Saturated hydraulic conductivity of soils in the Southern Piedmont of Georgia,USA: Field evaluation and relation to horizon and landscape properties

Saturated hydraulic conductivity (K_s) is one of the soil properties used most often to predict soil behavior and suitability for a variety of uses. Because of the difficulty in K_s measurement and its variability with depth and across the landscape, K_s is commonly predicted from other more easily evaluated properties including texture, clay mineralogy, bulk density, pedogenic structure and cementation. Of these, texture and pedogenic structure are most commonly used to estimate K_s, but the reliability of these estimates has not been evaluated for common soils in the Southern Piedmont of Georgia. Thus, the objectives of this study were to evaluate K_s for major horizons in soils and landscapes in the Georgia Piedmont and to relate K_s to morphological properties of these horizons. Ten sites across the region were selected, and 21 pedons arranged in three transects were described from auger holes and pits. For each pedon, K_s was measured in upper Bt horizons, at 140 cm below the surface (Bt, BC, or C horizon), and at a depth intermediate between the shallow and deep measurements (Bt, BC, or C horizon) with a constant head permeameter. The K_s of individual horizons ranged from 1 × 10^− 8 to 2 × 10^− 5 m s^− 1. At six of 10 sites evaluated, clayey upper Bt horizons had higher K_s than deeper horizons with less clay. This difference was attributed to weaker structure in the deeper BC horizons. Structural differences did not explain all variation in K_s with depth, however. Other soil and landscape properties including parent material composition, colluvium on lower slope positions, C horizon cementation, and depth of soil development also affected K_s of horizons in these soils and should be used to better estimate K_s.     

Support Vector Machine and Nonlinear Regression Methods for Estimating Saturated Hydraulic Conductivity

Pedotransfer functions (PTFs) are widely used for hydrological calculations based on the known basic properties of soils and sediments. The choice of predictors and the mathematical calculus are of particular importance for the accuracy of calculations. The aim of this study is to compare PTFs with the use of the nonlinear regression (NLR) and support vector machine (SVM) methods, as well as to choose predictor properties for estimating saturated hydraulic conductivity (K_s). K_s was determined in direct laboratory experiments on monoliths of agrosoddy-podzolic soil (Umbric Albeluvisol Abruptic, WRB, 2006) and calculated using PTFs based on the NLR and SVM methods. Six classes of predictor properties were tested for the calculated prognosis: K_s-1 (predictors: the sand, silt, and clay contents); K_s-2 (sand, silt, clay, and soil density); K_s-3 (sand, silt, clay, soil organic matter); K_s-4 (sand, silt, clay, soil density, organic matter); K_s-5 (clay, soil density, organic matter); and K_s-6 (sand, clay, soil density, organic matter). The efficiency of PTFs was determined by comparison with experimental values using the root mean square error (RMSE) and determination coefficient (R²). The results showed that the RMSE for SVM is smaller than the RMSE for NLR in predicting K_s for all classes of PTFs. The SVM method has advantages over the NLR method in terms of simplicity and range of application for predicting K_s using PTFs.     

Pedo-transfer functions for estimating the hydraulic properties of paddy soils in subtropical central China

Pedo-transfer functions (PTFs) have been widely used to estimate soil hydraulic properties in the simulation of catchment eco-hydrological processes. However, the accuracy of existing PTFs is usually inadequate for use. To develop PTFs for local use, soil columns were collected from a double rice-cropped agricultural catchment in subtropical central China. The PTFs for saturated soil hydraulic conductivity (K_s) and parameters (θ_s, α, and n) of the van Genuchten model for the soil water retention curve (SWRC) were obtained based on soil’s basic properties, and compared with models developed by Li et al. in 2007 and Wösten et al. in 1999, respectively. Our results indicated that K_s in the range of 0.04–1087 cm d^?1 and θ_s in the range of 0.34–0.51 cm³ cm^?3 were both well estimated with the R²_adj of 0.72 and 0.87, respectively, but α (0.04–0.65 cm^?1) and n (1.05–1.21) were relatively poorly predicted with the respective R²_adj of 0.38 and 0.55, despite the use of more input parameters. Our local derived PTFs outperformed the other two existing models. However, if the local PTFs for paddy soils are not available, the Wösten et al. 1999 model can be proposed as a useful alternative. Therefore, this study can improve our understanding of the development and application of PTFs for predicting paddy soil hydraulic properties in China.     

