Analysing soil variation in two dimensions with the discrete wavelet transform

Complex spatial variation in soil can be analysed by wavelets into contributions at several scales or resolutions. The first applications were to data recorded at regular intervals in one dimension, i.e. on transects. The theory extends readily to two dimensions, but the application to small sets of gridded data such as one is likely to have from a soil survey requires special adaptation. This paper describes the extension of wavelet theory to two dimensions. The adaptation of the wavelet filters near the limits of a region that was successful in one dimension proved unsuitable in two dimensions. We therefore had to pad the data out symmetrically beyond the limits to minimize edge effects. With the above modifications and Daubechies's wavelet with two vanishing moments the analysis is applied to soil thickness, slope gradient, and direct solar beam radiation at the land surface recorded at 100‐m intervals on a 60 × 101 square grid in south‐west England. The analysis revealed contributions to the variance at several scales and for different directions and correlations between the variables that were not evident in maps of the original data. In particular, it showed how the thickness of the soil increasingly matches the geological structure with increasing dilation of the wavelet, this relationship being local to the strongly aligned outcrops. The analysis reveals a similar pattern in slope gradient, and a negative correlation with soil thickness, most clearly evident at the coarser scales. The solar beam radiation integrates slope gradient and azimuth, and the analysis emphasizes the relations with topography at the various spatial scales and reveals additional effects of aspect on soil thickness.     

基于离散小波分解与重构的多源土壤含水量数据融合方法与评估

为提高土壤含水量格点数据的区域适用性、准确性，该研究提出了基于离散小波多尺度分解与重构的多源土壤含水量数据融合方法，利用2016-2018年6-9月ESA-CCI、SMAP、ERA5-Land数据集以及地面站点观测的土壤含水量数据，在以黄河流域为主体的主要农业气候区开展了融合方法可行性和适用性研究。结果表明，融合方法能有效捕获融合数据源的多尺度特征信息，通过多源多尺度逐层特征信息权重融合与重构，能有效改进单一数据源在不同农业气候区域的适用性、时空结构和波动特征的准确性。融合结果总体评估的均方根误差、偏差(Bias)和相关系数(r)分别为0.053 m³/m³、0.001 m³/m³和0.721，时空分解评估的综合表现均优于单一融合数据源的评估指标，多尺度时空波动频谱结构特征与观测时空序列更吻合，特别在25 d时间尺度以内时空波动吻合度改进最为明显。该研究获得了较理想的区域土壤含水量改进预期，可为区域生态环境监测、农业可持续发展、水土保持、防灾减灾等科学研究和业务应用提供可行有效的方法参考。     

Spatial analysis of categorical soil variables with the wavelet transform

This paper describes a wavelet transform for the analysis of categorical (multistate) soil variables, i.e. ones (such as profile classes) that have two or more discrete states. The states are transformed to a continuous variable by a mapping which is optimized by scale and location to highlight local variation. The method is illustrated with data from a transect across a gilgai landscape in Australia. A categorical variable on relief, with three states, was recorded from the sample sites, from which soil cores had also been collected and analysed. The wavelet analysis showed a transient feature of the variation at scales up to 32 m. There was an interval where the characteristic alternation of depressions with the level plain was interrupted. The variation at scale 64 m appeared to be non-stationary. The relief was more variable on one side of a change point than it was on the other. This complex variation of relief was matched by that of the electrical conductivity of the soil, most strongly at the 64-m scale. The periodicity of conductivity, and the strength of its correlation with relief, were also different either side of the change point identified in the analysis of relief alone. Conductivity also showed similar transient features to relief. Evidently the wavelet transform can be used to elucidate the variation of categorical soil variables. The information from such an analysis is likely to be useful for planning surveys of the soil to measure continuous variables by sampling and laboratory analysis.     

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.     

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.     

