Cotton lint yield variability in a heterogeneous soil at a landscape scale

Landscape variability associated with topographic features affects the spatial pattern of soil water and N redistribution, and thus N uptake and crop yield. A landscape-scale study was conducted in a center pivot irrigated field on the southern High Plains of Texas in 1999 to assess soil water, soil NO₃-N, cotton (Gossypium hirsutum L.) lint yield, and N uptake variability in the landscape, and to determine the spatial correlation between these landscape variables using a state-space approach. The treatments were irrigation at 50 and 75% cotton potential evapotranspiration (ET). Neutron access tubes were placed at a 15-m interval along a 710 m (50% ET) and 820 m (75% ET) transect across the field. Soil NO₃-N in early spring was autocorrelated at a distance varying between 60 and 80 m. Measured soil volumetric water content (WC), total N uptake, and lint yield were generally higher on lower landscape positions. Cotton lint yield was significantly correlated to soil WC (r=0.76), soil NO₃-N (r=0.35), and site elevation (r=−0.54). Differences of site elevation between local neighboring points explained the soil water, NO₃-N and lint yield variability at the micro-scale level in the landscape. Soil WC, cotton lint yield, N uptake, and clay content were crosscorrelated with site elevation across a lag distance of ±30–40 m. The state-space analysis showed that cotton lint yield was positively weighted on soil WC availability and negatively weighted on site elevation. Cotton lint yield state-space models give insights on the association of soil physical and chemical properties, lint yield, and landscape processes, and have the potential to improve water and N management at the landscape-scale.     

Tillage effects on soil hydraulic properties in space and time: State of the science

Soil tillage practices can affect soil hydraulic properties and processes dynamically in space and time with consequent and coupled effects on chemical movement and plant growth. This literature review addresses the quantitative effects of soil tillage and associated management (e.g., crop residues) on the temporal and spatial variability of soil hydraulic properties. Our review includes incidental management effects, such as soil compaction, and natural sources of variability, such as topography. Despite limited research on space–time predictions, many studies have addressed management effects on soil hydraulic properties and processes relevant to improved understanding of the sources of variability and their interactions in space and time. Whether examined explicitly or implicitly, the literature includes studies of interactions between treatments, such as tillage and residue management. No-tillage (NT) treatments have been compared with various tillage practices under a range of conditions with mixed results. The trend, if any, is for NT to increase macropore connectivity while generating inconsistent responses in total porosity and soil bulk density compared with conventional tillage practices. This corresponds to a general increase in ponded or near-zero tension infiltration rates and saturated hydraulic conductivities. Similarly, controlled equipment traffic may have significant effects on soil compaction and related hydraulic properties on some soils, but on others, landscape and temporal variability overwhelm wheel-track effects. Spatial and temporal variability often overshadows specific management effects, and several authors have recognized this in their analyses and interpretations. Differences in temporal variability depend on spatial locations between rows, within fields at different landscape positions, and between sites with different climates and dominant soil types. Most tillage practices have pronounced effects on soil hydraulic properties immediately following tillage application, but these effects can diminish rapidly. Long-term effects on the order of a decade or more can appear less pronounced and are sometimes impossible to distinguish from natural and unaccounted management-induced variability. New standards for experimental classification are essential for isolating and subsequently generalizing space–time responses. Accordingly, enhanced methods of field measurement and data collection combined with explicit spatio-temporal modeling and parameter estimation should provide quantitative predictions of soil hydraulic behavior due to tillage and related agricultural management.     

新疆膜下滴灌棉田生育期地温变化规律

覆膜条件下地温将发生改变,为研究其变化规律,2008和2009年在新疆库尔勒市开展了棉花膜下滴灌田间试验,设置了不同灌溉处理和地表覆盖情况的试验小区,对土壤水热状况进行了监测和对比,结果表明：气象条件、土壤水分、地膜和棉株覆盖等因素综合影响棉花生育期地温分布规律,出苗期15 cm深度处膜下地温高于膜间1.6℃,蕾期和花铃期膜间地温逐渐超过膜下,吐絮期二者又趋于相等;土壤水分和温度存在耦合作用,土壤含水率高则热容量大,相应的温度变化幅度小,但在相同的含水率下,覆膜处理平均地温高于无膜处理。研究表明,膜下滴灌有效起到保温保墒作用,克服土壤高地温低含水率或低地温高含水率的矛盾,可为作物生长创造较好的土壤水热条件。     