Alternative methods in the development of pedotransfer functions for soil hydraulic characteristics

Soil hydraulic properties are needed in the modeling of water flow and solute movement in the vadose zone. Pedotransfer functions (PTFs) have received the attention of many researchers for indirect determination of hydraulic properties from basic soil properties as an alternative to direct measurement. The objective of this study was to compare the performance of cascade forward network (CFN), multiple-linear regression (MLR), and seemingly unrelated regression (SUR) methods using prediction capabilities of point and parametric PTFs developed by these methods. The point PTFs estimated field capacity (FC), permanent wilting point (PWP), available water capacity (AWC), and saturated hydraulic conductivity (Ks) and the parametric PTFs estimated the van Genuchten retention parameters. A total of 180 soil samples was extracted from the UNSODA database and divided into two groups as 135 for the development and 45 for the validation of the PTFs. The model performances were evaluated with three statistical tools: the maximum error (ME), the model efficiency (EF), and the D index (D) using the observed and predicted values of a given parameter. Despite the fact that the differences among the three methods in prediction accuracies of the point and parametric PTFs were not statistically significant (p > 0.05) except θ_r and α (p < 0.05) based on the ANOVA test, overall MLR and SUR were somewhat better than CFN in prediction of the point PTFs, whereas CFN performed better than the other two methods in prediction of the parametric PTFs. The F.F values of FC and θ_r for CFN, MLR, and SUR methods were 0.705. 0.805, 0.795 and 0.356, −0.290, −0.290, respectively, which refer to the best and worst predictions. Properties (Ks, θ_r, α) having some difficulty in prediction were better predicted by CFN and SUR methods, where these methods predict all hydraulic properties from basic soil properties simultaneously rather than individually as in MLR. This suggests that multivariate analysis using such functional relationships between hydraulic properties and basic soil properties can be utilized in developing more accurate point and parametric PTFs with less time and effort.     

Spatial variability of water retention parameters and saturated hydraulic conductivity in a calcareous Inceptisols (Khuzestan province of Iran) under sugarcane cropping

The objective of this study was to quantify inherent spatial variability and spatial cross-correlation of the van Genuchten retention parameters and saturated hydraulic conductivity (K_s) of surface and subsurface layers in a calcareous Inceptisols (Khuzestan province, Iran) under sugarcane cropping. Measurements were performed on 100-cm³ undisturbed soil cores collected at 94 locations along a 30-m-long transect with horizontal sampling distance intervals of 0.3 and 1 m at soil depths of 0–40 and 40–80 cm, respectively. Spatial variability was investigated using conventional statistics and geostatistical techniques. Coefficient of variation (CV) varied from 8.2% (for shape parameter, n at 40–80 cm depth) to 256.7% (for K_s at 0–40 cm depth). The n parameter and saturated water content, θ_s, showed a small-scale spatial heterogeneity with a maximum CV of 11.3% for the first depth and 9.2% for the second depth. Most of the hydraulic parameters at both depths showed a spatial structure and convex experimental semivariograms with dominant spherical models with the influence range of 3.2–41 m. In most cases, the extent of spatial correlation scales of cross-semivariograms for pairs of cross-correlated hydraulic variables was found to be different with reference to those relating to the direct semivariograms of correlated variables.     

Estimation of soil saturated hydraulic conductivity by artificial neural networks ensemble in smectitic soils

The saturated hydraulic conductivity (K_s) of the soil is one of the main soil physical properties. Indirect estimation of this parameter using pedo-transfer functions (PTFs) has received considerable attention. The Purpose of this study was to improve the estimation of K_s using fractal parameters of particle and micro-aggregate size distributions in smectitic soils. In this study 260 disturbed and undisturbed soil samples were collected from Guilan province, the north of Iran. The fractal model of Bird and Perrier was used to compute the fractal parameters of particle and micro-aggregate size distributions. The PTFs were developed by artificial neural networks (ANNs) ensemble to estimate K_s by using available soil data and fractal parameters. There were found significant correlations between K_s and fractal parameters of particles and microaggregates. Estimation of K_s was improved significantly by using fractal parameters of soil micro-aggregates as predictors. But using geometric mean and geometric standard deviation of particles diameter did not improve K_s estimations significantly. Using fractal parameters of particles and micro-aggregates simultaneously, had the most effect in the estimation of K_s. Generally, fractal parameters can be successfully used as input parameters to improve the estimation of K_s in the PTFs in smectitic soils. As a result, ANNs ensemble successfully correlated the fractal parameters of particles and micro-aggregates to K_s.     

