基于指示Kriging法的土壤盐渍化与地下水埋深关系研究

在北方干旱、半干旱的地下水浅埋区,土壤盐渍化是土地资源退化的主要原因,防治土壤盐渍化是农业和生态环境可持续发展的重要保障。该文以内蒙古河套灌区解放闸灌域为例,运用指示Kriging法绘制并比较了不同阈值下地下水位埋深和土壤表层含盐量的概率分布图,从概率空间分布的角度分析研究了土壤盐渍化与地下水位埋深之间的关系,从而将这方面的研究从通常的农田尺度扩大到灌域尺度。结果表明:1)土壤盐分和地下水位埋深空间变异强度均为中等,且具有中等的空间自相关性,球状模型拟合变异函数的效果较好;2)在灌域尺度上,解放闸灌域4月底土壤表层发生中度、轻度盐渍化时地下水位临界埋深分别为2.0、2.5m,西南及中东部地下水位埋深小于临界埋深的概率较大,是土壤返盐的高风险区;3)3月底地下水位埋深对土壤返盐的影响比4月底更大一些,这表明地下水位埋深对土壤返盐的影响具有一定滞后效应,只有地下水位埋深小于临界深度的状态维持一段时间,才会造成土壤中度或轻度盐渍化。     

Temporal and Spatial Variations of Inorganic Nitrogen Levels in Surface and Groundwater Around Hanoi,Vietnam

Abstract

Pollution of surface and groundwater by inorganic nitrogen (N) was assessed in farm villages of northern Vietnam. The pH and ammonium‐N and nitrate‐N concentrations were monitored at three communes near Ha Noi in the Red River Delta in March and September 2003, following monitoring in October 2002. In each monitoring time, ammonium‐N concentrations exceeded the Vietnamese water standards applicable to surface and groundwater, whereas the nitrate‐N concentrations were relatively low and below the corresponding standards. Neither spatial nor temporal variation was found in the ammonium‐N and nitrate‐N concentrations of the surface water. A temporal increase in the ammonium‐N concentration was statistically confirmed in the groundwater. Intensively applied fertilizer‐N and disposed animal/human wastes were thought to be sources of ammonium‐N. Ammonium‐N originating from those sources was seen to accumulate steadily in the groundwater through percolation from the surface water and surrounding land. A spatial variation of the nitrate‐N concentration was observed in the groundwater. The nitrate‐N concentration in the groundwater was particularly low in communes located in lowland areas with alluvial soils. The suppression of nitrification or promotion of denitrification was considered to be responsible for the low nitrate‐N concentration. A spatial variation was also found in the groundwater pH. Therefore, variation of the pH may be linked to variation of the nitrate‐N concentration in the groundwater.     

Geostatistical modelling and mapping of nematode-based soil ecological quality indices in a polluted nature reserve

Nematodes are indicators of soil quality and soil health. Knowledge of the relationships between nematode-based soil quality indices and environmental properties is beneficial for assessing environmental threats on soil biota. This study evaluated the spatial distribution of nematode-based soil quality indices in a 23-ha heavy metal-polluted nature reserve using geostatistical methods. We expected that a selection of abiotic soil properties (pH and moisture, clay, organic matter, cadmium (Cd), and zinc (Zn) contents) could explain a significant portion of the spatial variation of the indices and that regression kriging could more accurately model their spatial distribution than ordinary kriging. A stratified simple random sampling scheme was used to select 80 locations where soil samples were taken to extract nematodes and derive the indices. The area had a distinct gradient in soil properties with Cd and Zn content ranging from 0.07 to 68.9 and 5.3 to 1329 mg kg^-1, respectively. Linear regression models were fitted to describe the relationships between the indices and soil properties. By also modelling the spatial correlation structure of regression residuals using spherical semivariograms, regression kriging was used to produce maps of the indices. The regression models explained between 21% and 44% of the total original variance in the indices. Soil pH was a significant explanatory variable in almost all cases, while heavy metal conent had a remarkably low effect. In some cases, the regression residuals had spatial structure. Independent validation indicated that in all cases, regression kriging performed slightly better because of having lower values of the root mean square prediction error and a mean prediction error closer to zero than ordinary kriging. This study showed the importance of soil properties in explaining the spatial distribution of biological soil quality indices in ecological risk assessment.     

