长期不同施肥对土壤无机硫组分的影响

通过棕壤长期定位施肥试验研究了玉米-玉米-大豆轮作方式下不同施肥处理对土壤无机硫各组分含量的影响,结果表明,长期施用有机肥或有机肥与化肥配合施用,可以显著提高土壤水溶性硫的含最;单施有机肥土壤中吸附态硫含量呈现先升高后降低的趋势,但总体为上升趋势;有机肥与化肥配合施用土壤中吸附态硫的含量在1991年前增长速率较快,此后基本保持平衡,而对照处理土壤中吸附态硫含量基本保持不变;各处理中除不施肥处理呈现缓慢下降趋势外,其他土壤盐酸可溶性硫的含量均持续增加.     

施肥结构对砂质潮土中微量营养元素空间变化的影响

本文通过长期定位施肥试验 ,分析了不同施肥结构对砂质潮土交换性钙、镁及有效硫、锌、锰、铜、铁等在 0～ 1 2 0cm土体中空间分布变化的影响 .结果表明 ,磷肥明显提高土壤交换性钙的含量 ,而有机肥与氮肥对土壤钙含量无明显影响 .但有机肥显著增加土壤交换性镁含量 ,各层镁含量与有机肥用量呈显著或极显著正相关 ,磷肥同样对土壤镁有提高作用 ,但氮肥无论是否与有机肥配施均降低了土壤各层交换性镁含量 .土壤 0～ 4 0cm有效锌、锰、铁均随有机肥增加而增加 ,并与有机肥用量呈极显著正相关 .而化肥无论是否与有机肥配施均降低土壤有效锌含量 ,但却增加了有效铁含量 .氮肥单施降低土壤有效锰含量 .在无有机肥情况下 ,施磷提高土壤有效铁含量 ,而在施有机肥条件下磷肥则降低耕层有效铁含量 .磷肥只在单施化肥时增加土壤有效锰含量     

不同施肥处理对棕壤几个肥力指标的影响

23年定位试验结果表明:土壤有机碳、全氮和碱解氮、生物氮量以:高量有机肥区>低量有机肥区>化肥区>对照。土壤C/N基本维持在11~16之间。单施化肥处理土壤微生物碳量降低,Kos值高于其它施化肥处理,有机无机肥配合施用,结合态腐殖质含量明显下降,松结态/重组腐殖质的比值和松/紧比值也有所降低。有机无机配施各处理土壤微生物碳量,以及土壤松结态、稳结态、紧结态腐殖质的含量显著升高,提高松结态/重组腐殖质和松/紧的比值;不同用量的施有机肥处理土壤微生物碳量与对照相比差异不显著,Kos值下降,其他指标均升高。     

长期施肥对棕壤有机碳及各组分的影响

本文通过棕壤长期定位施肥试验,研究了玉米-玉米-大豆轮作条件下不同施肥处理土壤有机碳及其不同密度组分的变化及其影响闪素.结果表明:经过27年的长期不同施肥,土壤有机碳含量有了明显变化,总的变化趋势是:高量有机肥区(12.30g kg-1)>低量有机肥区(11.41g k-1)>化肥区(9.95g kg-1)>1979年(试验前9.03g kg-1)>对照处理(8.23g kg-1),尤其以高量有机肥配施化肥处理的有机碳水平最高,氮磷钾配合施用有机碳水平要高于其它单施化肥处理;长期施肥可以显著提高土壤中轻组部分含量和轻组有机碳含量,不同施肥处理间差异显著.单施化肥处理,特别是氮磷钾配合施用,轻组部分数量和轻组有机碳含量高于无肥处理和试验前土壤.有机无机肥配合施用轻组有机碳含量明显高于单施化肥处理.施用不同肥料均可以提高土壤重组有机碳含量,有机无机肥配施效果明显.     

长期定位施肥对棕壤有机碳的影响

通过对棕壤有机肥和化肥长期定位施肥的研究表明,长期施肥对耕层土壤有机碳含量和有机碳储量有显著性影响(P<0.05)。与试验前土壤相比,施用有机肥能显著增加土壤有机碳含量和储量;当有机肥和无机肥配合施用时,其促进作用明显大于单施化肥。单施化肥能够提高土壤有机碳含量和储量,但增加幅度不大。经过26年施肥,不同层次土壤有机碳含量有一定程度的升高,随着土层的加深,有机碳含量迅速下降,各处理之间无明显差异。     