横断山区森林土壤饱和导水率传递函数的评价与构建研究

利用国际上具有代表性的9种土壤饱和导水率(Ks)传递函数模型估算了横断山地区贡嘎山不同类型森林土壤的K_s，并与实测数据进行了比较，结果表明，现有模型在横断山地区的拟合结果与实测数据的偏差极大，其在研究区的适用性差。结合研究区土壤含石率偏高的特点，增加土壤石砾含量(粒径>2 mm)作为输入变量，同时选取土壤容重、有机质含量和颗粒分布3种土壤基本特性参数作为输入变量，构建了本区域K_s传递函数模型：K_s=9.48+12.32×BD+0.29×SOM–1.94×GF+2.89×silt–5.34×sand，结果显示，模型预测值与实测值相关系数为0.67，该模型可以作为横断山地区自然林地K_s传递函数使用，从而为山地森林水文过程和自然灾害预警研究提供实用的参数估算工具。     

Accuracy of methods for field assessment of rill and ephemeral gully erosion

To properly assess soil erosion in agricultural areas, it is necessary to determine precisely the volume of ephemeral gullies and rills in the field by using direct measurement procedures. However, little information is available on the accuracy of the different methods used. The main purpose of this paper is to provide information for a suitable assessment of rill and ephemeral gully erosion with such direct measurement methods. To achieve this objective: a) the measurement errors associated to three methods used for field assessment of channel cross sectional areas are explored; b) the influence of the number of cross sections used per unit channel length on the assessment accuracy, is analysed and; c) the effect of the channel size and shape on measurement errors is examined. The three methods considered to determine the cross sectional areas were: the micro-topographic profile meter (1); the detailed measurement of section characteristic lengths with a tape (2); and the measurement of cross section width and depth with a tape (3). Five reaches of different ephemeral gully types 14.0 or 30.0 m long and a set of six 20.4 to 29.4 m long rill reaches were selected. On each gully reach, the cross sectional areas were measured using the three above mentioned methods, with a separation (s) between cross sections of 1 m. For rills, the cross sectional areas were measured with methods 1 and 3, with s = 2 m. Then, the corresponding total erosion volumes were computed. The volume calculated with method 1 with s = 1 m for gullies and s = 2 m for rills was taken as the reference method. For each channel, and for each one of the possible combinations of s and measurement method (m), the relative measurement error and the absolute value of the relative measurement error (E_sm^r and |E_sm^r|), defined with respect to the reference one, was calculated. |E_sm^r| much higher than 10% were obtained very easily, even for small s values and for apparently quasi prismatic channels. Channel size and shape had a great influence on measurement errors. In fact, the selection of the more suitable method for a certain gully shape and size seemed to be much more important than s, at least when s < 10 m. Method 1 always provided the most precise measurements, and its results were the less dependent on s. However, s must be < 5 m to guarantee an error smaller than 10%. Method 2 is not recommended, because it is difficult, time consuming and can lead to large errors. Method 3 seems to be enough for small, wide and shallow gullies, and for small rills, but only if s is shorter than 5 m. Results obtained after the analysis of rill measurement errors were similar to those of gullies. The analysis of E_sm^r and |E_sm^r| when calculating channel volumes using a unique representative cross section highlighted the importance of correctly selecting the adequate cross section. Due to the high error values that this method can entail, it is not considered as advisable whenever accurate erosion measurements are pursued.     

Surface soil hydraulic properties in four soil series under different land uses and their temporal changes