不同土壤水势与氮素营养对杂交水稻生理特性和产量的影响

以超级杂交水稻“两优培九”为试验材料,研究了不同土壤水势和氮素营养对其生理特性和产量及氮肥利用率的影响。结果表明, 1）同一土壤水势下,植株地上部分干重与总干重随氮肥水平的提高而提高,而根冠比则降低。2）在同一氮肥水平下,叶片净光合速率、叶绿素a和叶绿素b及其总含量、SPAD值及叶片水势随着土壤水势的降低而降低,而叶绿素a/b、丙二醛的含量和过氧化物酶的活性随之而增加;同一土壤水势下,叶绿素a和叶绿素b及其总含量、SPAD值均随氮肥水平的提高而提高,而叶片水势、叶绿素a/b和丙二醛的含量随之降低。3）在同一氮肥水平下,水稻产量随土壤水势的降低而降低;土壤轻度干旱时,水稻产量高低顺序为高氮中氮低氮;而当土壤水分充足或土壤重度干旱时,则表现为中氮高氮低氮。随着土壤水势的降低,中、高氮处理的氮肥农学利用率降低。试验结果还表明,225 kg/hm2施氮水平在0 kPa土壤水势下有明显的增产效果,过度增施氮肥并不利于水稻增产与氮肥利用率的提高。     

Tentative assessment of soil survey approaches to the characterization and interpretation of air-water properties of soils

Procedures used by soil survey organizations in characterizing and interpreting the air—water regimes of soils in France, Germany, The Netherlands, England and Wales, the United States and Canada are summarized and compared. The strengths and weaknesses of the systems are discussed, and research is suggested to resolve problems and to improve the basis of interpretations. The importance of sound field estimates supported regularly by reliable measurements is emphasized. Field estimates are essential in view of the dynamic nature and the spatial variability of some soil physical properties related to the air—water regimes. Research needs include continued development of improved methods of measuring air—water properties of soils, development of improved guidelines for estimating these properties from soil morphology, and identification of the relevant soil properties that can be estimated reliably. Interdisciplinary research is required to integrate expertise in hydrology, soil physics, agronomy and pedology with a view to improving the characterization and interpretation of air—water properties of soils.     

An analysis of the potential of precision farming in Northern Europe

Abstract. Precision farming is the process of adjusting husbandry practices within a field according to measured spatial variability. In this review, we explore the prospects for precision farming using the principles that underly conventional soil management and agronomy. The cost-effectiveness of precision farming is determined by the cost of defining zones within fields, the stability of zones through time, the difference in treatment between zones in terms of cost, and the responsiveness of the crop in terms of yield and quality to changes in treatment. Cost-effective precision farming is most likely where prior knowledge indicates large heterogeneity and where treatment zones can be predicted, for example from soil type or field history. Soil related factors are likely to provide the main basis for precision farming because they tend to be stable through time and influence crop performance. In particular, soil mapping may usefully indicate the moisture available for crop growth, organic matter maps may be utilized for precision application of fertilizers and soil acting herbicides, and variation in soil pH can be mapped and used as a basis for variable lime application. However, comprehensive nutrient mapping is less likely to be economic with existing techniques of chemical analysis. The value of yield mapping lies in identifying zones which are sufficiently stable to be of use in determining future practices. Maps of grain quality and nutrient content would significantly augment the value of yield maps in guiding marketing decisions and future agronomy. Interactions between soil differences and seasonal weather are large, so yield maps show considerable differences from season to season. Interpretation of such maps needs to follow a careful, informed, analytical process. Extensive and thorough field experimentation by crop scientists over many years has shown that yield variation arises as a result of a large and complex range of factors. It is highly improbable that simple explanations will be appropriate for much in-field yield variation. However, the capacity to sense yield variability within fields as opposed to between fields, where there are many confounding differences, provides an opportunity for the industry to improve its understanding of soil-based effects on crop performance. This should support its decision taking, whether through precision farming or through field-by-field agronomy. The main obstacle to the adoption of precision farming is the lack of appropriate sensors. Optimal sensor configurations that will measure the specific needs identified by end-users need to be developed. The conclusions reached in this paper probably apply to farming throughout northern Europe.     