长期定位施肥对棕壤钾素垂直分布状况的影响

通过26年棕壤肥料长期定位试验,研究化肥与有机肥长期定位施用对棕壤钾素垂直分布状况的影响,结果表明,从1979年到2004年不论施钾与否各处理0~20 cm土层土壤中各形态钾素含量均高于20~40 cm土层,长期施肥对土壤钾素的垂直移动影响不大。长期不施钾各处理0~20 cm和20~40 cm土层土壤中各形态钾均表现出明显的下降趋势;有机肥的长期施用能维持棕壤速效性钾的平衡,缓解非交换性钾的下降趋势,促进矿物钾的有效化进程。     

砂姜黑土长期定位培肥技术研究

根据20年定位试验资料,阐述了有机肥与化肥配施、单施有机肥、单施化肥及不施肥等五种施肥方式对作物产量和土壤肥力的影响。两季作物的总产量以有机肥与化肥配施处理最高,较单施有机肥和单施化肥分别增产18.4%～36.1%和7.4%～23.4%。有机肥与化肥配合,能显著增加土壤有机质、全氮、全磷、有效氮、磷的含量。每kg氮素增产粮食数也以等量的有机肥与化肥配施的处理最多。有机肥加化肥是砂姜黑土培肥改良较理想的施肥方式,但同时必须重视钾肥的施用。     

长期施肥对土壤颗粒有机碳和酶活性的影响

为探讨长期不同施肥条件下土壤颗粒有机碳和土壤酶活性的变化及其关系,对棕壤肥料长期定位试验地第27年耕层土壤的颗粒有机碳和主要酶活性进行了测定与分析.结果表明:长期施用有机肥显著提高土壤中的总有机碳(TOC)、游离态颗粒有机碳(FPOM-C)和闭蓄态颗粒有机碳(OPOM-C)含量及土壤颗粒有机碳POM-C/TOC和FPOM-C/OPOM-C.单施化肥使土壤的TOC含量有所增加,但显著降低了FPOM-C和OPOM-C含量及POM-C/TOC和FPOM-C/OPOM-C;长期施用有机肥显著提高土壤的过氧化氢酶、转化酶、脲酶和中性磷酸酶活性,且均随有机肥用量的增加而增加.单施化肥对土壤酶活性影响差异较大.相关分析结果显示:土壤的TOC、POM-C、FPOM-C和OPOM-C含最两两之间均呈现显著或极显著相关关系;土壤的TOC、POM-C、FPOM-C和OPOM-C含量与过氧化氢酶、转化酶、脲酶和中性磷酸酶活性之间存在密切关系.     

施肥对黑土农田土壤全碳、微生物量碳及土壤酶活性的影响

通过对吉林省德惠市中层黑土农田6年定位施肥试验研究表明,施有机肥、秸秆还田 有机肥、秸秆还田 化肥和半量有机肥 化肥处理较单施化肥、未施肥和休闲裸地处理提高了土壤全碳、全氮含量,降低了土壤碳氮比。对玉米播前、抽穗期和收获期土壤微生物量碳测定表明,抽穗期土壤微生物量碳最高,处理间差异显著,且不同采样时期的土壤微生物量碳与土壤全碳含量之间呈高度正相关。对土壤酶活性研究表明,施有机肥较单施化肥、未施肥和休闲裸地处理显著地提高了土壤脲酶、转化酶和过氧化氢酶活性;单施化肥处理对土壤转化酶和过氧化氢酶具有一定的抑制作用;而有机肥、秸秆和化肥之间的配合施用处理的土壤酶活性表现不一致。相关分析显示土壤微生物量碳与土壤酶活性呈显著或极显著正相关。该研究结果表明,长期向中层黑土农田增施有机物,不仅提高了土壤全碳和土壤微生物量碳的含量,而且也提高土壤酶活性,有利于提高土壤养分转化效率,可使黑土质量向健康方向发展。     

新垦淡灰钙土不同施肥定位试验初报

淡灰钙土是宁夏重点开发利用的耕地资源。针对新垦淡灰钙土土壤养分含量十分贫乏的问题,采取田间定位试验的方法,研究了新垦淡灰钙土4年不同施肥处理的增产培肥效应,结果表明:单施氮肥、有机肥和氮磷、氮磷锌及氮磷有机肥配施均有显著的增产作用。其中,施N225kg hm-2,较不施肥(对照)平均增产46.9%;施P2O5103.5~207.0kg hm-2,较单施氮肥平均增产31.3%,土壤速效磷提高1~2倍;每公顷第1年增施硫酸锌45kg hm-2的较氮磷配施平均增产7.7%,土壤有效Zn含量连续4年较氮磷配施提高1~1.5倍;增施羊粪11250~22500 kg的较氮磷配施平均增产14.1%,同时,土壤有机质含量较单施化肥提高30%左右。     

