Geostatistical interpolation and aggregation of crop growth model outputs

Many crop growth models require daily meteorological data. Consequently, model simulations can be obtained only at a limited number of locations, i.e. at weather stations with long-term records of daily data. To estimate the potential crop production at country level, we present in this study a geostatistical approach for spatial interpolation and aggregation of crop growth model outputs. As case study, we interpolated, simulated and aggregated crop growth model outputs of sorghum and millet in West-Africa. We used crop growth model outputs to calibrate a linear regression model using environmental covariates as predictors. The spatial regression residuals were investigated for spatial correlation. The linear regression model and the spatial correlation of residuals together were used to predict theoretical crop yield at all locations using kriging with external drift. A spatial standard deviation comes along with this prediction, indicating the uncertainty of the prediction. In combination with land use data and country borders, we summed the crop yield predictions to determine an area total. With spatial stochastic simulation, we estimated the uncertainty of that total production potential as well as the spatial cumulative distribution function. We compared our results with the prevailing agro-ecological Climate Zones approach used for spatial aggregation. Linear regression could explain up to 70% of the spatial variation of the yield. In three out of four cases the regression residuals showed spatial correlation. The potential crop production per country according to the Climate Zones approach was in all countries and cases except one within the 95% prediction interval as obtained after yield aggregation. We concluded that the geostatistical approach can estimate a country’s crop production, including a quantification of uncertainty. In addition, we stress the importance of the use of geostatistics to create tools for crop modelling scientists to explore relationships between yields and spatial environmental variables and to assist policy makers with tangible results on yield gaps at multiple levels of spatial aggregation.     

橡胶园土壤全氮和速效钾养分合理取样位置研究

通过地统计学方法分析了土壤全氮和速效钾空间变异特征,并对其合理取样位置进行探讨,绘制了兼顾土壤全氮和速效钾综合养分的合理取样位置空间分布图.结果表明:橡胶园土壤全氮和速效钾综合养分合理取样位置主要受土壤速效钾含量分布决定;在空间分布上,综合养分的合理取样位置主要位于远离施肥穴的橡胶树行间萌生带和中间树头附近区域.此结果为南方长期经济作物土壤样品取样位置的确定提供一种新的尝试.     

Spatial variability in the growth of direct-seeded rainfed lowland rice (Oryza sativa L.) in northeast Thailand

Large within-field variation in rice growth often causes production loss in broadcast-seeded (BC) rainfed lowland rice. The spatial variability of direct-seeded rainfed lowland rice was evaluated in 2004, 2005, and 2007 in on-station experiments at Ubon Ratchathani, northeast Thailand, in relation to soil water content and weed infestation, by adopting semivariogram and block kriging, including comparisons among BC with harrowing (BCH; no weeding), BC with no harrowing (BCNH; no weeding), and row-seeded (RS; interrow weeding once) fields. BCH and BCNH were also compared in 11 farmers’ fields in 2006 and 2007, to assess the effect of harrowing on rice growth and weed infestation. During most of the rice growing periods, flooded and non-flooded portions existed simultaneously in the fields, with different proportions among years and among seeding methods in the on-station experiment. BCH and BCNH rice had large within-field variation in seedling density, heading date, shoot dry matter, grain yield, harvest index, panicle density, and filled spikelet per panicle, as well as in weed infestation, measured by a quick visual estimation. Many of the measured variables (except mean soil water content in RS in 2007, seedling density in BCH in 2005 and 2007, shoot dry matter in BCH and BCNH in 2007, and panicle density in BCH in 2007) were spatially dependent (i.e., data from nearby locations were most similar) by geostatistical analysis. Analysis of correlations using the 420 data sets of BCH plots in 2005 and BCH, BCNH, and RS plots in 2007 revealed a positive correlation between soil water content and grain yield and negative correlations between weed infestation and soil water content and grain yield. Compared with BCH, in 2007 BCNH had much lower grain yield because of lower soil water content after establishment and more weed infestation. BCH had higher grain yield than BCNH in weedy fields in the farmers’ fields experiment. RS with interrow weeding resulted in a smaller coefficient of variation, smaller sill value, and higher grain yield than BCH, due to less weed infestation and a higher proportion of flooded water. These results indicated that reducing the spatial variability in rice growth requires careful field preparation, such as harrowing to level the soil surface and to reduce the uneven distribution of standing water and the variability in soil water content, combined with effective crop and weed management (i.e., harrowing and row-seeding). This is the first study that examined spatial variability in the growth of direct-seeded rice as a function of soil water content and weed infestation in a rainfed lowland environment.     