Modeling spatial variation in productivity due to tillage and water erosion

The advent of precision farming practices has heightened interest in managing field variability to optimize profitability. The large variation in yields across many producer fields demonstrated by yield–monitor–equipped combines has generated concern about management-induced causes of spatial variation in soil productivity. Soil translocation from erosion processes may result in variation in soil properties across field landscape positions that produce long-term changes in soil productivity. The objective of this study was to examine the relationships between soil redistribution caused by tillage and water erosion and the resulting spatial variability of soil productivity in a soil catena in eastern South Dakota. An empirical model developed to estimate tillage erosion was used to evaluate changes expected in the soil profile over a 50-year period on a typical toposequence found in eastern South Dakota and western Minnesota. Changes in the soil profile due to water erosion over a 50-year period were evaluated using the WEPP hillslope model. The tillage erosion model and the WEPP hillslope model were run concurrently for a 50-year period to evaluate the combined effect of the two processes. The resulting changes in soil properties of the root zone were evaluated for changes in productivity using a productivity index model. Tillage erosion resulted in soil loss in the shoulder position, while soil loss from water erosion occurred primarily in the mid to lower backslope position. The decline in soil productivity was greater when both processes were combined compared to either process acting alone. Water erosion contributed to nearly all the decline in soil productivity in the backslope position when both tillage and water erosion processes were combined. The net effect of soil translocation from the combined effects of tillage and water erosion is an increase in spatial variability of crop yields and a likely decline in overall soil productivity.     

基于水系改进的高分辨率DEM和GEOWEPP的流域产沙量估算及其空间尺度效应研究

基于水系改进的高分辨率DEM和GEOWEPP,从坡面、子流域和流域3种空间尺度对五桥河流域产沙量进行了估算。结果表明,从不同的空间尺度进行考察,流域的水土流失特征存在较大的差异。从坡面尺度到子流域尺度和流域尺度,研究区114.6 km2面积上的年产沙总量从3.79×105t减少至1.25×105t和0.84×105t,单位面积年产沙量从33.09 t hm-2减少至10.94 t hm-2和7.29 t hm-2,年均泥沙输移比从1.000减小至0.331和0.220。将GIS与GEOWEPP结合,既能反映流域输出终端的泥沙量,又可以刻画流域内部土壤侵蚀的强度和空间分布,能为流域水土保持措施布置提供更为科学的依据。     

Spatial heterogeneity of a microbial community in a sandy soil ecosystem

A fieldwork was carried out in Caesarea sand dunes, Israel, to determine the influence of fine-scale landscape-patch abiotic-factor heterogeneity on microbial activity in a Mediterranean region. Soil organisms in terrestrial systems are unevenly distributed in time and space, and are often aggregated. Spatio-temporal patchiness in the soil environment is thought to be crucial for the maintenance of soil biodiversity, providing diverse microhabitats that are tightly interwoven with resource partitioning. Determination of a ‘scale unit’ to help understand ecological processes has become one of the important and most debatable problems in recent years. To better understand the distribution of soil microbial communities at multiple spatial scales, a survey was conducted to examine the spatial organization of the community structure in two sandy soil ecosystems. One-hundred forty-four soil samples were collected from two patches 4000 m apart from each other. Basal respiration (CO₂ evolution without the addition of any external substrate), microbial biomass, functional diversity, and community-level physiological profile (CLPP) in soil were measured with a MicroResp? system. Soil abiotic analysis was performed by soil standard analytical methods. The results demonstrated that bacterial distributions can be highly structured, even within a habitat that appears to be relatively homogeneous at the plot and field scale. Different subsets of the microbial community were distributed differently across the plot. This is due to spatial heterogeneity associated with soil physical, chemical, and biological properties. Although spatial variability in the distribution of soil microorganisms is generally regarded as random, this variability often has a predictable spatial structure. This study provided evidence that a spatially explicit approach to soil ecology can enable the identification of factors that drive the spatial heterogeneity of populations and activities of soil organisms, at scales ranging from meters to hundreds of meters. Furthermore, there is increasing evidence that spatial soil ecology can yield new insights into the factors that maintain and regulate soil biodiversity, as well as on how the spatial distribution of soil organisms influences plant growth and plant community structure.     