土壤健康及土壤动物生物指示的研究与应用

对土壤健康的概念、土壤健康指示生物－土壤动物的特性、土壤动物及其作为土壤健康生物指示作用研究的进展及发展方向进行了论述,为我国从土壤动物学角度开展土壤健康质量研究提供参考。     

Influence of soil surface roughness on soil bidirectional reflectance

The non-Lambertian behaviour of soil surfaces depends on its roughness at micro-scale and larger scales, as well as on the incident angle of the direct solar beam on the surface. A geometrical model, taking into account the diffuse as well as the specular component of energy leaving soil surfaces in the visible and near-infrared, is used in the paper to describe the influence of soil surface roughness, caused by soil aggregates or soil clods, on the soil bidirectional reflectance distribution. A rough soil surface in the model is simulated by equalsized opaque spheroids lying on a horizontal surface. The model was tested in outdoor conditions on artificially formed soil surfaces made of two spectrally different soil materials: a mineral loam, and a loam with high organic matter content. The spectral data were measured by a field radiometer in the three SPOT (HRV) bands. The model predicts that at specific illumination conditions, soils surfaces with the highest roughness, expressed by the minimum distances between soil aggregates, can show lower variation of reflectance in the view zenith angle function than soil surfaces of a lower roughness.     

Unmixing of soil types and estimation of soil exposure with simulated hyperspectral imagery

Hyperspectral determination of soil types has the potential to become an important addition to the methods used for classification and mapping of soils. In this study laboratory measured spectra of different soils, vegetation and crop residue were combined to simulate hyperspectral remote sensing imagery. The overall aim was to examine the spectral unmixing of these materials under laboratory conditions to better understand the limits to prediction of soil types and determination of cover fractions. Two different methods were utilized to mix spectra of the soil and vegetation and substantial differences were observed in the unmixing results from the different image types, particularly in mixed pixels. Results found pure soils were easily distinguished from each other when not mixed with vegetation, while some mixes of soil and vegetation were confused as pure soil spectra. The accuracy of abundance fractions retrieved in the unmixing process also varied substantially with soil type and vegetation cover.     

Multiscale MAS modelling to simulate the soil environment: Application to soil ecology

Soils are important components of ecosystem and their functioning is of great importance for human well-being. Describing, understanding, foreseeing, and controlling biological activities and functions in soil in the context of global change are major objectives for scientists. Modelling soil bioturbation by soil engineers is of great importance although it is faced with the difficulty to describe the soil physical environment. Creating a model of a soil leads to complexity problems: a soil is a multi-scale heterogeneous, three-dimensional and dynamic environment that cannot be modelled and simulated without defining a suitable and optimized representation and taking assumptions about the studied system. An approach based on fractal theory (often used in soil sciences) was chosen to model such a real complex environment; it was integrated into a multi-agent system (MAS). MAS allows to simulate situated agents (earthworms) in an virtual world. The originality of this present MAS is that it is based on a dynamic environment which builds itself, on demand, according to an abstract canvas tree and agent movements. The aim of this paper is to present this approach and its originality, and to describe the model and the simulator. A theoretical view of the approach is given and applied to a case study: the impact of earthworms on soil structure and organic matter dynamics.     

Experimental data for separation of vegetation and soil and estimation of soil moisture using passive microwaves

Abstract

Microwave radiometer measurements of soil moisture content were made over bare and vegetated fields with dual polarized microwave radiometers at 1·55GHz (L-band) and 19·1 GHz (K.-band). Two typical Indian crops Bazra and Gawar have been studied. The bare field measurements were used to investigate the effect of soil texture on sensitivity of a radiometer to soil moisture and for soil moisture sampling depth. It is found that expression of soil moisture as available moisture content in the soil can minimize the texture effect. The estimated soil moisture sampling depth for L-band is 2-5 cm, while for K-band it is less than 2 cm. The vegetation cover affects the sensitivity of the radiometer to soil moisture. This effect is more pronounced the denser the vegetation and higher the frequency of observation. The measured polarization factor over a vegetated field at L-band was found to be appreciably reduced compared to that over a bare field. The difference between normalized brightness temperature from L-band and K-band is sensitive to vegetation type. The soil moisture under vegetation cover at L-band can be predicted well using Jackson's parametric model.     

