表征。红外光谱能够综合反应土壤的理化性质,在温室土壤研究中有具有明显的特点。常规的透射光谱在研究土壤时存在制样时间长和难以定量的缺点,而衰减全反射红外光谱(ATR-FTIR)则可克服这一缺点,结合化学计量学的方法,能够实现土壤的定性与定量分析[2,3]。红外光谱包含大量化学键信息,在分析时需进行合理的降维,抽取     

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。     

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.     

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.     

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.     

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.     

黑土区土壤侵蚀厚度对土地生产力的影响及其评价

为了研究黑土区土壤侵蚀厚度对土地生产力的影响,采用盆栽试验,人为剥离黑土表层0、5、10、15、20、25和30 cm土壤以模拟侵蚀厚度不同的耕层土壤,分析土壤侵蚀厚度对土壤理化性质、大豆生物性状和水分利用效率等指标的影响。并对TOPSIS(technique for order preference by similarity to ideal solution)模型进行改进,用于评价侵蚀厚度不同的土壤的土地生产力。结果表明:土壤全N、碱解N、全P、速效P、有机质含量和土壤田间持水率均随侵蚀厚度的增加而递减,土壤容重随侵蚀厚度的增加而递增。土壤侵蚀厚度对大豆生长有显著影响,随着侵蚀厚度的增加,大豆减产率呈"S型"曲线递增,产量、耗水量呈"Z型"曲线递减,水分利用效率呈指数曲线关系递减。改进的TOPSIS模型对不同侵蚀厚度下土地生产力的评价结果较为理想,计算的土地生产力指数随土壤侵蚀厚度的变化呈"Z型"曲线,与大豆产量的变化趋势相同,且二者呈指数函数关系,决定系数达0.996,均方根误差为0.65。研究结果可为黑土区土壤侵蚀防治提供理论依据。     

Tillage effects on soil degradation, soil resilience, soil quality, and sustainability

Soil degradation, decrease in soil's actual and potential productivity owing to land misuse, is a major threat to agricultural sustainability and environmental quality. The problem is particularly severe in the tropics and sub-tropics as a result of high demographic pressure, shortage of prime agricultural land, harsh environments, and resource poor farmers who presumably cannot afford science based recommended inputs. Tillage methods and soil surface management affect sustainable use of soil resources through their influence on soil stability, soil resilience, and soil quality. Soil stability refers to the susceptibility of soil to change under natural or anthropogenic perturbations. In comparison, soil resilience refers to soil's ability to restore its life support processes after being stressed. The term soil quality refers to the soil's capacity to perform its three principal functions e.g. economic productivity, environment regulation, and aesthetic and cultural values. There is a need to develop precise objective and quantitative indices of assessing these attributes of the soil. These indices can only be developed from the data obtained from well designed and properly implemented long-term soil management experiments conducted on major soils in principal ecoregions.