Soil landscape evolution due to soil redistribution by tillage: a new conceptual model of soil catena evolution in agricultural landscapes

This paper focuses on analysing tillage as a mechanism for the transformation of soil spatial variability, soil morphology, superficial soil properties and development of soil–landscape relationships in agricultural lands. A new theoretical two-dimensional model of soil catena evolution due to soil redistribution by tillage is presented. Soil profile truncation occurs through loss of soil mass on convexities and in the upper areas of the cultivated hillslopes; while the opposite effect takes place in concavities and the lower areas of the field where the original soil profile becomes buried. At sectors of rectilinear morphology in the hillslope (backslope positions), a null balance of soil translocation takes place, independent of the slope gradient and of the rate of downslope soil translocation. As a result, in those backslope areas, a substitution of soil material in the surface horizon with material coming from upslope areas takes place. This substituted material can produce an inversion of soil horizons in the original soil profile and sometimes, the formation of “false truncated soil”. In the Skogstad agricultural field (Cyrus, MN) spatial patterns of soil properties (soil calcium carbonate content) in the surface soil horizons and soil morphology along several slope transects were analyzed. These spatial patterns are compared with those estimated for soil redistribution (areas of erosion and deposition) due to tillage using the Soil Redistribution by Tillage (SORET) model and water erosion using the models Water Erosion Prediction Project (WEPP) and Universal Soil Loss Equation (Usle2D). Results show that tillage was the predominant process of soil redistribution in the studied agricultural field. Finally, some practical implications of the proposed model of soil landscape modification by tillage are discussed. Nomographs to calculated the intensity of the expansion process of the eroded soil units by tillage are proposed for three different patterns of tillage.     

Spatial covariation of Azotobacter abundance and soil properties: A case study using the wavelet transform

The soil microflora is very heterogeneous in its spatial distribution. The origins of this heterogeneity and its significance for soil function are not well understood. A problem for understanding spatial variation better is the assumption of statistical stationarity that is made in most of the statistical methods used to assess it. These assumptions are made explicit in geostatistical methods that have been increasingly used by soil biologists in recent years. Geostatistical methods are powerful, particularly for local prediction, but they require the assumption that the variability of a property of interest is spatially uniform, which is not always plausible given what is known about the complexity of the soil microflora and the soil environment. We have used the wavelet transform, a relatively new innovation in mathematical analysis, to investigate the spatial variation of abundance of Azotobacter in the soil of a typical agricultural landscape. The wavelet transform entails no assumptions of stationarity and is well suited to the analysis of variables that show intermittent or transient features at different spatial scales.In this study, we computed cross-variograms of Azotobacter abundance with the pH, water content and loss on ignition of the soil. These revealed scale-dependent covariation in all cases. The wavelet transform also showed that the correlation of Azotobacter abundance with all three soil properties depended on spatial scale, the correlation generally increased with spatial scale and was only significantly different from zero at some scales. However, the wavelet analysis also allowed us to show how the correlation changed across the landscape. For example, at one scale Azotobacter abundance was strongly correlated with pH in part of the transect, and not with soil water content, but this was reversed elsewhere on the transect.The results show how scale-dependent variation of potentially limiting environmental factors can induce a complex spatial pattern of abundance in a soil organism. The geostatistical methods that we used here make assumptions that are not consistent with the spatial changes in the covariation of these properties that our wavelet analysis has shown. This suggests that the wavelet transform is a powerful tool for future investigation of the spatial structure and function of soil biota.     

