Soil electrical conductivity as a function of soil water content and implications for soil mapping

Apparent soil electrical conductivity (EC_a) has shown promise as a soil survey tool in the Midwestern United States, with a share of this interest coming from the precision agriculture community. To fully utilize the potential of EC_a to map soils, a better understanding of temporal changes in EC_a is needed. Therefore, this study was undertaken to compare temporal changes in soil EC_a between different soils, to investigate the influence of changes in soil water content on soil EC_a, and to explore the impacts these EC_a changes might have on soil mapping applications. To this end, a 90 m long transect was established. Soil EC_a readings were taken in the vertical and horizontal dipoles at five points once every one to two weeks from June until October in 1999 and 2000. At the same time, soil samples were collected to a depth of 0.9 m for volumetric soil water content analysis. Soil EC_a readings were compared to soil water content. At four of the five sites linear regression analysis yielded r ² values of 0.70 or higher. Regression line slopes tended to be greater in lower landscape positions indicating greater EC_a changes with a given change in soil water content. Two of the soils had an EC_a relationship that changed as the soils became dry. This is an item of concern if EC_a is to be used in soil mapping. Results indicated that soil water content has a strong influence on the EC_a of these soils, and that EC_a has its greatest potential to differentiate between soils when the soils are moist. Soil water content is an important variable to know when conducting EC_a surveys and should be recorded as a part of any report on EC_a studies.     

The impact of various sprinkler irrigation patterns on spatial soil moisture variation in Vertisols

The objective of this research was to assess the effect of soil cracks on soil moisture distribution under various sprinkler irrigation applications and to identify the optimal irrigation strategy that enhances soil moisture distribution and reduces water drainage for the upper soil layer 0–250 mm. The assessment was made for six irrigation events: the first two were for 10 and 46 mm water applications using a hand shift-set sprinkler system. The second set was for 43 and 19 mm water applications using the lateral move system with fixed sprayer heads and the third pair of events were for 43 and 32 mm water applications using the lateral move system with rotating sprinklers. The experiments were conducted on two adjacent fields at the University of Queensland, Gatton, Australia. Each field was divided into 2 m × 2 m grids that covered 62 sampling locations. For each event, the initial soil moisture content (SMC) was measured at each sampling location before irrigation. After irrigation, catch can readings were recorded for each sampling location. After 12 h overnight, the second set of soil moisture measurements was taken at each location. The area1 distribution of SMC for the studied applications was quantified. An attempt was made to identify the relationship between the applied water uniformity using catch cans and the soil moisture uniformity using gravimetric water content measurements. The study also took into consideration variables that could affect the soil physical and hydrological properties including the field slope, the soil texture, the infiltration rate, the salt content and the soil organic matter content of the two fields. Since the soils were cracking clay Vertisols, further analyses were conducted on the crack dynamics, size and distribution using image analysis techniques. The research findings demonstrated that the cracks were the main contributors to water drainage below 250 mm soil depth due to the micro-run off from the crust surface to the cracks. The cracks ranged from a few millimeters to more than 40 mm in width. It was observed that the cracks which were wider than 15 mm remained open after irrigation for the specified application rates. Improving the irrigation system application uniformity did not always result in higher uniformity of the surface SMC (0–250 mm). The event that best enhanced soil moisture distribution and thus improved soil moisture recharging was observed after the sixth irrigation event when the field received 32 mm water application. The soil was at a relatively high initial SMC of 25%, (which represented 43.3% of the plant available water range) and the sprinkler water uniformity was rather high above 87% Christiansen coefficient of uniformity (CUc). At this SMC, the extent of soil cracking is limited.     

广东山区土壤有机碳空间变异的尺度效应

研究土壤有机碳的尺度效应能够为区域生态环境保护和确定合理的土壤取样间距提供科学依据。采用土壤类型法估算了广东山区表层(0-20 cm)和全剖面(0-100 cm)土壤有机碳密度,选择4条采样带,获取采样间距为250 m的土壤有机碳密度序列,并利用离散小波变换工具对其进行多尺度分解,得到2×250 m、2²×250 m、2³×250 m、2⁴×250 m、2⁵×250 m和2⁶×250 m 6个分解尺度上的小波信息,计算小波信息方差。结果表明:土壤有机碳密度具有较强的空间异质性,其空间异质性的大小受控于不同尺度下土壤有机碳密度分布格局的主导因子影响程度;整体上在大于等于1 km的尺度,其空间异质性较强;各个样带特征尺度的差异与各样带的土壤和植被类型、地貌特征以及土地利用方式、耕作管理方式等人类活动干扰强度有关。     