The concepts of “genoform” and “phenoform” distinguish the genetically-defined soil series and the variation of soil properties resulted from different land uses and management practices. With the repeated field measurements over time, we attempted to understand the difference of soil hydraulic properties among different land uses for a given soil series, and their temporal dynamics. Four soil series (Glenelg, Hagerstown, Joanna, and Morrison) in Pennsylvania with contrasting textures, structures, and parent materials were investigated. Within each soil series, four common land uses (woodland, cropland, pasture, and urban) were examined. At each site of soil series–land use combination, field-saturated and near-saturated hydraulic conductivities, K(ψ), were measured at the soil surface using standard tension infiltrometers at water supply potentials (ψ) of − 0.12, − .06, − 0.03, − 0.02, − 0.01, and 0 m. Surface infiltration measurements were repeated at each site in May and October from 2004 to 2006. The analysis of variance indicated that the measurement time (May or October) had the greatest impact on all measured hydraulic conductivities (p < 0.001), followed by the land use (p < 0.05 for K_ψ = 0 and K_{ψ = − 0.06}) and soil series (p < 0.06 for K_{ψ = − 0.01} to K_{ψ = − 0.03}). The interactions between the time and land use and between the soil series and land use were statistically significant for K_ψ = 0 and K_{ψ = − 0.01.} When separated by the measurement time, land use showed greater impacts in October than in May, while soil series had greater impacts in May than in October. Among the four land uses, woodland showed less obvious temporal change compared to the other three land uses because of less human-induced impacts and more consistent ground cover. Other three land uses generally showed a higher hydraulic conductivity in May than in October due to the drier initial soil moisture condition and related management practices in the spring that gave rise to more significant macropore flow. The results suggested that the initial soil moisture is an important variable that drives the temporal variation of the surface soil hydraulic properties.     

Spatial and seasonal variations in soil respiration in a temperate deciduous forest with fluctuating water table

Our objectives were to determine both spatial and temporal variations in soil respiration of a mixed deciduous forest, with soils exhibiting contrasting levels of hydromorphy. Soil respiration (R_S) showed a clear seasonal trend that reflected those of soil temperature (T_S) and soil water content (W_S), especially during summer drought. Using a bivariate model (RMSE=1.03), both optimal soil water content for soil respiration (W_SO) and soil respiration at both 10 °C and optimal soil water content (R_S10) varied among plots, ranging, respectively, from 0.25 to 0.40 and from 2.30 to 3.60 μmol m⁻² s⁻¹. Spatial variation in W_SO was related to bulk density and to topsoil N content, while spatial variation in R_S10 was related to basal area and the difference in pH measured in water or KCl suspensions. These results offer promising perspectives for spatializing ecosystem carbon budget at the regional scale.     

A mass-balance approach to measuring microbial uptake and pools of phosphorus in nutrient-amended soils

Soil microbial biomass P is usually determined through fumigation-extraction (FE), in which partially extractable P from lysed biomass is converted to biomass P using a conversion factor (K_p). Estimation of K_p has been usually based on cultured microorganisms, which may not adequately represent the soil microbial community in either nutrient-poor or in altered carbon and nutrient conditions following fertilisation. We report an alternative approach in which changes in microbial P storage are determined as the residual in a mass balance of extractable P before and after incubation. This approach was applied in three low-fertility sandy soils of southwestern Australia, to determine microbial P immobilisation during 5-day incubations in response to the amendment by 2.323 mg C g⁻¹, 100 μg N g⁻¹ and 20 μg P g⁻¹. The net P immobilisation during the amended incubations determined to be 18.1, 14.1 and 16.3 μg P g⁻¹ in the three soils, accounting for 70.6-90.5% of P added through amendment. Such estimates do not rely on fumigation and K_p values, but for comparison with the FE method we estimated ‘nominal’ K_p values to be 0.20-0.31 for the soils under the amended conditions. Our results showed that microbial P immobilisation was a dominant process regulating P concentration in soil water following the CNP amendment. The mass-balance approach provides information not only about changes in the microbial P compartment, but also about other major P-pools and their fluxes in regulating soil-water P concentrations under substrate- and nutrient-amended conditions.     

Long-term (13 years) measurements of SO2 fluxes over a forest and their control by surface chemistry

