Uneven light distribution and low water holding capacity are two constraints limiting strawberry (Fragaria×ananassa Duch.) production in coastal northern Atlantic areas. A study was conducted in a commercial strawberry production field characterized by rapid internal soil drainage and undulating land features in Nova Scotia. The objectives were to examine the uneven distribution patterns of solar irradiance (IRR), temperature and soil water content (SWC) and quantify correlations of these physical variables with strawberry fruit yield, plant reflectance water index (WI) and leaf chlorophyll. Strawberry row orientation was along the field aspect in the north-south (N-S) direction for maximizing plant sunlight exposure and spring rainfall drainage. The measurement design consisted of a nested grid with five transects. Results showed that solar radiation incident upon the canopy was significantly higher (mean IRR 779-820Wm-2) in the shoulder and slope areas compared to the mean IRR of 709Wm-2 in downslope area (P<0.001), where higher SWC and lower temperature stimulated strawberry fruit bearing. Significantly higher reflectance WI was related to low strawberry yield (R2=0.55, P<0.05). Strawberry fruit yield was positively correlated to normalized difference vegetation index, ratio nitrogen vegetative index and leaf chlorophyll (0.46<R2<0.61, P<0.05). Distribution patterns and correlations between strawberry fruit yield and physical variables suggested that IRR and water stress occurring with the influence of high topographic features resulted in reduced strawberry fruit bearing ability. It was suggested that the N-S row orientation along the aspect would help sunlight capture but not water holding for strawberry plant fruit bearing needs. A new planting design for alternative orientation of rows (NE-SW or W-E) and drip irrigation should be tested for light and water management in soils with natural constraints.

Statistical analysis of the heterogeneity of soil bulk density in regional scale is important tocrop growth and tillage management. While most field data focus on bulk density up to a depth of 0.3 m, this study measured the bulk density of 28 in situ soil core locations up to a depth of 1.3 m. Geostatistical method was used to analyze the anisotropic spatial variability and three-dimensional Sequential Gaussian Simulation (SGSIM) was conducted. The results of nugget/sill ratio indicated that the sampling scheme was fine enough to capture the spatial correlation distance of bulk density in the vertical direction. The nugget effect, however, in the horizontal direction suggested that the sampling frequency was not enough for bulk density in that direction. The result of three-dimensional SGSIM is consistent with measured data, indicating that the simulation method is suitable for this research objective. The results may provide basic information for other agricultural management practices.

Understanding the distribution of alluvial soil textures on a large scale is crucial for agricultural and environmental management. In our study an indicator variogram and a sequence indicator simulation (SIS) algorithm were used to analyze and simulate the spatial distribution of soil textures based on observations of 139 soil profiles in a 15km2 region in the Huabei alluvial plain in China. The nugget-to-sill ratio value (SH) of the indicator variograms for all textures in a vertical direction (Z) was equal to 1. This suggests that spatial auto-correlation dominates in the direction of sedimentary deposition with 0.05 m sampling intervals. In contrast, SH ratios from 0.48 to 0.81 show that the soil textures have a degree of randomness in the horizontal direction (X, Y) where the sampling distance was about 300 m. Using the indicator variograms in 3 directions (X, Y and Z) as outlined above, a 3D SIS algorithm was used to simulate textures. Finally, the simulation results were evaluated by the reproduction of a histogram, variogram and the mean absolute error (MAE) of prediction. The mean absolute percentage error (MAPE) of the histogram reproduction showed that the main textures (sand, sandy loam and clay) were described well, whereas the less prevalent textures were underestimated. The MAPE of the indicator variograms reproduction were reasonable although some deviation existed as less prevalent textures in the vertical direction. The mean absolute error (MAE) of the SIS prediction was 0.47. This result is considered acceptable for a category variable because of the stochastic nature of soil textures in a horizontal direction, and hence may provide useful data for other agricultural research.