Nutrient Management Zones for Citrus Based on Variation in Soil Properties and Tree Performance

Site-specific soil management can improve profitability and environmental protection of citrus groves having large spatial variation in soil and tree characteristics. The objectives of this study were to identify soil factors causing tree performance decline in a variable citrus grove, and to develop soil-specific management zones based on easily measured soil/tree parameters for variable rate applications of appropriate soil amendments. Selected soil properties at six profile depths (0–1.5 m), water table depth, ground conductivity, leaf chlorophyll index, leaf nutrients and normalized difference vegetation index were compared at 50 control points in a highly variable 45-ha citrus grove. Regression analysis indicated that 90% of spatial variation in tree growth, assessed by NDVI, was explained by average soil profile properties of organic matter, color, near-infrared reflectance, soil solution electrical conductivity, ground conductivity and water table depth. Regression results also showed that soil samples at the surface only (0–150 mm) explained 78% of NDVI variability with NIR and DTPA-extractable Fe. Excessive available copper in low soil organic matter areas of the grove apparently induced Fe deficiency, causing chlorotic foliage disorders and stunted tree growth. The semivariograms of selected variables showed a strong spatial dependence with large ranges (varied from 230 m to 255 m). This grove can be divided into different management zones on the basis of easily measured NDVI and/or soil organic matter for variable rate application of dolomite and chelated iron to improve tree performance.     

Simulation of Cotton Production for Precision Farming

Most crop simulation models do not directly consider the spatial variability of inputs nor do they produce outputs that show the expected spatial variability of yield across a field. If such models were available for precision farming, then researchers could much better evaluate the effects of soil sampling densities to determine the number of samples necessary to adequately model a particular field. The objectives of this study were: (1) to design and implement a spatial simulation methodology for examining details of precision farming and (2) use this to evaluate the effects of different soil sampling resolutions on predicted yield and residual nitrates through spatially variable nitrogen applications. The GOSSYM/COMAX cotton growth model/expert system and the GRASS geographic information system were used to develop a spatial simulation that produces spatially variable outputs. Inputs to the model were collected from a 3.9-ha cotton field. Soil nitrate, a primary driver in fertilizer recommendations, was sampled on a 15.2-m regular grid for depths to 15 cm and on a 30.5-m regular grid at six 15-cm depth intervals (down to 90 cm). COMAX was used to determine spatially variable fertilizer recommendations. GOSSYM was used to simulate perfect application of these recommendations and predicted spatially variable yield and residual nitrates. Reductions in sampling density or resolution were simulated by systematically reducing the amount of data available to COMAX for calculating spatially variable fertilizer recommendations. GOSSYM subsequently used these recommendations (based upon less and less knowledge of soil nitrates) to simulate the effects of differing sampling resolutions on predicted yield and residual nitrates. For recommendations based upon a 15.2-m grid of inputs, 41.4 kg/ha of nitrate fertilizer produced 801.7 kg/ha of cotton and left an average of 9.4 ppm of nitrate in the soil profile. For a 30.5-m grid, 42.8 kg/ha of nitrate fertilizer resulted in a yield of 811.2 kg/ha and residual soil nitrate of 8.3 ppm. For 45.7-m and 61.0-m grids, the results were 43.3 kg/ha and 41.2 kg/ha of nitrate fertilizer, 755.3 kg/ha and 794.3 kg/ha of cotton, and 11.5 ppm and 8.1 ppm of residual soil nitrate, respectively. This study concluded that crop simulations and geographic information systems are a valuable combination for modeling the effects of precision farming and planning variable rate treatments. Simulation results indicate that excessive fertilization, while potentially damaging to the environment, may also have a negative impact on yield.     