Changes in Agricultural Land Use Affecting Future Soil Redistribution Patterns: A Case Study in Southern Tuscany (Italy)

Land‐use changes (LUCs) can be defined as the result of the direct action of the stakeholders in a particular area and natural or human driving forces. LUCs can influence various processes within the landscape and can have an impact on landscape functions. An analysis of the impact of LUCs on landscape processes can help to focus future rural policies. LUCs in Mediterranean areas particularly affect landscape functions because of their agro‐pedoclimatical characteristics. The aims of this work are as follows: (i) to characterise LUCs in the last 11 years in a typical Mediterranean area, the Trasubbie river basin (southern Tuscany, Italy); (ii) to extrapolate these changes and create spatially explicit LUC scenarios for the near future; and (iii) to simulate how and where the predicted LUCs may affect soil redistribution. We carried out an analysis of LUCs within the study area and used the trends to propose alternative scenarios for 2013. For these years, we spatially allocated land use (using the Conversions of Land Use and its Effects model) and used a landscape process model (landscape process modelling at multi‐dimensions and scales) to assess soil redistribution patterns. Land use in the study area changed almost linearly between 1996 and 2007, with cereals and annual fodder crops decreasing, and vineyards, perennial pastures and land abandonment increasing. Our LUC scenario extrapolates these dynamics to make predictions for 2013. A comparison of LAPSUS results between LUC and baseline scenarios for 2013 showed an increase in terms of net soil loss and total erosion, and a decrease in terms of sediment delivery ratio. Copyright © 2013 John Wiley & Sons, Ltd.     

Simulation of the redistribution of soil by tillage on complex topographies

Tillage redistributes soil and contributes significantly to the within‐field soil variation, especially on topographically complex terrain. Although the basic principles of the redistribution are well understood, models for simulating the redistribution are poor predictors. This paper presents a modelling structure that allows a simulation of the redistribution of soil constituents on complex topographies for various tillage implements. The model simulates the redistribution of soil constituents by convoluting the probability distribution of the tillage displacement with the spatial distribution of the soil constituents. The probability distributions in two dimensions are derived from a series of tillage experiments conducted with a mouldboard plough at various positions in the landscape. Furthermore, the effects of topography and tillage direction on the probability distributions were characterized and implemented in the model. A first application showed that the direction of tillage significantly affects the long‐term redistribution of soil constituents. The inclusion of other implements in the model was explored, and we found that data in the literature could be used for simulating the long‐term effects of tillage.     

Regional‐scale characterization of the geomorphic control of the spatial distribution of soil organic carbon in cropland

The heterogeneity of the spatial distribution of soil organic carbon (SOC) at the landscape scale is generally not considered in regional or national SOC dynamics models. In cropland this heterogeneity is controlled largely by topography, which influences the distribution of water, energy and sediments, and thus the SOC dynamics. Sediment redistribution rates have increased strongly since the mechanization of agriculture. The over‐simplification of landscape processes in regional models of C dynamics may add to the uncertainty in C balances. Therefore, a better characterization of the importance of landscape‐scale effects on the SOC distribution throughout a region is needed. This study characterized the relative importance of geomorphology in the SOC horizontal and vertical variability across croplands in the Belgian loess belt region. A large legacy dataset of soil horizons was exploited together with 147 recently sampled profiles. Mean SOC depth profiles for different soil types were compared. Various topographic attributes were computed from a digital elevation model, and their influence on SOC was quantified through simple linear models. Finally, SOC content was mapped at three depth layers through multiple linear models, and results were cross‐validated. The legacy dataset allowed identification of significant differences in the mean SOC profile according to texture, drainage or profile development classes. A clear relationship between SOC content and topographic attributes was demonstrated, but only for the recently sampled profiles. This may be explained by a substantial error in the location of the profiles of the legacy dataset. This study thus shows evidence that the major control of the vertical distribution of SOC is related to topography in a region where observed heterogeneities for other commonly involved factors are limited. However, the large amount of unexplained variability still limits the usefulness of the spatial prediction of SOC content, and suggests the importance of additional influencing factors.     