Scale‐ and location‐dependent correlation of nitrous oxide emissions with soil properties: an analysis using wavelets

This paper shows how the wavelet transform can be used to analyse the complex spatial covariation of the rate of nitrous oxide (N₂O) emissions from the soil with soil properties that are expected to control the evolution of N₂O. We use data on N₂O emission rates from soil cores collected at 4‐m intervals on a 1024‐m transect across arable land at Silsoe in England. Various soil properties, particularly those expected to influence N₂O production in the soil, were also determined on these cores. We used the adapted maximal overlap discrete wavelet transform (AMODWT) coefficients for the N₂O emissions and soil variables to compute their wavelet covariances and correlations. These showed that, over the transect as a whole, some soil properties were significantly correlated with N₂O emissions at fine spatial scales (soil carbon content), others at intermediate scales (soil water content) and others at coarse spatial scales (soil pH). Ammonium did not appear to be correlated with N₂O emissions at any scale, suggesting that nitrification was not a significant source of N₂O from these soils in the conditions that pertained at sampling. We used a procedure to detect changes in the wavelet correlations at several spatial scales. This showed that certain soil properties were correlated with N₂O emissions only under certain conditions of topography or parent material. This is not unexpected given that N₂O is generated by biological processes in the soil, so the rate of emission may be subject to one limiting factor in one environment and a different factor elsewhere. Such changes in the relationship between variables from one part of the landscape to another is not consistent with the geostatistical assumption that our data are realizations of coregionalized random variables.     

Identifying scale specific controls of soil water storage in a hummocky landscape using wavelet coherency

High spatio-temporal variability of soil water is contributed from different ecohydrological and soil processes operating in different intensities at different scales. Traditional Pearson correlation analysis only examines linear correlation at the measurement scale. In this study, the correlation between soil water storage and its controlling factors was examined at different scales and locations in a hummocky landscape using wavelet coherency. Time domain reflectometry and neutron probe were used to measure soil water storage up to 1.4 m depth along a transect of 576 m long established in a hummocky landscape at St. Denis National Wildlife Area, Saskatchewan, Canada. In spite of visual similarity of the spatial pattern of soil water storage and elevation, the value of Pearson correlation coefficient was very small. However, wavelet coherency identified strong scale- and location-specific correlations between soil water storage and elevation. The total area of significant correlations as calculated from the total number of significant coherencies at different scales and locations was higher between soil water storage and elevation than between soil water storage and any other factors, which indicated a dominant control from elevation on soil water storage in the hummocky landscape. The largest area of significant correlation was observed at large scales (> 70 m), which can be attributed to the alternating knolls and depressions. The relationship between soil water storage and elevation at different scales was persistent at different times of the year or at different seasons with a slight reduction in the magnitude of correlation. The persistent relationship indicated the dominant control from elevation with slight change in the degree of the control. The scale-location specific correlation provides a complete picture on the controls of soil water storage, which was not possible with traditional correlation analysis.     

基于RF和连续小波变换的露天煤矿土壤锌含量高光谱遥感反演

露天煤矿周边存在潜在重金属污染隐患,快速获取土壤重金属空间分布是土壤污染评价、土地复垦与修复的前提。传统调查方法费时费力且易造成对环境的二次污染,高光谱遥感为土壤重金属反演提供了新的视角。该研究以某露天煤矿土壤锌（Zn）含量为研究对象,采集了111个原位表层（0～20 cm）土壤样品及反射光谱;对样品反射光谱进行Savitsky-Golay（SG）平滑、连续统去除（Continuum Removal,CR）和连续小波变换（Continuous Wavelet Transform,CWT）以降噪和增强;利用Boruta算法确定特征波段;采用偏最小二乘回归（Partial Least Squares Regression,PLSR）和随机森林（Random Forest,RF）构建土壤Zn含量反演模型,使用留一交叉验证评估反演模型精度以确定最优反演模型;基于最优反演模型,利用空间插值方法绘制土壤Zn含量空间分布图。结果表明：1）CWT可有效降低光谱噪声,增强光谱响应。2）Boruta算法能消除光谱信息冗余,并能有效提取特征波段;特征波段的数目随CWT分解尺度和光谱测量条件变化。3）RF估算土壤Zn含量性能优于PLSR,且RF结合CWT具有较好的土壤Zn反演能力;最优野外原位光谱反演模型精度（建模集R2=0.92,验证集R2=0.54）低于实验室光谱反演模型（建模集R2=0.95,验证集R2=0.72）。4） 土壤Zn空间分布表现出显著的异质性,呈现高值集中于研究区西南部和东北部的特征。研究结果可为利用高光谱遥感开展露天矿区土壤重金属反演提供借鉴,为其他类似区域土壤污染评价、土地复垦与整治、土壤修复提供前提与依据。     