Soil Nutrient Relationships with Topography as Influenced by Crop

Variable-rate fertilizer application is often based on grid soil sample data from a single year of data in an annual crop rotation. The objectives of this study were to determine if crop history influences spatial dependence (the degree of spatial variability) of nutrients in a rotation including both annual crops and alfalfa, and to compare grid-based and topography-based sampling strategies for representing within-field nutrient levels. A site in the Red River Valley of North Dakota was observed over three years from 1994–1996. The site was divided into one field of continuous alfalfa (Medica sativa L.) and an adjacent field seeded to spring wheat (Triticum aestivum L.) in 1994, barley (Hordeum vulgare L.) in 1995 and alfalfa in 1996. Samples were taken from a 16.2-ha site each fall in a 33-m grid and analyzed for NO₃-N, P, SO₄-S and Cl. Topography was determined by measuring elevation in a 33-m grid with a laser-surveying device. Spatial dependence was determined by calculating the semivariogram and using regression analysis to assess the relationship between the semivariogram and the semivariogram model. Spatial dependence of NO₃-N and P was strongest following spring wheat and barley, while spatial dependence for SO₄-S and C1 was strongest for vigorous stands of alfalfa. When the continuous alfalfa stand declined following winter kill, NO₃-N and P spatial dependence intensified. Topography based sampling was correlated with the 33-m grid by giving each 33-m sampling location its value as directed by a topography sampling, then correlating that topography based value with the original 33-m sampling value. Topography-based sampling was correlated with the 33-m sampling grid for all nutrients following spring wheat and barley, but not in continuous alfalfa until the stand began to decline in vigor. Following alfalfa seeding in the annual crop field, topography relationships with NO₃-N and P decreased, while topography relationships with SO₄-S and Cl increased. Topography samplings of sulfate-S and chloride were most highly correlated to 33-m grid values in vigorous alfalfa. Lack of NO₃-N spatial dependence in the vigorous alfalfa stands suggests that a composite or field average soil test might be sufficient to provide soil NO₃-N information under similar conditions.     

Characterization and modeling of water movement and salts transfer in a semi-arid region of Tunisia (Bou Hajla,Kairouan) – Salinization risk of soils and aquifers

The semi-arid region of Bou Hajla (Kairouan – Central Tunisia) is exposed to the risk of soils and aquifers salinization. A characterization of water movement through the use of TDR probes installed at up to 4 m in depth, and of salts transfer by soil sampling was conducted to highlight this risk. At the same time, climatic parameters were monitored. The results were gathered over the period of approximately 1 year (June 12, 2006 to May 08, 2007). Water infiltration and evaporation, occurred at within distinct materials: two zero flux planes at 1 and 3 m, and a clay-silt layer at 2 m where the soil water content and electrical conductivity is highly varied. Saline profiles show salt accumulation at this layer where the electrical conductivity of soil paste extract exceeds 20 dS m⁻¹. However, the additive salt balance between soil surface and a depth of 4 m highlights the salt transfer beyond the studied unsaturated zone, increasing the salinization risk of the aquifer. The water movement and salts transfer were simulated by Hydrus-1d model, and inverse modeling was used to optimize the required hydrodynamic parameters. It was found that the simulated profiles of volumetric humidity and the electrical conductivity of soil are close to those measured. The calculated RMSE values are low, indicating the reliability of Hydrus-1d for the simulation of the hydro-saline dynamics in field conditions.     

Evaluation of a Geonics EM31-3RT probe to delineate hydrologic regimes in a tile-drained field

A world-wide need to use water resources efficiently necessitates more effective approaches to study water and contaminant transport in soil. This study examined the effectiveness of a multi-receiver electromagnetic induction probe (Geonics EM31-3RT) and modeling software (EMIGMA) to delineate hydrological regimes at field scale. The site consisted of 20 (15 m × 15 m) tile-drained plots in Southern Ontario, Canada. Measurements of apparent soil electrical conductivity (EC_a) and magnetic susceptibility were obtained using the EM31-3RT in each plot at four distances (0, 2.25, 4.5 and 7.5 m) from the tile drain, and on three occasions (August 22, 26 and 29) in 2003. The EMIGMA was used to simulate a depth profile of electrical conductivity (EC_s) from EM31-3RT readings. The near-surface soil showed significantly (p < 0.01) smaller EC_a values than at greater depth. The EC_a measurements made directly over the tile drains were smaller than those observed further away due to the presence of the drains. Cluster analysis indicated that the largest EC_a values were at the lower elevations of the site related to the redistribution of moisture from higher elevations. The effect of tile drains and rainfall events on EC_a was simulated well by EMIGMA, with smaller EC_s values above the drains compared to further away, and showing an increase in EC_s in the near-surface soil after rain. This study suggests that EM31-3RT measurements combined with EMIGMA simulation of electrical conductivity can provide valuable information on depth profiles of EC_a and water dynamics in soil.     