Long-term fluxes of sulphur dioxide (SO₂) have been measured over a mixed suburban forest subjected to elevated SO₂ concentrations. The net exchange was shown to be highly dynamic with substantial periods of both upward and downward fluxes observed in excellent conditions for flux measurement. Upward fluxes constituted 30% of selected fluxes and appeared more frequently when the canopy was acidic. Upward fluxes were shown to be due to desorption from a drying surface or when ambient levels declined after periods of increased SO₂ exposure.The long term average SO₂ flux (F) was −59 ng SO₂ m⁻² s⁻¹ for the period 1997-2009 corresponding to an average SO₂ concentration of 12.3 μg SO₂ m⁻³ and a deposition velocity υ_d of 5 mm s⁻¹. The smallest deposition fluxes and υ_d were measured in dry conditions (−42 ng m⁻² s⁻¹ and 3.5 mm s⁻¹, resp.), which represented 57% of all cases. Wet canopies were more efficient sinks for SO₂ and a dew-wetted canopy had a smaller υ_d (6 mm s⁻¹) than a rain-wetted canopy (ca 10 mm s⁻¹). Seasonal variability reflected differences in chemical climate or canopy buffering properties. During the summer half-year when surface acidity was low due to higher NH₃/SO₂ ratios, a higher deposition efficiency (υ_d/υ_dmax) and lower non-stomatal resistance (R_w) were observed compared to winter conditions. Comparisons of R_c for different combinations of canopy wetness and surface acidity categories emphasized the importance of both factors in regulating the non-stomatal sinks of SO₂. Increased surface water acidity gradually led to a lower υ_d/υ_dmax and an increased R_c for all considered canopy wetness categories. The smallest υ_d/υ_dmax ratio and highest R_c were obtained for a dry canopy with high surface acidity. Conversely, a rain-wetted canopy was the most efficient sink for SO₂. The canopy sink strength was further enhanced by high friction velocities (u_*), optimizing the mechanical mixing into the canopy. Long-term trends were strongly coupled to changes in the NH₃/SO₂ ratio, which has clearly enhanced the deposition efficiency of SO₂ in recent years.     

Development and validation of an acute biotic ligand model (BLM) predicting cobalt toxicity in soil to the potworm Enchytraeus albidus

An acute Biotic Ligand Model (BLM) was developed to predict the effect of cobalt on the survival of the potworm Enchytraeus albidus, exposed in nutrient solutions added to acid washed, precombusted sand. The extent to which Ca²⁺, Mg²⁺ and Na⁺ ions and pH independently mitigate cobalt toxicity to E. albidus was examined. Higher activities of Ca²⁺, Mg²⁺ and H⁺ linearly increased the 14 d LC50_Co²⁺ (LC50 expressed as Co²⁺-activity) whereas Na⁺-activity did not. Stability constants for the binding of Co²⁺, Ca²⁺, Mg²⁺ and H⁺ to the biotic ligand (BL) were derived, i.e. log K_CoBL=5.13, log K_CaBL=3.83, log K_MgBL=3.95 and log K_HBL=6.53. It was calculated that at Co-concentrations corresponding to the 14d-LC50 value, 32% of the BL sites were occupied by cobalt. An initial validation of the applicability of this BLM in true soil exposure systems was performed by comparing observed and model-predicted 14 d LC50 s in a standard artificial soil and a standard field soil. By assuming pore water to be the only route of exposure and assuming equilibrium between pore water Co²⁺ and solid phase Co, which is predicted by the geochemical WHAM-Model 6, LC50 s (as mg Co kg⁻¹ dry wt of soil) were predicted within an error of less than a factor two. Further validation in true soil exposures, combined with more detailed knowledge of Co binding to soil solid phases is needed, if this model is to be used as a tool for risk assessment and derivation of soil quality criteria for Co.     

Temporal change in spatial variability of soil respiration on a slope of Japanese cedar (Cryptomeria japonica D. Don) forest

Although information regarding the spatial variability of soil respiration is important for understanding carbon cycling and developing a suitable sampling design for estimating average soil respiration, it remains relatively understudied compared to temporal changes. In this study, soil respiration was measured at 35 locations by season on a slope of Japanese cedar forest in order to examine temporal changes in the spatial distribution of soil respiration. Spatial variability of soil respiration varied between seasons, with the highest coefficient variation in winter (42%) and lowest in summer (26%). Semivariogram analysis and kriged maps revealed different patterns of spatial distribution in each season. Factors affecting the spatial variability were relief index (autumn), soil hardness of the A layer (winter), soil hardness at 50 cm depth (spring) and the altitude and relief index (summer). Annual soil respiration (average: 39 mol m⁻² y⁻¹) varied from 26 mol m⁻² y⁻¹ to 55 mol m⁻² y⁻¹ between the 35 locations and was higher in the upper part of the slope and lower in the lower part. The average Q₁₀ value was 2.3, varying from 1.3 to 3.0 among the locations. These findings suggest that insufficient information on the spatial variability of soil respiration and imbalanced sampling could bias estimates of current and future carbon budgets.     