基于时空克里格的土壤重金属时空建模与预测

土壤重金属或其他生态环境属性在时间和空间上均存在连续性和变异性,而目前的研究忽略了它们在时间维的变异。为了在预测时使用多时期采样数据,该文提出使用时空克里格方法对土壤重金属进行时空建模及预测,着重介绍了经验半方差值的计算、理论变异模型的形式及参数拟合、时空克里格估值算法、估值方差和精度随邻近点数量的变化及时空克里格制图。以武汉市青山区土壤重金属为例介绍了时空克里格建模及预测的流程。结果表明,时空克里格方法能够很好地描述土壤重金属在空间、时间和时空上3个部分的变异特征,能够利用其他时期的数据对预测时间点的属性进行插值,而多时期的属性空间分布图能够很好地反映土壤重金属的分布变化规律。该研究可为资源环境生态时空建模及预测研究提供参考。     

Geostatistical analysis of soil mechanical properties in Ardabil plain of Iran

This study was conducted to estimate the spatial distribution of penetration resistance (PR), Proctor maximum bulk density (MBD) and critical water content (CWC) as soil mechanical indices. Soil samples to determine sand, silt, clay, organic carbon (OC), CaCO₃, bulk and particle density, total porosity, field water content, MBD and CWC values were collected. Field measurements of PR at 0–10 cm depth were taken from 105 geo-referenced points with 3000 × 3000 m intervals in agricultural lands of Ardabil plain, Iran. Ordinary kriging (OK) and inverse distance weighting (IDW) methods were used to analyze spatial variability of PR, MBD and CWC. The strongest spatial dependences with the lowest ranges of influence were found for OC (7560 m) and MBD (8370 m). The models of fitted semivariograms were Gaussian for PR and MBD, and exponential for CWC. The moderate spatial dependences with the ranges of 13,300 and 40,100 m were found for CWC and PR, respectively. The best prediction according to Lin’s concordance correlation coefficient was obtained by OK for PR (0.48) and IDW for MBD (0.09) and CWC (0.03). These results can be applied in programming of optimum tillage operations for reducing soil compaction risk in the studied region.     

Spatial and Temporal Variability of Groundwater Nitrate Concentrations in Irrigated Mediterranean Agriculture

As nitrogen (N) fertilizer-use efficiency rarely exceeds 50% in most agricultural systems, the potential leaching of N to the groundwater, particularly under irrigated conditions, has economic, health, and environmental implications. Research in the Akarsu irrigation district in the Lower Seyhan Plain in southern Turkey sought to determine spatial and temporal variability of groundwater (GW) nitrate (NO₃) concentrations in 2007–2008. Shallow groundwater observation wells 3 m deep were installed at different locations to represent the whole irrigation district. Groundwater samples were collected (February, April, July, October) and analyzed for ammonium (NH₄) and NO₃ concentrations. Because NH₄ values were negligible, only NO₃ data were processed to determine spatial and temporal variability and then used to develop regional NO₃ maps using geographic information systems. Groundwater NO₃ concentrations ranged between 0.17 and 55.96 mg L^–1 during the 2 years, only exceeding the critical 50 mg L^–1 concentration in 1% of the area sampled. The areal mean of NO₃ concentration was greatest in February, indicating a potential N leaching of unused N from the early season with intensive rainfall, especially in wheat-growing areas. Groundwater NO₃ concentrations decreased after February; however, during the peak irrigation season in July, NO₃ was relatively low because of crop uptake during spring and summer. In about half the area, groundwater NO₃ concentrations ranged between 20 and 50 mg L^–1 and were thus marginal relative to the critical pollution level. As N fertilizer use will continue to increase, especially with the expanded irrigation that is now occurring in the Mediterranean region, regular monitoring of groundwater NO₃ is advisable under such conditions.     