Spatial patterns of wilting in sugar beet as an indicator for precision irrigation

Precision irrigation requires the mapping of within-field variations of water requirement. Conventional remote sensing techniques provide estimates of water status at only shallow soil depths. The ability of a water sensitive crop, sugar beet, to act as an intermediate sensor providing an integrated measure of water status throughout its rooting depth is tested here. Archive aerial photographs and satellite imagery of Eastern England show crop patterns resulting from past periglacial processes. The patterns were found to be spatially and temporally consistent. Field sampling of soil cores to 1 m depth established that the within-field wilting zones were significantly associated with coarser or shallow soils. The stress classes, determined by classification of the digitised images, were weakly correlated with total available water (Pearson correlation r = 0.588, P < 0.05). These results suggest that wilting in sugar beet can be used as an intermediate sensor for quantifying potential soil water availability within the root zone. Within-field stress maps generated in 1 year could be applied as a strategic tool allowing precision irrigation to be applied to high-value crops in following years, helping to make more sustainable use of water resources.     

Evaluation of an on-the-go technology for soil pH mapping

Since conventional sampling and laboratory soil analysis do not provide a cost effective capability for obtaining geo-referenced measurements with adequate frequency, different on-the-go sensing techniques have been attempted. One such recently commercialized sensing system combines mapping of soil electrical conductivity and pH. The concept of direct measurement of soil pH has allowed for a substantial increase in measurement density. In this publication, soil pH maps, developed using on-the-go technology and obtained for eight production fields in six US states, were compared with corresponding maps derived from grid sampling. It was shown that with certain field conditions, on-the-go mapping can significantly increase the accuracy of soil pH maps and therefore increase the potential profitability of variable rate liming. However, in many instances, these on-the-go measurements need to be calibrated to account for a field-specific bias. After calibration, the overall error estimate for soil pH maps produced using on-the-go measurements was less than 0.3 pH, while non-calibrated on-the-go and conventional field average and grid-sampling maps produced errors greater than 0.4 pH.     

Wireless Soil Scout prototype radio signal reception compared to the attenuation model

Wireless underground Soil Scout prototypes, introduced here for the first time, were used for remote soil monitoring during 5 months in real conditions. Every Soil Scout transmitted moisture and temperature data once every 10 min. The prototype system works well. A signal attenuation model is able to predict long periods of lost signals when soil moisture and on-soil vegetation conditions change. The model attenuation −98 dB is the threshold level for distinguishing probable failure from success, even if the system hardware design would suggest −110 dB. Individual transmission failures do not always correlate to changes of condition. Further work should focus on increasing transmission power and improving knowledge of the effect of vegetation.     

Precision Farming Protocols: Part 1. Grid Distance and Soil Nutrient Impact on the Reproducibility of Spatial Variability Measurements

To determine temporal changes in soil nutrient status, reproducible results must be obtained at each time step. The objective of this paper was to determine the impact of grid distance on the reproducibility of spatial variability measurements. Soil samples from the 0 to 15 cm depth were collected from a 30 by 30 m grid in May 1995 in a 65 ha notill corn (Zea mays L.) field. Each bulk sample contained 15 individual cores, collected at sample points located every 11.4 cm along a transect that transversed 3 corn rows (57 cm). At each sampling point latitude, longitude, elevation, landscape position, and soil series were determined. The 30 m grid was used to develop 4 and 9 independent data sets having a 60 and 90 m, grids, respectively. Semivariograms, nugget to sill ratios, and mean squared errors were calculated for each data set. At 60 m: (i) the total N, total C, and pH semivariograms, of different start points, were similar, while semivariograms for Olsen P, K, and Zn were different; (ii) the spatial dependence ratings, based on the nugget to sill ratio, for total N, total C, and pH semivariograms were consistent and suggested moderate spatial dependence; (iii) the spatial dependence rating for Olsen P, K, and Zn for the 4 semivariograms were not consistent and ranged from weak to moderate spatial dependence. At 90 m all soil nutrients had different semivariograms for each start point, while the spatial dependence rating for each total N, total C, and pH start point were consistent and showed moderate spatial dependence. The total C, P, K, Zn, and pH MSE values at 60 m, were 30, 30, 41, 28, and 72% lower than the variance, respectively. This study showed that semivariogram, semivariance, MSE, and nugget to sill ratios reproducibility were dependent on soil nutrient and grid distance.     