Influence of relative surface age on hydraulic properties and infiltration on soils associated with desert pavements

Av horizons found in desert pavement environments are known to evolve pedogenically over geologic time. This study was conducted to determine whether increased pedogenic development of the Av (vesicular) horizon over relative time impacts the hydraulic properties of individual soil peds and the mechanism of infiltration as inferred by dye patterns. We examined peds from the Av horizons associated with desert pavements that mantled three different alluvial deposits with different relative surface ages (Qf5 (∼ 10 ka), Qf3 (∼ 50–100 ka), and Qf2 (∼ 10–50 ka)) and included an additional surface (Qf6 (∼ 4 ka)) for the dye studies. We hypothesized that increases in the development of the Av over time would lead to a more structured soil surface with greater potential flow between soil peds and lower hydraulic conductivity of the soil peds themselves. Results showed that average K_s and α of the Qf5 peds were significantly greater than estimated for the Qf2 and Qf3 peds. Although K_s was greater for the Qf5 peds, the steady-state infiltration rate was equal for the Qf3, Qf2, and Qf5 surfaces, perhaps indicating a reduction in matrix flow through soil peds and an increase in interped flow between soil peds.     

A half-a-century record of annual energy expenditure and geomorphic effectiveness of the monsoon-fed Narmada River,central India

This case study presents quantitative data on the magnitude and variability of specific power and total energy expenditure over a period of 51 years for the monsoon-dominated Narmada River, which produced an impressive flood of the order of 69 400 m³ s^− 1 in 1970. Daily specific stream power (ω) for a gauging site located in the lower Narmada Basin was estimated by using daily discharge data available from 1949 to 1999, at-a-station hydraulic geometry equations and the relationship between discharge and water surface slope. The total amount of energy expended per unit area by all the monsoon flows was estimated by integrating the area under the ω-graph. The estimates of effective stream power were then checked against work thresholds.     

Pedotransfer Functions for the Estimation of Saturated Hydraulic Conductivity for Some Indian Sandy Soils

Determination of the saturated hydraulic conductivity (k_s) is needed in many studies and applications related to irrigation, drainage, water movement and solute transport in the soil. Although many advances are made for direct measurements of k_s, they are usually time consuming and costly. Some attempts have been made to indirectly predict the saturated hydraulic conductivity from the more easily or readily available basic soil properties. The objective of this study was to develop and validate Pedotransfer Functions (PTFs) for estimation of saturated hydraulic conductivity using multiple non-linear regression technique. One hundred and one soil samples were collected from agricultural and forest soils at different depths, at different locations in the Pavanje River basin that lies in the southern coastal region of Karnataka, India. Saturated hydraulic conductivity was measured, by variable falling head method through Permeameter in the laboratory. Prediction accuracies were evaluated using coefficient of determination, root mean square error, mean error, geometric mean error ratio and geometric standard deviation of the error ratio between measured and predicted values. The results show that, the PTFs for the estimation of saturated hydraulic conductivity could be used appropriately for the soils with loamy sand and sandy loam textures falling in this area of the coastal region of southern India.     

Exploring the variation in soil saturated hydraulic conductivity under a tropical rainforest using the wavelet transform

Saturated hydraulic conductivity (K_s) of the soil is a key variable in the water cycle. For the humid tropics, information about spatial scales of K_s and their relation to soil types deduced from soil map units is of interest, as soil maps are often the only available data source for modelling. We examined the influence of soil map units on the mean and variation in K_s along a transect in a tropical rainforest using undisturbed soil cores at 0–6 and 6–12 cm depth. The K_s means were estimated with a linear mixed model fitted by residual maximum likelihood (REML), and the spatial variation in K_s was investigated with the maximum overlap discrete wavelet packet transform (MODWPT). The mean values of K_s did not differ between soil map units. The best wavelet packet basis for K_s at 0–6 cm showed stationarity at high frequencies, suggesting uniform small‐scale influences such as bioturbation. There were substantial contributions to wavelet packet variance over the range of spatial frequencies and a pronounced low frequency peak corresponding approximately to the scale of soil map units. However, in the relevant frequency intervals no significant changes in wavelet packet variance were detected. We conclude that near‐surface K_s is not dominated by static, soil‐inherent properties for the examined range of soils. Several indicators from the wavelet packet analysis hint at the more dominant dynamic influence of biotic processes, which should be kept in mind when modelling soil hydraulic properties on the basis of soil maps.     

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.