Spatial interpolation of orchard soil pH using soil type and planting duration as auxiliary information

Intensified field management in orcahrds has resulted in significant and widespread acidification in the soils. However, effectively mapping the spatial patterns of soil pH aiming to support ecological management is impeded by its large variotions across soil types and planting durations. Kriging methods were used to integrate soil type and planting duration information for effective mapping of orchard soil pH in a case study in orchards of the Northeast Jiaodong Peninsula, East China. A total of 1 472 surface soil samples were collected, and the planting duration of each sampled orchard was acquired to generate a planting duration map via Voronoi tessellations. The performance of five kriging methods was compared, namely, ordinary kriging (OK), OK combined with soil type (OK_ST), OK combined with planting duration (OK_PD), cokriging combined with soil type and planting duration (OCK_STPD), and OK combined with soil type and planting duration (OK_STPD). Results showed that soil pH declined significantly with increasing planting duration and exhibited moderate spatial variability over the study area. Soil type and planting duration both had significant influence on the spatial distribution of soil pH. The OCK_STPD and OK_STPD methods showed better prediction efficiency than OK, OK_ST, or OK_PD. With regard to the predicted maps of soil pH, the OCK_STPD and OK_STPD methods highly reflected local variations associated with soil type and planting duration, but the OK method was poorly representative. Categorical soil type and planting duration information may be used as ancillary information to improve the mapping quality of orchard soil pH. The OCK_STPD and OK_STPD methods were practical and efficient methods for interpolating orchard soil pH in the study area. The resultant high-quality soil pH maps can contribute to improved site-specific management in the orchards.     

土地混合使用制度下土壤硝态氮分布的地理空间制图研究

Mapping the spatial distribution of soil nitrate-nitrogen (NO₃-N) is important to guide nitrogen application as well as to assess environmental risk of NO₃-N leaching into the groundwater. We employed univariate and hybrid geostatistical methods to map the spatial distribution of soil NO₃-N across a landscape in northeast Florida. Soil samples were collected from four depth increments (0-30, 30-60, 60-120 and 120-180 cm) from 147 sampling locations identified using a stratified random and nested sampling design based on soil, land use and elevation strata. Soil NO₃-N distributions in the top two layers were spatially autocorrelated and mapped using lognormal kriging. Environmental correlation models for NO₃-N prediction were derived using linear and non-linear regression methods, and employed to develop NO₃-N trend maps. Land use and its related variables derived from satellite imagery were identified as important variables to predict NO₃-N using environmental correlation models. While lognormal kriging produced smoothly varying maps, trend maps derived from environmental correlation models generated spatially heterogeneous maps. Trend maps were combined with ordinary kriging predictions of trend model residuals to develop regression kriging prediction maps, which gave the best NO₃-N predictions. As land use and remotely sensed data are readily available and have much finer spatial resolution compared to field sampled soils, our findings suggested the effcacy of environmental correlation models based on land use and remotely sensed data for landscape scale mapping of soil NO₃-N. The methodologies implemented are transferable for mapping of soil NO₃-N in other landscapes.     

Nitrate and chloride loadings as anthropogenic indicators

Agricultural, urban, forest and groundwater protection areas as well as nitrate and chloride concentrations are documented in maps. Areal distribution shows regionally elevated nitrate and chloride concentrations in connection with urban areas and agricultural use. Transport of nitrate and chloride tends to be conservative in the groundwater of the investigated area. Therefore, the elevated concentrations of these anions are suitable as indicators of anthropogenic impact on the groundwater. The average concentration of nitrate and chloride from all surveyed wells amounts to 26 and 17 mg L^?1, respectively. It is shown that wells recharged through forests have lower nitrate and chloride concentrations (average: 21 and 13 mg L^?1, respectively). Wells affected by waste deposits have an average nitrate concentration of 35 mg L^?1 and chloride concentration of 24 mg L^?1. Urban use results in an average value of 28 mg L^?1 nitrate and 24 mg L^?1 chloride. As nitrate and chloride concentrations are stable with respect to the depth of the groundwater table, degradation processes or other protective effects of the unsaturated zone can be omitted.     

蔬菜地面源污染生态拦截系统与效果

针对蔬菜种植业面源污染日益严重的现状,该文选取浙江省太湖流域典型的蔬菜集约化种植区为研究对象,以因地制宜、实用高效、维护便捷、成本合理为原则,在研究区域构建了农田生态沟渠-生态消纳塘水肥一体化-过滤型主排水渠生态拦截系统,并对拦截系统效果进行综合分析研究,探索高效实用的农田面源污染生态拦截技术。结果表明,与2010年相比,工程建成运行后2011年、2012年总氮去除率分别达33%～52%、43%～67%,总磷去除率达23%～59%、43%～82%,在雨季6-9月间,去除效果最佳,且2012年效果优于2011年。该系统有效削减了菜地废水氮、磷等营养元素的排放,达到改善水质、美化景观、提升经济的综合效果,为蔬菜种植区面源污染控制提供技术工程示范,具有典型的推广应用价值。该文可为农田面源污染拦截技术研究及应用提供参考。     