2022. 基于RF和连续小波变换的露天煤矿土壤锌含量高光谱遥感反演

研究长期施肥对玉米连作体系下采煤塌陷区复垦土壤肥力变化和玉米产量的影响,明确玉米产量提高的驱动因素和最佳施肥处理,可为该区域培肥土壤和耕地质量提升提供理论依据。该研究依托7 a（2014—2020年）复垦定位肥料试验基地,设置不施肥对照（CK）、氮磷钾平衡施肥（NPK）、单施有机肥（M）和有机肥配施无机肥（MNPK）4个处理,采集0～20 cm土层土壤样品,研究不同施肥处理对作物产量、土壤化学指标（包括有机质、全氮、有效磷、速效钾、有效铁锰铜锌含量）、土壤物理指标,即团聚体分布比例及其碳氮含量以及土壤生物指标,即与碳循环相关的土壤酶活性的影响。结果表明,施化肥及有机肥较CK均显著提高了玉米籽粒产量,且以M处理的增幅最大。M处理显著提高了土壤有机质、全氮、速效钾及有效锰含量,增幅分别为21.50%、12.50%、98.37%及20.19%;MNPK处理改善了土壤的基本性质,显著提高了大粒径团聚体（> 2 mm）中有机碳和全氮含量,增幅分别达68.68%和471.43%,但是显著降低了土壤有效铜和有效锌含量,降幅分别为16.67%和16.46%。而且施加有机肥后,加速了大团聚体（0.25～2 mm）的破碎,伴随着粉黏粒组分（< 0.053 mm）数量的增加。此外,NPK处理显著提高了β-葡萄糖苷酶活性,增幅为29.17%,但是显著降低了脲酶活性,降幅为29.79%,施有机肥（M和MNPK）显著提高了蔗糖酶、β-葡萄糖苷酶、脲酶和碱性磷酸酶活性,增幅分别为45.87%～73.39%、54.98%～60.73%、43.09%～80.32%和51.52%～54.97%。进一步通过主成分分析以及土壤肥力综合指数评价,表明单施有机肥是该复垦区域耕地质量提升和维持土地生产力较好的农田管理措施。结合冗余分析结果可知,β-葡萄糖苷酶是评价土壤肥力的敏感性指标,它对玉米籽粒产量和土壤有机质含量的贡献率高达72.40%。因此,在现有的农田管理条件下,单施有机肥主要通过增强β-葡萄糖苷酶活性进而促进复垦土壤肥力的形成,最终提高了作物产量,是维持该复垦区作物高产稳产和培育耕地质量的有效措施。

     

小波包-局部最相关算法提高土壤有机碳含量高光谱预测精度

高光谱遥感可以实现水稻土排水期有机碳含量的快速预测,但土壤反射率受多种噪声的影响,有机碳光谱信号探测受阻,预测模型性能低下,如何在去除噪声的同时最大限度地保持有机碳光谱信号十分重要。以原状新鲜水稻土为研究对象,采用Bior1.3小波系对反射光谱进行1~7层小波包变换,通过相关分析确定最大分解层;将原始反射率至最大分解层以内的各层光谱相关系数组成相关系数集,采用局部最相关算法(local correlation maximization,LCM)构造土壤有机碳最优光谱;最后基于最优光谱建立有机碳含量偏最小二乘预测模型并进行分析。结果显示:1)随着小波包分解层数的增加,土壤反射率与有机碳含量的相关性不断增强,到第6层达到最高,确定为小波包最大分解层;2)基于LCM构造的最优光谱比未去噪光谱平滑,比小波包去噪光谱保留了更多光谱细节;3)未去噪光谱、小波包去噪光谱和LCM最优光谱有机碳预测模型的验证决定系数分别为0.693、0.727和0.781,均方根误差为1.952、1.840和1.679 g/kg,残留预测偏差为1.85、1.97和2.17。小波包-局部最相关算法在去噪同时有效保持了土壤有机碳光谱信号,可提高水稻土有机碳含量高光谱预测精度。     