土壤水分空间变异研究

以天津市静海县良种场内一块长约110 m,宽约40 m的冬小麦田作为试验区,采用规则格网采样,按照10 m×10 m设置格网,共设48个采样点,通过GPS手持机进行定位,分别于小麦越冬前、拔节期、灌浆期,利用便携式土壤湿度数据采集器对试验地各个采样点0～20、20～40 cm2种深度土壤含水量进行了测定,利用ARC/INFO的地统计分析模块绘制了冬小麦3个不同生育期试验区土壤水分空间分布图,并分析了其垂直和水平方向的空间变异特征,以期为确定最佳灌溉时机和灌溉量提供科学依据。     

科尔沁沙地樟子松疏林草地土壤有机碳及其稳定性特征

[目的]探讨科尔沁沙地半干旱区樟子松疏林草地土壤有机碳及其稳定性。[方法]通过分析林内0～5、5～10、10～20和20～30cm层土壤有机碳(SOC)、土壤微生物量碳(MBC)以及土壤易氧化有机碳(Clab)含量,揭示樟子松疏林草地SOC含量及其稳定性。[结果]樟子松疏林草地SOC含量随土层深度的增加而降低,由表层(0～5 cm)的6.77 g/kg降到深层(20～30 cm)的3.51 g/kg,下降了约48%;MBC在土壤空间分布上表现为先降低后增加,Clab含量呈相同的变化趋势。[结论]随着土层深度的增加,樟子松疏林草地Clab含量升高,表明樟子松疏林草地SOC的稳定性随土壤深度的增加而降低。     

Spatial Variability of Irrigated Corn Yield in Relation to Field Topography and Soil Chemical Characteristics

Corn yield, topography and soil characteristics were sampled on a 26 ha area of a centre pivot irrigated cropland. The aim of the study was to determine relationships between corn yield, field topography and soil characteristics. The study was carried out in the Alentejo region of Portugal. Corn yield was measured with a combine harvester fitted with a grain-flow sensor and positioned by means of the Global Positioning System (GPS). A grid-based digital elevation model (DEM) with 1-m resolution was constructed and several topographic attributes were calculated from the DEM: the local slope gradient (S), profile curvature (Curv), specific catchments area (SCa), and a steady-state wetness index (W). Yield and topographical attributes were computed for areas of radius 5, 10, 25 and 50 m, being considered its maximum, minimum, range and average values. The soil was systematically sampled with a mechanical probe for a total of 109 soil profiles used for analysis of the following soil superficial (<0.30 m) characteristics: extractable phosphorous (P₂O₅) and extractable potassium (K₂O), soil pH, cation exchange capacity (CEC) and exchangeable bases. With centre pivot irrigation systems, the Wave₅₀ index was shown to be useful for the identification of field areas in which low corn yields may be due to lack of water. At the same time, SCa was found to be useful for the identification of field areas in which low yields are due to excess water and drainage problems. Higher positive correlation between pH, Ca and Curv were observed; calcium concentration was found on the transition areas between flat surfaces to concave ones, while lower values were detected in convex and concave areas. Topographical indexes, namely Wave₅₀, SCa and Curv, can be especially helpful in site-specific management for delineating areas where crop yields are more sensitive to extreme water conditions.     

Effect of Daily Soil Temperature Fluctuations on Soil Electrical Conductivity as Measured with the Geonics® EM-38

Soil electrical conductivity (EC_a) measured by electromagnetic induction (EM) using the EM-38 has shown promise as a soil survey tool. Soil temperature influences EC_a readings, and temperature can fluctuate considerably in the upper 10cm of the soil during a day. EC_a readings were taken in the horizontal and vertical dipole orientations once an hour from 8a.m. to 8p.m. at four sites on three separate days to determine if EC_a values were influenced by diurnal temperature variations. Soil temperature readings were taken at the same times at four depths. EM-38 readings remained steady at all four sites all 3days. Linear regression analysis when temperature in the upper 10cm was plotted against EC_a yielded low r ² values and slopes, indicating no correlation between soil temperature in the upper 10cm and EC_a values. Diurnal changes in soil temperature do not significantly influence soil EC_a readings obtained with the EM-38 under the conditions encountered during the study.     