Impact of excreted nitrogen by grazing cattle on nitrate leaching

Abstract. At De Marke experimental farm, data on water and nitrogen flows in the unsaturated zone were gathered on two grazed pastures on sandy soils during the years 1991 to 1994. These provided a basis for calibration and validation of simulation models. The different levels of nitrate-N concentrations of the two plots could largely be explained by differences in crop uptake and simulated denitrification as influenced by different groundwater levels. The irregular distribution of excreta was taken into account by a simulation study quantifying the variability of nitrate-N concentrations under a grazed field. The resulting distribution of simulated nitrate-N concentrations explained the average and peak values of the measured concentrations. Temporal variability of weather was used to assess the nitrate leaching risk under urine patches deposited in either July or September. At site A the probability of exceeding the EC-directive by drinking water (11.3 mg/1 nitrate-N) under a urination deposited in either July or September was respectively 10 and 25%. The average field concentration at this site will hardly ever be a high risk for the environment under the current farm management. At site B the EC-directive will be exceeded under any urine patch in almost 100% of the years, affecting the field average concentration. In field B careful grazing management would result in less nitrate leaching, but the environmental goals would not be reached.     

Optimizing Phosphorus and Potassium Fertilizer Recommendations using Spatial Uncertainty Assessments

Abstract

Variable‐rate nutrient management relies on soil fertility maps, yet the associated uncertainty is typically ignored in developing recommendations. In this article, ordinary kriging (OK) and several alternatives that rely on local estimates of uncertainty derived via probability kriging (PK) are evaluated for developing phosphorus (P) and potassium (K) fertilizer recommendations, using soil data collected at two different intensities. A decision support framework that incorporates economic and agronomic criteria to derive block‐average optimal quantile estimates (Opt Q) maximized net return for an 8‐year fertilization program. The economic results show an increase of $7.31 ha^?1 and $1.04 ha^?1 for P and K fertilization, respectively, using Opt Q rather than OK with the 0.2‐ha sampling grid and $14.79 ha^?1 and $8.93 ha^?1 for P and K fertilization, respectively, using the 0.5‐ha sampling grid. These results illustrate the importance of accounting for estimation uncertainty in developing variable‐rate fertilizer recommendations.     

采样点空间集聚度对揭示区域土壤全氮变异性的影响

基于余江县中部地区土壤密集采样点,通过重采样获得4个集聚度样点分布等级,每个等级取5个重复,其分布VMR均值(样方分析中的样点数变差–均值比)分别为0.13、0.83、1.49和2.16,利用普通克里金(OK)和结合土地利用信息的克里金(KLU)方法对土壤全氮(STN)含量进行空间预测,并通过验证样点比较了4种集聚度采样点的STN空间预测精度,以揭示土壤采样点集聚度对STN空间预测精度的影响。研究结果表明:通过两预测方法得到的验证点实测值与预测值散点图的相关系数(r)均随采样点集聚度的增加而降低,其中OK方法的r值由0.400降低至0.142,KLU方法的r值由0.718降低至0.542;两方法的预测平均绝对误差(MAE)和均方根误差(RMSE)随着集聚度的增加均呈现增加趋势,OK和KLU方法的MAE分别又由0.49和0.33增加至0.61和0.44,RMSE则分别由0.56和0.39增加到0.65和0.47。表明在土壤采样点数量相同的前提下,采样点的空间集聚度越低,即样点分布越均匀,克里金方法的预测精度越高,这说明对STN进行空间预测时,基于规则网格的采样点更有利于克里金方法的空间估算;同时,采样点空间集聚度对不同克里金方法预测精度的影响也存在差异,对KLU方法的影响大于OK方法。     

Comparison of spatial interpolation techniques for mapping soil pH and salinity in agricultural coastal areas,northern Iran