Lateral flow in loamy to sandy Kandiudults of the Upper Coastal Plain of Georgia (USA)

Interest in site-specific agronomic management in intensively cropped regions necessitates characterization of subsurface water movement for efficient water management (irrigation timing) and control of off-site agrichemical movement. Soils formed in fluvial sediments in portions of the Upper Coastal Plain of Georgia (USA) are extensively used for peanut, cotton, and corn production. Certain proximate soils in this region possess contrasting subsoil properties, and it was hypothesized that these differences would have major effects on water redistribution across the landscape. This could be important in irrigation management, where soils possessing increased impedance to vertical flow could require decreased irrigation as opposed to soils without vertical flow restrictions. At a site near Plains, GA. (USA), hydraulic properties of soils with differences in overlying sand thickness and contrasting argillic horizon textures (sandy vs. loamy) were evaluated. The soils were predominantly in loamy and sandy families of Typic, Arenic, and Grossarenic Kandiudults. Laboratory measurements, field monitoring of matric potentials under simulated and natural rainfall, and modeling (VS2DT) were utilized to evaluate soil hydraulic properties. Reduction in vertical K_s occurred in horizons containing higher clay (argillic horizon). Changes in tension and build ups in hydraulic gradients associated with infiltration and redistribution events existed above and within horizons with low K_s. Evidence suggested there was less groundwater recharge occurring in the loamy than in the sandy pedons, suggesting more pronounced lateral flow occurred in the loamier soils. Model simulations of water movement across a slightly sloping (1%) simulated landscape indicated lateral gradients of flow existed within the solum of these soils. Analyses of tracer (Br) movement suggested a very slight lateral redistribution occurred within a relatively short monitoring period within the sandy pedon's Bt1 horizon, and the Bt2 and Bt3 horizons of the loamy pedon. Evidence suggested both loamy and sandy argillic horizons slightly, but not overwhelmingly, induced lateral flow on these landscapes.     

Spatial variability of glyphosate mineralization and soil microbial characteristics in two Norwegian sandy loam soils as affected by surface topographical features

The aim of this study was to investigate the possible influence of surface topographical features on the spatial variability of glyphosate degradation and some microbial characteristics in sandy loam soil. Soil samples were taken from the ploughed layer across an agricultural field after seedbed preparation for grain (Grue site), and down to 1 m depth under a ridge tilled field (Målselv site), both sites having similar soil textural characteristics (sandy loam soil). Laboratory experiments were performed looking at glyphosate mineralization and soil microbial activity at the Grue site, as well as microbial biomass, activity and substrate utilization patterns at the Målselv site. Microbial biomass and activity decreased, and substrate utilization patterns changed with increasing soil depth, reflecting naturally occurring changes in quantity and quality of soil organic carbon. Further, our results show that considerable spatial heterogeneity in the degradation rate of glyphosate and general carbon utilization exists even across small areas within a single agricultural field. This horizontal variability was observed over several spatial scales, and could not be clearly explained. It evidently arose from differences in environmental factors affecting microbial activity and growth, and topographical features controlling redistribution of water and matter flow patterns were correlated to the investigated soil microbial variables.     

复杂景观区土壤有机质预测模型的尺度效应

为研究复杂景观区土壤有机质预测模型的尺度效应,探讨不同空间尺度数据综合利用的问题,本文运用回归Kriging方法对河南省登封市土壤有机质进行预测,分析了不同空间尺度数据在建模过程中的作用和影响.结果表明:土壤有机质关于高程因子的趋势属于宏观趋势,以大尺度数据拟合该趋势值效果最优;小尺度数据不适合用于拟合土壤有机质的趋势值,但揭示了小尺度残差值的空间变异细节,增强了大尺度残差值的空间结构性,能够有效提高土壤有机质预测精度.因此,景观复杂区土壤有机质预测中,应基于大尺度数据模拟趋势值,大尺度数据和小尺度数据相结合拟合残差值的空间变异函数以预测残差值,最后趋势值加上残差值得到土壤有机质预测值.     