Data acquisition system for soil-tire interface stress measurement

In today’s production agriculture industry, a renewed interest has been placed on input costs and energy efficiency. The fact that the soil-tire interface of a tractive vehicle is inherently inefficient is widely known but not widely understood. To support evaluation of the soil-tire interface a measurement system was created to sense the normal stress at the interface of the tire and soil. To acquire and log the data from this sensor array, a unique data acquisition system was developed and is presented in this paper. The system utilized a microcontroller to process and write data to a compact flash card from a total of 56 analog channels. It also used a two-dimensional accelerometer to determine the angular position of the vehicle tire and the attached sensors. Custom data acquisition software was developed to log the data to the compact flash card in an efficient, organized manner. Results confirmed that the data acquisition system was capable of operating at 887 Hz per-channel analog sampling frequency. Data from field testing illustrated the capability of the accelerometer to determine wheel angular rotation and associate the applied normal stress with that angular rotation. Results also confirmed the capability of the data acquisition system to estimate the rotational angle of contact of the tire while engaging soil.     

Verification of color vegetation indices for automated crop imaging applications

An accurate vegetation index is required to identify plant biomass versus soil and residue backgrounds for automated remote sensing and machine vision applications, plant ecological assessments, precision crop management, and weed control. An improved vegetation index, Excess Green minus Excess Red (ExG − ExR) was compared to the commonly used Excess Green (ExG), and the normalized difference (NDI) indices. The latter two indices used an Otsu threshold value to convert the index near-binary to a full-binary image. The indices were tested with digital color image sets of single plants grown and taken in a greenhouse and field images of young soybean plants. Vegetative index accuracies using a separation quality factor algorithm were compared to hand-extracted plant regions of interest. A quality factor of one represented a near perfect binary match of the computer extracted plant target compared to the hand-extracted plant region. The ExG − ExR index had the highest quality factor of 0.88 ± 0.12 for all three weeks and soil-residue backgrounds for the greenhouse set. The ExG + Otsu and NDI − Otsu indices had similar but lower quality factors of 0.53 ± 0.39 and 0.54 ± 0.33 for the same sets, respectively. Field images of young soybeans against bare soil gave quality factors for both ExG − ExR and ExG + Otsu around 0.88 ± 0.07. The quality factor of NDI + Otsu using the same field images was 0.25 ± 0.08. The ExG − ExR index has a fixed, built-in zero threshold, so it does not need Otsu or any user selected threshold value. The ExG − ExR index worked especially well for fresh wheat straw backgrounds, where it was generally 55% more accurate than the ExG + Otsu and NDI + Otsu indices. Once a binary plant region of interest is identified with a vegetation index, other advanced image processing operations may be applied, such as identification of plant species for strategic weed control.     

Use of soil nitrogen parameters and texture for spatially-variable nitrogen fertilization

Recent studies have demonstrated the potential importance of using soil texture to modify fertilizer N recommendations. The objective of this study was to determine (i) if surface clay content can be used as an auxiliary variable for estimating spatial variability of soil NO₃–N, and (ii) if this information is useful for variable rate N fertilization of non-irrigated corn [Zea mays (L.)] in south central Texas, USA across years. A 64 ha corn field with variable soil type and N fertility level was used for this study during 2004–2007. Plant and surface and sub-surface soil samples were collected at different grid points and analyzed for yield, soil N parameters and texture. A uniform rate (UR) of 120 kg N ha⁻¹ in 2004 and variable rates (VAR) of 0, 60, 120, and 180 kg N ha⁻¹ in 2005 through 2007 were applied to different sites in the field. Distinct yield variation was observed over this time period. Yield and soil surface clay content and soil N parameters were strongly spatially structured. Corn grain yield was positively related to residual NO₃–N with depth and either negatively or positively related to clay content depending on precipitation. Residual NO₃–N to 0.60 and 0.90 m depths was more related to corn yield than from shallower depths. The relationship of clay content with soil NO₃–N was weak and not temporally stable. Yield response to N rate also varied temporally. Supply of available N with depth, soil texture and growing season precipitation determined proper N management for this field.