This study attempted to characterize the spatial distributions of soil pH and electrical conductivity (EC_e) of coastal fields in the Miyandoroud region, northern Iran, for three soil layer depths by assessing spatial variability and comparing different interpolation techniques such as inverse distance weighting (IDW), ordinary kriging (OK), and conditional simulations (CS). Three soil composite samples were collected from 0–50, 50–100, and 100–150 cm depths at 105 sampling sites. At all three soil depths, pH and EC_e were best fitted by exponential and spherical models, respectively. Nugget effects were higher for soil EC_e data sets compared with soil pH at all three soil depths showing soil EC_e had a spatial variability in small distances. The prediction accuracy of the interpolation methods indicated that the minimum error for all data sets was achieved with the OK method, except for pH at 50–100 cm depth, and the CS technique revealed the largest error. The effect of different numbers of simulations (100, 500 and 1000) in the CS interpolation method resulted not in a realistic mapping for the soil EC_e and pH. Considering the high importance of irrigated agriculture in the Caspian Sea coastal areas, more subsoil salinity build-up and groundwater salinity monitoring plans are needed as a prerequisite for sustainable agricultural production systems of the future.     

山东省种植区地下水硝酸盐污染空间变异及分布规律研究

近年来,我国部分地区地下水硝酸盐污染态势十分严峻,特别是集约化种植区由于施用大量氮肥导致的硝酸盐污染更为严重。为控制污染,应掌握地下水硝酸盐污染的空间变异规律与分布特征。采用地统计学方法,对山东省种植区地下水硝态氮含量数据进行空间变异分析。结果表明,不同区域地下水硝态氮含量存在一定的差异,存在明显的趋势效应以及变异性,且含量随地下水深度增加而减少。通过相关性分析,获得与地下水硝态氮含量相关性最高的两个因子（土壤有机质含量和全氮含量）,并作为协克里金（Cokriging）插值方法中的协同因子,对山东省地下水硝酸盐污染进行插值。经比较分析,协克里金法比普通克里金法（Ordinary Kriging）的精度高,减少了80%的平均误差。协克里金法空间插值结果表明,空间分布规律表现在从西南到东北逐渐升高的方向性效应,而地下水硝态氮含量较高的区域主要分布在潍坊、青岛、烟台种植区,如青岛的平度、莱西,潍坊的寿光等农业较发达的种植区。     

Spatial prediction of soil nutrient in a hilly area using artificial neural network model combined with kriging

It is widely recognized that using correlated environmental factors as auxiliary variables can improve the prediction accuracy of soil properties. In this study, a radial basis function neural network (RBFNN) model combined with ordinary kriging (OK) was proposed to predict spatial distribution of four soil nutrients based on the same framework used by regression kriging (RK). In RBFNN_OK, RBFNN model was used to explain the spatial variability caused by the selected auxiliary factors, while OK was used to express the spatial autocorrelation in RBFNN prediction residuals. The results showed that both RBFNN_OK and RK presented prediction maps with more details. However, RK does not always obtain mean errors (MEs) which were closer to 0 and lower root mean square errors (RMSEs) and mean relative errors (MREs) than OK. Conversely, MREs of RBFNN_OK were much closer to 0 and its RMSEs and MREs were relatively lower than OK and RK. The results suggest that RBFNN_OK is a more unbiased method with more stable prediction performance as well as improvement of prediction accuracy, which also indicates that artificial neural network model is more appropriate than regression model to capture relationships between soil variables and environmental factors. Therefore, RBFNN_OK may provide a useful framework for predicting soil properties.     

Spatial variability of the chemical characteristics of a trace-element-contaminated soil before and after remediation