Scaling analysis of soil water storage with missing measurements using the second‐generation continuous wavelet transform

Information on the spatial variability of soil water storage (SWS) at different scales is important for understanding various hydrological, ecological and biogeochemical processes in the landscape. However, various obstructions such as roads or water bodies may result in missing measurements and create an irregular spatial series. The wavelet transform can quantify spatial variability at different scales and locations but is restricted to regular measurements. The objective of this study was to analyse the spatial variability of SWS with missing measurements using the second‐generation continuous wavelet transform (SGCWT). Soil water content (converted to SWS by multiplying with depth) was measured with a neutron probe and time‐domain reflectrometry along a transect of 128 points. Because there were missing measurements, I used SGCWT to partition the total variation into different scales and locations. Whilst there were some small‐scale variations (< 20 m) along the transect, the medium scale variations (20–70 m with an average of about 30–45 m) were mainly concentrated within the depressions along the transect. The strongest variations were observed at around 90–110 m scale, representing the variations resulting from alternating knolls and depressions. Similar spatial patterns at different scales were observed during different seasons, indicating temporal stability in the spatial pattern of SWS. Among the controlling factors, the wavelet spectra of relative elevation (RE) and organic carbon (OC) were very similar to that of SWS. The wavelet covariance was also large between SWS and RE and OC at all seasons. As the OC reflects the long‐term history of water availability and might be controlled by topographic setting or elevation, it can be concluded that elevation is an important controlling factor of SWS irrespective of seasons in this type of landscape. The SGCWT provides a new way of analysing the spatial variability of regularly measured soil properties or those with missing measurements.     

Modelling variability in N2O emissions from fertilized agricultural fields

Estimates of long-term landscape-scale N₂O emissions for greenhouse gas inventories are complicated by large temporal and spatial variability. Much of this variability is likely caused by topographic effects on surface and subsurface water flows. We hypothesized that this variability could be explained as degassing events during anaerobic soil conditions and during transitions from anaerobic to aerobic soil conditions as controlled by precipitation and subsequent water redistribution in complex landscapes. We simulated degassing events in the ecosystem model ecosys run in three-dimensional mode to simulate a fertilized agricultural field with topographic variation derived from a digital terrain map. N₂O emissions modelled from two areas within the field that had received 15.5 and 9.9 g N m⁻² as urea in May 1998 were compared with those measured by micrometeorological flux towers during June and July 1998. Modelled N₂O emissions during 1998 accounted for 2.3 and 2.0% of urea N applied at 15.5 and 9.9 g N m⁻², respectively. Degassing events in the model coincided with a key N₂O emission event measured in the field during several days after a rainfall in mid-June. During this event, modelled and measured surface fluxes rose rapidly to exceed 1 mg N m⁻² h⁻¹ for 2-3 d before declining. Emissions modelled concurrently at different topographic positions within the landscape during the emission event had coefficients of variation that varied over time between 30 and 180%. Much of the spatial variability in modelled emissions was attributed to temporal differences in the progression of emission events at different landscape positions caused by lateral water movement. The magnitude of temporal and spatial variability in N₂O emissions suggests that aggregation of flux measurements to regional scales should be based upon sub-daily measurements at representative landscape positions, rather than upon less frequent measurements at individual sites as currently done. The use of three-dimensional ecosystem models with input from digital terrain maps may provide a means for such aggregation to be conducted.     

Application of Chernobyl-derived Cs for the assessment of soil redistribution within a cultivated field

Vast areas of Europe were contaminated by the Chernobyl-derived ¹³⁷Cs in April–May 1986. This paper reports a detailed study of the post-fallout ¹³⁷Cs redistribution within a 1 ha field located in the Chasovenkov Verh catchment in the northern part of the Middle-Russian upland. Particular attention was paid to the study of reference inventories. It is shown that the random spatial variability of ¹³⁷Cs is similar within undisturbed and cultivated parts of a flat interfluve. Systematic spatial variability is not essential for a relatively short (200 m) topographical unit with simple relief. The analysis of a soil redistribution pattern within the study field using the Chernobyl ¹³⁷Cs technique demonstrates that it is possible to identify areas of soil loss/gain. This pattern does not reflect soil redistribution for the whole field, because these have been only 12 years since the Chernobyl accident. Net erosion rates based on ¹³⁷Cs method were comparable to soil losses directly measured at the study field.