Changes in biological properties and antioxidant capacity of an agricultural soil amended with sewage sludge

The effects of applying sewage sludge (SS) to agricultural soil (at low rate of 22.5, LRS, and at high rate of 45 t ha^?1 dry basis, HRS) were monitored over a 120-d experimental period. Total organic carbon (TOC), water-soluble organic carbon (WSOC), alkali-soluble phenols, basal respiration, specific enzyme activity, dehydrogenase activity (DH-ase), metabolic potential (MP) and FDA-hydrolytic activity (FDA) were strongly increased by both rates of SS applications. In the SS amended soil, about 70% of the organic C added with the material remained at the end of the experiment. Basal respiration increased with increasing SS doses. The specific enzyme activity and the MP indicate an increase in the enzyme activity in soil.

The addition of SS led to higher values than the control of all the tested parameters up to the end of the experimental period. The antioxidant capacity (trolox equivalent antioxidant capacity, TEAC) was influenced by SS addition only when applied at HRS. After 120 days only HRS value of TEAC (5.13 mM g^?1) was higher than control (4.09 mM g^?1). The pattern of TEAC did not enable any link to be established between antioxidant capacity and both alkali-soluble phenols and basal respiration in soil.     

基于小波变换的最大冻深期气温与土壤水盐特征分析

土壤冻融过程中水分和盐分的耦合迁移一直是土壤水科学研究的难点和热点。为了解最大冻深期日最低气温与土壤水盐的尺度变化关系,该文利用墨西哥帽小波变换分析方法对内蒙古河套灌区1994-2006年最大冻深期(2月)日最低气温、0～40cm土层平均水分和盐分的时间-频率的尺度变化特征进行了分析。结果表明:在所研究的时间域内,该地区最大冻深期日最低气温、土壤水盐变化具有周期性特征;最大冻深期日最低气温以3a周期振动最强,土壤水盐均以2a周期振动最强;日最低气温、0～40cm土层水分和盐分有比较好的对应关系,即气温偏高期对应水分偏低期和盐分偏高期;日最低气温、0～40cm土层水分和盐分的周期性突变点位于1997年和2000年左右;盐分表现出不同时间尺度的振动变化,较日最低气温和水分变化更为复杂。该研究可为进一步研究干旱寒冷地区节水改造和盐渍化的防治提供参考。     

不同农艺措施下温室土壤酶活性的动态变化及其相关性分析

针对日光温室随种植年限增加,土壤质量退化的问题,研究了5种不同的农艺处理措施对土壤酶活性的影响。结果表明,食用菊花和番茄轮作、番茄嫁接2个处理对提高不同土壤酶活性的效果显著;夏季石灰氮消毒处理对提高脲酶、磷酸酶和过氧化物酶活性的效果显著;夏季填闲大葱对前季作物土壤酶活性的影响大于后季作物。番茄产量与土壤酶活性的变化趋势基本一致。蔗糖酶、脲酶、磷酸酶、多酚氧化酶和过氧化物酶可以作为设施蔬菜敏感的土壤酶学指标。在难以进行轮作的以番茄生产为主的地区,采取嫁接栽培能有效提高土壤酶活性;在有条件轮作地区,采取食用菊花与番茄轮作,对提高土壤酶活性和栽培效益方面有积极作用。     

Robust analysis of soil properties at the national scale: cadmium content of French soils