Analysis of TerraSAR-X data sensitivity to bare soil moisture, roughness, composition and soil crust

Soils play a key role in shaping the environment and in risk assessment. We characterized the soils of bare agricultural plots using TerraSAR-X (9.5 GHz) data acquired in 2009 and 2010. We analyzed the behavior of the TerraSAR-X signal for two configurations, HH-25° and HH-50°, with regard to several soil conditions: moisture content, surface roughness, soil composition and soil-surface structure (slaking crust).The TerraSAR-X signal was more sensitive to soil moisture at a low (25°) incidence angle than at a high incidence angle (50°). For high soil moisture (> 25%), the TerraSAR-X signal was more sensitive to soil roughness at a high incidence angle (50°) than at a low incidence angle (25°).The high spatial resolution of the TerraSAR-X data (1 m) enabled the soil composition and slaking crust to be analyzed at the within-plot scale based on the radar signal. The two loamy-soil categories that composed our training plots did not differ sufficiently in their percentages of sand and clay to be discriminated by the X-band radar signal.However, the spatial distribution of slaking crust could be detected when soil moisture variation is observed between soil crusted and soil without crust. Indeed, areas covered by slaking crust could have greater soil moisture and consequently a greater backscattering signal than soils without crust.     

Prediction of soil erodibility factor for Peninsular Malaysia soil series using ANN

Soil erodibility factor (susceptibility of soil to be lost to erosion) is one of the components of the universal soil loss equation. This study presents an artificial neural network (ANN) model using 74 soil series provided by the Department of Agriculture, Malaysia. The ANN model produces acceptable results: the K values for 74 soil series of Peninsular Malaysia give much better information to engineers in determining the soil loss and sediment yield for a given development area.     

Comparison of different soil dielectric models for microwave soil moisture retrievals

ABSTRACT

Soil dielectric model is an essential part of the microwave soil moisture retrieval process. This study compared the performance of four widely used dielectric models, the Wang-Schmugge model (WS), Dobson model, generalized refractive mixing dielectric model (GRMDM), and multi-relaxation generalized refractive mixing dielectric model (MRGRMDM), and investigated the effects of the uncertainties of each model on soil moisture retrievals. Furthermore, the simulated soil dielectric constants were evaluated by measured dielectric data at the P/L/C/X bands. The results showed that the uncertainties induced in soil moisture retrievals by an alternative dielectric model exceeded 0.09 m³ m^?3 in the worst case. The Dobson model is sensitive to the sand content. WS, GRMDM, and MRGRMDM model are sensitive to the clay content. The measured dielectric data further verified that the applicability of each dielectric model depends on the soil texture type and soil moisture condition. Compared with Dobson model, WS showed better performance at dry soil. GRMDM and MRGRMDM provided better results under lower clay content soil. Especially, MRGRMDM has better simulation accuracy than GRMDM in the low-frequency range (< 1 GHz).     

Prediction of soil properties by digital terrain modelling

We investigated two approaches for large-scale analysis and prediction of the spatial distribution of soil properties in an agricultural landscape in the Canadian prairies. The first approach was based on the implementation of nine types of digital terrain models (DTMs) and regression analysis of soil and topographic data. The second approach used a concept of accumulation, transit, and dissipation zones of the landsurface. Soil properties were soil moisture, residual phosphorus, solum thickness, depth to calcium carbonate, and organic carbon content. The dependence of soil properties on topography was supported by correlations for the upper soil layer. However, topographic control of soil moisture and residual phosphorus decreased with depth. Also, correlation coefficients and regression equations describing topographic control of soil moisture and residual phosphorus differed among seasons. This imposes limitations on regression-based predictions of the spatial distribution of soil properties. The prediction of soil property distribution with the concept of accumulation, transit and dissipation zones can be more successful and appropriate than the prediction based on linear regression. The variability in relationships between soil and topographic characteristics with depth may stem from spatial variability in the rate of decline of hydraulic conductivity with depth. Temporal variability in soil–topography relationships occurs because soil properties result from interactions of a variety of pedogenetic factors and processes marked by different temporal variability. In soil studies with digital terrain modelling, there is a need to take into account four types of variability in relations between soil and relief: regional, temporal, depth, and scale.     

Spatially discontinuous ionization phenomenon in inhomogeneous soil

By using X-ray film imaging technology,a phenomenon of discontinuous ionization was observed in the inhomogeneous soil around the grounding electrode on which a surge voltage was applied.A simplified two-phase solid-gas model was built to study the electric field distribution in the soil to explain the discontinuous ionization phenomenon.Analysis showed the differences of the dielectric properties,the shapes and sizes of soil particles can cause discontinuous ionization in the soil.