基于地统计与遥感反演相结合的有机质预测制图研究

土壤水分对土壤光谱反射率有显著影响,而以往有机质遥感反演制图中却很少将水分作为预测建模的变量。为了使遥感制图更加符合野外实际环境,提高有机质预测制图精度,在充分考虑土壤样点空间自相关、异相关与野外复杂环境特点的基础上,通过地统计获得研究区水分的空间分布数据,结合遥感反射率,建立多因子预测模型,得到了吉林省黑土区土壤有机质空间分布图。结果表明,有机质遥感制图中,水分因素的加入,使模型的建立更加符合野外实际情况,显著提高了有机质预测制图的精度。     

南方竹林地土壤有机碳空间异质性研究

土壤养分空间异质性是土壤质量评价的一个重要内容,为提高竹林有机碳估算精度,利用2013年永安六乡镇138个竹林地土壤有机碳样点数据,运用GIS技术和地统计学方法分析了永安市竹林地土壤有机碳数据的空间变异特征与格局。结果表明:竹林土壤养分有机碳含量极为丰富,全剖面及各层土壤有机碳含量在空间上属于中等变异;空间自相关Morans'I系数总体上随空间距离的增加而呈现递减趋势;全剖面、A层、B层及C层最佳理论模型依次为指数、高斯、指数、球状模型;半方差拟合决定系数分别为0.684、0.831、0.506、0.538,空间上均表现出强烈的自相关性,块金效应值分别为10.330%、13.100%、10.160%、0.120%;分形维数值为A层(1.964)B层(1.962)C层(1.944)全剖面(1.938);从空间分布特征看,永安市毛竹林地土壤有机碳明显呈带状和斑块状分布,东部和西部有机碳含量明显高于中部。研究结果可为永安市竹林有机碳含量空间插值、制图和野外取样的设计提供参考,同时也可为精准农业和土壤可持续经营发展提供科学依据。     

Site-Specific Nitrogen Management in Rice Using Remote Sensing and Geostatistics

Proper doses of nitrogenous fertilizer are most important for rice production system because a large part of the nitrogen may be lost if it is not applied judiciously. A study was conducted covering five blocks of Balasore and two blocks of Bhadrak districts. Soil samples were collected randomly, and field visit was conducted during peak vegetative stage of rice. Two approaches have been used in this study for estimating the site-specific nitrogen (N) requirement in the study area. In one approach, geostatisical analysis and kriging was used to develop the soil test–based N recommendation map by which a minimum of 72 kg N ha^?1 and maximum of 94 kg N ha^?1 were recommended. In a second approach, remote sensing was used and N recommendation map was developed using the moderate-resolution imaging spectroradiometer (MODIS) leaf area index (LAI) and normalized difference vegetation index (NDVI) satellite data, and a minimum requirement of 60 kg N ha^?1 and maximum of 120 kg N ha^?1 was estimated through this approach.     

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.     

河北沧州果品主产区土壤砷空间变异性研究

采用GIS技术和地统计学相结合的方法对河北沧州果品主产区献县、泊头、沧县3个县表层土壤(0～20 cm)砷的空间分异特征进行了分析。结果表明:3个县表层土壤砷的平均值为12.46 mg kg-1,砷污染存在的风险较低。土壤砷最优理论模型为指数模型,空间结构上具有中等程度空间相关性,说明其空间变异主要是由母质、地形、土壤类型等结构性因素引起的。各向异性分析表明地质背景、河流和飘尘可能影响着土壤砷的分布。Kriging插图结果直观的反映出研究区内土壤砷的空间变异特征。调查结果显示含砷污水的农田灌溉,含砷煤燃烧产生的大气降尘,含砷农药、化肥的使用等是影响土壤砷分布的人为因素。     

Landscape and Land‐Use Effects on the Spatial Variation of Soil Chemical Properties

The current study addressed the spatial variation of soil organic matter (SOM), total nitrogen (TN), extractable phosphorus (EP), and extractable potassium (EK) in agricultural soils of a representative region, northeast China. Soil cation exchange capacity (CEC) and the effects of landscape attributes and land use were also investigated. The techniques used included conventional statistics, geostatistics, and geographic information systems (GIS). Our study demonstrated that EP had the greatest coefficient of variation (CV), and CEC had the least CV. The experimental semivariograms of the five soil chemical properties included in this study were all fitted with exponential models. The five soil variables all showed moderate spatial dependence. The SOM, EK, and CEC decreased with increasing altitude. Significant negative relationships were found between the slope gradient and EP, EK, and CEC. Relatively steeper slopes might result in greater soil erosion, which leads to a decline in soil nutrients. Soil types had significant impacts on all soil chemical properties, which reflect the effect of the parent soil material. In general, the mean values of soil variables for vegetable land were statistically greater than those for upland and paddy fields. After being divided into two parts along the Yinma River, soil samples of the western part have statistically greater SOM, EP, EK, and CEC values than those collected from the eastern part.     

稻田土壤养分的空间变异性研究

本研究以嘉善县陶庄农场内一块5.1hm2的水稻田为研究区,区内不规则采样,共128个采样点。以土壤的pH、有机质、全磷、全氮、碱解氮、速效钾和速效磷含量为研究对象,研究其相应的统计规律,结果表明土壤各养分属性的变异系数在6.3%~35.61%之间,pH为5.3%;采用地统计的半方差函数分析,发现有机质,全氮,碱解氮和速效钾在一定范围内存在空间相关性;采用克立格方法进行最优内插,绘制了养分含量分布图,并对其空间变异进行了初步分析。