Excessive irrigation and nitrogen applications result in substantial nitrate leaching into groundwater in intensively cropped oases in desert areas of Alxa, Inner Mongolia. An integrated modelling approach was developed and applied to compare policy incentives to reduce nitrate leaching. The integrated model consists of a process-based biophysicalmodel, a meta-model, a farm economic model and an assessment of policy incentives. The modelling results show that there are "win-win" opportunities for improving farm profitability and reducing nitrate leaching. We found that 4471 Yuan ha 1 of farm gross margin could be obtained with a reduction in nitrate leaching of 373 kg ha 1. Farmers' lack of knowledge about water and nitrogen in soil, and on crop requirements for water and nitrogen could explain the differences, so that agricultural extension is an appropriate policy incentive for this area. When the economic optimumis obtained reductions in nitrate leaching are not achievable without profit penalties and there is a "trade-off" relationship between farm profitability and groundwater quality protection. The combination of low elasticity of nitrate leaching and large elasticity of farm gross margin against water price increases results in very high costs for reducing nitrate leaching (105.6 Yuan kg 1). It is suggested that if the water price increases were coupled with subsidies for adopting nitrate leaching mitigation practices, environmental gains could come at a lower cost.

Water scarcity and nitrate contamination in groundwater are serious problems in desert oases in Northwest China. Field and 15N microplot experiments with traditional and improved water and nitrogen management were conducted in a desert oasis in Inner Mongolia Autonomous Region. Water movement, nitrogen transport and crop growth were simulated by the soil-plant system with water and solute transport model (SPWS). The model simulation results, including the water content and nitrate concentration in the soil profile, leaf area index, dry matter weight, crop N uptake and grain yield, were all in good agreement with the field measurements. The water and nitrogen use efficiency of the improved treatment were better than those of the traditional treatment. The water and nitrogen use efficiency under the traditional treatment were 2.0 kg m-3 and 21 kg kg-1, respectively, while under the improved treatment, they were 2.2 kg m-3 and 26 kg kg-1, respectively. Water drainage accounted for 24-35% of total water input (rainfall and irrigation) for the two treatments. Nitrogen loss by ammonia volatilization and denitrification was less than 5% of the total N input (including the N comes from irrigation). However, 32-61% of total nitrogen input was lost through nitrate leaching, which agreed with the 15N isotopic result. It is impetrative to improve the water and nitrogen management in the desert oasis.

The objective of this study was to xplore the spatio-temporal variability of soil organic matter (SOM) in the urban-rural transition zone of Beijing. SOM content in agricultural soils were measured in 1980, 1990 and 2000 in Daxing County of Beijing in-situ and data of 1980 and 1990 were obtained from the National Soil Survey (NSS). Descriptive statistics and geostatistics were used to analyze the data and the kriging method was applied to map the spatial patterns of SOM. The results showed that mean SOM was 9.95g kg−1 in 1980, 12.76g kg−1 in 1990 and 12.89gkg−1 in 2000. SOM was spatially correlated at a larger distance of 32.0km in the E–W direction for the three years, and at a shorter distance of 24.6, 23.3 and 19.0km in the N-S direction in 1980, 1990 and 2000, respectively, which showed that there was more variability in SOM in the N-S areas across the period of 20years. The mapping showed a decreasing trend of SOM from north to south across the county. SOM levels were classified into six levels (b6, 6-10, 10-12, 12-15, 15-20 and N20g kg−1) based on the standards set by the NSS. The SOM slightly increased from low to high levels from 1980 to 2000. The main factors affecting SOM levels were the soil texture, land use and farming practices. The increasing trend might be attributed to the widespread practices of mulching and organic manure applications.

To estimate water drainage at the field scale, a frequently adopted approach is using a deterministic model with field-averaged hydraulic parameters. However, spatial variability of soil hydraulic properties in the field is a potential source of error. This study evaluated the effect of spatial variability of surface soil saturated hydraulic conductivity (Ks) on water drainage. A conditional simulation (CS) method was used to generate a random field of surface soil Ks based on 117 observed values in the study area. The random field of surface soil Ks was then coupled with a dynamic soil water movement model (HYDRUS-1D). Water drainage during a period of 3 months was stochastically simulated with a total water input of 354mm (including 270 mm of irrigation). Accumulated drainage beyond 2 m soil depth ranged from 23.7 to 64.7 mm, which accounted for 8.8-24.0% of the irrigation input. In addition, the accumulated drainage was also calculated using the measured Ks data and Ks estimated by an ordinary kriging (OK) method. Results obtained from the three methods showed that the accumulated quantities of water drainage obtained by the CS method agreed well with those from measured Ks data, while the water drainage range was narrowed by the OK method because of its apparent 'smoothing effect'. The effect of spatial variability of surface soil Ks on water drainage was demonstrated by the three methods and their results were all better than a traditional method that did not consider the spatial variability of surface soil Ks. An irrigation schedule was finally determined using the CS method. When the irrigation input was controlled between 190 and 200 mm, the schedule saved about 747 m3 of water in a 1 hm2 field, accounting for about 28% of the traditional irrigation applied, and the mean accumulated quantity of water drainage was only 2.3 mm, far lower than the 58.9 mm generated by the traditional method.