This study addresses the spatial and temporal variability of soil properties before and after the application of organic and inorganic amendments in a trace-element-polluted soil using statistics and geostatistical methods. The experiment took place in a plot (20×50 m) affected by the acid toxic pyritic sludge from the Aznalcóllar mine (Seville, Spain) in April 1998. Soil samples from 0- to 15-cm depth were collected within 48 locations, on a 14×45 m grid in 2002 and 2003, respectively. The samples were analysed for pH, total organic carbon, total sulphur and total, available and soluble As, Cd, Cu, Pb and Zn concentrations. Classic statistical and geostatistical methods were used to assess variability in contamination levels.All soil properties determined in the plot showed a large variability with high coefficients of variation. In both years, mean values of total concentrations of As, Cd, Cu, Pb and Zn were higher than the background values in the area. In general, amendment application increased soil pH and total organic carbon content and decreased heavy metal solubility, however it did not have a clear effect on total and available trace-element contents. Experimental semivariograms were developed to determine the spatial dependence of soil properties and were adjusted to spherical and linear models with nugget effect. Then, the spatial distribution of the different variables was estimated by kriging to design contour maps. These contour maps can help to identify the pollution patterns and delineate the range of contamination. A spatial similarity pattern among total As and Pb (the lesser mobile elements) and total S content was found in both samplings revealing a correspondence between the contamination and spots of residual sludge. Levels of metal pollution were influenced by soil pH. Despite those clean-up efforts the soil still presents significant levels of pollution related to the presence of remaining sludge in the soil.The kriging-interpolated maps were a very valuable tool in studying pollution and monitoring soil parameters after amendment application at field scale.     

A Modified DRASTIC Approach to Shallow Groundwater Vulnerability in the West Lake Watershed in Hangzhou, China

The quality of shallow groundwater in the West Lake watershed was investigated from March to July 2000. Integrating with Blackland GRASS GIS system, the DRASTIC model was used to compile the groundwater vulnerability map. A land use factor was added to the DRASTIC model and the modified model (LDRASTIC) increased the accuracy of prediction from 26.9% to 51.3%. The vulnerability map showed that the lowly, moderately and highly susceptible area predicted occupied about 11.6%, 70.9% and 17.5% of the whole watershed, respectively. Compared with the observed values of nitrate and electric conductivity, the LDRASTIC index improved the Pearson correlation coefficients from -0.010 to 0.237 and 0.380 to 0.503;both the improved coefficients were significant at the 0.01 level. The modified DRASTIC analysis showed a great potential as a screening tool for policy decision-making in groundwater management.``     

改进的DRASTIC方法研究杭州西湖分水岭的浅层地下水的易污性

The quality of shallow groundwater in the West Lake watershed was investigated from March to July 2000. Integrating with Blackland GRASS GIS system, the DRASTIC model was used to compile the groundwater vulnerability map. A land use factor was added to the DRASTIC model and the modified model (LDRASTIC) increased the accuracy of prediction from 26.9% to 51.3%. The vulnerability map showed that the lowly, moderately and highly susceptible area predicted occupied about 11.6%, 70.9% and 17.5% of the whole watershed, respectively. Compared with the observed values of nitrate and electric conductivity, the LDRASTIC index improved the Pearson correlation coefficients from -0.010 to 0.237 and 0.380 to 0.503; both the improved coefficients were significant at the 0.01 level. The modified DRASTIC analysis showed a great potential as a screening tool for policy decision-making in groundwater management.     

灌溉、施肥和浅水埋深对小麦产量和硝态氮淋溶损失的影响

利用ArcGIS9.0软件中嵌套地质统计模块分析河套灌区浅层地下水埋深（2009年）空间分布状况,结合在2010年3－7月间开展的灌溉量、施氮量和浅层地下水埋深对春小麦产量和土壤中硝态氮淋溶损失影响的显著性以及最优组合研究,确定出适用于河套灌区内不同区域的春小麦农业管理的最优综合模式。研究表明,表层（0～80 cm）土壤含水率随着浅水埋深的增大而减小,当浅水埋深≥2.0 m时,在同一浅水埋深水平下灌溉量成为土壤含水率显著影响因子;对春小麦产量影响程度高低是浅水埋深＞灌溉量＞施氮量,影响显著因子为浅水埋深;对硝态氮淋溶量影响程度高低是灌溉量＞施氮量＞浅水埋深;灌溉量对硝态氮淋溶影响呈极显著性,施氮量对其影响呈显著性,而浅水埋深起到辅助作用。灌区年均浅层地下水埋深主要有3个阈值：1.25～1.75、1.75～2.25和2.25～3.00 m。在灌区内浅水埋深不同区域内（1.5、2.0和2.5 m）时,三因素最优综合组分别为灌溉量（280 mm）+施肥量（尿素150 kg·hm-2,二铵165 kg/hm2）、灌溉量（320 mm）+施肥量（尿素150 kg/hm2,二铵165 kg/hm2）和灌溉量（360 mm）+施肥量（尿素255 kg/hm2,二铵375 kg/hm2）。