National-scale soil datasets exhibit variation over widely disparate spatial scales. Geological variation is an important source at the coarsest scale, and one in which exhaustive information is commonly available, in geological maps. Superimposed on this is continuous spatial variation caused by factors such as relief, vegetation and diffuse 'background' pollution. Further variation is caused by locally distinct factors such as point pollution from industrial sites or occasional geological anomalies. In this paper, we propose a single statistical model to encompass all of these effects which we describe as 'geological variation', 'continuous spatial variation' and 'local anomalies'. In our model, the geological and continuous spatial variation are described, respectively, by the fixed and random effects of a linear mixed model (LMM) and the local anomalies lead to observations which are spatial outliers with respect to the LMM. We fit the model to a survey of 1887 observations of cadmium concentration in soil (Cd) collected on an incomplete regular grid across the French metropolitan territory (550 000 km²) and use it to predict Cd across France. We find that (i) it is not possible to fit a valid model—in terms of cross-validation statistics—of Cd variation unless the effects of local anomalies are identified and separated from the larger-scale processes; (ii) the LMM is not valid if the outliers are merely discarded but a valid model does result if the outliers are winsorized. On the basis of these findings we suggest a practical robust algorithm for national-scale spatial analysis.     

Shrinkage of clay soils: A statistical correlation with other soil properties

The hypothesis that the shrinkage of soils is greater when expansible minerals are dominant was tested with 63 soils containing between 40 and 64% clay. Shrinkage between pF 2 and 4 (0.1 and 10 bar) correlated significantly with the expansible mineral content (measured by ethylene glycol retention) for remoulded but not for dried and rewetted specimens. Shrinkage between pF 4 and 6 (10 and 10³ bar) was strongly correlated with the expansible mineral content for both kinds of specimens. The physical significance of the results is discussed, and it is concluded that interlamellar shrinkage is not the principal component of bulk shrinkage.     

Sorption behavior of triazole fungicides in Indian soils and its correlation with soil properties

Adsorption-desorption of triazole fungicides, hexaconazole [2-(2,4-dichlorophenyl)-1-(1H-1,2,4,-triazol-1-yl) hexan-2-ol], triadimefon [1-(4-chlorophenoxy)-3,3-dimethyl-1-(1H-1,2,4-triazol-1-yl) butan-2-one], and penconazole[1-(2,4-dichloro-beta-propyl phenethyl)-1H-1,2,4-triazole] was studied in five Indian soils using batch method. The adsorption isotherms fitted very well to the Freundlich equation. Adsorption of various triazole fungicides increased in this order: triadimefon > hexaconazole > penconazole. The product of the Freundlich adsorption constants, K(f)(1/n), showed good correlation with the soil organic carbon (OC) content, suggesting that soil OC is the main controlling factor for triazoles adsorption. Clay and silt content of the soil also affected the adsorption constants. Adsorption of hexaconazole and triadimefon was nearly reversible in two low OC soils (soil 3, soil 5) where 90-100% of the sorbed fungicides was released in a single washing step. Otherwise, desorption of triazole fungicides showed hysteresis, and 30-60% of the triazole fungicides were retained by the soil after single washing. IR spectra showed that H-bonds and charge-transfer bonds between humic acid and fungicides probably operated as mechanisms of adsorption.     

Changes in soil properties of an eastern Australian vertisol irrigated with treated sewage effluent following gypsum application

Historically many towns in inland Australia disposed of their treated sewage by pumping into local rivers. This is no longer a feasible proposition. Alternatives to river pumping include irrigation and/or aquaculture. As treated sewage effluent may contain large amounts of nitrogen, phosphorus and sodium salts, if not managed carefully, soil salinity, sodicity and nutrient accumulation could increase. The objective of this study was to evaluate if gypsum application had any effect on soil‐quality changes in a Vertisol due to irrigating a cotton–wheat rotation with tertiary treated sewage effluent. The treatments were application of 2·5 t ha⁻¹ of gypsum in June 2000 before commencing irrigation and an untreated control. Annually, between June 2000 and April 2004, irrigation water quality and soil changes in nitrate‐N, EC_1:5, pH, organic carbon, Cl, dispersion index, and exchangeable cations to a depth of 1·8 m were measured and deep drainage inferred with the chloride mass balance method. Cotton lint yield and fibre characteristics were also evaluated. Irrigation with treated sewage effluent increased exchangeable Na in all depths, and exchangeable Ca and K in the clayey‐textured surface 0·6 m, but decreased exchangeable Ca and K, and SOC in the coarser clay‐loam‐textured depths > 0·6 m. Nitrate‐N leaching, associated with deep drainage had occurred, as the crops had not used all the N in irrigation water. Gypsum application decreased exchangeable Ca, increased dispersion and during the 2003–2004 season deep drainage, but had no effect on salinity, sodicity or pH. Application of commercial gypsum at sub‐optimal rates with sodium‐rich irrigation water is, therefore, unlikely to improve soil properties. Stubble incorporation before sowing cotton in 2003 appears to have mobilized gypsum applied during 2000. Gypsum application reduced cotton lint yield and fibre quality during 2003–2004. Copyright © 2006 John Wiley & Sons, Ltd.     