To identify the main sources responsible for soil heavy metal contamination, 70 topsoils were sampled from the Daxing County in the urban-rural transition zone of Beijing. The concentrations of heavy metals Cu, Zn, Pb, Cr, Cd, Ni, As, Se, Hg, and Co; the soil texture; and the organic matter content were determined for each soil sample. Descriptive statistics and geostatistics were used to analyze the data, and Kriging analysis was used to estimate the unobserved points and to map the spatial patterns of soil heavy metals. The results showed that the concentrations of all the soil heavy metals exceeded their background levels with the exception of As and Se. However, only the Cd concentration in some areas exceeded the critical value of the national soil quality standard. The semivariance analysis showed that the spatial correlation distances for soil Cu, Zn, Cr, Cd, As, Ni, and Co ranged from 4.0 to 7.0 km, but soil Se, Pb, and Hg had a larger correlation distance. Soil Co, Se, Cd, Cu and Zn showed a strong spatial correlation, whereas the other soil heavy metals showed medium spatial correlation. Soil heavy metal concentrations were related to soil texture, organic matter content, and the accumulation of heavy metals in the soils, which was because of air deposition and use of water from the Liangshui, Xinfeng, and Fenghe rivers that are contaminated by wastewater and sewage for the purpose of irrigation of fields. Hence, a comprehensive treatment plan for these rivers should be formulated.

In recent years, nitrate (NO3) contamination of groundwater has become a growing concern for people in rural areas in North China Plain (NCP) where groundwater is used as drinking water. The objective of this study was to evaluate groundwater resource level, to determine groundwater quality and to assess the risk of NO3 pollution in groundwater in Quzhou County in the NCP. Ordinary Kriging (OK) method was used to analyze the spatial variability of shallow groundwater level, groundwater electrical conductivity (EC) and NO3–N concentrations, and Indictor Kriging (IK) method was used to analyze the data with NO3–N concentrations equal or greater than the groundwater NO3 pollution threshold (20 mg L-1). The results indicated that groundwater level averaged 9.81 m, a level 6 m lower than in 1990. The spatial correlation distances for groundwater level, EC and NO3-N concentration were 21.93, 2.19 and 3.55 km, respectively. The contour map showed that shallow groundwater level areas extended from north to south across the County. Groundwater EC was above 3 dS m_1 in the most part of the northern county. Groundwater NO3 pollution (NO3–N-20 mg L-1) mainly occurred in the County Seat areas due to wastewater irrigation and excessive fertilizer leaching from agricultural fields. At Henantuang town, besides suburban of the County Seat, groundwater was also contaminated by NO3 shown by the map generated using the IK method, which was not reflected in the map generated using the OK method. The map generated using the OK method could not reflect correctly the groundwater NO3 pollution status. The IK method is useful to assess the risk of NO3 pollution by giving the conditional probability of NO3 concentration exceeding the threshold value. It is uggested that risk assessment of NO3 pollution is useful for better managing groundwater resource, preventing soil salinization and minimizing NO3 pollution in groundwater.

利用GPS定位，2005年在山西省太原市主要农业用地采集土样1821个，分析了全氮和有机质的含量。应用传统统计学和地质统计学方法对数据进行了分析。结果表明，按照1980年全国第二次土壤普查养分分级标准，土壤全氮和有机质的平均含量均属中等水平。通过半方差函数分析，土壤全氮和有机质在一定范围内存在空间相关性；它们的窄间相关距离分别为122.4km和75.6km；全氮的空间变异主要受结构性因素的影响，而土壤有机质的空间变异是由结构性因素和随机性因素共同作用引起的。太原市土壤全氮含量的空间分布呈现由西南向东北逐渐降低的趋势，而有机质的分布规律较为复杂，它们的空间分布主要受土壤类型、海拔高度、土地利用方式和人类生产活动等因素的影响。土壤全氮与有机质的空间分布存在很大的差异，这与娄烦县、古交市当地土壤受煤粉尘污染严重以及所处地形地貌密切相关。研究揭示了在自然和社会条件十分复杂的情况下太原市土壤全氮和有机质的空间变异规律及其影响因素，为实现土壤肥力评价和养分资源精准管理提供了科学依据。