土壤水盐动态的BP神经网络模型及灰色关联分析

以陕西洛惠渠灌区实测数据为例,引用3层前馈型BP网络建模方法,对灌区综合条件下土壤水盐动态进行研究,采用附加动量法和学习速率自适应调整策略对反向传播算法进行改造;在此基础上运用缺省因子检验法分析了土壤含盐量和土壤碱度对输入层各因子的敏感性,并采用灰色关联法加以验证。结果表明,人工神经网络模型具有较高的精度,能够很好地定量描述土壤水盐动态变化与其影响因子之间的响应关系;土壤含水率、地下水含盐量和蒸发量是影响土壤水盐动态的主要敏感因子,各因子之间相互作用,形成了复杂条件下的耦合关系。灰色关联法进一步验证了各因子的敏感程度。将以上方法相结合,可为分析浅地下水埋深条件下作物生育期内土壤水盐动态规律提供有效可行的方法,是对传统土壤水盐动态研究方法的补充与完善。     

Spatial variation of ammonia volatilization from soil and its scale‐dependent correlation with soil properties

Quantitative predictions of ammonia volatilization from soil are useful to environmental managers and policy makers and empirical models have been used with some success. Spatial analysis of the soil properties and their relationship to the ammonia volatilization process is important as predictions will be required at disparate scales from the field to the catchment and beyond. These relationships are known to change across scales and this may affect the performance of an empirical model. This study is concerned with the variation of ammonia volatilization and some controlling soil properties: bulk density, volumetric water content, pH, CEC, soil pH buffer power, and urease activity, over distances of 2, 50, 500, and >2000 m. We sampled a 16 km × 16 km region in eastern England and analyzed the results by a nested analysis of (co)variance, from which variance components and correlations for each scale were obtained. The overall correlations between ammonia volatilization and the soil properties were generally weak: –0.09 for bulk density, 0.04 for volumetric water content, –0.22 for CEC, –0.08 for urease activity, –0.22 for pH and 0.18 for the soil pH buffer power. Variation in ammonia volatilization was scale‐dependent, with substantial variance components at the 2‐ and 500‐m scales. The results from the analysis of covariance show that the relationships between ammonia volatilization and soil properties are complex. At the >2000 m scale, ammonia volatilization was strongly correlated with pH (–0.82) and CEC (–0.55), which is probably the result of differences in parent material. We also observed weaker correlations at the 500‐m scale with bulk density (–0.61), volumetric water content (0.48), urease activity (–0.42), pH (–0.55) and soil pH buffer power (0.38). Nested analysis showed that overall correlations may mask relationships at scales of interest and the effect of soil variables on these soil processes is scale‐dependent.     

Changes in selected soil physical properties caused by sodicity of soil and irrigation water

Abstract

Sodic water and spring water percolated through clay, clay loam, and sandy loam (SL) soils with exchangeable sodium percentages (ESPs) of 0, 10, 30, and 50. Reduction in saturated hydraulic conductivity and water stable aggregates recorded at higher ESPs. At ESP ≈30, application of sodic and spring water to clay soil (C) reduced saturated hydraulic conductivity from 1.2 to 3 mm hr^?1, whereas in SL soil, the values were 2.8 and 6.2 mm hr^?1, respectively. Results indicated that at any ESP and water source, the highest free swelling obtained was in the C soil. This study has practical importance to the management of irrigation water quality with respect to soil deterioration.